Cell-Free Massive MIMO with Rician Fading: Estimation Schemes and Spectral Efficiency

As the cell sizes in cellular networks shrink, the inter-cell interference becomes more of an issue. Instead of operating each cell autonomously, we can connect all the access points (APs) together to form a cell-free massive MIMO (multiple-input multiple-output) system that can alleviate interference by spatial processing. Previous studies have focused on Rayleigh fading channels, but in densely deployed systems, it is likely that some of the users will have line-of-sight (LoS) propagation to some of the APs. In this paper, we model this by arbitrarily distributed Rician fading channels. Two types of channel estimators are considered: a classical least-square (LS) estimator and a Bayesian minimum mean square error (MMSE) estimator. We derive closed-form spectral efficiency (SE) expressions for the uplink (UL) and downlink (DL) when using each of these estimators for maximum ratio (MR) processing. The performance difference is evaluated numerically to figure out under which conditions it is beneficial to know the channel statistics when estimating a channel.