Adaptive Grouping Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks

In this paper, we propose an adaptive group-based cooperative spectrum sensing scheme to maximize the spectrum efficiency without degrading the sensing accuracy. We consider cooperating secondary users with non-identical energy thresholds and average signal-to-noise ratio which will be represented by non-identical local probabilities of detection and false alarm. We formulate the throughput efficiency maximization problem for non-identical secondary users subject to a minimum requirement on the sensing accuracy. To solve the formulated problem, we propose an adaptive user and group assignment algorithm that minimizes the sensing overhead and maximizes the throughput efficiency. Simulation results demonstrate that our proposed algorithm can effectively improve the throughput efficiency with guaranteed sensing accuracy as compared to the non-adaptive and sequential cooperative sensing schemes.