Energy-Efficient User-Centric Association and Precoding for Cell-Free Massive MIMO Networks.

This paper considers a cell-free massive MIMO network composed of multi-antenna access points (APs) and single-antenna users. A more practical power consumption model involving AP selection is proposed to derive the expression for energy efficiency (EE). On this basis, a user-centric AP selection algorithm is proposed, in which each user selects a subset of APs to provide services that can reduce power consumption. Then, the EE performance of three precoding algorithms, maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE), are compared. In addition, an algorithm for scheduling is proposed to determine the optimal number of users served by the network, which aims to maximize the total EE by fully utilizing the spectral and energy resources of the network. The results show that by using our proposed user-centric AP selection scheme and selecting suitable precoding algorithms based on specific scenarios, the total EE is significantly improved compared to the original method where all APs serve all users, especially at low user density. Furthermore, we show that the optimal size of served users is closely related to the number of antennas.