Beamforming Design for IRS-Aided Decode-and-Forward Relay Wireless Network

继电器 波束赋形 计算机科学 最大比值合并 无线 无线网络 算法 天线(收音机) 功率(物理) 拓扑(电路) 电子工程 解码方法 电信 电气工程 工程类 量子力学 衰退 物理
作者
Xuehui Wang,Feng Shu,Weiping Shi,Xiaopeng Liang,Rongen Dong,Jun Li,Jiangzhou Wang
出处
期刊:IEEE transactions on green communications and networking [Institute of Electrical and Electronics Engineers]
卷期号:6 (1): 198-207 被引量:29
标识
DOI:10.1109/tgcn.2022.3145031
摘要

As a low-cost and low-power-consumption passive reflector, intelligent reflecting surface (IRS) can make a significant rate improvement by building a programmable wireless environment. To improve the rate performance and coverage range of wireless networks, an IRS-aided decode-and-forward (DF) relay network is proposed with multiple antennas at relay station (RS). To achieve a high rate, an alternately iterative structure (AIS) of maximizing receive power (Max-RP) at RS is proposed to jointly optimize the beamforming vectors at RS and phase shifts at IRS. Considering its high-complexity, two low-complexity Max-RP schemes of null-space projection (NSP) plus maximum ratio combining (MRC) and IRS element selection (IRSES) plus MRC are presented to reduce this complexity, respectively. For the former, NSP is used to separate the reflected signal from IRS and the direct transmitted signal from source and MRC is adopted to combine the two signals at RS. For the latter, the basic concept of IRSES is as follows: IRS is partitioned into ${M}$ subsets of elements and adjusting the phases of all elements per subset make all reflected signals and the direct signal from source phase alignment (PA) at the corresponding antenna of relay. Simulation results show that the proposed three methods perform much better than the existing network with single-antenna relay in terms of rate performance. In particular, a 85% rate gain over existing scheme is achieved in the high signal-to-noise ratio region. Moreover, it is verified that the positions of RS and IRS have a substantial impact on rate performance, and there exists an optimal positions of RS and IRS.
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