基于深度学习的MIMO系统联合信号检测与信道译码  

Joint signal detection and channel decoding for MIMO systemsbased on deep learning

作　　者：李国权[1,2] 杨鹏 马珺杰[3] 徐永海 林金朝 LI Guoquan;YANG Peng;MA Junjie;XU Yonghai;LIN Jinzhao(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,P.R.China;Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology,Chongqing 400065,P.R.China;Shanxi Railway and Logistics Industry Group Co.Ltd.,Xi’an 710076,P.R.China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]光电信息感测与传输技术重庆市重点实验室,重庆400065 [3]陕西铁路物流集团有限公司,西安710076

出　　处：《重庆邮电大学学报（自然科学版）》2021年第2期176-184,共9页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

基　　金：国家重点研发计划(2019YFC1511300);重庆市自然科学基金面上项目(cstc2019jcyj-msxmx0666)。

摘　　要：为进一步提高多输入多输出(multiple-input multiple-output, MIMO)系统性能,研究了深度学习方法来联合解决MIMO系统信号检测与信道译码问题。通过将深度神经网络、自动编码器神经网络与传统MIMO通信系统的物理层架构进行有机融合,构建了基于神经网络的MIMO系统模型,可获取系统发射端的信息比特或码字及信道状态信息,采用了端对端的训练方式,使不同神经网络模型可学习系统收发端的信息比特与码字的映射关系,联合实现了MIMO系统信号检测和信道译码,同时具有较低的复杂度。仿真结果表明,相比一些传统检测和译码算法,所提方法具有较优的检测和译码性能。In order to further improve the performance of multiple input multiple output systems,a deep learning method is studied to jointly solve the problem of signal detection and channel decoding.Two neural networks,deep neural network and autoencoder neural network,are organically integrated with the physical layer architecture of the traditional multiple-input multiple-output(MIMO)communication systems to build MIMO systems model based on the neural network,which can obtain the information bits or codewords at the transmitter and channel state information.An end-to-end training mode is adopted,so that the different neural network models can learn the mapping relationship between the information bits and codewords on the transmitting and receiving end of the MIMO systems.Therefore,signal detection and channel decoding can be jointly realized with lower complexity.Simulation results show that the proposed method can outperform the performance of some traditional detection and decoding algorithms.

关 键 词：多输入多输出(MIMO)系统 深度学习 信号检测 信道译码 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]