On Information Coupling in Cooperative Network Synchronization

Wireless networks are growing in the value of application in many areas, in which accurate clock synchronization is required when tasks are performed in a collaborative fashion among nodes. Especially, cooperative synchronization techniques lead to significant performance improvement compared with traditional methods. However, the correlation among agents renders the performance analysis of cooperative network synchronization difficult. In this paper, we introduce the concept of information coupling intensity to the analysis of interaction between agents. Our approach enables us to derive closed-form asymptotic expressions under specific network topologies, and relate them to various network parameters.

[1]  Hyundong Shin,et al.  Machine Learning for Wideband Localization , 2015, IEEE Journal on Selected Areas in Communications.

[2]  Moe Z. Win,et al.  Cooperative Network Synchronization: Asymptotic Analysis , 2017, IEEE Transactions on Signal Processing.

[3]  Gianluca Cena,et al.  Implementation and Evaluation of the Reference Broadcast Infrastructure Synchronization Protocol , 2015, IEEE Transactions on Industrial Informatics.

[4]  Nan Wu,et al.  Cooperative Detection-Assisted Localization in Wireless Networks in the Presence of Ranging Outliers , 2017, IEEE Transactions on Communications.

[5]  Yik-Chung Wu,et al.  Distributed Clock Synchronization for Wireless Sensor Networks Using Belief Propagation , 2011, IEEE Transactions on Signal Processing.

[6]  Yik-Chung Wu,et al.  Ieee Transactions on Wireless Communications, Accepted for Publication 1 Distributed Clock Parameters Tracking in Wireless Sensor Network , 2022 .

[7]  L. Seno,et al.  Industrial Wireless Networks: The Significance of Timeliness in Communication Systems , 2013, IEEE Industrial Electronics Magazine.

[8]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[9]  Nan Wu,et al.  On the Performance Limits of Cooperative Localization in Wireless Sensor Networks With Strong Sensor Position Uncertainty , 2017, IEEE Communications Letters.

[10]  Moe Z. Win,et al.  Energy-Efficient Network Navigation Algorithms , 2015, IEEE Journal on Selected Areas in Communications.

[11]  Yik-Chung Wu,et al.  Distributed Clock Skew and Offset Estimation in Wireless Sensor Networks: Asynchronous Algorithm and Convergence Analysis , 2013, IEEE Transactions on Wireless Communications.

[12]  D. McDonald,et al.  An elementary proof of the local central limit theorem , 1995 .

[13]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[14]  John E. Mitchell,et al.  Networking and application interface technology for wireless sensor network surveillance and monitoring , 2011, IEEE Commun. Mag..

[15]  Moe Z. Win,et al.  Power Optimization for Network Localization , 2013, IEEE/ACM Transactions on Networking.

[16]  Hua Wang,et al.  Cooperative Joint Localization and Clock Synchronization Based on Gaussian Message Passing in Asynchronous Wireless Networks , 2016, IEEE Transactions on Vehicular Technology.

[17]  Henk Wymeersch,et al.  Cooperative Synchronization in Wireless Networks , 2013, IEEE Transactions on Signal Processing.

[18]  Raghuraman Mudumbai,et al.  Fundamental limits on phase and frequency tracking and estimation in drifting oscillators , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[19]  Moe Z. Win,et al.  Distributed Power Allocation for Cooperative Wireless Network Localization , 2015, IEEE Journal on Selected Areas in Communications.

[20]  Moe Z. Win,et al.  Network Navigation With Scheduling: Error Evolution , 2017, IEEE Transactions on Information Theory.

[21]  B. C. Ng,et al.  On the Cramer-Rao bound under parametric constraints , 1998, IEEE Signal Processing Letters.