Cluster-Based Cooperative Spectrum Sensing Assignment Strategy in Cognitive Radio Networks

Cognitive radio is proposed as an efficient way to address the issue of spectrum shortage and under-utilization, in which cooperative spectrum sensing (CSS) is used to enhance the sensing performance. One of the most fundamental problems of CSS is: how to appropriately assign the secondary users (SUs) to sense the primary user (PU) channels? In this paper, We study the CSS problem under a more practical scenario where taking the heterogeneous characteristics of both SUs and PU channels into consideration. With the objective to maximize the achievable throughput for SUs, we propose a cluster-based CSS to obtain a proper assignment policy, in which all the cluster members cooperative in sensing the same channels, moreover, the CSS problem is formulated as a Maximum Weight One-Sided Biclique Problem, and a greedy heuristic algorithm is proposed to find the suboptimal assignment policy. To evaluate the tradeoff between sensing accuracy and spectrum opportunity, the simulation is conducted between the number of sensed channels and the achievable throughput.