Distributed Wideband Spectrum Sensing

TL;DR

This paper presents a distributed approach for wideband spectrum sensing using compressive measurements and local statistical processing, enabling efficient reconstruction of spectra in a networked environment.

Contribution

It introduces a novel distributed method combining compressive sensing and local statistical operations for wideband spectrum reconstruction.

Findings

Effective reconstruction from distributed compressive measurements

Utilizes simple local operations like ridge regression and shrinkage

Enables spectrum sensing with reduced measurement and communication overhead

Abstract

We consider the problem of reconstructing wideband frequency spectra from distributed, compressive measurements. The measurements are made by a network of nodes, each independently mixing the ambient spectra with low frequency, random signals. The reconstruction takes place via local transmissions between nodes, each performing simple statistical operations such as ridge regression and shrinkage.