Cooperative beamforming in multiuser MIMO networks: Fast SINR fairness algorithms

This paper studies efficient signal transmission strategies in a multiuser MIMO network where multiple source nodes form a large virtual MIMO array to perform cooperative beamforming. In order to reduce instantaneous feedback needs, we investigate joint power control and cooperative beamforming techniques to maximize the minimum weighted average SINR based on statistical channel information, which consists of the covariance matrices in the beamforming network. Since the joint optimization problem over power, transmit beamformer and receive beamformer is non-convex, we analyze two sub-problems: the joint optimization of power and transmit beamformer under fixed receive beamformer, and the joint optimization of power and receive beamformer under fixed transmit beamformer. For both sub-problems, we use nonlinear Perron-Frobenius theory to characterize the optimal solution and present decentralized algorithms with provable geometrically fast convergence rate. By combining the developed techniques and the network duality, we provide an effective iterative algorithm for the joint optimization problem.