NWDAF Integration

As 5G Standalone (SA) networks introduce network slicing, ultra-low-latency applications, and massive IoT connectivity, real-time analytics becomes essential for network optimization, cost reduction, and revenue growth. Traditional NWDAF implementations, often tied to rigid architectures and high operational costs, limit CSPs’ ability to fully leverage predictive network analytics and AI-driven automation.

DigitalRoute enables NWDAF integration with a modular and cost-efficient framework, where its telco data mediation solution provides the Data Collection Coordination Function (DCCF) and Messaging Framework Adaptor Function (MFAF). These capabilities ensure seamless data collection, transformation, and distribution across multiple sources, supporting integration with various AI/ML analytics platforms and vertical-specific applications. AI/ML processing and predictive analytics are handled by an AI/ML partner or the CSP’s existing AI/ML infrastructure, ensuring flexibility and vendor independence.

Addressing key challenges in NWDAF Implementation 

As telecom operators deploy 5G Standalone (SA) networks, they face several challenges in implementing NWDAF (Network Data Analytics Function) effectively.

Key challenges include:

• High Total Cost of Ownership (TCO): Traditional NWDAF solutions require significant investment in infrastructure, AI/ML models, and data storage, increasing operational costs. 
• Data Redundancy & Inefficient Processing: Duplicate data collection and lack of centralized data mediation result in excessive storage costs and slower real-time analytics. 
• Limited Interoperability: Standard 3GPP-defined NWDAF implementations do not easily extend to private 5G, MEC (Multi-access Edge Computing), and enterprise IoT applications, limiting cross-industry analytics potential. 
• Slow AI/ML Adoption: CSPs struggle to integrate AI/ML frameworks due to fragmented data sources and inconsistent data quality, delaying predictive analytics capabilities. 
• Vendor Lock-in: Monolithic NWDAF deployments prevent CSPs from leveraging existing analytics infrastructure, forcing reliance on proprietary vendor solutions. 
• Challenges in Monetizing Network Insights: QoS-based charging models are difficult to implement without real-time network analytics and automated revenue assurance mechanisms. 

Without a modular and adaptable NWDAF framework, CSPs risk higher operational costs, slower innovation, and limited monetization opportunities from data-driven network automation.

DigitalRoute’s NWDAF integration solves these challenges by enabling real-time data collection, transformation, and analytics readiness, ensuring cost-efficient and scalable 5G intelligence. 

How DigitalRoute’s Modular NWDAF Integration Solves These Challenges

DigitalRoute’s modular NWDAF integration framework enables CSPs to overcome these limitations by providing: 

• Cost-Efficient, AI/ML-Ready Deployments: Reduces TCO by leveraging existing data infrastructure and eliminating redundant analytics processes. 
• Centralized Data Mediation: Eliminates data duplication through Data Collection Coordination Function (DCCF) and Messaging Framework Adapter Function (MFAF), optimizing analytics processing. 
• Flexible AI/ML Integration: Ensures structured, high-quality data delivery to support predictive and prescriptive analytics across network operations. 
• Cross-Network & Cross-Vertical Analytics: Supports both 3GPP and non-3GPP analytics, enabling enterprise monetization in smart cities, healthcare, manufacturing, and IoT ecosystems. 
• Vendor Independence & Seamless Interoperability: Allows CSPs to avoid vendor lock-in, ensuring integration with third-party AI/ML platforms and existing analytics systems. 
• QoS-Based Monetization & Revenue Assurance: Provides real-time network insights, enabling premium service pricing, SLA compliance, and Analytics-as-a-Service offerings. 

With DigitalRoute’s DCCF (Data Collection Coordination Function) and MFAF (Messaging Framework Adapter Function), CSPs gain a cost-efficient, scalable, and AI-driven analytics framework, ensuring real-time network intelligence, operational agility, and long-term profitability. 

Who Benefits from DigitalRoute´s NWDAF Integration? 

• Network Operations Teams: Gain enhanced visibility and real-time control over 5G network performance, supporting proactive service adjustments. 
• Data Science and Analytics Teams: Can work with clean, organized data from multiple sources, enabling faster model training and deployment for diverse analytics use cases.
• Finance and Business Operations: Benefit from reduced operational and capital expenses by leveraging existing infrastructure and avoiding vendor lock-in.
• Enterprise Clients and Vertical-Specific Teams: Gain insights into network data tailored to specific sectors, such as healthcare, manufacturing, or IoT, supporting targeted service delivery and new monetization opportunities. 

 

The Growing Importance of NWDAF in 5G SA Networks

With the deployment of 5G Standalone (SA) networks, NWDAF has become a strategic necessity for CSPs. Real-time network insights enable predictive maintenance, proactive network management, and improved customer experiences. 5G SA demands sophisticated capabilities such as network slicing, IoT connectivity, and ultra-low-latency services—all of which require dynamic, data-driven network optimization. NWDAF, integrated with AI/ML frameworks, ensures that CSPs can apply predictive and prescriptive analytics, effectively allocating resources and anticipating network challenges before they impact performance.

DigitalRoute’s Modular Approach: The Future of NWDAF 

DigitalRoute’s modular NWDAF solution is designed to support CSPs in navigating industry shifts and unlocking new opportunities. By providing DCCF and MFAF functions, DigitalRoute enables CSPs to integrate with their existing AI/ML frameworks, analytics platforms, and data repositories. This flexible architecture reduces TCO, accelerates time to market, and fosters innovation without vendor constraints. 
Moreover, DigitalRoute’s modular approach expands NWDAF capabilities beyond traditional network analytics, enabling CSPs to support vertical-specific analytics for industries such as healthcare, manufacturing, and finance. By eliminating data silos, CSPs can repurpose data for multiple applications, maximizing insights across 3GPP and non-3GPP use cases. This adaptability allows CSPs to tap into new revenue opportunities, such as offering Analytics as a Service, while maintaining a competitive edge in the evolving telecom ecosystem.