A Simplified Compressive Sampling Approach based on Weights for Efficient Spectrum usage in Wideband DSA Networks

The comprehensive compressive sampling method is indeed a path breaking approach in the field of wideband DSA networks. The block samples of cognitive radio spectrum used for intelligent spectrum allocation based on respective block weights. Reconstruction of the available spectrum is the designating factor of compressive sampling and which acts as the backbone of the cognitive radio architecture. The wideband spectrum sensing is the trending research area in the field of communication. A significant amount of research work has been done in the past decade which enables the wideband spectrum recovery by utilizing the comprehensive compressive sampling at sub-Nyquist rates. In practical, the wideband spectrum is not heterogeneous as each band has its occupancy pattern and, the applications with criteria's often allocate the same bock spectrum and, this development makes the wideband spectrum as heterogeneous. As discussed, in our proposed method, the core idea is taking the wideband spectrum as the heterogeneous which helps to exploit the block like structures and, these structures helps to design the effective compressive spectrum sensing methods that are well accommodated for heterogeneous wideband spectrum. The recovery spectrum by the weighted based recovery algorithm is more stable and robust when compared to the conventional algorithms. The recovery spectrum by the weighted based recovery algorithm is more stable and robust when compared to the conventional algorithms. The proposed method is profound to show variations in the occupancy both in terms of time and frequency dimensions. Finally, the biggest and the significant achievement of this paper is recovering the unused frequencies smaller number of sensing measurements when compared to the traditional state of art methods.