FFT-based multiband spectrum sensing in SIMO in-band full-duplex cognitive radio networks

This paper presents fast Fourier transform (FFT)-based multiband spectrum sensing overmultipath Rayleigh frequency selective fading channels in single input multiple output (SIMO) in-band full-duplex (FD) cognitive radio (CR) networks (FDCRNs) under residual self-interference (RSI). In this work, first, multiband energy detection using Neyman Pearson criterion is proposed in FDCRNs under RSI, where the secondary user is equipped with multiple receive antennas to exploit spatial diversity. Next, a two-dimensional averaging is done to overcome spectrum leakage problem occurring due to FFT operation in orthogonal frequency division multiplexing (OFDM) system. The closed form expressions for average probability of detection and probability of false alarm are derived for SIMO FDCRNs under RSI. Further, RSI cancelation is performed employing noise robust wavelet decomposition-based least squares scheme and the corresponding simulation studies indicate that the proposed algorithm further improves the detection performance in SIMO FDCRNs.