Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network-Reference-Cited by-同舟云学术

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Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

Published:2023 Issue:1 Volume:46 Page:73-92
ISSN:0267-6192
Container-title:Computer Systems Science and Engineering
language:en
Short-container-title:

Author:

Amine Ouamri Mohamed,Alkanhel Reem,Singh Daljeet,M. El-kenaway El-sayed,S. M. Ghoneim Sherif

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.techscience.com/csse/v46n1/51329/pdf

Reference42 articles.

1. Resource allocation in a multi-carrier cell using scheduler algorithms;Sylia,2018

2. A survey of resource management toward 5G radio access networks;Olwal;IEEE Communications Surveys & Tutorials,2016

3. Millimeter wave mobile communications for 5G cellular: It will work!;Rappaport;IEEE Access,2013

4. Coverage, handoff and cost optimization for 5G heterogeneous network;Ouamri;Physical Communication,2020

5. Optimizing resource allocation in the short blocklength regime for ultra-reliable and low-latency communications;Sun;IEEE Transactions on Wireless Communications,Jan. 2019

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1. Radio Map-Based Trajectory Design for UAV-Assisted Wireless Energy Transmission Communication Network by Deep Reinforcement Learning;Electronics;2023-10-30

2. Joint Optimization of Resource Utilization, Latency and UAV Trajectory in the Power Information Acquisition System;Electronics;2023-09-12

3. A Reliable Delivery Logistics System Based on the Collaboration of UAVs and Vehicles;Sustainability;2023-08-22

4. Multi-Agent Deep Reinforcement Learning Framework Strategized by Unmanned Aerial Vehicles for Multi-Vessel Full Communication Connection;Remote Sensing;2023-08-16

5. DRL-Based Backbone SDN Control Methods in UAV-Assisted Networks for Computational Resource Efficiency;Electronics;2023-07-06

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