Non-binding Analytics for Wireless Link Resource Allocation
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Solution Overview
Problem
Current wireless communication systems face challenges in optimizing resource allocation and scheduling for user equipment (UE) communications due to limited information about UE behavior and communication patterns, leading to inefficiencies in spectral usage and increased overhead.
Innovation Solution
The implementation of non-binding analytics-based information, which includes recommendations for wireless link configurations, such as expected payload, communication intervals, and prioritization, is received by network nodes from user equipment via an application server and applied to radio resource management (RRM) configurations, enabling more efficient resource allocation and scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional wireless resource allocation is used, then system simplicity is maintained, but spectral efficiency is limited due to insufficient information about UE behavior and communication patterns
Solution Approach 1:
The system performs preliminary analytics processing of UE behavior patterns and communication characteristics before resource allocation decisions are made. The network node collects and analyzes historical communication data, UE mobility patterns, and application requirements in advance, generating predictive models that inform subsequent resource allocation and scheduling decisions, thereby improving spectral efficiency without adding real-time complexity
Solution Approach 2:
An analytics-based information layer is introduced as an intermediary between raw UE communication data and resource allocation decisions. This intermediary layer processes and transforms raw data into actionable insights about UE behavior patterns, communication priorities, and spectral usage optimization opportunities, enabling more informed resource allocation without directly modifying the core scheduling mechanisms
2Manufacturing precision
If detailed link information is collected and processed, then resource allocation accuracy improves, but system complexity and overhead increase
Solution Approach 1:
The patent extracts only the most critical analytics-based information elements needed for resource allocation decisions, such as UE behavior patterns, communication priority levels, and spectral efficiency metrics. By selecting and processing only these essential parameters rather than all available link information, the system achieves improved resource allocation accuracy while avoiding the complexity burden of processing comprehensive detailed information
Solution Approach 2:
The system transforms detailed link information into simplified analytics-based parameters that capture essential UE behavior characteristics. By changing the representation form from raw detailed measurements to aggregated behavioral parameters, the system maintains allocation accuracy while reducing the complexity of information processing and storage requirements
3Productivity
If dynamic scheduling is optimized with more information, then communication performance improves, but overhead increases
Solution Approach 1:
The system applies partial action by implementing analytics-based optimization only for specific high-priority communication scenarios and UE types where the performance benefit justifies the overhead. Rather than applying comprehensive analytics processing to all communications, the system selectively enhances scheduling for cases where detailed behavioral information provides marginal gains, thereby improving overall communication performance while controlling overhead growth
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network node may receive link information associated with a wireless link between a second network node and a user equipment (UE). The first network node may provide non-binding analytics-based information associated with the wireless link. Numerous other aspects are described.