Compressive Sensing Receiver Spurious Signal Removal
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Solution Overview
Problem
Compressive sensing receivers face accuracy degradation in spectral slice detection due to spurious signals generated by cross modulation of local oscillators, which are not effectively removed by existing methods, affecting the normal operation of measurement matrices.
Innovation Solution
A method that estimates and removes spurious signals from baseband signals using a stored spurious average value, and calibrates the measurement matrix by generating a calibration signal, performing Fast Fourier transforms, and decomposing singular values to improve spectral slice detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a compressive sensing receiver uses a theoretical measurement matrix for spectral slice detection, then the detection process is simple, but spurious signals from local oscillator cross modulation degrade detection accuracy
Solution Approach 1:
The patent performs preliminary spurious signal estimation and removal before spectral slice detection, and pre-calibrates the measurement matrix to account for non-linear effects. This preliminary processing eliminates the harmful spurious components that would otherwise degrade detection accuracy, allowing the use of a relatively simple detection process while maintaining high accuracy.
Solution Approach 2:
The patent introduces an intermediary calibration process that creates a corrected measurement matrix accounting for non-linear effects and spurious signals. This calibrated matrix acts as a mediator between the theoretical measurement matrix and the actual received signal, compensating for system imperfections and enabling accurate detection despite the presence of spurious components.
2Device complexity
If spurious signals are not removed from the baseband signal, then the processing is straightforward, but the spectral slice detection accuracy deteriorates
Solution Approach 1:
The patent performs preliminary spurious signal estimation and removal operations before the main spectral slice detection process. By eliminating spurious components in advance, the subsequent detection can proceed with relatively simple processing while achieving high accuracy, as the harmful interference has already been removed.
Solution Approach 2:
The patent extracts and removes the spurious signal components from the baseband signal through estimation and subtraction operations. This separation of the harmful spurious components from the useful signal allows the detection process to focus on the clean signal components, maintaining simplicity while improving accuracy.
3Measurement precision
If a calibration signal processing is performed to calibrate the measurement matrix, then the detection accuracy is improved, but the processing time and complexity increase
Solution Approach 1:
The patent performs the measurement matrix calibration as a preliminary operation before actual signal detection. Although the calibration process itself is computationally intensive, it is performed once in advance rather than repeatedly during detection, thereby improving detection accuracy while minimizing the time loss during actual operation.
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 enhances the accuracy of spectral slice detection by effectively removing spurious signals and calibrating the measurement matrix, leading to improved performance in compressive sensing receivers.
Implementation Method 1
a second signal generated by a local oscillator based on a pseudo random binary sequence (PRBS)
Implementation Method 2
performing a Fast Fourier transform on the filtered sampled second baseband signal
Implementation Method 3
decomposing singular values to improve spectral slice detection accuracy
Data Source
AI summary
A method of processing a signal in a compressive sensing receiver, includes: obtaining a first signal received via an antenna; generating a first baseband signal by mixing the first signal with a second signal generated by a local oscillator based on a pseudo random binary sequence (PRBS); removing a spurious from the first baseband signal based on a pre-stored estimation value obtained by estimating the spurious generated by the local oscillator in advance; and detecting a spectral slice including the first signal based on the first baseband signal from which the spurious is removed and a measurement matrix.