Visible Light Communication(VLC) has emerged in the last years as a new way to communicate. Using the existing lighting infrastructure, it has great potential to provide high bandwidth and communication security, making it a strong alternative against conventional Radio Frequency (RF) communications. Although VLC addresses several of the problems that RF communications have for specific scenarios, its potential for Internet-of-Things (IoT) applications must still be unleashed.
IoT deployments are, by nature, limited in some way. The limitation could be given by the hardware used, as the cost may need to be minimal to have dense realistic deployments; the energy available, which depends on the battery size of the device; and computing power available, which is given by the available energy and the processing power of the device, among others. Therefore, there is an interest in studying the advantages, drawbacks, and limitations of integrating VLC in IoT scenarios with the constraints mentioned above. This is especially necessary in the case of real-life deployments, mainly if the devices used are multi-purpose, and they need to perform other tasks, such as sensing, in addition to communicating.
First of all, VLC deployments for IoT use the available dense lighting infrastructure to achieve communication on top of illumination in indoor scenarios. The advantage of such an approach is that it allows reusing the existing infrastructure, improving the coverage, and the energy consumed. Although VLC is energy efficient, it consumes more than just illuminating. If the luminaries are not correctly controlled, energy could be wasted by transmitting from a luminary with little or no effect into the receiver.
In DenseVLC, we explore the energy consumption of luminaries in dense deployments, and we propose an approach to optimize the Signal-to-Interference-plus-Noise Ratio (SINR) given an energy budget. In order to do so, we propose to coordinate the transmission done by several independent devices concurrently. We introduce a novel synchronization method that uses the Non Line-Of-Sight (NLOS) component of the signal to tackle this problem. Our approach can improve the average system throughput by 45%, or improve the average power efficiency by 2.3 times, compared to existing solutions.
Secondly, even if the required infrastructure follows the design presented above, IoT deployments still need to face one fundamental problem: power management at deployed mobile devices. Having batteries increases the price of the device, its size, the maintenance required, and the ecological impact that the product has. Removing the battery while still being able to operate under realistic circumstances would be desired. In this work, we study what limitations such a system has. We then propose a new communication scheme, combining VLC and RF backscattering, that allows having continuous end-to- end communication with a custom-designed battery-free device. We design the hardware, software, and protocol that optimizes each aspect of the system to decrease the power requirement of each component. Finally, we evaluate our system and show that it can run with consumptions as low as 95μW, transmit continuously at 500 bits/second, and achieve more than 20 meters on backscattering distance, even with blockage elements as glass and walls covering the Line-Of-Sight (LOS).
Thirdly, we explore one of the multiple applications that the designed VLC systems for IoT allow to implement; device positioning. The majority of the literature requires to have multiple transmitters and/or receivers to achieve localization.
The objective of this work is to localize with the minimum amount of necessary hardware, which is critical for IoT applications. We investigate how VLC systems could be used for positioning in dynamic scenarios. Exploiting the fact that, in our scenario, the transmitter and receiver are relatively moving, we propose a mathematical solution that, just using one VLC transmitter and one receiver both equipped with a compass, computes the correct relative position. We then implement our solution in a modified version of OpenVLC and achieve accuracies with less than 5 cm of error. Nevertheless, in this work we assume that the NLOS is non-existent, which may not always be the case.
Finally, we try to overcome the problem mentioned above of NLOS reflections for device positioning with a low resource consumption NLOS component detector. Similar work try to solve this problem computing the Channel Impulse Response (CIR), but for systems with limited resources this is impractical because 1) The VLC front-end may not be fast enough for acquiring required data for the CIR calculation or 2) IoT boards are not able to run computationally expensive algorithms in real time.
In this thesis, we propose a solution that in complex environments, reduces the localization error using LEDs up to 93%. In order to perform experimental research in VLC for IoT, a research platform is needed. In this thesis, we also present the latest version of an open-source, software- based, VLC platform, OpenVLC. OpenVLC was first introduced as part of the thesis of Dr. Qing Wang. During this thesis, the platform has been re-designed on both hardware and software. The throughput improved more than 23 times and the transmission distance increased by a factor of 4. In this thesis, OpenVLC, parts of it, or modified versions have been used as a framework to create new IoT systems and explore the practical side of VLC.
As a summary, in this work, we explore how VLC can be leveraged for IoT deployments. We study the features of such real-world deployments from different perspectives in a variety of scenarios, and we show that realistic implementations of VLC systems are not only possible but doable, enabling new features that IoT developer can exploit.
About Ander Galisteo
In 2014, Ander obtained his B.Sc. in Telecommunications System Engineering from the University of Navarra (San Sebastian, Spain). In 2016, he received his M.Sc. in Telecommunications Engineering from the same University and a M.Sc in Engineering Technology: Network Communication Track from the University of Houston.
The thesis defense will be conducted in English. Given the coronavirus crisis, the thesis defense will be online.
PhD Thesis Advisor: Dr. Domenico Giustiniano, IMDEA Networks Institute, Madrid, Spain
University: University Carlos III of Madrid, Spain
Doctoral Program: Telematics Engineering
PhD Committee members: