Multi-IRS Assisted Wireless-Powered Mobile Edge Computing for Internet of Things

被引:14
作者
Chen, Pengcheng [1 ]
Lyu, Bin [1 ]
Liu, Yan [1 ]
Guo, Haiyan [1 ]
Yang, Zhen [1 ]
机构
[1] Nanjing Univ Posts & Telecommun, Key Lab, Minist Educ Broadband Wireless Commun & Sensor Net, Nanjing 210003, Peoples R China
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2023年 / 7卷 / 01期
基金
中国国家自然科学基金;
关键词
Array signal processing; Servers; Wireless communication; Task analysis; Internet of Things; Wireless power transfer; Multiuser detection; Mobile edge computing; intelligent reflecting surface; wireless power transfer; energy beamforming; multiple-user detection; INTELLIGENT REFLECTING SURFACE; COMPUTATION RATE MAXIMIZATION; RESOURCE-ALLOCATION; BEAMFORMING OPTIMIZATION; ENERGY EFFICIENCY; SWIPT; INFORMATION; NETWORKS; NOMA;
D O I
10.1109/TGCN.2022.3205030
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper proposes a multiple intelligent reflecting surfaces (IRSs) assisted wireless-powered mobile edge computing (MEC) system, where the IRSs are deployed to assist both the downlink wireless power transfer (WPT) from the multi-antenna hybrid access point (HAP) to the wireless devices (WDs) and the uplink computation offloading from the WDs to the MEC server. To further improve the system performance, the energy beamforming and multiple-user detection (MUD) technologies are exploited. We consider both partial and binary offloading schemes and formulate the sum computation rate (SCR) maximization problems for them, respectively. To tackle the non-convexity of each problem, we propose an efficient alternating optimization (AO) method. Specifically, the Lagrange duality method is used to optimize the energy beamforming vector and the MUD matrix at the HAP, and the CPU frequencies and transmit power of the WDs. Then, we optimize the discrete phase shifts via the successive convex appropriation (SCA) method, the rank-one equivalents, and rounding method. Finally, the optimal time scheduling can be obtained via the one-dimensional search method. In addition, we propose a greedy algorithm with low complexity to optimize the computing modes for the binary offloading scheme. Numerical results show that our proposed schemes outperform the benchmarks.
引用
收藏
页码:130 / 144
页数:15
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