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 language | English (US) |
|---|---|
| Title of host publication | 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
| Event | 17th International Conference on Digital Signal Processing, DSP 2011 - Corfu, Greece Duration: Jul 6 2011 → Jul 8 2011 |
Other
| Other | 17th International Conference on Digital Signal Processing, DSP 2011 |
|---|---|
| Country | Greece |
| City | Corfu |
| Period | 7/6/11 → 7/8/11 |
Keywords
- Channel Estimation
- Compressed Sensing
- Sparsity
- System Identification
ASJC Scopus subject areas
- Signal Processing
Cite this
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 proceeding › Conference contribution
}
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
AN - SCOPUS:80053147648
SN - 9781457702747
BT - 17th DSP 2011 International Conference on Digital Signal Processing, Proceedings
ER -