Frequency Error Estimation via Autocorrelation Phase Processing
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Solution Overview
Problem
Existing methods for estimating frequency errors between transmitters and receivers in wireless communication networks are either limited in frequency capture range, computationally intensive, or perform poorly at low signal-to-noise ratios (SNR), especially due to noise affecting angle estimation.
Innovation Solution
A method that processes pairs of correlator outputs with specific spacings to combine them coherently, improving the signal-to-noise ratio and preserving phase changes, which involves autocorrelation to remove noise and allow for accurate frequency error estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing frequency error estimation methods are used, then the estimation process is simple, but the accuracy deteriorates at low signal-to-noise ratios due to noise affecting angle estimation
Solution Approach 1:
The patent introduces an intermediary variable (the series of values with phase components) that mediates between the raw correlator outputs and the frequency error estimation. By processing the correlator outputs through this intermediary representation and applying autocorrelation, the method filters out noise while preserving the phase information needed for accurate frequency error estimation, even in low SNR conditions
Solution Approach 2:
The patent performs preliminary autocorrelation processing on the correlator outputs before conducting the frequency error estimation. This preliminary action of generating a series of values with phase components and removing noise through autocorrelation prepares the data in advance, ensuring that the subsequent frequency error calculation is based on cleaned, high-quality phase information
2Adaptability or versatility
If existing frequency error estimation methods are used, then the computational process is simple, but the frequency capture range is limited
Solution Approach 1:
The patent transitions from direct frequency error calculation to a multi-dimensional approach by first computing correlator outputs, then generating a series of values with phase components, applying autocorrelation across different lags, and finally extracting the frequency error. This dimensional expansion in the processing space enables broader frequency capture range while managing complexity through structured computation
3Measurement precision
If existing frequency error estimation methods are used, then the processing is straightforward, but the computational intensity increases for accurate estimation
Solution Approach 1:
The patent segments the frequency error estimation process into distinct computational stages: (1) correlator output generation, (2) series of values with phase components creation, (3) autocorrelation processing, and (4) frequency error calculation. This segmentation allows the method to achieve high accuracy through systematic processing while managing computational intensity by breaking down the complex estimation into manageable, optimized steps
Data Source
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AI summary
A frequency error embodied in a series of values is determined by processing each of two or more selected values with another value in the series, each other value being spaced from its respective selected value by a first spacing, to generate processed values that all comprise substantially the same phase component; combining the processed values to generate a combined value that comprises substantially the same phase component as the processed values; repeating the processing and combining with the same selected values but a second spacing, different from the first spacing, to generate a combined value comprising a different phase component from the combined value generated using the first spacing, reflecting the frequency error; and determining the frequency error in dependence on the combined values generated using the first and second spacings.