A Game-Theoretic Approach for User-Centric AP Selection in Cell-Free Massive MIMO Under Dynamic User Demand Environment

Abstract

This letter investigates user-centric (UC) access point (AP) selection for sum spectral efficiency (SE) maximization in cell-free massive multiple-input multiple-output (MIMO) systems under dynamic user demand environment. The AP selection problem can be modeled as a stochastic game with local altruistic characteristics. It can be proved to be an exact potential game (EPG), which further clarifies the existence of pure strategy Nash equilibrium (NE). Then, we propose a stochastic learning-based distributed UC AP selection algorithm (DUAPSA) to achieve the NE. Finally, simulation results are conducted to verify the validity of the DUAPSA algorithm in dynamic user demand environment.