Identifying Unused RF Channels Using Least Matching Pursuit
Abstract
Cognitive radio aims at identifying unused radio-frequency (RF) bands with the goal of re-using them opportunistically for other services. While compressive sensing (CS) has been used to identify strong signals (or interferers) in the RF spectrum from sub-Nyquist measurements, identifying unused frequencies from CS measurements appears to be uncharted territory. In this paper, we propose a novel method for identifying unused RF bands using an algorithm we call least matching pursuit (LMP). We present a sufficient condition for which LMP is guaranteed to identify unused frequency bands and develop an improved algorithm that is inspired by our theoretical result. We perform simulations for a CS-based RF whitespace detection task in order to demonstrate that LMP is able to outperform black-box approaches that build on deep neural networks.
Keywords
Cite
@article{arxiv.2005.02571,
title = {Identifying Unused RF Channels Using Least Matching Pursuit},
author = {Emre Gönültaş and Milad Taghavi and Sweta Soni and Alyssa B. Apsel and Christoph Studer},
journal= {arXiv preprint arXiv:2005.02571},
year = {2020}
}
Comments
To appear at IEEE SPAWC 2020