Networks
that learn
and improve
Ericsson’s cloud native Network Data Analytics
Function solution is 3GPP-standardized andenables custom analytics use cases to keep costs
low, service quality high and operations smooth.

Ericsson | Networks that learn and improve2

Data-driven
5G networks
5G is changing the way people and things communicate.

Compared with previous core network
standards, cloud native 5G Core adds
complexity, and 5G devices produce asignificantly increased amount of data
for the core network to manage.
As new network capabilities emerge tohandle the increase in complexity, automateddata-driven solutions will become instrumental
in controlling network operational costs. Serviceproviders cannot afford to rely on humaninterventions and inflated staff levels innetwork operations.
There are high expectations on the5G Core network to use the benefits ofartificial intelligence (AI) and automation
for network optimization to deliver superior
network experiences.
This is where Ericsson’s Network Data
Analytics Function (NWDAF), the new 3GPP
standard for analytics in the 5G Core, comes
into play. Ericsson has been active in 3GPP since
its inception and has helped shape NWDAF as
standard, ensuring it promotes a multi-vendor
approach to avoid vendor lock-in. NWDAF
addresses three primary standardization points:• Data collection interface from network nodes• Predefined analytics insights• Data exposure interface for consumers

Why NWDAF?
NWDAF is designed to overcome market
fragmentation and proprietary solutions in
the area of network analytics, streamlining
the way core network data is produced andconsumed, as well as generating insights
and taking actions based on these insights.

Figure 1: New tech and higher complexity requires
automated data-driven networks.

User diversity

Expectations

Device diversity

Businessopportunities

Services

Capabilities

Complexity

Ericsson | Networks that learn and improve3

The benefits of AI to build
data-driven networks
The new analytics standard allows for multiple
implementations or deployments of NWDAF andthis is at the heart of Ericsson’s value proposition.

Ericsson’s NWDAF solution enables several total
cost of ownership reduction drivers that resultin capex and opex savings of up to 45 percent
compared to other third-party solutions:•	
Smart data acquisition. Data movement
is minimized between access/aggregation
cloud to standalone locations.
•	
Efficient integration and testing.
Co-located/pre-tested NWDAF delivery andinterworking between different generations(2G/3G/4G/5G) out of the box.
•	Simpler orchestration. Co-located NWDAF
is part of the cloud native network
function (CNF) and can be deployed
The road to NWDAF is facilitated by Ericsson’sin the same orchestration flow.
well-established dual-mode 5G Core products:
Optimized footprint. Both co-locatedPacket Core Controller, Packet Core Gateway, •	
NWDAF and standalone NWDAF
Cloud Core Resource Controller, Cloud Core(see “Ericsson’s NWDAF solution”)
Policy Controller, and others, which allowbuild on existing products, reusing
the introduction of NWDAF through acommon services.
software upgrade.
Service providers evaluate three overarchingquestions when embarking on theirNWDAF journey:
1. The road to NWDAF. How do I evolvefrom existing analytics solutions in thecore network?
2. Using NWDAF. What is the total
cost of ownership for a new NWDAF 		
solution, compared to different solutions
on the market?
3. Beyond NWDAF. What can I expect to get
on top of the standardized interfaces?

Ericsson’s extensive experience in theanalytics field enables the building of new
analytics use cases, supporting multi-vendor
proprietary data sources and multi-domain
event correlation. Ericsson’s NWDAF solution
supports flexible cloud deployment options on
the Ericsson and 3P infrastructure, including
hyperscale cloud provider deployments(both private cloud and public cloud).

Figure 2: Ericsson’s NWDAF value proposition

EvolveOptimize

ExpandEvolution from anexisting solution toNWDAF standard

Optimized NWDAF
implementation tolower TCO

Expanded set of use cases
covering 5G and legacy
beyond NWDAF

A smooth journey to 3GPP
standard through well-established
Ericsson cloud native products.

Lower TCO through smart dataacquisition, efficient integration,
optimized footprint and simpler
lifecycle management
and orchestration.

Ericsson’s NWDAF enables
automated closed loops andassurance based on 3GPP andcustom use cases.

Ericsson | Networks that learn and improve

4

Ericsson’s
NWDAF solution
Building on Ericsson’s dual-mode 5G Core and Expert Analytics
solutions, we provide two types of NWDAF deployment.

Ericsson’s NWDAF solution covers a wide setof use cases in various areas, including mobility
and behavior tracking and prediction, as well
as different Quality of Service (QoS) scenarios.
To cover these and other cases, Ericsson’s
NWDAF solution can be deployed in a rangeof ways. For example, as a co-located NWDAF,
as standalone NWDAF or as a combinationof the two.

Co-located NWDAF
Data, insights and actions are generated
within network functions (NFs), enabling
automated closed loops on the local level.
Insights can also be exposed externally.

Standalone NWDAF
Data is generated within NFs, before insights
are generated from larger and combined data
sets coming from multiple network functions
and multiple domains. Actions are thentriggered by these insights. This will allow
for automated closed loops on the network
level combining different NFs.

Figure 3: Ericsson’s NWDAF solution overview
Insight exposure to any NF/AF and NWDAF

NWDAF

NWDAF
Pre-processed
insight exposureCore internal
insight exposure

Dual-mode 5G Core products

Co-located deployment of NWDAF

Event exposure

3P NF andNWDAF

Expert Analytics

Standalone deployment of NWDAF

Ericsson supports scenarios with both
NWDAF deployment models and model
portability across the common platform.

Ericsson | Networks that learn and improve

5The evolving ecosystem
of NWDAF use cases
Ericsson works closely with service providers to develop
new analytics use cases and has already produced
multiple solutions.
Mobility tracking/prediction
ML-assisted paging:•	Predicting individual or groups of UE
movement, optimizing paging schemes
to avoid congestion in cells by adjusting
QoS parameters.
•	Adjusting resource allocation to thenetwork as needed.
Behavior tracking/prediction
UE behavior handling:•	Finding abnormal patterns in UE or traffic
behavior and adjusting accordingly.
Predictive congestion management:•	Influencing the NF Discovery Servicewith past congestion patterns toselect proper NF.

Quality of service tracking/prediction
Enterprise service level agreement (SLA)
assurance:•	Ensuring SLA is guaranteed withincertain regions.
•	Calculating/monitoring service quality
for every user.
User plane function (UPF) selectionand reselection:•	Providing session management function
support to select a UPF node to serve theprotocol data unit session.
•	Based on user location, data network
name, UPF node priority and UPF node
weight, latency reductions, reduced trafficrouting and opex savings achieved by
reducing the number of UPFs the RAN
needs to connect to.

Adaptative policies:•	Adapting actions based on the input fromnetwork, past policies and the next policy
to execute.
Optimizing best data plan:•	Adapting the data plan parameters to meetthe current needs of the subscriber, taking
into account the historical data.
Slice selection based on load:•	Selection of what slice the UE shouldcamp on based on the load.

SummaryNetworks that have the ability to learn and improve will soon be the industry standard. Service providers that start their journey towards
automated analytics sooner rather than later can position themselves as market leaders by offering reduced latency, increased bandwidthand a superior customer experience. By partnering with Ericsson rather than third-parties, service providers are just one configuration
update away from 3GPP standardization. They also stand to benefit from lower TCO and new analytics use cases.

Ericsson is a world leader in communications
technology and services with headquartersin Stockholm, Sweden. Our organizationconsists of more than 111,000 experts who
provide customers in 180 countries with
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we are building a more connected future
where anyone and any industry is empowered
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