Performance Analysis in Cognitive Radio using Multirate Asynchronous Sub-Nyquist Sampling System

Abstract

Wideband spectrum sensing is performed by developed by employing multiple low-rate sampler in a Multirate asynchronous sub-Nyquist sampling (MASS) system. Due to the low sampling rate, this approach is best suited for cognitive radio networks. Robustness during time synchronization issues, energy efficient data sensing and low complexity implementation are the key advantages of MASS. In synchronous and asynchronous samplers, implementation of spectrum sensing can be performed with recovery performance for energy detection. The performance of spectrum sensing can be improved by increasing the sampling branches. MASS utilizes sub-Nyquist sampling. Disadvantages of Nyquist sampling are High sampling rate, high energy cost, high implementation complexity, so sub-Nyquist sampling will be considered. Advantages of sub Nyquist sampling are low sampling rate, probability of overlapping of signal is less, low signal acquisition cost. Parameters like log-normal fading channels, Rayleigh fading, fading conditions for additive white Gaussian noise (AWGN), SNR levels, at different levels of sparsity, the detection probability vs possibility of false alarm are used for measurement of performance. In future MASS is combined with OFDM, to be called as multi carrier MASS and performance measures are evaluated. The paper presents sufficient conditions to uniquely recover the full spectrum by using compressive sensing theory.