Deep Learning Driven Buffer-Aided Cooperative Networks for B5G/6G: Challenges, Solutions, and Future Opportunities-Reference-Cited by-同舟云学术

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Deep Learning Driven Buffer-Aided Cooperative Networks for B5G/6G: Challenges, Solutions, and Future Opportunities

Published:2024-08 Issue:4 Volume:31 Page:215-222
ISSN:1536-1284
Container-title:IEEE Wireless Communications
language:
Short-container-title:IEEE Wireless Commun.

Author:

Xu Peng¹,Chen Gaojie²,Quan Jianping¹,Huang Chong²,Krikidis Ioannis³,Wong Kai-Kit⁴,Chae Chan-Byoung⁵

Affiliation:

1. Chongqing University of Posts and Telecommunications,China

2. Sun Yat-sen University,China

3. University of Cyprus,Cyprus

4. University College London,U.K.

5. Yonsei University,South Korea

Funder

Chongqing Natural Science Foundation Innovation and Development Joint Fund

Natural Science Foundation of Chongqing

IITP

NRF through MSIT, Korea

European Union's Horizon 2020

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7742/10628020/10500738.pdf?arnumber=10500738

Reference15 articles.

1. Toward Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication, and Security

2. Buffer-aided cooperative communications: opportunities and challenges

3. Low-Delay Path Selection for Cluster-Based Buffer-Aided Vehicular Communications

4. Modeling and Performance Analysis for Satellite Data Relay Networks Using Two-Dimensional Markov-Modulated Process

5. Throughput Maximization of Mixed FSO/RF UAV-Aided Mobile Relaying With a Buffer

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