Back to Search Start Over

Transformer-Based Detection for Highly Mobile Coded OFDM Systems.

Authors :
Wang, Leijun
Zhou, Wenbo
Tong, Zian
Zeng, Xianxian
Zhan, Jin
Li, Jiawen
Chen, Rongjun
Source :
Entropy. Jun2023, Vol. 25 Issue 6, p852. 15p.
Publication Year :
2023

Abstract

This paper is concerned with mobile coded orthogonal frequency division multiplexing (OFDM) systems. In the high-speed railway wireless communication system, an equalizer or detector should be used to mitigate the intercarrier interference (ICI) and deliver the soft message to the decoder with the soft demapper. In this paper, a Transformer-based detector/demapper is proposed to improve the error performance of the mobile coded OFDM system. The soft modulated symbol probabilities are computed by the Transformer network, and are then used to calculate the mutual information to allocate the code rate. Then, the network computes the codeword soft bit probabilities, which are delivered to the classical belief propagation (BP) decoder. For comparison, a deep neural network (DNN)-based system is also presented. Numerical results show that the Transformer-based coded OFDM system outperforms both the DNN-based and the conventional system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10994300
Volume :
25
Issue :
6
Database :
Academic Search Index
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
164637416
Full Text :
https://doi.org/10.3390/e25060852