Presentation at AfricCom 2018, Cape Town, SOUTH AFRICA

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Leveraging SDN/NFV as key stepping stones to the
5G era in emerging markets
Sabelo Dlamini

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Contents
• Vision of 5G
• Software Defined Networking (SDN)
• Network Function Virtualizations (NFV)
• Research Group Objectives
• Testbed Architecture
• Emerging Market Use Cases
• Current Research/Topics

3. 3
Vision of 5G
• Enhanced Mobile Broadband
– Mobile Broadband addresses the human-centric use cases for access
to multi-media content, services and data. The demand for mobile
broadband will continue to increase, leading to enhanced Mobile
Broadband.
• Massive Machine type Communication
– This use case is characterized by a very large number of connected
devices typically transmitting a relatively low volume of non-delay
sensitive data. Devices are required to be low cost, and have a very
long battery life
• Ultra-reliable and low latency communications
– This use case has stringent requirements for capabilities such as
throughput, latency and availability. Some examples include wireless
control of industrial manufacturing or production processes, remote
medical surgery, distribution automation in a smart grid,
transportation safety, etc.
Usage scenarios for IMT for 2020 and beyond.
Source: IMT Vision – IMT for 2020 and beyond

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Vision of 5G…
5G use case families and related examples Source: NGMN 5G White Paper

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Software Defined Networking
• Enable innovation/differentiation
• Accelerate new features and
services introduction
• Simplify provisioning
• Optimize
performance
• Granular policy
management
• Decouple:
• Hardware & Software
• Control plane &
forwarding
• Physical & logical
configuration
Programmability
Centralized Intelligence
Abstraction
Data Plane
Hardware Abstraction Layer
Switching Silicon
Control Plane
e
Network Operating System
Applications
API API API API
NBIs
SBIs
SDK APIs

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Network Function Virtualisation (NFV)
1. The objective of NFV is to translate the classic network appliances
to software modules
– Running on high volume servers with high volume storage
– Interconnected by generic high volume switches
– Automatically orchestrated and remotely installed
2. NFV is a novel paradigm that presumes that the network functions:
– Are implemented only as software (programs)
– Can run on top of common servers
3. NFV has to fix the following main issues:
– Performance
– Co-existence and portability
– Automation
– Scalability
– Resilience

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Network Function Virtualisation
• From: dedicated appliances
• To: server software/VMs
• Widely enabled by SDN
• Forwarding plane modifiable by remote
software
• ETSI NFV ISG
• Formal partner
• They do requirements
• We do specifications, POCs
• Common leaders, members, objectives
• OPNFV
• Cooperation, collaboration
Programmable Data Plane
Network Apps Business Apps
Network Services
Function Virtualization / Orchestration /
Routing
OpenFlow Control

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SDN/NFV & Open Innovation
Creates competitive
supply of
innovative
applications
by 3rd parties
Open Innovation
Software
Defined
Networking
Network
Function
VirtualisationCreates
abstractions to
enable faster
innovation
Leads to agility,
Reduces CAPEX and
OPEX
1. NFV and SDN are highly complementary, they are mutually
beneficial but not dependent on each other (NFV can be deployed
without SDN and vice-versa)
2. SDN can enhance NFV performance, simplify compatibility,
facilitate operations
3. NFV aligns closely with SDN objectives to use software,
virtualization and IT orchestration and management techniques

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Research Group Objectives
• Provide Thought Leadership – leadership and direction in the development of the next generation networks
• Human Capital Development – knowledge and skills developments in the core and RAN technologies
• Drive Innovation – technical demonstration of new methods, ideas and products
• Standards and Policy Developments – contribute with meaningful results and evidence-based policy contributions
• Contextualise Technologies – adopt/adapt new technologies for the country and continent use cases
• 4th Industrial Revolution – contribute to positioning the country for the next industrial revolution with practical and tested use
cases

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Testbed Architecture
Lifecycle Service Orchestration
Network Slice Layer
Service
Orchestration
Software
Network
Functions
Physical
Infrastructure
Internet
SDN
Controller
Radio Access Network Core Network Internet
Future Wireless Networks Advanced Networks
RAN Network
Management and Orchestration
Wi-Fi
Network
Orchestrator
Spectrum
Toolbox
Edge
Computing
EPC Core
SDN Core
ImplementedNot Implemented

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Fundamental 5G/4G core network functionality
• Functionality includes the main network functions of the 3GPP 5G CN and the 3GPP EPC
– UE connectivity manager for Android and Linux
– AMF(MME-) – enabling authentication, authorization, handover, idle mode, SMS
– SMF(PGW-C+) – allocation of IP addresses and data paths, data path reselection
– UDM/UDR (HSS) – including S6a Diameter interface
– gNB(eNB) emulation with NAS overlay over IP communication
– UE emulation with NAS support
• Currently emulated
• To be integrated with commercial eNBs
• To be used with COTS (normal) phones
Implementation of the 3GPP 5G architecture and the 3GPP EPC architecture (Release 14).

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Data Path Diversity
• Develop capability by having different research topics in this area with
partner institutions
• Explore real-time media transmission with the Media Technologies
research group
• The implemented functionality in the SMF enables the following
scenarios:
– Support for multiple APNs and dedicated bearers
– Data path offloading for specific bearers (when connected to specific
gNBs)
– Congestion triggered, network only data paths change
– Fast handover between Local Service Hosts (with and without IP address
continuity)
Implements a large number of deployment scenarios for data path diversity using the CUPS feature

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NB-IoT core network extension
• Integrate with other research groups and competency areas that are
involved in IoT for research projects
• The NB-IoT extension is addressing the current stringent needs of
the 5G use cases to provide low power, low cost efficiency
communication for a massive number of devices
• A prototype including the following features:
– Control Plane CIoT EPS Optimization
– Attach without PDN connectivity
– Non-IP Data Delivery (NIDD) and IP data delivery
– Network Exposure Function (NEF)/Service Capability Exposure
Function (SCEF)
Implementation of the 3GPP NB-IoT features enabling the demonstration of low energy IoT communication

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Benchmarking
• Develop capability and provide this as a service to different service providers
• The benchmarking tool and environment include the following functional
features:
– Flexible and intuitive eNB topology configurations
– Flexible subscriber mobility and load patterns (can replay workloads)
– Support for x10000 emulated subscribers and x100 eNBs
– Support for S1-MME and S1-U interfaces and procedures
– Monitoring parameters - 50+ metrics including:
• Quality: Success rate, procedure delay at benchmarking tool
• Performance: procedure delay, compute and storage in the network
• On demand extensible for different:
– RAN topologies or functionality,
– Mobility and resource patterns
– Interfaces towards the network
Providing quantitative evaluations of different customized core networks on top of different resource
infrastructures

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Multi-slice support
• Network slicing can used to explore the technical functionality of different business
models (e.g. new business models for MVNOs)
• Management and orchestration of network slicing can yield research outputs
• The Network Slice Selection Function (NSSF) can be placed as a separate
component enabling:
– Indications to the AMF(MME-) to redirect the UE during attachment to another slice
– Indications to the gNB/eNB to direct the UE during sequent procedures to the
appropriate slice
• NSSF can be integrated with the MME and with the gNB to act as a proxy for
multiple slices
Uses the 3GPP DÉCOR for slice selection as an independent network function

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Edge-Central Functionality Split
Private Network
Low Delay Operator Network
Edge-Central Functionality Split
Backhaul
MVNO Network
Edge Node
Central Node
Highly depends on the type of edge network operator deployed and on the backhaul capabilities
• Edge computing can be used in different use cases that
require low latency and faster decision-making
• Edge computing can be a key enabler of the next industrial
revolution
• Use cases such as:
– Freeway Surveillance with edge nodes to support decision
making at the edge of the network
– Manufacturing – partner with MSM to explore the use of edge
computing in manufacturing
– Defense and aerospace applications

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Spectrum allocation alternatives for local networks
• Using Unlicensed Spectrum only
– Using an independent access point with a separated modem
like WiFi now
– 5G-U / LTE-U – deployment of an LTE base station in
unlicensed spectrum (e.g. 5GHz)
• Combining Licensed and Unlicensed spectrum
– Carrier aggregation with WiFi
– Licensed assisted access (aggregating unlicensed access in the
same base station)
• Using licensed spectrum with limited lease
– Licensed Shared Access (LSA) – spectrum is allocated through
an independent broker
– Authorized Shared Access (ASA) – spectrum is leased by the
operator
Core
Network
LTE-U
Core
Network
WiFi

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Smart Agriculture Use Cases
• Water management – providing remote control of water metering and device control
• Agriculture – connecting specific sensors with low cost wide-area wireless connectivity
• Earthquake detection – providing a sensor grid for data acquisition
The use cases are rather similar, albeit within different network conditions: connecting reliable an overlay of
fixed sensors

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Enterprise 5G Networks Use Cases
• Secure and customized local access network (e.g. local WiFi, NB-IoT, LoRa network)
• Provide customized connectivity
• Secure backhaul connectivity
• Backhaul selection and aggregation
• Remote management and orchestration
• Management of the backhaul and of the edge routing
• Management of the data synchronization between edge and central locations
Develop a secure local network / 5G overlay for bringing edge intelligence to the existing enterprise networks

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Current Research/Projects
• PhD Level
– Optimisation of Autonomous Systems using Fog Computing
– Network slicing optimization methods for automation
• MSc Level
– SDN planning in emerging markets through optimal controller placement
– SDN Controller comparison for WAN migrations
– Energy Efficiency in Fog computing systems
Human Capital Development with specific focus on addressing emerging market challenges

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Partnerships/Collaborations
• Universities
– University of Cape Town
– University of Zululand
– University of Limpopo
• International
– Fraunhofer FOKUS – Open5GCore (Part of 5G Playground)
Partnership with leading local institutions in human capital development and technology localisation

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Thank you
sabelo.dlamini@csir.co.za