Simultaneous Detection and Channel Estimation for Censoring-Based Spectrum Sensing in Cognitive Radio Networks

Abstract

This letter considers simultaneous primary user (PU) detection and channel estimation for censoring-based spectrum sensing in cognitive radio networks over fading channels. We formulate the problem mathematically for Rician and Rayleigh fading channels. Closed-form expressions are derived for the critical performance metrics in low SNR regime. Further, we optimize the censoring parameter and the power allocation for throughput maximization under transmit and interference power constraints. Our results demonstrate that simultaneous PU detection and channel estimation substantially improve the throughput of cognitive radio networks over an approach where PU detection and channel estimation are treated independently.