A Specification-Aware Optimization Framework for Continuous-Time Linear Equalizers in High-Speed SerDes Systems

Abstract—This paper presents a designer-driven optimization framework for Continuous-Time Linear Equalizers (CTLEs) used in high-speed SerDes systems. The proposed Python-based model integrates parameter sweeping, transfer function analysis, and curve fitting to align circuit behavior with specification targets. By automating the sizing process while preserving transparency and control, the framework accelerates schematic-level design and supports multi-standard compatibility. Additionally, the model incorporates AI-assisted hierarchical modeling and hybrid optimization strategies, enabling rapid generation of surrogate models and reducing simulation overhead. Simulation results demonstrate strong correlation with HSPICE outcomes, validating the model’s effectiveness for early-stage analog design.