Optimization and design of a diffuse optical wireless sensor network

Thomas Kamalakis; Zabih Ghassemlooy; Stanislav Zvanovec; Luis Nero Alves; Mohammad Khalighi

doi:10.1364/AO.463330

Applied Optics
Vol. 61,
Issue 22,
pp. 6599-6608
(2022)
•https://doi.org/10.1364/AO.463330

Optimization and design of a diffuse optical wireless sensor network

Thomas Kamalakis, Zabih Ghassemlooy, Stanislav Zvanovec, Luis Nero Alves, and Mohammad Khalighi

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Thomas Kamalakis, Zabih Ghassemlooy, Stanislav Zvanovec, Luis Nero Alves, and Mohammad Khalighi, "Optimization and design of a diffuse optical wireless sensor network," Appl. Opt. 61, 6599-6608 (2022)

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Related Topics
Table of Contents Category
- Fiber Optics, Fiber Sensors, and Optical Communications
Optics & Photonics Topics
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The topics in this list come from the Optics and Photonics Topics applied to this article.

About this Article
History
- Original Manuscript: May 10, 2022
- Revised Manuscript: June 30, 2022
- Manuscript Accepted: July 1, 2022
- Published: July 25, 2022

Abstract

Wireless sensor networks (WSNs) are currently being deployed in everyday objects to collect and transmit information related to humidity, temperature, heartbeat, motion, etc. Such networks are part of the massive machine-type communication (mMTC) scenario within the fifth/sixth generation of wireless networks. In this paper, we consider the optimization and design of an optical WSN composed of multiple battery-powered sensor nodes based on light-emitting diode transmitters. Extending our previous work, we take into account both line-of-sight and diffuse-light propagation, and show that in indoor scenarios, diffuse radiation can improve link availability under shadowing/blocking and extend battery life. In order to optimize the optical wireless link parameters, we use a machine-learning approach based on a genetic algorithm to ascertain the performance limits of the system. The presented results indicate that the proposed system is a viable wireless option for WSNs within the context of mMTC.

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No data were generated or analyzed in the presented research.

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Parameter	Config. A	Config. B
Length, $L$	5 m	10 m
Width, $W$	5 m	10 m
Height, $H$	3 m	4 m
Window height, $H_{w}$	1 m	2 m
Window width, $W_{w}$	1 m	2 m
Peak spectral irradiance, $p_{n}$	$2 W / n m / m^{2}$
Ambient light temperature, $T_{K}$	5800 K
Wall reflectivity, $ρ_{w}$	0.8
Ceiling reflectivity, $ρ_{c}$	0.8
Floor reflectivity, $ρ_{f}$	0.3
MN FOV, ${F O V}_{M N}$	$π / 2$
SN FOV, ${F O V}_{S N}$	$π / 2$
MN orientation, $n_{M N}$	$\hat{z}$
SN orientation, $n_{S N}$	$- \hat{z}$
MN transmission power, $P_{M N}$	6 W
Maximum SN transmission power, $P_{S N}$	25 mW
IR LED half-intensity angle, $Φ_{1 / 2}$	$60^{\circ}$
IR LED pattern order, $m$	$1$
IR LED driver curve	TSFF5210 [23]
Max SN driver current, $I_{max}$	100 mA
Responsivity model	BPV10NF [23]
VLC rejection filter model	VTB5051BH [23]
IR rejection filter model	BPV10NF [23]
Maximum data rate, $R_{max}$	10 kb/s
Target error rate, ${B E R}_{0}$	$10^{- 3}$
Spectral efficiency, $η_{e f f}$	0.4 bit/s/Hz
Uplink message length, $L_{u}$	$200 b i t s$
Downlink message length, $L_{d}$	$200 b i t s$
Feedback resistance, $R_{F}$	$1 M Ω$
Modulation type	OOK
RMS voltage noise density, $V_{r m s}$	$15 n V / \sqrt{H z}$
RMS current noise density, $V_{r m s}$	$400 f A / \sqrt{H z}$
Voltage noise corner frequency, $f_{c v}$	$1 k H z$
Current noise corner frequency, $f_{c i}$	$1 k H z$
Sleep mode current, $I_{S L}$	400 nA
Wake-up current, $I_{W U}$	1.3 mA
Read-out current, $I_{R O}$	1.3 mA
Wake-up time, $t_{W U}$	20 ms
Read-out time, $t_{R O}$	40 ms
Cycle period, $t_{C Y}$	1 min
Battery capacity, $Q_{T O T}$	220 mAh

Thomas Kamalakis	https://orcid.org/0000-0002-4288-1438
Zabih Ghassemlooy	https://orcid.org/0000-0002-5780-9703
Stanislav Zvanovec	https://orcid.org/0000-0002-7902-2143
Mohammad Khalighi	https://orcid.org/0000-0002-0522-6688

Abstract

Data availability

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Equations (10)

Applied Optics