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Mobility Management and Localizability for Cellular Connected UAVs
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0001-5298-7490
2024 (English)Licentiate thesis, comprehensive summary (Other academic)Alternative title
Mobilitetshantering och Lokalisering för Mobilanslutna UAV:er (Swedish)
Abstract [en]

Unmanned Aerial Vehicles (UAVs) connected to cellular networks present novel challenges and opportunities in mobility management and localization, distinct from those faced by terrestrial users. This thesis presents an integrated approach, combining two key aspects essential for the integration of UAVs with cellular networks.

Firstly, it introduces the mobility management challenges for cellular-connected UAVs, which differ significantly from terrestrial users. While terrestrial mobility management primarily aims to prevent radio link failures near cell boundaries, aerial users experience fragmented and overlapping coverage with line-of-sight conditions involving multiple ground base stations (BSs). Thus, mobility management for UAVs extends beyond link failure avoidance, aiming to minimize unnecessary handovers while ensuring extended service availability, particularly in up-link communication. Line-of-sight conditions from a UAV to multiple BSs increase the likelihood of frequent handovers, resulting in control packet overheads and communication delays. This thesis proposes two approaches to address these challenges: 1) A model-based service availability-aware Mobility Robustness Optimization (MRO) adapting handover parameters to maintain high service availability with minimal handovers, and 2) A model-free approach using Deep Q-networks to decrease unnecessary handovers while preserving high service availability. Simulation results demonstrate that both the proposed algorithms converge promptly and increase the service availability by more than 40 %  while the number of handovers is reduced by more than 50%  as compared to traditional approaches.

Secondly, to assess the ability of a network to support the range-based localization for cellular-connected UAVs, an analytical framework is introduced. The metric B-localizability is defined as the probability of successfully receiving localization signals above a specified Signal-to-Interference plus Noise Ratio (SINR) threshold from at least B ground BSs. The framework, accounting for UAV-related parameters in a three-dimensional environment, provides comprehensive insights into factors influencing localizability, such as distance distributions, path loss, interference, and received SINR. Simulation studies explore the correlation between localizability and the number of participating BSs, SINR requirements, air-to-ground channel characteristics, and network coordination. Additionally, an optimization problem is formulated to maximize localizability, investigating the impact of UAV altitude across different scenarios. Our study reveals that in an urban macro environment, the effectiveness of cellular network-based localization increases with altitude, with localizability reaching 100% above 60 meters. This finding indicates that utilizing cellular networks for UAV localization is a viable option.

Abstract [sv]

Unmanned Aerial Vehicles (UAV) anslutna till cellulära nätverk presenterar nya utmaningar och möjligheter inom mobilitetshantering och lokalisering, skilda från dem som markanvändare står inför. Denna avhandling presenterar ett integrerat tillvägagångssätt, som kombinerar två nyckelaspekter som är väsentliga för integrationen av UAV:er med cellulära nätverk.

För det första introducerar den mobilitetshanteringsutmaningarna för mobilanslutna UAV:er, som skiljer sig avsevärt från markbundna användare. Medan markbunden mobilitetshantering i första hand syftar till att förhindra radiolänkfel nära cellgränser, upplever antennanvändare fragmenterad och överlappande täckning med siktlinjeförhållanden som involverar flera markbasstationer (BS). Mobilitetshantering för UAV sträcker sig sålunda bortom att undvika länkfel, och syftar till att minimera onödiga överlämningar samtidigt som man säkerställer utökad servicetillgänglighet, särskilt i upplänkskommunikation. Synlinjeförhållanden från en UAV till flera BS:er ökar sannolikheten för frekventa överlämningar, vilket resulterar i kontrollpaketkostnader och kommunikationsförseningar. Denna avhandling föreslår två tillvägagångssätt för att möta dessa utmaningar: 1) En modellbaserad tjänsttillgänglighetsmedveten Mobility Robustness Optimization (MRO) som anpassar parametrar för överlämning för att bibehålla hög servicetillgänglighet med minimal överlämning, och 2) Ett modellfritt tillvägagångssätt med Deep Q- nätverk för att minska onödiga överlämningar samtidigt som hög servicetillgänglighet bibehålls. Simuleringsresultat visar att båda de föreslagna algoritmerna konvergerar snabbt och ökar tjänstens tillgänglighet med mer än 40% medan antalet överlämningar minskas med mer än 50% jämfört med traditionella metoder.

För det andra, för att bedöma förmågan hos ett nätverk att stödja den räckviddsbaserade lokaliseringen för de cellulärt anslutna UAV:erna, introduceras ett analytiskt ramverk.Metriska B-lokaliseringsförmågan definieras som sannolikheten för att framgångsrikt ta emot lokaliseringssignaler över en specificerad signal-till-interferens plus brusförhållande (SINR) tröskel från minst B jord BSs.Ramverket, som tar hänsyn till UAV-relaterade parametrar i en tredimensionell miljö, ger omfattande insikter i faktorer som påverkar lokaliserbarhet, såsom avståndsfördelningar, vägförlust, störningar och mottagen SINR. Simuleringsstudier undersöker korrelationen mellan lokaliserbarhet och antalet deltagande BS:er, SINR-krav, luft-till-mark-kanalegenskaper och nätverkskoordination. Dessutom har ett optimeringsproblem formulerats för att maximera lokaliseringsförmågan, undersöka effekten av UAV-höjd över olika scenarier. Vår studie avslöjar att i en urban makromiljö ökar effektiviteten av mobilnätsbaserad lokalisering med höjden, med lokaliserbarhet som når 100% över $60$ meter. Detta fynd indikerar att användning av mobilnät för UAV-lokalisering är ett gångbart alternativ.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2024. , p. 68
Series
TRITA-EECS-AVL ; 2024:28
Keywords [en]
Unmanned aerial vehicles, Localization, Service availability, Air-to-ground channel, Mobility, Handover
Keywords [sv]
Unmanned aerial vehicles, Localization, Service availability, Air-to-ground channel, Mobility, Handover
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-344494ISBN: 978-91-8040-870-7 (print)OAI: oai:DiVA.org:kth-344494DiVA, id: diva2:1845283
Presentation
2024-04-12, https://kth-se.zoom.us/s/68309059736, Amiga, Kistagången 16, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20240319

Available from: 2024-03-19 Created: 2024-03-18 Last updated: 2024-03-25Bibliographically approved
List of papers
1. Mobility Management for Cellular-Connected UAVs: Model Based Versus Learning Based Approaches for Service Availability
Open this publication in new window or tab >>Mobility Management for Cellular-Connected UAVs: Model Based Versus Learning Based Approaches for Service Availability
2024 (English)In: IEEE Transactions on Network and Service Management, ISSN 1932-4537, E-ISSN 1932-4537, p. 1-1Article in journal (Refereed) Published
Abstract [en]

Mobility management for terrestrial users is mostlyconcerned with avoiding radio link failure for the edge users wherethe cell boundaries are defined. The problem becomes interestingfor an aerial user experiencing fragmented coverage in the sky andline-of-sight conditions with multiple ground base stations (BSs).For aerial users, mobility management is not only concerned withavoiding link failures but also avoiding unnecessary handoverswhile maintaining extended service availability, especially inup-link communication. The line of sight conditions from anUnmanned Aerial Vehicle (UAV) to multiple neighboring BSs makeit more prone to frequent handovers, leading to control packetoverheads and delays in the communication service. Depending onthe use cases, UAVs require a certain level of service availability,which makes their mobility management a critical task. Thecurrent mobility robustness optimization (MRO) procedure thatadaptively manages handover parameters to avoid unnecessaryhandovers is optimized only for terrestrial users. It needs tobe updated to capture the unique mobility challenges of aerialusers. In this work, we propose two approaches to accomplishthis: 1) A model based service availability-aware MRO wherehandover control parameters, such as handover margin and timeto trigger are tuned to maintain high service availability witha minimum number of handovers, and, 2) A deep Q-networkbased model free approach for decreasing unnecessary handoverswhile maintaining high service availability. Simulation resultsdemonstrate that both the proposed algorithms converge promptlyand increase the service availability by more than 40% while thenumber of handovers is reduced by more than 50% as comparedto traditional approaches.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024
Keywords
Air-to-ground channel; Autonomous aerial vehicles; Delays; DQN; Handover; Handover; Interference; Mobility; MRO; Optimization; Quality of experience; Service availability; Three-dimensional displays; Unmanned aerial vehicles
National Category
Communication Systems
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-344492 (URN)10.1109/tnsm.2024.3353677 (DOI)2-s2.0-85182920106 (Scopus ID)
Note

QC 20240327

Available from: 2024-03-18 Created: 2024-03-18 Last updated: 2024-03-27Bibliographically approved
2. Cellular localizability of unmanned aerial vehicles
Open this publication in new window or tab >>Cellular localizability of unmanned aerial vehicles
2023 (English)In: Vehicular Communications, ISSN 2214-2096, E-ISSN 2214-210X, Vol. 44, article id 100677Article in journal (Refereed) Published
Abstract [en]

To enable pervasive applications of cellular-connected unmanned aerial vehicles (UAVs), localization plays a key role. The successful reception of localization signals from multiple base stations (BSs) is the first step to localize targets, which is called cellular localizability. In this paper, we propose an analytical framework to characterize the B-localizability of UAVs, which is defined as the probability of successfully receiving localization signals above a certain signal-to-interference plus noise ratio (SINR) level from at least B ground BSs. Our framework considers UAV-related system parameters in a three-dimensional environment and provides a comprehensive insight into factors affecting localizability such as distance distributions, path loss, interference, and received SINR. We perform simulation studies to explore the relationship between localizability and the number of participating BSs, SINR requirements of the received localization signals, air-to-ground channel characteristics, and network coordination. We also formulate an optimization problem to maximize localizability and investigate the effects of UAV altitude in different scenarios. Our study reveals that in an urban macro environment, the effectiveness of cellular network-based localization increases with altitude, with localizability reaching 100% above 60 meters. This finding indicates that utilizing cellular networks for UAV localization is a viable option.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Air-to-ground channel; Cellular networks; Interference; Localization; Unmanned aerial vehicles
National Category
Engineering and Technology Communication Systems
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-344493 (URN)10.1016/j.vehcom.2023.100677 (DOI)001092931200001 ()2-s2.0-85172922394 (Scopus ID)
Note

QC 20240327

Available from: 2024-03-18 Created: 2024-03-18 Last updated: 2024-03-27Bibliographically approved

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Meer, Irshad Ahmad

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