Res-DNN based signal detection algorithm for end-to-end MIMO systems

Guoquan LI; Yonghai XU; Jinzhao LIN; Zhengwen HUANG

doi:10.11959/j.issn.2096-3750.2022.00256

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Res-DNN based signal detection algorithm for end-to-end MIMO systems

Theory and Technology | 更新时间：2024-06-05

- Res-DNN based signal detection algorithm for end-to-end MIMO systems
- Chinese Journal on Internet of Things Vol. 6, Issue 1, Pages: 65-72(2022)
- 作者机构：
  
  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. 伦敦布鲁内尔大学电子与计算机工程系，英国伦敦 UB8 3PH
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2022.00256
  CLC： TN92
- Published：30 March 2022，
  
  Published Online：2022-03，
- 稿件说明：
移动端阅览
GUOQUAN LI, YONGHAI XU, JINZHAO LIN, et al. Res-DNN based signal detection algorithm for end-to-end MIMO systems. [J]. Chinese journal on internet of things, 2022, 6(1): 65-72.
DOI：

GUOQUAN LI, YONGHAI XU, JINZHAO LIN, et al. Res-DNN based signal detection algorithm for end-to-end MIMO systems. [J]. Chinese journal on internet of things, 2022, 6(1): 65-72. DOI： 10.11959/j.issn.2096-3750.2022.00256.

摘要

深度学习可通过提取无线通信数据的内在特征提升信号检测效果。针对MIMO系统信号检测存在的性能与复杂度的折中问题，提出一种基于深度学习的端到端MIMO系统信号检测方案。基于残差深度神经网络的编码器和解码器分别替代无线通信系统的发送端和接收端，将它们看作一个整体通过端到端的方式进行训练。编码器首先对输入数据进行特征提取，进而建立通信模型并传入迫零检测器进行初步检测，最终通过解码器重构得出检测信号。仿真结果表明，所提检测方案优于同类型算法，并且在牺牲一定时间复杂度的情况下，检测性能明显优于MMSE检测算法。

Abstract

Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection

an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively

and they were trained in an end-to-end manner as a whole.Firstly

the features of the input data were extracted by encoder

then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally

the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm

and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.

关键词

深度学习MIMO系统信号检测残差深度神经网络端到端

Keywords

deep learningMIMO systemsignal detectionRes-DNNend-to-end

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