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Erschienen in: Wireless Networks 3/2021

01.03.2021

Performance metric analysis of transmission range in the ZigBee network using various soft computing techniques and the hardware implementation of ZigBee network on ARM-based controller

verfasst von: Prativa P. Saraswala, Sagarkumar B. Patel, Jaymin K. Bhalani

Erschienen in: Wireless Networks | Ausgabe 3/2021

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Abstract

ZigBee is one of the latest technologies developed by the ZigBee Alliance to enable Wireless Personal Area works. ZigBee technology has better characteristics when compared with other wireless standards such as WI-FI, Bluetooth and WiMAX, and so on. Though the transmission range in ZigBee ranges up to a few meters, the network has several layers, designed to enable interpersonal communication within the network, appropriate routing technique can lead the data to be reached to a longer distance, leading to an increase in the transmission range. Present research emphases on the maximization of the transmission range in the ZigBee network. For the analysis, the Simulink based software called TRUETIME 2.0 in MATLAB tool is used. Energy Efficient ZigBee based AODV routing protocol with incorporated CSMA-CA MAC channel access (EE-ZAODVCSMA) is proposed for maximizing the transmission range in the ZigBee network. To maximize the transmission range, various soft computing techniques such as Fuzzy Logic, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System, and one more technique which is an integration of ANN and Genetic Algorithm are applied to the network. A small ZigBee network is implemented with four nodes on LPC 2148 to show the data communication based on the proposed algorithm.

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Metadaten
Titel
Performance metric analysis of transmission range in the ZigBee network using various soft computing techniques and the hardware implementation of ZigBee network on ARM-based controller
verfasst von
Prativa P. Saraswala
Sagarkumar B. Patel
Jaymin K. Bhalani
Publikationsdatum
01.03.2021
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 3/2021
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-021-02568-4

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