Abstract
We consider the problem of sparse signal reconstruction from noisy 1-bit compressed measurements when the receiver has access to side information. We assume that compressed measurements are corrupted by additive white Gaussian noise before quantization and sign-flip error after quantization. A generalized approximate message passing-based algorithm for signal reconstruction from noisy 1-bit compressed measurements is proposed and then, it is extended to the case when side information is available. We show that 1-bit compressed measurements based signal reconstruction is quite sensitive to noise and the reconstruction performance can be greatly improved by exploiting available side information at the receiver.
Original language | English (US) |
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Title of host publication | Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 |
Editors | Michael B. Matthews |
Publisher | IEEE Computer Society |
Pages | 1964-1968 |
Number of pages | 5 |
ISBN (Electronic) | 9781538692189 |
DOIs | |
State | Published - Jul 2 2018 |
Event | 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States Duration: Oct 28 2018 → Oct 31 2018 |
Publication series
Name | Conference Record - Asilomar Conference on Signals, Systems and Computers |
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Volume | 2018-October |
ISSN (Print) | 1058-6393 |
Conference
Conference | 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 |
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Country/Territory | United States |
City | Pacific Grove |
Period | 10/28/18 → 10/31/18 |
Keywords
- 1-bit compressed measurements
- approximate message passing
- side information
- sparse signal reconstruction
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications