Wiener Filter Tap Selection via Autocorrelation Estimation
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Solution Overview
Problem
Current channel estimation methods in wireless communication systems, such as LTE, face challenges in accurately selecting filter taps for Weiner filters due to unknown channel statistics, leading to sub-optimal performance and high computational complexity, especially in real-time digital signal processing.
Innovation Solution
The method estimates autocorrelation of channel taps based on received pilots in both time and frequency directions, allowing for the selection of optimal taps for Weiner filters, which can be pre-calculated or calculated in real-time, and uses arbitrary correlation functions, reducing complexity and improving channel estimation performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If channel statistics are assumed to be known for Wiener filter design, then channel estimation performance is improved, but in practice channel statistics are unknown leading to sub-optimal performance
Solution Approach 1:
The patent uses feedback by estimating autocorrelation from received pilot signals and using this estimated autocorrelation to select or design filter taps for the Wiener filter. This closed-loop approach allows the filter to adapt to actual channel conditions without requiring prior knowledge of channel statistics, resolving the contradiction between needing accurate statistics for optimal performance and the reality that statistics are unknown.
Solution Approach 2:
The system performs self-service by autonomously estimating its own channel autocorrelation properties from the received pilot signals and using this self-derived information to configure the Wiener filter. This eliminates the need for external knowledge of channel statistics, allowing the system to achieve optimal performance through self-characterization.
2Measurement precision
If optimal Wiener filter taps are selected using accurate channel statistics, then channel estimation performance is improved, but calculating these taps increases computational complexity
Solution Approach 1:
The patent pre-calculates and stores filter tap values for various autocorrelation scenarios in lookup tables. During real-time operation, the system only needs to estimate the autocorrelation and perform a table lookup to select the appropriate taps, avoiding the computationally intensive real-time calculation of optimal Wiener taps while maintaining estimation accuracy.
Solution Approach 2:
The system creates simplified representations of the optimal filter taps by pre-computing them for different channel conditions and storing them as lookup tables. This copying approach allows the system to use pre-prepared tap values that approximate the optimal solution without performing the complex real-time calculations required to derive them, thus reducing computational complexity while preserving accuracy.
3Adaptability or versatility
If real-time calculation of Wiener filter taps is performed, then adaptation to changing channels is improved, but processing time and complexity increase
Solution Approach 1:
The patent pre-computes filter tap values for various autocorrelation conditions and stores them in lookup tables before real-time operation. During channel estimation, the system only needs to estimate the current autocorrelation and retrieve the corresponding pre-computed taps, achieving rapid adaptation to channel changes without the time-consuming real-time calculation of optimal taps.
Solution Approach 2:
The system dynamically adapts to changing channel conditions by estimating the current autocorrelation and selecting appropriate pre-computed taps from lookup tables. This dynamic selection approach maintains adaptability to channel variations while avoiding the computational burden of real-time tap calculation, thus reducing processing time.
4Ease of manufacture
If standard correlation functions are used for filter design, then implementation is simplified, but performance may not match arbitrary channel models
Solution Approach 1:
The patent uses feedback by estimating the actual channel autocorrelation from received pilot signals and using this measured autocorrelation to select or design filter taps. This allows the system to adapt to the actual channel model rather than relying on standard correlation functions, improving performance match with the true channel while maintaining implementation simplicity through automated selection.
Solution Approach 2:
The system changes the autocorrelation parameter by estimating it from the actual received signals rather than assuming a standard form. This parameter adaptation allows the filter design to match the specific characteristics of the actual channel, improving reliability while the automated estimation process keeps implementation simple.
Data Source
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AI summary
The present invention relates to a method and apparatus for performing channel estimation in a wireless communication system, wherein pilot reference signals are extracted from a received signal based on pilot reference signal positions. The extracted pilot signals are compensated by an expected conjugate pilot reference signal and estimated tap values for a channel filter are derived by performing autocorrelation based on at least one of extracted and compensated pilot signals with different predetermined lag values in the time domain and extracted and compensated pilot signals with different predetermined lag values in the frequency domain. The estimated tap values are compared with precalculated tap values by using a comparison metric, and optimal ones of the estimated tap values are selected based on the result of the comparison metric.