Distributed Wideband Spectrum Sensing
Thomas Kealy, Oliver Johnson, Robert Piechocki

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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSparse and Compressive Sensing Techniques · Photoacoustic and Ultrasonic Imaging · Electrical and Bioimpedance Tomography
