학술논문

Novel Optimization Methodology of Design Parameters in High-Speed Differential Via for PCIe Gen5 Channels Based on Particle Swarm Optimization Algorithm
Document Type
Periodical
Source
IEEE Transactions on Components, Packaging and Manufacturing Technology IEEE Trans. Compon., Packag. Manufact. Technol. Components, Packaging and Manufacturing Technology, IEEE Transactions on. 13(10):1545-1552 Oct, 2023
Subject
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Impedance
Optimization
Mathematical models
Scattering parameters
Three-dimensional displays
Estimation
Power transmission lines
Algorithm
channels
design parameters
differential via
high speed
optimization
particle swarm optimization (PSO)
peripheral component interconnect express (PCIe)
printed circuit board (PCB)
signal integrity
time-domain reflectometry (TDR)
Language
ISSN
2156-3950
2156-3985
Abstract
In high-speed serializer/deserializer (SerDes) channels, reducing impedance mismatches at the differential via is crucial to minimize signal reflection. However, due to the complex 3-D structure of the differential via, obtaining optimal design parameters for impedance matching can be a time-consuming process. This article introduces an equation-based time-domain reflectometry (TDR) estimation model for the differential via, which is validated by comparing it with a commercial model of the coupled transmission line. In addition, this article proposes a method to optimize the design parameters of the differential via using a figure of merit (FOM) based on TDR impedance in a particle swarm optimization (PSO) algorithm. The optimization procedure is applied to an actual printed circuit board (PCB) design, and the simulation results, including TDR, ${S}$ -parameters, and bit error rate (BER) at 1E −12 contours, validate the optimization performance. To further verify the optimization performance in a realistic scenario, test coupons are fabricated, and the TDR impedance is measured, demonstrating excellent performance in real-world conditions.