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Kalman prediction based neighbor discovery and its effect on routing protocol in vehicular ad hoc networks

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Liu, Chunfeng, Zheng, Gan, Guo, Weisi and He, Ran (2020) Kalman prediction based neighbor discovery and its effect on routing protocol in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 21 (1). pp. 159-169. doi:10.1109/TITS.2018.2889923

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Official URL: https://doi.org/10.1109/TITS.2018.2889923

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Abstract

Efficient neighbor discovery in vehicular ad hoc networks is crucial to a number of applications such as driving safety and data transmission. The main challenge is the high mobility of vehicles. In this paper, we proposed a new algorithm for quickly discovering neighbor node in such a dynamic environment. The proposed rapid discovery algorithm is based on a novel mobility prediction model using Kalman filter theory, where each vehicular node has a prediction model to predict its own and its neighbors’ mobility. This is achieved by considering the nodes’ temporal and spatial movement features. The prediction algorithm is reinforced with threshold triggered location broadcast messages, which will update the prediction model parameters, and improve the efficiency of neighbor discovery algorithm. Through extensive simulations, the accuracy, robustness, and efficiency properties of our proposed algorithm are demonstrated. Compared with other methods of neighbor discovery frequently used in HP-AODV, ARH and ROMSG, the proposed algorithm needs the least overheads and can reach the lowest neighbor error rate while improving the accuracy rate of neighbor discovery. In general, the comparative analysis of different neighbor discovery methods in routing protocol is obtained, which shows that the proposed solution performs better than HP-AODV, ARH and ROMSG.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH): Kalman filtering -- Industrial applications, Mobile communication systems, Algorithms
Journal or Publication Title: IEEE Transactions on Intelligent Transportation Systems
Publisher: IEEE
ISSN: 1524-9050
Official Date: January 2020
Dates:
DateEvent
January 2020Published
25 January 2019Available
13 December 2018Accepted
Volume: 21
Number: 1
Page Range: pp. 159-169
DOI: 10.1109/TITS.2018.2889923
Status: Peer Reviewed
Publication Status: Published
Publisher Statement: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
61871286[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
61672131 [NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
U1701263[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
U1701263Natural Science Foundation of Guangdong Provincehttp://dx.doi.org/10.13039/501100003453
2018-30Tianjin Universityhttp://dx.doi.org/10.13039/501100004517
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