Sensing Service Analytics Interfaces for 5G Data Collection
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Solution Overview
Problem
Existing DCCF and NWDAF frameworks in 5G networks do not provide standardized interfaces for handling sensing-related analytics, failing to efficiently collect, process, and deliver sensing data, which is crucial for advanced applications such as object detection, tracking, and environment monitoring.
Innovation Solution
Introduce a framework that includes sensing service management functions (SSMF) interfacing with RAN and AMF, leveraging the DCCF/NWDAF to define sensing-related analytics IDs and data filters, enabling efficient data collection, processing, and delivery through enhanced interfaces like NS2, NS4, NS5, and NS6, and utilizing AI/ML for advanced post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing DCCF and NWDAF frameworks are used without sensing-specific extensions, then network infrastructure is leveraged, but standardized interfaces for sensing analytics are missing and data processing efficiency is insufficient
Solution Approach 1:
The patent extends existing DCCF and NWDAF frameworks to serve dual purposes: traditional network data analytics and sensing-related analytics. By making the framework universal, it can handle both communication data and sensing data through standardized interfaces, eliminating the need for separate specialized systems while maintaining sensing-specific capabilities.
Solution Approach 2:
The patent introduces sensing-specific analytics identifiers (Analytics ID) and data filters as separate, modular components within the existing framework. This segmentation allows sensing analytics to be processed independently through dedicated interfaces (NS2, NS4, NS5, NS6, NS7) while maintaining compatibility with the overall network analytics architecture.
2Productivity
If sensing data is collected and processed through existing interfaces, then infrastructure is utilized, but data collection and delivery efficiency is insufficient
Solution Approach 1:
The patent pre-configures sensing-related analytics identifiers and data filters before data collection begins. By establishing the processing framework in advance with predefined interfaces and parameters, the system can immediately process sensing data without delays for configuration or setup, thereby improving processing efficiency and reducing delivery time.
Solution Approach 2:
The patent implements feedback mechanisms through the enhanced interfaces that allow continuous monitoring and adjustment of data collection and processing operations. This feedback loop enables real-time optimization of data handling processes, ensuring efficient utilization of infrastructure and rapid data delivery.
3Reliability
If standardized interfaces are introduced for sensing analytics, then data handling capability is improved, but interface complexity increases
Solution Approach 1:
The patent modifies existing interface parameters and adds sensing-specific parameters to the standardized interfaces. By changing and extending parameters rather than creating entirely new interfaces, the system maintains compatibility with existing infrastructure while adding necessary sensing capabilities, thus improving reliability without proportionally increasing complexity.
Solution Approach 2:
The patent introduces sensing-related analytics identifiers and data filters as intermediary elements that mediate between the sensing data source and the processing infrastructure. These intermediaries simplify the interface by providing standardized abstraction layers, making the complex sensing data handling process more manageable and reliable.
Data Source
AI summary
The present disclosure is related to integrated sensing and communication services, and in particular, to data analytics for integrated sensing and communication services in 3GPP networks. Various input and output parameters related to sensing service analytics are provided by defining the sensing data at different processing stages of various sensing devices. Additionally, a service producer receives, from a service consumer, an analytics identifier (ID) that corresponds to a sensing service and a set of input parameters related to the sensing service. The service producer obtains analytics information based on the analytics ID and the set of input parameters. The service producer sends a second message including the analytics information to the service consumer. Other embodiments may be described and/or claimed.