Regularized Secondary Beamforming in Cognitive Radio Networks with Limited Feedback

This paper proposes a novel technique for secondary user beamforming in cognitive radio networks (CRN). A practical scheme based on limited rate feedback from secondary users to secondary base station (SBS) and feedback from primary users to SBS are employed to acquire the secondary user channel and interference channel state information. Subsequently, a scheme is presented for regularized beamforming in a secondary user system to avoid performance degradation caused by noise amplification. The proposed scheme decomposes the optimal beamformer computation paradigm into sub-problems followed by solving them in an iterative manner. Simulation results demonstrate the better performance of the proposed practical scheme in comparison to ideal scheme.