Optimization of Cell Individual Offset for Handover of Flying Base Station
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00350982" target="_blank" >RIV/68407700:21230/21:00350982 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/VTC2021-Spring51267.2021.9448970" target="_blank" >https://doi.org/10.1109/VTC2021-Spring51267.2021.9448970</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/VTC2021-Spring51267.2021.9448970" target="_blank" >10.1109/VTC2021-Spring51267.2021.9448970</a>
Alternative languages
Result language
angličtina
Original language name
Optimization of Cell Individual Offset for Handover of Flying Base Station
Original language description
Flying base stations (FlyBSs) mounted on unmanned aerial vehicles (UAVs) are widely used in mobile networks to improve a coverage and/or quality of service for users. To ensure a seamless mobility of the FlyBSs among the static base stations (SBSs), an efficient handover mechanism is required. In this paper, we develop a novel handover mechanism determining the serving SBS for the FlyBS in order to increase the sum capacity of the users served by the FlyBS. We propose to dynamically optimize the handover by adjusting the cell individual offset of the SBS via Q-learning. The results show that the Q-learning converges promptly and the proposed approach increases the users capacity (by up to 18%) and their satisfaction with required minimum capacity (by up to 20%) comparing to state-of-the-art algorithms.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/GA18-27023S" target="_blank" >GA18-27023S: Communication in Self-optimizing Mobile Networks with Drones</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
ISBN
978-1-7281-8964-2
ISSN
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e-ISSN
1550-2252
Number of pages
7
Pages from-to
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Publisher name
IEEE Conference Publications
Place of publication
Piscataway
Event location
Helsinki
Event date
Apr 25, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000687839601170