-
- News
- Books
Featured Books
- design007 Magazine
Latest Issues
Current IssueDesigning Through the Noise
Our experts discuss the constantly evolving world of RF design, including the many tradeoffs, material considerations, and design tips and techniques that designers and design engineers need to know to succeed in this high-frequency realm.
Learning to Speak ‘Fab’
Our expert contributors clear up many of the miscommunication problems between PCB designers and their fab and assembly stakeholders. As you will see, a little extra planning early in the design cycle can go a long way toward maintaining open lines of communication with the fab and assembly folks.
Training New Designers
Where will we find the next generation of PCB designers and design engineers? Once we locate them, how will we train and educate them? What will PCB designers of the future need to master to deal with tomorrow’s technology?
- Articles
- Columns
Search Console
- Links
- Media kit
||| MENU - design007 Magazine
The Impact of PCB Dielectric Thickness on Signal Crosstalk
August 27, 2018 | Chang Fei Yee, Keysight TechnologiesEstimated reading time: Less than a minute

This article studies the impact of dielectric thickness on crosstalk for transmission lines in single-ended and differential mode on outer (microstrip) and inner (stripline) PCB layers. Crosstalk analysis is performed in 2D simulation and S-parameters are subsequently observed.
Introduction to Crosstalk
Crosstalk is an unintentional electromagnetic (EM) field coupling between transmission lines on a PCB. This phenomenon becomes a major culprit in signal integrity (SI), contributing to the rise of bit error occurrence in data communications and electromagnetic interference (EMI). With the existence of mutual inductance and capacitance between two adjacent transmission lines on a PCB, crosstalk has become more severe due to the shorter signal rise/fall times at today’s higher data speed rates.
Crosstalk can be minimized by routing the PCB traces further apart and reducing the dielectric thickness between PCB trace and reference plane. We will observe how a PCB’s dielectric thickness affects the signal crosstalk. All crosstalk analyses are carried out in 2D simulation using Mentor’s HyperLynx.
To read this entire article, which appeared in the August 2018 issue of Design007 Magazine, click here.
Suggested Items
IT Distribution Records Strong Revenue Growth in Q1 Fueled by Personal Computing Purchases Amidst Tariff Uncertainty
05/02/2025 | IDCSales through distribution in North America posted a second consecutive quarter of growth in the first quarter of 2025. Distributor Revenues came in at $19.9B which is a 7.6% increase year-over-year, according to the International Data Corporation (IDC) North America Distribution Track e r (NADT).
INEMI Smart Manufacturing Tech Topic Series: Enhancing Yield and Quality with Explainable AI
05/02/2025 | iNEMIIn semiconductor manufacturing, the ability to analyze vast amounts of high-dimensional data is critical for ensuring product quality and optimizing wafer yield.
Nolan's Notes: The Next Killer App in Component Manufacturing
05/02/2025 | Nolan Johnson -- Column: Nolan's NotesFor quite a while, I’ve been wondering what the next “killer app” will be in electronics manufacturing and why it has been so long since the last disruptive change in EMS. I believe the answer lies in artificial intelligence, which has exploded as the next disruptor.
Keysight EDA, Intel Foundry Collaborate on EMIB-T Silicon Bridge Technology for Next-Generation AI and Data Center Solutions
04/30/2025 | BUSINESS WIREKeysight Technologies, Inc. announced a collaboration with Intel Foundry to support Embedded Multi-die Interconnect Bridge-T (EMIB-T) technology, a cutting-edge innovation aimed at improving high-performance packaging solutions for artificial intelligence (AI) and data center markets in addition to the support of Intel 18A process node.
Machine Vision: MVTec Expands Deep Learning Portfolio with New Versions of its Deep Learning Tool
04/29/2025 | MVTec Software GmbHThe machine vision industry is gaining significant momentum by using deep learning, a subset of artificial intelligence, which allows for the automation of entirely new applications and improved results.