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Nowadays, with the incursion of solid state lighting technology in our daily life, visible light communication (VLC) systems are becoming more important. This fact has generated a lot of attention on VLC to provide solutions on multiple applications where this technology can be exploited. At the same time, the growing of automation processes has created the necessity of knowing the localization of different objects and devices. Indoor localization based on radio frequency signals is one of the most used techniques (Wi‐Fi, Bluetooth, UWB, RFID, etc); however, VLC is a new and interesting method, which is gaining enormous research attention. Moreover, there are environments where the use of RF technologies is restricted or even prohibited. In such cases, VLC technology becomes an interesting alternative to solve this problem. In this paper, we design and implement a novel VLC‐based indoor localization system that combines the application of a VLC scheme for downlink and an ultrasonic communication for the uplink. Practical localization experiments are carried out in an actual office room environment, and results show a localization accuracy of 4 cm on average for direct links and 10 cm for indirect links. In this paper, we design and implement a novel VLC‐based indoor localization system that combines the application of a VLC scheme for downlink and an ultrasonic communication for the uplink. Practical localization experiments are carried out in an actual office room environment, and results show a localization accuracy of 4 cm on average for direct links and 10 cm for indirect links. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the Matrix‐MMC propagation model for indoor wireless optical channels. This proposed method is evolved from the modified Monte Carlo (MMC)–based ray tracing algorithm, but in addition to the properties of MMC, it has the capability of capturing reflection phenomena implying changes on wavelength (eg, fluorescence, phosphorescence, or iridescence) with a simplified analytical expression. The model provides unprecedented information about the mechanism of surface reflection in a visible light communication channel, which influences the propagation of the light waves, that depends on wavelength. In this paper, we present the Matrix‐MMC method to evaluate the channel impulse response for indoor Visible Light Communication (VLC). The approach is based on Monte Carlo ray‐tracing method (MMC) with the ability to capture reflection phenomena with changes on wavelength. The Matrix‐MMC provides an accurate channel and wavelength response estimation that will be of a great interest when dealing with equalization, security applications or when trying to use VLC systems in real‐lighting scenarios, using color‐shift keying modulation or other polychromatic system. [ABSTRACT FROM AUTHOR]

This paper presents an experimental evaluation of a wearable light-emitting diode (LED) transmitter in an optical camera communications (OCC) system. The evaluation is conducted under conditions of controlled user movement during indoor physical exercise, encompassing both mild and intense exercise scenarios. We introduce an image processing algorithm designed to identify a template signal transmitted by the LED and detected within the image. To enhance this process, we utilize the dynamics of controlled exercise-induced motion to limit the tracking process to a smaller region within the image. We demonstrate the feasibility of detecting the transmitting source within the frames, and thus limit the tracking process to a smaller region within the image, achieving an reduction of 87.3% for mild exercise and 79.0% for intense exercise.

This paper presents an experimental study of the turbulence impact caused by temperature inhomogeneity and air bubbles on a global shutter-based underwater optical camera communication (UOCC). The effects of these two phenomena on UOCC links are illustrated in terms of the intensity variations and an associated reduction in the average received intensity of the illuminated pixels corresponding to the optical source projection and the dispersion of the projection on the captured images. Additionally, it is shown that the area of illuminated pixels in the temperature-induced turbulence scenario is higher than in the bubbly water case. To analyze the effects of those two phenomena on the optical link performance, the signal-to-noise ratio (SNR) of the system is evaluated by considering different points as the regions of interest (ROI) from the light source projection of the captured images. The results indicate that the system performance is improved by averaging over the value of several pixels produced by the point spread function, compared to simply using the central and the maximum pixel value as the ROIs.

In rolling shutter (RS)-based optical camera communication (OCC) links, selecting the appropriate camera's exposure time is critical, as it limits the reception bandwidth. In long exposures, the pixels accumulate over time the incoming irradiance of several consecutive symbols. As a result, a harmful intersymbol interference corrupts the received signal. Consequently, reducing the exposure time is required to increase the reception bandwidth at the cost of producing dark images with impracticable light conditions for human or machine-supervised applications. Alternatively, deep learning (DL) equalizers can be trained to mitigate the exposure-related ISI. These equalizers must be trained considering the transmitter clock and the camera's exposure, which can be exceptionally challenging if those parameters are unknown in advance (e.g., if the camera does not reveal its internal settings). In those cases, the receiver must estimate those parameters directly from the images, which are severely distorted by the exposure time. This work proposes a DL estimator for this purpose, which is trained using synthetic images generated for thousands of representative cases. This estimator enables the receiver operation under multiple possible configurations, regardless of the camera used. The results obtained during the validation, using more than 7000 real images, registered relative errors lower than 1% and 2% when estimating the transmitter clock and the exposure time, respectively. The obtained errors guarantee the optimal performance of the following equalization and decoding receiver stages, keeping bit error rates below the forward error correction limit. This estimator is a central component of any OCC receiver that operates over moderate exposure conditions. It decouples the reception routines from the cameras used, ultimately enabling cloud-based receiver architectures.

Optical camera communication (OCC) is a promising technology to be used in future wireless communication systems. In this work, a cluster-based data detection procedure is applied to enhance the performance of an OCC system. A multispectral camera is employed to capture the spectral variations in light-emitting diodes (LEDs) caused by temperature. This strategy's system performance is compared with a system that uses traditional linear methods, such as zero-forcing (ZF) and minimum mean square error (MMSE) equalizers. The findings of this study indicate that an improvement in the bit error rate (BER) can be achieved by applying a clustering approach.

Current vehicular systems require real-time information to keep drivers safer and more secure on the road. In addition to the radio frequency (RF) based communication technologies, Visible Light Communication (VLC) has emerged as a complementary way to enable wireless access in intelligent transportation systems (ITS) with a simple design and low-cost deployment. However, integrating VLC in vehicular networks poses some fundamental challenges. In particular, the limited coverage range of the VLC access points and the high speed of vehicles create time-limited links that the existing handover procedures of VLC networks can not be accomplished timely. Therefore, this paper addresses the problem of designing a vehicular VLC network that supports high mobility users. We first modify the traditional VLC network topology to increase uplink reliability. Then, a low-latency handover scheme is proposed to enable mobility in a VLC network. Furthermore, we validate the functionality of the proposed VLC network design method by using system-level simulations of a vehicular tunnel scenario. The analysis and the results show that the proposed method provides a steady connection, where the vehicular node is available more than 99% of the time regardless of the number of vehicular nodes on this network. Additionally, the system is able to achieve a Frame-Error-Rate (FER) performance lower than 10 -3 .

In this paper, we explore the potential applications of Optical Wireless Communications in the tourism industry, considering both indoor and outdoor scenarios and different transmission speeds. They range from high-speed atmospheric outdoor links (Free-Space Optics (FSO)) to indoor systems based on high-speed lighting networks (known under the trade name LiFi©) or low-speed services support the Internet of Things networks, using visible light (VLC) or IR emitters, with receivers based on either on classical photodiodes or in image sensors, known as Optical Camera Communications. The avant-garde applications of this technology have been studied focusing on three possible use scenarios: the traveler himself, in what we have called TAN (Tourist Area Network); the tourist facility, which includes not only the hotel but also leisure areas (theme parks, museums, natural protected areas) or services (restaurants, shopping areas, etc.); and the entire destination, which can be both the city or the territory where the tourist is received, within the paradigm of the Smart Tourist Destination (STD). In addition to the classic services based on radio frequency and wired broadband networks, these technologies will make it possible to meet the tourist's challenging needs, the establishment, and the destination. Besides, they cover the services imposed by the new marketing services related to location or context and feed the big data systems used to study tourist behavior.

In rolling shutter-based optical camera communication (OCC), the camera's exposure time limits the achievable reception bandwidth. In long-exposure settings, the image sensor pixels average the incident received power, producing inter-symbol interference (ISI), which is perceived in the images as a spatial mixture of the symbol bands. Hence, the shortest possible exposure configuration should be selected to alleviate ISI. However, in these conditions, the camera produces dark images with impracticable light conditions for human or machine-supervised applications. In this paper, a novel convolutional autoencoder-based equalizer is proposed to alleviate exposure-related ISI and noise. Furthermore, unlike other systems that use artificial neural networks for equalization and decoding, the training procedure is conducted offline using synthetic images for which no prior information about the deployment scenario is used. Hence the training can be performed for a wide range of cameras and signal-to-noise ratio (SNR) conditions, using a vast number of samples, improving the network fitting and the system decoding robustness. The results obtained in the experimental validation record the highest ISI mitigation potential for Manchester encoded on-off keying signals. The system can mitigate the ISI produced by exposure time windows that are up to seven times longer than the transmission symbol duration, with bit error rates (BER) lower than 10 -5 under optimal SNR conditions. Consequently, the reception bandwidth improves up to 14 times compared to non-equalized systems. In addition, under harsh SNRs conditions, the system achieves BERs below the forward error correction limit for 1dB and 5 dB while operating with exposure times that are 2 and 4 times greater than the symbol time, respectively.