Joint Compressive Sensing in Wideband Cognitive Networks

In this paper, a distributed compressive spectrum sensing scheme in wideband cognitive radio networks is discussed. An AIC RF front-end sampling structure is proposed requiring only low rate ADCs and few storage units for spectrum sampling. Multiple CRs collect compressed samples through AICs and recover spectrum jointly. A novel joint sparsity model is defined in this scenario, along with a universal recovery algorithm based on S-OMP. Numerical simulations show this algorithm outperforms current existing algorithms under this model and works competently under other existing models.