Distributed Beam Combining in Cell-Free Massive MIMO Networks

Abstract

Cell-free massive multiple-input multiple-output (CF mMIMO) network has gained significant attention due to its ability to provide a ubiquitous connectivity over a wide geographical area without having any cell boundary. It serves the user equipments (UEs) by employing multiple access points (APs) connected to a central processing unit (CPU). In this paper, we focus on designing beam combiners for the APs under limited availability of the pilots. We argue that the received signal-to-interference plus noise (SINR) can be maximized if received signals at each AP are beam combined in a way that it aligns with the desired signal and nullifies the interference arising due to the pilot reuse. We use this strategy to improve three popular beam combiners for the CF mMIMO network based on the maximum ratio (MR), generalized MR (GMR), and reduced-complexity minimum mean square error (RCMMSE) criteria, respectively. The proposed distributed combiners handle the issue of pilot contamination and reduce the amount of signal exchanges between APs and CPU. We have analytically shown that the proposed combiners improve the spectral efficiency of their respective counterparts without increasing their overall complexities. We have corroborated this using simulations for both uncorrelated and correlated channels.