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车联网中基于能量采集中继的分布式波束成形传输

  

  • 修回日期:2020-06-07 出版日期:2020-06-25 发布日期:2020-07-14

Distributed Beamforming for Energy-Harvesting Relaying in Vehicular Networks

Yuxiang Liang(),Bing Li(),Rongqing Zhang(),Hongze Li(),Shengjie Zhao()   

  1. School of Software Engineering, Tongji University,Shanghai 201804,China;School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
    School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
    School of Software Engineering, Tongji University,Shanghai 201804,China
    School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
    School of Software Engineering, Tongji University,Shanghai 201804,China
  • Revised:2020-06-07 Online:2020-06-25 Published:2020-07-14
  • About author:Yuxiang Liang is currently pursuing her B.S.degree with Tongji University, Shanghai, China. Her research interests include simultaneous wireless information and wireless transfer, energy harvesting relay networks,and distributed beamforming.|Bing Li received her B.S. degree from University of Electronics Science and Technology of China, Chengdu, China, in 2015. She is currently pursuing her Ph.D. degree with Tongji University, Shanghai,China.Her current research interests include UAV communications,wireless resource allocation,and relay communications.|Rongqing Zhang[corresponding author]received his B.S. and Ph.D. degrees (with honors) from Peking University,Beijing,China,in 2009 and 2014,respectively. From 2014 to 2018, he worked as a postdoctoral research fellow at Colorado State University,CO, USA.Since 2019,he has been an associate professor at Tongji University,Shanghai,China. He has authored and co-authored two books, two book chapters, and over 100 papers in refereed journals and conference proceedings. His current research interests include physical layer security, vehicular communications and networking, UAV communications, and autonomous driving.|Dr. Zhang was the recipient of the Academic Award for Excellent Doctoral Students,Ministry of Education of China,the co-recipient of the FirstClass Natural Science Award,Ministry of Education of China,and received the Best Paper Awards at IEEE ITST’12, ICC’16, GLOBECOM’18, and ICC’19. He was also awarded as International Presidential Fellow of Colorado State University in 2017.Currently,he is serving as an associate editor of IET Communications and Hindawi Complexity.|Hongze Li is currently pursuing his B.S.degree with Tongji University, Shanghai, China. His research interests include simultaneous wireless information and wireless transfer, channel modeling, and signal processing.|Shengjie Zhao received his B.S. degree in electrical engineering from University of Science and Technology of China,Hefei,China,in 1988,his M.S.degree in electrical and computer engineering from China Aerospace Institute, Beijing, China, in 1991, and his Ph.D. degree in electrical and computer engineering from Texas A＆M University, College Station, TX, USA,in 2004.He is currently the dean of the College of Software Engineering,a professor with the College of Software Engineering and the College of Electronics and Information Engineering,Tongji University,Shanghai,China.In previous postings,he has conducted research with Lucent Technologies,Whippany,NJ,USA,and China Aerospace Science and Industry Corporation,Beijing,China.His research interests include artificial intelligence,big data,wireless communications,image processing,and signal processing.He is a fellow of the Thousand Talents Program of China.
  • Supported by:
    National Key Research and Development Project under(2017YFE0119300);National Key Research and Development Project under(2019YFB2102300);National Natural Science Foundation of China under(61936014);National Natural Science Foundation of China under(61901302);Shanghai Aerospace Science and Technology (SAST) Innovation Fund under(SAST2019-091);Fundamental Research Funds for the Central Universities (China) under(22120190218)

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摘要：

近年来，电池容量和充电速度成为移动通信网络发展的重要约束。随着无线能量传输技术的发展，能量采集（Energy Harvesting，EH）中继已经成为5G绿色通信的一种有前景的解决方案。在本文中，我们研究了车联网中的EH中继，并采用分布式波束成形（Distributed Beamforming，DB）方案来提高EH中继传输的可靠性和传输容量。更具体地说，我们提出了一种基于功率分配（Power-Splitting，PS）因子联合优化的DB策略。对于放大–转发（Amplify-and-Forward，AF）中继，为了将优化问题转化为一个准凸优化问题，我们应用了半定松弛（Semidefinite Relaxation，SDR）方法，以便可以有效地获得全局最优解，同时还给出了只需要本地信道状态信息的具有分布最优PS因子的次优DB解。对于解码–转发（Decode-and-Forward，DF）中继，为了获得最优PS因子，我们在中继处预设了一定的信噪比阈值，可以有效降低由于传输链路不良而导致的系统误码率。仿真结果证明了我们在车联网中提出的基于DB的EH中继方案的有效性。

Abstract:

Abstract—Recently, battery capacity and charging speed have been the bottlenecks of mobile communication networks.Energy harvesting (EH) relaying has become a promising solution for green 5th generation mobile communication with the advancement of wireless power transfer technology.In this paper, we investigate EH relaying in vehicular networks and adopt distributed beamforming(DB)to enhance the reliability and capacity of EH relaying.To be more specific, we propose a DB solution based on the joint optimization of power-splitting (PS)factors.For amplify-and-forward relaying,to transform the optimization problem into a quasi-convex one, we apply the semidefinite relaxation(SDR)method so that we can effectively attain the global optimal solution,while the suboptimal DB solution with distributed optimal PS factor which only requires local channel state information is also proposed.For decode-and-forward relaying, to get the optimal PS factors, we set a signal-to-noise ratio threshold at the relays,which can reduce the system error rate caused by the poor transmission link.Simulation results demonstrate the efficiency of our proposed DB-based EH relaying scheme in vehicular networks.

车联网中基于能量采集中继的分布式波束成形传输

近年来，电池容量和充电速度成为移动通信网络发展的重要约束。随着无线能量传输技术的发展，能量采集（Energy Harvesting，EH）中继已经成为5G绿色通信的一种有前景的解决方案。在本文中，我们研究了车联网中的EH中继，并采用分布式波束成形（Distributed Beamforming，DB）方案来提高EH中继传输的可靠性和传输容量。更具体地说，我们提出了一种基于功率分配（Power-Splitting，PS）因子联合优化的DB策略。对于放大–转发（Amplify-and-Forward，AF）中继，为了将优化问题转化为一个准凸优化问题，我们应用了半定松弛（Semidefinite Relaxation，SDR）方法，以便可以有效地获得全局最优解，同时还给出了只需要本地信道状态信息的具有分布最优PS因子的次优DB解。对于解码–转发（Decode-and-Forward，DF）中继，为了获得最优PS因子，我们在中继处预设了一定的信噪比阈值，可以有效降低由于传输链路不良而导致的系统误码率。仿真结果证明了我们在车联网中提出的基于DB的EH中继方案的有效性。

Key words: vehicular networks, SWIPT, power splitting, distributed beamforming

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