Spectrum Recovery Improvement in Cognitive Radio Using Grey Wolf Optimizer

Abstract

By using spectrum gaps caused by the underuse of frequency spectrum, cognitive radio is one of the most promising methods to enable opportunistic spectrum access for secondary users. In order to prevent interference with primary users, a cognitive radio unit must frequently sense the spectrum. Wideband spectrum sensing techniques that use compression are gaining popularity because they eliminate the need for high-rate analog-to-digital converters, which in turn reduces the complexity and power consumption of the cognitive radio. The Grey Wolf Optimizer is one of the most recent optimization techniques, that is capable of resolving the compressive spectrum recovery technique’s optimization issue. By comparing the effectiveness of algorithms for detecting the spectrum, the simulation results in this study have shown that the grey wolf optimizer algorithm performed better than basis pursuit denoising approach.