02154nas0-2200517---450 99000102588020331620240214125712.01022-72880102588USA010102588(ALEPH)000102588USA01010258820020311a19599999km-y0itay0103----balatVAaka--------Decisiones seu sententiae selectae inter quae anno...prodieruntTribunal apostolicum Sacrae Romanae Rotaecura eiusdem apostolici tribunalis editaeV.41 (1949)-[Roma]typis Polyglottis Vaticanis1959-v29 cmIl luogo di pubblicazione variaAnnuale0010001013202001S.Romanae Rotae decisiones seu sententiaecura eiusdem S.tribunalis editaeDiritto canonicoPeriodici262.905Santa SedeSacrae Romanae Rotae553382ITsalbcISBDCELDES_2499000102588020331690GIUXV.20V.41(1949)-SEPATTY9020020311USA011510PATTY9020020311USA011510PATTY9020020321USA011658PATTY9020020321USA01172820020403USA011743ANNAPIA9020021126USA011033PATRY9020040406USA011711VITTORIANA9020041220USA011524MUSELLA9020130306USA011220Decisiones seu sententiae selectae inter quae anno...prodierunt977452UNISAUSA50AdministrativeISSUEGIUGIUPer VIII 10136847-302003051319999109NON PrestabileVol.91 (1999)2003123120040130USA50AdministrativeISSUEGIUGIUPer VIII 1033781136847-102002112619978909NON PrestabileVol.89 (1997)200112312002013020021126USA50AdministrativeISSUEGIUGIUPer VIII 1035452/03136847-202002112619989009NON PrestabileVol.90 (1998)20021231200301302003051312067nam 2200565 450 991083045950332120231013234542.01-119-91144-31-119-91146-X(MiAaPQ)EBC30764568(Au-PeEL)EBL30764568(EXLCZ)992843284290004120231013d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierPositioning and Location-Based Analytics in 5G and Beyond /edited by Stefania Bartoletti and Nicola Blefari MelazziFirst edition.Hoboken, New Jersey :John Wiley & Sons, Inc.,[2024]©20241 online resource (291 pages)Print version: Bartoletti, Stefania Positioning and Location-Based Analytics in 5G and Beyond Newark : John Wiley & Sons, Incorporated,c2023 9781119911432 Includes bibliographical references and index.Cover -- Title Page -- Copyright -- Contents -- About the Editors -- List of Contributors -- Preface -- Acknowledgments -- List of Abbreviations -- Chapter 1 Introduction and Fundamentals -- 1.1 Introduction and Motivation -- 1.2 Use Cases, Verticals, and Applications -- 1.2.1 Emergency Calls -- 1.2.2 Public Safety and Natural Disasters -- 1.2.3 ITS and Autonomous Vehicles -- 1.2.4 IIoT, Construction Sites, and Mines -- 1.2.5 Commercial and Transport Hubs -- 1.2.6 Internet‐of‐Things -- 1.2.7 Education and Gaming -- 1.3 Fundamentals of Positioning and Navigation -- 1.3.1 Position‐Dependent Measurements -- 1.3.2 Positioning Methods -- 1.3.3 AI/ML for Positioning -- 1.4 Fundamentals of Location‐Based Analytics -- 1.5 Introduction to Architectural Principles -- 1.5.1 5G Architecture and Positioning -- 1.5.2 Location‐Based Analytics Platform -- 1.6 Book Outline -- References -- Part I Positioning Enablers -- Chapter 2 Positioning Methods -- 2.1 Positioning as Parameter Estimation -- 2.1.1 The Snapshot Positioning Problem -- 2.1.2 Fisher Information and Bounds -- 2.1.3 Tracking and Location‐Data Fusion -- 2.1.3.1 Practical Aspects -- 2.2 Device‐Based Radio Positioning -- 2.2.1 Theoretical Foundations -- 2.2.1.1 Signal Model -- 2.2.1.2 Equivalent Fisher Information Matrix -- 2.2.1.3 Interpretation -- 2.2.2 Signal Processing Techniques -- 2.2.3 Example Results of 5G‐Based Positioning in IIoT Scenarios -- 2.3 Device‐Free Radio Localization -- 2.3.1 Theoretical Foundations -- 2.3.1.1 Signal Model -- 2.3.1.2 EFIM for DFL -- 2.3.1.3 Interpretation -- 2.3.2 Signal Processing Techniques -- 2.3.3 Experimental Results on 5G‐Based DFL -- 2.4 AI/ML for Positioning -- 2.4.1 Fingerprinting Approach -- 2.4.2 Soft Information‐Based Approach -- 2.4.3 AI/ML to Mitigate Practical Impairments -- References -- Chapter 3 Standardization in 5G and 5G Advanced Positioning.3.1 Positioning Standardization Support Prior to 5G -- 3.1.1 GNSS and Real‐Time Kinematics (RTK) GNSS Positioning -- 3.1.2 WiFi/Bluetooth‐Based Positioning -- 3.1.3 Terrestrial Beacon System -- 3.1.4 Sensor Positioning -- 3.1.5 RAT‐Dependent Positioning Prior to 5G -- 3.1.5.1 Enhanced CID (eCID) -- 3.1.5.2 Observed Time‐Difference‐of‐Arrival (OTDoA) -- 3.1.5.3 Uplink Time‐Difference‐of‐Arrival (UTDoA) -- 3.1.6 Internet of Things (IoT) Positioning -- 3.1.7 Other Non‐3GPP Technologies -- 3.1.7.1 UWB -- 3.1.7.2 Fingerprinting -- 3.2 5G Positioning -- 3.2.1 5G Localization Architecture -- 3.2.2 Positioning Protocols -- 3.2.3 RAT‐Dependent NR Positioning Technologies -- 3.2.3.1 Downlink‐Based Solutions -- 3.2.3.2 Uplink‐Based Solutions -- 3.2.3.3 Downlink‐ and Uplink‐Based Solutions -- 3.2.4 Specific Positioning Signals -- 3.2.4.1 Downlink Positioning Reference Signal -- 3.2.4.2 Uplink Signal for Positioning -- 3.2.5 Positioning Measurements -- 3.3 Hybrid Positioning Technologies -- 3.3.1 Outdoor Fusion -- 3.3.2 Indoor Fusion -- 3.4 5G Advanced Positioning -- References -- Chapter 4 Enablers Toward 6G Positioning and Sensing -- 4.1 Integrated Sensing and Communication -- 4.1.1 ISAC Application: Joint Radar and Communication with Sidelink V2X -- 4.1.1.1 V2X and Its Sensing Potential -- 4.1.1.2 V2X Target Parameter Estimation and Signal Numerology -- 4.1.1.3 V2X Resource Allocation -- 4.1.2 ISAC Application: Human Activity Recognition and Person Identification -- 4.1.2.1 Beyond Positioning -- 4.1.2.2 System Aspects -- 4.1.2.3 Processing Chain (see Figure ) -- 4.2 Reconfigurable Intelligent Surfaces for Positioning and Sensing -- 4.2.1 RIS Enabling and Enhancing Positioning -- 4.2.1.1 RIS Enabling Positioning -- 4.2.1.2 RIS Enhancing Positioning -- 4.2.1.3 Use Cases -- 4.2.2 RIS for Sensing -- 4.3 Advanced Methods -- 4.3.1 Model‐Based Methods.4.3.2 AI‐Based Methods -- 4.3.2.1 Use Case -- References -- Chapter 5 Security, Integrity, and Privacy Aspects -- 5.1 Location Privacy -- 5.1.1 Overview on the Privacy Implication -- 5.1.2 Identification and Authentication in Cellular Networks -- 5.1.3 IMSI Catching Attack -- 5.1.4 Enhanced Privacy Protection in 5G Networks -- 5.1.5 Location Privacy Algorithms -- 5.1.6 Location Privacy Considered Model -- 5.1.7 Location Privacy Tested Approach -- 5.2 Location Security -- 5.2.1 Location Security in 4G/5G Networks -- 5.2.2 Threat Models and Bounds -- 5.2.2.1 Formal Model -- 5.2.2.2 Error Model for the Spoofing Attack -- 5.2.2.3 Threat Model Example Case Study: Range‐Based Localization Using RSSI -- 5.2.2.4 Error Bound Under Spoofing Attack -- 5.2.2.5 Case Study -- 5.3 3GPP Integrity Support -- References -- Part II Location‐based Analytics and New Services -- Chapter 6 Location and Analytics for Verticals -- 6.1 People‐Centric Analytics -- 6.1.1 Crowd Mobility Analytics -- 6.1.1.1 Introduction and Related Work -- 6.1.1.2 Example Experimental Results from Crowd Mobility Analytics: Group Inference -- 6.1.2 Flow Monitoring -- 6.1.2.1 Introduction and Related Work -- 6.1.2.2 Selected DL Approaches and Results for Trajectory Prediction -- 6.1.3 COVID-19 Contact Tracing -- 6.1.3.1 Introduction and Related Work -- 6.1.3.2 Selected Approach and Example Results from Contact Tracing -- 6.2 Localization in Road Safety Applications -- 6.2.1 Safety‐Critical Use Cases and 5G Position‐Related Requirements -- 6.2.1.1 Introduction and Related Work -- 6.2.1.2 Example Results for Safety‐Critical Use Cases -- 6.2.2 Upper Layers Architecture in ETSI ITS Standard -- 6.2.2.1 Introduction and Related Work -- 6.2.2.2 Example Results for ITS -- 6.2.3 5G Automotive Association (5GAA) Activities -- References -- Chapter 7 Location‐Aware Network Management -- 7.1 Introduction.7.2 Location‐Aware Cellular Network Planning -- 7.2.1 What Is the Cellular Network Planning? -- 7.2.2 Why Is Localization Important in the Planning Phase? -- 7.2.3 Location‐Aware Cellular Network Planning -- 7.2.4 Future Directions -- 7.3 Location‐Aware Network Optimization -- 7.3.1 What Is the Cellular Network Optimization? -- 7.3.2 Why Is Location Information Important in Optimization? -- 7.3.3 Hybrid Clustering‐Based Optimization of 5G Mobile Networks -- 7.3.3.1 Clustering Methods and Algorithmic Approach -- 7.3.3.2 Results and Conclusions -- 7.3.4 Location‐Aware Capacity and Coverage Optimization -- 7.3.4.1 Dual‐Connectivity Optimization -- 7.3.4.2 Results and Conclusions -- 7.3.5 SINR Prediction in Presence of Correlated Shadowing in Cellular Networks -- 7.3.5.1 SINR Prediction with Kriging -- 7.3.5.2 Results and Conclusions -- 7.3.5.3 Multi‐user (MU) Scheduling Enhancement with Geolocation Information and Radio Environment Maps (REMs) -- 7.3.5.4 Results and Conclusions -- 7.3.6 Social‐Aware Load Balancing System for Crowds in Cellular Networks -- 7.3.6.1 Social‐Aware Fuzzy Logic Controller (FLC) Power Traffic Sharing (PTS) Control -- 7.3.6.2 Results and Conclusions -- 7.3.7 Future Directions -- 7.4 Location‐Aware Network Failure Management -- 7.4.1 What Is the Cellular Network Failure Management? -- 7.4.2 Why Is Localization Important in Failure Management? -- 7.4.3 Contextualized Indicators -- 7.4.3.1 Contextualized Indicators -- 7.4.3.2 Results and Conclusions -- 7.4.4 Location‐Based Deep Learning Techniques for Network Analysis -- 7.4.4.1 Synthetic mages and Deep‐Learning Classification -- 7.4.4.2 Results and Conclusions -- References -- Part III Architectural Aspects for Localization and Analytics -- Chapter 8 Location‐Based Analytics as a Service -- 8.1 Motivation for a Dedicated Platform -- 8.2 Principles.8.2.1 Microservice Architectural Approach -- 8.2.2 Software Containerization -- 8.2.3 Mixed Kappa and Lambda Data Lake Approach -- 8.2.4 Designing an ML‐ and AI‐Aware Solution -- 8.2.5 Abstracting Computation Optimization Processes -- 8.2.6 Automating Dependency Resolution and Linking -- 8.2.7 Achieving Low Latency End‐to‐End -- 8.2.8 Decoupling Processing and API Access -- 8.2.9 Offering Dynamic Resource Allocation -- 8.2.10 Decoupling Services and Security -- 8.3 Platform System Overview -- 8.4 Platform System Blocks Description -- 8.4.1 API Blocks -- 8.4.2 Control Blocks -- 8.4.3 Core Blocks -- 8.4.4 Virtualization Management and Infrastructure Blocks -- 8.5 Functional Decomposition -- 8.5.1 Data Collection Functions -- 8.5.2 Persistence and Message Queue Functions -- 8.5.3 Positioning and Analytics Functions -- 8.5.3.1 Positioning Functions -- 8.5.3.2 Analytics Functions -- 8.5.4 Security and Privacy Functions -- 8.5.4.1 Security Functions -- 8.5.4.2 Privacy Functions -- 8.5.5 Analytics API Functions -- 8.5.6 Control Functions -- 8.5.7 Management, Orchestration, and Virtualization Functions -- 8.6 System Workflows and Data Schema Analysis -- 8.6.1 System Workflows -- 8.6.1.1 Service Activation -- 8.6.1.2 Service Consumption -- 8.6.1.3 Southbound Data Collection -- 8.6.1.4 Positioning and Analytics Service Operation -- 8.6.2 Applicable Data Schema -- 8.6.2.1 GeoJSON Data Format -- 8.6.2.2 JSON SQL Table Schema Format -- 8.6.2.3 3GPP Location Input Data -- 8.7 Platform Implementation: Available Technologies -- 8.7.1 Access Control Module -- 8.7.2 Service Discovery Module -- 8.7.3 API Gateway and Service Subscription Module -- 8.7.4 Data Operations Controller -- 8.7.5 ML Pipeline Controller -- 8.7.6 ML Model Repository -- 8.7.7 Data Collection Module -- 8.7.8 Data Persistence Module -- 8.7.9 Message Queue -- 8.7.10 Virtualization layer.8.7.11 Management and Orchestration."Location information is a pivotal service of 5G-and-beyond cellular networks and will enable a plethora of new location-dependent use cases. Since Release 16, the 3rd Generation Partnership Program (3GPP) is enhancing 5G networks and devices with localization functionalities targeting a very high level of location. Besides the localization of users, there is a growing interest in location-based analytics - the analysis of the location and behavior of people and objects in public areas, roads, and buildings - through dedicated infrastructures or by relying on user devices. While closely related, location-based analytics are not a mere extension of user equipment localization, but rather a new paradigm that enables a large variety of scenarios and applications"--Provided by publisher.Wireless localizationLocation-based services5G mobile communication systemsWireless communication systemsWireless localization.Location-based services.5G mobile communication systems.Wireless communication systems.621.38456Bartoletti StefaniaBlefari-Melazzi NicolaMiAaPQMiAaPQMiAaPQBOOK9910830459503321Positioning and Location-Based Analytics in 5G and Beyond4020852UNINA