Joint User Association and Phase Optimization for IRS-Assisted Multi-Cell Networks

This paper introduces a new interference-aware user association (UA) scheme for a multi-base station (BS) wireless network in which intelligent reflecting surfaces (IRSs) are leveraged to improve each multi-antenna BS's coverage region and mitigate the vulnerability to non-line of sight paths. We aim to maximize the total network downlink achievable rate by jointly optimizing the reflective phase shifters at IRSs while associating mobile users (MUs) to BSs, which is an intractable non-convex problem. An alternating optimization-based algorithm based on solving two sub-problems, i.e., one for UA and one for reflective phase shift optimization, is proposed to tackle the non-convex problem. The proposed algorithm optimizes phase shifters at IRS through fractional programming techniques, and the UA is solved by successive convex approximation (SCA). Simulation results show that the proposed algorithm significantly improves the total network achievable rate compared to heuristic methods, e.g., matching game.