一种基于深度学习的物联网信道状态信息获取算法

廖勇; 姚海梅; 花远肖

doi:10.11959/j.issn.2096-3750.2019.00085

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一种基于深度学习的物联网信道状态信息获取算法

理论与技术 | 更新时间：2024-06-05

- 一种基于深度学习的物联网信道状态信息获取算法
- Channel state information acquisition algorithm based on deep learning for IoT
- 物联网学报 2019年3卷第1期页码：8-13
- 作者机构：
- 作者简介：
  
  [ "廖勇（1982- ），男，四川自贡人，博士，重庆大学副研究员、博士生导师，主要研究方向为下一代无线通信技术、AI 及其在行业中的应用。" ]
  [ "姚海梅（1992- ），女，江西吉安人，重庆大学硕士生，主要研究方向为AI及其在无线通信中的应用。" ]
  [ "花远肖（1994- ），男，四川阆中人，重庆大学硕士生，主要研究方向为AI及其在无线通信中的应用。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61501066);重庆市基础与前沿研究计划项目(cstc2015jcyjA40003);中央高校基本科研业务费基金资助项目;The Fundamental Research Funds for the Central Universities(106112017CDJXY500001)
- DOI：10.11959/j.issn.2096-3750.2019.00085
  中图分类号： TN929.5
- 纸质出版日期：2019-03-30，
  
  网络出版日期：2019-03，
- 稿件说明：
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廖勇, 姚海梅, 花远肖. 一种基于深度学习的物联网信道状态信息获取算法[J]. 物联网学报, 2019,3(1):8-13.

YONG LIAO, HAIMEI YAO, YUANXIAO HUA. Channel state information acquisition algorithm based on deep learning for IoT. [J]. Chinese journal on internet of things, 2019, 3(1): 8-13.
廖勇, 姚海梅, 花远肖. 一种基于深度学习的物联网信道状态信息获取算法[J]. 物联网学报, 2019,3(1):8-13. DOI： 10.11959/j.issn.2096-3750.2019.00085.

YONG LIAO, HAIMEI YAO, YUANXIAO HUA. Channel state information acquisition algorithm based on deep learning for IoT. [J]. Chinese journal on internet of things, 2019, 3(1): 8-13. DOI： 10.11959/j.issn.2096-3750.2019.00085.

摘要

针对基于大规模多输入多输出（MIMO）的物联网系统中用户侧将信道状态信息（CSI）发送到基站时反馈开销大的问题，提出一种基于深度学习的CSI反馈网络用来反馈CSI。该网络首先使用卷积神经网络（CNN）提取信道特征矢量和最大池化层通过降维来达到压缩CSI的目的，然后使用全连接和CNN将压缩的CSI解压，恢复原始信道。仿真结果表明，与现有的CSI反馈方法相比，所提出的CSI反馈网络恢复的CSI更接近原始信道，重构质量明显提高。

Abstract

To solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system

a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly

the proposed network used convolutional neural network (CNN) to extract channel feature vectors and maxpooling to compress the data.Then the compressed CSI was decompressed by using full connection and CNN to restore the original channel.The simulation results show that compared with the existing CSI feedback methods

the CSI recovered by the proposed CSI feedback network is closer to the original channel

and the reconstruction quality is improved significantly.

关键词

大规模MIMO物联网CSI反馈深度学习

Keywords

massive MIMOInternet of thingsCSI feedbackdeep learning

references

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WEN C K, SHIH W T, JIN S . Deep learning for massive MIMO CSI feedback[J]. IEEE Wireless Communications Letters, 2018,7(5): 748-751.

WANG T, WEN C K, JIN S ,et al. Deep learning-based CSI feedback approach for time-varying massive MIMO channels[J]. IEEE Wireless Communications Letters, 2018: 1-4.

SIM M S, PARK J, CHAE C ,et al. Compressed channel feedback for correlated massive MIMO systems[C]// 2014 IEEE Globecom Workshops (GC Wkshps). IEEE, 2014: 327-332.

TIAN R, LIANG Y, LI T . Overlapping user grouping in IoT oriented massive MIMO systems[C]// International Conference on Computing. IEEE, 2017: 255-259.

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