Q-Learning-based Setting of Cell Individual Offset for Handover of Flying Base Stations

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00359437" target="_blank" >RIV/68407700:21230/22:00359437 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/VTC2022-Spring54318.2022.9860721" target="_blank" >https://doi.org/10.1109/VTC2022-Spring54318.2022.9860721</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/VTC2022-Spring54318.2022.9860721" target="_blank" >10.1109/VTC2022-Spring54318.2022.9860721</a>

Result language
angličtina
Original language name
Q-Learning-based Setting of Cell Individual Offset for Handover of Flying Base Stations
Original language description
Flying base stations (FlyBSs) are widely used to improve coverage and/or quality of service for users in mobile networks. To ensure a seamless mobility of the FlyBSs among the static base stations (SBSs), an efficient handover mechanism is required. We focus on the handover of FlyBSs among SBSs and we dynamically adjust the cell individual offset (CIO) of the SBSs based on their load to increase the sum capacity of the users served by the FlyBSs while considering also a handover cost. Due to complexity of the defined problem and limited knowledge of other parameters required for conventional optimization methods, we adopt Q-learning to solve the problem. For Q-learning, we define a reward function reflecting the tradeoff between the capacity of users and the cost of performed handovers. The proposed Q-learning based approach converges promptly and increases the sum capacity of the users served by the FlyBSs by up to 23% for eight deployed FlyBSs comparing to state-of-the-art algorithms. At the same time, the number of handovers performed by the FlyBSs is notably reduced (up to 25%) by the proposal.
Czech name
—
Czech description
—

Project
<a href="/en/project/LTT20004" target="_blank" >LTT20004: Cooperation with International Research Centre in Area of Digital Communication Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
ISBN
978-1-6654-8243-1
ISSN
—
e-ISSN
2577-2465
Number of pages
7
Pages from-to
—
Publisher name
IEEE Conference Publications
Place of publication
Piscataway
Event location
Helsinki
Event date
Jun 19, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000861825801151

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