IMPROVED SPECTRUM SENSING THRESHOLD FOR COGNITIVE RADIO USING SMOOTHED PSEUDO WIGNER- VILLE DISTRIBUTION

Abstract

Cognitive Radio (CR) technology emerges as a promising solution to solve the
electromagnetic spectrum scarcity due to the fixed allocation employed worldwide by
regulatory bodies. Essentially, the idea behind CR is to dynamically access underutilized
frequency bands in order to improve the spectrum utilization. The process of spectrum
sensing is a fundamental task for obtaining this awareness and the result of this process
determines the successful operation of CR. Energy detection was used in this work because
it has the lowest computational complexity but with low performance at low signal to noise
ratio. Time-frequency analysis was employed to analyze the energy spectral density of an
observed signal with a view to setting a sensing threshold. Smoothed Pseudo Wigner-Ville
Distribution (PWVD) of the time frequency analysis has been employed in this work to
reduce the effect of cross-terms and a better sensing threshold was gotten, validated through
comparison with the existing work which employed PWVD with an average reduction of
9.09% and 11.1% for Additive White Gaussian Noise Channel in the probabilities of missed
detection and false alarm respectively. This work was being carried out using the time-
frequency tool box developed for MATLAB R2016a.