Wi-Fi Sensing Channel Variation Detection Using Time-Domain Representation
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Solution Overview
Problem
Wi-Fi sensing systems face inefficiencies in detecting physical processes like motion, as channel perturbations are easier to detect at some frequencies and harder at others due to destructive or constructive interference of time-domain pulses.
Innovation Solution
The system calculates a time-domain channel representation (TD-CRI) from channel state information (CSI) and uses this to generate estimated channel responses for various transmission channels, allowing it to determine preferred transmission channels for accurate detection of physical processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Wi-Fi sensing system measures all available frequencies to determine optimal transmission channels, then detection accuracy is improved, but system complexity and measurement time increase
Solution Approach 1:
The system performs preliminary channel sounding to obtain channel state information (CSI) before actual sensing measurements. This preliminary action characterizes the channel properties in advance, allowing the system to identify optimal frequencies without needing to measure all frequencies during the actual sensing operation. The CSI data is stored and reused to determine preferred transmission channels.
Solution Approach 2:
The system creates a time-domain channel representation (TD-CRI) as a copy or model of the actual channel characteristics. This TD-CRI serves as a simplified representation that can be used to estimate channel responses at different frequencies without performing actual measurements at all frequencies. The copying approach allows efficient determination of optimal frequencies based on the modeled channel behavior.
2Measurement precision
If the Wi-Fi sensing system uses trial and error methods to find optimal frequencies, then detection accuracy is improved, but time consumption and productivity decrease
Solution Approach 1:
The system uses the obtained CSI data to provide feedback about channel conditions at different frequencies. This feedback mechanism allows the system to identify which frequencies are most suitable for sensing without random trial and error. The feedback loop enables intelligent selection of optimal frequencies based on actual channel characteristics, significantly reducing the time needed to achieve accurate detection.
Solution Approach 2:
The system transforms the channel state information from frequency domain to time domain representation (TD-CRI), and then uses this transformed data to estimate channel responses at various frequencies. By changing the domain and representation parameters of the channel data, the system can efficiently determine optimal frequencies without exhaustive measurement or trial-and-error approaches.
3Measurement precision
If the Wi-Fi sensing system operates at frequencies with constructive interference, then detection accuracy is improved, but the system cannot predict which frequencies are optimal without measurement
Solution Approach 1:
The system performs preliminary channel sounding to obtain CSI that characterizes the channel's frequency response and interference patterns. This preliminary action allows the system to predict which frequencies will exhibit constructive or destructive interference before actual sensing measurements begin. The pre-obtained CSI data is used to generate TD-CRI and estimate optimal frequencies in advance.
Solution Approach 2:
The time-domain channel representation (TD-CRI) acts as an intermediary between the raw CSI data and the optimal frequency selection. The TD-CRI transforms the frequency-domain CSI into a time-domain representation that makes it easier to identify channel characteristics and predict optimal frequencies. This intermediary representation bridges the gap between raw measurements and actionable frequency selection without requiring direct trial-and-error measurement at each frequency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the Wi-Fi sensing system to efficiently detect physical processes by identifying optimal frequencies for transmission and measurement, improving detection accuracy and reducing the need for trial-and-error methods.
Implementation Method 1
a sensing transmitter and a sensing receiver to exchange sensing transmissions with each other via a sensing space
Implementation Method 2
calculating a time-domain channel representation (TD-CRI) of the first CSI by transforming the first CSI into the time domain
Implementation Method 3
channel perturbances in a sensing space due to a physical process in the sensing space (for example, motion or movement)
Data Source
AI summary
Systems and methods for Wi-Fi sensing are provided. A method for Wi-Fi sensing carried out by a sensing device including a processor is described. Initially, first channel state information (CSI) of a first transmission channel representing a first sensing measurement performed on a first sensing transmission transmitted from a sensing transmitter to a sensing receiver in the first transmission channel may be received. A time-domain channel representation (TD-CRI) of the first CSI may be calculated by transforming the first CSI into the time domain. Then, a plurality of estimated channel responses corresponding to a plurality of transmission channels may be generated according to the TD-CRI. One or more preferred transmission channels from among the plurality of transmission channels may be determined according to the plurality of estimated channel responses.