Reduced Complexity Group-based Precoding for Downlink Cell-free Massive MIMO

Abstract

We consider a user-centric cell-free massive MIMO system in which many distributed access points are connected to a central processing unit to serve multiple users. In practice, linear precoding schemes can achieve high spectral efficiency in massive MIMO systems. However, for cell-free massive MIMO, these methods suffer from a large training overhead and high computational complexity. We reduce the complexity of the zero-forcing precoder and improve the performance of the maximum ratio transmission precoder by dividing the users into groups and assigning different frequency resources to each group. Further, we reduce the training overhead by assigning highly interfering users to different groups. We propose a graph coloringbased user grouping scheme with an adjustable group size. Numerical results show that the proposed scheme can achieve about 96% spectral efficiency of zero-forcing while requiring only 32% processing complexity of zero-forcing. Further, the proposed scheme improves the performance of maximum ratio transmission by 24%. Finally, we investigate the impact of the coherence block length.