Shirazinia, Amirpasha and Dey, Subhrakanti (2015) Optimized Compressed Sensing Matrix Design for Noisy Communication Channels. In: 2015 IEEE International Conference on Communications (ICC). IEEE, pp. 4547-4552. ISBN 978-1-4673-6432-4

Preview

Download (275kB) | Preview

Abstract

We investigate a power-constrained sensing matrix design problem for a compressed sensing framework. We adopt a mean square error (MSE) performance criterion for sparse source reconstruction in a system where the source-to-sensor channel and the sensor-to-decoder communication channel are noisy. Our proposed sensing matrix design procedure relies upon minimizing a lower-bound on the MSE. Under certain conditions, we derive closed-form solutions to the optimization problem. Through numerical experiments, by applying practical sparse reconstruction algorithms, we show the strength of the proposed scheme by comparing it with other relevant methods. We discuss the computational complexity of our design method, and develop an equivalent stochastic optimization method to the problem of interest that can be solved approximately with a significantly less computational burden. We illustrate that the low-complexity method still outperforms the popular competing methods.

Item Type:	Book Section
Additional Information:	Cite as: A. Shirazinia and S. Dey, "Optimized compressed sensing matrix design for noisy communication channels," 2015 IEEE International Conference on Communications (ICC), 2015, pp. 4547-4552, doi: 10.1109/ICC.2015.7249039.
Keywords:	Optimized; Compressed; Sensing Matrix Design; Noisy Communication Channels;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	14533
Identification Number:	https://doi.org/10.1109/ICC.2015.7249039
Depositing User:	Subhrakanti Dey
Date Deposited:	15 Jun 2021 14:09
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads