Paper Abstract and Keywords |
Presentation |
2012-10-18 16:50
[Invited Talk]
Applications of Compressed Sensing in Wireless Communication Systems Doohwan Lee (Univ. of Tokyo) RCS2012-145 SR2012-65 AN2012-39 USN2012-42 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Compressed sensing has been drawn explosive attention during last several years. It is a new framework that uses signal sparsity to reduce the amount of data that needs to be measured. The measurement of an M-dimensional vector onto an N-dimensional (N<<M) vector loses some information in general and the inverse problem (N equations with M variables) has an infinite number of solutions. However, when the signal only has K nonzero coefficients (K<N<<M) in some convenient basis and the measurement matrix is incoherent with the basis, or equivalently satisfies the restricted isometry property, the inverse problem has, with high probability, a unique and exact solution. Inspired by above seminal work of Candes and Donoho, and a plethora of related research has taken place from theory to applications including astronomy, magnetic resonance imaging, and digital imaging by exploiting the natural sparsity of their underlying data. Interpretation of compressed
sensing in the sense of wireless technology is as follows: radio wave data can be received, transmitted, and reconstructed using
sub-Nyquist rate information without aliasing if the original signal is sparse in time domain or frequency domain. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Compressed sensing / Compressive sampling / L1-norm minimization / Compressed sensing applications / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 240, SR2012-65, pp. 179-179, Oct. 2012. |
Paper # |
SR2012-65 |
Date of Issue |
2012-10-10 (RCS, SR, AN, USN) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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RCS2012-145 SR2012-65 AN2012-39 USN2012-42 |
Conference Information |
Committee |
SR AN USN RCS |
Conference Date |
2012-10-17 - 2012-10-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Fukuoka univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
wireless distributed network, general topics |
Paper Information |
Registration To |
SR |
Conference Code |
2012-10-SR-AN-USN-RCS |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Applications of Compressed Sensing in Wireless Communication Systems |
Sub Title (in English) |
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Keyword(1) |
Compressed sensing |
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Compressive sampling |
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L1-norm minimization |
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Compressed sensing applications |
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1st Author's Name |
Doohwan Lee |
1st Author's Affiliation |
The Univeristy of Tokyo (Univ. of Tokyo) |
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Speaker |
Author-1 |
Date Time |
2012-10-18 16:50:00 |
Presentation Time |
35 minutes |
Registration for |
SR |
Paper # |
RCS2012-145, SR2012-65, AN2012-39, USN2012-42 |
Volume (vol) |
vol.112 |
Number (no) |
no.239(RCS), no.240(SR), no.241(AN), no.242(USN) |
Page |
p.121(RCS), p.179(SR), p.91(AN), p.85(USN) |
#Pages |
1 |
Date of Issue |
2012-10-10 (RCS, SR, AN, USN) |
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