Subspace-based cooperative spectrum sensing for cognitive radio

Cognitive radio with its capability to sense the radio environment and dynamically access the vacant spectrum opportunistically, is an important technology to improve the efficiency of current spectrum utilization. In this paper, a cooperative wideband spectrum sensing approach based on subspace methods is proposed to estimate the number of primary user signals present in the band of interest and their carrier locations. Specifically, each secondary user implements eigen-decomposition of its sample covariance matrix to provide a local estimate. The fusion center generates a global estimate through a weighted sum of these local estimates. Experimental results demonstrate the efficiency of the proposed algorithm in detecting the correct number of primary users and estimating their carrier frequencies.