Day 1 29/11/2019
Room #1

Registration 08:30 - 09:30

Jinsong Hall

Opening Ceremony 09:00 - 09:30

Jinsong Hall

Keynote Speech 1 /Jinsong Hall/ 09:30 - 10:20

Prof. Haijun Zhang, University of Science and Technology Beijing, China

Coffee break 10:20 - 10:40

Keynote Speech 2 /Jinsong Hall/ 10:40 - 11:30

Prof. Yang Yang, ShanghaiTech University, China

Lunch 12:00 - 14:00

Keynote Speech 3 /Jinsong Hall/ 14:00 - 14:50

Prof. Xinheng Wang, Xi’an Jiaotong – Liverpool University, China

Coffee break 14:50 - 15:00

Keynote Speech 4 /Jinsong Hall/ 15:00 - 15:50

Prof. Congfeng Jiang, Hangzhou Dianzi University

Session 1 16:00 - 17:00

Jinsong Hall
16:00 - 16:00
A Cross-layer Protocol For Mobile Ad Hoc Network Based on Hexagonal Clustering and Hybrid MAC Access Approach

Due to its flexible and convenient networking, Ad hoc networks have been used in more and more scenarios. But, the features of mobility, constantly changing topologies and centerless architecture limit its applications. In order to improve the performance of Ad hoc, this paper proposes a cross-layer protocol for mobile Ad hoc network based on Hexagonal Clustering and Hybrid MAC Access (HCHMA) approach. Through the clustering algorithm, cluster heads are selected to form a backbone network for route discovery and establishment. And the MAC layer uses two different access mechanisms to ensure efficient transmission of routing packets and data packets. Benefiting from the above approaches, network overhead is greatly reduced and the throughput is improved. By doing simulations in the network simulator 2 (NS2) software, the HCHMA protocol shows better packet delivery rate, higher throughput and lower end-to-end delay compared with the Ad hoc On-demand Distance Vector Routing (AODV) protocol and the Optimized Link State Routing (OLSR) protocol.
Authors: Longchao Wang (Xidian University,P.R.China), Xiandeng He (Xidian University,P.R.China), Qingcai Wang (Xidian University,P.R.China), Heping Yao (Dalian Haoyang Technology Development Ltd.,P.R.China), Yifan Qiu (State Key Laboratory of Integrated Service Networks, Xidian University),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
ON SDN CONTROLLERS PLACEMENT PROBLEM IN WIDE AREA NETWORKS

Software Defined Networking (SDN) is a new paradigm where the forward plan is decoupled from the control plan. The controller is a central program that tells the switches and routers how to react to the incoming flows and different network changes. The placement of the controllers considering different metrics becomes a challenge in SDN WAN. In this paper, we study the controller placement problem in terms of propagation delay and load balancing. An extended K-means algorithm is introduced to partition the network into several subnetworks and place the controllers in nodes that minimize the network delay. Then a load balance index is calculated to check the effectiveness of the load balancing considering a metric β as the load difference between controllers. The result analysis shows that a trade off should be done between the delay and load balancing depending on the priority of the network and no optimal case can be found that minimize both of the metrics at the same time.
Authors: Firas Zobary (Wuhan University of Technology), ChunLin Li (Wuhan University of Technology),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Performance Analysis of Consensus-based Distributed System under False Data Injection Attacks

This paper investigates the security problem of consensus-based distributed system under false data injection attacks (FDIAs). Since the injected false data will spread to the whole network through data exchange between neighbor nodes, and result in continuing effect on the system performance, it is significant to study the impact of the attack. In this paper, we consider two attack models according to the property of the injection data, the deterministic attack and the stochastic attack. Then, the necessary and sufficient condition for the convergence of distributed system under the attack are derived, and the attack feature making the system unable to converge is provided. Moreover, the convergence result under resource-limited attack is deviated. On the other hand, the statistical properties of the convergence performance under zero-mean and non-zero-mean stochastic attacks are analyzed, respectively. Simulation results illustrate the effects caused by FDIAs on the convergence performance of distributed system.
Authors: Xiaoyan ZHENG (Zhejiang University), Lei XIE (Zhejiang University), Huifang CHEN (Zhejiang University), Chao SONG (Zhejiang University),
Hide Authors & Abstract

Show Authors & Abstract
16:30 - 16:30
A Resource Scheduling Algorithm with High Task Request Acceptance Rate for Multi-platform Avionics System

By utilizing the resources of different aircraft, the multi-platform avionic systems (MPA) take advantage of various resources and enhance the ability to perform complex tasks. In MPA, the resource management and task scheduling are the key function. In order to simulate and verify the MPA’ resource management and task scheduling, the MPA resource modeling methods and scheduling algorithms are studied to rationalize the hardware resources to increase task acceptance rate. A multi-level hierarchical to-pology is used to modelling multi-platform avionic resources, and analyze MPA mis-sion requirements, and designs a scheduling algorithm based on the SST adaptive scheduling algorithm. Due to the deficiency of the SST algorithm, such as reducing the task acceptance rate due to energy consumption considerations and not considering the limitations of sensors and priorities, the algorithm cannot adapt to the requirements of the avionic systems. Therefore, in this paper, a system resource selection method is de-signed, and can improve the high priority acceptance rate, so as to get a scheduling al-gorithm with high task acceptance rate. Finally, we use the CloudSim to set up a simu-lation experiment environment and implement the designed algorithm. Through the experiments of different scenes and the comprehensive analysis of the experimental re-sults, it is shown that the algorithm proposed in this paper outperforms the existing al-gorithm in terms the acceptance rate.
Authors: Kui Li (National Key Laboratory of Science and Technology on Avionics Integration, China Aero-nautical Radio Electronics Research Institute), Qing Zhou (National Key Laboratory of Science and Technology on Avionics Integration, China Aeronautical Radio Electronics Research Institute), Guonan Cui (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics), Liang Liu (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics),
Hide Authors & Abstract

Show Authors & Abstract

Welcome Banquet 17:30 - 20:00

Day 2 30/11/2019
Room #1

Session 1 09:00 - 10:00

Huashan Hall (4th Floor)
09:00 - 09:00
Pricing-Based Partial Computation Offloading in Mobile Edge Computing

For mobile devices (MDs) and Internet of Things (IoT) devices with limited computing capacity and battery, offloading part of tasks to the mobile edge computing (MEC) server is attractive. In this paper, we propose a joint partial computation offloading and pricing scheme in a multi-user MEC system. Firstly, we establish MD's cost model and MEC server's revenue model in terms of money. Secondly, we investigate MD's cost minimization partial offloading strategy to jointly control MD's task allocation, local CPU frequency and the amount of computational resource blocks (CRBs) requested. Finally, we formulate the revenue maximization problem for MEC server with limited computing capacity, a heuristic algorithm is proposed for MEC server to find the optimal service price. Numerical results verify the effectiveness of our proposed scheme in cost saving and pricing.
Authors: Lanhui Li (Beijing University of Posts and Telecommunications), Tiejun Lv (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Dynamic Resource Allocation in High-Speed Railway Fog Radio Access Networks with Delay Constraint

By applying caching resource at the remote radio heads (RRHs), the fog radio access network (Fog-RAN) has been considered as an promising wireless architecture in the future network to reduce the transmission delay and release the heavy burden of backhaul link for huge data delivery. In this paper, we propose to use the Fog-RAN to assist the data transmission in the high-speed railway scenario. In specific, we investigate the dynamic resource allocation in high-speed railway Fog-RAN systems by considering the delay constraint. The instantaneous power allocation at the RRHs and the instantaneous content delivery rate over the backhaul links are jointly optimized with an aim to minimize the total power consumed at the RRHs and over the backhaul links. An alternating optimization (AO) approach is used to find solutions of the instantaneous power and instantaneous content delivery rate in two separate subproblems. The closed-form solutions are derived in two subproblems under certain special conditions. Simulation results demonstrate that the proposed dynamic resource allocation is significantly superior to the constant resource allocation scheme.
Authors: Rui Wang (Tongji University), jun wu (Tongji University), Jun Yu (Tongji Univeristy),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Distributed Task Splitting and Offloading in Mobile Edge Computing

With the rapid development of the mobile internet, many emerging compute-intensive and data-intensive tasks are extremely sensitive to latency and cannot be implemented on mobile devices (MDs). To solve this problem, mobile edge computing (MEC) appears to be a promising solution. In this paper, we propose a distributed task splitting and offloading algorithm (DSOA) for the scenario of multi-device and multi-MEC servers in ultra-dense networks (UDN). In the proposed scheme, the MDs can perform their tasks locally or offload suitable percentage of tasks to the MEC server. The optimization goal is to minimize the overall task computation time. Since the MDs are selfish, we propose a game theory approach to achieve optimal global computation time. Finally, the numerical simulation results verify that the algorithm can effectively reduce global computation time.
Authors: Yanling Ren (Jiangsu University of Science and Technology), Zhihui weng (Jiangsu University of Science and Technology), Yuanjiang Li (Jiangsu University of Science and Technology), Zhibin Xie (Jiangsu University of Science and Technology), Kening Song (PLA AF 95829), Xiaolei Sun (PLA Navy Submarine Academy),
Hide Authors & Abstract

Show Authors & Abstract

Session 2 10:00 - 11:00

Huashan Hall (4th Floor)
10:00 - 10:00
Energy-efficient Coded Caching and Resource Allocation for Smart Grid-supported HetNets

Coded caching (CC) is able to exploit accumulated cache size and hence superior to uncoded caching by distributing fractions of a file in different nodes. This paper investigates CC, resource allocation (RA) and energy cooperation (EC) in cache-enabled energy harvesting (EH) heterogeneous networks (HetNets), where base stations (BSs) with cache ability are powered by both conventional grids and renewable energy (RE) sources, and energy can be shared between BSs via the smart grid (SG). We formu- late the joint optimization problem with the objective of minimizing the conventional grid energy consumption while satisfying quality of service (QoS) requirements of users. Simulation results demonstrate the considerable reduction in conventional grid energy consumption compared with other benchmarks.
Authors: Fangfang Yin (Beijing University of Posts and Telecommunications), Junyi Lyu (Beijing University of Posts and Telecommunications), Danpu Liu (Beijing University of Posts and Telecommunications), Zhilong Zhang (Beijing Laboratory of Advanced Information Network, Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications.), Minyin Zeng (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Task-Aware Joint Computation Offloading for UAV-Enabled Mobile Edge Computing Systems

With the emergence of diverse computation-intensive mobile applications (such as virtual reality), demands for data processing from users are rapidly increasing in mobile edge computing (MEC). However, existing mobile edge servers (MES) are susceptible to propagation delays and loss and fail to provide timely and efficient services. Facing this problem, we focus on applying unmanned aerial vehicles(UAVs) equipped with computing resources to provide mobile edge computing offload services for users. UAV as an MES can guarantee low propagation delay and high reliability due to its maneuverability and short-distance line-of-sight communications. In this paper, we study a joint computing offloading problem consideration of user equipments, ground base stations and aerial UAVS. The system provides two offloading methods. The first offloading method is the air-offloading, where a user equipment can offload computing tasks to UAV-enabled MEC servers. The second offloading method is ground-offloading, where a user equipment can offload computing tasks to existing MESs. The task-aware optimization offloading scheme is proposed and it selects local execution or offloading method based on the latency and energy constraints. Simulation results show that our proposed offloading selection scheme outperforms benchmark schemes. The results demonstrate that the proposed schemes improve quality of service (QOS) and have low task block rate under latency and energy constraints.
Authors: Junshi Hu (Beijing University of Posts and Telecommunications), Heli Zhang (Beijing University of Posts and Telecommunications), Xi Li (Beijing University of Posts and Telecommunications), Hong Ji (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Burst Traffic Awareness WRR Scheduling Algorithm in Wide Area Network for Smart Grid

Smart grid achieves optimal management of the entire power system operation by constant monitoring and rapid demand response (DR) for power supply-demand balance. Constantly monitoring the system state realized by Wide Area Measurement Systems (WAMS) provides a global view of the power grid. With a global view of the grid, Wide Area Control (WAC) generated DR command to improve the stability of power systems. When the regular monitoring data flow and the sudden DR data coexist, the suddenness of the demand response may result in delay or loss of the data packet due to uneven resource allocation when the network communication resources are limited, thereby affecting the accuracy of the power system state estimation. To solve this problem, this paper proposes a burst traffic perception weighted round robin algorithm (BTAWRR). The proposed algorithm defines the weight of the cyclic scheduling according to the periodicity of the monitoring data and the suddenness of the demand response. Then it adopts the iterative cyclic scheduling to adjust the transmission of data packets in time by adaptively sensing the changes of the traffic flow. The simulation results show that the proposed algorithm can effectively reduce the scheduling delay and packet loss rate when the two data coexist, and improve the throughput, which is beneficial to ensure the stability of the smart grid.
Authors: Xin Tan (School of information Science and Engineering, Wuhan University of Science and Technology), Xiaohui Li (School of information Science and Engineering, Wuhan University of Science and Technology), Zhenxing Liu (School of information Science and Engineering, Wuhan University of Science and Technology), Yuemin Ding (School of Computer Science and Engineering, Tianjin University of Technology),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

Session 3 11:15 - 12:15

Huashan Hall (4th Floor)
11:15 - 11:15
DBS: Delay Based Hierarchical Downlink Scheduling For Real-time Stream In Cellular Networks

With the rapid development of cellular networks, demand for real-time stream is increasing dramatically. How to guarantee better quality-of-service (QoS) of real-time stream services under limited resources becomes an increasingly im-portant issue. This paper proposes a delay based hierarchical downlink sched-uling (DBS) algorithm for real-time stream in cellular networks. The hierar-chical scheduler is divided into two levels. The upper level scheduler offers a prediction of the number of data bits that each real-time stream needs to guar-antee the QoS. The lower level scheduler classifies all real-time streams into grade A, B and C according to Head of Line Delay and allocates resources to streams according to their different grades. The simulation results show that our algorithm performs better than other real-time schedulers, such as frame level scheduler (FLS), Modified Largest Weight Delay First (M-LWDF), EXP/PF and EXP-LOG in the aspects of delay and throughput.
Authors: Wenjin Fan (Beijing University of Posts and Telecommunications), Yu Liu (Beijing University of Posts and Telecommunications), Yumei Wang (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Combination of Multiple PBCH Blocks in 5G NR Systems

Physical broadcast channel (PBCH) in 5G new radio (NR) systems transmits system informations required for the user equipment (UE) to access the cell. In the long term evolution (LTE) system, multi- ple PBCHs are usually combined to improve demodulation performances in the case of poor channel conditions. However, in 5G NR systems, the payload of PBCH includes the system frame number and the payloads of multiple frames are not exactly consistent. Hence, it is impossible to adopt the same combination approach as that in LTE. In this paper, there proposes a method to solve the problem of combining multiple PBCH blocks in 5G NR systems. The main idea is to convert log likelihood ra- tios (LLRs) of all transmitted PBCH blocks into that of the rst block and accumulate all LLRs at the receiving end. Then, an improved com- bination algorithm is considered to reduce the complexity. The simula- tion results show that the proposed combination algorithm can correctly combine multiple PBCH blocks. Besides, the improved combination al- gorithm with sort can also reduce the complexity.
Authors: Fang Wang, Hang Long (supervisor), Wenxi He (Colleague),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
A Channel Threshold based Multiple Access Protocol for Airborne Tactical Networks

Airborne Tactical Network is a promising and special mobile Ad hoc network, connecting the ground stations and all kinds of flying combat aircrafts on battlefield through tactical data links. Designing a low delay, large capacity, high flexibility, strong scalability, and multi-priority traffic differentiated media access control (MAC) protocol is a great challenge in the researches and applications of ATNs. In order to overcome the disadvantages in IEEE 802.11 Distributed Coordination Function (DCF) and Time Division Multiple Access (TDMA) protocols, we present a channel threshold based multiple access (CTMA) protocol for ATNs in this paper. The CTMA protocol is a novel random contention type of MAC protocols, and it can differentiate multiple priority services, and utilize multi-channel resource based on channel awareness. We intensively describe the channel occupancy statistic mechanism, multi-queueing and scheduling mechanism of multi-priority services, and channel threshold based admission control mechanism involved in the protocol. We further derive the channel threshold of each priority service, the expressions of the successful transmission probability and mean delay mathematically. Simulation results show that the CTMA protocol can differentiate services for different priorities in ATNs according to the real-time channel state, and provide effective QoS guarantee for transmissions of various information.
Authors: Bo Zheng (Northwestern Polytechnical University), Yong Li (Northwestern Polytechnical University), Wei Cheng (Northwestern Polytechnical University), Weilun Liu (Air Force Engineering University),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30

Session 4 13:30 - 14:30

Huashan Hall (4th Floor)
13:30 - 13:30
Cluster and Time Slot Based Cross-layer Protocol for Ad Hoc Network

Due to its good extendibility and robustness, Ad hoc network has been widely used in various aspects. However, its performance is restricted by the mobility, limited bandwidth and centerless architecture. In order to improve the performance of Ad hoc network, this paper proposes a cross-layer Hexagonal Clustering, Position and Time slot based (HCPT) protocol. According to the geographical location, clusters and time slots are divided, and furthermore, an effective algorithm to find routes through the geographical locations of cluster heads is proposed, which can greatly reduce message collisions and reduce network overhead. By doing simulations in the Network Simulator 2 (NS2) software, we found that the HCPT protocol shows better performance in network topology discovery compared with the Optimized Link State Routing (OLSR) protocol. Simulation results also show that the proposed scheme outperforms the standard OLSR and the improved OLSR algorithm, which is proposed by N. Harrag, in terms of routing overhead and packet delivery ratio.
Authors: Yifan Qiu (State Key Laboratory of Integrated Service Networks, Xidian University), Xiandeng He (State Key Laboratory of Integrated Service Networks, Xidian University), Qingcai Wang (Xidian University,P.R.China), Heping Yao (Dalian Haoyang Technology Development Ltd.,P.R.China), Nan Chen (Xidian University,P.R.China),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
A Cluster-Based Small Cell On/Off Scheme for Energy Efficiency Optimization in Ultra-Dense Networks

Ultra-Dense Networks (UDN) can greatly meet the demand for explosively growing data traffic via deploying small cells (SCs) densely. However, the SCs densification causes higher energy consumption and more severe inter-cell inter-ference (ICI). The SC on/off control is one of the effective ways to solve above problems, but the challenge is to maintain network coverage while avoiding deg-radation of the quality of service (QoS) of user equipment (UEs). In this paper, we formulate energy efficiency (EE) optimization problem in stochastic geome-try-based network and take into consideration the QoS of UEs and ICI to maxim-ize the EE. The solution is obtained by dividing the problem into SCs clustering and intra-cluster SC on/off control. We first use an improved K-means clustering algorithm to divide the dense SCs into disjoint clusters according to the distance and density of SCs. Then, within each cluster, selecting a SC as the cluster head (CH) is responsible for performing SC on/off operations under taking minimum rate of UEs and ICI as constraints. In addition, a heuristic search algorithm (HSA) is proposed for the intra-cluster SC on/off control. Simulation results demonstrate that the proposed scheme can effectively improve the network ener-gy efficiency and suppress interference.
Authors: Cui-Qin Dai (Chongqing University of Posts and Telecommunications), Biao Fu (Chongqing University of Posts and Telecommunications), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
A DASH-based Peer-to-Peer VoD Streaming Scheme

For peer-to-peer (P2P) video-on-demand (VoD) streaming, this paper proposes a new P2P VoD scheme based on Dynamic Adaptive Streaming over HTTP (DASH), called P2P-DASH VoD scheme. The scheme takes advantage of both the scalability and low cost properties of P2P technology and the dynamic self-adaptation of DASH. In the proposed scheme, a multi-overlay architecture is constructed, and a DASH streaming rate control approach is proposed. The multi-overlay architecture integrates the power-law ring overlay structure and the Fibonacci ring overlay structure. Peers can search the target video segments based on the power-law ring overlay structure or the Fibonacci ring overlay structure according to the search distance. The integrated overlay structure can reduce the jump latency caused by VCR operations and improve the smooth-ness of playback. Furthermore, the DASH streaming rate control approach is proposed to combine DASH in P2P VoD Streaming. The DASH streaming rate control approach considers four adaptive factors (on-time arrival rate of segment, available buffer length of peers, current overlay available bandwidth and current overlay upload bandwidth utilization). Through simulations, we demonstrate that the proposed P2P-DASH VoD scheme has short jump laten-cy, high playback fluency and the satisfaction of users.
Authors: Pingshan Liu (Business School, Guilin University of Electronic Technology), Yaqing Fan (Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Gui-lin, China), Kai Huang (Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Gui-lin, China), Guimin Huang (Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Gui-lin, China),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 14:30 - 15:00

Session 5 15:00 - 16:00

Huashan Hall (4th Floor)
15:00 - 15:00
Trajectory Clustering based Oceanic Anomaly Detection Using Argo Profile Floats

The observation data of Argo profile floats are very crucial for long-term climate change and natural variability, which reflect three-dimensional distribution of temperature and salinity in the sea. In order to solve the anomalies in the profile caused by uncertainties factors, this paper proposes a trajectory clustering method with specially designed Clustering-Restore procedures. The proposed algorithm uses an improved trajectory clustering method to discriminate Argo data’ normal and abnormal. Extensive experiments on real datasets from Argo profile floats verify that our method has better results under different conditions compared to existing methods including LOF and DBSCAN.
Authors: wenyu cai (Hangzhou Dianzi University), ziqiang liu (hangzhou Dianzi University), meiyan zhang (Zhejiang University of Water Resources and Electric Power),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
DICOM-Fuzzer:Research on DICOM vulnerability mining based on Fuzzing technology

DICOM is an international standard for medical images and related information, and is a medical image format that can be used for data exchange. The agreement is widely used in medical fields such as radiology and cardiovascular imaging. Most of the currently used PACS systems use open-source DICOM protocol libraries to implement data exchange functions. However, since DICOM libraries have less security considerations in protocol implementation, they have a large number of security risks. Aiming at the security issue of DICOM libraries, the paper conducts research on vulnerability mining technology for DICOM open source libraries, proposing a vulnerability mining framework based on Fuzzing technology, and implementing a prototype system named DICOM-Fuzzer, which includes initialization, test case generation, automatic test, exception monitoring and other modules. Finally, the open source library DCMTK was selected to test the generated 1000 test cases, and it was found that data overflow would occur when the content of the received file was greater than 7080 lines, which would lead to the denial of service of the PACS system. At last, security suggestions and repair measures were proposed for this problem.
Authors: zhiqiang wang (1.Beijing Electronic Science and Technology Institute,Beijing China; 2.State Information Center; 3. Key Lab of Information Network Security, Ministry of Public Security), quanqi li (Beijing Eletronic Science and Technology Institute, Beijing, China), qian liu (Beijing Eletronic Science and Technology Institute, Beijing, China), biao liu (Beijing Eletronic Science and Technology Institute, Beijing, China), jianyi zhang (Beijing Eletronic Science and Technology Institute, Beijing, China), Tao Yang (Key Lab of Information Network Security, Ministry of Public Security, Shanghai China), Qixu Liu (Key Laboratory of Network Assessment Technology, Institute of Information Engineering, Chinese Academy of Sciences),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
Secure Communication with a Proactive Eavesdropper Under Perfect CSI and CDI

In this paper, we study physical layer security of a three node multicarrier network with a legitimate source node, a legitimate destination node, and a full-duplex proactive eavesdropper who sends jamming signals to improve its eavesdropping performance. We aim to minimize the average secrecy outage probability on all subcarriers by optimizing transmit power allocation under the total transmit power constraint and the peak transmit power constraint. For availability of the channel state information (CSI) on the channels related to the eavesdropper at the source node, we consider the scenario that the source node knows perfect CSI and also consider the scenario that only channel distribution information (CDI) is known at the source node. We propose algorithms to solve the optimization problems for both scenarios and verify the proposed algorithms by simulation results. It is shown that the proposed algorithms greatly outperform the benchmark algorithms in terms of average secrecy outage probability.
Authors: Qun Li (Nanjing University of Posts and Telecommunications), Ding Xu (Nanjing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Session 6 16:00 - 17:00

Huashan Hall (4th Floor)
16:00 - 16:00
Personalized QoS Improvement in User-centered Heterogeneous V2X Communication Networks

With the rapid increasing personalized demand of cellular V2X and vehicular ad hoc networks (VANET), the hybrid application of the two vehicular communications on unlicensed spectrum is becoming a trend. However, due to channel conflicts, the coexistence issue will lead to a serious drop in QoS of vehicular users. How to allocate the wireless resource to ensure comprehensive user experience is a challenge. In this paper, in order to satisfy the personalized QoS of different users while guarantee fair coexistence, we propose a conflict mitigation scheme through user association and time allocation to jointly optimize the delay and throughput, then formulate the multi-objective optimization into a mixed integer nonlinear programming (MINLP). To solve the NP-hard problem and obtain the Pareto optimal solution efficiently, we propose a PSO-based joint optimization of delay-throughput algorithm (DT-PSO). Simulation results show that our scheme outperforms existing approaches.
Authors: Mo Zhou (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China), Chuan Xu (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China), Guofeng Zhao (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China), Syed Mushhad Gilani (University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
A Lightweight Interference Measurement Method for Wireless Sensor Networks

The most applications of wireless sensor network have stringent requirements for communication performance. To meet applications requirements, it is crucial to measure the wireless interference between nodes, which is the major factor that reduces the performance of wireless sensor networks (WSNs). However, the key problem of accurately measuring wireless interference is that the node cannot predict the neighbor node information after the network is deployed, and thus cannot establish the correspondence between the wireless interference strength and the neighbor node. To tackle this problem, this paper presents a lightweight interference measurement algorithm for WSNs. The algorithm divides the interference measurement process into three phases. The first two phases are used to gather all two-hop neighbor information by exchanging between nodes. In the third phase, each node performs interference measurements and builds the relationship of wireless interference between nodes. The experimental results show that our proposed approaches can obtain accurate inter-node wireless interference strength with low energy and communication overhead.
Authors: zeng bo, Gege Zhang (Shanghai Jiao Tong University), Zhixue Zhang (Henan University of Science and Technology), Shanshan Li (Henan University of Science and Technology),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Dynamic Network Change Detection via Dynamic Network Representation Learning

The structure of the network in the real world is very complex, as the dynamic network structure evolves in time dimension, how to detect network changes accurately and further locate abnormal nodes is a research hotspot. Most current feature learning methods are difficult to capture a variety of network connectivity patterns, and have a high time complexity. In order to overcome this limitation, we introduce the network embedding method into the field of network change detection, we find that node-based egonet can better reflect the connectivity patterns of the node, so a dynamic network embedding model Egonet2Vec is proposed, which is based on extracting the connectivity patterns of the node-based egonets. After the dynamic network representation learning, we use a dynamic network change detection strategy to detect network change time points and locate abnormal nodes. We apply our method to real dynamic network datasets to demonstrate the validity of this method.
Authors: Feng Hao (State Key Laboratory of Mathematical Engineering and Advanced Computing), Liu Yan (State Key Laboratory of Mathematical Engineering and Advanced Computing), Zhou ZiQiao (State Key Laboratory of Mathematical Engineering and Advanced Computing), Chen Jing (State Key Laboratory of Mathematical Engineering and Advanced Computing),
Hide Authors & Abstract

Show Authors & Abstract
Room #2

Session 1 09:00 - 10:00

Xiangshan Hall (4th Floor)
09:00 - 09:00
Evolution Computation Based Resource Allocation for Hybrid Visible-Light and RF Femtocell

Incorporating visible light communication (VLC) with existing radio frequency (RF) access techniques has received widespread concern to enhance network coverage/capacity. This paper focuses on the joint downlink resource allocation (RA) in a hybrid VLC-RF network. The problem is formulated as utility maximization by jointly adjusting downlink sub-channel allocation. A Evolution Computation (EC) based centralized algorithm is developed to solve the problem. To reduce computation complexity, the algorithm is decoupled into two sub-steps. First, users are assigned to different VLC access points and the allocation is initialized in a proportional fair (PF) like method. Second, EC search procedures are iteratively operated until optimality. Through simulation, the algorithm outperforms classic PF and Round Robin RA methods in terms of throughput and user fairness.
Authors: Yuan Zhang (State Grid Information and Telecommunication Branch), Yang Li (State Grid Information and Telecommunication Branch), Liang Chen (State Grid Information and Telecommunication Branch), Ning Wang (State Grid Information and Telecommunication Branch), Bo Fan (Beijing University of Technology),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Gradient-Based UAV Positioning Algorithm for Throughput Optimization in UAV Relay Networks

Under natural disaster or other emergency situations, the fixed communication infrastructures are unavailable, which brings great inconvenience to information interaction among people. In this paper, we design a UAV relay network, using a small-scale UAV fleet serves as communication relays of a team of ground users performing collaborate tasks. Aiming at the user's requirement for high communication capacity for multi service transmission, we present a distributed gradient-based algorithm of finding the optimal positions of UAV in UAV relay network to improve the network average end-to-end throughput in real-time. The system optimization objective is formulated by using Shannon-Hartley Theorem and received signal-to-noise ratio (SNR) that incorporates with UAV positions and ground user positions. Due to the non-smoothness of the objective function, we use generalized gradient instead. Each UAV moves along the generalized gradient direction of objective function to optimize the target locally, and finally, all UAV convergence to stable positions of optimizing the network throughput. Simulation results show the effectiveness of our method in improving the network average end-to-end throughput.
Authors: Xiangyu Li (Beijing University of Post and Telecommunications), Tao Peng (Beijing University of Post and Telecommunications), Xiaoyang Li (Beijing University of Post and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
A Dynamic Network Mapping Algorithm Based on Node Multi-attribute and Partial Resource Sharing

As an important technology in cloud communication and internet of things, network virtualization is facing the challenge of network mapping. As the network mapping problem proves to be NP-hard, most of the mapping proposals are based on heuristics and have some limitations, including: 1) the storage resources attribute on nodes is usually ignored, while in practical applications, storage and calculation are separated and reconstructed dynamically; 2) The resource attributes of a single node are considered, while the network topology attributes are ignored; 3) Fixed re-sources are allocated throughout the life cycle, while the users' resource requirements are flexible in practice. In this paper, we propose a dynamic network mapping algorithm based on node multi-attribute and partial resource sharing, NMA-PRS-VNE. In which, the attributes of nodes include computing resources, storage resources and topological attributes, and an improved node evalua-tion method is used to measure the node availability. Besides, we divide the resource requirement of the virtual network request (VNR) into two parts: basic sub-requirements and variable sub-requirements. The former represents the basic resource demand of VNR, while the latter repre-sents the flexibility of the probability of VNR occupying resources by calculating collision prob-ability. The simulation results show that NMA-PRS-VNE performs better in terms of acceptance rate, network cost, link pressure and average revenue.
Authors: xiancui xiao, Xiangwei Zheng (Shandong Normal University),
Hide Authors & Abstract

Show Authors & Abstract

Session 2 10:00 - 11:00

Xiangshan Hall (4th Floor)
10:00 - 10:00
Joint Task Offloading, CNN Layer Scheduling and Resource Allocation in cooperative Computing SystemJoint Task Offloading, CNN Layer Scheduling and Resource Allocation in cooperative Computing System

In this paper, we consider a cooperative computing system which consists of a number of mobile edge computing (MEC) servers deployed with convolutional neural network (CNN) model, a remote mobile cloud computing (MCC) server deployed with CNN model and a number of mobile devices (MDs). We assume that each MD has a computation task and is allowed to offload its task to one MEC server where the CNN model with various layers is applied to conduct task execution, and one MEC server can accept multiple tasks of MDs. To enable the cooperative between the MEC servers and the MCC server, we assume that the task of MD which has been processed partially by the CNN model of the MEC server will be sent to CNN model of the MCC server for further processing. We study the joint task offloading, CNN layer scheduling and resource allocation problem. By stressing the importance of task execution latency, the joint optimization problem is formulated as an overall task latency minimization problem. As the original optimization problem is NP hard, which cannot be solved conveniently, we transform it into three subproblems, i.e., CNN layer scheduling subproblem, task offloading subproblem and resource allocation subproblem, and solve the three subproblems by means of extensive search algorithm, reformulation-linearization-technique (RLT) and Lagrangian dual method, respectively. Numerical results demonstrate the effectiveness of the proposed algorithm.
Authors: Xia Song, Rong Chai (CQUPT), Qianbin Chen (Key Lab of Mobile Communication Technology Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Orbital Angular Momentum Microwave Generated by Free Electron Beam

Based on the theory of classical electrodynamics and quantum mechanics, we quantitatively deduce microwave carrying Orbital Angular Momentum (OAM) radiated from the moving free electron beams on different closed-curved trajectories. It shows that the non-relativistic free electrons can also transit quantized OAM to the microwave photons in addition to the relativistic cyclotron electrons in the magnetic field. This work indicates the effective way to modify the selection rule of the dipole antennas and generate high OAM modes of the microwave photon by multi-electron radiation.
Authors: Chao ZHANG (School of Aerospace Engineering, Tsinghua University, Beijing, China.), Pengfei XU (School of Aerospace Engineering, Tsinghua University, Beijing, China),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
MmWave-NOMA-based Semi-Persistent Scheduling for Enhanced V2X Services

This paper investigates the semi-persistent scheduling (SPS) strategy for enhanced vehicle-to-everything (eV2X) services, which aims to meet the low latency and high reliability (LLHR) demands. To increase available spectrum and improve resource utilization, millimeter wave (mmWave) and non-orthogonal multiple access (NOMA) are considered. We first formulate the optimization problem of scheduling and resource allocation to minimize the SPS period. To solve this problem, the LLHR power control algorithm is proposed to provide evaluation indicators for user scheduling. Then, the beam division and user clustering algorithm is designed to reduce the complexity of the matching between users and resource blocks. After that, the matching problem with peer effects is solved by the proposed union-based matching algorithm. Complexity analysis is presented, and simulation results show that the scheduling period of eV2X systems can be improved by the proposed SPS strategy compared with the conventional mmWave SPS schemes.
Authors: Fanwei Shi (Soochow University), Bicheng Wang (Soochow University), Ruoqi Shi (Soochow University), Jianling Hu (Soochow University),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

Session 3 11:15 - 12:15

Xiangshan Hall (4th Floor)
11:15 - 11:15
Multi-Service Routing with Guaranteed Load Balancing for LEO Satellite Networks

Low Earth Orbit (LEO) Satellite Networks (SN) offers communication services with low delay, low overhead, and flexible networking. As service types and traffic demands increase, the multi-service routing algorithms play an important role in ensuring users' Quality of Service (QoS) requirements in LEO-SN. However, the multi-service routing algorithm only considers the link QoS information, ignoring the uneven distribution of ground users, causing satellite link or node congestion, increasing the packet transmission delay, and packet loss rate. In order to solve the above problems, we propose a Multi-Service Routing with Guaranteed Load Balancing (MSR-GLB) algorithm which balances the network load while satisfying multi-service QoS requirements. Firstly, the Geographic Location Information Factors (GLIF) are defined to balance the network load by scheduling the ISLs with lower loads. Then, the optimization objective function is constructed by considering delay, remaining bandwidth, packet loss rate, and GLIF in order to characterize the routing problems caused by multi-service and load balancing. Following this, we propose an MSR-GLB algorithm that includes the state transition rule and the pheromone update rule. The simulation results show that the MSR-GLB algorithm can well meet the QoS requirements of different services and balance the network load.
Authors: Cui-Qin Dai (Chongqing University of Posts and Telecommunications), Guangyan Liao (Chongqing University of Posts and Telecommunications), P. Takis Mathiopoulos (National and Kapodestrian University of Athens), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Mode Identification of OAM with Compressive Sensing in the Secondary Frequency Domain

The Electro-Magnetic (EM) waves with Orbital Angular Momentum (OAM) can achieve high spectral efficiency by multiplexing different OAM modes. Different modes are mapped to the frequency offset in the secondary frequency domain at the receiving end, in order to effectively identify the OAM modes received in partial phase plane. The traditional method requires high-speed acquisition equipment in the process of receiving Radio Frequency (RF) signals directly and its hardware cost is high. Even if analog devices are used for down-conversion to Intermediate Frequency (IF) sampling, the IF bandwidth limits transmission rate. However, Compressive Sensing (CS) can break the Nyquist restriction by random observation, and realize the detection and identification of different OAM modes at a lower sampling rate, so that the cost is low. Therefore, this paper proposes an OAM modes identification method based on CS. At the same time, random sampling is carried out based on the existing hardware device Analog-to-Information Converter (AIC) to realize the OAM modes identification of high-speed data transmission with low sampling rate. The simulation results verify the correctness and effectiveness of the method.
Authors: Chao ZHANG (School of Aerospace Engineering, Tsinghua Univ., Beijing, China), Jin LI (School of Aerospace Engineering, Tsinghua Univ., Beijing, China),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Improved Incremental Freezing HARQ Schemes Using Polar Codes over Degraded Compound Channels

The error propagation problem in incremental freezing (IF) hybrid automatic repeat request (HARQ) scheme using Polar codes is studied. We propose two IF HARQ schemes using polar codes, namely the cyclic redundancy check (CRC)-aided IF HARQ scheme and the cumulative-path-metrics-based IF HARQ scheme. In the CRC-aided IF HARQ scheme, several CRC bits are added to each transmitted block. Using these CRC bits, the proposed IF HARQ scheme and the Chase Combining HARQ scheme can be combined to achieve a better error correction performance in the cost of a larger decoding delay. In the cumulative-path-metrics-based IF HARQ scheme, the successive joint decoder maintains multiple possible paths simultaneously, and the cumulative path metrics is used to represent the reliability of each surviving path in the decoding process. Moreover, a modified path splitting reduced successive cancellation list (SCL) decoding algorithm is presented to reduce the computational complexity and the memory requirement of cumulative-path-metrics-based IF HARQ scheme. Simulation results show that, using the Polar code constructed under long block length and high block error rate, the CRC-aided IF HARQ scheme has a higher system throughput. With the Polar code constructed under short block length and low block error rate, the cumulative-path-metrics-based IF HARQ scheme has a higher system throughput. In both situations, the system block error rate of the CRC-aided IF HARQ scheme performs well.
Authors: Tianze HU (Zhejiang University), Lei XIE (Zhejiang University), Huifang CHEN (Zhejiang University), Hongda DUAN (Zhejiang University), Kuang WANG (Zhejiang University),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30

Session 4 13:30 - 14:30

Xiangshan Hall (4th Floor)
13:30 - 13:30
A Generic Polynomial-Time Cell Association Scheme in Ultra-Dense Cellular Networks

Cell association in heterogeneous cellular networks is a significant research issue, but existing schemes mainly optimize a single objective and could not solve such a problem with a generic utility function in polynomial time. This paper proposes a cell association scheme for generic optimization objectives with polynomial-time complexity, which employs a virtual base station method to transform it into a 2-dimensional assignment problem solved by Hungarian algorithm. Based on this scheme, a framework for the tradeoff among multiple optimization objectives is designed. This framework jointly considers spectral efficiency and load balancing, designs a weight factor to adjust their impacts on the optimization, and uses an experience pool to store the relationship between performance demands and corresponding weight factor values. For an instantaneous cell association decision in a given network scenario, the association results are obtained as soon as the corresponding factor value is taken from the pool and the Hungarian algorithm is called for the matching. Compared with existing schemes, our proposal achieves a better tradeoff between system capacity and UE fairness with an extremely low time cost.
Authors: Chao Fang (Anhui Province Key Laboratory of Industry Safety and Emergency Technology, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China), Lusheng Wang (Anhui Province Key Laboratory of Industry Safety and Emergency Technology, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China), Hai Lin (Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education. School of Cyber Science and Engineering, Wuhan University, Wuhan, China), Min Peng (Anhui Province Key Laboratory of Industry Safety and Emergency Technology, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Deep Q Network for Wiretap Channel Model with Energy Harvesting

An energy harvesting wiretap channel model is considered in which the sender is an energy harvesting node. It is assumed that at each time slot only information about the current state of the sending node is available. In order to find an effective power allocation strategy to maximize secrecy rate, we put forward a deep Q network (DQN) scheme. First, we analyze the constraints of the system and the issue of maximizing the secrecy rate. Next, the power allocation problem is formulated as a Markov Decision Process (MDP) with unknown transition probabilities. In order to solve the continuous state space problem that traditional Q learning algorithms cannot handle, we apply neural networks to approximate the value function. Finally, an online joint resource power allocation algorithm based on DQN is presented. Simulation results show that the proposed algorithm can effectively improve the secrecy rate of the model.
Authors: Zhaohui Li (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Weijia Lei (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Building gateway interconnected heterogeneous ZigBee and WiFi network based on Software Defined Radio

The ZigBee Alliance Lab proposes the concept of ZigBee-WiFi network. ZigBee-WiFi network has a broad development space when combined with the advantages of ZigBee and WiFi. However, since ZigBee and WiFi are heterogeneous in various aspects, it is necessary to find a way to interconnect the two networks. The traditional approach is to design dedicated hardware. Since the physical layer functions and part of MAC layer functions in the hardware are fixed, this method cannot adapt to the new physical layer and signal processing algorithms. Software Defined Radio (SDR) is an emerging and flexible method of transferring signal processing components from dedicated hardware to a combination of software and general purpose processors. In this paper, we use SDR in conjunction with the Universal Software Radio Peripheral (USRP) to build a flexible and universal ZigBee-WiFi gateway for interconnecting heterogeneous ZigBee and WiFi networks. The gateway has the ability to simultaneously receive and demodulate ZigBee packets, create and transmit WiFi data frames. A comprehensive performance test confirmed that the built gateway can well interconnect heterogeneous ZigBee and WiFi networks. And the built gateway provides a reference prototype for the interconnection research of heterogeneous networks.
Authors: Shuhao Wang (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Yonggang Li (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Chunqiang Ming (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Zhizhong Zhang (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 14:30 - 15:00

Session 5 15:00 - 16:00

Xiangshan Hall (4th Floor)
15:00 - 15:00
GNSS Spoofing Detection Using Moving Variance of Signal Quality Monitoring Metrics and Signal Power

Spoofing is a significant threat to the integrity of applications that rely on Global Navigation Satellite System (GNSS). A spoofer transmits counterfeit satellite signals to deceive the operation of a receiver. As multipath and spoofing signals have similar signal structures, Signal Quality Monitoring (SQM) techniques, originally designed for multipath detection, were identi-fied to be useful for detecting spoofing. Recently, a moving variance (MV) based SQM method was developed to improve the performance of raw SQM metrics. However, the main problem of implementing the MV-based SQM technique is to differentiate the spoofing attack from multipath. This work presents a two-dimensional detection method using carrier power and moving variance to improve detection performance. Besides, false alarm caused by multipath is avoided by the two-dimensional threshold. We employed a dataset called Texas Spoofing Test Battery and a multipath scenario from Osaka to evaluate the performance of the proposed algorithm.
Authors: Lixuan Li (Beihang University), Chao Sun (Beihang University),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
Towards a Complete View of the SSL/TLS Service Ports in the Wild

With the emergence of service port obfuscation and abuse, malicious services can hide their communication behaviors in large-scale normal SSL/TLS traffic easily. Therefore, it is of great significance to get the complete view of SSL/TLS service ports and understand the potential threat of SSL/TLS usage. In this paper, we conduct a comprehensive analysis of the SSL/TLS service port by carrying out a large-scale passive measurement based on two ISP-level networks with a total bandwidth of up to 100Gbps for over one year. Specifically, we first investigate the overall SSL/TLS service port view and uncover that the actual usage of port is in a state of confusion. At the same time, through in-depth analysis of specific well-known ports which are used by SSL/TLS, it is revealed that the well-known ports could be exploited by malicious SSL/TLS services easily. Then, we dig into some specific certificates to explore their ports behavior and discover that the self-signed certificates and EV certificates are in sorry state. Meanwhile, we uncover practices that may be exploited by malicious services, and reveal the potential threats or vulnerabilities in SSL/TLS service ports. We believe that the work will be beneficial to both SSL/TLS and web security in the future.
Authors: Peipei Fu (Institute of Information Engineering, Chinese Academy of Sciences), Mingxin Cui (Institute of Information Engineering, Chinese Academy of Sciences), Zhenzhen Li (Institute of Information Engineering, Chinese Academy of Sciences),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
Secrecy Precoder Design for k-User MIMO Interference Channels

In this paper, we study the secrecy precoding problem for a $k$-user multiple-input multiple-output (MIMO) interference channel, where an external eavesdropper aims to wiretap one of the legitimate links. By adopting a ``maxmin" fairness criteria, we formulate a secrecy rate maximization (SRM) problem for the proposed system, which naturally constitutes a difference convex (DC)-type programming problem and can be iteratively solved by employing a successive convex approximation (SCA) method. With the SCA method, the nonconvex parts of the SRM problem are approximated by their first-order Taylor expansion. Then, relying on successive convex programming of the convexified problem, an iterative precoding algorithm is developed. Moreover, a proximal point-based regularization is also pursued to ensure the convergence of the proposed algorithm without requiring any special restrictions on the channel ranks. Numerical simulations are further provided to demonstrate the proposed algorithm. Results show that our algorithm can converge fast to a near-optimal solution with guaranteed convergence.
Authors: bing fang (Army Command College of PLA), Wei Shao (Army Engineering University of PLA),
Hide Authors & Abstract

Show Authors & Abstract

Session 6 16:00 - 17:00

Xiangshan Hall (4th Floor)
16:00 - 16:00
Robust RSS-Based Localization in Mixed LOS/NLOS Environments

In this paper, we propose a robust received signal strength (RSS) based localization method in mixed line-of-sight/non-line-of-sight (LOS/NLOS) environments, where additional path losses caused by NLOS signal propagations need to be included. Considering that the additional path losses vary in a dramatic range, we express the additional path losses as the sum of a balancing parameter and some error terms. By doing so, we formulate a robust weighted least squares (RWLS) problem with the source location and the balancing parameter as unknown variables, which is, simultaneously, robust to the error terms. By employing the S-Lemma, the RWLS problem is transformed into a non-convex optimization problem, which is then approximately solved by applying the semidefinite relaxation (SDR) technique. The proposed method releases the requirement of knowing specific information about the additional path losses in the previous study. Simulation results show that the proposed method works well in both dense and sparse NLOS environments.
Authors: Yinghao Sun (Ningbo University), Gang Wang (Ningbo University), Youming Li (Institute of Communication Technology, Ningbo University),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Primary synchronization signal low complexity sliding correlation method

Abstract:With the development of technology, the mobile communication system has the characteristics of high rate and low delay. How to deal with the signal quickly and accurately has become a research hotspot. As the first step of the mobile communication system, the efficiency and performance of synchronization directly determine the follow-up signal Processing. In the mobile communication system, the terminal needs to synchronize the frequency and time of the received signal, that is, the synchronization signal is captured and processed. Frequency synchronization mainly carries on the digital down-conversion operation to the signal, the time synchronization is mainly through sliding the baseband signal with the locally generated synchronization sequence to determine the starting position of the synchronization signal, so as to achieve the time synchronization. Therefore, in this paper, taking LTE-A (Long Term Evolution Advanced) system as an example, a low-complexity sliding correlation method based on Fast Fourier Transform (FFT) is proposed in this paper, which can significantly reduce the computations in the synchronization process the complexity.
Authors: Hua-hua WANG (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Dong-feng CHEN (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Juan LI (School of Science College, Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Analysis of Frequency Offset Effect on PRACH in 5G NR Systems

Physical Random Access Channel (PRACH) in 5G new radio (NR) systems transmits random access preamble for the user equipment (UE) to access the network. In 5G NR systems, Zadoff-Chu (ZC) sequences are used as random access preamble sequences. Frequency offset severely affects the perfect autocorrelation properties of the preamble sequences, thereby affecting the preamble detection performance and timing accuracy. In this paper, frequency offset effect on PRACH preamble miss detection rate and timing error in 5G NR systems is analyzed. Firstly, the frequency offset effect on inter-carrier interference and the correlation of general sequences is derived. Then, based on the former derivation and characteristics of ZC sequences, the frequency offset effect on correlation of ZC sequences is derived. Moreover, PRACH preamble miss detection rate and timing error are analyzed. The analytical results show that for different random access UEs with different PRACH preamble numbers, the random access performances are differently affected by the same frequency offset. Besides, the higher miss detection rate, the smaller timing error. The simulation results show the rationality of the analysis.
Authors: Wenxi He (Beijing University of Posts & Telecommunications), Yifan Du (Beijing University of Posts & Telecommunications), Hang Long (Beijing University of Posts & Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
Room #3

DISA Workshop 1 09:00 - 10:00

Changyue Hall (3rd Floor)
09:00 - 09:00
Multi-convex Combination Adaptive Filtering Algorithm Based on Maximum Versoria Criterion

Aiming at the contradiction between the convergence rate and steady state mean square error of adaptive filter based on Maximum Versoria Criterion (MVC), this paper introduces the multi-convex combination strategy into MVC algorithm, and proposes a multi-convex combination MVC (MCMVC) algorithm. Simulation results show that compared with the existing MVC algorithm, MCMVC algorithm can select the best filter more flexibly under different weight change rates, and thus it has faster convergence speed and stronger tracking ability. Moreover, compared with the existing multi-convex combination maximum correntropy criterion (MCMCC) algorithm, MCMVC algorithm not only ensures the tracking performance, but also has lower exponential computation and steady-state error.
Authors: Wenjing Wu (Chang'an University), Zhonghua Liang (Chang'an University), Yimeng Bai (Chang'an University), Wei Li (Chang'an University),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Secure k-Anonymization Linked with Differential Identifiability

Most k-anonymization mechanisms that have been developed presently are vulnerable to re-identification attacks, e. g., those generating a generalized value based on input databases. k-anonymization mechanisms do not properly capture the notion of hiding in a crowd, because they do not impose any constraints on the mechanisms. In this paper, we define (k, ρ)-anonymization that achieves secure k-anonymization notion linked with differential identifiability under the condition of privacy parameter ρ. Both differential identifiability and k-anonymization limit the probability that an individual is re-identified in a database after an adversary observes the output results of the database. Furthermore, differential identifiability can provide the same strong privacy guarantees as differential privacy. It can make k-anonymization perform securely, while (k, ρ)-anonymization achieves the relaxation of the notion of differential identifiability, which can avoid a lot of noise and help obtain better utility for certain tasks. We also prove the properties of differential identifiability and (k, ρ)-anonymization under composition that can be used for application in data publishing and data mining.
Authors: Zheng Zhao (Beihang University), tao shang (BeiHang University), Jianwei Liu (Beihang University),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Energy management strategy based on battery capacity degradation in EH-CRSN

Energy Harvesting Cognitive Wireless Sensor Network (EH-CRSN) is a novel network which introduces cognitive radio (CR) technology and energy harvesting (EH) technology into traditional WSN. Most of the existing works do not con-sider that battery capacity of the sensor is limited and will decay over time. Bat-tery capacity degradation will reduce the lifetime of the sensor and affect the per-formance of the network. In this paper, in order to maximize the network utility of the energy harvesting sensor node in its life cycle, we are concerned with how to determine the optimal sampling rate of sensor node under the condition of bat-tery capacity degradation. Therefore, we propose an optimal adaptive sampling rate control algorithm (ASRC), which can adaptively adjust the sampling rate ac-cording to the battery level and effectively manage energy use. In addition, the impact of link capacity on network utility is further investigated. The simulation results verify the effectiveness of the algorithm, which shows that the algorithm is more realistic than the existing algorithm. It can maximize the network utility and improve the overall performance of the network.
Authors: Errong Pei (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Shan Liu (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Maohai Ran (Chongqing Electric Power College),
Hide Authors & Abstract

Show Authors & Abstract

DISA Workshop 2 10:00 - 11:00

Changyue Hall (3rd Floor)
10:00 - 10:00
Multipath and distorted detection based on multi-correlator

With the advent of new Global Navigation Satellite Systems (GNSS) and sig-nals, the signal quality monitoring techniques for navigation signals also need to be updated. In the traditional satellite signal integrity detection, the multi-correlator processing method is commonly used in signal quality monitoring to detect if a signal is distorted. This method often assumes that multipath signals have been eliminated, avoiding multipath signals from interfering with the detection results. However, if there is a multipath signal that has not been eliminated, since the correlation functions of the multipath signal and the distorted signal have a certain similarity, if the detection method without considering the multipath effect is used, here is a case where the multipath signal is erroneously detected as a distorted signal. Since the influence of the multipath signal and the distorted signal on the positioning result is very dif-ferent, it is necessary to distinguish the two signals during the detection pro-cess. In this paper, the model of multipath signal and distorted signal is dis-cussed for the new generation GNSS signal (BOC signal). Based on the char-acteristics of the correlation functions of these two models, a multi-correlator range setting method is proposed, and the appropriate detection values are selected, which can effectively distinguish multipath signals and distorted signals at the relevant peak levels.
Authors: rongtao qin (BeiHang University),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Delay Optimization-based Joint Route Selection and Resource Allocation Algorithm for Cognitive Vehicular Ad Hoc Networks

Cognitive vehicular ad-hoc networks (CVANETs) are expected to improve spectrum utilization efficiently and offer both infotainment and safety services for vehicles. In this paper, the joint route selection and resource allocation problem is considered for CVANETs. Taking into account the lifetime of transmission links, we first propose a candidate link selection method which selects the transmission links satisfying the link lifetime constraint. Then stressing the importance of transmission delay, we formulate the joint route selection and resource allocation problem as an end-to-end transmission delay minimization problem. As the formulated optimization problem is a complicated integer nonlinear problem, which cannot be solved conveniently, we equivalently transform the original problem into two subproblems, i.e., resource allocation subproblem for candidate links and route selection subproblem. Solving the two optimization subproblems by applying the K shortest path algorithm and the Dijkstra algorithm, respectively, we can obtain the joint route selection and resource allocation strategy. Simulation results demonstrate the effectiveness of the proposed algorithm.
Authors: Changzhu Liu (Chongqing University of Posts and Telecommunications), Rong Chai (Chongqing University of Posts and Telecommunications), Shangxin Peng (Chongqing University of Posts and Telecommunications), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Energy Efficiency Optimization-based Joint Resource Allocation and Clustering Algorithm for M2M Communication Networks

In recent years, machine-to-machine (M2M) communications have attracted great attentions from both academia and industry. In M2M communication networks, machine type communication devices (MTCDs) are capable of communicating with each other intelligently under highly reduced human interventions. In this paper, we address the problem of joint resource allocation and clustering for M2M communications. By defining the system energy efficiency (EE) as the sum of the EE of MTCDs, the joint resource allocation and clustering problem is formulated as a system EE maximization problem. As the original optimization problem is a nonlinear fractional programming problem, which cannot be solved conveniently, we transform it into two subproblems, i,e., power allocation subproblem and clustering subproblem, and solve the two subproblems by means of Lagrange dual method and modified K-means algorithm, respectively. Numerical results demonstrate the effectiveness of the proposed algorithm.
Authors: Changzhu Liu (Chongqing University of Posts and Telecommunications), Ahmed Zubair (Chongqing University of Posts and Telecommunications), Rong Chai (Chongqing University of Posts and Telecommunications), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

DISA Workshop 3 11:15 - 12:15

Changyue Hall (3rd Floor)
11:15 - 11:15
Latency-reliability Analysis for Multi-antenna System

The relationship between the latency and reliability of multi-antena diversity system is investigated in this paper. The system performance of diversity system is analysed with the outage probability chosen as the reliability metric. Two combining techniques are considered in the diversity system. It is proved that the latency-reliability trade-off degree (LRTD), i.e., the slope of the latency-outage curves with logarithmic scales, equals the number of the diversity order. In addition, the diversity system with considering system overhead is investigated. Golden section search algorithm and a simplified iterative method can be used to obtain the optimum diversity order of multiple-input and single-output (MISO) system adopted with maximal ratio combining and section combining techniques, respectively.
Authors: Zhichao Xiu (Beijing University of Posts and Telecommunications), Hang Long (Beijing University of Posts & Telecommunications), Yixiao Li (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Cost Function Minimization-based Joint UAV Path Planning and Charging Station Deployment

The rapid development of automatic control, wireless communication and intelligent information processing promotes the prosperity of unmanned aerial vehicles (UAVs) technologies. In some applications, UAVs are required to fly from given source places to certain destinations for task execution, a reasonable path planning and charging stations (CSs) strategy can be designed to achieve the performance enhancement of task execution of the UAVs. In this paper, we consider joint UAV path planning and CS deployment problem. Stressing the importance of the total time of the UAVs to perform tasks and the cost of deploying and maintaining CSs, we formulate the joint path planning and CS deployment problem as a cost function minimization problem. Since the formulated optimization problem is an NP-hard problem which cannot be solved easily, we propose a heuristic algorithm which successively solves two subproblems, i.e, path planning subproblem and destination path selection subproblem by applying the A* algorithm, K-shortest path algorithm and genetic algorithm (GA), respectively. Simulation results validate the effectiveness of the proposed algorithm.
Authors: Tao Wei, Rong Chai (CQUPT), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Energy Efficient Computation Offloading for Energy Harvesting-Enabled Heterogeneous Cellular Networks

Mobile edge computing (MEC) is regarded as an emerging paradigm of computation that aims at reducing computation latency and improving quality of experience. In this paper, we consider an MEC-enabled heterogeneous cellu- lar network (HCN) consisting of one macro base station (MBS), one small base station (SBS) and a number of users. By defining workload execution cost as the weighted sum of the energy consumption of the MBS and the workload drop- ping cost, the joint computation offloading and resource allocation problem is formulated as a workload execution cost minimization problem under the con- straints of computation offloading, resource allocation and delay tolerant, etc. As the formulated optimization problem is a Markov decision process (MDP)-based offloading problem, we propose a hotbooting Q-learning-based algorithm to ob- tain the optimal strategy. Numerical results demonstrate the effectiveness of the proposed scheme.
Authors: mengqi mao (Chongqing University of Posts and Telecommunications), Rong Chai (CQUPT), Qianbin Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30

DISA Workshop 4 13:30 - 14:30

Changyue Hall (3rd Floor)
13:30 - 13:30
Wi-Fi Gesture Recognition Technology Based on Time-Frequency Features

With the rapid development of artificial intelligence, gesture recognition has become the focus of many countries for research. Gesture recognition using Wi-Fi signals has become the mainstream of gesture recognition because it does not require additional equipment and lighting conditions. Firstly, how to extract useful gesture signals in a complex indoor environment. In this paper, after de-noising the signal by Discrete Wavelet Transform (DWT) technology, Principal Component Analysis (PCA) is used to eliminate the problem of signal redundancy between multiple CSI subcarriers, further to remove noise. Secondly, the frequency domain features of the gesture signal are constructed by performing Short-Time Fourier Transform (STFT) on the denoised CSI amplitude signal. Then, the time domain features are combined with the frequency domain features, and the features are trained and classified using the Support Vector Machine (SVM) classification method to complete the training and recognition of gesture. The experimental results show that this paper can effectively identify gestures in complex indoor environments.
Authors: Zengshan Tian (13364031496), Mengtian Ren (13983700028), Qing Jiang (13983700028), Xiaoya Zhang (13364031496),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Accompaniment Music Separation Based on 2DFT and Image Processing

For the difficulty of separation of accompaniment from mono music, image filtering was applied into a novel approach to separate accompaniment music. Our approach presents how single channel music manifests in the 2D Fourier Transform spectrum. In image domain, the position of periodic peak energy was determined by image filtering, and then masking matrix was constructed by rectangular window to extract the constituent of the accompaniment music. We find that our system is more robust and very simple to describe. The simulation experiments show that the method in this work has an advantage over other separation algorithm.
Authors: Tian Zhang, Tianqi Zhang (Chongqing University of Posts and Telecommunications, Chongqing, China), Congcong Fan (Chongqing University of Posts and Telecommunications, Chongqing, China),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Average Speed Based Broadcast Algorithm for Vehicular Ad Hoc Networks

In order to solve the problem of broadcast storm and broadcast unreliability in Vehicular Ad Hoc Networks (VANET) on highways, an improved algorithm based on Speed Adaptive Probabilistic Flooding (SAPF) [1],which is referred to as Average Speed Based Broadcast (ASBB),is proposed. Since the average speed of vehicles in the vicinity reflects the network congestion around the current node more accurately, ASBB dynamically calculates the forwarding probability according to the average speed of the current node and the corresponding neighbor nodes. To obtain the speed of neighbor nodes, each node encapsulates its speed into the header of packets it transmits, instead of employing new types of packet for exchanging speed. This approach alleviates the network load and reduces the complexity of implementation. Meanwhile, only the nodes located behind the current node may participate in the forwarding of the broadcast packet, which reduces the number of nodes participating in the forwarding and further mitigates the broadcast storm and improves the broadcast reliability. The simulation results show that ASBB performs well in terms of suppressing broadcast storms, increasing the reachability and reducing the end-to-end delay.
Authors: Qichao Cao (Zhejiang Gongshang University), Yanping Yu (Zhejiang Gongshang University), Xue Su (Zhejiang Gongshang University),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 14:30 - 15:00

Session 5 15:00 - 16:00

Changyue Hall (3rd Floor)
15:00 - 15:00
Wireless Channel Pattern Recognition using k-nearest neighbor algorithm for High-speed railway

Channel is important for the wireless communication system. The channel in high-speed railway is rapid time-variation and non-stationary. This papers discusses the channel characteristic in open space scenario, and defines 4 patterns. Furthermore a channel pattern recognition algorithm is proposed using k-nearest neighbor method. Simulation results show that the proposed method performs well with high accuracy and robust.
Authors: lei xiong (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University), Huayu li (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University), zhengyu zhang (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University), Bo Ai (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University), Pei Tang (China Railway Siyuan Survey and Design Group CO., LTD),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
Price-Based Power Control in NOMA based Cognitive Radio Networks Using Stackelberg Game

This paper studies the price-based power control strategies for non-orthogonal multiple access (NOMA) based cognitive radio networks. The primary user (PU) profits from the secondary users (SUs) by pricing the interference power made by them. Then, SUs cooperate to maximize their total revenue at the base station with successive interference cancellation (SIC) while considering their payoff to the primary user. Considering the pricing and power control strategies between the PU and SUs as a Stackelberg game. The closed-form expression of the optimal price for the non-uniform pricing scheme is given. The computational complexity of the proposed uniform-pricing algorithm is only linear with respect to the number of SNs. the Simulation results are presented to verify the effectiveness of our proposed pricing algorithm.
Authors: Zhengqiang Wang (Chongqing University of Posts and Telecommunications), Hongjia Zhang (Chongqing University of Posts and Telecommunications,Chongqing, P. R. Chin), Zifu Fan (Chongqing University of Posts and Telecommunications, P. R. China), Xiaoyu Wan (Chongqing University of Posts and Telecommunications, P. R. China), Xiaoxia Yang (Chongqing University of Posts and Telecommunications,Chongqing, P. R. Chin),
Hide Authors & Abstract

Show Authors & Abstract
15:00 - 15:00
Deep Learning Based Single-Channel Blind Separation of Co-frequency Modulated Signals

This paper presents our results in deep learning (DL) based single-channel blind separation (SCBS). Here, we propose a bidirectional recurrent neural network (BRNN) based separation method which can recover information bits directly from co-frequency modulated signals after end-to-end learning. Aiming at the real-time processing, a strategy of block processing is proposed, solving high error rate at the beginning and end of each block of data. Compared with the conventional PSP method, the proposed DL separation method achieves better BER performance in linear case and nonlinear distortion case with lower computational complexity. Simulation results further demonstrate the generalization ability and robustness of the proposed approach in terms of mismatching amplitude ratios.
Authors: Chen Chen (Shanghai Jiao Tong University), Zhufei Lu (Yichang Testing Institute of Technology Research), Zhe Guo (Shanghai Microwave Research Institute & CETC Key Laboratory of Data Link Technology), Feng Yang (Shanghai Jiao Tong University), Lianghui Ding (Shanghai Jiao Tong University),
Hide Authors & Abstract

Show Authors & Abstract

Session 6 16:00 - 17:00

Changyue Hall (3rd Floor)
16:00 - 16:00
Energy-Efficient Mode Selection for D2D Communication in SWIPT Systems

In D2D communication mode selection, we add simultaneous wireless information and power transfer (SWIPT) to realize the coordinated transmission of information and energy, so that users can obtain energy in the process of receiving information, and reduce the battery energy consumption in the communication process. We use the theory of stochastic geometry to analyze the ergodic energy harvesting (EEH) of D2D and cellular links in the three communication modes. Then, based on the data transmission process, we get the expressions of system energy efficiency (EE), and finally, perform the mode selection according to the energy-efficiency. The simulations show that ergodic energy harvesting of D2D and cellular links increases gradually as user transmit power increases in all three modes. After using power splitting (PS), we can see that the dedicated mode delivers the highest energy efficiency, the reuse mode ranks the second, and the cellular mode renders the lowest energy efficiency.
Authors: Jingjing Cui (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Jun Huang (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Research on OTFS Performance Based on Joint-Sparse Fast Time-Varying Channel Estimation

Contraposing the problem of high pilot overhead and poor estimation performance for OFDM system in fast timevarying channels, a novel channel estimation method based on joint-sparse basis expansion model is proposed. In order to resist the inter-carrier interference (ICI) of OFDM system over fast time-varying channel, we introduce the OTFS (Orthogonal Time Frequency Space) technique and propose an implementation scheme of OTFS system based on time-frequency domain channel estimation. Simulation results demonstrate that the proposed OTFS system has higher reliability and better adaptability than the OFDM system in high dynamic scenarios.
Authors: Wenjing Gao, Shanshan Li (Beijing University of Posts and Telecommunications), Lei Zhao (Beijing University of Posts and Telecommunications), Wenbin Guo (Beijing University of Posts and Telecommunications), Tao Peng (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
16:00 - 16:00
Load Balancing Mechanism Based on Sparse Matrix Prediction in C-RAN Networks

In order to solve the problem that the existing algorithms in large-scale networks have high complexity in adjusting power iteratively, a load balancing mechanism based on sparse matrix prediction is proposed to achieve load balancing in C-RAN architecture. In order to minimize the correlation degree of load transfer and the balance of load transfer, the optimal sparse matrix block is obtained combined with Ncut cutting algorithm to realize dimension reduction and zero removal of the load transfer matrix. After the block, the load transfer matrix of each block is recalculated, and the load transfer matrix is used to predict the load. Finally, combined with the predicted load, the power adjustment step size is determined, and the pilot signal power of each block is adjusted in parallel to achieve load balancing. The simulation results show that the load balancing mechanism can reduce the complexity of load balancing.
Authors: Yang Liu (School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications), Zhanjun Liu (School of Communication and Information Engineering,Chongqing University of posts and Telecommunications), Ling Kuang (School of Communication and Information Engineering,Chongqing University of Posts and Telecommunication), Xinrui Tan (School of Communication and Information Engineering,Chongqing University of Posts and Telecommunication),
Hide Authors & Abstract

Show Authors & Abstract
Day 3 01/12/2019
Room #1

Session 1 09:00 - 10:00

Huashan Hall (4th Floor)
09:00 - 09:00
A Signaling Analysis Algorithm in 5G Terminal Simulator

Focused on the issue that the low efficiency for 5G network signaling analysis and processing, a hash topology under a new architecture based on the traditional LTE-A signaling monitoring and analysis system was proposed, its main subsystems and specific functional modules were introduced in detail, provided support for 5G terminal emulator signaling analysis. Firstly, the Key of the signaling message was sorted according to the value by using a large top heap; Secondly, the Key was mapped to a hash table, and the position of the Key value in the linked list was determined according to the probability, and the probability was obtained. The larger Key value was placed in the hash table with less conflicts. Finally, the hash table record was accessed, and the same signaling process information of the same user was associated and synthesized. The experimental results show that the improved algorithm under the proposed new architecture reduces the time spent on signaling analysis by 55.66% compared with the traditional algorithm, so it is suitable for practical engineering applications.
Authors: Yu Duan (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications), Wanwan Wang (School of Data Science, Chongqing Vocational College of Transportation), Zhizhong Zhang (School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Design and Implementation of Assembler for High Performance Digital Signal Processor (DSP)

With the rapid development of the fifth-generation mobile communication technology (5G), existing digital signal processors (DSP) on the market cannot efficiently provide the performance required by some applications. In this situation, we design a new DSP with faster speed, lower latency and higher performance. In this article, based on the new DSP which can adapt to the new technology of 5G, we designed an assembler called Swift Assembler (SA). Different from the traditional assembler, SA is based on the Gnu Architecture Description Language, (GADL). We perform semantic analysis on GADL description files and then with the help of flex, bison and Binutils, the assembler is compiled and generated. With the support of GADL, SA has a clearer architecture and better scalability. At the same time, it covered the underlying implementation. Benefit from this, programmers can modify its source code with no need to understand the underlying implementation process. In this way, the design of interdependent hard-ware and software can be more easily.
Authors: Peng Ding (Tongji university), Haoqi Ren (Tongji University), Zhifeng Zhang (Tongji University), jun wu (Tongji University), Fusheng Zhu (GuangDong Communications & Networks Institute), Wenru Zhang (GuangDong Communications & Networks Institute),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Image Aesthetic Assessment

Image aesthetic assessment is a challenging problem in the field of computer vision. Recently, the input size of images is often lim- ited by the network of aesthetic problems. The methods of cropping, wrapping and padding unify images to the same size, which will de- stroy the aesthetic quality of the images and affect their aesthetic rating labels. In this paper, we present an end-to-end deep Multi-Task Spa- tial Pyramid Pooling Fully Convolutional Neural NasNet(MTP-NasNet) method for image aesthetic assessment that can directly manipulate the original size of the image without destroying its beauty. Our method is developed based on Fully Convolutional Network(FCN) and Spatial Pyramid Pooling(SPP). In addition, existing studies regard aesthetic assessment as a two-category task, a distribution predicting task or a style predicting task, but ignore the correlation between these tasks. To address this issue, we adopt the multi-task learning method that fuses two-category task, style task and score distribution task. Moreover, this paper also explores the reference of information such as variance in the score distribution for image reliability. Our experiment results show that our approach has significant performance on the large-scale aesthetic assessment datasets), and demonstrate the importance of multi- task learning and size preserving. Our study provides a powerful tool for image aesthetic assessment, which can be applied to photography and image optimization field.
Authors: XIN SUN (Shanghai JiaoTong University), JUN ZHOU (Shanghai JiaoTong University),
Hide Authors & Abstract

Show Authors & Abstract

Session 2 10:00 - 11:00

Huashan Hall (4th Floor)
10:00 - 10:00
A Panoramic Video Face Detection System Design and Implement

A panorama is a wide-angle view picture with high-resolution, usually composed of multiple images, and has a wide range of applications in surveillance and entertainment. This paper presents a end-to-end real-time panoramic face detection video system, which generates panorama video efficiently and effectively with the ability of face detection. We fix the relative position of the camera and use the speeded up robust features (SURF) matching algorithm to calibrate the cameras in the offline stage. In the online stage, we improve the parallel execution speed of image stitching using the latest compute unified device architecture (CUDA) technology. The proposed design fulfils high-quality automatic image stitching algorithm to provide a seamless panoramic image with 6k resolution at 25fps. We also design a convolutional neural network to build a face detection model suitable for panorama input. The model performs very well especially in small faces and multi-faces, and can maintain the detection speed of 25fps at high resolution.
Authors: Hang Zhao (Tongji University), Dian Liu (Tongji University), Bin Tan (Jinggangshan University), Songyuan Zhao (Tongji University), Jun Wu (Tongji University), Rui Wang (Tongji University),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Coherence Histogram Based Wi-Fi Passive Human Detection Approach

Some traditional Wi-Fi indoor passive human detection systems only extract the coarse-grained statistical information such as the variance, which leads to low detection accuracy and poor adaptability. To solve the problem, we propose a new coherence histogram for Wi-Fi indoor passive people detection. In the histogram construction process, the method leverages time continuity relationship between received signal strength (RSS) measurements. The coherence histogram captures not only the occurrence probability of signals but also the time relationship between adjacent measurements. Compared to statistical features, the coherence histogram has more effective fine-grained information. The feature vector that is used to train the classifier consists of coherence histograms. To eliminate the position drift problem, the Allen time logic helps to establish the transfer relationship between the sub-areas, and the initial result of the position is corrected to improve the locating rate by the relationship. Compared with the classic people detection technology, the proposed method has better performance, and F1-measure improves by nearly 5%.
Authors: Zengshan Tian (13527430328), Xiaoya Zhang (13364031496), Lingxia Li (13628381659),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
A Convolutional Neural Network Decoder for Convolutional Codes

The convolutional neural network (CNN) decoder for general convolutional decoding is proposed. The parameters of CNN are determined by the initial state of each input block and the constraint relationship between adjacent bits is extracted by the convolutional layer as the constraint features. Then CNN decoder realizes decoding process through the extracted constraint feature instead of codewords directly. The result shows that, without changing the structure of decoder, the decoding performance of CNN decoder on different convolutional codes is equivalent to Viterbi soft decoding algorithm. Compared with Viterbi decoding, the larger constraint length or the lower SNR, the greater gain can be obtained in CNN decoder. Besides, we consider CNN trained by the two kinds of training sets in order to further investigate the potential and limitations of CNN decoder with respect to decoding performance, analysing the advantages and factors of these two kinds of training sets.
Authors: Zhengyu Zhang (Beijing Jiaotong University), Dongping Yao (Beijing Jiaotong University), Lei Xiong (Beijing Jiaotong University), Bo Ai (Beijing Jiaotong University), Shuo Guo (Shanghai Gezhi High School),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

Session 3 11:15 - 12:15

Huashan Hall (4th Floor)
11:15 - 11:15
Legitimate Eavesdropping with Multiple Wireless Powered Eavesdroppers

This paper considers a suspicious communication network with multiple suspicious source-destination nodes and multiple wireless powered legitimate eavesdroppers, where the legitimate eavesdroppers are assumed to be collusive or non-collusive. A minimum harvested energy constraint is applied at each eavesdropper such that each eavesdropper must harvest a minimum required energy. The legitimate eavesdropping in such a scenario is investigated and our aim is to maximize the average successful eavesdropping probability by optimizing the power splitting ratio at each eavesdropper under the minimum harvested energy constraint. The optimal algorithm is proposed to solve the optimization problem for both collusive eavesdroppers and non-collusive eavesdroppers. Simulation results show that the proposed algorithm achieves the upper bound of the successful eavesdropping probability when the energy harvesting efficiency is large, the required minimum harvested energy is small, or the transmit power of the suspicious source node is high.
Authors: Qun Li (Nanjing University of Posts and Telecommunications), Ding Xu (Nanjing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
WiHlo: A Case Study of WiFi-based Human Passive Localization by Angle Refinement

The emergence of the Internet of Things (IoT) has promoted the interconnection of all things. And the access control of devices and accurate service promotion are inseparable from the acquisition of location information. We propose WiHlo, a passive localization system based on WiFi Channel State Information (CSI). WiHlo directly estimates the human location by refining the angle-of-arrival (AoA) of the subtle human reflection. WiHlo divides the received signals into static path components and dynamic path components, and uses phase offsets compensation and direct wave suppression algorithms to separate out the dynamic path signals. By combining the measured AoAs and time-of-arrivals (ToAs) with Gaussian mean clustering and probability analysis, WiHlo identifies the human reflection path from the dynamic paths. Our implementation and evaluation on commodity WiFi devices demonstrate WiHlo outperforms the state-of-the-art AoA estimation system in actual indoor environment.
Authors: Zengshan Tian (Chongqing University of Posts and Telecommunications), Weiqin Yang (Chongqing University of Posts and Telecommunications), Yue Jin (Chongqing University of Posts and Telecommunications), Gongzhui Zhang (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
An Integrated Processing Method based on Wasserstein Barycenter Algorithm for Automatic Music Transcription

Given a piece of acoustic musical signal, various automatic music transcription (AMT) processing methods have been proposed to generate the corresponding music notations without human intervention. However, the existing AMT methods based on signal processing or machine learning cannot perfectly restore the original music signal and have significant distortion. In this paper, we propose a novel processing method which integrates various AMT methods so as to achieve better performance on music transcription. This integrated method is based on the entropic regularized Wasserstein Barycenter algorithm to speed up the computation of the Wasserstein distance and minimize the distance between two discrete distributions. Moreover, we introduce the proportional transportation distance (PTD) to evaluate the performance of different methods. Experimental results show that the precision and accuracy of the proposed method increase by approximately 48 percent and 67 percent respectively compared with the existing methods.
Authors: cong jin (Communication University of China), zhongtong li (Communication University of China, Beijing), yuanyuan sun (Communication University of China), haiyin zhang (communication University of China), xin lv (Communication University of China), jianguang li (Communication University of China), shouxun liu (Communication University of China),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30

Session 4 13:30 - 14:30

Huashan Hall (4th Floor)
13:30 - 13:30
Underwater Acoustic Channel Estimation Based on Signal Cancellation

Aiming at the requirement of underwater information security transmission, the security of encryption key generation and distribution in underwater acoustic communication is concerned. Key generation technology based on underwater acoustic channel (UAC) estimation can improve the security and real-time genera-tion of encryption keys. In this paper, the idea of estimating the multipath struc-ture of UAC is to retrieve the arrival signal by acquiring the parameters of larger energy Eigen-ray from real arrival signal, and to eliminate the arrival signal of larger energy Eigen-ray path from the real signal through signal cancellation, so as to eliminate the influence of side lobes of larger energy signal to arrival signals of other Eigen-ray path, to improve the estimation performance of multipath structure in underwater acoustic channel. The simulation and experimental results show that the improved algorithm can estimate the multipath structure of under-water acoustic channel more accurately and provide support for the subsequent underwater information security transmission.
Authors: Junkai Liu, Yangze Dong (Science and Technology on Underwater Acoustic Antagonizing Laboratory), Gangqiang Zhang (Science and Technology on Underwater Acoustic Antagonizing Laboratory), Junqing Zhang (Science and Technology on UnderWater Acoustic Antagonizing Laboratory),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
A Novel Spectrum Correlation Based Energy Detection For Wideband Spectrum Sensing

With the rapid development of wireless communications technology, the problem of scarcity of spectrum resources is becoming serious. Cognitive radio (CR) which is an effective technology to improve the utilization of spectrum resources is getting more and more attention. Spectrum sensing is a key technology in cognitive radio. Wideband spectrum sensing (WBSS) can help secondary users (SUs) find more spectrum holes. However, for the traditional energy detection (ED) algorithm, when the signal-to-noise ratio (SNR) of the primary user (PU) is low, the detection performance is extremely poor owing to the single frequency point detection method. Therefore, the concept of spectrum correlation is proposed. Spectrum correlation algorithm uses the detection window to realize joint detection of multiple frequency points which can improve performance. This paper focuses on how to make the best of spectrum correlation to ensure the detection performance for low SNR signals. We propose an adaptive detection window (ADW) method, whose detection window is adaptively selected based on the estimated SNR of signal. The method can be directly used for wideband spectrum sensing when the approximate position of each signal and its estimated SNR are known. In this context, simulations of methods comparison demonstrate that the proposed ADW method outperforms the commonly used iterative energy detection method, frequency correlation methods and histogram-based segmentation method by far.
Authors: bo lan (Beijing University of Post and Telecommunications), Tao Peng (Beijing University of Post and Telecommunications), Peiliang Zuo (Beijing University of Post and Telecommunications), Wenbo Wang (Prof.),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Spread Spectrum Audio Watermark Based On Non-Uniform Quantization

Audio watermarking is an information hiding technology which is widely used in copyright protection and information security. This paper proposes a novel audio watermarking scheme based on spread spectrum and non-uniform quantization. The watermarks are embedded by modifying the quantization coefficients. The proposed algorithm utilizes the characteristics of non-uniform quantization to adopt different quantized signal-to-noise ratios for the low-frequency and high-frequency parts of the audio signal, thus improving the robustness of the technology while ensuring the sound quality is not damaged. Compared with the existing audio watermarking methods, the proposed scheme is especially robust against additive white Gaussian noise(AWGN). Experimental analysis shows that the proposed method provides high audio quality and excellent capability to withstand various noise attacks particularly in AWGN.
Authors: Meijun Ning (Beijing University of Posts and Telecommunications), Tao Peng (Beijing University of Posts and Telecommunications), Yue Qing Xu (Beijing University of Posts and Telecommunications), Qing Yi Quan (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
Room #2

Session 1 09:00 - 10:00

Xiangshan Hall (4th Floor)
09:00 - 09:00
Near-Field Source Localization by Exploiting the Signal Sparsity

This work aims to study the source localization problem using a symmetric array in a near-field environment. To reduce the computational complexity, in this work, two spatial correlation signals are created in which each signal only depends on one parameter of direction of arrival (DOA) or range. In the development process, the each resulting signal still possesses the array spatial structure, and therefore, the atomic norm minimization is utilized to obtain the corresponding solutions. The utilization of atomic norm also allows one to avoid the off-grid problem when the sparse reconstruction concept is employed. The numerical studies demonstrate the proposed method provides a superior performance compared with other approaches.
Authors: huan meng (School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing, China), Hongqing Liu (Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing, China), Yi Zhou (School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing, China), Zhen Luo (Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing, China),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Layer-wise Entropy Analysis and Visualization of Neurons Activation

Understanding the inner working mechanism of deep neural networks (DNNs) is essential and important for researchers to design and improve the performance of DNNs. In this work, the entropy analysis is leveraged to study the neurons activation behavior of the fully connected layers of DNNs. The entropy of the activation patterns of each layer can provide an efficient performance metric for the evaluation of the network model accuracy. The study is conducted based on a well trained network model. The activation patterns of shallow and deep layers of the fully connected layers are analyzed by inputting the images of a single class. It is found that for the well trained deep neural networks model, the entropy of the neuron activation pattern is monotonically reduced with the depth of the layers. That is, the neuron activation patterns become more and more stable with the depth of the fully connected layers. The entropy pattern of the fully connected layers can also provide guidelines as to how many fully connected layers are needed to guarantee the accuracy of the model. The study in this work provides a new perspective on the analysis of DNN, which shows some interesting results.
Authors: longwei wang, Peijie Chen (Auburn university), Chengfei Wang (Auburn University), Rui Wang (Tongji University),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Analog Images Communication Based on Block Compressive Sensing

Recently, owing to graceful performance degradation for various wireless channels, analog visual transmission has attracted considerable attention. The pioneering work about analog visual communication is SoftCast, and many advanced works are all based on the framework of SoftCast. In this paper, based block compressive sensing, we propose a novel analog communication system of images called CSCast. Firstly, we present the system framework and detail design of CSCast, which consists of discrete wavelet transform, power scaling, compressive sampling and analog modulation. Furthermore, we discuss how to determine the appropriate value of scaling factor $\alpha$ in power allocation, and size of measurement matrix in compressive sampling. Simulations show that the performance of CSCast better than Softcast in all SNR range, and better than Cactus, which is another analog visual communication system based on SoftCast, in high SRN range. On test iamges, CSCast outperforms over Softcast about $1.72$ \ dB. And CSCast achieves the maximum average PSNR gain 1.8 \ dB over Cacuts and 2.03 \ dB over SoftCast when SNR = 25 \ dB, respectively. In addition, analyses shows CSCast can save about 75\% overhead comparing to SoftCast and Cactus.
Authors: Min Wang (Gannan Normal University, China), Bin Tan (Jinggangshan University), Jiamei Luo (Gannan Normal University), Qin Zou (Gannan Normal University),
Hide Authors & Abstract

Show Authors & Abstract

Session 2 10:00 - 11:00

Xiangshan Hall (4th Floor)
10:00 - 10:00
A classifier combining local distance mean and centroid for imbalanced datasets

The K-Nearest Neighbor (KNN) algorithm is widely used in practical life because of its simplicity and easy understanding. However, the traditional KNN algorithm has some shortcomings. It only considers the number of samples of different classes in k neighbors, but ignores the distance and location distribution of the unknown sample relative to the k nearest training samples. Moreover, classes imbalance problem is always a challenge faced with the KNN algorithm. To solve the above problems, we propose an improved KNN classification method for classes imbalanced datasets based on local distance mean and centroid (LDMC-KNN) in this paper. In the proposed scheme, different numbers of nearest neighbor training samples are selected from each class, and the unknown sample is classified according to the distance and position of these nearest training samples. Experiments are performed on the UCI and the KEEL datasets. The results show that the proposed algorithm has strong competitiveness and is always far superior to KNN algorithm and its variants.
Authors: Yingying Zhao (School of Electronics and Information Technology, Sun Yat-sen University), Xingcheng Liu (School of Electronics and Information Technology, Sun Yat-sen University; School of Information Science, Xinhua College of Sun Yat-sen University),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Content Recommendation Algorithm Based on Double Lists in Heterogeneous Network

Applying recommendation algorithms in the mobile edge caching can further improve the utilization of the caching and relieve the pressure of the backhaul. The key is to capture a highly accurate user preferences. Capturing user preferences from the user's request record has hysteresis, and capturing user preferences from the user's current request is inaccurate. In this paper, we propose a content recommendation algorithm based on double lists which can overcome hysteresis and inaccuracy. The content, user preferences and user’s requests are modeled as vectors from multiple content dimensions, and the dimensions is determined by the classification of the content. Based on user's request record, we capture the user preferences vector (Pre-Vector) by using the maximum likelihood estimation. The Pre-Vector accurately reflects user preference but has hysteresis. The user current request vector (Req-Vector) can reflect the user's current hobby but its accuracy is not high. We generated the preference-based recommendation list and the request-based recommendation list based on the Pre-Vector and the Req-Vector. In order to ensure the accuracy of the recommendation list, the final recommendation list is generated based on the Pre-Vector and the Req-Vector’s cosine similarity. The simulation results show that, the proposed algorithm has improved hit rate compared with existing recommendation algorithms.
Authors: Jianing Chen (Beijing University of Posts and Telecommunications), XI LI (Beijing University of Posts and Telecommunications), Hong Ji (BUPT), Heli Zhang (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Research on High Precision Location Algorithm of NB Terminal Based on 5G/NB-IoT Cluster Node Information Fusion

With the development of the Internet of Things, a large number of connection requirements for sensing and control are generated. However, in wireless positioning, Narrowband Internet of Things(NB-IoT) has poor positioning accuracy. The further integration of 5G and NB-IoT networks is expected to effectively improve the positioning accuracy of NB-IoT networks. Therefore, the high-precision positioning algorithm for researching converged networks has broad application prospects and academic significance. In order to improve the positioning accuracy of NB-IoT, based on the 5G and NB-IoT heterogeneous positioning framework, we propose to introduce a number of cluster nodes, which have the function of communicating with 5G and NB-IoT networks simultaneously. Limited by narrow bandwidth and clock synchronization, only DOA (Direction of Arrival) and RSSI principles can be considered. In this paper, we firstly use 5G to locate cluster nodes according to the principles of TDOA (Time Difference of Arrival). Based on the solution space (x±εx, y±εy), the NB-IoT terminal is located by the cluster nodes according to the DOA and RSSI fusion method. This method helps reduce the matching time and improve the accuracy of single DOA/RSSI positioning method. Meanwhile, considering cluster node errors, higher precision NB-IoT network positioning results can be obtained. Compared to a single NB-IoT network positioning, the final positioning accuracy of NB-IoT terminal can be improved by 80~90%.
Authors: Wei Ju (Shanghai JiaoTong University), Di He (Shanghai JiaoTong University), Xin Chen (Shanghai JiaoTong University), Changqing Xu (Shanghai JiaoTong University), Wenxian Yu (Shanghai JiaoTong University),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

Session 3 11:15 - 12:15

Xiangshan Hall (4th Floor)
11:15 - 11:15
Spinal-Polar Concatenated Codes in Non-coherent UWB Communication Systems

Non-coherent ultra-wideband (UWB) systems have attracted great attention due to their low complexity, and without the need of channel estimation. In order to improve the transmission reliability, polar codes were recently introduced into non-coherent UWB systems because of their capability of approaching the Shannon channel capacity, and their low complexity in both coding and decoding. In the case of polar codes with medium and short length, the bit error rate (BER) performance of coded incoherent UWB systems is limited to incompletely channel polarization, poor Hamming distance and the sensitivity of successive cancellation (SC) decoding resulting in error propagation. In order to improve the performance of coded systems using polar codes with medium and short length, Spinal-Polar concatenated codes are were recently presented, in which inner codes and outer codes are complementary, and the outer codes have good pseudo-random characteristics and error correction performance in the case of short length. Therefore, in this paper, the interleaved Spinal-Polar concatenated codes are introduced into the non-coherent UWB systems. Simulation results show that the interleaved Spinal-Polar concatenated codes can effectively improve the BER performance of the coded incoherent UWB system using polar codes with medium and short code length.
Authors: Qianwen Luo (Chang’an University), Zhonghua Liang (Chang’an University), Yue Xin (Chang’an University),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Dynamic Programming Based Cooperative Mobility Management in Ultra Dense Networks

In ultra dense networks (UDNs), base stations (BSs) with mobile edge computing (MEC) function can provide low latency and powerful computation to energy and computation constrained mobile users. Meanwhile, existing wireless access-oriented mobility management (MM) schemes are not suitable for high mobility scenario in UDNs. In this paper, a novel dynamic programming based MM (DPMM) scheme is proposed to optimize delay performance considering both wireless transmission and task computation under an energy consumption constraint. Based on markov decision process (MDP) and dynamic programming (DP), DPMM utilizes statistic system information to get a stationary optimal policy and can work in an offline fashion. Cooperative transmission is considered to enhance uplink data transmission rate. Simulations show that the proposed scheme can achieve close-to-optimal delay performance while consume less energy. Moreover, the number of handover is effectively reduced so that quality of service (QoS) is improved.
Authors: Ziyue Zhang (School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China), Jie Gong (School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China), Xiang Chen (School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Low-Latency Transmission and Caching of High Definition Map at a Crossroad

High definition (HD) map attracts more and more attention of researchers and map operators in recent years and has become an indispensable part for autono-mous or assistant driving. Different from existing navigation map, HD map has the features of high precision, large-volume data and real-time update. Therefore, the real-time HD map transmission to the vehicles becomes one main challenge in vehicular networks. This paper considers the scenario that a RSU at the crossroad caches and transmits HD maps to its covered vehicles in four directions. To re-duce the average delay of HD map delivery, the transmission power allocation for vehicles and the cache allocation for HD maps of different road segments are op-timized by leveraging the traffic density and vehicle positions. Simulation results indicate that the proposed scheme has lower latency than that of equal power allo-cation scheme based on real traffic data.
Authors: Yue Gu (Beijing University of Posts and Telecommunications), Jie Liu (Beijing University of Posts and Telecommunications), Long Zhao (Beijing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30

Session 4 13:30 - 14:30

Xiangshan Hall (4th Floor)
13:30 - 13:30
Maximum Ergodic Capacity of Intelligent Reflecting Surface Assisted MIMO Wireless Communication System

Intelligent reflecting surface (IRS) is currently adopted by massive multiple-input multiple-output (MIMO) systems as a new expansion scheme. It effectively copes with the increasing cost and energy consumption. In this paper, we concentrate on an IRS-assisted MIMO system, in which the base station, IRS and user are all equipped with multiple antennas. We first give the upper bound of the ergodic capacity of the system. Then we maximize this upper bound and obtain the sub-optimal phase shifts of IRS by applying semi-definite relax and Gaussian random methods. Numerical results shows the advantage of the proposed solution and the performance increase brought by multiple antennas.
Authors: Chang Guo (Shanghai Jiao Tong University), Zhufei Lu (Yichang Testing Institute of Technology Research), Zhe Guo (Shanghai Microwave Research Institute & CETC Key Laboratory of Data Link Technology), Feng Yang (Shanghai Jiao Tong University), Lianghui Ding (Shanghai Jiao Tong University),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
Trajectory Optimization for UAV Assisted Fog-RAN Network

In this paper, we study an unmanned aerial vehicle (UAV) assisted Fog-RAN network where an UAV perform as mobile remote radio head (RRH) to help base station forwards signals to the multiple users in the downlink transmissions, and a dedicated ground station (GS) acts as baseband unit (BBU) pool. To achieve fairness among users, we minimize the maximum transmission delay over all ground users in the downlink communication by jointly optimizing the user scheduling and the UAVs trajectory. As the formulated problem is the mixed integer nonconvex optimization problem, we propose an effective iterative algorithm to find efficient solutions by using Majorize Minimization (MM) algorithm. We also confirm the convergence of our proposed algorithm. Numerical results demonstrate that the proposed algorithm is able to significantly reduces transmission delay compared to circular trajectories and fixed base station solutions.
Authors: qi qin (Tongji University), Erwu Liu (Tongji University), Rui Wang (Tongji University),
Hide Authors & Abstract

Show Authors & Abstract
13:30 - 13:30
A Design of D2D-Clustering Algorithm for Group D2D Communication

Due to the characteristics of low latency and proximity discovery, D2D communication is considered to have an inherent advantage in supporting Internet-of-Vehicles (IoV) service. In this paper, considering that vehicular users can detect neighbor nodes in adjacent areas which are able to maintain high reliable communication with themselves, a novel design of D2D-Clustering algorithm is proposed in order to improve the QoS of users. The algorithm uses undirected graph to describe the neighborhood relationship between users. And the undirected graph is continuously simplified by multi-round traversal of vehicular users until user clustering is complete. Simulation results prove the validity of the proposed algorithm, pointing out that it helps reduce the energy consumption of the whole system.
Authors: Ruoqi Shi (Soochow University), Bicheng Wang (Soochow University), Fanwei Shi (Soochow University), Dongming Piao (Soochow University), Jianling Hu (Soochow University),
Hide Authors & Abstract

Show Authors & Abstract
Room #3

Session 1 09:00 - 10:00

Changyue Hall (3rd Floor)
09:00 - 09:00
Tier-based Directed Weighted Graph Coloring Algorithm for Device-to-Device Underlay Cellular Networks

Device-to-Device(D2D) communication has been recognized as a promising technology in 5G. Due to its short-range direct communication, D2D improves network capacity and spectral efficiency. However, interference management is more complex for D2D underlaying cellular networks compared with traditional cellular networks. In this paper, we study channel allocation in D2D undelaying cellular networks. A tier-based directed weighted graph coloring algorithm(TDWGCA) is proposed to solve cumulative interference problem. The proposed algorithm is composed of two stages. For the first stage, the tier-based directed weighted graph is constructed to formulate the interference relationship among users. For the second stage, the maximum potential interference based coloring algorithm(MPICA) is proposed to color the graph. Different from the hypergraph previously investigated in channel allocation, our proposed graph reduces the complexity of graph construction significantly. Simulation results show that the proposed algorithm could better eliminate cumulative interference compared with the hypergraph based algorithm and thus the system capacity is improved.
Authors: Yating Zhang (Beijing University of Post and Telecommunications), Tao Peng (Beijing University of Post and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
Iterative Phase Error Compensation Joint Channel Estimation in OFDM Systems

Orthogonal frequency division multiplexing (OFDM) system is very sensitive to the phase noise especially in high frequency since the orthogonality between sub-carriers is easily destroyed. It is very important to estimate and compensate the phase noise in the research of 5G systems. The influence of phase noise on OFDM systems is manifested in two aspects: introducing common phase error (CPE) and causing inter-carrier interference (ICI). In this paper, we propose a new joint channel and CPE estimation algorithm to obtain more accurate channel and CPE estimates through iterations. In each iteration, we update the channel and CPE estimates to make them closer to the true value. Besides, the performance improvement brought by the algorithm under the simplified system model is analyzed. Simulation results show that this algorithm has a great impact on improving the accuracy of channel and CPE estimation.
Authors: Qian Li (Beijing University of Posts & Telecommunications), Hang Long (Beijing University of Posts & Telecommunications), Mingwei Tang (Beijing University of Posts & Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract
09:00 - 09:00
A Practical Low Latency System for Cloud-based VR Applications

With the development of multimedia technologies, VR services have quickly gained popularity at an accelerating speed. To reduce the high cost of purchasing high-performance VR terminals for end users and to enhance the user experience, recently, the concept of cloud-based VR was proposed which brings the cloud computing technologies to VR services. On-cloud GPU clusters and multi-core servers are expected to be used for simplifying VR terminals at the users' side. This idea, however, arises several challenges in deploying such cloud-based VR system for practical applications, among which the cloud-to-end latency is mainly concerned. In this paper, we designed a practical solution for bearing cloud-based VR applications. We aim at reducing the cloud-to-end latency to improve the experience of end users. In our system, a frame splitting technique was proposed to fulfill the goal. Specially designed algorithms including reference frame determination and rate control strategies were also included to limit the computational complexity and improve the coding efficiency while obtaining promising user experience. Experimental results showed that the proposed system can significantly reduce the cloud-to-end latency.
Authors: Shuangfei Tian (State Key Laboratory of ISN, Xidian University, Xi’an, China), Mingyi Yang (State Key Laboratory of ISN, Xidian University, Xi’an, China), Wei Zhang (State Key Laboratory of ISN, Xidian University, Xi’an, China),
Hide Authors & Abstract

Show Authors & Abstract

Session 2 10:00 - 11:00

Changyue Hall (3rd Floor)
10:00 - 10:00
A Novel Indoor Positioning Algorithm Based on IMU

Although the Global Positioning System (GPS) can provide more accurate outdoor positioning services, it cannot detect the signals in indoor environments. Therefore, indoor positioning service has gradually been paid more attention. Most researchers currently use a nine-axis inertial sensor for indoor positioning. However, when the object is moving fast and frequently, it is obvious that using nine-axis inertial sensor has a large amount of computation. In addition, Kalman filtering algorithm is always cumbersome when data fusion is carried out for inertial sensors. The use of zero-velocity update algorithm (ZVU) to improve double integral can reduce the cumulative error, but the degree is far from enough. This paper mainly completes the following works: Firstly, the six-axis inertial sensor is used for indoor positioning. Then the digital motion processor is used instead of Kalman filter for attitude solution. Lastly, ZVU is optimized. Specifically, in the six-axis inertial sensor, the three-axis acceleration is used to measure the force of the object, and the three-axis gyroscope is used to detect the current posture of the object. In addition, the digital motion processor is used instead of the Kalman filter for the attitude solution, which avoids cumbersome filtering and data fusion. Finally, we optimize the ZVU so that the cumulative error is reduced again. The experimental results show that the algorithm has certain feasibility and practical application value.
Authors: Hui Wang (Zhejiang Normal University), Bi He (Zhejiang Normal University), Minshuo Li (Zhejiang Normal University), Kozyrev Yury (Zhejiang Normal University), Xu Shi (Zhejiang Normal University),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
Service Delay Minimization-based Joint Clustering and Content Placement Algorithm for Cellular D2D Communication Systems

Service Delay Minimization-based Joint Clustering and Content Placement Algorithm for Cellular D2D Communication Systems The rapidly increasing content fetching requirements pose challenges to the transmission performance of traditional cellular system. Due to the limited transmission performance of cellular links and the caching capabilities of the base stations (BSs), it is highly difficult to achieve the quality of service (QoS) requirements of multi-user content requests. In this paper, a joint user association and content placement algorithm is proposed for cellular device-to-device (D2D) communication network. Assuming that multiple users located in a specific area may have content requests for the same content, a clustering and content placement mechanism is presented in order to achieve efficient content acquisition. A joint clustering and content placement optimization model is formulated to minimize total user service delay, which can be solved by Lagrange partial relaxation, iterative algorithm and Kuhn-Munkres algorithm, and the joint clustering and content placement strategies can be obtained. Finally, the effectiveness of the proposed algorithm is verified by MATLAB simulation.
Authors: Rong Chai (CQUPT),
Hide Authors & Abstract

Show Authors & Abstract
10:00 - 10:00
T-HuDe: Through-The-Wall Human Detection with WiFi Devices

With the rapid development of emerging smart homes applications, the home security systems based on passive detection without carrying any devices has been increasing attention in recent years. Through-The-Wall (TTW) detection is a great challenge since through-the-wall signal can be severely attenuated, and some of the existing TTW-based detection techniques require special equipment or have strict restrictions on placement of devices. Due to the near-ubiquitous wireless coverage, WiFi based passively human detection technique becomes a good solution. In this paper, we propose a robust scheme for device-free Through-the-wall Human Detection (T-HuDe) in TTW with Channel State Information (CSI), which can provide more fine-grained movement information. Especially, T-HuDe utilizes motion information on WiFi signal and uses statistical information of motion characteristics as parameters. To evaluate T-HuDe performance, we prototype it in different environments with commodity devices, and the test results show that human activity detection rate and human absence detection rate of T-HuDe are both above 93% in most detection areas.
Authors: Wei Zeng (Chongqing University of Posts and Telecommunications), Zengshan Tian (Chongqing University of Posts and Telecommunications), Yue Jin (Chongqing University of Posts and Telecommunications), Xi Chen (Chongqing University of Posts and Telecommunications),
Hide Authors & Abstract

Show Authors & Abstract

Coffee break 11:00 - 11:15

Session 3 11:15 - 12:15

Changyue Hall (3rd Floor)
11:15 - 11:15
Deep Reinforcement Learning Based Computation Offloading for Mobility-Aware Edge Computing

Mobile Edge Computing (MEC) has become the most likely network architecture to solve the problems of mobile devices in terms of resource storage, computing performance and energy efficiency. In this paper, we first model the MEC system with the exploitation of mobility prediction. Considering the user's mobility, the deadline constraint and the limited resources in MEC servers, we propose a deep reinforcement learning approach named deep deterministic policy gradient (DDPG) to learn the power allocation policies for MEC servers users. Then, the aim of the policy is to minimize the overall cost of the MEC system. Finally, simulation results are illustrated that our proposed algorithm achieves performance gains.
Authors: Minyan Shi (Tongji University), Rui Wang (Tongji University), Erwu Liu (Tongji University), Zhixin Xu (Tongji University), Longwei Wang (University of Texas at Arlington),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Priority EDF Scheduling Scheme for MANETs

Analytical EDF Priority schedulers are not common in Mobile Ad-hoc Networks (MANETs). Some researchers like Abhaya et al have proposed a classical preemptive Earliest Deadline First (EDF) scheduler. The goal of this EDF scheduler was to favor higher priority packets thereby reducing their waiting times. Accordingly, favoring higher priority queues end up increasing the waiting times of lower priority queues. We improve Abhaya’s approach and adopt it to the MANETs environment. We numerically study the performance of the Adopted and Improved Adopted Abhaya Earliest Deadline First (IEDF) models for different packet queues. Our analytical results show that the IEDF model shortens the waiting times of packets of the different queues at various system loads in comparison to the Adopted Abhaya EDF model.
Authors: Abel Mukakanya Muwumba (University of Dar es Salaam), Godfrey Justo (University of Dar es Salaam), Libe Massawe (University of Dar es Salaam), John Ngubiri (Makerere University),
Hide Authors & Abstract

Show Authors & Abstract
11:15 - 11:15
Joint Collaborative Task Offloading for Cost-efficient Applications in Edge Computing

Edge computing is a new network model providing low-latency service with low bandwidth cost for the users by nearby edge servers. Due to the limited computational capacity of edge servers and devices, some edge servers need to offload some tasks to other servers in the edge network. Although offloading task to other edge servers may improve the service quality, the offloading process will be charged by the operator. In this paper, the goal is to determine the task offloading decisions of all the edge servers in the network. A model is designed with different types of cost in edge computing, where the overall cost of the system reflects the performance of the network. We formulate a cost minimization problem which is NP-hard. To solve the NP-hard problem, we propose a Joint Collaborative Task Offloading algorithm by adopting the optimization process in nearby edge servers. In our algorithm, an edge server can only offload its tasks to other edge servers within a neighborhood range. Based on the real-world data set, an adequate range is determined for the edge computing network. In cases of different density of tasks, the evaluations demonstrate that our algorithm has a good performance in term of overall cost, which outperforms an algorithm without considering the influence of neighborhood range.
Authors: Chaochen Ma (SJTU ParisTech Elite Institute of Technology, Shanghai Jiao Tong University), Zhida Qin (Department of Electronics Engineering, Shanghai Jiao Tong University), Xiaoying Gan (Department of Electronics Engineering, Shanghai Jiao Tong University), Luoyi Fu (Department of Electronics Engineering, Shanghai Jiao Tong University),
Hide Authors & Abstract

Show Authors & Abstract

Lunch 12:15 - 13:30