Self-Optimized Agent for Load Balancing and Energy Efficiency: A Reinforcement Learning Framework With Hybrid Action Space-Reference-Cited by-同舟云学术

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Self-Optimized Agent for Load Balancing and Energy Efficiency: A Reinforcement Learning Framework With Hybrid Action Space

Published:2024 Issue: Volume:5 Page:4902-4919
ISSN:2644-125X
Container-title:IEEE Open Journal of the Communications Society
language:
Short-container-title:IEEE Open J. Commun. Soc.

Author:

Salama Attia Bishoy¹,Elgharably Aamen²,Nabil Aboelwafa Mariam³^ORCID,Alsuhli Ghada⁴,Banawan Karim²^ORCID,Seddik Karim G.¹^ORCID

Affiliation:

1. Electronics and Communications Engineering, The American University in Cairo, New Cairo, Egypt

2. Electrical Engineering Department, Alexandria University, Alexandria, Egypt

3. Computer, Communications and Autonomous Systems Department, NewGiza University, 6th of October City, Egypt

4. Department of Computer and Information Engineering, Khalifa University, Abu Dhabi, UAE

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8782661/10362961/10599522.pdf?arnumber=10599522

Reference60 articles.

1. Load balancing optimization in LTE/LTE-a cellular networks: A review;Mishra;arXiv:1412.7273,2014

2. A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

3. Energy management in Wireless Sensor Networks: A survey

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