Optimal User Pairing for NOMA-assisted Cell-free Massive MIMO System

This study investigates user pairing strategies in a NOMA-assisted cell-free massive MIMO system. A random user pairing naturally leads to non-optimal performance, whereas an exhaustive search is unfavorable in practice due to high complexity. In this paper, we propose a joint optimization of user pairing strategy with beamforming and power allocation to maximize the minimum downlink rate per user. To solve the problem, we first relax the binary variables to continuous variables, and then we develop an iterative algorithm based on the inner approximation method. Numerical results show that the proposed user pairing algorithm outperforms the existing counterparts, such as beamforming, random pairing, far pairing, and close pairing strategies.