Adaptive Equalization for Probabilistic Shaping Polarization Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional DSP algorithms fail to effectively compensate for polarization crosstalk and polarization mode dispersion in probabilistic shaping optical communication systems, leading to system failure.
Innovation Solution
An adaptive equalization method and apparatus that adjusts the equalizer coefficients based on a novel error calculation formula, incorporating a second error term representing the difference between the average value of squares of output signal moduli and target average power, to compensate for channel losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional Constant Module Algorithm (CMA) is used for adaptive equalization, then the algorithm is simple to implement, but it fails to correctly compensate for polarization crosstalk and polarization mode dispersion in high-degree probabilistic shaping systems
Solution Approach 1:
The patent modifies the error calculation parameters by introducing a new error term that accounts for average power convergence. The error signal is changed from the conventional CMA error to include both the modulus difference and the average power difference, allowing the algorithm to adapt to probabilistic shaping while maintaining computational feasibility
Solution Approach 2:
The patent implements a feedback mechanism where the error signal continuously guides the adjustment of equalizer coefficients. The updated error signal incorporates feedback about both constellation point convergence and average power convergence, enabling the system to self-correct and adapt to the probabilistic shaping distribution
2Productivity
If probabilistic shaping is applied to improve transmission capacity, then the transmission performance is improved, but conventional DSP algorithms fail and the system cannot operate
Solution Approach 1:
The patent changes the fundamental parameters of the equalization algorithm by introducing a new error metric that includes average power convergence. This parameter change allows the algorithm to work correctly with probabilistically shaped signals while maintaining system operability
Solution Approach 2:
The patent makes the equalization algorithm dynamic by continuously adapting the error signal calculation based on the statistical properties of the received signal. The algorithm dynamically adjusts to the probabilistic shaping distribution through the new error term that monitors average power convergence
3Reliability
If the error signal only considers modulus differences (conventional CMA), then the calculation is simple, but polarization crosstalk and mode dispersion cannot be correctly compensated
Solution Approach 1:
The patent segments the error calculation into two distinct components: the first error term handles constellation point convergence (modulus differences), while the second error term handles average power convergence. This segmentation allows each component to address specific aspects of the compensation problem
Solution Approach 2:
The patent merges the two error terms (modulus difference and average power difference) into a unified error signal that guides the equalizer. This combination allows the algorithm to simultaneously address both constellation convergence and power normalization, achieving comprehensive compensation
Data Source
AI summary
The present application discloses an adaptive equalization method and apparatus for a probabilistic shaping system, and a readable storage medium. The adaptive equalization method may include: determining a tap length of a filter, and setting an initial coefficient of an equalizer; performing butterfly filtering on two polarized input signals according to the coefficient of the equalizer to obtain two polarized output signals; determining an error signal according to the two polarized output signals, wherein the error signal is a sum of a first error which is a minimum value of differences between a target convergence radius and squares of modulus of the output signals, and a second error which is a difference between an average value of squares of modulus of a plurality of output signals and a target average power; and adjusting the coefficient of the equalizer according to the error signal.