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Paper Abstract and Keywords
Presentation 2018-03-02 11:15
Prediction Scheme of WLAN Idle Status using Probabilistic Neural Network and Implementation on FPGA
Julian Webber, Abolfazl Mehbodniya, Yafei Hou, Kazuto Yano, Makoto Usui, Tomoaki Kumagai (ATR) SR2017-134
Abstract (in Japanese) (See Japanese page) 
(in English) WLAN traffic is becoming increasingly congested particularly in the 2.4,GHz band.
Simultaneous utilization of multiple-bands has been proposed as one solution to this problem. To take advantage of the scattered resources across channels an agile transceiver is required that operates on multiple channels simultaneously.
To realize this concept a busy/idle (B/I) predictor is required in the sensing unit of the multi-band WLAN. In this paper we report on the prediction of upcoming WLAN B/I status using the probabilistic neural network (PNN) algorithm based on pattern matching technique. Using actual captured IEEE~802.11 wireless data frames, the prediction performance is compared for different PNN configurations as well as interval of retraining and results show that the PNN is a suitable prediction algorithm. The PNN firmware development including functional design and resource requirements are described.
Keyword (in Japanese) (See Japanese page) 
(in English) WLAN / probabilistic neural network / machine-learning / idle prediction / FPGA / implementation / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 457, SR2017-134, pp. 117-124, Feb. 2018.
Paper # SR2017-134 
Date of Issue 2018-02-21 (SR) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 SR2017-134

Conference Information
Committee RCS SR SRW  
Conference Date 2018-02-28 - 2018-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) YRP 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To SR 
Conference Code 2018-02-RCS-SR-SRW 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Prediction Scheme of WLAN Idle Status using Probabilistic Neural Network and Implementation on FPGA 
Sub Title (in English)  
Keyword(1) WLAN  
Keyword(2) probabilistic neural network  
Keyword(3) machine-learning  
Keyword(4) idle prediction  
Keyword(5) FPGA  
Keyword(6) implementation  
Keyword(7)  
Keyword(8)  
1st Author's Name Julian Webber  
1st Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
2nd Author's Name Abolfazl Mehbodniya  
2nd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
3rd Author's Name Yafei Hou  
3rd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
4th Author's Name Kazuto Yano  
4th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
5th Author's Name Makoto Usui  
5th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
6th Author's Name Tomoaki Kumagai  
6th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
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Speaker Author-1 
Date Time 2018-03-02 11:15:00 
Presentation Time 25 minutes 
Registration for SR 
Paper # SR2017-134 
Volume (vol) vol.117 
Number (no) no.457 
Page pp.117-124 
#Pages
Date of Issue 2018-02-21 (SR) 


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