MTIE and TDEV Analysis of Unevenly Spaced Time Series Data

Abstract

This work investigates how uneven data spacing affects the computations of MTIE (maximum time interval error) and TDEV (time deviation). MTIE and TDEV are evaluated with unevenly spaced data in five different power-law noise types.Each simulated data set has 3600 evenly spaced data points spaced one second apart.Dat a points are then removed from each file according to the parameter p. Each data point in a file is removed with probability p and retained with probability (1 – p). For the unevenly spaced data files, the average spacing is recomputed.Then MTIE and TDEV were calculated for data files with different p values.The simulated results show that the difference among the performance of various p values is not significant when the observation time exceeds 100 seconds. Additionally, the discrepancy between the computation results of evenly (p = 0) and slightly unevenly (0>p>0.1) spaced data files is often negligible.Therefore, the effect of slightly unevenly spaced data on computations of MTIE and TDEV can be ignored.Based on these results, the telecommunications synchronization measurement can be performed using a simple model, which does not require a clock recovery device to recover the timing signal from the data bits.Instead, the network data signal can be input directly to the time interval counter (TIC).The measured data are often unevenly spaced as the data bits of “1” and “0” are not distributed regularly. However, this novel measurement model can still be validated using previous results.