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 2026-06-17 18:10
Evaluation of AI/ML-Based TRP Selection Method to Maximize System Throughput Using a 6G System-Level Simulator
Yuta Hayashi, Hiromasa Terashi, Dan Morhi, Satoshi Suyama, Yuyuan Chang, Huiling Jiang (NTT DOCOMO) RCS2026-48
Abstract (in Japanese) (See Japanese page) 
(in English) The sixth-generation mobile communication system (6G) sets forth a wide range of requirements, including extreme-high-speed and high-capacity communications. To realize 6G, the advancement of wireless communication technologies and the exploration of new network topologies are essential. Furthermore, as a newly added element in 6G, the use of artificial intelligence (AI) and machine learning (ML) is being investigated to control and operate wireless communication systems more intelligently. Therefore, the authors have been developing a 6G system-level simulator (6G simulator) to evaluate and visualize 6G-oriented technologies. Our previous works include the implementation and evaluation of new candidate frequency bands such as the sub-terahertz and centimeter-wave bands, the integration of advanced distributed network technologies like reconfigurable intelligent surfaces (RIS), and the deployment of AI/ML-driven predictive control techniques for communication quality. In this report, we further advance the AI/ML scenarios implemented in the 6G simulator by introducing a transmission and reception point (TRP) selection scenario aimed at maximizing system throughput. We conduct visualization and performance evaluation, compare the performance using different learning methods, and clarify an effective TRP selection approach to maximize system throughput.
Keyword (in Japanese) (See Japanese page) 
(in English) 6G / System level simulator / AI / Machine learning / TRP selection / System throughput maximization / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 72, RCS2026-48, pp. 129-134, June 2026.
Paper # RCS2026-48 
Date of Issue 2026-06-10 (RCS) 
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 RCS2026-48

Conference Information
Committee RCS  
Conference Date 2026-06-17 - 2026-06-19 
Place (in Japanese) (See Japanese page) 
Place (in English) The Ohama Nobumoto Memorial Hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) First Presentation in IEICE Technical Committee, Resource Control, Scheduling, Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2026-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of AI/ML-Based TRP Selection Method to Maximize System Throughput Using a 6G System-Level Simulator 
Sub Title (in English)  
Keyword(1) 6G  
Keyword(2) System level simulator  
Keyword(3) AI  
Keyword(4) Machine learning  
Keyword(5) TRP selection  
Keyword(6) System throughput maximization  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuta Hayashi  
1st Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
2nd Author's Name Hiromasa Terashi  
2nd Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
3rd Author's Name Dan Morhi  
3rd Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
4th Author's Name Satoshi Suyama  
4th Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
5th Author's Name Yuyuan Chang  
5th Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
6th Author's Name Huiling Jiang  
6th Author's Affiliation NTT DOCOMO, INC. (NTT DOCOMO)
7th Author's Name  
7th Author's Affiliation ()
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 2026-06-17 18:10:00 
Presentation Time 20 minutes 
Registration for RCS 
Paper # RCS2026-48 
Volume (vol) vol.126 
Number (no) no.72 
Page pp.129-134 
#Pages 6 
Date of Issue 2026-06-10 (RCS) 

[Return to Top Page]

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