Power Optimization for Aerial Intelligent Reflecting Surface-Aided Cell-Free Massive MIMO-Based Wireless Sensor Network

Tao Zhou,Chunguo Li,Zhexian Shen,Kui Xu,Xin Liu

doi:10.1155/2021/9989098

Tao Zhou, Chunguo Li + Show 3 more

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https://doi.org/10.1155/2021/9989098

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Abstract

Intelligent reflecting surfaces (IRSs) have significant advantages in enhancing the coverage and reducing the deployment cost of wireless networks. This paper studies an aerial IRS- (AIRS-) enhanced cell-free massive multiple-input multiple-output- (MIMO-) based wireless sensor network (WSN) in which multiple access points (APs) serve several sensor users (SUs). Direct links between the APs and SUs are blocked due to occlusion by tall buildings. Hence, we deploy an AIRS to improve the communication quality of the SUs. Our goal is to minimize the total transmit power of all APs under a given minimum signal-to-interference-plus-noise ratio (SINR) requirement. We propose a joint iterative optimization algorithm by designing an active beamforming mechanism at each AP and a passive beamforming mechanism at the AIRS to solve this problem. Simulation results illustrate the good performance of the proposed method.

Highlights

Compared with fifth-generation (5G) communication, sixth-generation (6G) communication will require higher speeds, lower latency, and Internet of Everything (IoE) capabilities [1,2,3]
(2) We propose a joint optimization algorithm to optimize the total transmission power for the singleAIRS case. en, we extend to power optimization for the multi-aerial IRS (AIRS) case. e simulation results show the good performance of our proposed method in power savings
Inspired by the traditional idea of alternating iterations in intelligent reflective surfaces (IRSs)-aided communication [22, 33], we propose a joint optimization strategy to solve this problem. at is, first, for fixed Φ, we optimize the beamforming at the access points (APs), and for fixed beamforming design at the APs, that is, wli, we optimize the passive beamforming at the AIRS. e above steps are alternatively performed until convergence

Summary

Introduction

Compared with fifth-generation (5G) communication, sixth-generation (6G) communication will require higher speeds, lower latency, and Internet of Everything (IoE) capabilities [1,2,3]. As one of the core technologies for 6G, intelligent reflective surfaces (IRSs) can effectively enhance the regional coverage and reduce the energy consumption of wireless networks [7]. E signals reflected by an IRS can be made to be coherently superimposed at the receiver by suitably designing the reflection coefficients of the IRS. Erefore, IRSs can effectively reduce the costs and energy consumption of wireless networks [11, 12]. We call this approach passive beamforming [13, 14]

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