Doppler Frequency Shift Determination via CSI Conjugate Multiplication
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Solution Overview
Problem
Current methods for determining the Doppler frequency shift of wireless signals reflected by moving objects in high carrier frequency systems, such as Wi-Fi and RFID, face challenges in accurately extracting the tiny frequency shifts due to the high noise levels and require modifications to existing commercial wireless devices.
Innovation Solution
A method utilizing channel state information (CSI) from multiple antennas to eliminate random phase shifts and static path signals, employing the MUSIC algorithm to calculate the frequency spectrum and determine the Doppler frequency shift of wireless signals directly reflected by a moving object without modifying hardware, using conjugate multiplication and mean subtraction to isolate dynamic path signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high carrier frequency signals (hundreds of MHz to dozens of GHz) are used in commercial wireless systems, then communication bandwidth and data rate are improved, but the Doppler frequency shift becomes extremely small (mere dozens of Hertz) and difficult to extract accurately
Solution Approach 1:
The patent segments the received signal into multiple paths based on arrival time and angle, separating the weak reflected signal from the strong direct signal. By processing each path independently through eigenvalue decomposition, the method can accurately measure the tiny Doppler shift of the reflected signal without being overwhelmed by the dominant direct path signal.
Solution Approach 2:
The patent introduces an intermediary processing step using eigenvalue decomposition and autocorrelation matrix analysis. This intermediary method acts as a bridge between the high-frequency carrier signal and the low-frequency Doppler shift measurement, enabling accurate extraction of the tiny frequency shift by transforming the problem into the eigenvalue domain where the small Doppler components become distinguishable.
2Measurement precision
If conventional Wi-Fi signal receivers are modified to splice multiple signal symbols for high-precision frequency domain sampling, then Doppler frequency shift extraction accuracy is improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent leverages the self-service capability of existing commercial Wi-Fi receivers by utilizing their built-in Channel State Information (CSI) functionality. Instead of modifying the receiver architecture, the method uses the receiver's existing ability to provide CSI data, which contains the necessary phase and amplitude information, and processes this data through eigenvalue decomposition to achieve high-precision Doppler measurement.
Solution Approach 2:
The patent changes the processing parameter from time-domain signal splicing to frequency-domain CSI parameter analysis. By working with the CSI parameters (amplitude and phase) already provided by commercial receivers at the frequency domain, the method achieves high-precision Doppler measurement without requiring complex time-domain signal processing or receiver modifications.
3Measurement precision
If the MUSIC algorithm is used to estimate frequency spectrum from CSI data, then Doppler frequency shift determination accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary action by constructing the autocorrelation matrix and conducting eigenvalue decomposition before applying the MUSIC algorithm. This preliminary processing organizes the CSI data into a structured form with identified signal and noise subspaces, which significantly simplifies the subsequent MUSIC algorithm execution and reduces the computational burden during real-time Doppler frequency estimation.
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 method effectively determines the complete Doppler frequency shift, including magnitude and direction, with high accuracy, suitable for common commercial wireless devices like Wi-Fi network cards, without hardware modifications, ensuring reliable and efficient operation.
Implementation Method 1
If one of the transmitting terminal, the reflector, or the receiving terminal in a signal path is in constant motion, this would lead to an offset between the frequency of the signal measured at the receiving terminal and the carrier frequency of the signal transmitted at the transmitting terminal. Such frequency shift is called a Doppler frequency shift.
Data Source
AI summary
The present disclosure provides a method for determining a Doppler frequency shift of a wireless signal directly reflected by a moving object. An example method includes eliminating a random phase shift caused by non-synchronization between a wireless transmitting device and a wireless receiving device by using conjugate multiplication of the channel state information (CSI) on two antennas, thereby obtaining the complete Doppler frequency shift information from the phase information of the channel state information. The example method eliminates the effect on the Doppler frequency shift caused by frequency information of static paths in a manner of removing the mean, thereby obtaining an accurate frequency estimation of the moving object. A Multiple Signal Classification (MUSIC) algorithm may be used to estimate a frequency spectrum according to practical sampling intervals to avoid an effect on the frequency estimation accuracy caused by uneven sampling rate in a practical wireless transceiving system.