Joint Spectrum and Power Allocation in Wireless Network: A Two-Stage Multi-Agent Reinforcement Learning Method
Author:
Affiliation:
1. School of Mathematics, Southeast University, Nanjing, China
2. Purple Mountain Laboratories, Nanjing, China
3. Marketing Service Center (Metrology Center), State Grid Jiangsu Electric Power Company, Ltd., Nanjing, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Jiangsu Provincial Key Laboratory of Networked Collective Intelligence
Guangdong Basic, Applied Basic Research Foundation
Natural Science Foundation of Jiangsu Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/7433297/10538459/10438524.pdf?arnumber=10438524
Reference35 articles.
1. A Survey of Energy Efficient Resource Management Techniques for Multicell Cellular Networks
2. Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open Challenges
3. Multi-UAV Mobile Edge Computing and Path Planning Platform Based on Reinforcement Learning
4. Optimal Computational Offloading and Content Caching in Wireless Heterogeneous Mobile Edge Computing Systems With Hopfield Neural Networks
5. A DRL-Driven Intelligent Joint Optimization Strategy for Computation Offloading and Resource Allocation in Ubiquitous Edge IoT Systems
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