AI-Assisted Positioning Measurement Reporting with Metric Filtering
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Solution Overview
Problem
The increasing complexity of wireless communication networks due to ultra-high rates, ultra-low latency, and ultra-large connections poses challenges in network planning, operation, and maintenance, particularly in positioning terminal devices effectively using artificial intelligence.
Innovation Solution
A positioning method and apparatus utilizing artificial intelligence (AI) to adaptively adjust measurement results and configure reference signals based on channel conditions, reducing transmission overheads while maintaining positioning accuracy by selectively reporting or enhancing measurement results and reference signal configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all measurement results are reported to the location management apparatus, then positioning accuracy is improved, but transmission overheads increase
Solution Approach 1:
The patent changes the parameter of measurement result reporting by introducing a metric-based filtering mechanism. The first communication apparatus evaluates measurement results using a first metric and compares it against a first condition (threshold) to determine whether to report. This parameter change transforms the reporting behavior from unconditional (all results) to conditional (only results meeting the metric threshold), thereby reducing transmission overheads while preserving positioning accuracy for qualifying measurements.
Solution Approach 2:
The patent applies partial action by selectively reporting only a subset of measurement results that satisfy the first condition rather than reporting all measurement results. The first communication apparatus performs partial reporting based on the metric evaluation, sending only those measurement results that meet the predefined threshold criteria to the location management apparatus, thus reducing unnecessary data transmission while maintaining positioning accuracy.
2Productivity
If measurement reporting is reduced to lower transmission overheads, then network efficiency is improved, but positioning accuracy may deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where the first communication apparatus continuously evaluates measurement results using the first metric and compares them against the first condition (threshold). This feedback loop ensures that only measurement results meeting the quality criteria are reported, providing the location management apparatus with sufficient information to maintain positioning accuracy while reducing unnecessary transmissions to improve network efficiency.
Solution Approach 2:
The patent changes the reporting parameter from fixed (all or nothing) to dynamic (conditional based on metric evaluation). By introducing the first metric and first condition as variable parameters, the system adaptively adjusts reporting behavior based on actual measurement quality, ensuring positioning accuracy is maintained when needed while optimizing network efficiency when measurements meet the threshold criteria.
3Adaptability or versatility
If AI-based positioning is implemented in complex wireless networks, then positioning capability is enhanced, but system complexity increases
Solution Approach 1:
The patent segments the positioning system into distinct functional components: the first communication apparatus performs measurement and metric evaluation, the location management apparatus receives filtered measurement results and performs AI-based positioning. This segmentation distributes complexity across multiple entities, with each performing specialized functions, thereby enhancing overall positioning capability while managing system complexity through functional decomposition.
Solution Approach 2:
The patent introduces an intermediary filtering mechanism (the first metric and first condition evaluation) between the measurement process and the AI positioning process. This intermediary layer pre-processes measurement results by filtering based on quality criteria, reducing the data burden on the AI positioning algorithm and simplifying its input requirements, thereby enhancing positioning capability while managing system complexity.
Data Source
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AI summary
A positioning method and an apparatus are provided. The method includes: A first communication apparatus separately measures a first reference signal and a second reference signal from a second communication apparatus, and determines a first measurement result of the first reference signal and a second measurement result of the second reference signal. The first communication apparatus determines whether a first metric corresponding to the first measurement result meets a first condition. The first communication apparatus sends all or a part of the second measurement result to a location management apparatus based on a determining result, where all or the part of the second measurement result is used to determine location information of the first communication apparatus or the second communication apparatus based on an AI manner. In this application, reported measurement results may be adaptively adjusted based on different measurement results.