Residual-Aided End-to-End Learning of Communication System Without Known Channel-Reference-Cited by-同舟云学术

Residual-Aided End-to-End Learning of Communication System Without Known Channel

Published:2022-06 Issue:2 Volume:8 Page:631-641
ISSN:2332-7731
Container-title:IEEE Transactions on Cognitive Communications and Networking
language:
Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

Jiang Hao¹^ORCID,Bi Shuangkaisheng²^ORCID,Dai Linglong¹^ORCID,Wang Hao³^ORCID,Zhang Jiankun³^ORCID

Affiliation:

1. Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China

2. Standard Patent Department, Huawei Technologies Company Ltd., Shenzhen, China

3. Algorithm Department, Beijing Huawei Technologies Company Ltd., Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/6687307/9790075/09741252.pdf?arnumber=9741252

Reference34 articles.

1. Deep Learning for Beamspace Channel Estimation in Millimeter-Wave Massive MIMO Systems

2. End-to-End Deep Learning of Optical Fiber Communications

3. DeepMIMO: A generic deep learning dataset for millimeter wave and massive MIMO applications;alkhateeb;Proc IEEE Inf Theory Appl Workshop (ITA),2019

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