Achievable Rate Analysis of NOMA in Cell-Free Massive MIMO: A Stochastic Geometry Approach

Abstract

Cell-free massive multiple-input multiple-output (MIMO) is a form of distributed massive MIMO aiming to provide massive access and improve spectral efficiency by inheriting favorable properties of traditional massive MIMO, while mitigating detrimental effects such as shadowing and spatially correlated fading. This paper investigates how the throughput of cell-free massive MIMO is affected by non-orthogonal multiple access (NOMA) for the next-generation cellular networks under stochastic access point (AP) and user locations. Thus, we consider homogeneous Poisson point processes (PPPs) to model node locations, while considering a Rayleigh channel with log-distance path loss. The time division duplexing (TDD) mode is employed and uplink channels are estimated autonomously/locally at each AP via uplink pilots sent by users. Moreover, while unique pilots are used between NOMA clusters, pilots are reused within each cluster in order to strike a balance between the training overhead and number of clusters. Matched filter based precoding is performed within the downlink based on the estimated channels. The aggregate signal received from all access points is characterized based on the moment generating function and approximated via moment matching. Thereby, the achievable rates for the users are derived, under the consideration of error propagation due to imperfect successive interference cancellation (SIC). It is shown that NOMA increases the overall rate under environments with low path loss exponents and networks with high access point densities, while careful power allocation can significantly improve user fairness.