Convolutional-Type Neural Networks for Fading Channel Forecasting-Reference-Cited by-同舟云学术

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Convolutional-Type Neural Networks for Fading Channel Forecasting

Published:2020 Issue: Volume:8 Page:193075-193090
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ahrens Lia^ORCID,Ahrens Julian^ORCID,Schotten Hans Dieter

Funder

Federal Ministry of Education and Research of the Federal Republic of Germany through the FunKI Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09235319.pdf?arnumber=9235319

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Physical Layer Security Performance Prediction Based on Deep Learning;2023 2nd International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT);2023-08-04

2. Machine Learning Based Channel Prediction for NR Type II CSI Reporting;ICC 2023 - IEEE International Conference on Communications;2023-05-28

3. An Efficient Wireless Propagation Loss Prediction Model Based on 3-D Terrain Features Extracted by Deep Learning;IEEE Antennas and Wireless Propagation Letters;2023-05

4. Combining AI/ML and PHY Layer Rule Based Inference - Some First Results;2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC);2022-07-04

5. Hybrid Neural Network-Based Fading Channel Prediction for Link Adaptation;IEEE Access;2021

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