Censored truncated sequential spectrum sensing for cognitive radio networks

A truncated censored sequential spectrum sensing technique is considered as an energy saving approach for a cooperative spectrum sensing system. In order to design the underlying sensing parameters, the maximum energy consumption per sensor is minimized subject to a lower bounded global probability of detection and an upper bounded false alarm rate. We compare the performance of the proposed scheme with a fixed sample size censoring scheme. It is shown that the truncated censored sensing approach is highly energy efficient, particularly when the sensing cost is high.