ml for mobile operators - itu · 3g 4g 5g centralized uson platform geo engine anr mlb ai...
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ML for Mobile OperatorsDr. Salih Ergut, TURKCELL
Xi’an, China
April 25th, 2018
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TURKCELL: Leader Operator in the Region
50+ millionsubscribers
Listed on NYSE &
Istanbul Stock Exchange
$9.6 BillionMarket cap
45%
31%25%
TURKCELL Operator 2 Operator 3
Turkish Mobile Market
33
mill
ion
• Turkcell R&D company• ~1,000 R&D personnel• Dedicated 5G R&D team
Operating in
9 countries
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TURKCELL: Leader Digital Operator in the Region
• Voice, Data, Messaging
• Broadband Internet
Traditional
• Broadband
• Mobile App
IPTV
• BiP(messaging)
• fizzy (music)
• lifebox(storage)
Digital Apps
• Mobile payment
PayCell
•Fleet tracking
•Smart meeting
•NB-IoT, CAT-M1
IoT
•Digital only service
•Up to 62GB monthly data
Lifecell
•A TURKCELL energy distribution company
Energy
•Producing Turkey’s first electric car
Automotive
A TURKCELL FinTechcompany
TURKCELL is one of the 5-company consortium to produce Turkey’s first domestic electric car
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Data is the new oil of digital world
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Descriptive
• Customer locations
• Mobility patterns
• Network performance analysis
• Investment prioritization
• Coverage holes
• ...
Predictive
• Churn prediction
• Next best offer
• Customer experience management
• Customer segmentation
• ...
ML & AI
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ERA
• Wide range of use cases with diverse needs• eMBB – URLLC – mMTC• Network slicing
• Increased network complexity• Densification• Edge intelligence• Dynamic composition of network functions
• Flexible architectures in core and radio access• Virtualization• Softwarization• Cloudification
Increased use of ML for network orchestration, management, monitoring, ...
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Evolution of Centralized SON towards 5G
Radio Network
Data Processing
OSSs
Location
Aware SON
Virtual Drive-testing
of VIP routes
Automated Planning
Densification Support
“
Automated RAN
Optimization
Launch
Configuration
Optimization
Healing
“
GSM, UTRAN, LTE, 5G
Geo-Engine
Service (slice)
Centric SON
VoLTE
NB-IoT
Cat-M
Ultra Latency
“
SON for Backhaul
& Core Network
Configuration
Capacity
Monitoring
Mobile & Fixed
Convergence
WTTX Plan
New Site
Capacity
Site Removal
AI Based Prediction
Customer
Experience
CEM
Radio
Propagation
Atoll
Core &
Backhaul
TN Core
Fixed
Network
FixedCrowd/
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Turkcell Architecture
OSS
Network
2G
3G
4G
5G
Centralized
uSON Platform
Geo
Engine
ANR MLB
AI
Algorithms
CEM
Turkcell External
Systems
Web User Interface
Geo
Analytics
SON
Modules
CRM
Inventory
AnalyzeOptimize
24/7
SON
Observe Service Quality
Investment
Operational Efficiency
Benefits
Clustering
Classification
ML Methods
Prediction
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Real-time network monitoring
Core Network
MEC
MEC
Real time Monitoring ML Engine
• Real time network performance monitoring is missing in today’s operator network
• Critical for immediate resolution of network degradations
• Can be achieved through distributed computing at edges due to excessive traffic load of centralized solutions
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• Predicted QoS is essential in URLLC applications such as platooning
• Needs to be estimated at the edge with cooperation from terminal
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Data Collection in a Multi-vendor Network
Operator A--------------------------
Dataware HouseBig data
App 1
Operator B--------------------------
Dataware HouseBig data
App 1Each vendor has to repeat for each operator- Identify available data (description,
frequency, delay, etc.)- Integrate with data sources- Modify ML algorithms
App 2
Operator has to provide the following to each operator- Available data list (vendor
specific)- Assist in integration to own
network- Compare the performances of
competing systems
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Founders
> 500 Members including Turkcell
AI and Applied ML Project Group
Focus Areas• Network Operations, Optimization and Planning• Customer Behavior Driven Service Optimization• Multi-vendor Data Exchange Format
Participation Criteria• Operators to provide data• Vendors to open solution interfaces
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Thank you