基于LSTM网络的OFDM系统信道估计研究与分析

Research and Analysis of Channel Estimation of OFDM System Based on LSTM Network

长短时记忆神经网络(LSTM)由于其在序列数据处理方面的显著优势,因此在无线通信领域得到广泛地应用。本文面向OFDM系统对基于LSTM网络的信道估计方法进行系统地研究与分析。该方法对输入的训练数据进行离线训练,使其学习到信道变化特征,获取信道状态信息预测结果。仿真结果显示,利用LSTM进行信道估计,其估计性能优于传统信道估计方法。

Due to its significant advantages in sequence data processing,long short-term memory neural network(LSTM)is diffusely applied in the field of wireless communication.This paper systematically researches and analyzes the channel estimation based on LSTM for OFDM system.This method performs offline training on the input training data,which makes it learn the channel change characteristics and obtain the prediction result of channel state information.The simulation results reveal that using LSTM for channel estimation has better estimation performance than traditional channel estimation methods.