A Decoding Method Based on RNN for OvTDM  

作　　者：Yue Hu Yafeng Wang Haocheng Wang 

机构地区：[1]Key Laboratory of Universal Wireless Communication,Ministry of Education,Beijing University of Post and Telecommunications,Beijing 100876,China

出　　处：《China Communications》2020年第4期1-10,共10页中国通信（英文版）

基　　金：supported by the National Natural Science Foundation of China under Grant No.61871049.

摘　　要：Overlapped X domain multiplexing(Ov XDM) 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 Ov XDM, which is unbearable for practical implementations. This paper proposes an Ov TDM decoding method based on Recurrent Neural Network(RNN) to realize fast decoding of Ov TDM system, which has lower decoding complexity than the traditional fast decoding method. The paper derives the mathematical model of the Ov TDM 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.

关 键 词：overlapped X-domain multiplexing(OvXDM) MAXIMUM LIKELIHOOD sequence detection(MLSD) RECURRENT neural network(RNN) fast DECODING algorithm 

分 类 号：TN929.5[电子电信—通信与信息系统]