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Paper Abstract and Keywords
Presentation 2026-06-18 10:45
A Study on Neural Network-Based Spectrum Shaping Filter Design for FTN Transmissions
Shotaro Yajima, Shinsuke Ibi, Hisato Iwai (Doshisha Univ.) RCS2026-54
Abstract (in Japanese) (See Japanese page) 
(in English) Faster-than-Nyquist (FTN) transmission can improve data rate by superimposing symbols at intervals shorter than the Nyquist interval. However, as the data rate increases, inter-symbol interference (ISI) occurs, and the accuracy of signal detection decreses.

Conventionally, a root raised cosine (RRC) filter is used as a spectrum shaping filter in FTN transmission. Due to the non-Gaussian ISI in FTN transmission, however, the RRC filter is not necessarily the optimal spectrum shaping filter.

In this paper, a data-driven optimization of spectrum shaping filters using a neural network (NN) is investigated without restricting to the RRC filter. A wireless autoencoder (WAE), which is a type of deep learning framework, is constructed by employing the NN-based modulator and spectrum shaping filter at the transmitter and minimum mean square error (MMSE) detection at the receiver. This approach aims to improve the symbol error rate (SER) performance while suppressing spectral leakage.
Keyword (in Japanese) (See Japanese page) 
(in English) FTN transimissions / spectrum shaping filter / neural network / wireless autoencoder / signal constellation / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 72, RCS2026-54, pp. 164-169, June 2026.
Paper # RCS2026-54 
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 RCS2026-54

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) A Study on Neural Network-Based Spectrum Shaping Filter Design for FTN Transmissions 
Sub Title (in English)  
Keyword(1) FTN transimissions  
Keyword(2) spectrum shaping filter  
Keyword(3) neural network  
Keyword(4) wireless autoencoder  
Keyword(5) signal constellation  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shotaro Yajima  
1st Author's Affiliation Doshisha University (Doshisha Univ.)
2nd Author's Name Shinsuke Ibi  
2nd Author's Affiliation Doshisha University (Doshisha Univ.)
3rd Author's Name Hisato Iwai  
3rd Author's Affiliation Doshisha University (Doshisha Univ.)
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Speaker Author-1 
Date Time 2026-06-18 10:45:00 
Presentation Time 10 minutes 
Registration for RCS 
Paper # RCS2026-54 
Volume (vol) vol.126 
Number (no) no.72 
Page pp.164-169 
#Pages 6 
Date of Issue 2026-06-10 (RCS) 

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