Long-distance indoor optical camera communication using side-emitting fibers as distributed transmitters.

We present a design approach for a long-distance optical camera communication (OCC) system using side-emitting fibers as distributed transmitters. We demonstrate our approach feasibility by increasing the transmission distance by two orders up to 40 m compared to previous works. Furthermore, we explore the effect of the light-emitting diode (LED) modulation frequency and rolling shutter camera exposure time on inter-symbol interference and its effective mitigation. Our proposed OCC-fiber link meets the forward-error-correction (FEC) limit of 3.8 · 10-3 of bit error rate (BER) for up to 35 m (with BER= 3.35 · 10-3) and 40 m (with BER=1.13 · 10-3) using 2-mm and 3-mm diameter side-emitting fibers, respectively. Our results at on-off keying modulation frequencies of 3.54 kHz and 5.28 kHz pave the way to moderate-distance outdoor and long-distance indoor highly-reliable applications in the Internet of Things and OCC using side-emitting fiber-based distributed transmitters.

General framework for calculating irradiance distributions of symmetric surface sources.

Symmetries in system modeling can be exploited to obtain analytical results on the system behavior and to speed up computations using the symmetric model. This work explores the use of symmetries in radiant surfaces for calculating the induced irradiance distributions by developing a general mathematical expression. The obtained model is applied to flat, cylindrical, and spherical sources to obtain explicit expressions. An experimental evaluation of the flat source is carried out and compared with a traditional point source, and the obtained procedure for the flat scenario is compared with the direct integration approach, which shows an improvement in the computation time of at least two orders of magnitude with a relative root mean square error of less than 10%. The results show that the proposed approach enhances short-range predictions for extended sources. To demonstrate the impact of this in optical wireless communications we have outlined a few applications.

Deep learning for signal clock and exposure estimation in rolling shutter optical camera communication.

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.

Convolutional autoencoder for exposure effects equalization and noise mitigation in optical camera communication.

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.

Design and Experimental Characterization of a Discovery and Tracking System for Optical Camera Communications.

Visible light communications (VLC) technology is emerging as a candidate to meet the demand for interconnected devices' communications. However, the costs of incorporating specific hardware into end-user devices slow down its market entry. Optical camera communication (OCC) technology paves the way by reusing cameras as receivers. These systems have generally been evaluated under static conditions, in which transmitting sources are recognized using computationally expensive discovery algorithms. In vehicle-to-vehicle networks and wearable devices, tracking algorithms, as proposed in this work, allow one to reduce the time required to locate a moving source and hence the latency of these systems, increasing the data rate by up to 2100%. The proposed receiver architecture combines discovery and tracking algorithms that analyze spatial features of a custom RGB LED transmitter matrix, highlighted in the scene by varying the cameras' exposure time. By using an anchor LED and changing the intensity of the green LED, the receiver can track the light source with a slow temporal deterioration. Moreover, data bits sent over the red and blue channels do not significantly affect detection, hence transmission occurs uninterrupted. Finally, a novel experimental methodology to evaluate the evolution of the detection's performance is proposed. With the analysis of the mean and standard deviation of novel K parameters, it is possible to evaluate the detected region-of-interest scale and centrality against the transmitter source's ideal location.

Wireless Sensor Networks Using Sub-Pixel Optical Camera Communications: Advances in Experimental Channel Evaluation.

Optical wireless communications in outdoor scenarios are challenged by uncontrollable atmospheric conditions that impair the channel quality. In this paper, different optical camera communications (OCC) equipment are experimentally studied in the laboratory and the field, and a sub-pixel architecture is raised as a potential solution for outdoor wireless sensor networks (WSN) applications, considering its achievable data throughput, the spatial division of sources, and the ability of cameras to overcome the attenuation caused by different atmospheric conditions such as rain, turbulence and the presence of aerosols. Sub-pixel OCC shows particularly adequate capabilities for some of the WSN applications presented, also in terms of cost-effectiveness and scalability. The novel topology of sub-pixel projection of multiple transmitters over the receiver using small optical devices is presented as a solution using OCC that re-uses camera equipment for communication purposes on top of video-monitoring.

Optical Camera Communication as an Enabling Technology for Microalgae Cultivation.

Optical Camera Communication (OCC) systems have a potential application in microalgae production plants. In this work, a proof-of-concept prototype consisting of an artificial lighting photobioreactor is proposed. This reactor optimises the culture's photosynthetic efficiency while transmitting on-off keying signals to a rolling-shutter camera. Upon reception, both signal decoding and biomass concentration sensing are performed simultaneously using image processing techniques. Moreover, the communication channel's theoretical modelling, the data rate system's performance, and the plant distribution requirements and restrictions for a production-scale facility are detailed. A case study is conducted to classify three different node arrangements in a real facility, considering node visibility, channel capacity, and space exploitation. Finally, several experiments comprising radiance evaluation and Signal-to-Noise Ratio (SNR) computation are performed at different angles of view in both indoor and outdoor environments. It is observed that the Lambertian-like emission patterns are affected by increasing concentrations, reducing the effective emission angles. Furthermore, significant differences in the SNR, up to 20 dB, perceived along the illuminated surface (centre versus border), gradually reduce as light is affected by greater dispersion. The experimental analysis in terms of scattering and selective wavelength attenuation for green (Arthrospira platensis) and brown (Rhodosorus marinus) microalgae species determines that the selected strain must be considered in the development of this system.

Correlation-based receiver for optical camera communications.

In color-multiplexed optical camera communications (OCC) systems, data acquisition is restricted by the image processing algorithm capability for fast source recognition, region-of-interest (ROI) detection and tracking, packet synchronization within ROI, estimation of inter-channel interference and threshold computation. In this work, a novel modulation scheme for a practical RGB-LED-based OCC system is presented. The four above-described tasks are held simultaneously. Using confined spatial correlation of well-defined reference signals within the frame's color channels is possible to obtain a fully operating link with low computational complexity algorithms. Prior channel adaptation also grants a substantial increase in the attainable data rate, making the system more robust to interferences.