Cooperative Compressive Power Spectrum Estimation
Spectral Theory
2016-11-17 v1
Abstract
We examine power spectrum estimation from wide-sense stationary signals received at different wireless sensors. We organize multiple sensors into several groups, where each group estimates the temporal correlation only at particular lags, which are different from group to group. A fusion centre collects all the correlation estimates from different groups of sensors, and uses them to estimate the power spectrum. This reduces the required sampling rate per sensor. We further investigate the conditions required for the system matrix to have full column rank, which allows for a least-squares reconstruction method.
Cite
@article{arxiv.1405.4160,
title = {Cooperative Compressive Power Spectrum Estimation},
author = {Dyonisius Dony Ariananda and Daniel Romero and Geert Leus},
journal= {arXiv preprint arXiv:1405.4160},
year = {2016}
}
Comments
To appear in Proceeding of the 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM 2014)