Characterizing Nonlinearities in IM-DD Links via the Best Linear Approximation: Distortion Analysis and Modulation Optimization

2026-08-12

AI Summary

This work addresses the challenge of modeling and compensating nonlinear distortions in intensity-modulation direct-detection (IM-DD) optical links, which significantly limits system performance. By introducing the Best Linear Approximation (BLA) framework, the study reveals—for the first time—that the orthogonal component of the nonlinear distortion exhibits non-Gaussian statistical characteristics. Leveraging this insight, the authors develop an optimization strategy for modulation depth tailored to various equalizer architectures based on BLA analysis. This approach effectively characterizes the nonlinear impairments and enables near-optimal modulation depth selection across different equalizers, thereby substantially enhancing overall system performance.

Abstract

We use the best linear approximation (BLA) to characterize nonlinearities in IM-DD links. The orthogonal nonlinear distortion is shown to be non-Gaussian. The BLA is used to approximate the optimum modulation depth for different equalizer structures.

Problem

• nonlinearities
• IM-DD links
• distortion analysis
• modulation optimization
• best linear approximation

Innovation

• Best Linear Approximation
• Nonlinear Distortion
• IM-DD
• Modulation Optimization
• Non-Gaussian