Uniform quantizer for Cooperative Sensing in cognitive radio networks

Cooperative spectrum sensing for dynamic spectrum access to unused licensed spectrum has been proposed as a solution to the spectrum scarcity problem. In this paper, a novel sensing algorithm, Cooperative Sensing with Decision Vector (CSDV), that employs uniform quantizer and a weight vector for global decision logic, is proposed. CSDV method is based on energy detection and performs better than conventional hard decision algorithms such as MAJORITY and M/N in terms of probability of detection and false alarm at the cost of a marginal increase in overhead bits. Probability of detection is maximized for a given probability of false alarm by proposed method via convex optimization. For detailed analysis, CSDV is compared with equal gain combiner scheme, which performs far better than hard decision algorithms, via highest bandwidth requirement. Moreover, robustness of CSDV method to sensing error is analyzed when some nodes always report false decisions to the fusion center.