Adaptive Threshold Control for Energy Detection Based Spectrum Sensing in Cognitive Radio Networks

Abstract

We consider energy detection based spectrum sensing for opportunistic SU (Secondary User) transmissions in cognitive radio networks. Due to the time-varying nature of wireless fading channels and PU (Primary User) activities, the instantaneous 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 value of energy threshold to detect the PU's occurrence, we let the SU transmitter dynamically adjust the threshold according to the instantaneous SINR. Under the constraint of limiting the average interference to the PU within a target level, the objective is to maximize the SU's average transmission rate and throughput. Our task is to determine a proper policy function for threshold control, which formulates the value of the threshold as a function of the SINR to achieve the above objective. In particular, we consider a linear policy function, which allows a higher threshold and thus more aggressive SU transmissions under a larger SINR. Simulation results show that the SU's average transmission rate can be significantly improved using the optimized policy function.