Multi-Band Wireless Communication Networks: Fundamentals, Challenges, and Resource Allocation-Reference-Cited by-同舟云学术

Multi-Band Wireless Communication Networks: Fundamentals, Challenges, and Resource Allocation

Published:2024-07 Issue:7 Volume:72 Page:4333-4383
ISSN:0090-6778
Container-title:IEEE Transactions on Communications
language:
Short-container-title:IEEE Trans. Commun.

Author:

Aboagye Sylvester¹^ORCID,Amin Saeidi Mohammad¹,Tabassum Hina¹^ORCID,Tayyar Yamin¹,Hossain Ekram²^ORCID,Yang Hong-Chuan³^ORCID,Alouini Mohamed-Slim⁴^ORCID

Affiliation:

1. Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada

2. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada

3. Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada

4. Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

Funder

Discovery Grant

Natural Sciences and Engineering Research Council of Canada

Discovery Grant from the Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/26/10604460/10438479.pdf?arnumber=10438479

Reference338 articles.

1. Evolution Toward 6G Multi-Band Wireless Networks: A Resource Management Perspective

2. A Survey of Free Space Optics (FSO) Communication Systems, Links, and Networks

3. Survey on Terahertz Nanocommunication and Networking: A Top-Down Perspective

4. Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

5. Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey

Cited by 2 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. Optimizing Femtocell Networks: A Novel Game Theory Based Power Management Model for Enhanced SINR and Energy Efficiency;IEEE Access;2024

2. Collaborative Deep Reinforcement Learning in 6G Integrated Satellite-Terrestrial Networks: Paradigm, Solutions, and Trends;IEEE Communications Magazine;2024