User-Centric Access Point Selection in Cell-Free Massive MIMO Systems: A Game-Theoretic Approach

In this letter, we investigate user-centric access point (AP) selection for cell-free massive multiple-input multiple-output (MIMO) systems. In contrast to existing works, we study this problem from the perspective of game theory and model user-centric AP service cluster formation as a local altruistic game, which is proven to be an exact potential game (EPG) and to have at least one pure Nash equilibrium (NE). Then, an improved maximum non-neighbor-set-based concurrent spatial adaptive play (MNSB-C-SAP) algorithm is proposed to achieve the NE. Simulation results show that the proposed algorithm outperforms existing algorithms in terms of convergence speed and verify the superiority of the game-theoretic AP selection method compared with some existing approaches.

Automated summary

In this paper, we investigate the problem of user-centric access point (AP) selection for cell-free massive MIMO systems. We employ game theory to model the AP service cluster formation as a local altruistic game and propose an improved concurrent spatial adaptive play algorithm to achieve the optimal solution. Simulation results show that the proposed algorithm outperforms existing algorithms in terms of convergence speed, highlighting the superiority of the game-theoretic AP selection method.