A Computationally Efficient Node-Selection Scheme for Cooperative Beamforming in Cognitive Radio Networks

Transmit beamforming is an effective mechanism to enable the operation of secondary users (SUs) in underlay cognitive radio networks. However, wireless nodes that are equipped with single omni-directional antennas cannot exploit the benefits of transmit beamforming on their own. Using cooperative beamforming, a group of nodes can collaborate to steer the signal towards the direction of the intended receiver while, at the same time, null the transmitted signal in the direction of primary receiver. In this paper, we study how to select a subset of N nodes out of NT nodes for performing cooperative beamforming. Specifically, we investigate how different node-selection schemes affect the performance of cooperative beamforming. Motivated by the findings from this study, we propose a computationally efficient node-selection scheme for achieving a near-optimal performance in cooperative beamforming. Using simulation results, we demonstrate the performance of our proposed scheme, and show that it is scalable with the system size (i.e., for different values of N and NT ) and is computationally very efficient as compared to other node-selection schemes.