Max-To-Mean Ratio Detection for Cognitive Radio

Signal detection is a crucial phase in building a cognitive radio system. However, energy detection, as well as other ´moment detector´, has been shown to exhibit considerable performance degradation in the presence of noise power uncertainty. In this paper, we discuss another method that employs fast Fourier transform (FFT) and max-to-mean ratio (MMR) to detect weak narrowband signals. An analytical approximation of the threshold used is derived, and compared with the empirically simulated constants to assess the degree of accuracy of the former. Simulation results are then presented to illustrate the impact of different parameters on the performance of the detector. Finally, comparisons with energy detector are drawn to highlight some important advantages of the MMR method, i.e. noise power independence and lower sample size requirement.