Sidelobe Reduction in NC-OFDM-Based CRNs Using Differential Evolution-Assisted Generalized Sidelobe Canceller

Abstract

Noncontiguous orthogonal frequency division multiplexing (NC-OFDM) is considered a suitable candidate for the cognitive radio network (CRN) to accomplish efficient data transmission. The NC-OFDM allows secondary users (SUs) to access the primary user (PU) spectrum while being detected idle. However, interference may occur in the adjacent frequency bands of the PU due to sidelobes of the SU transmission. The use of cancellation carriers (CCs) and generalized sidelobe canceller (GSC) is a widely adopted technique to tackle the sidelobes. To this end, this paper presents a differential evolution- (DE-) based GSC (DE-GSC) scheme to suppress unwanted sidelobes. At first, in the DE-GSC1 scheme, the adaptive weight vector is calculated using the DE algorithm while considering the complete samples of the sidelobes for optimization. The optimized weights are then added with the original weights to reduce the sidelobe issue. Next, in the DE-GSC2 scheme, selected elements for the adaptive weight vector near the main NC-OFDM signal are computed using the DE to reduce the search space. The performance of the proposed methods in terms of power spectral density (PSD) is compared with some of the recent techniques employing five different scenarios. Simulation results in the presence of single and multiple spectral hole scenarios validate that the proposed DE-GSC1 and DE-GSC2 methods result in enhanced suppression performance compared with the: original signal, simple CC, simple GSC, DE-based CC (DE-CC), and genetic algorithm- (GA-) based CC (GA-CC) schemes.