One-bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach

TL;DR

This paper introduces a new one-bit spectrum sensing method using the eigenvalue moment ratio (EMR), enabling efficient detection with minimal hardware by leveraging asymptotic distribution analysis.

Contribution

It develops a novel one-bit sensing approach based on EMR and derives its asymptotic distribution, facilitating spectrum sensing directly from one-bit samples.

Findings

Effective spectrum sensing with one-bit samples demonstrated

Theoretical analysis confirms the asymptotic distribution under null hypothesis

Simulation results show good sensing performance at low hardware cost

Abstract

One-bit analog-to-digital converter (ADC), performing signal sampling as an extreme simple comparator, is an overwhelming technology for spectrum sensing due to its low-cost, low-power consumptions and high sampling rate. In this letter, we propose a novel one-bit sensing approach based on the eigenvalue moment ratio (EMR), which has been proved to be highly efficient for conventional multi-antenna spectrum sensing in $\infty$-bit situation. Particularly, we determine the asymptotic distribution of one-bit EMR under null hypothesis via the central limited theorem (CLT), allowing us to perform spectrum sensing with one-bit samples directly. Theoretical and simulation analysis show the new approach can provide reasonably good sensing performance at a low hardware cost.