Method and Device for Predicting a Figure of Merit From a Distribution

A method for predicting a bit error rate (BER) from a jitter distribution, the method comprising:

• applying a Q-normalization scaled with a scaling factor k to the jitter distribution to linearize tail parts of the normalized jitter distribution to approximate Gaussian tail parts;
• and
• determining the BER based on the approximated Gaussian tail parts of the normalized jitter distribution.

A method for extracting deterministic and random components from a distribution, the method comprising:

• normalizing the distribution using a normalization function scaled with a scaling factor k to transform tail parts of the distribution to straight lines approximating tail parts of a Gaussian distribution (Gaussian tail parts);
• and
• calculating the deterministic and random components of the distribution using model parameters of the approximated Gaussian tail parts.

A device for extracting deterministic and random components from a probability distribution, the device comprising:

• means for normalizing the probability distribution using a scalable normalization function to transform tail parts of the normalized probability distribution to approximate tail parts of a predetermined probability distribution;
• and
• means for calculating the deterministic and random components of the probability distribution using model parameters obtained from the approximated tail parts of the predetermined probability distribution.

A device for predicting a bit error rate (BER) of interest from a measured jitter distribution, the device comprising:

• a Q-normalization unit adapted to scalably normalize the measured jitter distribution with a scaling factor k to approximate linearized tail parts of the normalized measured jitter distribution;
• and
• a prediction unit to determine the BER of interest based on the linearized tail parts.

A device for extracting deterministic jitter (DJ) and random jitter (RJ) components from a jitter distribution, the device adapted to:

• normalize the jitter distribution in the form of a cumulative density function (CDF) using a Q-function scaled with a scaling factor k to transform tail parts of the jitter distribution to straight lines approximating Gaussian tail parts;
• and
• calculate the deterministic jitter (DJ) and random jitter (RJ) components of the jitter distribution using model parameters of the approximated Gaussian tail parts.

A device for predicting a figure of merit from a distribution, the device adapted to scalably normalize the distribution to approximate a predetermined part of the normalized distribution to determine the figure of merit based on the approximated predetermined part of the normalized distribution.