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Intelligent reflecting surface-assisted federated learning in multi-platoon collaborative networks

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Digital Communications and Networks 2023年第3期9卷 628-637页

作者： Xiaoting Ma Junhui Zhao Jieyu Liao Ziyang Zhang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China China Telecom Corporation Limited Research Institute Beijing102209China School of Information Engineering East China Jiaotong UniversityNanchang330013China

Inspired by mobile edge computing(MEC),edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data center.However,the quality of model training will be affected by the limited communication and computing resources of network edge.In this paper,how to improve the training performance of a federated learning system aided by Intelligent reflecting surface(IRS)over vehicle platooning networks is studied,where multiple platoons train a shared federated learning model.Multi-platoon cooperation can alleviate the pressure of data processing caused by the limited computing resources of single platoon.Meanwhile,IRS can enhance the inter-platoon communication in a cost-effective and energy-efficient manner.Firstly,the federated learning optimization problem of maximizing the learning accuracy is formulated by jointing platoon scheduling,bandwidth allocation and phase shifts at the IRS to maximize the number of scheduled platoon.Specif-ically,in the proposed learning architecture each platoon updates the learning model with its own data and uploads it to the global model through IRS-based wireless networks.Then,a method based on sequential optimization algorithm(SOA)and a group-based optimization method are analyzed for single IRS aided and large-scale IRS aided commu-nication,respectively.Finally,a platoon scheduling scheme is designed based on the communication reliability and computing reliability of platoons.Simulation results demonstrate that large-scale IRS assisted communication can effectively improve the reliability of multi-user communication networks.The scheduling scheme based on learning reliability balances the communication performance and computing performance of platoons.

关键词： Vehicle platooning networks Federated learning Intelligent reflecting surface Platoon scheduling Resource allocation

Intelligent reflecting surface assisted untrusted NOMA transmissions: a secrecy perspective

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Science China(Information Sciences) 2023年第9期66卷 226-238页

作者： Dawei WANG Xuanrui LI Yixin HE Fuhui ZHOU Qihui WU School of Electronics and Information Northwestern Polytechnical University Research & Development Institute of Northwestern Polytechnical University in Shenzhen College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing University of Aeronautics and Astronautics

In this paper, we investigate the Intelligent reflecting surface(IRS) assisted secure transmissions for the untrusted non-orthogonal multiple access(NOMA) network threatened by an external eavesdropper,where the near user and two untrusted far users receive the privacy information from the transmitter assisted by the IRS’s passive reflection. To protect the privacy information against internal and external eavesdropping, we first provide a comprehensive analysis of the secrecy rates, which can offer suitable methods for separately handling the internal and external secrecy performance. Following the above results, we formulate a secrecy rate maximization problem by optimizing the transmission power allocation and phase shifts. To achieve this goal, we decouple the non-convex optimization problem into the external security problem and the internal security problem. Then, we propose a heuristic simulated annealing algorithm to iteratively solve the above problems, where the semi-definite relaxation(SDR) technique, the singular value decomposition(SVD) technique, and the Lagrange multiplier method are utilized to relax the problems and optimize the power allocation and phase shifts. Finally, numerical results show that the proposed scheme can improve the secrecy rate compared with the existing IRS-aided secure NOMA transmission schemes.

关键词： Intelligent reflecting surface non-orthogonal multiple access security untrusted users

Delay Minimization for Intelligent reflecting surface Assisted Federated Learning

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China Communications 2022年第4期19卷 216-229页

作者： Ning Huang Tianshun Wang Yuan Wu Suzhi Bi Liping Qian Bin Lin State Key Laboratory of Internet of Things for Smart City University of MacaoMacaoChina Department of Computer and Information Science University of MacaoMacaoChina Zhuhai-UM Science and Technology Research Institute Zhuhai 519031China College of Electronics and Information Engineering Shenzhen UniversityShenzhen 518060China College of Information Engineering Zhejiang University of TechnologyHangzhou 310014China Department of Communication Engineering Dalian Maritime UniversityDalian 116026China

Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread attention.However, the process of FL involves frequent communications between the server and mobile devices,which incurs a long latency. Intelligent reflecting surface(IRS) provides a promising technology to address this issue, thanks to its capacity to reconfigure the wireless propagation environment. In this paper, we exploit the advantage of IRS to reduce the latency of FL. Specifically, we formulate a latency minimization problem for the IRS assisted FL system, by optimizing the communication resource allocations including the devices’ transmit-powers, the uploading time, the downloading time, the multi-user decomposition matrix and the phase shift matrix of IRS. To solve this non-convex problem, we propose an efficient algorithm which is based on the Block Coordinate Descent(BCD) and the penalty difference of convex(DC) algorithm to compute the solution. Numerical results are provided to validate the efficiency of our proposed algorithm and demonstrate the benefit of deploying IRS for reducing the latency of FL. In particular, the results show that our algorithm can outperform the baseline of Majorization-Minimization(MM) algorithm with the fixed transmit-power by up to 30%.

关键词： federated learning Intelligent reflecting surface latency minimization

Secure Multigroup Multicast Communication Systems via Intelligent reflecting surface

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China Communications 2021年第3期18卷 39-51页

作者： Weiping Shi Jiayu Li Guiyang Xia Yuntian Wang Xiaobo Zhou Yonghui Zhang Feng Shu School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China School of Information and Communication Engineering Hainan UniversityHaikou 570228China School of Physics and Electronic Engineering Fuyang Normal UniversityFuyang 236037China School of Electronic and Electrical Engineering Shangqiu Normal UniversityShangqiu 476000China

This paper considers a secure multigroup multicast multiple-input single-output(MISO)communication system aided by an Intelligent reflecting surface(IRS).Specifically,we aim to minimize the transmit power at Alice via jointly optimizing the transmit beamformer,artificial noise(AN)vector and phase shifts at the IRS subject to the secrecy rate constraints as well as the unit modulus constraints of IRS phase shifts.To tackle the optimization problem,we first transform it into a semidefinite relaxation(SDR)problem,and then alternately update the transmit beamformer and AN matrix as well as the phase shifts at the IRS.In order to reduce the high computational complexity,we further propose a low-complexity algorithm based on second-order cone programming(SOCP).We decouple the optimization problem into two sub-problems and optimize the transmit beamformer,AN vector and the phase shifts alternately by solving two corresponding SOCP subproblem.Simulation results show that the proposed SDR and SOCP schemes require half or less transmit power than the scheme without IRS,which demonstrates the advantages of introducing IRS and the effectiveness of the proposed methods.

关键词： Intelligent reflecting surface multigroup multicast transmit beamformer secrecy rate phase shifts

Passive Beamforming Design for Intelligent reflecting surface Assisted MIMO Systems

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China Communications 2021年第3期18卷 18-28页

作者： Chenghao Feng Wenqian Shen Xinyu Gao Jianping An School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China Shaanxi Key Laboratory of Information Communication Network and Security Xian University of Posts and TelecommunicationsXianShaanxi 710121China Huawei Technologies Co.Ltd. Beijing 100085China

Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.

关键词： Intelligent reflecting surface MIMO systems passive beamforming

reflecting surface-Aided Device-to-Device Communications System

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Journal of Communications and Information Networks 2020年第4期5卷 403-410页

作者： Chiya Zhang Wenyu Chen Chunlong He Xingquan Li School of Electronic and Information Engineering Harbin Institute of TechnologyShenzhen 518055China.Peng Cheng Laboratory(PCL)Shenzhen 5180523China Guangdong Key Laboratory of intelligent Information Processing Shenzhen UniversityShenzhen518060China

Intelligent reflecting surface(IRS)is a promising technology for its capability of reflecting the incident signal towards the desired user.IRS can improve the efficiency of wireless communication systems.This paper introduces IRS into a device-to-device(D2D)communications system to improve the throughput of the D2D network.We adopt the block coordinate descent al-gorithm and semidefinite relaxation technique to optimize the beamforming vector,power allocation and phase shift matrix.Simulation results demonstrate that IRS is able to enhance the throughput of the D2D communications system,and the proposed algorithm significantly outper-forms the other benchmark algorithms.

关键词： Intelligent reflecting surface device-to-device communications block coordinate descent

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent reflecting surface Enhanced LEO Satellite Communication

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China Communications 2024年第2期21卷 227-244页

作者： Meng Meng Bo Hu Shanzhi Chen Jianyin Zhang State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Lab of Wireless Mobile Communication China Academy of Telecommunication TechnologyBeijing 100191China Research Institute of China Mobile Beijing 100053China

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

关键词： convex optimization Intelligent reflecting surface LEO satellite communication OFDM

Performance Analysis of Intelligent reflecting surface Assisted Wireless Communication System

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 775-787页

作者： Weiqiang Tan Quanquan Zhou Weijie Tan Longcheng Yang Chunguo Li School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510006China Key Laboratory of Advanced Manufacturing Technology Ministry of EducationGuizhou UniversityGuiyang550025China Sichuan Key Laboratory of Indoor Space Layout Optimization and Security Guarantee Chengdu Normal UniversityChengdu611130China School of Information Science and Engineering Southeast UniversityNanjing210096China

In this paper,we investigate the end-to-end performance of Intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.

关键词： Massive MIMO Intelligent reflecting surface uniform planar array achievable ergodic rate

Robust beamforming for IRS-aided SWIPT in cognitive radio networks

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Digital Communications and Networks 2023年第3期9卷 645-654页

作者： Zining Wang Min Lin Shupei Huang Ming Cheng Wei-Ping Zhu Yan Guo College of Telecommunications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical and Computer Engineering Concordia UniversityMontrealQCH3G 1M8Canada

Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer(SWIPT)in a cognitive radio network(CRN).Here,the base station(BS)utilizes spectrum assigned to the primary users(PUs)to simultaneously serve multiple energy receivers(ERs)and information receivers(IRs)through IRS-aided multicast technology.In particular,by assuming that only the imperfect channel state information(CSI)is available,we first formulate a constrained problem to maximize the minimal achievable rate of IRs,while satisfying the harvesting energy threshold of ERs,the quality-of-service requirement of IRs,the interference threshold of PUs and transmit power budget of BS.To address the non-convex problem,we then adopt triangle inequality to deal with the channel uncertainty,and propose a low-complexity algorithm combining alternating direction method of multipliers(ADMM)with alternating optimi-zation(AO)to jointly optimize the active and passive beamformers for the BS and IRS,respectively.Finally,our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.

关键词： Cognitive radio networks Intelligent reflecting surface Simultaneous wireless information and power transfer Robust beamforming