Energy-efficient Cooperative Sensing Schedule for heterogenous users in Cognitive Radio Networks

In this paper, we study the Cooperative Sensing Scheduling (CSS) problem for Cognitive Radio Network (CRN), from the perspective of balance between sensing performance and energy consumption. We place this problem in a practical scenario where both the primary users (PUs) and the secondary users (SUs) are heterogeneous: PU channels are different in terms of channel admission control, idle probability and channel capacity; SUs differs in sensing performance and sensing energy consumption. We formulate the CSS problem as a programming problem, whose optimal solution is proved to exist but takes considerable time and energy to reach. We then propose two heuristic algorithms, i.e., Centralized Algorithm and Multi-oligarch Algorithm, to obtain sub-optimal solutions. A Revised Initialization algorithm is also presented to improve the performance of these two algorithms. Simulation results show that the two algorithms achieve sub-optimal solutions with efficiency and effectiveness.