Optimization of the Receiving Orientation Angle for Zero-Forcing Precoding in VLC

We study the performance of linear zero-forcing (ZF) precoding in multiuser multiple-input single-output visible light communications (VLC) when we are able to select the receiving orientation angle (ROA) of each user. For radio-frequency communications, the non-line-of-sight rich scattering environment usually ensures the linear independence among user's channels. However, this condition is less likely to happen in VLC systems, degrading the performance of ZF precoding. In this work, we propose a variable ROA (vROA) photodetector able to modify its orientation vector in order to generate semi-orthogonal channel responses among users. We derive the algorithm for determining the orientation of the vROA photodetector of each user, obtaining optimal and suboptimal solutions with high and low complexity, respectively. Simulation results show that the performance of ZF precoding is improved considerably by managing the users ROA.This work has been supported by the Spanish National Project TERESAADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE) and the research project GEOVEOLUZ-CM-UC3M.Publicad

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Introduction to indoor networking concepts and challenges in LiFi

LiFi is networked, bidirectional wireless communication with light. It is used to connect fixed and mobile devices at very high data rates by harnessing the visible light and infrared spectrum. Combined, these spectral resources are 2600 times larger than the entire radio frequency (RF) spectrum. This paper provides the motivation behind why LiFi is a very timely technology, especially for 6th generation (6G) cellular communications. It discusses and reviews essential networking technologies, such as interference mitigation and hybrid LiFi/Wi-Fi networking topologies. We also consider the seamless integration of LiFi into existing wireless networks to form heterogeneous networks across the optical and RF domains and discuss implications and solutions in terms of load balancing. Finally, we provide the results of a real-world hybrid LiFi/Wi-Fi network deployment in a software defined networking testbed. In addition, results from a LiFi deployment in a school classroom are provided, which show that Wi-Fi network performance can be improved significantly by offloading traffic to the LiFi

Interference Suppression in Massive MIMO VLC Systems

The focus of this dissertation is on the development and evaluation of methods and principles to mitigate interference in multiuser visible light communication (VLC) systems using several transmitters. All components of such a massive multiple-input multiple-output (MIMO) system are considered and transformed into a communication system model, while also paying particular attention to the hardware requirements of different modulation schemes. By analyzing all steps in the communication process, the inter-channel interference between users is identified as the most critical aspect. Several methods of suppressing this kind of interference, i.e. to split the MIMO channel into parallel single channels, are discussed, and a novel active LCD-based interference suppression principle at the receiver side is introduced as main aspect of this work. This technique enables a dynamic adaption of the physical channel: compared to solely software-based or static approaches, the LCD interference suppression filter achieves adaptive channel separation without altering the characteristics of the transmitter lights. This is especially advantageous in dual-use scenarios with illumination requirements. Additionally, external interferers, like natural light or transmitter light sources of neighboring cells in a multicell setting, can also be suppressed without requiring any control over them. Each user's LCD filter is placed in front of the corresponding photodetector and configured in such a way that only light from desired transmitters can reach the detector by setting only the appropriate pixels to transparent, while light from unwanted transmitters remains blocked. The effectiveness of this method is tested and benchmarked against zero-forcing (ZF) precoding in different scenarios and applications by numerical simulations and also verified experimentally in a large MIMO VLC testbed created specifically for this purpose

Reliable indoor optical wireless communication in the presence of fixed and random blockers

The advanced innovation of smartphones has led to the exponential growth of internet users which is expected to reach 71% of the global population by the end of 2027. This in turn has given rise to the demand for wireless data and internet devices that is capable of providing energy-efficient, reliable data transmission and high-speed wireless data services. Light-fidelity (LiFi), known as one of the optical wireless communication (OWC) technology is envisioned as a promising solution to accommodate these demands. However, the indoor LiFi channel is highly environment-dependent which can be influenced by several crucial factors (e.g., presence of people, furniture, random users' device orientation and the limited field of view (FOV) of optical receivers) which may contribute to the blockage of the line-of-sight (LOS) link. In this thesis, it is investigated whether deep learning (DL) techniques can effectively learn the distinct features of the indoor LiFi environment in order to provide superior performance compared to the conventional channel estimation techniques (e.g., minimum mean square error (MMSE) and least squares (LS)). This performance can be seen particularly when access to real-time channel state information (CSI) is restricted and is achieved with the cost of collecting large and meaningful data to train the DL neural networks and the training time which was conducted offline. Two DL-based schemes are designed for signal detection and resource allocation where it is shown that the proposed methods were able to offer close performance to the optimal conventional schemes and demonstrate substantial gain in terms of bit-error ratio (BER) and throughput especially in a more realistic or complex indoor environment. Performance analysis of LiFi networks under the influence of fixed and random blockers is essential and efficient solutions capable of diminishing the blockage effect is required. In this thesis, a CSI acquisition technique for a reconfigurable intelligent surface (RIS)-aided LiFi network is proposed to significantly reduce the dimension of the decision variables required for RIS beamforming. Furthermore, it is shown that several RIS attributes such as shape, size, height and distribution play important roles in increasing the network performance. Finally, the performance analysis for an RIS-aided realistic indoor LiFi network are presented. The proposed RIS configuration shows outstanding performances in reducing the network outage probability under the effect of blockages, random device orientation, limited receiver's FOV, furniture and user behavior. Establishing a LOS link that achieves uninterrupted wireless connectivity in a realistic indoor environment can be challenging. In this thesis, an analysis of link blockage is presented for an indoor LiFi system considering fixed and random blockers. In particular, novel analytical framework of the coverage probability for a single source and multi-source are derived. Using the proposed analytical framework, link blockages of the indoor LiFi network are carefully investigated and it is shown that the incorporation of multiple sources and RIS can significantly reduce the LOS coverage blockage probability in indoor LiFi systems