Adaptive UE Position Estimation Selection Using RF-S and PRS
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communication systems lack support for passive positioning of user equipment (UE) using radio frequency (RF) sensing, which can enhance power savings and localization accuracy in 5G and beyond.
Innovation Solution
A position estimation selection scheme that selects from multiple schemes based on criteria, including RF-S measurement, PRS measurement, or combinations, to optimize power consumption and accuracy for UE positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If passive positioning using RF sensing is implemented, then power consumption is reduced and positioning accuracy is improved, but the system complexity increases due to multiple positioning schemes and selection criteria
Solution Approach 1:
The patent implements dynamic selection among multiple positioning schemes (first scheme using RF-S measurements from other nodes, second scheme using PRS measurements, third scheme combining both, fourth scheme using multiple position estimates) based on current positioning conditions and requirements. This dynamic adaptation allows the system to optimize power consumption and accuracy for each specific scenario without permanently increasing complexity
Solution Approach 2:
The patent changes key parameters including the type of measurement information used (RF-S vs. PRS), the transmitting node identity (UE itself vs. other wireless nodes), and the combination of measurement sources. By varying these parameters based on selection criteria, the system achieves different positioning performance characteristics without requiring a completely new system architecture
2Measurement precision
If multiple position estimation schemes are implemented, then positioning accuracy is improved, but processing time and latency increase
Solution Approach 1:
The patent performs preliminary evaluation of selection criteria (including measurement availability, accuracy requirements, and power constraints) before committing to a positioning scheme. This preliminary assessment prevents unnecessary processing of multiple schemes and reduces latency by selecting the most appropriate scheme in advance
Solution Approach 2:
The patent segments the positioning process into distinct schemes with specialized purposes: the first scheme for passive positioning scenarios, the second scheme for active positioning, the third scheme for combined approaches, and the fourth scheme for multiple estimate fusion. This segmentation allows each scheme to be optimized independently and selected based on specific needs, reducing overall processing time
3Measurement precision
If RF-S measurement information from other wireless nodes is used, then positioning accuracy is improved, but device complexity and coordination requirements increase
Solution Approach 1:
The patent introduces a positioning scheme selection mechanism that acts as an intermediary, deciding whether to use RF-S measurements from other wireless nodes based on predefined criteria. This intermediary layer simplifies coordination by providing clear rules for when multi-node RF-S measurements should be used, reducing the complexity burden
Data Source
AI summary
Aspects of the disclosure are directed to a position estimation selection scheme for position estimation of a user equipment (UE). For example, depending on various factors (e.g., UE battery level, positioning accuracy requirements, etc.), different positioning schemes (e.g., positioning reference signal (PRS)-only or legacy positioning, passive UE position estimation, semi-passive UE position estimation, etc.) may be preferred. In an aspect, a set of selection criteria may be evaluated to select the particular position estimation scheme to be implemented for a particular position estimation session of a UE. Such aspects may provide various technical advantages, such as reducing power consumption at the target UE (e.g., particularly advantageous for RedCap UEs), more accurate UE position estimation, reduced UE position estimation latency, and so on.