Sensing time and power optimization in MIMO cognitive radio networks

In this paper, we investigate the sensing-throughput tradeoff in multi-antenna cognitive radio (CR) systems. Specifically, we optimize the sensing threshold, sensing time, and transmit power of a multi-input multi-output (MIMO) CR system for maximization of the opportunistic system throughput under transmit power and probability of false alarm and detection constraints. To this end, we propose a new transmission protocol which allows the CR user to simultaneously perform data transmission and spectrum sensing on different spatial subchannels. We formulate a non-convex optimization problem for the optimal choice of the sensing threshold, sensing times, and transmit powers in the different spatial subchannels of MIMO CR systems. Since finding the global optimal solution entails a very high complexity, we develop an efficient iterative algorithm that is based on the concept of alternating optimization and solves only convex subproblems in each iteration. Simulation results show that the developed algorithm closely approaches the global optimal performance and achieves significant performance gains compared to baseline schemes employing equal powers or equal sensing times in all subcannels.