Frequency Offset Estimation via Preamble Interpolation
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Solution Overview
Problem
Existing OFDM systems face challenges in accurately estimating and compensating for frequency offset due to quasi-periodic property distortions in preambles, which lead to inter-carrier interference, and increasing sampling frequency is costly and impractical.
Innovation Solution
The method involves using interpolation, such as linear or sinc function interpolation, to reconstruct the quasi-periodic property of the preamble, allowing for more accurate estimation of frequency offset angles in wireless communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sampling frequency is increased to improve the quasi-periodic property of the preamble, then the accuracy of frequency offset estimation is improved, but the hardware cost increases
Solution Approach 1:
The patent changes the parameter of sampling frequency from a fixed high value to a lower value combined with interpolation processing. By adjusting the sampling frequency parameter and compensating through interpolation algorithms (linear interpolation, cubic interpolation, or sinc interpolation), the system achieves accurate frequency offset estimation without requiring high sampling frequency hardware
Solution Approach 2:
The patent replaces the mechanical approach of increasing sampling frequency with a signal processing approach using interpolation algorithms. Instead of relying on hardware-level sampling rate increases, the system uses software-based interpolation to reconstruct the quasi-periodic property, substituting mechanical hardware improvement with algorithmic processing
2Stability of the object's composition
If the sampling frequency is increased to improve the quasi-periodic property of the preamble, then the quasi-periodic property is improved, but the hardware cost increases
Solution Approach 1:
The patent modifies the sampling frequency parameter from high to low, and compensates for the resulting degradation in quasi-periodic property through interpolation processing. This parameter change approach maintains the necessary signal characteristics without requiring high sampling frequency hardware
Solution Approach 2:
The patent introduces interpolation algorithms as an intermediary processing step between sampling and frequency offset estimation. This intermediary reconstructs the quasi-periodic property that would otherwise be degraded by lower sampling frequency, acting as a bridge that maintains signal quality without hardware upgrades
3Measurement precision
If conventional frequency offset estimation is used without interpolation, then the device complexity is low, but the frequency offset estimation accuracy is poor
Solution Approach 1:
The patent applies interpolation processing as a preliminary step before frequency offset estimation. By pre-processing the received signal to reconstruct its quasi-periodic property, the system prepares the signal for more accurate frequency offset detection, improving measurement precision before the actual estimation occurs
Data Source
AI summary
A method for estimating frequency offset is provided. First, a baseband signal with a preamble featuring quasi-periodic property is received. Next, the quasi-periodic property of the preamble of the received baseband signal is reconstructed by interpolation. Next, a frequency offset angle is estimated by using the reconstructed baseband signal. The accuracy of estimating frequency offset is increased because of better reconstructed quasi-periodic property of the preamble.