Cooperative Spectrum Sensing Using Random Matrix Theory

TL;DR

This paper introduces a novel cooperative spectrum sensing method based on random matrix theory that does not require noise statistics and performs well even with few observations, outperforming traditional energy detection.

Contribution

The paper presents a new eigenvalue-based spectrum sensing scheme using asymptotic random matrix theory, eliminating the need for noise variance knowledge.

Findings

Outperforms classical energy detection methods

Effective with small sample sizes

Works for both AWGN and fading channels

Abstract

In this paper, using tools from asymptotic random matrix theory, a new cooperative scheme for frequency band sensing is introduced for both AWGN and fading channels. Unlike previous works in the field, the new scheme does not require the knowledge of the noise statistics or its variance and is related to the behavior of the largest and smallest eigenvalue of random matrices. Remarkably, simulations show that the asymptotic claims hold even for a small number of observations (which makes it convenient for time-varying topologies), outperforming classical energy detection techniques.