Novel adaptive non-uniform sub-Nyquist sampling technique for cooperative wideband spectrum sensing

Abstract

Spectrum sensing is a key technology in establishing and developing cognitive radio networks. High efficiency, reliability and real time are the most important required parameters for accurate sensing process. Wideband sensing is the main factor to achieve reliability of sensing process. Shadowing, fading and aliasing problems of signals affect the performance of spectrum sensing process therefore; cooperative sensing is effectively used to overcome such problems. In this paper, a novel system is proposed to sense the free channels in a wideband spectrum over distributed cooperative sensing platform of Multi-Coset (MC) periodic non-uniform sampling technique with lower branches then lower complexity than conventional MC sampler. The proposed system is designed to receive a blind input wideband signal. In this work, a system consists of four cooperated nodes by sharing their sensing output data to achieve sensing process. The cooperation between cognitive radio users is executed via reporting channels that connect different nodes. The final decision is based on the majority rules of cooperative sensing. Simulation results illustrated that the probability of detection results from cooperative sensing is higher than the individual sensing by each user itself.