Network Slicing with Multiple Slice Instance Variations
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Solution Overview
Problem
Next Generation mobile networks, such as 5G NR, face challenges in dynamically adapting to varying service requirements and performance characteristics across different data sessions, necessitating a more granular level of service differentiation within network slices.
Innovation Solution
The implementation of network slicing with sub-slicing into multiple slice instance variations, each with specific slice variation types and levels, allowing for dynamic allocation of resources and customization to meet diverse service needs, is facilitated by a Slice Manager and Orchestrator that creates and manages Network Slice Instances (NSIs) with unique identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network slicing is implemented with multiple slice instance variations, then service differentiation and resource allocation are enhanced, but device complexity and management overhead increase
Solution Approach 1:
The patent segments a network slice into multiple slice instance variations, each tailored to specific service requirements. This segmentation allows the network to provide differentiated services (e.g., enhanced mobile broadband, ultra-reliable low-latency communications) by creating specialized instances with customized resource allocations, performance parameters, and service level agreements, thereby enhancing service differentiation while managing complexity through structured division.
Solution Approach 2:
The patent implements dynamic management of slice instance variations through a network slice manager that can create, modify, and terminate slice instances based on real-time service demands. This dynamic capability allows the system to adapt to varying traffic patterns and service requirements by provisioning appropriate slice instances on-demand, enhancing versatility while using automation to manage the complexity of multiple slice variations.
2Productivity
If granular service differentiation is implemented across network slices, then spectral efficiency and capacity are improved, but system complexity increases
Solution Approach 1:
The patent applies local quality by assigning different performance characteristics and resource allocations to specific slice instance variations based on their intended service purposes. Each slice instance can be optimized locally for its specific function (e.g., high bandwidth for eMBB, low latency for URLLC), thereby improving overall spectral efficiency and network capacity while maintaining manageable complexity through targeted optimization rather than uniform design.
Solution Approach 2:
The patent utilizes parameter changes by allowing different slice instance variations to have customized performance parameters such as bandwidth, latency, reliability, and mobility support. The network slice manager can dynamically adjust these parameters based on service requirements and network conditions, improving spectral efficiency and capacity by optimizing each slice instance for its specific use case while using automated parameter management to control system complexity.
3Quantity of substance
If multiple slice instance variations are supported, then support for higher density of wireless users is enabled, but ease of operation decreases
Solution Approach 1:
The patent implements universality by creating a common network slice framework that can accommodate multiple slice instance variations serving different service types and user requirements. This universal framework provides standardized management interfaces and orchestration capabilities that simplify operations despite the diversity of slice instances, enabling support for high user density across various service scenarios while maintaining ease of operation through unified management procedures.
Solution Approach 2:
The patent applies self-service by enabling automated slice instance provisioning and management through the network slice manager, which can autonomously create, configure, and manage slice instances based on service requests and network conditions. This automation reduces manual operational complexity while supporting high user density by allowing the system to self-manage multiple slice variations without proportionally increasing operational burden.
Data Source
AI summary
One or more network devices create, in a network, a network slice with multiple network slice instances (NSIs) having multiple slice instance variations, where each of the multiple slice instance variations services a slice variation type and one of multiple slice variation levels. The slice variation type corresponds to a first performance characteristic of one or more performance characteristics met by the network slice while servicing sessions and the multiple slice variation levels sub-divide the slice variation type into multiple different levels of service within the slice variation type. The one or more network devices allocate, instantiate, and provision virtual resources for each of the multiple NSIs; and services User Equipment (UE) sessions via one of the multiple slice instance variations based on UE selection of one of the multiple slice variation levels of the slice variation type.