Optimization of Cell Individual Offset for Handover of Flying Base Stations and Users

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00370684" target="_blank" >RIV/68407700:21230/23:00370684 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/TWC.2022.3216342" target="_blank" >https://doi.org/10.1109/TWC.2022.3216342</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TWC.2022.3216342" target="_blank" >10.1109/TWC.2022.3216342</a>

Result language

angličtina

Original language name

Optimization of Cell Individual Offset for Handover of Flying Base Stations and Users

Original language description

To ensure a seamless mobility of users in the scenario with flying base stations (FlyBSs) and static ground base stations (GBSs), an efficient handover mechanism is required. In this paper, we introduce new framework simultaneously managing cell individual offset (CIO) for handover of both FlyBSs and mobile users. Our objective is to maximize capacity of the mobile users while considering also a cost of handover to reflect potential excessive signaling and energy consumption due to redundant handovers. This problem is of a very high complexity for conventional optimization methods and optimal solution would require knowledge of information commonly not available to the mobile network. Hence, we adjust the CIO of FlyBSs and GBSs via reinforcement learning. First, we adopt Q- learning to solve the problem. Due to practical limitations implied by a large Q-table, we also propose Q- learning with approximated Q-table. Still, for larger networks, even the approximated Q-table can require a large storage and computation time. Therefore, we apply also actor-critic-based deep reinforcement learning. Simulation results demonstrate that all three proposed algorithms converge promptly and increase the communication capacity by dozens of percent while the handover failure ratio and the handover ping-pong ratio are reduced multiple times compared to state-of-the-art.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20203 - Telecommunications

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

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Transactions on Wireless Communications

ISSN

1536-1276

e-ISSN

1558-2248

Volume of the periodical

22

Issue of the periodical within the volume

5

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

3180-3193

UT code for WoS article

000991554300020

EID of the result in the Scopus database

2-s2.0-85141443966