An improved reconstruction technique for wavelet-based compressive spectrum sensing using genetic algorithm

In this paper we introduce the genetic algorithm as an improved method of signal reconstruction in wavelet-based compressive sensing. Instead of using basis pursuit for reconstruction, a population of initial guesses is created and a genetic algorithm is applied to find the sparsest solution. The paper investigates the different possible objective functions and constraints to give the best performance in a Cognitive Radio spectrum sensing framework.