A decoding method based on RNN for OvTDM

Abstract

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.