MTIE and TDEV Analysis of Unevenly Spaced Time Series Data and its Application to Telecommunications Synchronization Measurements

摘要

In this work, we investigated the effect of uneven data spacing on the computations of MTIE and TDEV. We evaluated MTIE and TDEV with unevenly spaced data having the five different power-law noise types. Each simulated data set had 3600 evenly spaced data points spaced one second apart. In the next step, we removed data points for each file according to the parameter p. Each data point in a file was removed with probability p and not removed with probability (1-p). And for the unevenly spaced data files, the average spacing was recomputed. Then we computed MTIE and TDEV for these data files with different p values. The results show that the difference among the performance of various p values is not significant when the observation time tau is larger than 100 seconds. In addition, the discrepancy between the computation results of evenly and slightly unevenly (p is small) spaced data files can be negligible. It reveals that we can ignore the effect of slightly unevenly spaced data on the computations of MTIE and TDEV. Based on the results, one can employ a simple model to conduct the network synchronization measurement. In other words, in the telecommunications synchronization measurement, a clock recovery device that recovers the timing signal from the data bits is no longer required. We can input the network data signal to the time interval counter (TIC) directly. The measured data are often not evenly spaced, since the data bits of '1' and '0' are not distributed regularly. But based on the previous results, this novel measurement model can still be validated.