Distributed Computation for Centralized MMSE Combining in Cell-Free Massive MIMO Systems

Cell-Free (CF) massive multiple-input multiple-output (MIMO) technology is poised to revolutionize future wireless networks by significantly improving network capacity. However, the conventional centralized implementation of CF networks brings about computational complexities in the central processing unit (CPU) and imposes a heavy burden on fronthaul links due to extensive channel state information (CSI) exchange. In this paper, we propose a distributed computing architecture that employs the preconditioned conjugate gradient algorithm to achieve the performance level of centralized minimum mean square error (MMSE) combining. The proposed algorithm offers two key advantages: firstly, it offloads a significant portion of computations from the CPU to distributed access points, thereby alleviating the computational burden; secondly, it significantly reduces the transmission of instantaneous and historical data through fronthaul links. These benefits contribute to the overall efficiency and scalability of CF massive MIMO systems, as demonstrated in the simulation results.