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This paper present simulation-based results on the impact of transmitter (Tx) position and orientation uncertainty on the accuracy of the visible light positioning (VLP) system based on the received signal strength (RSS). There are several constraining factors for RSS-based algorithms, particularly due to multipath channel characteristics and set-up uncertainties. The impact of Tx uncertainties on positioning error performance is studied, assuming a statistical modelling of the uncertainties. Simulation results show that the Tx uncertainties have a severe impact on the positioning error, which can be leveraged through the usage of more transmitters. Concerning a smaller Tx’s position uncertainty of 5 cm, the average positioning errors are 23.3, 15.1, and 13.2 cm with the standard deviation values of 6.4, 4.1, and 2.7 cm for 4-, 9-, and 16-Tx cases, respectively. While for a smaller Tx’ orientation uncertainty of 5°, the average positioning errors are 31.9, 20.6, and 17 cm with standard deviation values of 9.2, 6.3, and 3.9 cm for 4-, 9-, and 16-Tx cases, respectively.

This paper presents a multi-user Visible Light Communication (VLC)-based Internet of Things (IoT) system using multi band-Carrierless Amplitude and Phase (m-CAP) modulation for IoT applications. The proposed system uses a digital m-CAP modulator embedded in a ceiling LED light fixture and analog receivers, aiming at low-cost, low-power, and small-sized IoT devices. The performance was evaluated in terms of the filtering stage design and the usage of guard bands. Different pairs of emitter and receiver filters were considered. While Bessel and Butterworth analog filters were tested in the analog receiver, the digital m-CAP modulator pulse shaping filter considered raised cosine filters, as well as digital matched filters for the analog Bessel and Butterworth filters. Regarding the guard bands, two approaches were considered: either by using the raised cosine roll-off factor (bandwidth compression) or by suppressing the even bands. The Bit Error Rate (BER) performance was obtained by simulation. The usage of the Bessel filter in the receiver, along with a digital matched filter, proved to be the best solution, achieving a BER lower than 10−3 for an Eb/No of 6 dB, using a third-order filter. Furthermore, guard bands should be used in order to mitigate inter-band interference in order to have improved performance when multiple users intend to simultaneously communicate.

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches. Three different ANN algorithms are considered, including Levenberg–Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, to minimize the positioning error (εp) in the VLP system. The ANN design is optimized based on the number of neurons in the hidden layers, the number of training epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional received signal strength (RSS) technique using the non-linear least square estimation for all values of signal to noise ratio (SNR). Furthermore, in the inner region, which includes the area of the receiving plane within the transmitters, the positioning accuracy is improved by 43, 55, and 50% for the SNR of 10, 20, and 30 dB, respectively. In the outer region, which is the remaining area within the room, the positioning accuracy is improved by 57, 32, and 6% for the SNR of 10, 20, and 30 dB, respectively. Moreover, we also analyze the impact of different training dataset sizes in ANN, and we show that it is possible to achieve a minimum εp of 2 cm for 30 dB of SNR using a random selection scheme. Finally, it is observed that εp is low even for lower values of SNR, i.e., εp values are 2, 11, and 44 cm for the SNR of 30, 20, and 10 dB, respectively.

In this paper, we propose and validate an artificial neural network-based equalizer for the constant power 4-level pulse amplitude modulation in an optical camera communications system. We introduce new terminology to measure the quality of the communications link in terms of the number of row pixels per symbol Npps, which allows a fair comparison considering the progress made in the development of the current image sensors in terms of the frame rates and the resolutions of each frame. Using the proposed equalizer, we experimentally demonstrate a non-flickering system using a single light-emitting diode (LED) with Npps of 20 and 30 pixels/symbol for the unequalized and equalized systems, respectively. Potential transmission rates of up to 18.6 and 24.4 kbps are achieved with and without the equalization, respectively. The quality of the received signal is assessed using the eye-diagram opening and its linearity and the bit error rate performance. An acceptable bit error rate (below the forward error correction limit) and an improvement of ~66% in the eye linearity are achieved using a single LED and a typical commercial camera with equalization.

The next generation wireless technology networks and beyond (i [...]

Real-time monitoring of torque in a rotating shaft is not easy to implement with technologies such as optic fiber sensors or strain gages. Surface acoustic wave (SAW) sensors are wireless and passive and can be used to monitor strain in moving parts. Commercial solutions (sensors, antennas and interrogation unit) can easily be purchased from some companies; however, they are not customized and may not meet the specificity of the measurements. In order to evaluate the adequacy of commercial off-the-shelf (COTS) solutions, temperature and strain sensors fabricated by SENSeOR (Besançon, France) were mounted on a load cell. The sensors were calibrated using a thermal chamber and a universal testing machine. The load cell was then assembled together with a steel shaft that rotated at different speeds inside an oven. The commercial antennas were replaced with an RF (radio frequency) coupler and the sensors were interrogated with the commercial interrogation unit. The influence of rotation in the accuracy on the measurements, as well as the adequacy of the sensors structure, was evaluated. It can be concluded that SAW sensors can be used to measure temperature or torque in a rotating environment; however, some customization of the components is required in order to overcome the limitations posed by COTS sensing solutions.

This paper proposes a novel, robust, and lightweight supervised Convolutional Neural Network (CNN)-based technique for frame identification and synchronization, designed to enhance short-link communication performance in a screen-to-camera (S2C) based visible light communication (VLC) system. Developed using Python and the TensorFlow Keras framework, the proposed CNN model was trained through three real-time experimental investigations conducted in Jupyter Notebook. These experiments incorporated a dataset created from scratch to address various real-time challenges in S2C communication, including blurring, cropping, and rotated images in mobility scenarios. Overhead frames were introduced for synchronization, which leads to enhanced system performance. The experimental results demonstrate that the proposed model achieves an overall accuracy of approximately 98.74%, highlighting its effectiveness in identifying and synchronizing frames in S2C VLC systems.

Optical Camera Communication (OCC) systems can take advantage of the row-by-row scanning process of rolling-shutter cameras to capture the fast variations of light intensity coming from Visible Light Communication (VLC) LED-based transmitters. In order to study the maximum data rate that is feasible in such kind of OCC systems, this paper presents its equivalent digital communication system model in which the rolling-shutter camera is modeled as a rectangular matched-filter whose time width is equal to the exposure time of the camera, followed by a sampling process at the pixel row sweep rate of the camera. Based on the proposed rolling-shutter camera model, the maximum symbol rate that such OCC systems can support is experimentally demonstrated, and the impact of imperfect time synchronization between the VLC transmitter and the rolling-shutter OCC receiver is characterized in the form of Inter-Symbol Interference (ISI). The equivalent three-tap channel model that results from this process is experimentally validated and the generated ISI is compensated with the use of linear equalization in reception. Simulation and experimental results show a strong correlation between them, demonstrating that the proposed approach can be used to make the OCC system work at the Nyquist sampling rate, which is equivalent to the pixel row sweep rate of the rolling-shutter camera used in reception.

This paper discusses bandwidth problems associated with second-generation current conveyors (CCII). In particular, our work is centered in high-capacitance applications, and has been oriented for wireless optical links and applied physics. We discuss techniques for improving bandwidth in these CCIIs, and develop a new CCII structure with larger bandwidth than traditional circuits. These circuits are then compared in terms of their noise and dynamic range characteristics. A test circuit was developed to verify these different bandwidth behaviors.