Machine Learning Positioning with PRS Measurement Error Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems, particularly in the context of 5G, face challenges in accurately determining positioning measurements due to measurement errors, which affect the precision of location estimation in network nodes.
Innovation Solution
Implementing a method where a first network node determines positioning measurements based on a channel estimate of a positioning reference signal (PRS) and obtains measurement error feedback, which is based on the expected positioning measurement considering the locations of both the first and second network nodes, to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If positioning measurements are determined based on channel estimate of PRS, then positioning capability is enabled, but measurement errors reduce positioning precision
Solution Approach 1:
The patent implements feedback by transmitting measurement error information from the location server to the network node. The measurement error is calculated as the difference between the expected positioning measurement (based on known locations) and the actual measurement. This feedback enables the network node to compensate for systematic errors and improve positioning accuracy in subsequent measurements.
Solution Approach 2:
The patent performs preliminary calculation of expected positioning measurements using known locations of network nodes before actual positioning measurements are taken. This preliminary action establishes a reference value against which actual measurements can be compared to determine measurement errors, enabling error compensation before the next positioning cycle.
2Measurement precision
If measurement error feedback is obtained based on expected positioning measurement, then positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The patent introduces a location server as an intermediary entity that performs the complex calculations for determining expected positioning measurements and measurement errors. This mediator handles the computationally intensive tasks of calculating time of flight, expected measurements, and error values, while network nodes perform simpler measurements and apply provided error corrections, distributing complexity across the system.
Solution Approach 2:
The system enables self-service by allowing network nodes to autonomously perform positioning measurements using their own channel estimates and PRS signals. The nodes receive measurement error feedback and automatically apply corrections to their measurements without requiring manual intervention or complex processing at the node level, simplifying node design while maintaining accuracy.
Data Source
AI summary
Disclosed are techniques for wireless communication. In an aspect, a first network node determines at least one positioning measurement based on a channel estimate of a positioning reference signal (PRS) transmitted by a second network node, and obtains measurement error feedback for at least the at least one positioning measurement, wherein the measurement error feedback is based on an expected positioning measurement corresponding to the at least one positioning measurement, and wherein the expected positioning measurement is based on a location of the first network node and a location of the second network node.