Delay Profile Compression for Accurate Wireless Positioning
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Solution Overview
Problem
Current wireless communication technologies face challenges in accurately estimating the position of wireless devices due to noise interference and multipath effects, which affect the determination of Time of Arrival (TOA) and lead to inaccurate positioning, especially in indoor scenarios where the Line of Sight (LOS) signal is weak.
Innovation Solution
The implementation of a method that compresses and decompresses delay profiles using autoencoders to enhance positioning accuracy while minimizing reporting overhead, allowing for more precise channel impulse response reporting and improved interference peak detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If delay profile is reported with high precision to improve positioning accuracy, then positioning accuracy is improved, but reporting overhead increases
Solution Approach 1:
The patent extracts only the essential features from the complete delay profile by identifying and reporting only significant peaks (those above a threshold) rather than the entire delay profile. This extraction approach maintains positioning accuracy by focusing on the most relevant information while significantly reducing reporting overhead.
Solution Approach 2:
The patent changes the representation parameters of the delay profile by transforming it from a complete time-domain signal to a filtered set of peak parameters (time delays and amplitudes of significant peaks only). This parameter transformation reduces the data volume while preserving the critical information needed for accurate positioning.
2Measurement precision
If complete delay profile is transmitted to capture all channel information, then positioning accuracy is improved, but data transmission volume increases
Solution Approach 1:
The patent extracts only the essential features from the complete delay profile by identifying and reporting only significant peaks (those above a threshold) rather than the entire delay profile. This extraction approach maintains positioning accuracy by focusing on the most relevant information while significantly reducing reporting overhead.
Solution Approach 2:
The patent applies partial action by reporting only a subset of the delay profile information - specifically, only the significant peaks that contribute meaningfully to positioning accuracy. This partial reporting is sufficient for achieving accurate positioning without the need to transmit the complete delay profile, thus reducing data transmission volume.
3Reliability
If noise filtering is applied to remove interference peaks, then positioning reliability is improved, but risk of removing weak LOS peaks increases
Solution Approach 1:
The patent applies local quality by using different selection criteria for different peaks in the delay profile. Instead of uniform filtering, it evaluates each peak individually based on its amplitude and characteristics, applying a threshold that allows weak LOS peaks to pass through while filtering out noise and interference peaks. This localized evaluation maintains positioning reliability without sacrificing LOS peak detection accuracy.
Data Source
AI summary
In a first method, a wireless device estimates a delay profile of a channel impulse response, CIR, for a channel between a network node and the wireless device, compresses the delay profile using a compression function, and transmits the compressed delay profile. The compression function includes a first function and a quantizer. The first function is configured to receive input data and reduce a dimension of the input data. In a second method, a network node receives a compressed delay profile of CIR for a channel between a network node and a wireless device, decompresses the compressed delay profile using a decompression function, and estimates a position of the wireless device based on at least the decompressed delay profile. The decompression function includes a first function which is configured to receive input data and provide output data in a higher dimensional space than the input data.