Please use this identifier to cite or link to this item:
Title: Maximum-Likelihood Estimator of Clock Offset between Nanomachines in Bionanosensor Networks
Authors: Lin, Lin
Yang, Chengfeng
Ma, Maode
Keywords: Bionanosensor networks
Molecular communication
Clock synchronization
Issue Date: 2015
Source: Lin, L., Yang, C., & Ma, M. (2015). Maximum-Likelihood Estimator of Clock Offset between Nanomachines in Bionanosensor Networks. Sensors, 15(12), 30827-30838.
Series/Report no.: Sensors
Abstract: Recent advances in nanotechnology, electronic technology and biology have enabled the development of bio-inspired nanoscale sensors. The cooperation among the bionanosensors in a network is envisioned to perform complex tasks. Clock synchronization is essential to establish diffusion-based distributed cooperation in the bionanosensor networks. This paper proposes a maximum-likelihood estimator of the clock offset for the clock synchronization among molecular bionanosensors. The unique properties of diffusion-based molecular communication are described. Based on the inverse Gaussian distribution of the molecular propagation delay, a two-way message exchange mechanism for clock synchronization is proposed. The maximum-likelihood estimator of the clock offset is derived. The convergence and the bias of the estimator are analyzed. The simulation results show that the proposed estimator is effective for the offset compensation required for clock synchronization. This work paves the way for the cooperation of nanomachines in diffusion-based bionanosensor networks.
ISSN: 1424-8220
DOI: 10.3390/s151229830
Schools: School of Electrical and Electronic Engineering 
Rights: © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Citations 50

Updated on Apr 10, 2024

Web of ScienceTM
Citations 20

Updated on Oct 24, 2023

Page view(s) 50

Updated on Apr 18, 2024

Download(s) 50

Updated on Apr 18, 2024

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.