Hybrid neural coded modulation: Design and training methodsopen access
- Authors
- Lim, Sung Hoon; Han, Jiyong; Noh, Wonjong; Song, Yujae; Jeon, Sang-Woon
- Issue Date
- Mar-2022
- Publisher
- 한국통신학회
- Keywords
- Machine learning; Neural networks; Modulation; Channel coding; Generalized mutual information
- Citation
- ICT Express, v.8, no.1, pp 25 - 30
- Pages
- 6
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- ICT Express
- Volume
- 8
- Number
- 1
- Start Page
- 25
- End Page
- 30
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/111379
- DOI
- 10.1016/j.icte.2022.01.018
- ISSN
- 2405-9595
- Abstract
- We propose a hybrid coded modulation scheme which composes of inner and outer codes. The outer-code can be any standard binary linear code with efficient soft decoding capability (e.g. low-density parity-check (LDPC) codes). The inner code is designed using a deep neural network (DNN) which takes the channel coded bits and outputs modulated symbols. For training the DNN, we propose to use a loss function that is inspired by the generalized mutual information. The resulting constellations are shown to outperform the conventional quadrature amplitude modulation (QAM) based coding scheme for modulation order 16 and 64 with 5G standard LDPC codes. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.
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Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles
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