Achievable Rate Analysis of Two-Hop Interference Channel With Coordinated IRS Relay

• Published in: IEEE transactions on wireless communications Vol. 21; no. 9; pp. 7055 - 7071
• Main Authors: Nguyen, The Vi, Truong, Thanh Phung, Nguyen, Thi My Tuyen, Noh, Wonjong, Cho, Sungrae
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Approximation; Array signal processing; Coordinated relay; Energy efficiency; intelligent reflecting surface; Interference; interference channel; Interference channels; Mathematical analysis; multihop multi-pair transmission; Optimization; Reflectors; Relaying; Relays; Robust control; Spread spectrum communication; Wireless communication; Wireless communications
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2022.3154372

Intelligent reflecting surface (IRS) is a promising 6G technology that can improve wireless communication capacity in a cost-effective and energy-efficient manner, by adjusting a large number of passive reflectors to appropriately change the signal propagation. In this study, we identified the achievable rate region of a two-hop interference channel with distributed multiple IRS relays. To do so, we formulated a non-convex problem that characterizes the rate-profile, and found its solution using successive convex approximation (SCA). We then proposed an alternating direction method of multipliers (ADMM) and alternating optimization (AO) based distributed and low-complex IRS control that maximizes the achievable sum-rate, and proved its convergence and optimality. We then compared the proposed IRS control with semi-definite relaxation (SDR)-, random phase-, deep reinforcement learning (DRL)- based IRS controls, and optimal amplify-and-forward (AF)-, interference neutralization (IN)-, and decode-and-forward (DF) based relaying schemes. We demonstrated that the proposed control with multiple IRS elements outperforms the benchmark controls in terms of the achievable rate region, achievable sum-rate, and energy efficiency under same power budget. We also confirmed that the discrete phase approximation of the proposed control provides near-optimal performance with fewer bits, and the proposed control is robust under imperfect CSI condition. The proposed controls can be efficiently applied to large-scale multi-pair multihop device-to-device and machine-type device communications in the interference-limited or low-powered dense networks of 5G and 6G environments.