人工智能辅助的信道估计最新研究进展

李坤; 张静; 李潇; 金石

doi:10.11959/j.issn.1000-0801.2020288

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人工智能辅助的信道估计最新研究进展

专题：智能通信技术 | 更新时间：2024-06-05

- 人工智能辅助的信道估计最新研究进展
- An overview of artificial intelligence assisted channel estimation
- 电信科学 2020年36卷第10期页码：46-55
- 作者机构：
- 作者简介：
  
  [ "李坤（1995- ），男，东南大学移动通信国家重点实验室硕士生，主要研究方向为无线通信物理层技术与深度学习结合" ]
  [ "张静（1993- ），女，东南大学移动通信国家重点实验室博士生，主要研究方向为 5G移动通信物理层关键技术、机器学习等" ]
  [ "李潇（1982- ），女，东南大学移动通信国家重点实验室副教授、硕士生导师，主要研究方向为移动通信理论与关键技术、人工智能在无线通信中的应用等" ]
  [ "金石（1974- ），男，东南大学移动通信国家重点实验室教授、博士生导师，主要研究方向为移动通信理论与关键技术、物联网理论与关键技术以及人工智能在无线通信中的应用等" ]
- 基金信息：
  
  国家重点研发计划项目;The National Key Research and Development Program(2018YFA0701602);国家自然科学基金杰出青年科学基金资助项目;NSFC for Distinguished Young Scholars of China(61625106);深圳基础研究基金资助项目;The Shenzhen Basic Research Foundation(JCYJ20170412104656685)
- DOI：10.11959/j.issn.1000-0801.2020288
  中图分类号： TN929
- 网络出版日期：2020-10，
  
  纸质出版日期：2020-10-20
- 稿件说明：
移动端阅览
李坤, 张静, 李潇, 等. 人工智能辅助的信道估计最新研究进展[J]. 电信科学, 2020,36(10):46-55.

Kun LI, Jing ZHANG, Xiao LI, et al. An overview of artificial intelligence assisted channel estimation[J]. Telecommunications science, 2020, 36(10): 46-55.
李坤, 张静, 李潇, 等. 人工智能辅助的信道估计最新研究进展[J]. 电信科学, 2020,36(10):46-55. DOI： 10.11959/j.issn.1000-0801.2020288.

Kun LI, Jing ZHANG, Xiao LI, et al. An overview of artificial intelligence assisted channel estimation[J]. Telecommunications science, 2020, 36(10): 46-55. DOI： 10.11959/j.issn.1000-0801.2020288.

摘要

作为第六代移动通信发展的主流方向，智能通信正在蓬勃发展中，且初步展示了其与传统通信方法相比的优势。人工智能辅助的信道估计作为智能通信的重要组成，在已有的研究成果中展示了其相比传统信道估计算法的优越性，尤其是基于压缩感知技术、超分辨技术、残差学习等开展的信道估计研究均获得了丰硕的成果。针对人工智能辅助的信道估计技术，结合近来学术界最新研究成果，分别从基于深度卷积神经网络、基于深度循环神经网络、基于超分辨技术、基于压缩感知技术 4 个维度展示了人工智能辅助的信道估计的全貌。最后，对比总结了4类信道估计方法优劣及其未来研究方向，展望了信道估计与深度学习结合的广阔前景。

Abstract

As the mainstream of the sixth generation mobile communication development

intelligent communication assisted by artificial intelligence technology is vigorously developing

and has initially demonstrated its advantages over traditional communication methods.As an important component of intelligent communication

artificial intelligence assisted channel estimation shows its superiority over traditional channel estimation algorithms in the existing research results

especially those researches based on compressive sensing technology

super resolution technology

residual learning

etc.Aiming at the channel estimation technology assisted by artificial intelligence

combined with the latest research results in the academic field

the whole picture of the channel estimation technology assisted by artificial intelligence from the four dimensions of deep convolution neural network

deep recurrent neural network

super-resolution technology and compression sensing technology were showed.Finally

the advantages and disadvantages of four kinds of channel estimation methods and their future research directions

and the broad prospect of the combination of channel estimation and deep learning were looked forward.

关键词

Keywords

references

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