Level Equalization for Optical Communication Systems
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Solution Overview
Problem
Higher-order modulation optical communication systems face performance degradation due to implementation imperfections such as limited bandwidth and non-linear responses of optical and electrical components, leading to higher bit error rates (BER) and error floors, which existing DSP-based equalization techniques fail to fully address.
Innovation Solution
The implementation of level equalization through binning and polynomial transformation functions to adjust signal levels, ensuring average signal levels align with ideal levels, thereby improving BER performance by compensating for implementation-related distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If higher-order modulation is employed to increase spectral efficiency, then transmission capacity is improved, but signal quality and bit error rate deteriorate due to implementation imperfections
Solution Approach 1:
The patent applies parameter changes by adjusting signal levels through level equalization. The system computes average levels for different signal amplitude bins and applies transformation functions to correct deviations from ideal levels, thereby improving signal quality while maintaining higher-order modulation benefits
Solution Approach 2:
The patent implements feedback through the level equalization process where received signal levels are measured, compared against ideal levels, and correction factors are applied back to the signal. This closed-loop approach continuously compensates for implementation imperfections in the transmission system
2Reliability
If DSP-based equalization techniques are applied to compensate for impairments, then signal conditioning is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the signal processing into distinct stages: binning signals based on amplitude levels, computing average levels for each bin, determining transformation functions, and applying corrections. This segmented approach makes the complex equalization process more manageable and implementable
Solution Approach 2:
The level equalization technique is self-adaptive, automatically computing correction factors from the received signal itself without requiring external calibration or complex training sequences. The system uses the signal's own statistical properties to determine and apply corrections
Data Source
AI summary
A method comprising receiving digital samples from an optical communication system, assigning the samples into bins based on signal levels of the samples, computing an average signal level for each bin, determining a level adjustment transformation function for the samples based on the average signal levels of the bins, and applying the level adjustment transformation function to the samples. Also, disclosed is an optical receiver comprising a frontend configured to receive an optical signal over an optical channel, and convert the optical signal into a plurality of sequences of digital samples, and a processor coupled to the frontend and configured to perform a channel equalization on the samples of the sequences, assign the channel equalized samples of each sequence into bins based on signal levels of the channel equalized samples, determine a level adjustment transformation function for each sequence, and apply the level adjustment transformation function to each sequence.