Cooperative spectrum sensing with adaptive node selection for cognitive radio networks

In cooperative spectrum sensing, secondary users can cooperate based on their own sensing observations so as to detect the primary signal more reliably. However, since of location disadvantage, observations from some secondary users may contribute little to the global decision at the fusion center, which also induce more energy consumption and sensing overhead. To mitigate this problem we propose a selection probability based adaptive cooperative spectrum sensing scheme exploiting historical observations to exclude nodes with low strength of the received primary signal. The node selection process is achieved by allocating nonidentical selection probability to each secondary user. The new scheme can exploit the location advantage and exhibit almost the same sensing performance compared with conventional cooperative spectrum sensing scheme but with less nodes involved for detection.