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Network Intelligence.
Engineered.
Network Intelligence
Evolutionto5Gwillseeincreasein
networkcomplexity
2G
3G
4G
5G
1990s 2000s 2010s 2020s
Complexity
Network function
virtualization
Vast differences in
terminal capability
Significant variation
in traffic demand
Completely new &
varied use cases
Dealing with opex and network performance in this environment will go beyond the reach of humans
Multiple coexisting
technologies
Machines and
humans
engineer intelligence
together
Network Intelligence.
Engineered.
Our approach aims to create self learning
networks to optimize workforce and network
efficiency as well as improve network performance.
Augmentinghumansandnetworks
Augmenting
human
capabilities
Augmenting
network
functionality
Network
Intelligence.
Engineered.
network services network products
Empowering engineers with
intelligence to increase efficiency
and quality of their work
Introducing intelligence into our
products to create a network that
learns as it is used
6Months Ahead, to address capacity bottlenecks
1 Sec To access required field instructions
2X Easier to deploy
30% Reduction in field dispatches
Newlevelsofefficiencyandperformance
Augmenting
human
capabilities
Up to
10% Energy reduction on node level
50% Reduction in OPEX for future RAN transport
2X Faster inter-frequency handover
99% One (1) incident for every 100 alarms
Augmenting
network
functionality
Network
Intelligence.
Engineered.
network services network products
6Months Capacity planning, boosted by AI
1 Sec AR assistant * for Ericsson Radio System
2X Connected technician
30% Radio site analytics
Newtypeofnetworkservicesandproducts
Augmenting
human
capabilities
10% Energy efficiency
50% Transport Intelligent Function
2X AI-enabled handover
99% Autonomic incident management
Augmenting
network
functionality
Network
Intelligence.
Engineered.
network services network products
Up to
* Prototype
“Machine learning is assisting our
engineers to make our mobile
networks more proactive and
immediately responsive to the needs
of our customers. Vodafone is leading
the industry in using AI in our radio
networks because of the pioneering
work between our Networks Centre of
Excellence and Ericsson.”
Francisco (Paco) Martin,
Vodafone Group Head of Radio Products
Feedbackfrom
customertrial
Whatwebringtothetable
A network first
approach
Training set
based on
anonymized
network data
Products &
services in
collaboration
Trials performed
on live Networks
Characters for Embedded characters:
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ΣΤΥΦΧΨΩΪΫΌΎΏЁЂЃЄЅІЇЈЉЊЋЌЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯЁЂЃ
ЄЅІЇЈЉЊЋЌЎЏѢѢѲѲѴѴҐҐәǽẀẁẂẃẄẅỲỳ№—–-
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γδεζηθικλνξορςΣΤΥΦΧΨΩΪΫΌΎΏЁЂЃЄЅІЇЈЉЊЋЌЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯАБВГДЕЖЗИЙКЛМНОПРСТУФХЦ
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ŕŖŗŘřŚśŞşŠšŢţŤťŪūŮůŰűŲųŴŵŶŷŸŹźŻżŽžƒȘșˆˇ˘˙˚˛˜˝ẀẁẃẄẅỲỳ‘’‚“”„†‡•…‰‹›⁄€™ĀĀĂĂĄĄĆĆĊĊČČĎĎĐĐĒĒĖĖĘĘĚĚĞĞĠĠĢĢĪĪĮĮİĶĶĹĹĻĻĽĽŃŃŅ
ŅŇŇŌŌŐŐŔŔŖŖŘŘŚŚŞŞŢŢŤŤŪŪŮŮŰŰŲŲŴŴŶŶŹŹŻŻȘș−≤≥fiflΆΈΉΊΌΎΏΐΑΒΓΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΪΫΆΈΉΊΰαβγδεζηθικλνξορςΣΤΥΦΧΨΩ
ΪΫΌΎΏЁЂЃЄЅІЇЈЉЊЋЌЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯЁЂЃЄЅІЇЈЉЊЋЌ
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ŐőŒœŔŕŖŗŘřŚśŞşŠšŢţŤťŪūŮůŰűŲųŴŵŶŷŸŹźŻżŽžƒȘșˆˇ˘˙˚˛˜˝ẀẁẃẄẅỲỳ‘’‚“”„†‡•…‰‹›⁄€™ĀĀĂĂĄĄĆĆĊĊČČĎĎĐĐĒĒĖĖĘĘĚĚĞĞĠĠĢĢĪĪĮĮİĶ
ĶĹĹĻĻĽĽŃŃŅŅŇŇŌŌŐŐŔŔŖŖŘŘŚŚŞŞŢŢŤŤŪŪŮŮŰŰŲŲŴŴŶŶŹŹŻŻȘș−≤≥fiflΆΈΉΊΌΎΏΐΑΒΓΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΪΫΆΈΉΊΰαβγδεζηθι
κλνξορςΣΤΥΦΧΨΩΪΫΌΎΏЁЂЃЄЅІЇЈЉЊЋЌЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫ
ЬЭЮЯЁЂЃЄЅІЇЈЉЊЋЌЎЏѢѢѲѲѴѴҐҐәǽẀẁẂẃẄẅỲỳ№—–-

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Network Intelligence. Engineered.

  • 2. Evolutionto5Gwillseeincreasein networkcomplexity 2G 3G 4G 5G 1990s 2000s 2010s 2020s Complexity Network function virtualization Vast differences in terminal capability Significant variation in traffic demand Completely new & varied use cases Dealing with opex and network performance in this environment will go beyond the reach of humans Multiple coexisting technologies
  • 3. Machines and humans engineer intelligence together Network Intelligence. Engineered. Our approach aims to create self learning networks to optimize workforce and network efficiency as well as improve network performance.
  • 4. Augmentinghumansandnetworks Augmenting human capabilities Augmenting network functionality Network Intelligence. Engineered. network services network products Empowering engineers with intelligence to increase efficiency and quality of their work Introducing intelligence into our products to create a network that learns as it is used
  • 5. 6Months Ahead, to address capacity bottlenecks 1 Sec To access required field instructions 2X Easier to deploy 30% Reduction in field dispatches Newlevelsofefficiencyandperformance Augmenting human capabilities Up to 10% Energy reduction on node level 50% Reduction in OPEX for future RAN transport 2X Faster inter-frequency handover 99% One (1) incident for every 100 alarms Augmenting network functionality Network Intelligence. Engineered. network services network products
  • 6. 6Months Capacity planning, boosted by AI 1 Sec AR assistant * for Ericsson Radio System 2X Connected technician 30% Radio site analytics Newtypeofnetworkservicesandproducts Augmenting human capabilities 10% Energy efficiency 50% Transport Intelligent Function 2X AI-enabled handover 99% Autonomic incident management Augmenting network functionality Network Intelligence. Engineered. network services network products Up to * Prototype
  • 7. “Machine learning is assisting our engineers to make our mobile networks more proactive and immediately responsive to the needs of our customers. Vodafone is leading the industry in using AI in our radio networks because of the pioneering work between our Networks Centre of Excellence and Ericsson.” Francisco (Paco) Martin, Vodafone Group Head of Radio Products Feedbackfrom customertrial
  • 8. Whatwebringtothetable A network first approach Training set based on anonymized network data Products & services in collaboration Trials performed on live Networks
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