Cooperative spectrum sensing with enhanced energy detection under GAUSSIAN noise uncertainty in cognitive radios

TL;DR

This paper introduces optimized energy detection thresholds for cooperative spectrum sensing in cognitive radios, effectively addressing Gaussian noise uncertainty and improving detection performance at low SNRs.

Contribution

It proposes enhanced ED thresholds and a two-step decision pattern to mitigate noise uncertainty effects in cooperative spectrum sensing.

Findings

Lower total error rate achieved at low SNRs with proposed thresholds

Proposed schemes outperform existing noise uncertainty methods

Enhanced detection sensitivity under Gaussian noise uncertainty

Abstract

This paper presents optimization issues of energy detection (ED) thresholds in cooperative spectrum sensing (CSS) with regard to general Gaussian noise. Enhanced ED thresholds are proposed to overcome sensitivity of multiple noise uncertainty. Two-steps decision pattern and convex samples thresholds have been put forward under Gaussian noise uncertainty. Through deriving the probability of detection (Pd) and the probability of false alarm (Pf ) for independent and identical distribution (i.i.d.) SUs, we obtain lower total error rate (Qe) with proposed ED thresholds at low signal-to-noise-ratio (SNR) condition. Furthermore, simulation results show that proposed schemes outperform most other noise uncertainty plans.