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Paper Abstract and Keywords
Presentation 2016-05-16 14:30
[Poster Presentation] Approximated Theoretical Analysis for Spectrum Sensing Based on Maximum Cyclic Autocorrelation Selection
Daiki Cho, Shusuke Narieda (NIT, Akashi College), Kenta Umebayashi (TUAT) SR2016-10 SRW2016-10
Abstract (in Japanese) (See Japanese page) 
(in English) Maximum cyclic autocorrelation selection (MCAS) is one of spectrum sensing technique based on cyclostationarity detection, and we have been presented sensing techniques extended MCAS for multiple receive antennas. MCAS utilizes the cyclic autocorrelation functions (CAFs) at some cyclic frequencies (peak and non-peak) and compares some test statistics which are computed by these CAFs. Moreover, the probability of false alarm ($P_mathrm{FA}$) can be controlled by the number of non-peak CAFs which is used signal detection. Therefore, MCAS does not need to use a threshold which is used many of spectrum sensing techniques, however, it is difficult to theoretical analysis and has not been examined. In this presentation, ``consequent threshold'' derived from desired $P_mathrm{FA}$ and probability density function is presented, and we attempt to approximate theoretical analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) cognitive radio networks / spectrum sensing / cyclostationarity detection / theoretical analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 29, SR2016-10, pp. 35-36, May 2016.
Paper # SR2016-10 
Date of Issue 2016-05-09 (SR, SRW) 
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)
Download PDF SR2016-10 SRW2016-10

Conference Information
Committee SR SRW  
Conference Date 2016-05-16 - 2016-05-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Hotel Lasaretti, Oulu, Finland 
Topics (in Japanese) (See Japanese page) 
Topics (in English) SmartCom2016 
Paper Information
Registration To SR 
Conference Code 2016-05-SR-SRW 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Approximated Theoretical Analysis for Spectrum Sensing Based on Maximum Cyclic Autocorrelation Selection 
Sub Title (in English)  
Keyword(1) cognitive radio networks  
Keyword(2) spectrum sensing  
Keyword(3) cyclostationarity detection  
Keyword(4) theoretical analysis  
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1st Author's Name Daiki Cho  
1st Author's Affiliation National Institute of Technology, Akashi College, Japan (NIT, Akashi College)
2nd Author's Name Shusuke Narieda  
2nd Author's Affiliation National Institute of Technology, Akashi College, Japan (NIT, Akashi College)
3rd Author's Name Kenta Umebayashi  
3rd Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
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Speaker Author-1 
Date Time 2016-05-16 14:30:00 
Presentation Time 100 minutes 
Registration for SR 
Paper # SR2016-10, SRW2016-10 
Volume (vol) vol.116 
Number (no) no.29(SR), no.30(SRW) 
Page pp.35-36 
#Pages 2 
Date of Issue 2016-05-09 (SR, SRW) 

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