Anti-Sampling-Distortion Compressive Wideband Spectrum Sensing for Cognitive Radio

TL;DR

This paper proposes a robust wideband spectrum sensing method for cognitive radio that accounts for sampling distortions in compressed sensing, significantly improving accuracy and noise resilience.

Contribution

It introduces an anti-sampling-distortion constraint (ASDC) and combines it with  norm sparse recovery to enhance performance under AIC distortions.

Findings

Outperforms standard CS in accuracy

Improves denoising ability

Enhances robustness to sampling distortions

Abstract

Too high sampling rate is the bottleneck to wideband spectrum sensing for cognitive radio in mobile communication. Compressed sensing (CS) is introduced to transfer the sampling burden. The standard sparse signal recovery of CS does not consider the distortion in the analogue-to-information converter (AIC). To mitigate performance degeneration casued by the mismatch in least square distortionless constraint which doesn't consider the AIC distortion, we define the sparse signal with the sampling distortion as a bounded additive noise, and An anti-sampling-distortion constraint (ASDC) is deduced. Then we combine the \ell1 norm based sparse constraint with the ASDC to get a novel robust sparse signal recovery operator with sampling distortion. Numerical simulations demonstrate that the proposed method outperforms standard sparse wideband spectrum sensing in accuracy, denoising ability, etc.