Capacity Balancing for Multiuser MIMO Cognitive Radio Network

We propose a capacity balancing beamforming technique for a multiple input and multiple output (MIMO) based cognitive radio (CR) network. The proposed algorithm is based on the mean square error (MSE) duality. And its aim is to maximize the worst capacity of multiple secondary users (SUs) by jointly designing their transceiver beamformers while ensuring the interference leakage to multiple primary users (PUs) are below the prescribed thresholds. We use an iterative approach to determine the transceiver beamformers so that the capacities achieved by all SUs are balanced and maximized. Due to the limited cooperation between the secondary base-station (SBS) and PUs, we assume the channel state information (CSI) between the SBS and PUs is imperfect. However, the interference to PUs caused by the transmission of the SBS is so little that it can be ignored. Therefore, it makes the proposed algorithm has strong robustness for the small disturbance in the CSI between the SBS and PUs. The performance of the algorithm proposed in this paper is demonstrated by the Monte Carlo simulation.