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Day 1 21/12/2019
Room #1

Opening of the Conference 09:00 - 09:20

By Prof. Wei Xiang

Keynote Lecture by Prof. Prof. Zhaocheng Wang 09:20 - 10:20

The Technology of AI-based Low-power Millimeter Wave Terminal

Coffee Break 10:20 - 10:50

Technical Session One 10:50 - 11:50

10:50 - 11:10
A Resource Allocation Scheme for 5G C-RAN Based on Improved Adaptive Genetic Algorithm

Cloud-Radio Access Networks (C-RAN) is a novel mobile network architecture where baseband resources are pooled, which is helpful for the operators to deal with the challenges caused by the non-uniform traffic and the fast growing user demands. The main idea of C-RAN is to divide the base stations into the baseband unit (BBU) and the remote radio head (RRH), and then centralize the BBUs to form a BBU pool. The BBU pool is virtualized and shared between the RRHs, improving statistical multiplexing gains by allocating baseband and radio resources dynamically. In this paper, aiming at the problem of resource dynamic allocation and optimization of 5G C-RAN, a resource allocation strategy based on improved adaptive genetic algorithm (IAGA) is proposed. The crossover rate and mutation rate of the genetic algorithm are optimized with the nonlinear adaptive adjustment of the crossover rate and the mutation rate. Simulation results show that the performance of the proposed resource allocation strategy is better than common frequency reuse algorithm and traditional genetic algorithm (GA).
Authors: Ma Xinyan (School of Information Science and Technology, University of Science and Technology of China, Hefei, P. R. China), Ma Yingteng (College of Electronic Science and Technology, National University of Defense Technology, Changsha, P. R. China), Ma Dongtang (College of Electronic Science and Technology, National University of Defense Technology, Changsha, P. R. China),
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11:10 - 11:30
A Comparison of Two Synchronization Algorithms for Burst-Mode MR-OFDM System in Smart Grid

This paper presents a comparison of the performance of two different synchronization algorithms for burst-mode MR-OFDM system in 802.15.4g for smart grid. The first algorithm does synchronization as traditional max search within a reasonable range which requires a large storage on the receiver implementation. The second algorithm is of real-time implementation property which doesn’t require large storage. Simulations show that the second one is of a very little performance loss since it uses a little shorter data length than the first one. (Note: the recommendation code is BJ118.)
Authors: Yahong Zhao, Xiaoke Tang (Beijing Smart-Chip Microelectronics Technology Co., Ltd.), Xu Zhao (Beijing Smart-Chip Microelectronics Technology Co., Ltd.), Yubing Zhang (Beijing Smart-Chip Microelectronics Technology Co., Ltd.),
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11:30 - 11:50
A Novel Adaptive Multiple-access Scheme for Wireless Chip Area Network in the Smart Grid System

The design and construction of the smart grid system in 5G super-dense network needs to be effectively integrated with the mobile communication technology. Wireless chip area network (WCAN), as an application of the smart grid, has promising research potential. Focusing on the issue of multi-user network communication, this paper proposes an adaptive time-hopping pulse position modulation (TH-PPM) multiple-access scheme that is applicable to WCAN. Combined with the specific applications of WCAN, the wireless channel characteristics of intra/inter-chip communication are investigated, the bit error rate (BER) performance of the TH–PPM multiple-access system is analyzed; then, based on the aforementioned results, an adaptive TH-PPM multiple-access distribution mechanism is proposed and an intelligent transmission mechanism is designed to appropriately select the monopulse signal-to-noise ratio of the intra/inter chip, BER, and transmission rate in WCAN. Finally, the performance is analyzed through simulation and is also compared with the fixed multiple-access technology. The results show that on the premise of ensuring wireless interconnection quality of service of the intra/inter chip, this scheme can allocate system rate and power resource properly, strengthen transmission performance, and address the limitations of fixed multiple-access technology. The findings presented in this paper provide a reference for multi-user multiple-access communication with large capacity. BJ103
Authors: Xin-Yue LUO (School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China), Hao GAO (School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China), Xue-Hua LI (School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China),
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Lunch 12:00 - 13:30

Faculty Cafeteria

Technical Session Two 14:30 - 15:30

14:30 - 14:50
Time -swithching Energy Harvesting Relay Optimizing Considering Decoding cost*

Energy harvesting (EH) from natural and man-made sources is of prime importance for enabling the Internet of Things (IoT) networks. Although, energy harvesting relays in a relay network, which form building blocks of an IoT network, have been considered in the literature, most of the studies do not account for the processing costs, such as the decoding cost in a decode-and-forward (DF) relay. However, it is known that the decoding cost amounts to a significant fraction of the circuit power required for receiving a codeword. Hence, in this work, we are motivated to consider an EH-DF relay with the decoding cost and maximize the average number of bits relayed by it with a time-switching architecture. To achieve this, we first propose a time-switching frame structure consisting of three phases: (i) an energy harvesting phase, (ii) a reception phase and, (iii) a transmission phase. We obtain optimal length of each of the above phases and communication rates that maximize the average number of bits relayed. We consider two EH scenarios, (a) when the radio frequency (RF) energy, to be harvested by the relay, is transmitted from a dedicated transmitter, and (ii) when the energy is harvested at the rely from the ambient environment. By exploiting the convexity of the optimization problem, we derive analytical optimum solutions under the above two scenarios and provide numerical simulations for verifying our theoretical analysis. Bj125
Authors: Chenxu Wang (Beijing Information and Science Technoloy University, Beijing 100190, China), Zhengwei Ni (Zhejiang Gongshang University, 310018 Zhejiang, China), Rajshekhar V Bhat (Indian Institute of Technology Dharwad, India), Yanxin Yao (Beijing Information and Science Technoloy University, Beijing 100190, China), Mehul Motani (National University of Singapore, Singapore),
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14:50 - 15:10
Enhanced LSTM Model for Short-Term Load Forecasting in Smart Grids

With the rapid development of smart grids, significant research has been devoted to the methodologies for short-term load forecasting (STLF) due to its significance in forecasting demand on electric power. In this paper an enhanced LSTM model is proposed to upgrade the state-of-the-art LSTM network by exploiting the long periodic information of load, which is missed by the standard LSTM model due to its constraint on input length. In order to distill in-formation from long load sequence and keep the input sequence short enough for LSTM, the long load sequence is reshaped into two-dimension matrix whose dimension accords to the periodicity of load. Accordingly, two LSTM networks are paralleled: one takes the rows as input to extract the temporal pat-tern of load in short time, while the other one takes the columns as input to dis-till the periodicity information. A multi-layer perception combines the two out-puts for more accurate load forecasting. This model can exploit more information from much longer load sequence with only linear growth in complexity, and the experiment results verify its considerable improvement in accuracy over the standard LSTM model.
Authors: Jianing Guo (Beijing University of Posts and Telecommunication, Beijing, China), Yuexing Peng (Beijing University of Posts and Telecommunication, Beijing, China), Qingguo Zhou (Lanzhou University, Lanzhou, China), Wei Xiang (James Cook University, Queensland, Australia),
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15:10 - 15:30
Colorization of Characters Based on the Generative Adversarial Network

With the development of economy, global demand for electricity is increasing, and the requirements for the stability of the power grid are correspondingly improved. The intelligence of the power grid is an inevitable choice for the research and development of power systems. Aiming at the security of the smart grid operating environment, this paper proposes a grayscale image coloring method based on generating anti-network, which is used for intelligent monitoring of network equipment at night, and realizes efficient monitoring of people and environment in different scenarios. Based on the original Generative Adversarial Network, the method uses the Residual Net improved network to improve the integrity of the generated image information, and adds the least squares loss to the generative network to narrow the distance between the sample and the decision boundary. Through the comparison experiments in the self-built CASIA-PlusColors high-quality character dataset, it is verified that the proposed method has better performance in colorization of different background images.
Authors: Changtong Liu (School of Information and Communication Engineering, Beijing Information Science and Technology University), Lin Cao (School of Information and Communication Engineering, Beijing Information Science and Technology University), KangNing Du (School of Information and Communication Engineering, Beijing Information Science and Technology University),
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Coffee Break 15:30 - 15:50

Technical Session Three 15:50 - 16:30

15:50 - 16:10
Multiple Time Blocks Energy Harvesting Relay Optimizing with Time-switching Structure and Decoding Cost

Energy harvesting (EH) is of prime importance for enabling the Internet of Things (IoT) networks. Although, energy harvesting relays have been considered in the literature, most of the studies do not account for the processing costs, such as the decoding cost in a decode-and-forward (DF) relay. However, it is known that the decoding cost amounts to a significant fraction of the circuit power required for receiving a code word. Hence, in this work, we are motivated to consider an EH-DF relay with the decoding cost and maximize the average number of bits relayed by it with a time-switching architecture. To achieve this, we first propose a time-switching frame structure consisting of three phases: (i) an energy harvesting phase, (ii) a reception phase and, (iii) a transmission phase. We obtain optimal length of each of the above phases and communication rates that maximize the average number of bits relayed. We consider the radio frequency (RF) energy to be harvested by the relay is from the dedicated transmitter and the multiple block case when energy is allowed from flow among the blocks, different from the single block case when energy is not allowed to flow among the blocks. By exploiting the convexity of the optimization problem, we derive analytical optimum solutions under the EH scenario. One of the optimal receiving rate for the relay is the same as in single block case. We also provide numerical simulations for verifying our theoretical analysis.
Authors: Meng Yang (Beijing Information Science and Technology University 100190, Beijing China), Yanxin Yao (Beijing Information Science and Technology University 100190, Beijing China), Zhengwei Ni (Zhejiang Gongshang University, 310018 Zhejiang, China), Rajshekhar V Bhat (Indian Institute of Technology Dharwad, India), Mehul Motani (NUS),
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16:10 - 16:30
Spectrum Sharing in Cognitive Radio Enabled Smart Grid: A Survey

Smart grid is viewed as the next generation electric power system to meet the demand of communication and power delivery in an intelligent manner. With large scale deployment of electric power systems, smart grid faces the challenge from large volume data and high spectrum needs. To realize effi-cient spectrum utilization in the fact of spectrum scarcity, cognitive radio (CR) is involved in smart grid and generates the cognitive radio enabled smart grid. Cognitive radio enabled smart grid coexists with primary network by employing CR technologies including spectrum sensing, sharing, access and so on. Spectrum sharing is an important CR technology which realizes network coexistence without harmful interference through radio resource al-location. In this paper, a comprehensive survey is provided to review the state-of-the-art researches on spectrum sharing in cognitive radio enabled smart grid. We identify the network architecture and communication tech-nology issues of cognitive radio enabled smart gird, and illustrate the inves-tigation of spectrum sharing in different radio resource dimensions to high-light the superiority in efficient spectrum utilization. (Recommendation Code: BJ128)
Authors: Shuo Chen (Beijing Information Science and Technology University, Beijing, China),
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Day 2 22/12/2019