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EuCNC2019 workshop6

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Presentations given at the
Workshop 6: European and Taiwanese Cooperation on 5G
Wednesday, 19 June 2019, at EUCNC 2019 in Valencia, Spain.
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EuCNC2019 workshop6

  1. 1. Li Fung Chang Chief Architect, 5GO DoIT, MoEA June, 2019 5G: Are We Ready?
  2. 2. Outline •Overview • 5G NR specification • Commercial launch plan • Spectrum allocation/policy •Readiness of the ecosystem • Infrastructure • Devices •Enterprise/private 5G network •Taiwan 5G activities •Summary 1
  3. 3. Overview
  4. 4. Standard Timeline 3 IMT-2020 (2015.6) Official 5G Approved 2020 2018 2019 2020 2021 2020 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 R17 Work Scope discussions R-15 R-15 late drop ASN.1 R-16 freeze R-17 freeze R-17 freeze ASN.1 R-16 freeze ASN.1 R-15 late drop freeze R-17 RAN1 freeze R-16 RAN1 freeze
  5. 5. 5G Commercial Launch Plan 4 Pre-commercial 2017 2018 2019 2020 Commercial Rel-15 (5G phase I) Rel-16 (5G phase II) mobile CMCC : 5 cities 500 sites CU : 16 cities 600 sites Oct. FWA April mobile launch Trial Dec. CPE Time : 2018H2 Freq. : 28G/39GHz Time : 2018 Dec. Freq. : 3.5G/28GHz Time : 2020 Freq. : Sub 6G, 28GHz Time : 2019 Freq : Sub 6G, 26GHz Time : 2020 Freq. : 2.6/3.5/4.8GHz AT&T 19 cities T-Mobile : 30 cities Sprint : 6 citiesVerizon : 4 cities Non-standalone standalone Phase II complete Source:5GO collected
  6. 6. Global 5G Spectrum – Sub 6GHz • Consider 5G single carrier bandwidth will be >= 100MHz in Sub 6GHz, at least 300MHz is need for market innovation and competition. 5 Considered for 5G by global regulators 300MHz 300MHz 600MHz 500MHz 400MHz 500MHz China USA Japan Korea EU 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 GHz 450MHz Taiwan 500MHz 400MHz 500MHz Further Studied by MOTC, Taiwan 150MHz CBRS (LTE or 5G) ITU Global primary MS band Non-global primary MS band Source : 5GIA, FCC, IMT-2020(PG), 5GMG, 5G Forum, May 2017. and MOTC Taiwan, June 2017. Edit by 5GO and MIC. 150MHz TD-LTE 120MHz 3.3-3.4 indoor use MOEA 5G R&D Spectrum (3.4-3.6GHz) 200MHz 100 MHz
  7. 7. Global 5G Spectrum – Above 6GHz 6 3 GHz 3.25 GHz 6.5 GHz 1.6 GHz 3 GHz 4.75 GHz 3 GHz Global primary MS band Non-global primary MS band Non AI1.13band 3.25 GHz 24.25 27.5 29.5 31.8 33.4 37 40.5 42.5 43.5 5.25 GHz 0.85GHz 7GHz ITU • Global harmonized spectrum for high band can boost 5G infrastructure, terminal and semiconductor economy scale and speed up emerging service. China USA Japan Korea EU Taiwan 1.6GHz 5.5GHz 6.5 GHz 7GHz unlicensed Considered for 5G by global regulators Further Studied by MOTC, Taiwan 40 30 45 50 60 70GHz 0.6GHz Sharing Spectrum MOEA 5G R&D Spectrum(38.6-40GHz)MOEA 5G R&D Spectrum (28GHz) Source : 5GIA, FCC, IMT-2020(PG), 5GMF, 5G Forum, and MOTC Taiwan, Nov. 2017. Edit by 5GO and MIC.
  8. 8. 5G Commercial Deployments •Fixed wireless, router, smart phones •Islands of deployment without continuous national coverage •Non-standalone (NSA), EN-DC architecture available, SA is yet to be proven •eMBB as initial services 7
  9. 9. Ecosystem Readiness
  10. 10. End Devices 9 2018/02 Snapdragon Balong 5G01 Exynos 5G modem 2018/01 5G module solution 2018/02 5G prototype 2017/11 Source:5GO/MIC collected from companies,2019/Feb. 28/39GHz ant.mod. 2018/07 2017 2018 2019/H1 2019/H2 2020 2018/08 Exynos 5100 M70 2018/12 2018/12 S855 processo r 2019/02 X55 modem 7nm 2/3/4G 5G NR TDD/FDD sub-6GHz & 26/28/39 GHz Balong 5000 2019/01 7nm 2/3/4G 5G NR TDD/FDD sub-6GHz & mmWave 10nm 2/3/4G 5G NR TDD/FDD sub-6GHz & mmWave 7nm 2/3/4G 5G NR TDD/FDD sub-6GHz 2019 H2 shipment
  11. 11. Infrastructure •Open RAN •Edge Computing •Ultra-low latency •Virtualization, micro-services, containers and performance optimization •Network Slicing •Cyber security •AI-assisted network management and operation 10
  12. 12. Private Network: End-End System Solution 4
  13. 13. Demands for Enterprise Network • Secure • Avoid operating confidential data outflows or external security attacks (private network vs. public network) • Ownership, QoS control • Total controls of network access, traffic quality (security、 QoS) • Reliability and flexibility • dedicated network、not subject to other interference • Coverage • Applications tailored end-end solution • Quickly import professional domain knowledge and fast deploy innovative service 12
  14. 14. Taiwan 5G Activities • 5G Program Under MoEA • ITRI/III, domestic and international partners • Target for vertical applications, trials for factory operation, smart hospital, chemical plant and entertainment • EU-Taiwan collaboration • H2020 EU-TW Open Target Call Phase II: Clear 5G, 5G Coral • Phase III projects: 5G CONNI, 5G DIVE to be started in Oct. 2019 • Taiwan 5G alliance • Lead by operators • To facilitate collaboration among MNOs and domestic ICT industries on small cells, switches, servers, terminals, and IoT devices • Pilot team led by CHT was formed in Jan. 2018 • Pioneering team led by FET was formed in Nov. 2018 • MoST/MoEA joint R&D • To leverage resource and research results from academia and apply results to system implementation 13
  15. 15. 5G E2E System Architecture 700MHz~70GHz Licensed + Unlicensed 5G NR gNB HSS PCRF 4G S/PGW Core Network MME Transmission network 2x2 antenna 20MHz BW LTE 150Mbps BBU RRH eMBB UDN URLLC IoT 5G Transmission network Transmission network BPN SON Server UDN Server MTC Server General Purpose CPUvEPC vEPC vEPC/5GC BPNCU CU SON Server iMEC GW Light vEPC/vNGC UHDVR Sensors Transmission network CU mmWave 5G NR gNB Transmission network drone vehicle Network Slicing NFVI NFVI General Purpose CPU Network virtualization 14 5GC
  16. 16. 2019/6/19 15 Pod Containers on K8S
  17. 17. Taiwan 5G Spectrum Plan 16 ~1GHz 1~6GHz 6GHz~ Phase 1 (Early 2020) 1775~1785/1870~1880 MHz 3.3-3.57 GHz 27~29.5 GHz Phase 2 (Planning) 600 MHz 800 MHz 4.5~5.0 GHz 24.25~26 GHz 37~40 GHz Spectrum Policy Trial MVNO、MEC and Network Slicing Vertical Industry can lease spectrum from telecom operators Telecom Operator Evaluating dedicated spectrums for private networks for security and performance purposes. Private Network Provide innovative experimental spectrums for 5G PoC or PoB trials before 5G spectrum auction Enabling 5G Vertical Application Source: Taiwan 5G SRB, Oct. 2018
  18. 18. Summary •Global spectrum harmonization is in the right direction •Initial commercial launches are mainly for eMBB & fixed wireless, isolated/dense hot spots •Fully service based infrastructure is yet to be architected and implemented •For vertical applications • Business model, architecture, spectrum, flexibility, specifications, performance etc., need to be addressed 17
  19. 19. 10
  20. 20. 5G Pre-commercial Trials 8 Immersive viewing experience at first row seat with VR 360 headset The 1st real-time VR 360 live streaming show adapting 5G eMBB Enterprise Network of Taiwan Industries Arbitrary view points switching, favorite perspective to catch exciting moment Share fun with friends through VR interactions and enjoy real-time body expressions
  21. 21. The Next 5G Field Trial - Chemical Plant Display route for inspection Real time display of the inspection results Automatic recording of the inspection results AR goggle display SoP w/remote assistance 5G+AI Cam for Face Recognition on Smart Glasses Access control Operation Safty Assurance Site Inspection w. AR Goggle Streamline Operation Efficiency 5G 120
  22. 22. Smart Hospital Health Monitoring & Tracking Position tracking Medical devices, equipment tracking Remote Diaganosis 5G connection High resolution video for remote assistance Optimize medical resources among hospital system Via AR for pre- surgerical/medical training, or remote assistance 4k/8k Low Latency AR/VR Data collection
  23. 23. Collaboration will Make Dream Come True
  24. 24. Backup
  25. 25. Deployment Scenarios 24 Public Wide area Low Entry point Spectrum RAN Core Netwrok Enterprise Control Center MVNO Mobile Virtual Network Operator MVPN Mobile Virtual Private Network Private Network control Security Regional Private Network : Enterprise: Telecom Operator
  26. 26. European Conference on Networks and Communications (EuCNC) 2019 European and Taiwanese Cooperation on 5G Valencia, 19 June 2019 Bernard Barani Deputy Head of Unit, Future Connectivity Systems European Commission – DG CONNECT
  27. 27. Motivation for International Cooperation in Network R&I • Industry Drive, competitiveness across value chains; • Pre competitive opportunities, towards • Global consensus and standards; • Interoperability, spectrum • Use case best practices • Addressing global societal challenges • Specific policy issues, fn(partner country), e.g. reciprocity
  28. 28. 5G Public Private Partnership Industrial R&I cooperation cartography
  29. 29. R&I , 2018-20 Work Programme Number of Projects Total N° of projects * Partner - Applications and trials with 5G networks - Beyond 5G, applicability of spectrum >275 GHz ➔spectrum, interop, use cases, Beyond 5G 2 6 5GMF - Application trials at mmwave bands - Interworking across multiple radios ➔ Standards validations, use cases 2 4 5G Forum - eMBB Trials at 3,5 GHz and in the V2X context ➔ standards, 5G V2X 1 1 IMT 2020 (5G) Promotion Group - 5G trials addressing end-to-end testbeds for specific applications ➔ 5G verticals, 2 4 DoIT-MoEA - Coordination of EU-NSF projects relevant to the Advanced Wireless Platform programme ➔ Longer term beyond 5G 1 1 NSF *5G/Network related only, under H2020 programme
  30. 30. EU-Taiwan: Horizon 2020 and 5G as catalyser 5G PPP Phase 1: Classical cooperation 5G PPP extension: Two dedicated call for Taiwanese partners Two EU-TW call 1 projects started in September 2017
  31. 31. 6 EU-TW call 2 results:
  32. 32. 5GPPP Phase 3: E2E Infrastructure and Vertical Trials
  33. 33. 8 Beyond 5G, 6G: Is it too early to start R&I?
  34. 34. Opportunities for the next decade « Digital Industries » « Physical Industries » Share of GDP 30% 70% Digital Investment 70% 30% Annual Productivity Growth (15 Years avg) 3% 0,7 % Automation and Industry: 3,5 to 10 Trillion € by 2025, 11% of economy (Mc Kinsey) Network share prospects, 10%? Doubling current broadband revenues? ➔ Assumption 1: Industrial/Vertical applications will remain a strong innovation driver over next decade Source, Nokia quote from:The coming productivity boom, Michael Mandel, Brett Swanson
  35. 35. What we observe today: - Social issues, coverage - 3,5 Billion people without wireless Internet - Energy, sustainability in hyperconnected society - « Energy skyrocketing at the edge ». - EMF raising concerns - What impact of untested spectrum usages? How to decrease exposure? - Human centricity and trust, data control and governance - Security and Autonomy - Coping with embedded critical infrastructres ➔ Assumption 2: Societal issues to gain accrued importance
  36. 36. 5G Vision and focus Parameters: will they remain valid? 11 Use cases and drivers • Capacity, still 50% traffic increase/ year • local applications, sub-ms latency • Gbps availability, e.g XR applications • Extreme reliability beyond 5x9; • mMTC “everywhere “ • Extreme energy efficiency • Further enhanced high security/trust • Very high mobility • cm-level localization Source: ITU-R Rec. M.2083 (modified) Enhanced mobile broadband (eMBB) Massive machine type communications (mMTC) Ultra-reliable and low latency communications (URLLC) Network traffic (exabytes/mont h) Positioning accuracy Security Distributed computing Smart Networks & Services
  37. 37. Assumption 3: 5G design parameters pushed towards new frontiers will remain valid towards wide industrial applicability Disruptions may be expected, for example: - Innovative spectrum use towards sensing and environment augmentation - Generalised use of AI and Machine Learning in multiple aspects, Intelligence and semantic - Multiple network architectural issues (extreme agility, energy, blurring device/network/cloud, security) - Untested technologies at scale, e.g. blockchain
  38. 38. Horizontal issue: Energy Efficiency - Energy needs, significant increase since 2014, expected to accelerate; - by 2030, 10 M edge clouds , 9 M robo-cars/yr ➔ new architectures. - Optical, virtualisation, densification: parts of the solution - Other techniques, energy harvesting and ambient energy use ➔ Towards EE as part of the network management, « EFCAPS » + E2E integration Source: Anders Andrae « best case », Nature News Feed, Sept 2018.
  39. 39. Unified & Access- agnostic Authenticat ion Primary Authenticat ion Secondary Authenticat ion Increased Home Control Initial NAS Security & Privacy Visibility and Configurabi lity Service Based Architectur e Steering of Roaming 5GS – EPS Interworkin g Security LTE-NR Dual Connect. (Option-3) PLMN Interconne ct Security - SEPP RAN Security – DU-CU Split Network Slice Security Long Term Key Update 256-bit Algorithms for 5G KDF Negotiation Vertical services and LAN Single Radio Voice Continuity from 5G to UTRAN Wireless and Wireline Convergence Security Cellular IoT Security for 5G 5G Phase I 5G Phase II “Journal of ICT Standardization” OpenAccess by River Publishers Special issues on “5G non-standard aspects” and “3GPP 5G specifications” Beyond 5G? > SaaS Interoperability, E2E Quantum AI based malware detection GDPR (Multiple) Identities Horizontal issue: Security Cross domains blockchains ………………
  40. 40. Assumption 4: Significant advances compared to foreseeable 5G will come from the combinatorial effect of a multiplicity of technologies, use cases, societal requirements, and business models. ➔ A modified approach may be required from the start.
  41. 41. Proposal: Partnership on Smart Networks and Services
  42. 42. Devices: Multiplicity of Connected Devices Industrial Automation 360o VR/XR Fully Automated Vehicles Haptic Communications for surgery Agri sensors Smartphones Computers Mobile & Last Mile Networks Versatile Infrastructure Multiple Topologies High density access Corporate nets Indoor Short Range Dense IoT Fixed wired access OLT CU AWG RU RU RUDU Service provisioning Computing and Storage Data Analytics End-to-endResource ManagementandEnergy Efficiency Drones Requirements Industrial & Consumer Applications Telemedicine Construction Connected Mobility Environment Factory Immersive tourism 8K movie Sport & events ….. End-to-endSecurityand Trust Smart Networks and Services - Value Chain Approach New opportunities Enabling Technology Components
  43. 43. Beyond 5G: A Possible Roadmap 2022 20242020 2026 2028 2030 Un-constrained R&D 6G Design R&D Standards SI launch:2006 Trials Launches Derived from Orange ~ Based on modified 5G Model Need agility in case of accelerated commercial pressure R&I International cooperation window?
  44. 44. Timeline and process for the preparation of Article 185/187 initiatives 3 May – 27 June: Structured consultation of Member States (as part of strategic coordinating process) May-June: Publication of draft Inception Impact Assessments and start of the Impact Assessment work Mid-June until Open Public Consultation on future European Partnerships based on Article September: 185/187 July SNS Stakeholders Workshop (extended, tentative) 24-26 September: European R&I Days (policy discussion and validation with stakeholders, covers all European Partnerships) October SNS Stakeholders Workshop End of 2019: Submission of Impact Assessment drafts to Regulatory Scrutiny Board Early 2020: Adoption of Commission proposals for Article 185/187 initiatives Early 2020 Finalisation of SNS SRIA and Roadmap (TBC) Early 2021: Launch of first European Partnerships under Horizon Europe Indicative timeline European Partnerships
  45. 45. By Way of Conclusion The B5G-6G journey has started. At this early stage, flexibility is key. We can today identify as potential drivers: • Networks in industrial environments, pushing the 5G envelope limits • Societal issues to get enhanced focus • 5G design drivers duly complemented remain valid • New innovation/disruptions to be integrated (AI/ML, DLT, mEC..) • New system/stakeholders approach targeted • Europe committed to support EU excellence in this critical domain.
  46. 46. 21 Thank you for your attention !
  47. 47. Clear5G Communication for the Factories of the Future Klaus Moessner (Technical University Chemnitz, University of Surrey) Project Coordinator, H2020 Clear5G project EuCNC 2019 WeC8: Workshop 6 : European and Taiwanese Cooperation on 5G Valencia, 19 June 2019
  48. 48. Project Vision: “to provide technical solutions that enable future 5G networks to act as dependable communications backbone for the Factories of the Future” Valencia, 19.06.2019 2
  49. 49. Project Brief • Clear5G-Converged wireless access for reliable 5G MTC for factories of the future (FoF) Valencia, 19.06.2019 3 • Horizon2020 EU-TW collaboration • Sept. 2017 – Feb. 2020 • Focus on 5G radio network for FoF (PHY, MAC, NET) • Coordinator: University of Surrey • Coordinator TW: Institute for Information Industry • Technical Manager: TNO • Objectives: to design, develop, validate, and demonstrate an integrated convergent wireless network for Machine Type and Mission Critical Communication (MTC/MCC) services for Factories of the Future (FoF)
  50. 50. Clear5G network view • While parts of the underlying communications infrastructure will be public networks, within factories there will be private (physically or virtually) factory wide 5G networks tailored to the particular needs of the individual site • Continuous monitoring while products or parts are within the logistics section of the production chain • Spectrum regulation and management plays a significant role Valencia, 19.06.2019 4
  51. 51. Challenges and Clear5G KPI’s The Industrial environment is challenging for wireless connectivity, e.g. both large- and small- scale fading (predictable?) • Massive connectivity • Coverage, reliability and latency • Heterogeneity (private and public network, different radio technologies) Valencia, 19.06.2019 5 Clear 5G KPI Targeted value Latency (end-to-end) Down to 1 ms Reliability Up to 99.999% Connection density Up to 100 nodes per 1 m3 Security PHY framework Heterogeneity (convergent air interfaces) Coexistence of various radio interfaces, and various FoF use cases Energy efficiency (Device battery life) >15 year battery life
  52. 52. How are we getting there? The technology components • PHY (WP2) • Adaptive frame structure • New waveform • Non-coherent modulation • NOMA • Physical-layer security • MAC (WP3) • Random access enhancement • (Adaptive) Contention-based or –free MAC • Joint PHY and MAY optimization • Heterogeneous Radio Access • Networking (WP4) • RAN architecture • RAN Slicing • Multiple connectivity, (UE) relaying • Public and private network integration Valencia, 19.06.2019 6
  53. 53. Example: Hardware prototyping of sparse code multiple access (SCMA) for massive connectivity in FoF SCMA: A code-domain NOMA which can support massive connectivity by efficiently exploiting the sparsity of codebook using message passing algorithm. Objective: To implement and demonstrate SCMA system over USRP testbeds. Testbed hardware & software • One NI-PXIe • Two USRP RIO-2943R • One CDA-2900 (10 MHz frequency clock) • LabVIEW Communication System Design Valencia, 19.06.2019 7 RIO1 TX PXIe RIO2 RX Channel Host PC System parameters Values Center frequency 2 GHz Bandwidth 10MHz FFT length 64 CP length 8 # of RB per frame 200 # of samples per frame 12000
  54. 54. Example: Network slicing in a factory network • Slicing enables operators to support different network instances on the same infrastructure • FoF as one of the slices, or • Different FoF use cases (e.g. URLLC, non- URLLC) may be served by different slices • URLLC: local controller • Non-URLLC: controller in the cloud • FoF slices may be provided by a public network operator, or a physically private network. Valencia, 19.06.2019 8
  55. 55. … leading to Traffic Abstraction and Analytics Showcase managing wired FoF network wrt specific requirements and analysing traffic statistics gathered from the network Steps to follow: ✓ Define multiple traffic classes in wired network ✓ Create and install a set of wired paths for each traffic-class – road network ✓ Mix traffic classes so as to achieve a fair distribution between different traffic classes ✓ Collect traffic statistics and analyse them Valencia, 19.06.2019 9 SDN controller Systems room Factory area: 50x50m NG core URLLC ctrl 1 URLLC ctrl 2 non-URLLC controller URLLC area 1 URLLC area 2 system mgr non-URLLC area RAN ctrl orchestrator edge core UPF UPF
  56. 56. Example: Closed-loop control of industrial AGV with UE relaying support Objectives • Demonstrates that 5G technologies can fulfil the strict requirements of a close-loop controlled Automated Guided Vehicle (AGV) moving in a factory. • Support low latency exchange of data in monitoring and analysis services such that the AGV can be remotely guided based on product quality results. • Showcases UE relaying in a factory environment as a mean to improve reliability. • If the default communication link of the AGV is unavailable, the AGV will use nearby UE(s) as relay node(s) in order to reach the destination node. Technical Benefits • Low latency exchange of data between the industrial devices (e.g. AGV, factory server) • Improvement in reliability by using multiple connectivity options • Improvement in radio coverage by using UE relaying • Improve the level of industrial automation Valencia, 19.06.2019 10 Processing Quality Check Packaging AGV (equipped withUSRP for5G connectivity, Wifi/LTE multi-connectivity) QC Passed ImproperMaterial Cloud platform (located in the Cloud or in a central factory location) USRP PC •Analysisof quality report •Decisionon AGV route •AGV control •SLAM (SimultaneousLocalizationand Mapping) •Navigation •Quality checking (e.g.using the camera,the dimensioning sensors) •Sendsquality report to the Cloud platform •Receivesrouting from the Cloud platform •Acts as a relay node •Forwardstraffic to server USRP (OAI) AGV UE (OAI) USRP (OAI) BS (eNodeB, gNB) EPC (OAI)
  57. 57. For more details, visit the Clear5G booth in the exhibition area! Valencia, 19.06.2019 11
  58. 58. Beyond simulations: the trial scenarios • Massive sensor data collection in FoF • Monitoring & Closed Loop Control in FoF • Seamless Interoperability and Mobility (private FoF and public networks) Valencia, 19.06.2019 12
  59. 59. Putting the Clear5G solutions on the factory floor Valencia, 19.06.2019 13
  60. 60. 1. Machine 3. Cleaning 2. Polishing/ Buffing A+ Project Data Collection Data from the motion of the arm WINGS AGV Clear5G Robot Control and decision 1. AGV Control (WINGS) ok 2. UE relaying/multi- connectivity (TNO) ok 3. Massive sensor data collection (III) ok (A+) 4. Packet duplication (UNIS) →video 5. LORA/LPWA (CEA) ok 6. Slicing (ARG/TT) ok ~50/60m What is 5G? • UE Relaying and RAT Selection • Communications with AGV (~40ms) • Slicing Cloud 1 2 3 4 App Server LTE & UE Relaying 5 7 Human intervention (e.g. loading/ unloading from AGV) Clear5G factory setup 6 Quality checking (Discard or continue) Pillar Pillar Intranet
  61. 61. 15 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 761745 and from the Government of Taiwan. Thank you! More info: http://www.clear5g.eu or follow Clear5G on twitter. @Clear5G
  62. 62. Visit the Clear5G booth in the exhibition area!
  63. 63. 5G-CORAL meets 5G-DIVE Antonio de la Oliva (UC3M) EuCNC 2019 19th June 2019
  64. 64. Introduction - The Cloud, Edge and Fog 2 User Telco Network Cloud APP Cloud User Telco Network Cloud Edge APP Edge FogProximity Distribution APP User Telco Network Cloud Edge APP APP Fog APP Fog APP Fog APP User- Centric
  65. 65. 5G-CORAL Project Vision • 5G brings a flexible RAN architecture including flexible functional split of the gNB/eNB (DU <-> CU) and a diverse set of terminal (UE/CPE) types which all have computing capability ready for harvesting • Edge and Fog are complementary, and jointly together will define the computing substrate of next generation radio access networks 4 The computing fabric does not stop at the Edge. It is more pervasively distributed through the Fog into access infrastructure and user terminals UE CU CU Core Data Network CloudCloud DU DU UE UE Edge DC … FogFog A rich pool of distributed computing fabric Fog
  66. 66. 5G-CORAL Project Mission 5 Target an integrated virtualized solution deep into the RAN offering distributed data services for various applications Mission: To develop the framework for an integrated virtualized Edge/Fog solution and demonstrate its value proposition for various use cases
  67. 67. Solution Building Blocks • OCS: A logical system for composing, controlling, managing, orchestrating, and federating one or more EFS(s). An OCS may interact with other OCS domains • EFS: A logical system providing service platforms, functions and applications on top of Edge and Fog resources. It may interact with other EFS domains 7 Builds on two sub-systems, the EFS (Edge and Fog computing System) and the OCS (Orchestration and Control System)
  68. 68. Integration and Demonstration 8 EFS and OCS baseline implementations integrated and demonstrated at several events Use Case Demonstrations Augmented Reality Shopping Mall (Nov’18) Virtual Reality Taiwan’s UK visit (Sep’18) Edge Congress (Sep’18) EuMA (Sep’18) Shopping Mall (Nov’18) Fog-Assisted Robotics EuCNC (Jun’18) 5TONIC (Jun’18) EuMA (Sep’18) Shopping Mall (Nov’18) IoT M-RAT Gateway EuCNC (Jun’18) Shopping Mall (Nov’18) Connected Cars Torino Trial (Oct’18)
  69. 69. 5G-CORAL Evolution: 5G-DIVE ■ Goal: Design, validate and verify an intelligent 5G solution that integrates 5G connectivity with edge and fog computing (and intelligence residing on this new distributed edge). ■ Target products: UE (including, drones), CPE, gNB, fog, edge, and core 9 Europe Taiwan
  70. 70. Vertical Pilots – Industry 4.0 Digital Twin Apps • Provides a virtual replica of a robot or of a part of a production line. • The 5G network coverage will be deployed to enable real-time visibility and remote insights into robot status and performance without having to directly operate on the physical machine. • Requires eMBB and URLLC for the on-time delivery of the information of the sensors to the virtual twin and for the interaction with the digital model. • Facilitates assessing the concepts of remote control, monitoring for preventive maintenance, and safety. Connected Worker Augmented Zero Defect Manufacturing (ZDM) Decision Support System (DSS) • Explores the capabilities of Fog/MEC/Cloud multi-tier Edge to address this local processing and visualization of geometric features for manufactured parts. • Deploys in the Fog devices (e.g., video cameras), algorithms able to detect characteristic patterns for defects in the production. • Requires eMBB for the interaction with the platform for reinforced learning and URLLC for processing of results in the Fog devices. • ZDM techniques may potentially reduce scrap by 100%, and predict form and/or welding errors. 10
  71. 71. Vertical Pilots – Autonomous Drone Scout Drone Fleet Navigation • Improves current Drone product portfolio, enabling a better piloting of the Drone swarm. • Providing intelligence in the Drones • Requires eMBB and URLLC for the on-time delivery of the information of the sensors to the edge data centre for drone interaction. • Enables new Drone-based services: • delivery, inspection and monitoring, scouting, Aerial Imaging, and precision agriculture on large scale. Intelligent processing of images in the Drones • Enables the deployment of intelligent functions in the Drones and its cooperation with the different tiers of the 5G-DIVE platform. • Requires eMBB and URLLC for the on-time delivery of the information of the Drone. • More automation in the scouting processes, creating a new value chain of services which can be used to provide more services to the customers. 11
  72. 72. What are we missing in 5G-CORAL? LatencyHigh Low Data FilteringLow High LocalizationCentralized Distributed
  73. 73. 5G-DIVE Building Blocks VIM EFS Manager EFS Orchestrator EFS Functions EFS Applications EFS Service Platform Operation Support System Business Support System 5G-DIVE Elastic Edge Platform (DEEP) EFS OCS Infrastructure and platform systems Vertical industries systems Business Automation Support Stratum hosting all proposed virtualized functions, services, and applications managing and controlling the EFS, and its interworking with other domains (1) EFS: (2) OCS: supporting vertical industries in day-by-day operations, management, and automation of businesses processes on-top of an edge and fog infrastructure. (3) DEEP: 13
  74. 74. Consortium partners and acknowledgment 06 December 201815 www.linkedin.com/in/5g-coral5g-coral.eu twitter.com/5G_CORAL Cost: 3.856.973,75€ Technical Managers: Dr. Alain Mourad (Interdigital Europe), Dr. Tony Do (ITRI) Coordinator: Dr. Antonio de la Oliva (UC3M) Project lifetime: 01/09/2017 - 31/08/2019 The 5G-CORAL projet has received funding from the European Commission H2020 Grant No. 761585
  75. 75. ICT-23-2019 EU-TW 5G COLLABORATION in H2020 5G-CONNI
  76. 76. © Fraunhofer HHI | 18.04.2019 | 2 Private 5G Networks for CONNected Industries EU-Taiwan Collaboration Project in Industry 4.0 Project scope on factory automation
  77. 77. © Fraunhofer HHI | 18.04.2019 | 3 Private 5G Networks for CONNected Industries Objectives from the Work Programme ICT-23-2019 ◼ The integrated end-to-end network for 5G trials activity is to utilize the infrastructure of the integrated 5G access/core networks in test beds, in Europe and Taiwan. ◼ Conduct 5G trials addressing technology and business validation of 5G end-to-end connectivity and associated management from applications in Taiwan that will support the development of advanced 5G technology. ◼ Consider network virtualization approaches such as SDN/NFV and network slicing to make the best use of the resources for services with a reduction in CAPEX and OPEX. ◼ Support the specific performance requirements stemming from the considered vertical use cases. The trials should go beyond proof of concept and leverage the results of related 5G PPP projects and Taiwan’s 5G Program.
  78. 78. © Fraunhofer HHI | 18.04.2019 | 4 Private 5G Networks for CONNected Industries Project Goal Demonstration of 5G radio, network and cloud technologies as enablers for future Smart Factories by integrating private local 5G networks into a multi- site end-to-end industrial communication testbed. Exploring new operator models, planning and deployment strategies for private 5G networks.
  79. 79. © Fraunhofer HHI | 18.04.2019 | 5 Private 5G Networks for CONNected Industries Consortium
  80. 80. © Fraunhofer HHI | 18.04.2019 | 6 Private 5G Networks for CONNected Industries Key Figures ◼ 3 years project, start October 1st 2019 ◼ 386 person months for 7 work packages ◼ Funding: 2 Million € in EU, matched fund in TW ◼ Coordinators: Fraunhofer HHI and ITRI ◼ Industry: Bosch, Alpha Networks, Chunghwa Telecom ◼ SME: Athonet ◼ Research: Fraunhofer, CEA-LETI, ITRI, III ◼ Academia: University of Rome ◼ Advisory Board: Nokia, Rohde & Schwarz, Intel
  81. 81. © Fraunhofer HHI | 18.04.2019 | 7 Private 5G Networks for CONNected Industries OVERALL SYSTEM ARCHITECTURE 5G CONNI EU/TW Joint Testbed Architecture
  82. 82. © Fraunhofer HHI | 18.04.2019 | 8 Private 5G Networks for CONNected Industries USE CASES Use Case Machining Center Wireless Connectivity of a Mobile Robot
  83. 83. © Fraunhofer HHI | 18.04.2019 | 9 Private 5G Networks for CONNected Industries USE CASES Use Case: Intelligent Machining Center Use Case: Smart Assembly Line © ITRI © Bosch
  84. 84. © Fraunhofer HHI | 18.04.2019 | 10 Private 5G Networks for CONNected Industries End-to-End Demonstration of Machining Center © ITRI ◼ Highly automated machining center ◼ Adaptive control of machining with sensor readouts ◼ Predictive Maintenance ◼ Anomaly detection ◼ Quality control during machining
  85. 85. © Fraunhofer HHI | 18.04.2019 | 11 Private 5G Networks for CONNected Industries End-to-End Demonstration of Smart Assembly Line © Bosch ◼ Flexible production cells with small lot sizes ◼ Scalable w.r.t. multi-cell, multi-building, indoor-outdoor ◼ Application specific slicing e.g. wireless bus extensions, production data up- and download, life cycle management ◼ Cloud assisted assembly and maintenance ◼ Support of AR / VR human machine interfaces
  86. 86. © Fraunhofer HHI | 18.04.2019 | 12 Private 5G Networks for CONNected Industries Implementation and Demonstration © FhG IOSB ◼ Deployment of private 5G networks at 3,7 GHz in two factories in EU and TW (3,7-3,8 GHz are dedicated to private 5G networks in Germany) ◼ Development and integration of specific 5G end- user equipment ◼ Integration of mobile edge computing capabilities within the local 5G network ◼ Development and implementation of specific core network functions ◼ Planning and testing of private networks
  87. 87. © Fraunhofer HHI | 18.04.2019 | 13 Private 5G Networks for CONNected Industries Impacts ◼ Proving feasibility of private 5G networks while defining new operator models and developing planning tools and edge cloud technologies for efficient deployments ◼ Contribution to understand and transfer how to plan, deploy, operate and maintain a private 5G network in a factory ◼ Demonstrate industrial applications in real-world 5G trial systems, potentially with global interconnectivity ◼ Contribution to trigger and facilitate the fast adoption of 5G CONNI key concepts by industrial players ◼ Contribution to standards and regulation aiming at private industrial 5G, exploiting the EU-Taiwan cooperation for working towards harmonized regulation for spectrum and numbering
  88. 88. TONIC Research Group Applying NOMA for Latency Reduction in Factories of the Future June 19, 2019 Hung-Yun Hsieh Graduate Institute of Communication Engineering & Department of Electrical Engineering National Taiwan University
  89. 89. TONIC Research Group Outline 2 • Introduction • III Contributions • NTU Contributions • Summary
  90. 90. TONIC Research Group Clear5G – WP3 3 • WP3 provides MAC-layer air interface enhancements for the MTC in the FoF use cases, including both the control plane and the user plane. • WP3 investigates cross-layer (PHY and MAC) IoT traffic management and the impact of heterogeneous radio networks. • Task 3.1: Random Access Enhancement • Task 3.2: Adaptive MAC Protocol for mMTC and uMTC • Task 3.3: Heterogeneous Radio Access • Task 3.4: Implementation
  91. 91. TONIC Research Group Clear5G – WP3 4
  92. 92. TONIC Research Group Clear5G – Task 3.2 5 • Task 3.2: Adaptive MAC protocol for mMTC and uMTC • Task 3.2 proposes an adaptive MAC protocol, which works in a contention-like manner in low-load traffic conditions to reduce the access latency. Moreover, the proposed MAC protocol will work in a scheduling-like manner in high-load traffic conditions to increase the system throughput and reliability.
  93. 93. TONIC Research Group Clear5G – Roles of III and NTU 6 • III (task leader) contributed to the design of MAC scheduler for massive connection, in addition to exploring designing flexible MAC concepts for reconfiguration of the amount of resources for RACH, system signaling, scheduling of low-latency users, etc. • NTU proposed designs of low latency random access for massive MTC, with the coexistence of multiple radio access technologies.
  94. 94. TONIC Research Group III Contributions (D3.2) 7 • III has designed a MAC-layer mechanism that performs resource allocation to users adaptively either in OMA or NOMA. • Code-domain NOMA (SCMA or LDS) and OMA (OFDMA or SC-FDMA) uplink multiple access schemes. • F candidate UEs to be allocated either in F resource blocks (OMA) or V>F resource blocks (NOMA) Omax: max modulation order NOMA BLER based on the worst SNR • Choose the MA with the best throughput (SOMA or SNOMA)
  95. 95. TONIC Research Group III Contributions (D3.2) 8 • Evaluation results with low and high SNRs • Low SNR: UE power = -20dBm • High SNR: UE power = -10dBm • Latency of the proposed mechanism can always achieve the lowest irrespective of the conditions Low SNR High SNR
  96. 96. TONIC Research Group NTU Contributions (D3.2) 9 • Two-tier architecture with heterogeneous radios • Tier-1 (to/from base station): 5G • Tier-2 (between IIoT devices): short-range radio (6TiSCH) • Latency reduction • Pure 5G -> two-tier: reduce bottleneck at the base station • Pure 6TiSCH -> reduce multi-hop delay • Use NOMA at tier-1 can further • reduce latency • Some interesting results for • IIoT devices
  97. 97. TONIC Research Group Data Characteristics of IIoT Devices 10 • IIoT devices are deployed to collectively gather (or report) data required by the target application • Collected data by individual devices is often related • Conventionally traffic from individual UEs are considered independent • Contention of radio resource • Conventionally, it matters to provide QoS to each UE • For IIoT devices, it is possible that they contend resource to transmit same (similar) data • Does it make sense to provide QoS to each IIoT devices without considering the data they carry? • Consider the problem of pairing & scheduling NOMA UEs
  98. 98. TONIC Research Group Sum-Rate Maximization Scheduling 11 • Conventional approach for NOMA user pairing is to maximize the sum data rate of the pair • machines are indexed in decreasing channel gain • Achievable rate of each machine • P is the transmission power of each machine • G accounts for the spectral gap to Shannon capacity
  99. 99. TONIC Research Group Overall Comparison 12 • NOMA under sum-rate maximization could perform worse than OMA
  100. 100. TONIC Research Group Resource Minimization Scheduling 13 • Sum rate maximization is typically good for backlogged traffic sources (e.g. FTP), yet is it the case to M2M communications used for data gathering? • Resource (time) needed for machine k • is the size of data • Required resource for a given pair • “Faster” machine needs to wait for the slower
  101. 101. TONIC Research Group Waiting-Time Minimization 14 • Waiting time inside a time slot indicates a waste of radio resource • Maximizing resource utilization is beneficial to resource minimization • Scheduling metric • Scheduling pairs in decreasing metric value
  102. 102. TONIC Research Group Overall Comparison 15 • Radio resource minimization and waiting-time minimization achieve the desired performance
  103. 103. TONIC Research Group Summary • Reducing latency in FoF using NOMA • Adaptive MAC to choose the best multiple access scheme depending on the achievable throughput • Two-tier architecture provides more flexibility with further reduction in end-to-end latency • For IIoT devices with limited amount of data to send, throughput maximization does not necessarily lead to latency minimization • Better user NOMA pairing and scheduling methods can be designed optimize latency performance in FoF 16
  104. 104. 5G CORAL Distributed Edge and Fog Computing Network Infrastructure and AR Navigations Dr. Jen-Shun Yang Manager of Advanced Communication Technology & Standard Development Dept. Division for Video & Multimedia Communications Technology Information and Communications Research Laboratory Industrial Technology Research Institute
  105. 105. Content • Motivation of Distributed Computing Resource Orchestration • 5G CORAL Use Cases • Introduction to Fully Distributed Computing Resource Orchestration • AI CNN Training for Resource Allocation Optimization • Performance Testing • Conclusions 2
  106. 106. 5G CORAL Hierarchical Multi-tier Computing Infrastructure 3 5G Edge&Fog Control Plane 5G Edge&Fog User Plane 5G Edge&Fog Hierarchical Multi-tier Computing Infrastructure and Use Cases A 5G Convergent Virtualized Radio Access Network Living at the Edge
  107. 107. • Complex 3D indoor environments in train station • Imagine that you are lost in a Taipei Main Station, looking for the entrance to MRT/HSR/TRA/Bus station/taxi ranks and up to 70 exits to parking and main roads. • Or you are trying to find a specific department or restaurants in an enormous shopping malls. • Since GPS is not working indoors, do we have any other better choose, except for the existing i-beacon and Wi-Fi positioning systems? 4 3D Taipei Main Station MAP Motivation: Indoor Navigation in Taipei Main Station
  108. 108. ❖Taiwanese manufacture ASKEY Computer was requesting ITRI to provide 5G CORAL Fully Distributed EFS&OCS and AR solutions for AR Navigation and Advertisement services in Taipei Main Station. ❖Video of an exemplary AR Service Scenario in Train Station Shopping Mall 5G CORAL Use Case: Distributed Computing for Indoor AR Navigation/Advertisement 5 ⚫ Low End-to-End (E2E) Service Latency to fulfill better user experience (e.g., < 1sec) ⚫ Support High User connection Density ⚫ Heavy Computing Loading shall not be happened in user’s smartphone – Small Size (database) User APP – Low power consumption ⚫ Indoor Localization precision < 1 meter Performance Requirements
  109. 109. Distributed Computing for Heavy Load AR Recognition 6 Fully Distributed Computing Resource Orchestration Benefits Low Latency (E2E): Minimize computing latency by processing image recognition and navigation tasks at the EFS Connection density: Increase number of connection by distributing the incoming requests Service Reliability: Overcome Single Point of Failure (SPF) by centralized distributed computing mechanism Crashed!! Centralized Load Balanced Controller Non-Centralized Load Balanced system SPF Crashed!! FCD FCDFCD FCDFCD FCD FCD FCD Traffic Jitter FCD: Fog Computing Device
  110. 110. Optimization of Fully Distributed Computing Resource Orchestration • AI CNN offline trains the dispatching model of computing requests for Distributed FCD Cluster. • Obtain online load balancing optimization among Distributed FCDs in Cluster. FCD FCD FCD FCD FCD FCD CNN offline Training with Fully Distributed Computing Resource Orchestration AI SoC Module 1 2 43 65 7 8 7 Distributed FCD Cluster (No:1~6) No Central Controller • Network Capacity Constrain • Delay Constrain • Network Topology • Computing Capacity • Load Balanced Constrain Training Input Data Trained Model in each FCD for Resource Allocation Optimizer (request dispatcher) Decision time range: 0.3ms~1ms HPF: High Performance FCD: Fog Computing Device HPF PC FCD 3 1 25 6 4
  111. 111. 8 Performance Testing Configuration for AR Image Recognition in Distributed Fog Computing Cluster preview camera send images & beacon ID features extraction features detection features query Target determine object rendering UI Display local images Web CAM/Smart Phone/AR Glasses E2E Low latency < 500ms AR Image Recognition Service Flow Projector/Smart Phone/AR Glasses nVidia TX2 FCD
  112. 112. Distributed Fog Computing with Native AR application • Using TX2 as Fog CDs without Virtual Machine • The E2E latency, measured by Timers 1, 2,3 and 4, is 279ms. • Including the time for the Distribution Handler to update the Statistics with all of the databases(step 2, 3), the time cost by the Resource Allocation Optimizer(step 4, 5) and the time for the Distribution Handler to read the Distribution Decision result and dispatch the job to AR Server(step 6, 8). 9 Virtualized Software Module Distributed Fog CD Manager Design
  113. 113. 10 • Using TX2 as Fog CDs with Container – User Plane virtualized by LXD – Control Plane signaling by FogO5 • The E2E, measured by Timers 1, 2, 3 and 4, is 317ms. Distributed Fog Computing with Container based AR application Virtualized Software Module Distributed Fog CD Manager Design
  114. 114. Fog Computing Device Software Platform Spec. Have developed modules and prototypes: • Fog Virtualization Layer Solutions • Docker/LXD virtualized container technologies • Fog Middleware Solutions − RESTFUL API − D2D based Wireless Relay Mesh Networking with Fast Deployment SON, Smart routing, and Broadband Relaying − Fog Plug&Play Configure Agent − Fog Application Monitor Management Agent − Fog Parallel Computing Control − Resource Discovery Agent • Fog Application and Service Prototypes − AR Navigation − Smart Lamp Pole (S-L-P) Video Surveillances and Recognition can identify/recognize illegal parking on red lines, roadside parking spaces − IIoT Robot Fog Computing − Stadium VR360 Broadcast Multicasting OK Under Developing Open Source Module Status: IIoT Robot Fog Computing SoC Drone Fleet Flight Control for Fast Network Deployment Augmented Reality Indoor & Outdoor Navigation Stadium VR360 Broadcast/Multicast Internet of Things Cloudlet Hotspot S-L-P Video Surveillances and Recognition Fog Application and Services Fog Virtualization Layer Hardware Platform Wi-Fi/LTE cV2X Container RAT D2D Wireless Relay Mesh Networking Fog P&P Configure Agent Fog Distributed Computing Service Migration Resource Discovery Agent Fog Application Monitor Agent Fog Security Management VIM interfacing Container Container Container Container Application Support API API API API API Fog Middleware Application Services NA OCS clients 11
  115. 115. Fog Computing Device Hardware Spec. 12 Fog Computing Device (FCD) Reference Price $720 Euro
  116. 116. Conclusions • Technology Objectives of Fully Distributed Fog Computing System • Industry Impacts of Fully Distributed Fog Computing System – New Solution for Indoor Navigations – New Business model by AR Advertisements – Successfully done the technical transformation to Taiwanese Manufactory and ongoing deploying in Taipei Train Stations – Potential Technologies for the Fog Computing of Car Fleet and UAV Fleet 24 June 201913
  117. 117. Q&A Thank you!!
  118. 118. preview camera send images & beacon ID features extraction features detection features query Target determine object rendering UI Display local images Web CAM/Smart Phone/AR Glasses Wi-Fi EFS in FCD E2E Low latency < 500ms Wi-Fi AP #n FCD#n Etherswitch RJ-45 RJ-45 Wi-Fi AP #1 FCD#1 Service Flow:AR Video Recognition Projector/Smart Phone/AR Glasses Ultra low latency Load Balanced Distributed Computing Cluster Enterprise Cloud Internet Cloud OCS Monitoring Distributed Fog CD Cluster Deployments of Distributed Computing EFS and OCS Filtered by i-Beacon i-beacon Internet Cloud AR Computing E2E Low latency 5 sec Enterprise Cloud AR Computing E2E Low latency 1.5 sec EFS: Edge and Fog computing system FCD: Fog Computing Device OCS: Orchestration Control System 15

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