Visible Light and Camera-based Receiver Employing Machine Learning for Indoor Positioning Systems and Data Communications

Indoor location-based services have played a crucial role in the development of various Internet of Things applications over the last few decades. The use of radio frequency (RF)-based systems in indoor environments suffers from additional interference due to the high penetration rate and reflections of the RF, which may severely affect positioning accuracy. Alternatively, the optical technology using the existing light-emitting diode (LED)-based lights, photodetectors (PDs), and/or image sensors could be utilised to provide indoor positioning with high accuracy. Because of its resilience to electromagnetic interference, license-free operation, large bandwidth, and dual-use for illumination and communication, visible light positioning (VLP) systems have shown great potential in achieving high-precision indoor positioning. This thesis focus is on investigating VLP systems based on employing a single PD, or an array of PDs in the form of a single image sensor (i.e. a camera) for both localization and data communication. Following a comprehensive literature review on VLP, the key challenges in existing positioning methods for achieving a low-cost, accurate, and less complex indoor positioning systems design are highlighted by considering the design characteristics of an indoor environment, position accuracy, number of light-emitting LED, PD, and any additional sensors utilized. The thesis focuses on the major constraints of VLP and provides novel contributions. In most reported VLP schemes, the assumptions of fixed transmitter (Tx) angle and height may not be valid in many physical environments. In this work, the impact of tilting Tx and multipath reflections are investigated. The findings demonstrated that tilting Tx can be beneficial in VLP by leveraging the influence of reflections from both near- and far-walls. It also showed that proposed system offers a significant accuracy improvement by up to ~66% compared with a typical non-tilted Tx VLP system.Furthermore, increasing robustness of image sensor-based receiver (Rx) is a major challenge, which is being addressed using a novel angle of arrival-received signal intensity and a single LED. Experimental results show that the proposed algorithm can achieve a three-dimensional root mean squared error of 7.56 cm. Visible light communications employing a camera-based Rx is best known as optical camera communications (OCC), which can also be used for VLP. However, in OCC the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera's sampling introduces intersymbol interference Indoor location-based services have played a crucial role in the development of various Internet of Things applications over the last few decades. The use of radio frequency (RF)-based systems in indoor environments suffers from additional interference due to the high penetration rate and reflections of the RF, which may severely affect positioning accuracy. Alternatively, the optical technology using the existing light-emitting diode (LED)-based lights, photodetectors (PDs), and/or image sensors could be utilised to provide indoor positioning with high accuracy. Because of its resilience to electromagnetic interference, license-free operation, large bandwidth, and dual-use for illumination and communication, visible light positioning (VLP) systems have shown great potential in achieving high-precision indoor positioning. This thesis focus is on investigating VLP systems based on employing a single PD, or an array of PDs in the form of a single image sensor (i.e. a camera) for both localization and data communication. Following a comprehensive literature review on VLP, the key challenges in existing positioning methods for achieving a low-cost, accurate, and less complex indoor positioning systems design are highlighted by considering the design characteristics of an indoor environment, position accuracy, number of light-emitting LED, PD, and any additional sensors utilized. The thesis focuses on the major constraints of VLP and provides novel contributions. In most reported VLP schemes, the assumptions of fixed transmitter (Tx) angle and height may not be valid in many physical environments. In this work, the impact of tilting Tx and multipath reflections are investigated. The findings demonstrated that tilting Tx can be beneficial in VLP by leveraging the influence of reflections from both near- and far-walls. It also showed that proposed system offers a significant accuracy improvement by up to ~66% compared with a typical non-tilted Tx VLP system.Furthermore, increasing robustness of image sensor-based receiver (Rx) is a major challenge, which is being addressed using a novel angle of arrival-received signal intensity and a single LED. Experimental results show that the proposed algorithm can achieve a three-dimensional root mean squared error of 7.56 cm. Visible light communications employing a camera-based Rx is best known as optical camera communications (OCC), which can also be used for VLP. However, in OCC the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera's sampling introduces intersymbol interference

Optical Axons for Electro-Optical Neural Networks

Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have ‎been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform ‎post-processing of the sensor data. The performance of spiking neural networks has been ‎improved using optical synapses, which offer parallel communications between the distanced ‎neural areas but are sensitive to the intensity variations of the optical signal. For systems with ‎several neuromorphic sensors, which are connected optically to the main unit, the use of ‎optical synapses is not an advantage. To address this, in this paper we propose and ‎experimentally verify optical axons with synapses activated optically using digital signals. The ‎synaptic weights are encoded by the energy of the stimuli, which are then optically transmitted ‎independently. We show that the optical intensity fluctuations and link’s misalignment result ‎in delay in activation of the synapses. For the proposed optical axon, we have demonstrated line of ‎sight transmission over a maximum link length of 190 cm with a delay of 8 μs. Furthermore, we ‎show the axon delay as a function of the illuminance using a fitted model for which the root mean square error (RMS) ‎similarity is 0.95

Experimental multi-user VLC system using non-orthogonal multi-band CAP modulation

This paper provides experimental results for a multi-user visible light communications system using multi-band carrier-less amplitude and phase (m-CAP) modulation scheme. We optimize the system performance by adapting pulse shaping filter parameters, subcarrier spacing and allocating different baud rates to individual sub-bands called allocated m-CAP (Am-CAP). We show that a maximal system data rate of ∼468 Mb/s for four users can be supported while gaining higher flexibility for optimization and the same or lower computational complexity compared with the conventional m-CAP scheme

Dynamic Physical-Layer Secured Link in a Mobile MIMO VLC System

This paper proposes a novel approach to provide a privately secured multiple-input and multiple-output visible light communication (VLC) in the mobility conditions. In the proposed system, a private secured VLC link is adaptively allocated to a mobile user all the time thanks to the movement tracking assistance by a camera-based detection system. The generation of the dynamic location-based scrambling matrix will be introduced providing a secured communication zone within a full normal coverage illumination area. An extensive range of numerical evaluation and practical experiments is carried out to demonstrate and evaluate the proposed system performance in different environment configurations including the mobility, camera resolutions, link range, and environment light intensity. We demonstrate that the proposed system is fully capable of securely steering the information with respect to a receiver location with a high level of reliability

Data rate enhancement in optical camera communications using an artificial neural network equaliser

In optical camera communication (OCC) systems leverage on the use of commercial off-the-shelf image sensors to perceive the spatial and temporal variation of light intensity to enable data transmission. However, the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera’s sampling will introduce intersymbol interference (ISI), which will degrade the system performance. In this paper, an artificial neural network (ANN)-based equaliser with the adaptive algorithm is employed for the first time in the field of OCC to mitigate ISI and therefore increase the data rate. Unlike other communication systems, training of the ANN network in OCC is done only once in a lifetime for a range of different exposure time and the network can be stored with a look-up table. The proposed system is theoretically investigated and experimentally evaluated. The results record the highest bit rate for OCC using a single LED source and the Manchester line code (MLC) non-return to zero (NRZ) encoded signal. It also demonstrates 2 to 9 times improved bandwidth depending on the exposure times where the system’s bit error rate is below the forward error correction limit.publishe

The Usage of ANN for Regression Analysis in Visible Light Positioning Systems

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

Performance of Vehicular Visible Light Communications under the Effects of Atmospheric Turbulence with Aperture Averaging

In this paper, we investigate the performance of a vehicular visible light communications (VVLC) link with a non-collimated and incoherent light source (a light-emitting diode) as the transmitter (Tx), and two different optical receiver (Rx) types (a camera and photodiode (PD)) under atmospheric turbulence (AT) conditions with aperture averaging (AA). First, we present simulation results indicating performance improvements in the signal-to-noise ratio (SNR) under AT with AA with increasing size of the optical concentrator. Experimental investigations demonstrate the potency of AA in mitigating the induced signal fading due to the weak to moderate AT regimes in a VVLC system. The experimental results obtained with AA show that the link’s performance was stable in terms of the average SNR and the peak SNR for the PD and camera-based Rx links, respectively with <1 dB SNR penalty for both Rxs, as the strength of AT increases compared with the link with no AT

An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy

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

The Utilization of Artificial Neural Network Equalizer in Optical Camera Communications

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 , 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 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