Joint Sensing and Transmission Optimization in IRS-Assisted CRNs: Throughput Maximization

Cognitive radio (CR) is one of the most disruptive techniques for enabling the next generation wireless communication networks due to its potential in improving the spectral efficiency. In this paper, an intelligent reflecting surface (IRS) is exploited to assist both spectrum sensing and secondary transmission in the CR network (CRN) employing opportunistic spectrum access. A novel IRS-enhanced spectrum sensing scheme and a redesigned detection threshold are proposed to improve the sensing performance. We formulate the throughput maximization problem by jointly optimizing the sensing time, the beamforming, and the IRS phase shifts. A computationally efficient block coordinate descent (BCD)-based algorithm is proposed to tackle the non-convex problem. Simulation results show that our proposed scheme is superior to other benchmark schemes in terms of both the throughput and the sensing performance.