Parallel Linear Convolutional Filters for Nonlinear Interference Compensation
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Solution Overview
Problem
Current methods for nonlinear interference compensation in optical communications systems become impractically complex for channel memories exceeding 100 UI, limiting the transmission reach and increasing bit error rates due to nonlinear interference and amplified spontaneous emission.
Innovation Solution
A parallel array of linear convolutional filters processes selected signal samples to estimate and compensate nonlinear interference, reducing computational complexity by using a simplified algorithm that applies the estimated interference field to the signal, thereby addressing intra-channel and inter-sub-channel nonlinearity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If present methods of nonlinear pre-compensation are used, then nonlinear interference compensation is achieved, but device complexity grows rapidly with channel memory making implementation impractical for channel memories exceeding 100 UI
Solution Approach 1:
The patent segments the nonlinear interference compensation process into multiple parallel linear convolutional filters. Instead of using a single complex algorithm, the method divides the compensation task across multiple simpler filter operations, each processing specific portions of the signal. This segmentation allows the system to achieve nonlinear interference compensation while keeping individual filter complexities manageable, thereby resolving the contradiction between compensation effectiveness and overall device complexity.
Solution Approach 2:
The patent changes the parameter of channel memory handling by introducing a simplified algorithm that effectively reduces the computational burden associated with high channel memories. The method transforms the complex nonlinear pre-compensation problem into a series of linear convolution operations with reduced memory requirements, enabling practical implementation even for channel memories exceeding 100 UI while maintaining compensation performance.
2Measurement precision
If channel memory is increased to improve compensation accuracy, then nonlinear interference estimation is improved, but computational complexity increases making implementation impractical
Solution Approach 1:
The patent segments the interference estimation task across multiple parallel linear convolutional filters, where each filter processes specific signal portions independently. This segmentation enables accurate nonlinear interference estimation by distributing the computational load, avoiding the need for a single complex high-memory algorithm. The parallel structure maintains estimation accuracy while keeping individual filter complexities low and manageable.
Data Source
AI summary
Aspects of the present invention provide techniques for compensating nonlinear impairments of a signal traversing an optical communications system. A parallel array of linear convolutional filters are configured to process a selected set of samples of the signal to generate an estimate of a nonlinear interference field. The predetermined set of samples comprises a first sample and a plurality of second samples. A processor applies the estimated nonlinear interference field to the first sample to least partially compensate the nonlinear impairment.