When DSA Meets SWIPT: A Joint Power Allocation and Time Splitting Scheme Based on Multi-Agent Deep Reinforcement Learning-Reference-Cited by-同舟云学术

When DSA Meets SWIPT: A Joint Power Allocation and Time Splitting Scheme Based on Multi-Agent Deep Reinforcement Learning

Published:2023-02 Issue:2 Volume:72 Page:2740-2744
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Zhang Renhao¹,Li Xuanheng¹^ORCID,Zhao Nan¹^ORCID

Affiliation:

1. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

Funder

National Natural Science Foundation of China

Dalian Talents Innovation Support Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10043591/09915473.pdf?arnumber=9915473

Reference17 articles.

1. Antenna Clustering for Simultaneous Wireless Information and Power Transfer in a MIMO Full-Duplex System: A Deep Reinforcement Learning-Based Design

2. Adaptive Rate and Energy Harvesting Interval Control Based on Reinforcement Learning for SWIPT

3. Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks

4. Multi-Agent Deep Reinforcement Learning for Distributed Resource Management in Wirelessly Powered Communication Networks

5. Sum-Rate Maximization for Multiuser MIMO Wireless Powered Communication Networks

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