Clipped Signal Reconstruction for Low-Resolution MIMO Receivers
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Solution Overview
Problem
Clipping distortion in massive MIMO systems introduces significant overload distortion, corrupting data and causing inaccurate channel state information and data estimation at the base station (BS) and/or user equipment (UEs), especially in multi-user MIMO systems, due to the limitations of analog-to-digital converters (ADCs) with reduced resolution.
Innovation Solution
A clipping-aware MMSE receiver reconstructs clipped samples by exploiting correlations among clipped and non-clipped samples, minimizing mean-squared error through an iterative algorithm that replaces clipped sample values with expected values based on posterior probability density functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If ADC resolution is reduced to lower power consumption and hardware complexity, then power consumption and device complexity are reduced, but overload distortion increases significantly
Solution Approach 1:
The patent applies minimum mean-squared error (MMSE) estimation to reconstruct the original high-resolution signal from clipped low-resolution ADC outputs. The MMSE estimator minimizes the expected squared error between the reconstructed signal and the original signal, effectively converting the harmful clipping distortion into a manageable estimation problem that can be solved optimally with statistical knowledge of the signal distribution
Solution Approach 2:
The patent introduces an intermediate reconstruction stage between the low-resolution ADC and the final signal processing. This intermediate MMSE estimator acts as a mediator that recovers the high-resolution signal characteristics from the degraded clipped samples, allowing the system to benefit from low-resolution ADCs while maintaining high signal quality
2Device complexity
If ADC resolution is reduced to reduce hardware complexity, then device complexity is reduced, but data quality deteriorates due to clipping distortion
Solution Approach 1:
The MMSE reconstruction technique converts the harmful effect of clipping into a beneficial estimation process. By exploiting the statistical properties of the clipped signal and minimizing mean-squared error, the system recovers high-quality data from low-resolution ADC outputs, effectively transforming hardware limitations into a solvable estimation problem
Solution Approach 2:
The patent creates a virtual copy of the high-resolution signal through statistical estimation. The MMSE estimator generates reconstructed samples that replicate the statistical characteristics and information content of the original high-resolution signal, allowing the system to work with low-resolution hardware while maintaining high-resolution data quality
3Adaptability or versatility
If clipping is applied to limit signal values, then system limitations are respected, but frequency components are introduced causing aliasing
Solution Approach 1:
The patent transforms the aliasing problem caused by clipping into a reconstructable distortion pattern. The MMSE estimator recognizes the statistical signature of clipped samples and recovers the original frequency content, converting the harmful aliasing effect into information that can be used to reconstruct the true signal spectrum
Data Source
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AI summary
Using information contained in clipped samples from analog-to-digital (ADC) conversion to improve receiver performance, by, for example, reducing the clipping distortion caused by ADCs due to its data resolution constraints. This provides an advantage over existing solutions, which perform sub-optimally because the existing solution discard information in the clipped samples.