Jitter histogram approximation

#The present invention relates to jitter measurements for digital data communication testing.

#Characterizing the transient behavior of high-speed digital circuits, i.e. the transition from a logical zero to a logical one and vice versa, has become increasingly important for designing as well as manufacturing such digital circuits. Timing problems can cause single transmission errors, or temporary or even permanent outage of an entire communication system, and have to be avoided. The standard overall figure of merit for a communications system is the Bit Error Rate (BER), however a high value of BER does not necessarily indicate timing problems, as there are many other potential sources of error in a system (for example level/threshold mismatch).

#One of the key specifications of high-speed circuits with respect to timing is Jitter. ITU-T G.701 defines jitter as short-term non-cumulative variations of the significant instants of a digital signal from their ideal positions in time. The significant instant can be any convenient, easily identifiable point on the signal such as the rising or falling edge of a pulse or the sampling instant. By plotting the relative displacement in the instants between an ideal pulse train and a real pulse train that has some timing jitter, the so-called jitter function is obtained. In addition to the jitter time function, the jitter spectrum can be displayed in the frequency domain.

#Other objects and many of the attendant advantages of the present invention will be readily appreciated and become better understood by reference to the following detailed description when considering in connection with the accompanied drawings. Features that are substantially or functionally equal or similar will be referred to with the same reference sign(s).

#FIG. 1 shows the right half of a bathtub curve for a Test Pattern Measurement;

#FIG. 2 shows the corresponding jitter histogram for the Test Pattern Measurement;

#In a preferred embodiment for obtaining a jitter value (substantially representing the data-dependent or deterministic jitter amount) of a digital data signal to be measured, the following steps are executed using e.g. the aforementioned Agilent® 81250 ParBERT®:

#1) A bathtub curve is determined for the digital data signal (e.g. a real-life signal or a test pattern such as a PRBS). Since both halves of the bathtub curve contain substantially the same jitter information, only the right side is considered (FIG. 1, with the x-axis denoting the delay time in unit intervals ui, and the y-axis denoting BER values). FIG. 2 shows the jitter histogram (in linear scale) derived from FIG. 1.

#2) FIG. 3 shows an example of a multi-kernel Gaussian distribution fit for the histogram data of FIG. 2: 1 Kernel# Mean Std. Dev. Relative Weight 1 0.41 ui 0.0123 ui 0.4 2 0.45 ui 0.0121 ui 0.3 3 0.5 ui 0.0124 ui 0.5 4 0.54 ui 0.0123 ui 0.4 5 0.58 ui 0.0122 ui 0.2