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	1. Research on Activity-based Device-Free Human Identification Approach
	YANG Yu,JIANG Ting,DING Xue,ZHONG Yi
	Electrics, Communication and Autocontrol Technology 31 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (538K B)

	Abstract:In recent years, with the development of device-free sensing (DFS), researchers have applied it to the field of identity recognition. By taking advantage of the unique influence that different people have on surrounding wireless signals, the technology is able to identify people in a contactless way. Some progress has been made in identification by analyzing the gait information in the received wireless signals, but it needs to provide enough space for walking, which limits its application scenarios to some extent. In order to solve this problem, this paper proposes WAID, a recognition system based on human activities. Through analyzing the unique influence of different people doing the same activity on the channel state information (CSI) of WiFi signal, the identity information of people can be extracted from it. Thus, identification can be achieved by performing activities in fixed locations where there are no area requirements. The experimental results show that in the case of 2 to 6 people, the average recognition accuracy of WAID is 94.3% to 88%, and the average accuracy under six positions is 84.8%.
	TO cite this article:YANG Yu,JIANG Ting,DING Xue, et al. Research on Activity-based Device-Free Human Identification Approach[OL].[31 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754417


	2. Edge Offloading Strategy for Mobile Devices in Intelligent Factories Based on Energy Consumption and Delay
	XIAO Ye,ZHOU Xiaoming,LI Zhao,ZHAO Chenglin,XU Fangmin
	Electrics, Communication and Autocontrol Technology 29 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (1096K B)

	Abstract:To cope with the challenge of successful edge offloading brought by the mobility of mobile devices in intelligent factories, this paper studies the optimization problem of the edge offloading strategy of mobile devices based on mobility. Considering the decision task flow executed by priority, the unique offloading method of a single task, the communication range of the edge server, and the delay constraint of the offloading of a single task, appropriate computing resources are selected according to the real-time location of the mobile device to offload the computing task. Based on the edge computing architecture of an intelligent factory, this paper puts forward five different computation offloading methods. From a global perspective, the energy consumption and delay of tasks offloading in local, edge, cloud center, local-edge collaboration, and local-edge-cloud collaboration are considered. In this paper, the algorithm based on genetic algorithm and particle swarm optimization is used to design the optimal decision task flow offloading strategy which can obtain the minimum energy consumption and delay. Simulation results show that the proposed algorithm can reduce the computation offloading energy consumption and delay of mobile devices.
	TO cite this article:XIAO Ye,ZHOU Xiaoming,LI Zhao, et al. Edge Offloading Strategy for Mobile Devices in Intelligent Factories Based on Energy Consumption and Delay[OL].[29 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754387


	3. An Applicable Scheme Employing Bispectrum and Convolutional Neural Network for Individual RF Fingerprint Identification
	ZHANG Yi-Ru,PAN Yu-Wen,YANG Yuan-Wang,WANG Bing-Cheng,WANG Bing-Cheng
	Electrics, Communication and Autocontrol Technology 23 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (1003K B)

	Abstract:In the background of artificial intelligence (AI) being widely applied, radio frequency (RF) fingerprint identification employing AI has become a trend. This paper mainly focuses on ways to process and identify RF signal transmitters. Contrapose to traditional RF fingerprint feature extracting and identifying methods, a method for modeling and extracting the RF signals features using integral bispectrum firstly was raised. Afterwards, A convolutional neural network has been proposed for classification of the RF individual transmitters. For verification, several mobile phones (with same or different type/brand) signals were processed by the above methods. The experiments results show that the proposed methods make up the weaknesses in accuracy and efficiency of previous used GBDT, XGBoost, and stacking algorithms. Moreover, the signal model derived by the proposed methods can describe individual signal transmitter with same type and brand, which is superior to signal model mentioned in references and has great significance in individual RF fingerprint identification.
	TO cite this article:ZHANG Yi-Ru,PAN Yu-Wen,YANG Yuan-Wang, et al. An Applicable Scheme Employing Bispectrum and Convolutional Neural Network for Individual RF Fingerprint Identification[OL].[23 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754163


	4. Growth of Vertically Stacked Two-Dimensional Materials: An Analytical vdW-BCF Model
	Xinshuang Xiang,Han Ye
	Electrics, Communication and Autocontrol Technology 16 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (1128K B)

	Abstract:The mechanism of spontaneous vertical versus in-plane lateral growth of two-dimensional (2D) materials is of great importance to fabricate novel 2D hetero- and homostructures. In this paper, we build a vdW-BCF growth model for vertically stacked 2D materials based on diffusion equations with boundary conditions from thermodynamic equilibrium and mass conservation. General solutions are analytically obtained for bilayer 2D materials (initial Layer1 and subsequent Layer2), taking adsorption and desorption into consideration. As the increase of Layer1 size, the Layer2 growth velocity decreases first and then increases due to the flux adsorption on the Layer1. Two critical sizes of Layer1 may exist for Layer2 to grow. Meanwhile, growth of Layer2 becomes unlimited if Layer2 size reaches a critical value. Moreover, the model can describe the size evolution as the growth process and we demonstrate that initial sizes plays a crucial role in determining the final structure.
	TO cite this article:Xinshuang Xiang,Han Ye. Growth of Vertically Stacked Two-Dimensional Materials: An Analytical vdW-BCF Model[OL].[16 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754168


	5. First-principle Study on Transport Properties of 2D Janus NbSeTe-MoSeTe-NbSeTe Lateral Heterostructure
	ZHENG Yanan,YE Han
	Electrics, Communication and Autocontrol Technology 11 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (706K B)

	Abstract:Two dimensional transition metal chalcogenides have important application prospects in optoelectronic devices, energy storage, catalysis and other fields due to their excellent properties. The research on this material covers its electronic properties, optical properties and so on, but the related research on transport properties is less. The electronic properties and applications of materials largely depend on their crystal structures. In this project, the first principles density functional theory and non-equilibrium Green\'s function are used to calculate the quantum transport of NbSeTe- MoSeTe- NbSeTe transport structure, and we study its electronic transport properties. By applying bias voltage to the electrode, the difference of transmission coefficient under different bias voltage and the relationship between current and bias voltage are discussed. By the means of analyzing the transmission spectrum of the non-equilibrium state of the device, we can understand the quantum transport properties of non-equilibrium state. When the bias voltage is less than 60mV, the transmission coefficient spectrum has no obvious change; while in 80mV or 100mV, it becomes larger having a positive effect on the current.
	TO cite this article:ZHENG Yanan,YE Han. First-principle Study on Transport Properties of 2D Janus NbSeTe-MoSeTe-NbSeTe Lateral Heterostructure[OL].[11 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754044


	6. High performance filtering and sensing structure based on coupled T-shaped resonator
	SUN Zhuoyue,ZHAO Tonggang,Wang Yusen
	Electrics, Communication and Autocontrol Technology 09 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (616K B)

	Abstract:This paper introduces a T-shaped resonator structure which is cross connected by double rectangles and coupled with waveguide. By using COMSOL simulation software based on finite element method, the physical characteristics of the structure are analyzed. The simulation results show that the transmission spectrum of the structure has one Fano peak and one Lorentz peak. Next, the influence of structural parameters on the transmission peak is studied. According to the research results, it can be found that the FR and LR peaks of the structure have excellent band-pass filtering effect. In addition, a new Fano resonance peak is excited by breaking the symmetry of the structure. The FOM value of the FR resonance peak is 210000, it means that the sensing performance of this structure is better than most sensors, which can be used as a high-performance refractive index sensor.
	TO cite this article:SUN Zhuoyue,ZHAO Tonggang,Wang Yusen. High performance filtering and sensing structure based on coupled T-shaped resonator[OL].[ 9 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754011


	7. Trajectory Design for Multi-UAV Aided Communication with Actor-critic-based Reinforcement Learning
	CHEN Ze-Chao,GUO Yi-Jun
	Electrics, Communication and Autocontrol Technology 01 March 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (695K B)

	Abstract:In this paper, the trajectory design problem is investigated in wireless communications aided by multiple unmanned aerial vehicles (UAVs), and a multi-UAV trajectory design method called multi-agent twin delayed deep deterministic policy gradient (MA-TD3) is proposed which is able to design continuous trajectories without pre-knowledge of global information such as user locations and channel conditions, through integrating the multi-agent deep deterministic policy gradient (MADDPG) algorithm and twin delayed deep deterministic policy gradient (TD3) algorithm based on actor-critic reinforcement learning (RL) framework. In particular, the multi-UAV trajectory design problem is firstly formulated as a stochastic game (SG) to maximize the completion rate of the transmission tasks. Then, the MA-TD3 method is proposed which is based on the actor-critic RL framework and the learned trajectory is obtained successively. Numerical results show that compared to traditional single agent RL methods, the proposed MA-TD3 method achieves higher completion rate of the transmission tasks by enabling cooperation between multiple UAVs through centralized training and distributed execution.
	TO cite this article:CHEN Ze-Chao,GUO Yi-Jun. Trajectory Design for Multi-UAV Aided Communication with Actor-critic-based Reinforcement Learning[OL].[ 1 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4753773


	8. Resource Allocation for UAV-aided Communication in High-Speed Railway Systems: A Multi-Agent Reinforcement Learning Approach
	Zhou Lanlan,Yu Jianguo
	Electrics, Communication and Autocontrol Technology 26 February 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (579K B)

	Abstract:The past decades have witnessed the rapid developments of high-speed railways (HSRs) communications. To provide seamless communication services between high-speed trains, both mobile edge computing (MEC) servers and UAVs are integrated into HSRs to provide on-demand resource access. However, the sensitive delay requirements of high-speed services pose significant challenges to the resource allocation in HSRs. This paper will formulate the UAV-aided resource allocation in high-speed railways (HSRs) as a distributed optimization problem to optimize the resource utilization while minimizing the path blocking probability. To address this problem, a multi-agent deep deterministic policy gradient (multi-agent DDPG) approach is proposed. The MEC servers are taken as the agents to make resource allocation decisions in the training phase. The simulation shows demonstrate that multi-agent DDPG outperforms the traditional single-agent method. The proposed multi-agent DDPG-based resource allocation algorithm can achieve satisfactory performance.?????

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