Decision Feedback Equalizer With SER-Biased Adaptation for ISI Mitigation
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Solution Overview
Problem
Existing communications methods and systems are overly power hungry and/or spectrally inefficient, leading to suboptimal performance in terms of energy consumption and spectral usage.
Innovation Solution
A decision feedback equalizer utilizing a symbol error rate biased adaptation function is implemented, which includes a system configured for low-complexity, highly-spectrally efficient communications. This system comprises a mapper, pulse shaping filter, timing pilot insertion, transmitter and receiver front-ends, filters, and equalization and sequence estimation circuits, designed to optimize symbol error rate performance and improve tolerance to non-linearity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional equalization methods are used, then inter-symbol interference can be mitigated, but system complexity and power consumption increase
Solution Approach 1:
The patent transforms the equalization problem from the time domain to the frequency domain by applying a discrete Fourier transform. This parameter transformation allows the equalizer to operate on frequency-domain representations of the signal, which simplifies the mathematical operations required for equalization and reduces computational complexity while maintaining effective interference mitigation.
Solution Approach 2:
The patent replaces traditional time-domain equalization mechanisms with a frequency-domain processing approach. By substituting the mechanical/time-based equalization process with frequency-domain transformation and processing, the system achieves the same equalization function with reduced computational burden and lower complexity.
2Reliability
If conventional equalization methods are used, then inter-symbol interference can be mitigated, but power consumption increases
Solution Approach 1:
The transformation to frequency-domain processing changes the operational parameters of the equalizer, enabling more efficient computation. This parameter change reduces the number of complex mathematical operations required, thereby lowering power consumption while maintaining the same level of interference mitigation performance.
Solution Approach 2:
By substituting time-domain equalization with frequency-domain processing, the patent replaces a power-intensive mechanical process with a more efficient computational approach, achieving the same reliability outcome with reduced energy expenditure.
3Productivity
If spectral efficiency is increased, then communication bandwidth utilization improves, but tolerance to channel non-linearity and distortion decreases
Solution Approach 1:
The patent implements a feedback mechanism where the receiver processes the received signal through frequency-domain equalization and determines the transmitted data. This feedback approach allows the system to adapt to channel conditions and maintain robustness against non-linearity and distortion even at high spectral efficiencies, as the equalization process compensates for channel impairments.
Solution Approach 2:
The substitution of time-domain processing with frequency-domain processing enables the system to handle high spectral efficiency transmissions more effectively. The frequency-domain approach provides better control over multi-path effects and non-linear distortions, maintaining reliability while achieving high spectral efficiency.
Data Source
AI summary
One or more embodiments describe a decision feedback equalizer utilizing symbol error rate biased adaptation function for highly spectrally efficient communications. A method may be performed in a decision feedback equalizer (DFE). The method may include determining values of tap coefficients used by the DFE based. The tap coefficients may be determined based on an error signal that is based on an estimated inter-symbol-correlated (ISC) signal. The tap coefficients may be determined based on a set of error vector(s), where each error vector in the set represents a difference between estimated symbols generated in the receiver and expected symbols. Determining the values of the tap coefficients may include using a symbol error rate function that estimates the actual symbol error rate in the receiver, wherein the symbol error rate function receives as input the set of error vector(s).