5G Verticals

RATH VANNITHAMBY, PhD is Senior Research Scientist at Intel Corporation, Oregon, USA. ANTHONY C.K. SOONG, PhD is Chief Scientist at Futurewei Technologies, Texas, USA.

• List of Contributors xiPreface xiiiAcknowledgments xvPart I Introduction to 5G Verticals 11 Introduction 3Anthony C.K. Soong and Rath Vannithamby1.1 Introduction 31.2 5G and the Vertical Industries 51.3 5G Requirements in Support of Vertical Industries 101.4 Radio Access 121.5 Network Slicing 141.6 Other Network Issues 171.7 Book Outline 19References 20Part II 5G Verticals – Deployments and Business Model Opportunities and Challenges 252 5G Network for a Variety of Vertical Services 27Jin Yang2.1 5G Services 292.1.1 Enhanced Mobile Broadband 292.1.2 Ultra Reliable and Low Latency Communications 312.1.3 Massive Machine Type Communications 322.2 Networks 332.2.1 5G Network Architecture 342.2.2 Multi-Access Edge Computing Network 382.2.3 Virtualized Radio Accesses 402.3 Service-Aware SON 422.3.1 5G-NR SON Control 442.3.2 An Intelligent Hybrid 3-Tier SON 462.3.3 Service-Aware Access Scheme 482.3.4 Performance Benefits 502.4 Summary 51Acronyms 52References 54Part III 5G Verticals – Radio Access Technologies 573 NR Radio Interface for 5G Verticals 59Amitava Ghosh, Rapeepat Ratasuk, and Frederick Vook3.1 Introduction 593.2 NR Radio Interface 603.2.1 eMBB 673.2.2 URLLC 703.2.3 mMTC 723.2.3.1 eMTC Overview 743.2.3.2 NB-IoT Overview 743.2.3.3 Coexistence with NR 763.3 5G Verticals 783.3.1 Industrial IoT 783.3.2 Automotive V2X 823.3.3 eHealth 863.4 Conclusion 88Acknowledgment 88Acronyms 89References 904 Effects of Dynamic Blockage in Multi-Connectivity Millimeter-Wave Radio Access 93Vitaly Petrov, Margarita Gapeyenko, Dmitri Moltchanov, Andrey Samuylov, Sergey Andreev, and Yevgeni Koucheryavy4.1 Introduction 934.2 Blockage Effects in 5G Millimeter-Wave Cellular Communication 944.2.1 Millimeter-Wave Link Blockage at a Glance 944.2.2 Blockage Modeling Methodology 954.2.2.1 Geometric Representation of Blocking Objects 954.2.2.2 Attenuation Caused by Blocking Objects 964.2.2.3 Channel Models 964.2.2.4 Blockage States 964.2.3 Accounting for mmWave Blockage 964.2.4 Summary 974.3 Modeling Consumer 5G-IoT Systems with Dynamic Blockage 974.3.1 Spontaneous Public Event 974.3.2 Moving Through the Crowd 984.3.3 AR Sessions in Dense Moving Crowd 1004.3.4 Connected Vehicles 1024.3.5 Summary 1034.4 Dynamic Multi-Connectivity 1034.4.1 Multi-Connectivity at a Glance 1034.4.2 Optimizing the Degree of Multi-Connectivity 1044.4.3 Modeling 5G NR Systems with Multi-Connectivity 1054.4.4 Impact of Multi-Connectivity Policy 1074.4.5 Summary 1084.5 Bandwidth Reservation 1094.5.1 Session Continuity Mechanisms 1094.5.2 Concept of Bandwidth Reservation 1094.5.3 Summary 1104.6 Proactive Handover Mechanisms 1114.6.1 Dynamic Blockage Avoidance 1114.6.2 Deterministic AP Locations 1124.6.3 Deterministic UE Locations/Trajectories 1134.6.4 Summary 1144.7 Conclusions 114References 1155 Radio Resource Management Techniques for 5G Verticals 119S.M. Ahsan Kazmi, Tri Nguyen Dang, Nguyen H. Tran, Mehdi Bennis, and Choong Seon Hong5.1 Introduction 1205.2 5G Goals 1205.3 Radio Access Network Management 1215.4 Network Slicing 1245.5 Use Case: Virtual Reality 1255.5.1 System Model 1255.5.2 Problem Formulation 1275.5.3 ADMM-Based Solution 1285.5.4 Performance Analysis 1315.6 Summary 131References 133Further Reading 135Part IV 5G Verticals – Network Infrastructure Technologies 1376 The Requirements and Architectural Advances to Support URLLC Verticals 139Ulas C. Kozat, Amanda Xiang, Tony Saboorian, and John Kaippallimalil6.1 Introduction 1406.2 URLLC Verticals 1416.2.1 URLLC for Motion Control of Industry 4.0 1416.2.2 Multi-Media Productions Industry 1426.2.3 Remote Control and Maintenance for URLLC 1426.2.4 Vehicle-to-Everything 1446.3 Network Deployment Options for Verticals 1456.4 SDN, NFV and 5G Core for URLLC 1476.4.1 SDN for URLLC 1476.4.2 NFV for URLLC 1486.4.2.1 NFV Background 1486.4.2.2 Reducing Virtualization Overhead on a Single Physical Server 1496.4.2.3 Evolution of NFV toward Cloud Native Network Functions 1526.4.3 5G Core and Support for URLLC 1546.5 Application and Network Interfacing Via Network Slicing 1616.6 Summary 165References 1657 Edge Cloud: An Essential Component of 5G Networks 169Christian Maciocco and M. Oğuz Sunay7.1 Introduction 1707.2 Part I: 5G and the Edge Cloud 1707.3 Part II: Software Defined Networking and Network Function Virtualization 1757.3.1 Rise of SDN 1767.3.2 SDN in Data Centers and Networks 1767.3.3 Network Function Virtualization 1797.4 Evolving Wireless Core, e.g. OMEC, Towards Cloud Native and 5G Service-Based Architecture 1847.4.1 High Volume Servers’ Software and Hardware Optimization for Packet Processing 1887.4.1.1 Data Plane Development Kit 1887.4.1.2 Flow Classification Bottleneck 1907.4.1.3 Cuckoo Hashing for Efficient Table Utilization 1907.4.1.4 Intel Resource Director Technology 1927.5 Part III: Software-Defined Disaggregated RAN 1937.5.1 RAN Disaggregation 1937.5.2 Software-Defined RAN Control 1947.6 Part IV: White-Box Solutions for Compute, Storage, Access, and Networking 1977.7 Part V: Edge Cloud Deployment Options 2007.8 Part VI: Edge Cloud and Network Slicing 2047.9 Summary 207Acknowledgments 207References 208Part V 5G Verticals – Key Vertical Applications 2118 Connected Aerials 213Feng Xue, Shu-ping Yeh, Jingwen Bai, and Shilpa Talwar8.1 Introduction 2138.2 General Requirements and Challenges for Supporting UAVs over a Cellular Network 2158.3 Summary on Current Drone Regulations 2178.4 Review of Aerial Communication R&D Activities in General 2178.4.1 R&D Activities from Industry and Government Agencies 2178.4.2 Academic Activities 2188.4.3 3GPP Activities in General 2198.5 3GPP Enhancement on Supporting Drones 2208.5.1 3GPP Drone Study Item and Work Item in RAN1 2208.5.2 3GPP Drone Study Item and Work Item in RAN2 2238.6 5G Challenges, Solutions, and Further Studies 2258.6.1 Challenges, New Emerging Usages, and Requirements for 5G 2258.6.2 3GPP Features Addressing These New Requirements 2278.6.2.1 eMBB 2278.6.2.2 URLLC 2288.6.2.3 Massive Machine-Type Communications 2288.6.2.4 V2X 2288.6.2.5 Next Gen Core Network 2298.6.2.6 Positioning 2298.6.3 Further Study Needed for Aerial Vehicles in 5G 229Acronyms 231References 2319 Connected Automobiles 235Murali Narasimha and Ana Lucia Pinheiro9.1 Introduction 2359.2 Levels of Vehicle Automation 2389.3 Multi-Access Edge Computing in 5G 2399.4 Platoon-Based Driving Use Case 2409.4.1 Platoon Model 2429.4.2 Edge Computing for Platooning 2499.5 High Definition Maps Use Case 2519.5.1 HD Maps Procedures 2539.5.1.1 Map Download Procedure 2539.5.1.2 Map Update Procedure 2549.5.2 Edge Computing for HD Maps 2579.6 Summary 259Acknowledgment 261References 26110 Connected Factory 263Amanda Xiang and Anthony C.K. Soong10.1 Introduction 26310.2 5G Technologies for the Manufacturing Industry 26410.2.1 Ultra-Reliable and Low-Latency Communications 26410.2.2 Enhanced Mobile Broadband 26410.2.3 Massive Machine Type Communication 26510.3 5G Alliance for Connected Industries and Automation 26610.4 Use Cases 26810.4.1 Motion Control 27010.4.2 Control to Control Communication 27210.4.3 Mobile Control Panels with Safety Functions 27210.4.4 Mobile Robots 27310.4.5 Massive Wireless Sensor Networks 27310.4.6 Remote Access and Maintenance 27410.4.7 Augmented Reality 27510.4.8 Process Automation – Closed Loop Control 27610.4.9 Process Automation – Process Monitoring 27610.4.10 Process Automation – Plant Asset Management 27610.4.11 Inbound Logistics 27610.4.12 Wide Area Connectivity for Fleet Maintenance 27710.4.13 High-End Camera 27810.5 3GPP Support 27810.5.1 5G Use Case and Requirements for Smart Factory 27810.5.2 5G Standardized Solution Development for Smart Factory 28210.5.2.1 5G System Architecture for Smart Factory (SA2) 28210.5.2.2 Other 3GPP Work for Smart Factory 28410.6 Early Deployments 28710.6.1 Spectrum 28710.6.2 Early Trials 28810.7 Conclusions 289Acronyms 290References 290Index 293