Wireless Positioning Reference Signals with AI LoS Reliability
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently transmitting and receiving radio signals, particularly in determining the reliability of line of sight (LoS) versus non-line of sight (NLoS) conditions for reference signals, which affects positioning accuracy and signal transmission efficiency.
Innovation Solution
The use of artificial intelligence/machine learning (AI/ML) models to obtain LoS-related information for reference signals, providing reliability information on whether each signal is via LoS or NLoS, and adjusting reference signal transmission power and muting patterns based on this information to enhance signal transmission and reception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AI/ML models are used to determine LoS/NLoS for reference signals, then positioning accuracy and reliability are improved, but device complexity and computational overhead increase
Solution Approach 1:
The system performs preliminary LoS/NLoS determination using AI/ML models before actual positioning operations. The device obtains LoS related information regarding reference signals in advance, storing results that can be quickly retrieved during positioning without repeating complex computations, thus improving reliability while managing computational overhead.
Solution Approach 2:
The patent introduces LoS related information as an intermediary element between the reference signals and positioning calculations. This intermediary contains pre-processed reliability data that simplifies subsequent positioning operations, reducing the computational burden while maintaining high positioning accuracy through the use of pre-analyzed LoS/NLoS characteristics.
2Measurement precision
If reference signal transmission power is increased to improve signal quality, then positioning accuracy improves, but energy consumption increases
Solution Approach 1:
The system applies partial action by adjusting reference signal transmission power based on LoS related information. Instead of uniformly increasing power for all signals, the device selectively enhances power only for reference signals identified as NLoS with low reliability, maintaining adequate power for LoS signals. This approach improves positioning accuracy for critical signals while minimizing overall energy consumption.
Data Source
AI summary
A method by which a device operates in a wireless communication system, according to at least one of the embodiments disclosed in the present specification, comprises: obtaining line of sight (LoS)-related information for at least one reference signal for positioning on the basis of an artificial intelligence/machine learning (AI/ML) model; and transmitting a signal including the LOS related information, wherein the LoS related information may include information about the reliability of determination by the AI/ML model regarding whether each reference signal is provided through the LoS or non-line of sight (NLoS).