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Paper Abstract and Keywords
Presentation 2019-07-11 09:35
A study on Auto-Regressive modeling of Duty Cycle
Kohei Okawa, Hiroki Iwata, Kenta Umebayashi (Tokyo Univ. of Agriculture and Tech.), Janne Lehtomäki (Univ. of Oulu), Miguel López-Benítez (Univ. of Liver), Satya Joshi (Univ. of Oulu) SR2019-29
Abstract (in Japanese) (See Japanese page) 
(in English) In dynamic spectrum sharing, it is useful to exploit statistical information on spectrum usage.
In this paper, we investigate an AR (Auto-Regressive) modeling to predict DC (Duty Cycle) which is spectrum occupancy rate over time axis.
Real DC measurements show behavior that is hard for the typical AR model to express such as a time-varying characteristic of mean DC and existence of time period with low-correlation.
To overcome the behavior, we propose a DC model based on AR model considering these behavior.
Specifically, the proposed model classifies the states of DC value (high or low) exploiting thresholding process and models the DC based on AR model each state.
We also consider the time-varying characteristic of mean DC by means of estimation of mean DC by sliding window process.
Several verifications based on real DC measurements show the proposed model can attain high enough prediction accuracy in case of long enough observation period of DC.
Keyword (in Japanese) (See Japanese page) 
(in English) Cognitive radio / dynamic spectrum access / smart spectrum access / duty cycle / auto-regressive model / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 109, SR2019-29, pp. 59-64, July 2019.
Paper # SR2019-29 
Date of Issue 2019-07-03 (SR) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 SR2019-29

Conference Information
Committee SeMI RCS NS SR RCC  
Conference Date 2019-07-10 - 2019-07-12 
Place (in Japanese) (See Japanese page) 
Place (in English) I-Site Nanba(Osaka) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication and Networked Control for the Future Radio of the AI Age, etc 
Paper Information
Registration To SR 
Conference Code 2019-07-SeMI-RCS-NS-SR-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on Auto-Regressive modeling of Duty Cycle 
Sub Title (in English)  
Keyword(1) Cognitive radio  
Keyword(2) dynamic spectrum access  
Keyword(3) smart spectrum access  
Keyword(4) duty cycle  
Keyword(5) auto-regressive model  
1st Author's Name Kohei Okawa  
1st Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agriculture and Tech.)
2nd Author's Name Hiroki Iwata  
2nd Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agriculture and Tech.)
3rd Author's Name Kenta Umebayashi  
3rd Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agriculture and Tech.)
4th Author's Name Janne Lehtomäki  
4th Author's Affiliation University of Oulu (Univ. of Oulu)
5th Author's Name Miguel López-Benítez  
5th Author's Affiliation University of Liverpool (Univ. of Liver)
6th Author's Name Satya Joshi  
6th Author's Affiliation University of Oulu (Univ. of Oulu)
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Speaker Author-1 
Date Time 2019-07-11 09:35:00 
Presentation Time 25 minutes 
Registration for SR 
Paper # SR2019-29 
Volume (vol) vol.119 
Number (no) no.109 
Page pp.59-64 
Date of Issue 2019-07-03 (SR) 

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