TRP Clustering for 5G Positioning Accuracy
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Solution Overview
Problem
Current reference signal-based positioning methods in 5G NR communication networks face high computational complexity and position estimation errors due to the inclusion of all Transmission Reception Points (TRPs), which can lead to inaccurate results.
Innovation Solution
The method involves clustering TRPs based on reliable measurement data, selecting a 'trusted' cluster for positioning, and using second reference signals to determine the mobile device's position, thereby reducing computational complexity and estimation errors through favorable weight settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all TRPs are included in the positioning calculation, then positioning accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments TRPs into multiple clusters based on measurement quality and spatial distribution. Instead of treating all TRPs uniformly, the system divides them into distinct groups (e.g., first cluster, second cluster) and selects representative TRPs from each cluster for positioning calculations. This segmentation reduces the number of TRPs processed while maintaining positioning accuracy.
Solution Approach 2:
The patent extracts and selects only the most reliable TRPs from the complete set. By evaluating measurement quality metrics and spatial characteristics, the system identifies and extracts a subset of TRPs that are most suitable for positioning calculations, excluding those with poor measurement quality or redundant spatial information.
2Measurement precision
If all TRPs are included in the positioning calculation, then positioning accuracy is improved, but measurement uncertainty increases
Solution Approach 1:
The patent applies local quality assessment by evaluating and comparing measurement characteristics of different TRPs. Each TRP is assessed based on its local measurement quality (e.g., signal strength, measurement accuracy) and spatial properties. TRPs with superior local quality metrics are selected for positioning calculations, ensuring that only reliable measurements are used.
3Device complexity
If TRP clustering is performed, then computational complexity is reduced, but positioning accuracy may deteriorate
Solution Approach 1:
The patent performs preliminary clustering of TRPs before the actual positioning calculation. By pre-organizing TRPs into clusters based on spatial and measurement characteristics, the system prepares a structured subset of TRPs that will be used for positioning. This preliminary action reduces the computational burden during positioning while maintaining accuracy through careful cluster formation.
Data Source
AI summary
Described is a method of determining a position of a mobile wireless device in a wireless communication network. The method comprises, for a plurality of clusters of transmission reception points (TRPs) associated with said mobile wireless device, measuring a parameter of first reference signals transmitted between said mobile wireless device and a single TRP from each cluster of TRPs. The method includes, based on the respective measured parameter of the first reference signals, selecting one cluster of TRPs from said plurality of clusters of TRPs. Position estimation information is determined from second reference signals transmitted between said mobile wireless device and a plurality of the TRPs comprising the selected cluster of TRPs. The determined position estimation information is used to determine a position for said mobile wireless device.