Channel Estimation Path Selection for Noise Suppression
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Solution Overview
Problem
Existing channel estimation methods suffer from poor accuracy due to insufficient noise suppression and signal filtering, affecting the performance of channel equalization in wireless communication systems.
Innovation Solution
A method involving initial channel estimation based on time-domain training sequences, calculation of path power, setting a channel estimation window, determining a noise threshold, and selecting effective paths to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing channel estimation methods are used, then the channel estimation process can be completed, but the accuracy is poor due to insufficient noise suppression and signal filtering
Solution Approach 1:
The patent segments the channel estimation process into distinct stages: initial channel estimation, path power calculation, effective path selection, and target channel estimation. This segmentation allows for targeted noise suppression and signal filtering at each stage, improving overall accuracy by addressing harmful factors systematically rather than attempting single-stage estimation.
Solution Approach 2:
The patent performs preliminary actions by calculating path powers and determining effective paths before final channel estimation. This preliminary analysis of signal characteristics allows the system to identify and weight significant paths while suppressing noise components, thereby improving the accuracy of the subsequent target channel estimation.
2Measurement precision
If more complex noise suppression and signal filtering are applied, then channel estimation accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent applies partial action by focusing computational resources on identifying and processing only the effective paths rather than attempting to process all possible paths equally. By determining a limited number of effective paths based on power thresholds, the system achieves improved accuracy without the computational burden of exhaustive processing of all signal components.
Solution Approach 2:
The patent changes parameters by transitioning from raw received signals to path power representations, then to effective path selections, and finally to target channel estimates. This parameter transformation sequence simplifies the processing at each stage by working with increasingly refined representations, reducing overall computational complexity while maintaining accuracy.
Data Source
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AI summary
A channel estimation method and apparatus, a device, and a storage medium are provided. The method includes: determining an initial channel estimation according to a received time-domain training sequence and a local time-domain training sequence, and calculating the power of each path of the initial channel estimation; setting a channel estimation window with a preset length in the initial channel estimation, and determining a noise threshold according to the power of a path within the channel estimation window and/or the power of a path outside the channel estimation window; determining a number of effective paths according to the noise threshold and the power of each path of the channel estimation window; and selecting a path for the initial channel estimation according to the number of effective paths to obtain a target channel estimation.