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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/LTT20004" target="_blank" >LTT20004: Spolupráce s mezinárodním výzkumným centrem v oblasti digitálních komunikačních systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Wireless Communications

ISSN

1536-1276

e-ISSN

1558-2248

Svazek periodika

22

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

3180-3193

Kód UT WoS článku

000991554300020

EID výsledku v databázi Scopus

2-s2.0-85141443966