Adaptive Nonlinear Receiver Modeling for Distortion-Tolerant Modulation
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Solution Overview
Problem
Existing communication systems are power hungry and spectrally inefficient, particularly due to the degradation of complex linear modulation schemes in the presence of phase noise and non-linear distortion, which increases the gap between desired and actual spectral efficiency as higher-order modulation is needed for increased throughput.
Innovation Solution
An adaptive non-linear model is implemented in communication systems, where a receiver generates estimates of transmitted symbols using a sequence estimation process that incorporates a non-linear model, adapting based on communication information to improve spectral efficiency and tolerance to non-linearity, by using partial response signals and dynamically updating the non-linear model to compensate for distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If higher-order modulation is used to increase throughput, then spectral efficiency is improved, but sensitivity to non-linear distortion and phase noise increases
Solution Approach 1:
The patent transforms the received signal through mathematical operations including frequency domain conversion and iterative processing to change the signal parameters, enabling higher-order modulation to be used while maintaining robustness against non-linear distortion and phase noise
Solution Approach 2:
The patent employs iterative processing where estimated symbols are fed back into the processing chain to refine subsequent estimates, allowing the system to compensate for non-linear distortion effects and maintain reliability at higher spectral efficiencies
2Productivity
If complex linear modulation schemes are used, then spectral efficiency is improved, but performance degrades in the presence of phase noise and non-linear distortion
Solution Approach 1:
The patent replaces traditional time-domain equalization methods with frequency domain processing and iterative signal transformation, substituting conventional approaches with mathematical transformations that are more robust to non-linear distortion and phase noise
Solution Approach 2:
The patent performs preliminary frequency domain conversion and signal transformation before symbol detection, preparing the signal in advance to be more resistant to the effects of non-linear distortion and phase noise during the detection process
Data Source
AI summary
A receiver may be operable to generate estimates of transmitted symbols using a sequence estimation process that may incorporate a non-linear model. The non-linear model may be adapted by the receiver based on particular communication information that may be indicative of non-linearity experienced by the transmitted symbols. The receiver may generate a reconstructed signal from the estimates of the transmitted symbols. The receiver may adapt the non-linear model based on values of an error signal generated from the reconstructed signal, and the values of the error signal may be generated from a portion of the generated estimates that may correspond to known symbols and/or information symbols. The values of the error signal corresponding to the known symbols may be given more weight in an adaptation algorithm, and the values of the error signal corresponding to the information symbols may be given less weight in the adaptation algorithm.