Capacity Balancing for Multiuser MIMO Cognitive Radio Network

We propose a capacity balancing beamforming technique for a multiple inputs and multiple outputs (MIMO) based cognitive radio (CR) network. The proposed algorithm is based on mean square error (MSE) duality and it is aimed at maximizing the worst case user capacity of multiple secondary users (SUs) by jointly designing their transceiver beamformers while ensuring the interference leakage to multiple primary users (PUs) are below a specific set of thresholds. We use an iterative approach to determine the transceiver beamformers so that the capacities achieved by all SUs are balanced and maximized. The performance of the algorithm is demonstrated through Monte Carlo simulation results.