Sub-Nyquist Wideband Spectrum Sensing based on Random Demodulation in Cognitive Radio

Cognitive radio (CR) has emerged as one of the most promising candidate solutions for improving spectrum utilization in next generation cellular networks. Spectrum sensing is a process used to detect the unused spectrum bands, holes, to enhance the utilization of scarce radio spectrum. Sampling rate is the bottleneck for spectrum sensing over multi-GHz bandwidth. Compressed sensing (CS) has been recently applied to reduce the sampling rate. In this paper, a wideband sub-Nyquist spectrum sensing architecture based on random demodulation is designed. A Simulink model of the random demodulator based spectrum sensing architecture is built and simulated on MATLAB to prove the system functionality. Implementation of an efficient high speed chipping sequence for the random demodulator is presented. The proposed chipping sequence architecture can operate at 2.27 GHz clock frequency in targeted technology of 130 nm with a speed up of 13.5% compared to previously published work. Moreover, a power-optimized architecture is implemented. The Orthogonal Matching Pursuit (OMP) which is one of the greedy iterative algorithms that is suitable for VLSI implementation is used for spectrum recovery.