Compressed channel sensing

Is the restricted isometry property the right metric?

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper we are concerned with the estimation of doubly-selective multi-path communication channels trough methods referred to as compressed channel sensing. Many authors have used the Restricted Isometry Property (RIP) as a guiding principle to select training to ensure good estimation performance. In this paper we discuss why this approach can be restrictive and why its entanglement with modeling aspects can be misleading. More importantly, we provide an alternative approach to classify inputs based on a new metric that we call localized coherence.

Original languageEnglish (US)
Title of host publication17th DSP 2011 International Conference on Digital Signal Processing, Proceedings
DOIs
StatePublished - 2011
Externally publishedYes
Event17th International Conference on Digital Signal Processing, DSP 2011 - Corfu, Greece
Duration: Jul 6 2011Jul 8 2011

Other

Other17th International Conference on Digital Signal Processing, DSP 2011
CountryGreece
CityCorfu
Period7/6/117/8/11

Keywords

  • Channel Estimation
  • Compressed Sensing
  • Sparsity
  • System Identification

ASJC Scopus subject areas

  • Signal Processing

Cite this

Scaglione, A., & Li, X. (2011). Compressed channel sensing: Is the restricted isometry property the right metric? In 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings [6005010] https://doi.org/10.1109/ICDSP.2011.6005010

Compressed channel sensing : Is the restricted isometry property the right metric? / Scaglione, Anna; Li, Xiao.

17th DSP 2011 International Conference on Digital Signal Processing, Proceedings. 2011. 6005010.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Scaglione, A & Li, X 2011, Compressed channel sensing: Is the restricted isometry property the right metric? in 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings., 6005010, 17th International Conference on Digital Signal Processing, DSP 2011, Corfu, Greece, 7/6/11. https://doi.org/10.1109/ICDSP.2011.6005010
Scaglione A, Li X. Compressed channel sensing: Is the restricted isometry property the right metric? In 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings. 2011. 6005010 https://doi.org/10.1109/ICDSP.2011.6005010
Scaglione, Anna ; Li, Xiao. / Compressed channel sensing : Is the restricted isometry property the right metric?. 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings. 2011.
@inproceedings{febca8f6d26f4887889c9974485eac51,
title = "Compressed channel sensing: Is the restricted isometry property the right metric?",
abstract = "In this paper we are concerned with the estimation of doubly-selective multi-path communication channels trough methods referred to as compressed channel sensing. Many authors have used the Restricted Isometry Property (RIP) as a guiding principle to select training to ensure good estimation performance. In this paper we discuss why this approach can be restrictive and why its entanglement with modeling aspects can be misleading. More importantly, we provide an alternative approach to classify inputs based on a new metric that we call localized coherence.",
keywords = "Channel Estimation, Compressed Sensing, Sparsity, System Identification",
author = "Anna Scaglione and Xiao Li",
year = "2011",
doi = "10.1109/ICDSP.2011.6005010",
language = "English (US)",
isbn = "9781457702747",
booktitle = "17th DSP 2011 International Conference on Digital Signal Processing, Proceedings",

}

TY - GEN

T1 - Compressed channel sensing

T2 - Is the restricted isometry property the right metric?

AU - Scaglione, Anna

AU - Li, Xiao

PY - 2011

Y1 - 2011

N2 - In this paper we are concerned with the estimation of doubly-selective multi-path communication channels trough methods referred to as compressed channel sensing. Many authors have used the Restricted Isometry Property (RIP) as a guiding principle to select training to ensure good estimation performance. In this paper we discuss why this approach can be restrictive and why its entanglement with modeling aspects can be misleading. More importantly, we provide an alternative approach to classify inputs based on a new metric that we call localized coherence.

AB - In this paper we are concerned with the estimation of doubly-selective multi-path communication channels trough methods referred to as compressed channel sensing. Many authors have used the Restricted Isometry Property (RIP) as a guiding principle to select training to ensure good estimation performance. In this paper we discuss why this approach can be restrictive and why its entanglement with modeling aspects can be misleading. More importantly, we provide an alternative approach to classify inputs based on a new metric that we call localized coherence.

KW - Channel Estimation

KW - Compressed Sensing

KW - Sparsity

KW - System Identification

UR - http://www.scopus.com/inward/record.url?scp=80053147648&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053147648&partnerID=8YFLogxK

U2 - 10.1109/ICDSP.2011.6005010

DO - 10.1109/ICDSP.2011.6005010

M3 - Conference contribution

SN - 9781457702747

BT - 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings

ER -