Multi-antenna cognitive radio systems: Environmental learning and channel training

This paper presents a multi-antenna cognitive radio (CR) system that is capable of operating concurrently with the primary radio (PR) link. The operation of the CR system consists of three stages: environmental learning, CR channel training and CR data transmission. In environmental learning stage, partial channel information between PR and CR are obtained blindly, based on which the transmit beamforming and the receive beamforming strategies are designed at CR to remove/reduce the interference to and from PR, respectively. We characterize all the interference values analytically and study the problem of learning/training tradeoff associated with the proposed scheme. The optimal balancing between learning and training is examined via the minimum mean square error (MSE) of the channel estimation. It is shown that for a given total learning/training time, there indeed exists a optimal learning time that minimizes the MSE of the channel estimation, yet the interference power to the PR is regulated.