Pricing-Based Semi-Distributed Clustering and Beamforming for User-Centric MIMO Networks

User-centric dynamic base station (BS) clustering can efficiently avoid cell edge effect, which results in overlapped clusters and introduces tremendous complexity in beamforming optimizations. However, existing works mainly focus on addressing the problem in a centralized manner. In this letter, a semi-distributed user-centric clustering and beamforming scheme for sum-rate maximization is proposed, where the optimization problem is split by introducing interference pricing and solved subsequently at the anchor of each cluster. Specifically, based on interference pricing, the problem is decomposed into parallel subproblems by decoupling interference constraints and power constraints, where beamforming matrices are optimized at the anchor of each cluster through generalized iterative minimization of mean-square error; besides, cluster size is controlled by taking power spent as penalizing term and minimum rate constraints are taken into consideration to guarantee the throughput of edge users. Simulation results show about <inline-formula> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula> gains in sum-rate criteria and <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> gains in proportional fair criteria of the proposed scheme in terms of 5%-tile user throughput compared to BS-centric and centralized schemes.