Sum-Rate Maximization in IRS-Assisted Wireless Power Communication Networks
Sum-Rate Maximization in IRS-Assisted Wireless Power Communication Networks
复制标题
IRS 辅助无线充电通信网络中的总速率最大化
DOI：
10.1109/jiot.2021.3072987
复制
发表时间：
2021-04
影响因子：
10.6
通讯作者：
Jonathon A. Chambers
中科院分区：
文献类型：
--
作者：
Xingquan Li;Chiya Zhang;Chunlong He;Gaojie Chen;Jonathon A. Chambers
无线供电通信网络 (WPCN) 是一项有前途的技术，支持物联网 (IoT) 中的资源密集型设备。然而，它们的长距离传输效率非常有限。新出现的智能反射面（IRS）可以通过控制无源反射元件的相移来有效减轻传播引起的损伤。在本文中，我们将 IRS 集成到 WPCN 中以协助能量和信息传输。我们的目标是通过联合优化时间分配变量、功率发射基站（PTBS）的能量波束矩阵、信息接收基站的接收波束成形矩阵以及受时间分配约束的UL和下行链路（DL）IRS的相移以及PTBS的发射功率约束和单位模数约束，来最大化所有物联网设备的上行链路（UL）总速率。由于变量的高度耦合，该问题很难直接求解，导致优化问题既不呈线性也不呈凸形式。因此，我们使用块坐标下降法将该问题分解为三个子问题。在具有固定时间分配和DL变量的UL优化子问题中交替优化UL接收波束成形矩阵和相移。深度学习优化子问题通过所提出的逐次凸逼近算法来解决。仿真结果表明，集成 IRS 和 WPCN 的性能优于传统 WPCN。此外，结果表明 IRS 是保持物联网中能源效率和传输效率权衡的有效方法。
Wireless-powered communication networks (WPCNs) are a promising technology supporting resource-intensive devices in the Internet of Things (IoT). However, their transmission efficiency is very limited over long distances. The newly emerged intelligent reflecting surface (IRS) can effectively mitigate the propagation-induced impairment by controlling the phase shifts of passive reflection elements. In this article, we integrate IRS into WPCNs to assist both the energy and information transmission. We aim to maximize the uplink (UL) sum rate of all IoT devices by jointly optimizing the time allocation variable, energy beam matrix at the power transmitting base station (PTBS), receive beamforming matrix at the information receiving base station, and the phase shifts of the IRS both in the UL and downlink (DL) subject to time allocation constraint, together with transmit power constraint for the PTBS and unit modulus constraints. This problem is very difficult to solve directly due to the highly coupled variables, which results in the optimization problem taking neither linear nor convex form. Hence, we decouple this problem into three subproblems by using the block coordinate descent method. The UL receive beamforing matrix and phase shift are alternatively optimized in the UL optimization subproblem with fixed time allocation and the DL variables. The DL optimization subproblem is solved by the proposed successive convex approximation algorithm. Simulation results demonstrate that the performance of integrating IRS and WPCNs outperforms traditional WPCNs. Besides, the results show that IRS is an effective method to preserve the tradeoff of energy efficiency and transmission efficiency in the IoT.
登录
查看更多内容
大型智能表面/天线 (LISA)：使反射式无线电变得智能
DOI：
10.23919/jcin.2019.8917871
发表时间：
2019-06
期刊：
Journal of Communications and Information Networks
影响因子：
--
作者：
Ying-Chang Liang;Ruizhe Long;Qianqian Zhang;Jie Chen;Hei Victor Cheng;Huayan Guo
通讯作者：
Huayan Guo
通过 SWIPT 对 NOMA 进行能效优化
DOI：
10.1109/jstsp.2019.2898114
发表时间：
2019-06-01
影响因子：
7.5
作者：
Tang, Jie;Luo, Jingci;Chambers, Jonathon A.
通讯作者：
Chambers, Jonathon A.
影响因子：
5.2
作者：
WITh A ReD COVeR;INTeNDeD TO KeeP;You IN The Black;ReTAIN eXCeL;MOTIVATe eNGAGe;DAY-TO-DAY ReCOGNITION-DAY-TO-DAY-ReCOGN
通讯作者：
WITh A ReD COVeR;INTeNDeD TO KeeP;You IN The Black;ReTAIN eXCeL;MOTIVATe eNGAGe;DAY-TO-DAY ReCOGNITION-DAY-TO-DAY-ReCOGN
智能反射表面：用于物理层安全的可编程无线环境
影响因子：
3.9
作者：
Chen, Jie;Liang, Ying-Chang;Guo, Huayan
通讯作者：
Guo, Huayan
影响因子：
5.4
作者：
Zhou, Gui;Pan, Cunhua;Nallanathan, Arumugam
通讯作者：
Nallanathan, Arumugam