Statistical Prediction of “Reasonable Worst-Case” Crosstalk in Cable Bundles

Abstract

Worst-case estimates of crosstalk in cable bundles are useful for flagging potential problems, but may also flag problems that only occur very rarely, due to the random variation of wire positions and other characteristics of the harness. Prediction of crosstalk that may realistically occur requires statistical methods. Monte Carlo simulation techniques are often used to account for statistical variation, but are time consuming and do not provide intuition toward the cause of, or solution to, problems. Here, we investigate prediction of the statistically ldquoreasonable worst-caserdquo crosstalk by forming probability distributions using inductance and capacitance parameters from a single harness cross section and using lumped-element approximations for crosstalk that account for strong coupling within the harness when the circuit is electrically small. The accuracy of this technique was evaluated through comparison to simulation results using the random displacement spline interpolation method for multiple random instantiations of several harness configurations. Tests were performed while varying the size of the bundle, its height above the return plane, the value of load impedances, and the presence of a return wire. The reasonable worst-case crosstalk was estimated within about 5 dB or less in each case.