University of Oulu

M. Leinonen, M. Codreanu and M. Juntti, "Signal Reconstruction Performance Under Quantized Noisy Compressed Sensing," 2019 Data Compression Conference (DCC), Snowbird, UT, USA, 2019, pp. 586-586. doi: 10.1109/DCC.2019.00098

Signal reconstruction performance under quantized noisy compressed sensing

Saved in:
Author: Leinonen, Markus1; Codreanu, Marian2; Juntti, Markku1
Organizations: 1Centre for Wireless Communications, University of Oulu, Erkki Koiso-Kanttilan katu 3, Oulu, FI-90570, Finland
2Linköping University, Sweden
Format: abstract
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.1 MB)
Persistent link:
Language: English
Published: IEEE Computer Society Press, 2019
Publish Date: 2019-06-03


We study rate-distortion (RD) performance of various single-sensor compressed sensing (CS) schemes for acquiring sparse signals via quantized/encoded noisy linear measurements, motivated by low-power sensor applications. For such a quantized CS (QCS) context, the paper combines and refines our recent advances in algorithm designs and theoretical analysis. Practical symbol-by-symbol quantizer based QCS methods of different compression strategies are proposed. The compression limit of QCS — the remote RDF — is assessed through an analytical lower bound and a numerical approximation method. Simulation results compare the RD performances of different schemes.

see all

Series: Proceedings. Data Compression Conference
ISSN: 1068-0314
ISSN-E: 2375-0391
ISSN-L: 1068-0314
ISBN: 978-1-7281-0657-1
ISBN Print: 978-1-7281-0658-8
Pages: 586 - 586
DOI: 10.1109/DCC.2019.00098
Host publication: 2019 Data Compression Conference (DCC)
Conference: Data Compression Conference
Field of Science: 213 Electronic, automation and communications engineering, electronics
Copyright information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.