Weighted sum-rate maximization for distributed ris-assisted cell-free massive MIMO

The feasibility of utilizing distributed reconfigurable intelligent surfaces (RISs) in a cell-free massive multiple-input multiple-output (mMIMO) setup is investigated. To maximize the system-wide weighted sum rate under the minimum quality-of-service of the users and a transmit power constraint at the access points (APs), we formulate a joint optimization problem for the transmit/active beamformers at the APs and reflective/passive beamforming at the distributed RISs. We solve this optimization problem by using a fractional programming-based alternate optimization method. We present a comprehensive set of numerical results to evaluate the performance of the proposed system model and optimization framework. Moreover, the proposed algorithm's convergence and computational complexity aspects, and our analytical and simulation results investigate the effects of the numbers of APs, RISs, and reflecting elements. Consequently, we reveal that the proposed distributed RIS-assisted cell-free mMIMO system helps to achieve high spectral efficiency gains for future wireless networks.