Frontiers in Physics (Mar 2022)
Two Novel One-Way Delay Clock Skew Estimators and Their Performances for the Fractional Gaussian Noise/Generalized Fractional Gaussian Noise Environment Applicable for the IEEE 1588v2 (PTP) Case
Abstract
Papers in the literature dealing with the Ethernet network characterize packet delay variation (PDV) as a long-range dependence (LRD) process. The fractional Gaussian noise (fGn) or the generalized fractional Gaussian noise (gfGn) belong to the LRD process. The IEEE1588v2 is a two-way delay (TWD) protocol that uses the messages from the Forward (Master to Slave) and the Reverse (Slave to Master) paths. Suppose we have a significant difference between the PDV variances of the Forward and the Reverse paths. Thus, if we can use only the path with the lowest PDV variance (namely, only the one-way delay (OWD) technique), we might get a better clock skew performance from the mean square error (MSE) point of view compared with the traditional TWD method. This paper proposes two OWD clock skew estimators, one for the Forward path and one for the Reverse path applicable for the white-Gaussian, fGn and gfGn environment. Those OWD estimators do not depend on the unknown asymmetry between the fixed delays in the Forward and Reverse paths and nor on the clock offset between the Master and Slave. We also supply two closed-form approximated expressions for the MSE related to our new proposed OWD clock skew estimators. In addition, we supply some conditions, summarized in a table, guiding us whether we should use the OWD clock skew estimator for the Forward path or for the Reverse path, or just use the TWD algorithm. Simulation results confirm that our new proposed OWD clock skew estimators achieve better clock skew performances from the MSE point of view, compared with the TWD clock skew estimator recently proposed by the same authors and compared with two literature known OWD methods (the maximum likelihood and Kalman clock skew estimators).
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