5G Networks
Architecture and Operations
Ravi Sharma
Dec, 2018
5G NETWORKS !1
5G Network for future

1.Wireless Networks Evolution
1.Wireless Networks Evolution 2
2. 5G Network - use cases: Mobility to Industry 4
3. 5G Networks KPI’s - Industrial grade reliability 6
4. 5G Architectural Changes & challenges 7
A. Cloud native Architecture 8
B. Network slicing - 5G Services Architecture 9
C. RAN Architecture Changes 10
D. Mobile edge computing 11
5. New horizons - AI/ML lead Operations 12
A. Zero Touch Services Orchestration 13
B. Cognitive Network Operations 16
C. Closed Loop Automation 18
6. Conclusion 19
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Wireless Network has evolved over the years from only voice(2G) to voice over
IP (4G LTE) networks. The traditional telcos are transforming towards CSP
(communication service providers), moving from traditional business of voice
and data, to OTT Apps ecosystem for mobile payments and infotainment .
In the latter part of 2000’s Internet has become the only solution for all day to
activity with advent of Smartphones on 3G/4G connectivity from mere mail
solution on 1990’s. Today NLP of Alexa and Google are moving the day to day
life of average individual tightly bound to mobile only ecosystem.
Video traffic on mobile network are increasing with the 3G, 4G becoming the
de-facto mobile connectivity around the world. According to ericsson mobility
report 2018, 4G technology will become most dominant wireless access by 2023.
The wireless standard for new 5G NR is also getting finalised and it will be
available for mass deployment by end of 2019, the limited trails are taking place
globally in 2018 with early basestation and MIMO designs.
The video traffic is going to be dominant with advent of more streaming &.
broadcasting services, augmented reality videos, virtual reality headsets,
increasing use of video calling and video surveillance solutions etc. The 5G
technology is bound to increase trend. The terms exabyte is coined for growth
of mobile internet traffic. (Source: Ericsson mobility report 2018 )
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Source : Ericsson Mobility Report, 2018

2. 5G Network - Use Cases: Mobility To
Industry
In the new era of Digital Service Providers (DSPs), new requirements challenges
service providers on legacy networks in terms of technologies and business
models. Thus arising a need for more mature wireless access to support people's
demand for digital lifestyle, and focuses on services which needs higher
bandwidth, such as high definition (4K) videos, virtual reality (VR), and
augmented reality (AR).
Considering the new advancement in media and platform services,
International Telecommunication Union (ITU) has classified 5G NR mobile
network services into three categories:
1. Enhanced Mobile Broadband (eMBB)-allowing seamless customer
experience from a broadband speed point of view and the rise of new
applications on-the-go such as UHD Augmented Reality;
2. Ultra-reliable and Low-latency Communications (uRLLC) -
essentially enabling the smart cities of the future by using internet of things
(IOT) and Industrial IOT;
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Source: Ericsson Mobility Report, 2017

3. Massive Machine Type Communications (mMTC)- a must for mass
deployment of autonomous car types of applications.
5G goals are aligned with the Operators vision globally where they want to
transform them self into a digital services provider by focusing on
1) Communication services, 2) Media, lifestyle apps & Content based services,
3) IOT services and 4) Cloud Based services
• Communication Services: The exponential growth in connected devices
and bandwidth will still remain a major driving factor while consumers expect
to have a significantly enhanced differentiated user experience.
5G NETWORKS !5
Source: ITU - 5G White Paper

• Media & Life style Apps : will be at the core of future digital services.
These services include all rich content oriented new services and business
models, such as, 4K/8K video, online gaming, Virtual Reality, etc.
• IOT Services: IOT Services will bring innovations within various industry
segments it serves with pre-packaged vertical solutions.
• Cloud Based Services: The 5G architecture will enable transformation in
network and introduce Network slicing to enable new active sharing among
Operators. It will also push uCPE and SDWAN as whole infrastructure will be
transform on telco cloud.
5G standards are evolving and the changes it brought to the networking
ecosystems are still evolving. ITU’s plan for 5G standard finalisation are show
below. It is expected to have mass deployment from early 2021-22.
3. 5G Networks KPI’S - Industrial Grade
Reliability
The ITU has also introduced the key aspirations for 5G technology over and
above LTE 4G technology. Many of them will rely on enhanced and more
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efficient management of the network, in addition to improvements in underlying
technologies and Radio Access bandwidth.
• 1000 times higher mobile data volume per geographical area. Approx 10-25
Gb/Site
• 10 to 100 times more connected devices. 1 Million/Km2
• 10 times to 100 times higher typical user data rate.
• 10 times lower energy consumption.
• End-to-End latency of < 5ms, in air latency <1 ms
• Ubiquitous 5G access including in low density areas.
• Reliability of 99.999%
• Services Deployment time to be reduced by 1000 in comparison with the
current 4G system apron 90 minutes
The 5G KPIs ensures that it can be used for not only connectivity consumers
but can easily be suitable for Industry users. The availability, reliability and
latency are inline with industrial use cases of autonomous cars, Industrial IOT
driving big factories etc. At the same time higher throughput and 3X spectrum
efficiency ensure seamless coverage for each and every users.
4. 5G Architectural Changes & Challenges
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The 5G KPIs and use case need the architecture changes from current 4G RAN
and Backhaul Network. 5G will completely revolutionised mobile networks for
accommodating the ever increasing data demands of users, services and
application. 5G require much complex management requirements based on the
softwarization of network resources. The ITU has defined a cloud native
architecture as a base line for 5G network. This has been achieved by control
plane user plane CUPS architecture.
The control and user plane separation divides complex control logic functions
for convergence into control planes, which reduces the costs of distributed edge
gateways(routers/switches/BBU etc.) deployment, interface load, and number
of alternative signaling routes. In addition, the control plane and user plane
separation supports scaling of the forwarding and control planes, which further
improves network architecture flexibility, facilitates centralized control logic
functions, and ensures easy network slicing for diversified industry applications.
ITU IMT Vision for 5G are shown in below picture which explains the three
main drivers 1)Softwarization 2)Flexibility & 3)Costomization
To achieve above following are the changes discussed in details.
A. Cloud native Architecture
End-to-end flexibility will be one of the defining features of 5G networks.This flexibility will
result in large part from the introduction of network softwarization where the core network
hardware and the software functions are separated. Network softwarization – through
network functional virtualization (NFV), software defined networking (SDN), network
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slicing and Cloud-RAN (C-RAN) – aims to increase both the pace of innovation and the pace
at which mobile networks can be transformed.
• NFV – replaces network functions on dedicated appliances – such as routers, load
balancers, and firewalls, with virtualized instances running on commercial off-the-shelf
hardware, reducing the cost of network changes and upgrades.
• SDN – allows the dynamic reconfiguration of network elements in real-time, enabling
5G networks to be controlled by software rather than hardware, improving network
resilience, performance and quality of service.
• Network slicing – permits a physical network to be separated into multiple virtual
networks (logical segments) that can support different RANs or several types of
services for certain customer segments, greatly reducing network construction costs by
using communication channels more efficiently.
• C-RAN – is presented as a key disruptive technology, vital to the realization of 5G
networks. It is a cloud-based radio network architecture that uses virtualization
techniques combined with centralized processing units, replacing the distributed signal
processing units at mobile base stations and reducing the cost of deploying dense
mobile networks based on small cells.
B. Network slicing - 5G Services Architecture
The network slicing is emerging as a future-proof framework for
accommodating to the technological and business needs of different industries
and respective services. 5G network slicing enables logical isolation of
programmable infrastructure resources (i.e., physical and/or logical resources) to
configure functions and services.
The network slicing will require the upgrade of existing 4G network to cloud
based infrastructure based on SDN & NFV. For achieving the service
orchestration in cloud based network ETSI, has been developing MANO
architecture which is detailed in next section.
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! A
A network slice can provide the functionality of a complete network, including radio access
network functions and core network functions (e.g., potentially from different vendors). One
network can support one or several network slices. Same is explained in picture above where
the network is divided into three slices of Enterprise , OTT and MVNO and providing QoS
for each service seperatly on same network.
C. RAN Architecture Changes
The 5G RAN architecture has several changes due to the KPIs required from RAN, i.e
higher throughput, lower latency, lower energy consumption, high device density and
ubiquitous coverage.
Small Cell
The deployment of small cells is one way of boosting the capacity and quality of existing 4G
networks while laying the foundation for commercial 5G networks and early eMBB services.
Small cells are already being used by some wireless operators to boost the capacity and
coverage of their existing 4G networks particularly in a dense urban setting
Massive MIMO & Beam forming
Massive MIMO provides independent narrow beams targeted at multiple users and transmits
data through a user-spe- cific space isolation system. This helps increase system throughput by
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dozens of times. Leading operators around the globe have already begun deploying
commercial Massive MIMO.
It support of beamforming, essential for efficient power transmission. Massive MIMO
increases spectral efficiency and in conjunction with dense small cell deployment, will help
operators to meet the challenging capacity requirement of 5G.
Fronthaul
In current 4G wireless network, the fronthaul link exists between radio frequency (RF) func-
tion and the remaining layer 1, 2 and 3 (L1/L2/L3) functions. Recommendation ITU-T Y.
3100 defines fronthaul as “a network path between centralized radio controllers and remote
radio units (RRU) of a base station function”. This architecture allows for most
stringent fronthaul latency and bandwidth requirements.
The increase in data rates in 5G makes it impractical to continue with the conventional
Common Public Radio Interface (CPRI) fronthaul implementation. Thus following
technologies are getting popular as frontal options 1) XGSPON 2) CWDM 3)25 GE/50GE
ethernet 4) OTN transport.
The concept of “Anyhaul” is also progressing which talks about 5G Antenna active antenna
unit (AAU) getting connected to 5G DU on Fronthal and DU to CloudRAN on Midhaul.
The conventional Backahul will be used to connect the CloudRAN to MEC and Core Cloud.
D. Mobile edge computing
In-network content caching provided by the operator, a 3rd party or both, can improve user
experience, reduce backhaul resource usage and utilize radio resource efficiently.
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The operation of in-network caching includes flexible management of the location of the
content cache within the network and efficient delivery of content to and from the
appropriate content caching application.
Fox example : CCTV camera live feed is monitored and processed at the MEC server near
the LTE Base Station. Only video clips, meta data, triggers etc. which are low bandwidth are
sent to the core network. This improves the response time and reduces the load on the
backhaul.One application could be to public safety, Smart cities etc.
MEC benefits can be summed up but not limited to :
1) (Ultra-)low latency: disruptive improvement of customer experience,
2) Reduction of backhaul/core network traffic: cloud services (e.g., big data) near to user &
3) In-network data processing
5. New Horizons - AI/ML Lead Operations
In the 5G era and on the journey towards 5G, there is a need for a true and unified network
management offering that can manage complex hybrid networks including 5G, all physical
and virtual network elements, as well as VNF lifecycle management. To understand the
requirements better, here are five key essentials required to win in 5G network management.
AI is making the leap from use cases that mimic human behaviors to large complex systems
that leverage human capabilities. Within the field of AI, there has been rapid progress in
machine intelligence, a discipline which augments the structuring and modeling of machine
learning with reasoning and planning techniques.
• Managing the increasing complexity of networks
• Machine learning plus reasoning and planning is machine intelligence
• Enabling machine intelligence through structured knowledge
The operators are focusing on real time operations with respect to operation support system
OSS migration for 5G. The basic
• Distributed real-time orchestration of diverse complex services across all network
domains, including vCore and intelligent edge (e.g. MEC)
• End-to-end management of hybrid virtual and physical cross-generation access,
aggregation, and core infrastructure
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• Real-time QoS management with closed-loop and analytics-driven service
assurance tools
• Dedicated M2M/ IoT Platform for vendor- agnostic device and data management
A. Zero Touch Services Orchestration
Zero touch network and Service Management is conceived as a next-generation management
system that leverages the principles of Network Functions Virtualization (NFV) and Software
Defined Networking (SDN). It will be designed for the new, cloud-based network
infrastructures and functions, and based on cloud-native principles to address zero-
touch (fully automated) management and operation.
Open network automation platform ONAP is a linux foundation initiative which is working
on a NFV, SDN automation architecture using open standards and taken a lead by combining
operators and vendors ecosystem. They have ready to deploy VNFs to create and manage the
underlying vEPC and vIMS services by interworking with vendor-specific components,
including VNFMs, EMSs, VIMs and SDN controllers, across Edge Data Centers and a Core
Date Center.
5G Network is programmable, software-driven, service-based and holistically-managed
infrastructures, utilising enablers and catalysts, such as NFV, SDN and Edge Computing.
Metro ethernet forum (MEF) has defined the standard for zero touch orchestration and
customer journey for the services such as IoT, MVNO etc. Several other standard are also
coming into such as ZOOM from TM forum.
The MEF has defined its zero touch requirement in the life cycle service Orchestration (LSO)
specifications, following journeys are covered with architecture references in LSO :
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1- Agile methodology for service provision life cycle
2- Order fulfilment and Services Control
3- Security Management
4- Analytics Managment
5- Billing & usages management
5- Standards APIs for customer, service provider and partner domains.
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Oracle, Juniper and Infovista has demonstrated LSO based architecture for vCPE
deployment over SDN based infrastructure. Similarly other services can be used and tightly
coupled into ETSI MANO architecture
ETSI MANO
Open Source Mano is an ETSI-hosted initiative to develop an Open Source NFV
Management and Orchestration (MANO) software stack aligned with ETSI NFV.
The MANO architecture provides VNF definition, use case and network slicing orchestration
architecture. MANO also details about virtual network function VNF management. “VNF”
refers to the implementation of a network function using a virtual machine that lies on top of
the underlying hardware.Effective lifecycle management of these VNFs is essential for
comprehensive network management of a complex hybrid network that may include 4G,
Enterprise MEN & 5G.
MANO Functional Blocks
• NFV Orchestrator:
• on-boarding of new Network Service (NS), VNF-FG and VNF Packages
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• NS lifecycle management (including instantiation, scale-out/in, performance
measurements, event correlation, termination)
• global resource management, validation and authorization of NFVI resource requests
• policy management for NS instances
• VNF Manager:
• lifecycle management of VNF instances
• overall coordination and adaptation role for configuration and event reporting between
NFVI and the E/NMS
• Virtualised Infrastructure Manager (VIM):
• controlling and managing the NFVI compute, storage and network resources, within
one operator’s infrastructure sub-domain
• collection and forwarding of performance measurements and events
B. Cognitive Network Operations
The Cognitive NOC has three main focus are according the challenges the operators are
facing now
• Real-time in measuring, detecting and resolving problems;
• Proactive, predictive and prescriptive;
• Automated in service provisioning and fulfillment;
• Agile and adaptive to frequent configuration changes; and
• Distributed in implementation to effectively realize the "recover first before trouble-
shooting" approach
The current challenges for a NOC solution are following
• No single-pane-of-glass view or correlation across subsystems, leading to a lack of
network-wide context
• An excessive number of events, noise, and duplication, leading to too many non-
actionable trouble tickets
• A lack of support for collaboration, leading to domain-specific teams troubleshooting
in silos
• Reactive workflow – too much time spent on customer-reported faults, leaving insuf-
ficient time for proactively preventing faults
The only way that these difficult goals can be achieved is Future OSS with vastly increased
automation in management and operation of 5G network
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Machine learning is the process by which a computer-driven machine can learn pattern
recognition, make predictions, and provide actionable insights through sophisticated
algorithms.
It offers the opportunity to increase the level of automation in network management even
further. The data already available in the network can be turned into insights on how to
prioritize and fix network faults as quickly as possible. And this allow for significantly reduced
investments in designing and maintaining automation solutions.
The prototype NOC software enables automatic fault management by applying machine
intelligence techniques.
This enables it to:
– Map composite conditions from historical information (performing intelligent grouping of
cross-domain alarms for detection using pattern mining techniques)
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– Form rules from the composite conditions using machine learning
– Detect incidents based on the rules – Identify root causes, and derive
appropriate actions by mapping root causes to resolution procedures from system or solution
documentation
C. Closed Loop Automation
A cornerstone in developing automated decision-making is knowledge collection and the
subsequent organization of the knowledge into a graph of interlinked domains.
Automation in activities such as generating actionable insights, network configuration, and
ensuring network quality will be critical to ensure improved network performance and
operational efficiency.
Operators must prepare for the increased size and complexity of the network in the 5G and
IoT era. The amount of opex spent on incident management in a network operations center
(NOC) today will increase exponentially unless much higher efficiency is attained. Each NOC
engineer will soon have to manage more than 10 times more complexity than today, and this
challenge must be addressed with automation.
Fault conditions and alarm grouping is made possible by
• Embedding network information, such as alarms and events, into a telco knowledge
graph which includes raw as well as insightful, derived information that forms the basis
for enabling automated intelligent behaviors at the NOC
• Automatically capturing the behaviors in the network data – alarms and events – in a
data-driven manner into digitalized versions which we will refer to as machine learning
(ML) generated rules.
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6. Conclusion
As operators plan for the deployment of new technologies such as 5G and NFV, the key
criteria they are looking for from their service assurance solutions include:
• Cross-domain (access edge, core, etc.) analysis with an end-to-end visualization of
services across a hybrid of physical and virtualized network functions
• Complete, real-time inventory/topology covering all functional elements
• Combining bottom-up and top-down real-time inputs – infrastructure-level
information such as SNMP traps can help determine the cause of a fault, while
application-level information (gleaned from active monitoring) can help determine
service health
• Automated mapping of customer-reported issues to underlying infrastructure issues
• Automated mapping of network events to their service impacts and prioritization of
alarms according to customer impact level
• Automated triggering of proactive, corrective actions (e.g., issuing requests to an
orchestrator to resolve a performance degradation before it impacts the customer
experience)
Machine learning presents an interesting new toolset for service assurance. By automating the
collection and analysis of monitoring telemetry (events, alerts, Syslog, SNMP traps, etc.), and
using the power of machine learning, operators may be able to uncover new insights about
their networks that enable them to reduce their cost of operations and improve the customer
experience.
The service assurance solution must also be closely integrated with fulfillment/ orchestration
systems to deliver the "holy grail" of closed-loop automation.
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