Fairness-aware Location and Hybrid Beamforming Optimization in IRSs-aided Cell-free MIMO System

Intelligent reflecting surface/Reconfigurable intelligent surface (IRS/RIS) and cell-free networks have been proposed as revolutionary technologies for beyond fifth-generation (B5G) and sixth-generation (6G) communication, which may significantly improve the connection quality and coverage to meet future communication demand for extremely massive connectivity and high reliability. In this paper, we proposed a low-complexity fractional programming (FP) based fairness-aware location and hybrid beamforming optimization method in IRSs-assisted cell-free MIMO systems. The minimum rate of user (UE) was optimized by jointly optimizing the passive beamforming in IRSs, location of IRSs, and transmit beamforming at base stations (BSs). Different from previous works, which required solving many feasible second-order cone program (SOCP) and semi-definite relaxation (SDR) problems in each iteration, our algorithm only needs to solve SOCP and SDR once in each iteration. The convergence of the proposed algorithm is validated by numerical results and our proposed method can improve the minimum rate by approximately 51% compared with FP transmit beamforming with random phase shift of IRS.