Categories: Telecom

How Network Data Analytics Function (NWDAF) is Impacting the Telco Industry?

With the growing complexity in the telecom industry, the operators are looking for ways to best utilize the technology and data for effective monetization. Hence comes data analytics into the picture and it has now become a crucial element that is accompanied by both challenges and opportunities.

The current scenario is that less than 2% of data generated have been stored and from that only, 10% have been analyzed and applied. This implies that 98% of the data is not being analysed. When we talk about productivity and innovation gains, it’s a huge loss for organizations.

Data is the key element of the digital economy

Communication Service Providers need to understand better the type of data they own and what value it possesses. This becomes even more crucial in the current scenario where telco-specific standards are still mellowing. One of such standards is NWDAF which is a 3rd Generation Partnership Project (3GPP) – based analytics function.

NWDAF stands for Network Data Analytics Function that focuses on the 5G core (5GC). It is designed to help the operators in gaining clarity in terms of the business value they attain from the data and its analyses.

Existing Telecom Industry Scenario

With growing cloudification and disaggregation, there’s an increase in the complexities and operational challenges too. The point to be considered is that the hardware and software components in 5G networks are located on different networks. Now for Virtual RAN environments where CSPs are experiencing a huge increase in the number of Data Centers from 100 to 1000s, there is a need to align network functions with the distributed nature of the ecosystem.

The solution for this is to place data, analytics and AI at the heart of the innovation model of CSPs. Thus, it is beneficial for the operators to invest in big data and analytics solutions.

What are the current Telecom industry priorities?

Now the primary goal of the telecom operators is to become a data-driven and AI-powered companies to enhance revenue growth, efficiency, competitiveness and service quality. Hence comes the concept of change management which is critical for the modern-day telco industry. Moreover, 5G has arrived and it is placing new requirements on network efficiency and reliability. It is expected that there will be more than 10 times an increase in CDRS (Call Data Records) when the networks will shift from 4G to 5G. This is a pain point for Big Data and Analytics, as it is now required to meet the changed SLA performance, orchestration and analytics needs of the complex network ecosystem.

Hence come the 5G Data Analytics standards and NWDAF into the picture.

NWDAF is a standards-based analytics function which is set by 3GPP as an active part of 5G Service Based Architecture (SBA). It is meant to offer wide and in-depth standards for analytics to dig into actionable insights. It provides the following features:

  • Real-time data
  • Operational intelligence to Network Functions (NFs) in 5GC
  • Unified data management
  • Policy control function
  • Service orchestration
  • Network automation

NWDAF utilizes KPIs such as user statistics, load, control, and more and generates predictions to NFs and other systems.

Operational intelligence offered by NWDAF can be observed via three scenarios.

  1. Network Operational Intelligence: Includes network fault prediction, automatic network management, tracking network load and service assurance.
  2. Service Experience: The data derived from NWDAF support constantly changing service requirements and thus enhances service experience. It depicts metrics of user and application.
  3. User Device Connectivity Behaviour: NWDAF even offers real-time operational intelligence by allowing tracking device mobility and communication patterns. Even abnormal usage can be easily detected with this function.

3GPP Network (NWDAF) Roadmap

When we talk about network standards, then NWDAF is just one of them and there are various others like Near-RT RIC, Non-RT-RIC, etc. The level of adoption of different standards is different, but regardless of the standard that

predominates, the TSP should define an information data model. In easier words, the companies should design a data model that allows a detailed and accurate description of business procedures, internal topology and life cycles of a variety of segments of the core network and the RAN.

Basically, the idea of all the network standards is to get the work done and with a common standard, it’s easier to do it. A common data standard eliminates the need for data normalization and also helps in developing operational models for automation and orchestration. With NFs, TSPs are relishing a very positive outcome and a comfortable working environment.  

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Pallavi Yadav

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