Energy Sensing Strategy Optimization for Opportunistic Spectrum Access

This paper introduces a correlator-based energy sensing strategy for opportunistic spectrum access in a slow, flat-fading channel. The correlator provides weighted energy accumulation in time. We assume that the noise variance is known and the primary user (PU) traffic follows a two state Markov chain with known idle and busy rates. Using Chebyshev bounds on missed detection and false alarm probabilities, we find that the optimal weighting function is an increasing function of time and its shape is dependent on the PU traffic characteristics and SNR. We show that the traditional flat-integration based energy collection method is suboptimal both in the error probability and channel utilization sense.