Adaptive Threshold Control for Energy Detection Based Spectrum Sensing in Cognitive Radios

We study energy detection based spectrum sensing of SU (Secondary User) in cognitive radios. Due to the time varying nature of wireless channels and PU (Primary User) activities, the SINR (Signal to Interference plus Noise Ratio) at the SU receiver changes from slot to slot in a time-slotted system. Unlike the conventional energy detector which uses a fixed energy threshold for spectrum sensing, we dynamically adjust the energy threshold according to the SINR. By limiting the average interference to the PU within a target level, the objective is to maximize the SU's average rate using an optimized policy function, which formulates the threshold as a linear increasing function of the SINR. Simulation results show that the SU's average rate can be significantly improved using the optimized function for dynamic threshold control.