Title :
A novel jitter separation method based on Gaussian mixture model
Author :
Mistry, Deepak ; Joshi, Sunil ; Agrawal, Navneet
Author_Institution :
Dept. of ECE, MPUAT, Udaipur, India
Abstract :
Jitter is random variations in bit period of a digital signal. It may be regarded as single most limiting factor in high speed digital links. Separating jitter into its components and identifying their root causes help in improving phase locked loop design. Proposed methodology for separating and estimating total jitter is based on Gaussian mixture model (GMM). Expectation-maximization (EM) algorithm is used to find the maximum likelihood estimation of GMM parameter. The total jitter time series data is directly fit using the EM algorithm. The method eliminates problem of careful initial value selection for EM algorithm and automatically find the unknown number of mixing kernels using Bayesian information criterion (BIC). After finding the fitting parameter dual-Dirac Model can be used to calculate total jitter at the bit error rate (BER) level of interest.
Keywords :
Bayes methods; Gaussian processes; error statistics; expectation-maximisation algorithm; jitter; mixture models; phase locked loops; source separation; time series; Bayesian information criterion; EM algorithm; GMM parameter; Gaussian mixture model; bit error rate level; digital signal; expectation-maximization algorithm; fitting parameter dual-Dirac model; high speed digital links; jitter separation method; limiting factor; maximum likelihood estimation; mixing kernels; phase locked loop design; total jitter estimation; total jitter separation; total jitter time series data; Bit error rate; Fitting; Gaussian mixture model; Jitter; Maximum likelihood estimation; Simulation; Bayesian information criterion; Gaussian mixture model; bit error rate; dual-Dirac model; timing jitter;
Conference_Titel :
Pervasive Computing (ICPC), 2015 International Conference on
Conference_Location :
Pune
DOI :
10.1109/PERVASIVE.2015.7087091
