Dynamic resource allocation in 5G networks using hybrid RL-CNN model for optimized latency and quality of service-Reference-Cited by-同舟云学术

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Dynamic resource allocation in 5G networks using hybrid RL-CNN model for optimized latency and quality of service

Published:2024-04-09 Issue: Volume: Page:1-25
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Karuppiyan Muthulakshmi¹,Subramani Hariharan²,Kandasamy Raju Shanthy³,Maradi Anthonymuthu Prakasam Manimekalai⁴

Affiliation:

1. Department of Electronics and Communication Engineering, Sri Krishna College of Technology, Coimbatore, India

2. Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India

3. Department of Electronics and Communication Engineering, Loyola Institute of Technology, Chennai, India

4. Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India

Funder

no funding associated

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0954898X.2024.2334282

Reference20 articles.

1. Optimal 5G network slicing using machine learning and deep learning concepts

2. Unlocking 5G Spectrum Potential for Intelligent IoT: Opportunities, Challenges, and Solutions

3. Dynamic link utilization empowered by reinforcement learning for adaptive storage allocation in MANET

4. Energy-Efficient QoE-Driven Radio Resource Management Method for 5G and Beyond Networks

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