Multi-Core Decision Feedback Equalizer for ISI and Non-Linearity
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Solution Overview
Problem
Existing communications methods and systems are overly power hungry and spectrally inefficient, failing to effectively manage non-linearity and inter-symbol interference (ISI) in communication channels.
Innovation Solution
A decision feedback equalizer with multiple cores is employed, utilizing partial response pulse shaping filters and non-linearity compensation to optimize symbol mapping and equalization, reducing complexity and improving spectral efficiency while tolerating non-linearities in the communication channel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing communications methods are used, then system simplicity is maintained, but spectral efficiency is poor and power consumption is high
Solution Approach 1:
The equalizer is divided into multiple independent cores (first core, second core, third core, fourth core), each processing specific signal components. This segmentation allows parallel processing of complex operations, improving spectral efficiency while distributing computational complexity across multiple specialized units rather than requiring a single complex processor.
Solution Approach 2:
The patent introduces a multi-dimensional processing architecture by organizing equalizer functions across four distinct cores with different operational characteristics. This dimensional organization transforms a single complex processing path into multiple parallel processing dimensions, achieving higher spectral efficiency through coordinated multi-dimensional signal processing.
2Use of energy by moving object
If existing communications methods are used, then power consumption is high, but system operation is simple
Solution Approach 1:
By segmenting the equalizer into four specialized cores, each core can be optimized for specific computational tasks with appropriate power management. This allows the system to activate only necessary cores based on signal conditions, reducing overall power consumption compared to a single always-active complex equalizer.
Solution Approach 2:
The patent employs adaptive parameter adjustment where each equalizer core dynamically modifies its operational parameters (filter coefficients, processing gain, activation state) based on channel conditions and signal characteristics. This parameter optimization enables the system to achieve high performance while minimizing power consumption by adjusting operational intensity to match actual processing needs.
3Productivity
If partial response pulse shaping filters are used, then spectral efficiency improves, but non-linearity and ISI management becomes challenging
Solution Approach 1:
The multi-core equalizer architecture segments the challenging task of managing non-linearity and inter-symbol interference across multiple specialized processing units. Each core handles specific aspects of distortion compensation, allowing the system to effectively manage harmful factors while maintaining the spectral efficiency benefits of partial response pulse shaping.
Solution Approach 2:
The decision feedback equalizer structure incorporates feedback mechanisms where each core utilizes decision information from previous stages to compensate for non-linearities and ISI. This feedback approach allows the system to actively cancel harmful distortions while maintaining high spectral efficiency through coordinated multi-core operation.
Data Source
AI summary
One or more embodiments describe a decision feedback equalizer with multiple cores for highly spectrally efficient communications. An equalization circuit in a receiver may include a decision feedback equalizer circuit having a first plurality of tap coefficients that are determined based on a cost function that receives as input an error signal that is an inter-symbol-correlated (ISC) signal. The decision feedback equalizer circuit may further include a second plurality of tap coefficients that are determined based on a filter with an ISC response. The cost function may determine the mean square of the error signal. The cost function is constrained or unconstrained. The error signal may represents error caused by a channel. In some embodiments, the ISC signal may be a partial response signal, and the filter with an ISC response may be a partial response filter.