UE-Based DL-RFFP Positioning With Capability-Aware Assistance Data
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Solution Overview
Problem
Existing wireless communication systems, particularly in the context of 5G, face challenges in achieving highly accurate positioning due to limitations in downlink radio frequency fingerprinting (DL-RFFP) procedures, which are not adequately supported by current UE capabilities and assistance data mechanisms.
Innovation Solution
User equipment (UE) transmits capabilities messages to a location server for engaging in DL-RFFP positioning and receives positioning assistance data based on these capabilities, utilizing machine learning models for enhanced RF fingerprinting-based positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DL-RFFP positioning procedure is implemented, then positioning accuracy is improved, but UE capability requirements and system complexity increase
Solution Approach 1:
The patent segments the positioning capability into distinct sets (first set and second set of capabilities), allowing UEs to selectively indicate their supported DL-RFFP features. This segmentation enables the system to activate only the necessary positioning functions based on UE capability, improving accuracy where needed while managing complexity by not requiring all UEs to support all features.
Solution Approach 2:
The patent introduces dynamic capability indication through provide capabilities messages that can be updated based on UE state. The UE can transition between different capability sets depending on operational conditions, allowing the system to adapt positioning accuracy requirements to actual UE capabilities and environmental factors, thereby managing the trade-off between accuracy and complexity dynamically.
2Measurement precision
If DL-RFFP positioning procedure is implemented, then positioning accuracy is improved, but assistance data requirements increase
Solution Approach 1:
The patent applies local quality by providing different sets of assistance data corresponding to different capability sets. The location server delivers tailored assistance data (first set or second set) based on the specific DL-RFFP capabilities indicated by the UE, ensuring that the UE receives only the necessary assistance data for its capabilities, thereby improving positioning accuracy while optimizing assistance data quantity.
3Measurement precision
If machine learning models are utilized for RF fingerprinting, then positioning precision is improved, but processing requirements and energy consumption increase
Solution Approach 1:
The patent implements partial action by selectively activating machine learning-based DL-RFFP processing only when the UE indicates support for the appropriate capability set. The system applies ML models partially - only for UEs that have indicated capability to handle them - thereby achieving high positioning precision for capable devices while avoiding unnecessary energy consumption in devices that do not require or support ML-based positioning.
Data Source
AI summary
Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) transmits one or more provide capabilities messages to a location server, the one or more provide capabilities messages indicating at least a first set of capabilities of the UE to engage in a downlink radio frequency fingerprint (DL-RFFP) positioning procedure, and receives one or more positioning assistance data messages for the DL-RFFP positioning procedure from the location server, the one or more positioning assistance data messages based at least on the first set of capabilities.