Optimizing Resource Allocation in MEC-Enabled CR-NOMA-Assisted IoT Networks: A DRL-Driven Strategy-Reference-Cited by-同舟云学术

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Optimizing Resource Allocation in MEC-Enabled CR-NOMA-Assisted IoT Networks: A DRL-Driven Strategy

Published:2024-04-21 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE Wireless Communications and Networking Conference (WCNC)
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Author:

Qaiser Muhammad Taha¹,Sohail Muhammad Sarmad¹,Shafqat Minahil¹,Ullah Syed Asad¹,Jung Haejoon²,Hassan Syed Ali¹

Affiliation:

1. School of Electrical Engineering & Computer Science (SEECS), National University of Sciences & Technology (NUST),Islamabad,Pakistan,44000

2. Kyung Hee University,Department of Electronics and Information Convergence Engineering,Yongin,South Korea,17104

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10570463/10570502/10570963.pdf?arnumber=10570963

Reference11 articles.

1. Cooperative Computational Offloading in Mobile Edge Computing for Vehicles: A Model-Based DNN Approach

2. Deep Reinforcement Learning-Based Resource Management for Flexible Mobile Edge Computing: Architectures, Applications, and Research Issues

3. A New QoS-Guarantee Strategy for NOMA Assisted Semi-Grant-Free Transmission

4. Intelligent Offloading in Multi-Access Edge Computing: A State-of-the-Art Review and Framework

5. Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices

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