Programmable Radio Exposure Function for Open RAN Resource Allocation
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Solution Overview
Problem
Next-generation telecommunications networks, such as 6G, face challenges in securely exposing services and capabilities while addressing the varying communication needs of different types of connected devices, due to lack of universally accepted standards and proprietary implementations.
Innovation Solution
The implementation of a programmable radio exposure function that operates as a network abstraction layer, decentralizing radio access network functions, creating multiple virtual networks, automating radio resource management, and using machine learning to identify network slices and detect security violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If next-generation networks connect a larger volume of devices, then network capability and service coverage are improved, but network congestion and security challenges worsen
Solution Approach 1:
The patent segments the network into multiple network slices, each dedicated to specific services or device types. This segmentation allows different security policies and resource allocation strategies to be applied to each slice, improving overall network security while maintaining the ability to connect diverse devices. The network exposure function further segments service exposure by providing different API interfaces for different device categories.
Solution Approach 2:
The patent introduces a network exposure function as an intermediary layer between the core network and external devices/services. This intermediary securely manages service exposure, device authentication, and resource allocation, thereby enhancing security without limiting network capability. It acts as a mediator that handles security challenges while enabling diverse device connections.
2Adaptability or versatility
If next-generation networks support more devices simultaneously, then network coverage and service capacity are improved, but network congestion and performance degradation worsen
Solution Approach 1:
The patent divides the network into multiple slices, each optimized for specific service types or device categories. This segmentation prevents congestion in one slice from affecting others, maintaining network performance even as service capacity increases. Each slice can be independently managed and scaled to meet specific demand patterns.
Solution Approach 2:
The patent implements dynamic resource allocation where network resources are automatically adjusted based on real-time demand, device type, and service requirements. The network exposure function dynamically manages resource allocation across different device categories, ensuring optimal performance while supporting high service capacity.
3Adaptability or versatility
If proprietary implementations are used for network functions, then specific service requirements are met, but lack of universal standards and interoperability worsens
Solution Approach 1:
The patent implements a universal network exposure function that provides standardized interfaces and capabilities for diverse devices and services. This universal function supports multiple service types and device categories through a common framework, enabling interoperability while maintaining the ability to customize services through configuration rather than proprietary implementations.
Solution Approach 2:
The patent employs dynamic, configurable network functions that can adapt to different service requirements through software configuration rather than proprietary hardware implementations. The network exposure function dynamically adjusts its behavior based on device type, service category, and network conditions, providing universal interoperability with service-specific customization capabilities.
Data Source
AI summary
Methods for resource and slice allocation for multi-mode operation in Open RAN architectures are described. A programmable radio exposure function switches between real-time and near-real-time modes of operation for a radio access network (RAN) intelligent controller of a telecommunications system. An application programming interface is exposed by the radio exposure function and performs radio resource management for the telecommunications system. The application programming interface communicates with services and/or applications to control RAN functions, and allocates RAN resources of the telecommunications system to a user equipment for the services and/or applications. A machine learning module is embedded within the radio exposure function and trained to identify network slices of the telecommunications system for the services and/or applications.