OCC/MUI Removal Filter for Frequency-Domain Channel Estimation
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Solution Overview
Problem
Existing channel estimation methods in 5G/NR communication systems face challenges in effectively suppressing multi-user interference (MUI) and orthogonal cover code (OCC) interference, leading to high normalized mean square error (NMSE) and degraded performance, especially in high SNR regimes.
Innovation Solution
Implementing a filtering-based channel estimation approach that designs filters with a stopband region between bandpass regions in the time domain to suppress MUI/OCC interference, utilizing time domain behavior without requiring fast Fourier transform (FFT) operations, and optimizing performance across various channel scenarios using supervised machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MMSE estimator is used for channel estimation, then estimation accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the channel estimation process into two distinct stages: a first stage that obtains an initial noisy channel estimate by removing reference signals, and a second stage that refines this estimate using filtering. This segmentation allows the computationally intensive refinement to be applied selectively rather than requiring complex MMSE calculations throughout the entire process, thereby reducing overall computational complexity while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary channel estimate acquisition in the first stage before applying refinement filtering in the second stage. By obtaining a preliminary estimate first and then selectively refining it, the system avoids the need to compute complex MMSE estimators from scratch, thus reducing computational complexity while preserving estimation accuracy where needed.
2Quantity of substance
If pilots/RS are transmitted sparsely in time and frequency domain, then overhead is reduced, but channel estimation performance degrades
Solution Approach 1:
The patent introduces a filtering mechanism as an intermediary process that operates on the initially estimated channel. This filter acts as a mediator that enhances the quality of channel estimates obtained from sparsely transmitted pilots by suppressing interference and noise, thereby improving estimation accuracy without requiring increased pilot overhead.
3Adaptability or versatility
If RS display varying SNR due to power control and environment change, then adaptability is improved, but estimation reliability deteriorates
Solution Approach 1:
The patent employs dynamic filtering in the refinement stage that can adapt to varying channel conditions including changing SNR levels. The filter characteristics can be adjusted based on observed channel behavior, allowing the system to maintain reliable estimation even when reference signals experience varying SNR due to power control adjustments or environmental changes.
4Adaptability or versatility
If channel experiences non-stationarity especially in mobility scenario, then mobility support is improved, but estimation stability worsens
Solution Approach 1:
The patent uses dynamic filtering approaches in the refinement stage that can track and adapt to non-stationary channel conditions. The filter can respond to rapid channel changes experienced in mobility scenarios while maintaining estimation stability through adaptive parameter adjustment, thus supporting mobility without sacrificing estimation reliability.
Data Source
AI summary
A method and device for filtering-based channel estimation. A method comprises configuring a filter design with a stopband region between at least two bandpass regions in a time domain associated with channel behavior, suppressing, via the filter design, multi-user interference (MUI) or orthogonal cover code (OCC) interference in the time domain, and providing frequency domain-based channel estimation (CE) based on the filter design.