Communication Device Sensing via Channel Matrix Eigenvalue Decomposition
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Solution Overview
Problem
Current communication systems lack an explicit solution for implementing sensing functions in scenarios such as intrusion detection and track tracing, despite having sensing capabilities for direction, distance, and speed measurement.
Innovation Solution
A sensing method and apparatus that utilize channel estimation to obtain time-frequency domain channel matrices, which are then used to derive covariance or correlation coefficient matrices, allowing for eigenvalue decomposition to determine target sensing measurement results, enabling the detection of location and speed of objects in environments like intrusion detection or track tracing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensing functions are implemented in communication systems, then sensing capability is improved, but device complexity increases
Solution Approach 1:
The patent implements sensing functions within existing communication devices by reusing communication infrastructure (base stations, user equipment) and signaling protocols. The same wireless signals used for communication are also utilized for sensing measurements, allowing one device to perform multiple functions (communication and sensing) without requiring separate dedicated sensing hardware, thus improving versatility while controlling complexity.
2Measurement precision
If explicit sensing solutions are added for intrusion detection and track tracing, then sensing precision is improved, but device complexity increases
Solution Approach 1:
The patent enables sensing functions to be implemented using existing communication device capabilities and protocols. The base station and user equipment utilize their inherent signal processing, channel estimation, and measurement capabilities to perform sensing operations without requiring additional specialized hardware or complex external systems, allowing the devices to serve themselves for both communication and sensing purposes.
3Measurement precision
If channel estimation and eigenvalue decomposition are performed, then sensing measurement precision is improved, but processing time increases
Solution Approach 1:
The patent performs channel estimation and obtains channel matrices as part of the regular communication process before sensing measurements are required. By having the channel information readily available from prior communication signaling, the system avoids redundant processing and can quickly perform eigenvalue decomposition for sensing measurements when needed, reducing the effective processing time for sensing operations.
Data Source
AI summary
A sensing method and a communication device are provided. The sensing method includes: obtaining, by a first device, at least one sensing measurement result based on an eigenvalue of at least one first matrix. The at least one first matrix is obtained based on a time-frequency domain channel matrix. The time-frequency domain channel matrix includes related information of frequency domain channel responses corresponding to a plurality of time-frequency domain sampling points. Each time-frequency domain channel matrix corresponds to one antenna transmit-receive combination. The related information of the frequency domain channel response is obtained by the first device by performing channel estimation on a received first signal. The first matrix is a covariance matrix or a correlation coefficient matrix corresponding to the time-frequency domain channel matrix; and obtaining, by the first device, a target sensing measurement result based on the at least one sensing measurement result.