حيدر رافع كريم ال موسى

Cell-free Massive Multiple-Input Multiple-Output (MIMO) is introduced as a promising network architecture for the upcoming fifth-generation (5G) wireless communication networks. It enhances user experience and improves the overall system performance by providing huge throughput and coverage probability to all users throughout a system. In this paper, a resource allocation problem is studied for downlink cell-free massive MIMO networks, where each access point (AP) serves a cluster of user equipment (UE). Transmit precoding and power allocation are linked to the underlying max-min scheduling to ensure uniform and excellent service throughout the coverage area. Due to the coupled interference among UEs, the resulting max-min resource allocation optimization problem becomes non-convex. We demonstrate the uplink-downlink duality and propose an iterative algorithm which solves the primal downlink problem efficiently. By utilizing the max-min beam former and taking the channel estimation error into account, we further derive the capacity lower bound of the underlying cell-free massive MIMO network. The performance of the introduced scheme is also investigated through simulations. Numerical results show the efficiency of the introduced algorithm.