Fair Adaptive Power Allocation for Cell-Free Massive MIMO Systems

This paper investigates cell-free massive multiple input multiple output systems with a particular focus on downlink power allocation strategies. Our analysis considers channel estimation errors, where the access points (APs) acquire channel state information by means of uplink pilots sent by the users. In particular, we focus on the downlink power optimization for the maximization of the minimum signal to interference-plus-noise ratio (SINR) subject to per-AP power constraints. First, we present an existing optimal iterative solution for benchmarking purposes. Then, we propose an efficient solution with low computational cost to tackle the considered optimization problem. Interestingly, the proposed solution has a scalar parameter that can be controlled to adjust its main objective to either maximize the minimum SINR or to maximize the spectral efficiency. Through numerical results we show that our solution is effective in providing fairness and achieving high spectral efficiency in the system. Furthermore, unlike existing solutions, our solution can be executed in a non-iterative fashion with negligible performance loss.