Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2026-07-22 15:10
ASSET: An Ensemble-Learning-Based Framework for Adaptive Signal Strength Estimation and Tracking -- Part I: Integrating Spatial Diversity and Prediction Uncertainty for Measurement-Efficient Active Sampling --
Ou Zhao, Huan-Bang LI, Hirokazu Sawada (NICT), Daisuke Matsuo, Yasushi Fuwa (Shishu Univ.), Takeshi Matsumura (NICT), Lin Shan (Shishu Univ.) RCC2026-28
Abstract (in Japanese) (See Japanese page) 
(in English) This study introduces the first-stage architecture of the ASSET framework for adaptive RSS prediction, as well as tracking and updating in evolving wireless environments. To enable cross-domain adaptation under limited measurement budgets, we utilize an AI Committee of multiple convolutional neural networks to quantify prediction uncertainty, driving a novel uncertainty-aware regional active sampling (URAS) strategy for practical field measurements. Validated via extensive 920 MHz field experiments across three distinct Japanese regions, results show that effective adaptation requires a fine-grained balance among information acquisition, sample diversity, and measurement feasibility. While exhaustive random sampling is practically unfeasible, URAS successfully balances uncertainty levels and spatial constraints, achieving acceptable prediction performance and high measurement efficiency across diverse propagation environments.
Keyword (in Japanese) (See Japanese page) 
(in English) Wireless communications / Received signal strength prediction / Transfer learning / Ensemble learning / Active sampling / Field experiments / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 119, RCC2026-28, pp. 32-37, July 2026.
Paper # RCC2026-28 
Date of Issue 2026-07-14 (RCC) 
ISSN 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 RCC2026-28

Conference Information
Committee SR RCC  
Conference Date 2026-07-21 - 2026-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Yamaguchi 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IoT, Wireless Distributed Networks, Sensor Networks, Control Communications, Network Control, General Topics 
Paper Information
Registration To RCC 
Conference Code 2026-07-SR-RCC 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) ASSET: An Ensemble-Learning-Based Framework for Adaptive Signal Strength Estimation and Tracking 
Sub Title (in English) Part I: Integrating Spatial Diversity and Prediction Uncertainty for Measurement-Efficient Active Sampling 
Keyword(1) Wireless communications  
Keyword(2) Received signal strength prediction  
Keyword(3) Transfer learning  
Keyword(4) Ensemble learning  
Keyword(5) Active sampling  
Keyword(6) Field experiments  
Keyword(7)  
Keyword(8)  
1st Author's Name Ou Zhao  
1st Author's Affiliation NICT (NICT)
2nd Author's Name Huan-Bang LI  
2nd Author's Affiliation NICT (NICT)
3rd Author's Name Hirokazu Sawada  
3rd Author's Affiliation NICT (NICT)
4th Author's Name Daisuke Matsuo  
4th Author's Affiliation Shishu Univ. (Shishu Univ.)
5th Author's Name Yasushi Fuwa  
5th Author's Affiliation Shishu Univ. (Shishu Univ.)
6th Author's Name Takeshi Matsumura  
6th Author's Affiliation NICT (NICT)
7th Author's Name Lin Shan  
7th Author's Affiliation Shishu Univ. (Shishu Univ.)
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2026-07-22 15:10:00 
Presentation Time 25 minutes 
Registration for RCC 
Paper # RCC2026-28 
Volume (vol) vol.126 
Number (no) no.119 
Page pp.32-37 
#Pages 6 
Date of Issue 2026-07-14 (RCC) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan