Technology of Network & Communication
|
1507-1510

Deep learning based NBI mitigation method in OFDM systems

Ma Tao1a
Li Yue2
Yang Feng1b
Ding Lianghui1a
1. a. Institute of Image Communication & Network Engineering, b. Institute of Wireless Communication Technology, Shanghai Jiao Tong University, Shanghai 200240, China
2. Naval Research Institute, Beijing 100161, China

Abstract

Considering the performance deterioration of OFDM system due to narrowband interference(NBI), this paper employed deep learning into NBI mitigation of OFDM systems and proposed two structures with CNN. These two structures firstly pre-processed the received data in receiver, then adopted CNN to exploit the interference estimation in time domain. Finally it removed the impact of NBI from received signal. The simulation results demonstrate that the two systems can learn the interference effectively and improve system performance.

Foundation Support

国家自然科学基金资助项目(61771309,61671301,61420106008,61521062)
上海市重点实验室基金资助项目(STCSM15DZ2270400)
数据链技术重点实验室开放基金资助项目(CLDL-20162306)
上海交通大学医工交叉基金资助项目(YG2017QN47)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.11.0834
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 5
Section: Technology of Network & Communication
Pages: 1507-1510
Serial Number: 1001-3695(2020)05-045-1507-04

Publish History

[2020-05-05] Printed Article

Cite This Article

马涛, 李悦, 杨峰, 等. 基于深度学习的OFDM系统窄带干扰消除方法研究 [J]. 计算机应用研究, 2020, 37 (5): 1507-1510. (Ma Tao, Li Yue, Yang Feng, et al. Deep learning based NBI mitigation method in OFDM systems [J]. Application Research of Computers, 2020, 37 (5): 1507-1510. )

About the Journal

  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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