Private 5G UE Positioning Using Pathloss Heatmap Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge of accurately determining the location of user equipment (UE) in 5G networks is exacerbated by the increased complexity and diversity of user equipment and data bandwidth usage, which complicates network design and management.
Innovation Solution
Implementing a system for location determination in private next-generation networks, utilizing techniques such as pathloss heatmaps and multi-pixel matching to enhance UE location accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional location determination methods are used in 5G networks, then network design and management become simpler, but UE location accuracy deteriorates due to increased complexity and diversity of user equipment and data bandwidth usage
Solution Approach 1:
The patent segments the location determination process into multiple components: pathloss measurement, heatmap generation with multi-pixel matching, and AI/ML model application. Each component handles a specific aspect of location determination, allowing the system to achieve high accuracy without overwhelming network design complexity by breaking down the problem into manageable segments
Solution Approach 2:
The patent changes the parameters used for location determination by introducing pathloss-based heatmaps with multi-pixel matching instead of traditional single-point measurement methods. This parameter change enables more accurate location estimation by considering multiple pixels and pathloss variations, thereby improving measurement precision while managing complexity through structured parameter transformation
2Measurement precision
If pathloss heatmaps with multi-pixel matching are implemented, then UE location precision improves, but computational complexity and processing requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-generating heatmaps with multi-pixel matching data and pre-training AI/ML models offline. This allows the complex computational work to be done in advance, reducing real-time processing complexity while maintaining high location determination precision during actual network operation
Solution Approach 2:
The patent uses copying by creating heatmap representations that replicate the spatial pathloss characteristics across multiple pixels. These heatmaps serve as simplified models that can be efficiently processed and matched against actual measurements, reducing computational complexity while preserving location determination accuracy
Data Source
AI summary
An apparatus and system are described to provide indoor positioning and movement information using a private next generation (NG) network. A heatmap of pathloss vs distance from a remote radio unit (RRU) is provided from the UE and federated with other heatmaps from different UEs under similar conditions. The federated heatmap is provided to the UE. A private location server containing an AI module is trained using data from the UEs. The location and movement of the UE is determined to a particular pixel based on the heatmap. WiFi reference points (RP) are used if multiple pixels satisfy data of the heatmap.