In this paper, an intelligent reflecting surface (IRS)-and-unmanned aerial vehicle (UAV)-assisted two-way amplify-and-forward (AF) relay network in maritime Internet of Things (IoT) is proposed, where ship1 (S1) and ship2 (S2) can be viewed as data collecting centers. To enhance the message exchange rate between S1 and S2, a problem of maximizing minimum rate is cast, where the variables, namely AF relay beamforming matrix and IRS phase shifts of two time slots, need to be optimized. To achieve a maximum rate, a low-complexity alternately iterative (AI) scheme based on zero forcing and successive convex approximation (LC-ZF-SCA) algorithm is presented. To obtain a significant rate enhancement, a high-performance AI method based on one step, semidefinite programming and penalty SCA (ONS-SDP-PSCA) is proposed. Simulation results show that by the proposed LC-ZF-SCA and ONS-SDP-PSCA methods, the rate of the IRS-and-UAV-assisted AF relay network surpass those of with random phase and only AF relay networks. Moreover, ONS-SDP-PSCA perform better than LC-ZF-SCA in aspect of rate.
@article{arxiv.2306.00412,
title = {Beamforming Design for IRS-and-UAV-Aided Two-Way Amplify-and-Forward Relay Networks in Maritime IoT},
author = {Xuehui Wang and Feng Shu and Yuanyuan Wu and Weiping Shi and Shihao Yan and Yifan Zhao and Qiankun Cheng and Zhongwen Sun and Jiangzhou Wang},
journal= {arXiv preprint arXiv:2306.00412},
year = {2024}
}