The End to End FutureX Network for 5G Vision and Expanded Role for OpenAirInterface

Theodore(Tod) Sizer

EVP, Smart Optical Fabric and Devices Lab

Nokia Bell Labs

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Bell Labs: Defining, then Inventing the future

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The Goal

4 © Nokia 2018

The Innovations

Transistor Solar cell CCD Laser/fiber optics

Satellite comms UNIX/C/C++ Universe origin Coherent Optics

Super-resolution microscopy

AI/CNNs

Cellular comms

The Internet

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T H E I M P E R A T I V E

“Productivity isn’t everything, but in the

long run it is almost everything”

Paul Krugman

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S T A G N A T I O N

I N

P R O D U C T I V I T Y

G R O W T H

2016 1900 1950 1960

ELECTRICITY & EARLY NETWORKS AGE

INFORMATION AND COMMUNICATIONS AGE

P P

4%

3%

2%

1%

0%

US Productivity Growth

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8 © Nokia 2019

Physical industries Digital industries

30% 70%

Share of GDP Investment in ICT Annual productivity growth (15 year average)

2.7%

.7% 70% 30%

Source: The Technology CEO Council

T A L E O F T W O

I N D U S T R I E S

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Consumer:

Many smartphones

Few centralized clouds

E-commerce and social

platforms

Best effort internet

connectivity

Industrial:

Myriad ‘things’

Multitude of edge clouds

Augmented intelligence

control platforms

High performance,

dynamic, deterministic

networking

H U M A N

I N T E R A C T I O N W I T H ‘ D I G I T A L ’

W I L L C H A N G E

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OT Operation Tech

ICT Information Communication Tech

Mission-critical Carrier-grade

Business process

control

Media delivery

&

information

services

Specialized

General-

purpose/

standardized

Slow (decades) Rapid

(months to

years)

Reliability

Technologies

Service(s)

Rate of tech

change

I C T & O T

C O M E

T O G E T H E R

⟶ ‘ I OC T ’

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Bandw

idth

Latency

10kbps

1Mbps

100Mbps

10Gbps 360 Video VR+VRAN+Vehicles

People & Things System Control

1ms 10ms 100ms 1s 10s 100us

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E V O L U T I O N T O M I S S I O N - C R I T I C A L

A P P L I C A T I O N S

PRECISION & AUGMENTED

INTELLIGENCE

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M O D E R N I Z A T I O

N

O F I N D U S T R Y D R I V E S

M A S S I V E

E C O N O M I C

I M P A C T

Industry Sites

Transport venues & ports 50,000

Military bases 10,000

Warehouses 3,300,000

Industrial & manufacturing 10,710,000

Oil & gas 8,000

Power generation 47,6000

Water utility plants 140,000

Mining 54,000

Hospitals & labs 263,000

Total: 14,582,600

Comparison: Global base stations sites:

~7M Source: Harbor Research

$3.8T to $11T

Economic value

of IoT (by 2025)

Source: McKinsey

up to

11% of global economy

(in 2025) Source: McKinsey

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The Future X Network

E2E Networks are Key Enablers of the Future

Converged

Edge Cloud 2 Software defined,

end-end

Smart Network Fabric 3

Universal

Adaptive Core 4

Access agnostic converged core

modular, decomposed network functions

Common data layer

Programmable

Network OS 5

Dynamic customer services

Dynamic network optimization

Management

&

Orchestration SDN NFV

Multi-operator federation

self-optimized coverage & capacity

Massive

Scale Access 1

Long fibers

Access

Remote

Short waves & wires

Digital Value

Platforms 7 ANP, CSP, ICP,

Vertical apps

External data sources

Open APIs

Augmented

Cognition Systems 6 Machine

learning Analytics

Humans

& Machines

Dynamic

Data Security 8

• New trust framework

• Ecosystem sharing

• Mass edge monitoring

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Distributed cloud support for vRAN and Industrial applications

Confidential

• Disaggregation of RAN components integration of transport elements/performance

• New applications require advanced RAN performance

• Support for Network slicing in an E2E Network

• New Opportunities for OAI?

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Challenge: Dynamic Fabric for Industrial applications

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• The E2E network must evolve from Best Effort Networks to Dynamic Deterministic Networks.

• Standard packet-based networks necessarily exhibit non-deterministic latency variability, especially under load.

• Overlay networks to provide Deterministic Performance per application does not scale economically as the number of 5G applications grow.

• Dynamic learning/adaptation for robust E2E Reliability is essential for mission critical 5G Applications.

• Time to reconfigure: The turn-up/tear-down challenge SDN is essential.

Cloud RAN, Industry 4.0, and 5G Mission Critical applications drive new performance requirements

In today’s DC (measured)

What we need for time sensitive

apps

Target = remove delay variation for time sensitive apps

Latency (s)

Latency (s)

Latency through 10 state-of-the-art DC switches

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Dynamic Deterministic Network Performance

Key Elements to support Dynamic Deterministic Performance for new 5G use cases:

E2E circuits with rapid (~100ms) and prioritized provisioning and teardown through full SDN control of access, metro, core and DC

At low deterministic traffic load, TSN (Time Sensitive Networking) can be employed.

At high load new solutions needed – evolution of TSN standard towards scheduled synchronous Ethernet and optical solutions to rapidly configure and meet performance guarantees.

Deterministic Performance is essential to support emerging 5G Use cases

Converged

Edge Cloud 2 Sof t war e def ined, end- end

Smart Network Fabric 3

Universal

Adaptive Core 4

Access agnostic converged core

modular, decomposed network functions

Com m on data layer

Programmable

Network OS 5

Management &

Orchestration

SDN NFV

self - opt imized cover age & capacit y

Massive

Scale Access 1

Long fibers

Access

Remote

Short waves & wires

Digital Value

Platforms 7 ANP, CSP, I CP, Ver tical apps

External data sources

Open APIs

Augmented

Cognition Systems 6

M achine lear ning

Analyt ics

Hum ans & M ac hines

Dynamic

Data Security 8

Nokia FutureX Network

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• Asset

- Use existing Polarization State sensors as a monitor

• Opportunity

- Use Machine Learning to identify Polarization state events.

- Classify events in real time as normal or potential fiber disruption.

- Proactively reroute traffic for the high reliability network.

Confidential

Network Reliability Enhancement ML Monitoring of the mechanical stress of fibers

Proactive fiber cut detection and re-routing to avoid Network outage

buried optical f iber

Reactive

Rerouting

Trigger

Proactive

Rerouting

Trigger

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Challenge: Industrial Use case requirement: Localization

10m Wi-Fi density

1m

10cm

1cm

Accura

cy

AP intersite distance (m)

0

20

60

40

80

100

Wi-Fi density Small cell density 10m

ToA – Time of Arrival – Uses time of flight from multiple sites for location through

triangulation -- requires high levels of network synchronization, and slot

information

AoA – Angle of Arrival – Uses antenna arrays to determine radio direction –

multiple sites can use triangulation to provide location of user per slot.

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Challenge: Multiple Industrial Requirements

(4 Slice Types x 5 Slice Specifics) per industry x 1000 industries = 20000 simultaneous optimizations

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Use Cases: Opportunities with Dynamic Network Operation

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SDN Enabled

CPE

RRH

Base Station

SDN Enabled

Access Node Core Router

Access/Aggregation Metro Core

E2E Slice, e.g., E2E Slice 1 := RAN Slice 1 + X-haul Slice 1 + Core Slice 1 E2E Network Slice

(Technology-Agnostic Abstraction)

Slice Stitching Operation

X-haul Slice Core Slice RAN Slice Domain-

Specific

Network Slice (Technology-Specific

Abstraction)

Downlink video High Latency Low reliability

Uplink video Low Latency High reliability

Application Server

Application Server

The new Industrial Revolution demands new communication solutions for Industry to grow overall productivity, and thus opportunity for all people.

Radio access networks are disaggregating requiring a focus upon access,

transport and cloud performance.

New application solutions, such as localization, offer great opportunity but

also challenges in synchronization and performance.

Tools such as OAI solutions can provide great advantage to show and create these new communication solutions, if evolved to support new requirements.

Essential Messages