Q-Learning-based Setting of Cell Individual Offset for Handover of Flying Base Stations
Author:
Affiliation:
1. FEE, Czech Technical University in Prague,Dpt. of Telecommunication Engineering,Prague,Czech Republic
2. EURECOM,Communication Systems Department,Sophia Antipolis,France
Funder
Ministry of Education
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9860273/9860350/09860721.pdf?arnumber=9860721
Reference23 articles.
1. A Q-Learning strategy for LTE mobility Load Balancing
2. A Novel Handover Process for Mobility Load Balancing in LTE Heterogeneous Networks
3. A Reinforcement Learning Based User Association Algorithm for UAV Networks
4. Mobility Management for Cellular-Connected UAVs: A Learning-Based Approach
5. An Enhanced Handover Scheme for Cellular-Connected UAVs
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1. Machine learning-based approaches for handover decision of cellular-connected drones in future networks: A comprehensive review;Engineering Science and Technology, an International Journal;2024-07
2. Mobility Management for Cellular-Connected UAVs: Model-Based Versus Learning-Based Approaches for Service Availability;IEEE Transactions on Network and Service Management;2024-04
3. Energy Efficiency Optimization of Multi-user Switching and Scheduling in EH-SBS System;2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC);2023-02-24
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