Energy-Efficient Trajectory Planning With Joint Device Selection and Power Splitting for mmWaves-Enabled UAV-NOMA Networks-Reference-Cited by-同舟云学术

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Energy-Efficient Trajectory Planning With Joint Device Selection and Power Splitting for mmWaves-Enabled UAV-NOMA Networks

Published:2024 Issue: Volume:2 Page:617-632
ISSN:2831-316X
Container-title:IEEE Transactions on Machine Learning in Communications and Networking
language:
Short-container-title:Trans. Mach. Learn. Comm. Netw.

Author:

Gendia Ahmad¹^ORCID,Muta Osamu²^ORCID,Hashima Sherief³^ORCID,Hatano Kohei³^ORCID

Affiliation:

1. Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

2. Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

3. Computational Learning Theory Team, RIKEN-AIP, Fukuoka, Japan

Funder

Ministry of Higher Education (MoHE) of the Arab Republic of Egypt

Support Center for Advanced Telecommunications (SCAT) Technology Research Foundation

Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9882533/10356147/10517756.pdf?arnumber=10517756

Reference55 articles.

1. Joint 3D Trajectory Design and Time Allocation for UAV-Enabled Wireless Power Transfer Networks

2. A Survey on Beyond 5G Network With the Advent of 6G: Architecture and Emerging Technologies

3. 6G Vision and Requirements: Is There Any Need for Beyond 5G?

4. Toward Tactile Internet in Beyond 5G Era: Recent Advances, Current Issues, and Future Directions

5. Client-Centric Access Device Selection for Heterogeneous QoS Requirements in Beyond 5G IoT Networks

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