Joint Reporting And Linear Fusion Optimization In Collaborative Spectrum Sensing For Cognitive Radio Networks

In this paper, the cooperative spectrum sensing in centralized cognitive radio networks is studied as a three-phase process, composed of local sensing, reporting, and decision/data fusion and a novel approach is proposed to optimize the linear soft combining scheme at the fusion phase jointly with two elements of the reporting phase: i) the number of bits used by each node to quantize the local sensing outcomes, and ii) the power level by which each node reports its sensing outcome to the fusion center. The proposed optimization problem is represented using the conventional false alarm and missed detection probabilities and two straightforward solutions are also provided. Finally, the performance improvement associated with the proposed joint optimization scheme is demonstrated by a set of illustrative simulation results.