Joint precoding design for wideband intelligent reflecting surface-assisted cell-free network

In this paper, we propose an efficient joint precoding design method to maximize the weighted sum-rate in Intelligent Reflecting Surface (IRS)-assisted cell-free networks by jointly optimizing the active beamforming of base stations and the passive beamforming of IRS. To address the high-dimensional non-convex optimization problem, we employ a fractional programming approach to decouple the non-convex problem into subproblems for alternating optimization between active and passive beamforming. The active beamforming subproblem is addressed using the Consensus Alternating Direction Method of Multipliers (CADMM) algorithm, while the passive beamforming subproblem is tackled using the Accelerated Projection Gradient (APG) method. Simulation results demonstrate that our proposed approach achieves significant improvements in weighted sum-rate under various performance metrics compared to Primal-Dual Subgradient (PDS).