User-Centric Clustering and Beamforming Design for Satellite-Assisted Cell-Free Networks

The exponential growth in mobile traffic has driven significant interest in cell-free networks, particularly those integrated with satellites, to support high data rates and overcome geographic limitations. In this paper, we propose a novel dynamic clustering and beamforming control that maximizes the minimum data rate in satellite-assisted user-centric cell-free networks. Specifically, we formulate a nonconvex max-min fairness problem to optimize clustering and beamforming under a user-centric cluster size and transmit power constraints. To find a solution, this problem is decomposed into two subproblems: clustering and beamforming. A modified Gale-Shapley-based user-centric clustering algorithm is proposed for the clustering subproblem, which is solved on a long-term basis using statistic channel information. The beamforming subproblem transform is transformed into a semidefinite problem using linear approximation and a linear matrix inequality. We propose a robust beamforming algorithm that considers imperfect instantaneous channel state information, solved on a short-term basis. Lastly, we analyze the computational complexity, revealing that the proposed scheme has polynomial complexity. We evaluate its performance under user mobility in satellite-assisted cell-free networks. The proposed algorithm offers significant performance gains, achieving up to a 15.15% higher minimum data rate and a 14.14% higher average data rate than zero-forcing beamforming and distance-based clustering benchmark schemes.