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Electronics
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Visible Light Communications Technology and Its Applications
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Visible Light Communications Technology and Its Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 14215

Special Issue Editors

Prof. Dr. Jose Alberto Rabadan Borges

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Guest Editor
Institute for Technological Development and Innovation in Communications (IDeTIC), University of Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain
Interests: optical wireless communications; VLC/OCC
Special Issues, Collections and Topics in MDPI journals
Dr. Victor Guerra

E-Mail Website
Guest Editor
1. Pi Lighting Sarl, 1950 Sion, Switzerland
2. IDeTIC, Universidad de Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas, Spain
Interests: optical wireless communication; underwater wireless optical communication; optical camera communication
Special Issues, Collections and Topics in MDPI journals
Dr. Julio Francisco Rufo Torres

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Guest Editor
Departamento de Ingeniería Industrial, Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain
Interests: optical camera communication; visible light communications; spectral signature multiplexing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Visible light communication (VLC) has been presented as a promising technology for indoor and outdoor mobile networks, providing high bandwidth and unregulated spectrum use, among other interesting capabilities. Visible LEDs (white LEDs or RGB LEDs) are included not only in the new solid-state illumination systems (LED lamps) but in many COST devices, such as smartphones or laptops. These illumination devices and their ubiquity are the reason behind the development of VLC, since they are capable of transmitting data at rates which are high enough to support different services and application demands (from low/medium to high data rates). In the same way, digital camera evolution and implantation has led to the creation of optical camera communications (OCC), a new VLC subset which uses these image devices as optical receivers.

The relevance of and interest in the VLC systems are demonstrated through the several standards already published or in the process of being published on this issue in recent years, such as IEEE 802.15.7 and IEEE 802.15.13, or the ITU G.9991. Those standards deal with the different aspects and applications of VLC systems, considering MAC and physical layers for low-, medium-, and high-speed links; and capabilities such as illumination control, indoor localization or vehicle communications, among others.

The main aim of this Special Issue is to provide original and high-quality papers addressing both theoretical and practical aspects of system development in this area. It will highlight the latest research and innovative applications and provide new perspectives on future initiatives and challenges.

The topics of interest include but are not limited to:

  • Diversity/MIMO technique implementation;
  • VLP systems;
  • Underwater VLC systems;
  • Machine learning strategies for VLC/OCC;
  • Electronic circuits for modulation/demodulation;
  • Energy-efficient/energy-harvesting VLC systems;
  • Efficient driver and receiver design, noise characterization;
  • V2X/IoT/Smart city systems;
  • New applications of VLC/OCC systems

Prof. Dr. Jose A. Rabadan
Dr. Victor Guerra
Dr. Julio Rufo
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Published Papers (6 papers)

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25 pages, 10278 KiB  
Article
Testbed for Experimental Characterization of Indoor Visible Light Communication Channels
by Miqueas Fortes and Oswaldo González
Electronics 2021, 10(11), 1365; https://doi.org/10.3390/electronics10111365 - 7 Jun 2021
Cited by 5 | Viewed by 2075
Abstract
In this paper, we describe an experimental testbed designed to evaluate indoor visible light communications (VLC) in realistic scenarios. The system is based on a mockup where the location and orientation of the optical receiver can be modified with precision for a static [...] Read more.
In this paper, we describe an experimental testbed designed to evaluate indoor visible light communications (VLC) in realistic scenarios. The system is based on a mockup where the location and orientation of the optical receiver can be modified with precision for a static configuration of walls and ceiling lamp arrangements. The system utilizes a timing synchronization method, which is based on evaluating the training sequence periods used for channel response estimation, which enables robust frame synchronization. In addition, an adaptive rate orthogonal frequency-division multiplexing (OFDM) scheme is used to assess the VLC performance throughout the receiver plane emulating a real communication. The preliminary results obtained with this prototype, considering a multiple-input single-output (MISO) scenario, demonstrate that reflection on walls yields a significant increase in data rates, which can be additionally improved if appropriate orientation of the receiver is implemented. However, vertical orientation upward of the optical receiver still constitutes a simple solution but efficient enough. Moreover, a good agreement between simulation and experimental results is observed, which confirms the suitability of the mockup as an experimental testbed for practical evaluation of indoor VLC systems, where system performance for different lamp arrangements and receiver designs, including multi-user communications, can be studied. Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
►▼ Show Figures

Figure 1

Figure 1
<p>Illustration of the indoor VLC environment with LOS contribution of a single LED and its power contribution after off a wall.</p> Full article ">Figure 2
<p>Mockup design: (<b>a</b>) Mockup scheme. (<b>b</b>) View of the mockup design. (<b>c</b>) Zoom of receiver. (<b>d</b>) Zoom of emitters at ceiling.</p> Full article ">Figure 3
<p>Electronic board designs: (<b>a</b>) Receiver board. (<b>b</b>) Emitter board.</p> Full article ">Figure 4
<p>Received power and illuminance at receiver plane for room described in <a href="#electronics-10-01365-t001" class="html-table">Table 1</a>: (<b>a</b>) Power balance. (<b>b</b>) Illuminance. (<b>c</b>) Contour map of LOS component percentage in the total received power. (<b>d</b>) Contour map of illumination level.</p> Full article ">Figure 5
<p>Simulated impulse responses at three locations: (<b>a</b>) Impulse response under lamp 1 (close to a window). (<b>b</b>) Zoom of impulse response under lamp 1. (<b>c</b>) Impulse response at the center of the room. (<b>d</b>) Zoom of impulse response at the center of the room. (<b>e</b>) Impulse response under lamp 4 (close to a corner). (<b>f</b>) Zoom of impulse response under lamp 4.</p> Full article ">Figure 6
<p>Simulated temporal dispersion of the impulse responses throughout the room: (<b>a</b>) Mean delay. (<b>b</b>) Delay spread.</p> Full article ">Figure 7
<p>Received power from two lamps for different orientations of the receiver when it moves along the x-direction: (<b>a</b>) Results for a distance between lamps of 3 m. (<b>b</b>) Results for a distance between lamps of 2 m.</p> Full article ">Figure 8
<p>Received power throughout the room when the orientation method defined in Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>) is used: (<b>a</b>) Power balance. (<b>b</b>) Contour map of LOS component percentage in the total received power. (<b>c</b>) Elevation of the receiver as a function of its position. (<b>d</b>) Azimuth of the receiver as a function of its position.</p> Full article ">Figure 9
<p>Received power and illuminance at receiver plane for mockup illustrated in <a href="#electronics-10-01365-f002" class="html-fig">Figure 2</a>: (<b>a</b>) Power balance. (<b>b</b>) Illuminance. (<b>c</b>) Contour map of LOS component percentage in the total received power. (<b>d</b>) Contour map of illumination level.</p> Full article ">Figure 10
<p>Simulated impulse responses at two locations of the mockup: (<b>a</b>) Impulse response under lamp 1 (close to a window). (<b>b</b>) Zoom of impulse response under lamp 1. (<b>c</b>) Impulse response at the center of the mockup. (<b>d</b>) Zoom of impulse response at the center of the mockup.</p> Full article ">Figure 11
<p>Simulated throughput in bits per symbol (BPS) at the receiver plane of the mockup by using the adaptive OFDM algorithm described in <a href="#sec3dot2-electronics-10-01365" class="html-sec">Section 3.2</a> (with <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>=</mo> <mn>3.8</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>) for two situations: (<b>a</b>) Receiver pointing upward (<math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>6.1</mn> </mrow> </semantics></math> BPS, <math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>5.8</mn> </mrow> </semantics></math> BPS, <math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>5.1</mn> </mrow> </semantics></math> BPS). (<b>b</b>) Receiver oriented as defined by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>) (<math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>6.1</mn> </mrow> </semantics></math> BPS, <math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>5.9</mn> </mrow> </semantics></math> BPS, <math display="inline"><semantics> <mrow> <msub> <mi>th</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>5.3</mn> </mrow> </semantics></math> BPS).</p> Full article ">Figure 12
<p>Views of the manufactured mockup: (<b>a</b>) General view of the experimental testbed. (<b>b</b>) Graphical user interface developed in Python. (<b>c</b>) Zoom of optical receiver. (<b>d</b>) Zoom of emitters at ceiling.</p> Full article ">Figure 13
<p>Experimental results obtained at the center of the mockup receiver plane when the four lamps transmit the same information: (<b>a</b>) Timing metric during a transmission. (<b>b</b>) Average of measured SNR. (<b>c</b>) Symbol constellations at receiver.</p> Full article ">Figure 14
<p>Experimental results with mockup when just one lamp is used to transmit data: (<b>a</b>) Measured throughput (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>31.1</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>17.3</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math> Mbps for locations where communication was possible). (<b>b</b>) Measured mean SNR (<math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>17.3</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mi>mean</mi> </msub> <mo>=</mo> <mn>13.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mo>−</mo> <mn>0.9</mn> </mrow> </semantics></math> dB for locations where communication was possible).</p> Full article ">Figure 15
<p>Experimental results for mockup without walls when the four lamps transmit the same data: (<b>a</b>) Measured throughput (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>44.8</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>42.8</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>38.9</mn> </mrow> </semantics></math> Mbps). (<b>b</b>) Measured mean SNR (<math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>21.2</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mi>mean</mi> </msub> <mo>=</mo> <mn>20.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>19.4</mn> </mrow> </semantics></math> dB). (<b>c</b>) Measured BER (<math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>2.4</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>1.7</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>1.4</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>). (<b>d</b>) Measured illuminance (<math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>795</mn> </mrow> </semantics></math> lx, <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>681</mn> </mrow> </semantics></math> lx, <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>500</mn> </mrow> </semantics></math> lx).</p> Full article ">Figure 16
<p>Experimental results for mockup with walls when the four lamps transmit the same data considering vertical orientation upward of the receiver and orientation given by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>): (<b>a</b>) Measured throughput for vertical orientation (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>47.5</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>46.1</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>43.9</mn> </mrow> </semantics></math> Mbps). (<b>b</b>) Measured throughput for receiver orientation given by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>) (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>47.2</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>46.3</mn> </mrow> </semantics></math> Mbps, <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>45.2</mn> </mrow> </semantics></math> Mbps). (<b>c</b>) Measured mean SNR for vertical orientation (<math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>21.8</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mi>mean</mi> </msub> <mo>=</mo> <mn>21.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>21.1</mn> </mrow> </semantics></math> dB). (<b>d</b>) Measured mean SNR for receiver orientation given by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>) (<math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>21.8</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mi>mean</mi> </msub> <mo>=</mo> <mn>21.5</mn> </mrow> </semantics></math> dB, <math display="inline"><semantics> <mrow> <msub> <mover> <mi>SNR</mi> <mo>¯</mo> </mover> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>21.2</mn> </mrow> </semantics></math> dB). (<b>e</b>) Measured BER for vertical orientation (<math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>1.2</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>1.1</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>0.7</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>). (<b>f</b>) BER for receiver orientation given by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>) (<math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>1.2</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>1.1</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>BER</mi> <mo movablelimits="true" form="prefix">min</mo> </msub> <mo>=</mo> <mn>0.7</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>).</p> Full article ">Figure 17
<p>Summary of throughput maps for different configurations (if not specified, the receiver points vertically upward): (<b>a</b>) One-lamp transmission. (<b>b</b>) Four-lamp transmission without walls. (<b>c</b>) Four-lamp transmission with walls. (<b>d</b>) Four-lamp transmission with walls and receiver oriented as defined by Equation (<a href="#FD14-electronics-10-01365" class="html-disp-formula">14</a>).</p> Full article ">
26 pages, 1398 KiB  
Article
Flickering-Free Distance-Independent Modulation Scheme for OCC
by Patricia Chavez-Burbano, Jose Rabadan, Victor Guerra and Rafael Perez-Jimenez
Electronics 2021, 10(9), 1103; https://doi.org/10.3390/electronics10091103 - 8 May 2021
Cited by 7 | Viewed by 2045
Abstract
Communications for IoT sensor networks in Smart City applications are demanding new technologies to avoid the radio frequency spectrum saturation and support the massive nodes situation required in this kind of network. Visible Light Communications are gaining interest as an alternative scheme for [...] Read more.
Communications for IoT sensor networks in Smart City applications are demanding new technologies to avoid the radio frequency spectrum saturation and support the massive nodes situation required in this kind of network. Visible Light Communications are gaining interest as an alternative scheme for solving this problem. In particular, Optical Camera Communication (OCC) takes advantage of the presence of cameras in a wide range of devices (smartphones, surveillance systems). Several transmission and modulation schemes, specifically developed for OCC, have been proposed but they present different problems as the communication range, the flickering effects in the transmitted signal, or the system complexity. In this work, an Optical Camera Communication modulation scheme that addresses the considerable variability of the transmitter–receiver distance is proposed. As will be shown, the modulation scheme works properly independently of this separation for a wide range of distances. Additionally, it performs a flickering free transmission to avoid undesired blinking effects for humans and uses a simplified transmission and reception scheme, reducing the system complexity and cost. Results of the modulation’s performance for short (<20 m), medium (20–60 m), and long (>60 m) ranges are presented in the paper, showing a 16 bps transmission rate with Bit Error Rate below the Forward Error Correction (FEC) limit (3.8 · 10−3). Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
►▼ Show Figures

Figure 1

Figure 1
<p>Analysis of Optical Camera Communication modulation schemes distributed by complexity and achieved link range.OCC modulations schemes</p> Full article ">Figure 2
<p>Transmission diagram.</p> Full article ">Figure 3
<p>Similar images with <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>C</mi> <mi>C</mi> <mo>=</mo> <mn>0.7306</mn> </mrow> </semantics></math> (close to 1).Similar images</p> Full article ">Figure 4
<p>Inverse images with <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>C</mi> <mi>C</mi> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Images with low linear correlation presenting <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>C</mi> <mi>C</mi> <mo>=</mo> <mn>0.1605</mn> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Rolling shutter effect: ROI of images containing an LED-based lamp switching at 1500 Hz, acquired with a rolling shutter camera at 25 fps with different frame resolution and environmental lighting conditions.</p> Full article ">Figure 7
<p>General flow chart of the proposed modulation scheme.</p> Full article ">Figure 8
<p>Transmission’s examples. (<b>a</b>): the transmission started previous to the emitter’s acquisition; (<b>b</b>): the emission began after the projection of the transmitter on the frame; (<b>c</b>): the first bit was transmitted during the acquisition of the emitter’s pixel rows.Transmission’s examples.</p> Full article ">Figure 9
<p>Image acquisition example. In this case, <span class="html-italic">D</span> is the distance between the camera (receiver) and the object (transmitter), <math display="inline"><semantics> <msub> <mi>d</mi> <mi>x</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>d</mi> <mi>y</mi> </msub> </semantics></math> are the horizontal and vertical distances in the real world.Image acquisition</p> Full article ">Figure 10
<p>Relation between the PCC values and the switching frequencies. All the experiments were performed with a camera’s frame rate of 30 fps. The straight red line represents <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, and band’s size = 36 pixels. The dashed blue line represents <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>60</mn> </mrow> </semantics></math>, and band’s size = 18 pixels. The dotted black line represents <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>120</mn> </mrow> </semantics></math>, and band’s size = 9 pixels.</p> Full article ">Figure 11
<p>Simulated binary image. (<b>a</b>): <span class="html-italic">α</span> = 10; <span class="html-italic">F</span><sub>Sw</sub> = 300 Hz; (<b>b</b>): <span class="html-italic">α</span> = 50; <span class="html-italic">F</span><sub>Sw</sub> = 1500 Hz.</p> Full article ">Figure 12
<p>Pearson Correlation Coefficient vs. switching frequency.</p> Full article ">Figure 13
<p>Example of obtained ROIs for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math> at D<math display="inline"><semantics> <mrow> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math> m with the calculated PCC.</p> Full article ">Figure 14
<p>Communication BER for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>15</mn> </mrow> </semantics></math>.</p> Full article ">Figure 15
<p>Communication BER for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>.</p> Full article ">Figure 16
<p>Communication BER for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>75</mn> </mrow> </semantics></math>.</p> Full article ">
8 pages, 2829 KiB  
Article
Optical Filter-Less WDM for Visible Light Communications Using Defocused MIMO
by Andrew Burton, Petr Chvojka, Paul Anthony Haigh, Zabih Ghassemlooy and Stanislav Zvanovec
Electronics 2021, 10(9), 1065; https://doi.org/10.3390/electronics10091065 - 30 Apr 2021
Cited by 10 | Viewed by 2123
Abstract
This paper experimentally investigates, for the first time, a new wavelength-division multiplexing-based visible light communications link based on a defocused non-imaging multiple-input multiple-output (MIMO), which removes the need for tuned optical bandpass filters paired with each receiver. The proposed system is based on [...] Read more.
This paper experimentally investigates, for the first time, a new wavelength-division multiplexing-based visible light communications link based on a defocused non-imaging multiple-input multiple-output (MIMO), which removes the need for tuned optical bandpass filters paired with each receiver. The proposed system is based on using the natural diversity of the individual light emitting diodes (LEDs) within a single light source to generate an H-matrix, which is independent of spatial diversity. We show that, by transmitting K-independent sets of non-return to zero on-and-off keying signals on separate wavelengths, the received superposed symbols can be demultiplexed. The non-imaging MIMO diversity is achieved by considering the power-current characteristics of the light emitting diode, the responsivity of the photodetector array, and the defocused beam spot. The system is empirically verified for K = 3 using red, green, and blue LEDs with Q-factors of 7.66, 7.69, and 4.75 dB, respectively. Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
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<p>(<b>a</b>) Defocused MIMO system block diagram. BT: bias tee, LD: laser driver, and (<b>b</b>) photograph of the defocused beam on the PD array.</p> Full article ">Figure 2
<p>(<b>a</b>) A typical Si PD responsivity curve and (<b>b</b>) normalized E/O conversion of the RGB LED.</p> Full article ">Figure 3
<p>CSI coefficient extraction h<sub>k,{R,G,B}</sub> from the transmitted pilot signal.</p> Full article ">Figure 4
<p>RGB LED: (<b>a</b>) normalized frequency response; (<b>b</b>) power profiles; (<b>c</b>) beam profile; and (<b>d</b>) LED.</p> Full article ">Figure 5
<p>Transmitted and estimated data with the corresponding eye diagrams of the estimated data for: (<b>a</b>,<b>b</b>) the λ<sub>R</sub>, (<b>c</b>,<b>d</b>) λ<sub>B</sub>, and (<b>e</b>,<b>f</b>) λ<sub>G</sub>.</p> Full article ">
14 pages, 5929 KiB  
Article
An ANN-Based Adaptive Predistorter for LED Nonlinearity in Indoor Visible Light Communications
by Jenn-Kaie Lain and Yan-He Chen
Electronics 2021, 10(8), 948; https://doi.org/10.3390/electronics10080948 - 16 Apr 2021
Cited by 10 | Viewed by 1861
Abstract
By modulating the optical power of the light-emitting diode (LED) in accordance with the electrical source and using a photodetector to convert the corresponding optical variation back into electrical signals, visible light communication (VLC) has been developed to achieve lighting and communications simultaneously, [...] Read more.
By modulating the optical power of the light-emitting diode (LED) in accordance with the electrical source and using a photodetector to convert the corresponding optical variation back into electrical signals, visible light communication (VLC) has been developed to achieve lighting and communications simultaneously, and is now considered one of the promising technologies for handling the continuing increases in data demands, especially indoors, for next generation wireless broadband systems. During the process of electrical-to-optical conversion using LEDs in VLC, however, signal distortion occurs due to LED nonlinearity, resulting in VLC system performance degradation. Artificial neural networks (ANNs) are thought to be capable of achieving universal function approximation, which was the motivation for introducing ANN predistortion to compensate for LED nonlinearity in this paper. Without using additional training sequences, the related parameters in the proposed ANN predistorter can be adaptively updated, using a feedback replica of the original electrical source, to track the LED time-variant characteristics due to temperature variation and aging. Computer simulations and experimental implementation were carried out to evaluate and validate the performance of the proposed ANN predistorter against existing adaptive predistorter schemes, such as the normalized least mean square predistorter and the Chebyshev polynomial predistorter. Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
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<p>Illustration of the application of an adaptive predistorter to compensate for LED time-variant nonlinearity.</p> Full article ">Figure 2
<p>Illustration of DCO-OFDM VLC system with adaptive predistorter.</p> Full article ">Figure 3
<p>Illustration of the proposed ANN predistorter: (<b>a</b>) The structure of an artificial neural network; (<b>b</b>) the structure of a specified neuron <math display="inline"><semantics> <mi>j</mi> </semantics></math>.</p> Full article ">Figure 4
<p>The characteristic function of the adopted LED.</p> Full article ">Figure 5
<p>Illustration of the proposed ANN predistorter: (<b>a</b>) 16 QAM DCO-OFDM with <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>25</mn> <mrow> <mtext> </mtext> <mi>dB</mi> </mrow> </mrow> </semantics></math>; (<b>b</b>) 64 QAM DCO-OFDM with <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>30</mn> <mrow> <mtext> </mtext> <mi>dB</mi> </mrow> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Convergence of the proposed ANN predistorter with different nodes in the hidden layer.</p> Full article ">Figure 7
<p>BER in AWGN versus <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </semantics></math> of the proposed ANN predistorter for different numbers of hidden layers with 16 QAM.</p> Full article ">Figure 8
<p>BER in AWGN versus <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </semantics></math> of the proposed ANN predistorter for different numbers of hidden layers with 64 QAM.</p> Full article ">Figure 9
<p>BER in AWGN versus <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </semantics></math> for the NLMS, the Chebyshev polynomial, and the proposed ANN predistortion with 16 QAM.</p> Full article ">Figure 10
<p>BER in AWGN versus <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>b</mi> </msub> <mo>/</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </semantics></math> for the NLMS, the Chebyshev polynomial, and the proposed ANN predistortion with 64 QAM.</p> Full article ">Figure 11
<p>Experimental setup of the DCO-OFDM VLC testbed.</p> Full article ">Figure 12
<p>Constellation diagrams of 16 QAM and 64 QAM modulation. (<b>a</b>–<b>c</b>) are constellation diagrams of the 16 QAM modulated OFDM signal with the NLMS, Chebyshev polynomial, and the proposed ANN predistorters, respectively. (<b>d</b>–<b>f</b>) are constellation diagrams of the 64 QAM modulated OFDM signal with the NLMS, Chebyshev polynomial, and the proposed ANN predistorters, respectively.</p> Full article ">Figure 13
<p>BER versus the distance between the LED and the PD of the 16 QAM modulated OFDM for the NLMS, the Chebyshev polynomial, and the proposed ANN predistortion.</p> Full article ">Figure 14
<p>BER versus the distance between the LED and the PD of the 64 QAM modulated OFDM for the NLMS, the Chebyshev polynomial, and the proposed ANN predistortion.</p> Full article ">
15 pages, 2848 KiB  
Article
Spectral Domain-Based Data-Embedding Mechanisms for Display-to-Camera Communication
by Lakpa Dorje Tamang and Byung Wook Kim
Electronics 2021, 10(4), 468; https://doi.org/10.3390/electronics10040468 - 15 Feb 2021
Cited by 7 | Viewed by 2295
Abstract
Recently, digital displays and cameras have been extensively used as new data transmission and reception devices in conjunction with optical camera communication (OCC) technology. This paper presents three types of frequency-based data-embedding mechanisms for a display-to-camera (D2C) communication system, in which a commercial [...] Read more.
Recently, digital displays and cameras have been extensively used as new data transmission and reception devices in conjunction with optical camera communication (OCC) technology. This paper presents three types of frequency-based data-embedding mechanisms for a display-to-camera (D2C) communication system, in which a commercial digital display transmits information and an off-the-shelf smartphone camera receives it. For the spectral embedding, sub-band coefficients obtained from a discrete cosine transform (DCT) image and predetermined embedding factors of three embedding mechanisms are used. This allows the data to be recovered from several types of noises induced in wireless optical channels, such as analog-to-digital (A/D) and digital-to-analog (D/A) conversion, rotation, scaling, and translation (RST) effects, while also maintaining the image quality to normal human eyes. We performed extensive simulations and real-world D2C experiments using several performance metrics. Through the analysis of the experimental results, it was shown that the proposed method can be considered as a suitable candidate for the D2C system in terms of the achievable data rate (ADR), peak signal-to-noise ratio (PSNR), and the bit error rate (BER). Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
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<p>Schematic of the network architecture of the proposed D2C system.</p> Full article ">Figure 2
<p>Sequential image frames of the displayed by the screen.</p> Full article ">Figure 3
<p>Discrete cosine transform (DCT) coefficients of an image of size M × N.</p> Full article ">Figure 4
<p>Data-embedded images obtained using different mechanisms. (<b>a</b>) Original input image, (<b>b</b>) M1: peak signal-to-noise ratio (PSNR) = 48 dB (<span class="html-italic">α</span> = 10), (<b>c</b>) M2: PSNR = 26 dB (<span class="html-italic">α</span> = 0.1), and (<b>d</b>) M3: PSNR = 25 dB (<span class="html-italic">α</span> = 0.1).</p> Full article ">Figure 5
<p>(<b>a</b>) The captured image, and (<b>b</b>) reconstructed image.</p> Full article ">Figure 6
<p>Experiments conducted under various lighting conditions. (<b>a</b>) Normal lighting, (<b>b</b>) normal lighting with a varying distance, (<b>c</b>) normal lighting with a varying angle, and (<b>d</b>) ambient lighting.</p> Full article ">Figure 7
<p>Bit error rate (BER) performance with respect to PSNR [dB], in simulations in which images were rotated at the receiver. (<b>a</b>) <span class="html-italic">m</span> = 250 and (<b>b</b>) <span class="html-italic">m</span> = 500.</p> Full article ">Figure 8
<p>BER performance with respect to PSNR [dB] for images captured via an optical wireless channel. (<b>a</b>) <span class="html-italic">m</span> = 250 and (<b>b</b>) <span class="html-italic">m</span> = 500.</p> Full article ">Figure 9
<p>Achievable data rate (ADR) [bps] against the PSNR [dB] performance of the proposed system. (<b>a</b>) <span class="html-italic">m</span> = 250 and (<b>b</b>) <span class="html-italic">m</span> = 500.</p> Full article ">Figure 10
<p>The BER performance of the proposed system (<b>a</b>) by distance (<span class="html-italic">D</span>) and (<b>b</b>) angle of capture (<span class="html-italic">AOC</span>).</p> Full article ">Figure 11
<p>The BER against the PSNR [dB] for the proposed system under normal and ambient lighting conditions.</p> Full article ">
20 pages, 2771 KiB  
Article
Effect of Temperature on Channel Compensation in Optical Camera Communication
by Daniel Moreno, Julio Rufo, Victor Guerra, Jose Rabadan and Rafael Perez-Jimenez
Electronics 2021, 10(3), 262; https://doi.org/10.3390/electronics10030262 - 22 Jan 2021
Cited by 9 | Viewed by 2833
Abstract
General-purpose Complementary Metal Oxide Semiconductor (CMOS) sensors perform the image desegregation in three channels (red, green, and blue) as a result of a band-pass wavelength filtering carried out using Foveon or Bayer filters. This characteristic can be used in Optical Camera Communication (OCC) [...] Read more.
General-purpose Complementary Metal Oxide Semiconductor (CMOS) sensors perform the image desegregation in three channels (red, green, and blue) as a result of a band-pass wavelength filtering carried out using Foveon or Bayer filters. This characteristic can be used in Optical Camera Communication (OCC) systems for increasing the links’ data rate by introducing Wavelength Division Multiplexing (WDM) or Color Shift Keying (CSK) modulation schemes. However, these techniques need a compensation stage to mitigate the cross-talk between channels introduced by the filters. This compensation is performed by a Channel State Information (CSI) estimation and a zero-forcing compensation scheme. The impact of the temperature effects of light-emitting diode (LED) emissions on the zero-forcing compensation scheme’s performance has not been analyzed in depth. This work presents a comprehensive methodology and experimental characterization of this impact for Foveon and Bayer-based image sensors, assuming that the CSI is estimated under temperature conditions different from the LED’s stationary temperature regime. Besides, Signal-to-Interference-plus-Noise Ratio (SINR) and Bit Error Rate (BER) performance metrics are presented in order to estimate the repercussion in an OCC link. The results reveal that the Foveon sensor obtains more unsatisfactory performance than the Bayer-based sensor. On the other hand, the blue band is the most penalized by the thermal effect. Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
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<p>Image sensor filter responses. These graphs illustrate the product between filter transmissivity and silicon sensor responsivity. (<b>a</b>) Sony IMX249. (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 2
<p>Filter patterns for the spectral information acquisition. (<b>a</b>) Foveon-based sensor. (<b>b</b>) Bayer filter sensor.</p> Full article ">Figure 3
<p>Diagram of the experimental setup.</p> Full article ">Figure 4
<p>Flow diagram of the experimental procedure.</p> Full article ">Figure 5
<p>Emission spectra at different p-n junction temperatures.</p> Full article ">Figure 6
<p>Examples of images of the blue light-emitting diode (LED) driven at different currents, taken by a thermographic camera. (<b>a</b>) LED at 10 mA and (<b>b</b>) LED at 100 mA. Both X and Y axes correspond to pixels.</p> Full article ">Figure 7
<p>Signal-to-Interference-plus-Noise Ratio (SINR) at different temperatures, compensating the channel using the Channel State Information (CSI) corresponding to 27 °C and with a high SNRvalue (30 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 8
<p>SINR at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a high SNR value (30 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 9
<p>Bit error rate (BER) at different temperatures, compensating the channel using the CSI corresponding to 27 °C and with a high SNR value (30 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 10
<p>BER at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a high SNR value (30 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 11
<p>SINR at different temperatures, compensating the channel using the CSI corresponding to 27 °C and with a medium SNR value (20 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 12
<p>SINR at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a medium SNR value (20 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 13
<p>BER at different temperatures, compensating the channel using the CSI corresponding to 27 °C and with a medium SNR value (20 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 14
<p>BER at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a medium SNR value (20 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 15
<p>SINR at different temperatures, compensating the channel using the CSI corresponding to 27 °C and with a low SNR value (10 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 16
<p>SINR at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a low SNR value (10 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 17
<p>BER at different temperatures, compensating the channel using the CSI corresponding to 27 °C and with a low SNR value (10 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">Figure 18
<p>BER at different temperatures, compensating the channel using the CSI corresponding to 60 °C and with a low SNR value (10 dB). (<b>a</b>) Sony IMX249 and (<b>b</b>) Foveon X3. Dashed line, dotted line, and dash-dot line correspond to red, green, and blue, respectively.</p> Full article ">
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