Jongkwan Park. Head of Network Technology R&D Center, SK Telecom

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1 Jongkwan Park Head of Technology R&D Center, SK Telecom 0

2 G Requirement & Architecture SKT s Journey for Future OSS SKT s toward Journey 5G to Future OSS Future OSS Future OSS Vision & Consideration 1

3 SK Telecom s Mobile History SK Telecom has always been the first-mover in mobile network evolution including 5G to enhance mobile subscriber s experience 5G 500Mbps LTE-A 4.5G 900Mbps LTE-A Pro World s First 5G-LTE Interworking (2017.9) 5G Stadium Showcase (2017.3) LTE-A 300Mbps LTE-A M Carrier Aggregation 5G mmwave Mobility 3.6Gbps@170km/h (2017.2) 4G/LTE 10+10M Carrier Aggregation M Carrier Aggregation M Carrier Aggregation 4x4 MIMO 256QAM World s First 5G Connected Car ( ) 2G CDMA,1x & EVDO 3G WCDMA/HSDPA World s First 20Gbps Data-rate (MWC 2016) 1996~ / World s World s First First Korea s/world s First First Korea s Korea s First First World s World s First First World s World s First First World s World s First First World World First First 2

4 5G Key Driving Factors More than 1Gbps data rate for VR/AR services Less than 10ms latency for mission critical services Devices connected 20.8B 2.8 per person Exabytes Devices per connected month 35EB 6.4B 0.8 per person 7EB

5 Rethinking operational transformation for 5G Mobile Technologies Devices & Services Industry Growth Operations Operational transformations is needed to realize 5G Silo, Manual Unified, Autonomous 4

6 Operational Challenges in Today s Mobile Aggressive and continuous network expansion and architectural changes leads to heterogeneous and complex network that is expensive and difficult to manage Engineering Construction Operation TCO Access Efficiency Transport Siloed OSS Agility Core The 5G should be designed with network operating innovation in mind 5

7 Vision on Future Telco Infrastructure: ATSCALE SK Telecom have set the future evolution direction of Telco infrastructure mainly focusing on Scalable, Cognitive, Automated, Lean and End-to-end Scalable End-to-End E2E analytics E2E optimization E2E automation E2E operation Efficient resource use On-demand agility Adoptive operation ATSCALE Cognitive E2E network visibility Real-time analytics Intelligent optimal decisions Lean Open H/W, S/W Open Interface Modularized Standardized Automated Intelligent operations Self-configuration Self-optimization 6

8 End-to-end Architecture of ATSCALE Technology domains of ATSCALE: COSMOS, SDRAN, vcore, uctn, Unified-O, NG-OSS Unified-O COSMOS Low Latency Service Immersive Media Telco Service Fronthaul Edge DC Local NFV Orchestrator RNF Open & Programmable H/W CNF Service Orchestration and Exposure End-to-end Orchestration Virtualized Functions TNF Mobile Connectivity Functions Resource Abstraction Layer Transport Infrastructure Transport Open H/W Service Functions uctn POTN Virtualized Slice #1 Transport Infra Orchestrator ESF CSF OSF Centralized DC #2 Open & Programmable H/W #N NG-OSS (E2E (E2E Hybrid Hybrid Resource Mgmt., Cognitive & Intelligent Automation) NG-OSS NG-OSS Unified-O SDRAN vcore uctn Next Generation OSS Unified Orchestration Software-Defined RAN Virtualized Core Unified & Converged Transport N/W 4G L1/L2 WAN 5G RF Remote Unit SDRAN vcore uctn COSMOS Telco Data Center Infrastructure. COSMOS: Composable, Open, Scalable, Mobile-Oriented System 7

9 G Requirement & Architecture SKT s Journey for Future OSS SKT s toward Journey 5G to Future OSS Future OSS Future OSS Vision & Consideration 8

10 SK Telecom s Journey for Future OSS SK Telecom has implemented a phased operational strategy for evolving into 5G future OSS based on ATSCALE SKT s NG-OSS called TANGO Yesterday Layered & Siloed OSS - Manual operation Today Unified OSS - Manual & Rule-based operation with big data analytics Tomorrow Autonomous OSS - Autonomous operation & Manual assistant with AI/ML Engineering Construction Operation Engineering Construction Operation Engineering Construction Operation Access Access Access Access Access Access Transport More than 150 OSS Transport Consolidated OSS Transport Autonomous OSS Core Core Core Core Analytics Core Core Advanced Analytics AI/ML Big barrier: Difficulty of multi-vendor/purpose OSS integration in terms of DB, IF, Poral, Process 9

11 TANGO Overview TANGO is SKT Advanced Next Generation OSS to manage and optimize our networks in a cost-efficient and intelligent way Improving investment efficiency Optimized network investment analysis & process environment Reducing MTTR mean time to repair End-to-end real time network monitoring & correlation Analysis Planning tool OSS Integration Analytics Knowledge Unified DW AI/ML Innovative use case discovery environment Leading service innovation Systemized operation knowledges & closed loop control Minimizing human error 10

12 Application Layer TANGO Architecture TANGO consists of 6 components supporting overall operational domains of end-to-end network Executive Officer Operator Field Engineer Biz. Partner O Operation Unified Operation, monitoring, statistics and work management UI/UX EC Engineering/Construction O Operation A Analytics Real-time service analytics with network big data processing Mobile I Coverage prediction & Engineering N/W Inventory Investment Mgmt. D Data Repository Unified Assurance A Work & TT Mgmt. Analytics Platform EC Engineering Construction I Inventory Unified network planning and deployment Physical/logical network resource data management PF Unified DB Criteria Info. Configuration N/W Statistics Operation Info. Infra Physical / Virtualization Zone Web / Big Data Zone D Dataware house big data repository and data discovery Access Transport Core NFV 5G PF Platform Unified OSS Platform with open source s/w and virtualized infra. 11

13 Use Cases of TANGO Operation Rapid reaction support of network operator from single-view monitoring Single-view monitoring & fault correlation Optimization configuration optimization based on traffic condition and performance Root cause analysis & neighbor optimization Customer Experience Mgmt. Customer experience optimization per subscriber with end-to-end data Near Real-time CE-Index measurement Service area quality monitoring Traffic Optimization based TPO In-depth CEI/KPI analysis 12

14 Bharti Airtel partners with SK Telecom about TANGO TANGO was proven by global operator for absolutely appropriate solution for managing network capacities and optimizing mobile networks Telecom operator Bharti Airtel announced strategic partnership with SK Telecom, on September 13, 2017 known for using latest technologies, to build the most advanced telecom network in India. Source: Business Korea 13

15 Evolutionary Barriers for TANGO s Next Step Future OSS is expected for promising to overcome these barriers in 5G era Needs for Culture & Skillset Transformation Limited Data for AI/ML Lack of Standards (Data Model & API) Fears of Automation (service outage) Lack of Killer Use Case through Automation Hybrid NW Integration Complexity Needs for New Tech. Adoption (5G,IoT,NFV/SDN) Environments Technologies 14

16 G Requirement & Architecture SKT s Journey for Future OSS SKT s toward Journey 5G to Future OSS Future OSS Future OSS Vision & Consideration 15

17 Additional Operational Challenges in 5G Previous manual best-effort operational approach will be no longer sufficient for extreme flexible and dynamical requirements within dramatically reduced costs 2G IMS 5G 3G EPC 5GC 4G LTE 5GNR 16

18 Future OSS in 5G The only way that these difficult goals can be achieved is Future OSS with vastly increased automation in management and operation of 5G network Ratio 100% Present OSS Evolved OSS Future OSS (LTE) (Early 5G) (5G~) Manual Operations Zero-touch operation means extreme automation with seldom required manual intervention Autonomous Operations OSS Maturity 17

19 Future OSS Vision Future OSS should be evolved toward providing 1 Proactive operation, 2 Zero-touch optimization, 3 Sophisticated CEM, through iterative learning and prediction of network & Mobile Broadband Mission Critical Massive IoT Immersive Media Energy Saving & Security Service Agility Anomaly Detection Root Cause Analysis Next Best Action AI/ML & Big Data Connectivity End-to-end 5G Edge DC 5G Central DC IT server farm 18

20 Future OSS in Action 4 Discovery analytics ML, AI Non-real time zero-touch automation Undefined Case Data (Inventory, CE quality, quality, Log) Knowledges Experts 2 Real-time analytics Defined Case 3 Decision & Control AI Assistant ML based Analytics Pre-defined Rule Use Case Root Cause Analysis Service Outage Prediction CE Quality Predilection Deployment Recommendation Next Best Action Pre-defined Execution N/W Control Real time zero-touch automation 1 Data Collection End-to-end network Legacy NFV / SDN Aspects of consideration 19

21 Considerations Service Aspect Sophisticated management and optimization is required to accommodate a wide range of horizontal or vertical network services such as network slicing management Single efficient network Horizontal Slicing NasS: Vertical Slicing Voice Media Cars Things Voice Media Cars Things Today s network serving all service and devices A few network slicing for macro objectivate Several-hundreds vertical slicing for service specific customization 20

22 Considerations Orchestration Technology Aspect Hybrid network infra orchestration is required to implement gradually in order to minimize the impact of NFV/SDN integration Phase 1 Phase 2 Phase 3 BSS BSS BSS Service Portal EMS Legacy OSS MANO Evolved OSS EMS MANO EMS MANO Future OSS (Converged Orchestration) Legacy NFV Legacy NFV SDN Legacy NFV SDN No or limited interface with Independent MANO deployment Expanded interface with MANO supporting limited orchestration Fully integrated OSS supporting network and service + Major EMS function support aware autonomous orchestration 21

23 Considerations AI/ML Technology Aspect Both AI assistant and ML based analytics are required to automate and simplify network operation, through defining common data model AI Assistant ML based Analytics Cognitive Language APIs Anomaly Detection Root Cause Analysis Next Best Action Control ML Framework HCI New Model, Rule Voice UI / UX Conv. Image Q&A Data Set Discovery Analytics (Model learning, Verification, Test) Common Data Model Data Data Warehouse Knowledges (Inventory, CE quality, quality, Log) 22

24 Mgmt. & Operation Considerations Open Ecosystem Aspect Cooperation and alignment across the siloed industry is essential to achieve future OSS for realizing zero-touch management and operation Applications Analytics Orchestration, Mgmt., Policy Cloud & NFV Infra Mgmt. Control Open Source Initiatives SDO & Fora Supporting Associations 23

25 Conclusions Future OSS is not just developing a new state of the art technology It s a journey with real paradigm shift in whole areas Technology Technology should automate operational tasks, enabling people to improve results rapidly Technology should support the process and eliminate repetitive or tedious tasks People Process 24

26 Thank you 25