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Maximized Effective Transmission Rate Model for Advanced Neighbor Discovery Process in Bluetooth Low Energy 5.0
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Publication Year
2022-09-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Internet of Things Journal, Vol.9, pp.16272-16283
Keyword
Advanced neighbor discovery process (A-NDP)BLE specification 50bluetooth low energy (BLE)device to device communicationperformance model
Mesh Keyword
Advanced neighbor discovery processBluetooth low energyBluetooth low energy specification 5.0Device to device communication.Device-to-Device communicationsEffective transmission rateLower energiesNeighbor discoveryPerformance Modeling
All Science Classification Codes (ASJC)
Signal ProcessingInformation SystemsHardware and ArchitectureComputer Science ApplicationsComputer Networks and Communications
Abstract
Bluetooth low-energy (BLE) technology is one of the most promising communication technologies applicable to a variety of Internet of Things (IoT) services. The neighbor discovery process (NDP) plays a key role in BLE-enabled IoT services. The basic NDP (B-NDP) specified in BLE specification 4.0 has a limitation in supporting large numbers of BLE devices, owing to its use of three channels. To overcome the limitation of B-NDP, advanced NDP (A-NDP) has been recently introduced in BLE specification 5.0. However, most existing studies have focused on B-NDP, with very few studies having been conducted on A-NDP. In this article, we propose a model for analyzing the effective transmission rate for a BLE advertiser with an A-NDP operation. Using the proposed model, we also propose a performance model to maximize the transmission rate by optimally setting the BLE parameters. The proposed models are validated by comparing with extensive simulation results. It also demonstrates that the maximum transmission rate by the proposed models can be achieved with low energy consumption.
ISSN
2327-4662
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/32560
DOI
https://doi.org/10.1109/jiot.2022.3152513
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SHAN GAOYANGSHAN, GAOYANG
Department of Software and Computer Engineering
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