A decoding method based on RNN for OvTDM

Overlapped X domain multiplexing (OvXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing Inter-Symbol Interference (ISI). However, the computational complexity of Maximum Likelihood Sequence Detection (MLSD) increases exponentially with the growth of spectral effici...

Full description

Saved in:
Bibliographic Details
Published in:China communications Vol. 17; no. 4; pp. 1 - 10
Main Authors: Hu, Yue, Wang, Yafeng, Wang, Haocheng
Format: Journal Article
Language:English
Published: China Institute of Communications 01.04.2020
Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Post and Telecommunications, Beijing 100876, China
Subjects:
Complexity theory
Encoding
fast decoding algorithm
Maximum likelihood decoding
maximum likelihood sequence detection (MLSD)
Multiplexing
overlapped X-domain multiplexing (OvXDM)
recurrent neural network (RNN)
Recurrent neural networks
Spectral efficiency
recurrent neural network (RNN)
fast decoding algorithm
maximum likelihood sequence detection (MLSD)
overlapped X-domain multiplex-ing (OvXDM)
ISSN:1673-5447
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Overlapped X domain multiplexing (OvXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing Inter-Symbol Interference (ISI). However, the computational complexity of Maximum Likelihood Sequence Detection (MLSD) increases exponentially with the growth of spectral efficiency in OvXDM, which is unbearable for practical implementations. This paper proposes an OvTDM decoding method based on Recurrent Neural Network (RNN) to realize fast decoding of OvTDM system, which has lower decoding complexity than the traditional fast decoding method. The paper derives the mathematical model of the OvTDM decoder based on RNN and constructs the decoder model. And we compare the performance of the proposed decoding method with the MLSD algorithm and the Fano algorithm. It's verified that the proposed decoding method exhibits a higher performance than the traditional fast decoding algorithm, especially for the scenarios of a high overlapped multiplexing coefficient.
ISSN:1673-5447
DOI:10.23919/JCC.2020.04.001