Name
Title | ||
|---|---|---|
Robust Clock Synchronization in Wireless Sensor Networks Through Noise Density Estimation |
Abstract | ||
|---|---|---|
Assuming that the network delays are normally distributed and the network nodes are subject to clock phase offset errors, the maximum likelihood estimator (MLE) and the Kalman filter (KF) have been recently proposed with the goal of maximizing the clock synchronization accuracy in wireless sensor networks (WSNs). However, because the network delays may assume any distribution and the performance of MLE and KF is quite sensitive to the distribution of network delays, designing clock synchronization algorithms that are robust to arbitrary network delay distributions appears as an important problem. Adopting a Bayesian framework, this paper proposes a novel clock synchronization algorithm, called the Iterative Gaussian mixture Kalman particle filter (IGMKPF), which combines the Gaussian mixture Kalman particle filter (GMKPF) with an iterative noise density estimation procedure to achieve robust performance in the presence of unknown network delay distributions. The Kullback-Leibler divergence is used as a measure to assess the departure of estimated observation noise density from its true expression. The posterior Cramér-Rao bound (PCRB) and the mean-square error (MSE) of IGMKPF are evaluated via computer simulations. It is shown that IGMKPF exhibits improved performance and robustness relative to MLE. The prior information plays an important role in IGMKPF. A MLE-based method for obtaining reliable prior information for clock phase offsets is presented and shown to ensure the convergence of IGMKPF. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TSP.2011.2141660 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
clock phase,wsn,kf,noise density estimation,cramér–rao bound,particle filtering (numerical methods),kalman filters,maximum likelihood estimator,kullback-leibler divergence,wireless sensor networks (wsns),bayes methods,unknown network delay distribution,maximum likelihood estimation,wireless sensor network,mean-square error method,network delay,clock phase offset error,pcrb,network node,posterior cramer-rao bound,particle filter,robust clock synchronization,iterative gaussian mixture kalman particle filter,filter,clock phase offset,mse,network delay distribution,gaussian processes,clock synchronization algorithm,novel clock synchronization algorithm,wireless sensor networks,computer simulation,clock synchronization accuracy,kalman,bayesian framework,arbitrary network delay distribution,synchronisation,mean square error methods,iterative noise density estimation,igmkpf,mle,clock synchronization,mathematical model,normal distribution,mean square error,kalman filter,cramer rao bound,kullback leibler divergence,noise,estimation,synchronization,maximum likelihood estimate,density estimation | Wireless network,Synchronization,Network delay,Noise measurement,Control theory,Kalman filter,Robustness (computer science),Clock synchronization,Noise spectral density,Mathematics | Journal |
Volume | Issue | ISSN |
59 | 7 | 1053-587X |
Citations | PageRank | References |
11 | 0.59 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jang-Sub Kim | 1 | 133 | 13.04 |
| Jaehan Lee | 2 | 94 | 5.57 |
| E. Serpedin | 3 | 554 | 40.14 |
| K. Qaraqe | 4 | 152 | 7.01 |