FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems

Channel estimation is of crucial importance in massive multiple-input multiple-output (m-MIMO) visible light communication (VLC) systems. In order to tackle this problem, a fast and flexible denoising convolutional neural network (FFDNet)-based channel estimation scheme for m-MIMO VLC systems was proposed. The channel matrix of the m-MIMO VLC channel is identified as a two-dimensional natural image since the channel has the characteristic of sparsity. A deep learning-enabled image denoising network FFDNet is exploited to learn from a large number of training data and to estimate the m-MIMO VLC channel. Simulation results demonstrate that our proposed channel estimation based on the FFDNet significantly outperforms the benchmark scheme based on minimum mean square error.Comment: This paper will be published in IEEE WC

Lights and Shadows: A Comprehensive Survey on Cooperative and Precoding Schemes to Overcome LOS Blockage and Interference in Indoor VLC

Visible light communications (VLC) have received significant attention as a way of moving part of the saturated indoor wireless traffic to the wide and unregulated visible optical spectrum. Nowadays, VLC are considered as a suitable technology, for several applications such as high-rate data transmission, supporting internet of things communications or positioning. The signal processing originally derived from radio-frequency (RF) systems such as cooperative or precoding schemes can be applied to VLC. However, its implementation is not straightforward. Furthermore, unlike RF transmission, VLC present a predominant line-of-sight link, although a weak non-LoS component may appear due to the reflection of the light on walls, floor, ceiling and nearby objects. Blocking effects may compromise the performance of the aforementioned transmission schemes. There exist several surveys in the literature focused on VLC and its applications, but the management of the shadowing and interference in VLC requires a comprehensive study. To fill this gap, this work introduces the implementation of cooperative and precoding schemes to VLC, while remarking their benefits and drawbacks for overcoming the shadowing effects. After that, the combination of both cooperative and precoding schemes is analyzed as a way of providing resilient VLC networks. Finally, we propose several open issues that the cooperative and precoding schemes must face in order to provide satisfactory VLC performance in indoor scenarios.This work has been supported partially by Spanish National Project TERESA-ADA(TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE), the research project GEOVEOLUZ-CM-UC3Mfunded by the call “Programa de apoyo a la realización de proyectos interdisciplinares de I+D parajóvenes investigadores de la Universidad Carlos III de Madrid 2019-2020” under the frame ofthe Convenio Plurianual Comunidad de Madrid-Universidad Carlos III de Madrid and projectMadrid Flight on Chip (Innovation Cooperative Projects Comunidad of Madrid - HUBS 2018/MadridFlightOnChip). Additionally, it has been supported partially by the Juan de la CiervaIncorporación grant IJC2019-040317-I and Juan de la Cierva Formación grant (FJC2019-039541-I/AEI/10.13039/501100011033)

Améliorations des transmissions VLC (Visible Light Communication) sous contrainte d'éclairage : études théoriques et expérimentations

Abstract : Indoor visible light communication (VLC) networks based on light-emitting diodes (LEDs) currently enjoy growing interest thanks in part to their robustness against interference, wide license-free available bandwidth, low cost, good energy efficiency and compatibility with existing lighting infrastructure. In this thesis, we investigate spectral-efficient modulation techniques for the physical layer of VLC to increase throughput while considering the quality of illumination as well as implementation costs. Numerical and experimental studies are performed employing pulse amplitude modulation (PAM) and carrierless amplitude and phase (CAP) modulation under illumination constraints and for high modulation orders. Furthermore, the impact of LED nonlinearity is investigated and a postdistortion technique is evaluated to compensate these nonlinear effects. Within this framework, transmission rates in the order of a few hundred Mb/s are achieved using a test bench made of low-cost components. In addition, an imaging multiple input multiple-output (MIMO) system is developed and the impact on performance of imaging lens misalignment is theoretically and numerically assessed. Finally, a polynomial matrix decomposition technique based on the classical LU factorization method is studied and applied for the first time to MIMO VLC systems in large space indoor environments.Les réseaux de communication en lumière visible (VLC) s’appuyant sur l’utilisation de diodes électroluminescentes (LED) bénéficient actuellement d’un intérêt grandissant, en partie grâce à leur robustesse face aux interférences électromagnétiques, leur large bande disponible non-régulée, leur faible coût, leur bonne efficacité énergétique, ainsi que leur compatibilité avec les infrastructures d’éclairage déjà existantes. Dans cette thèse, nous étudions des techniques de modulation à haute efficacité spectrale pour la couche physique des VLC pour augmenter les débits tout en considérant la qualité de l’éclairage ainsi que les coûts d’implémentation. Des études numériques et expérimentales sont réalisées sur la modulation d’impulsion d’amplitude (PAM) et sur la modulation d’amplitude et de phase sans porteuse (CAP) sous des contraintes d’éclairage et pour des grands ordres de modulation. De plus, l’impact des non-linéarités de la LED est étudié et une technique de post-distorsion est évaluée pour corriger ces effets non-linéaires. Dans ce cadre, des débits de plusieurs centaines de Mb/s sont atteints en utilisant un banc de test réalisé à partir de composants à bas coûts. Par ailleurs, un système multi-entrées multi-sorties (MIMO) imageant est également développé et l’impact du désaxage de l’imageur sur les performances est étudié. Finalement, une technique de décomposition polynomiale basée sur la méthode de factorisation classique LU est étudiée et appliquée aux systèmes MIMO VLC dans des grands espaces intérieurs

Intelligent Massive MIMO Systems for Beyond 5G Networks: An Overview and Future Trends

Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the potential of challenging large-scale problems in conventional massive multiple-input-multiple-output (CM-MIMO) systems. This introduces the concept of intelligent massive MIMO (I-mMIMO) systems. Due to the surge of application of different ML techniques in the enhancement of mMIMO systems for existing and emerging use cases beyond fifth-generation (B5G) networks, this article aims to provide an overview of the different aspects of the I-mMIMO systems. First, the characteristics and challenges of the CM-MIMO have been identified. Secondly, the most recent efforts aimed at applying ML to a different aspect of CM-MIMO systems are presented. Thirdly, the deployment of I-mMIMO and efforts towards standardization are discussed. Lastly, the future trends of I-mMIMO-enabled application systems are presented. The aim of this paper is to assist the readers to understand different ML approaches in CM-MIMO systems, explore some of the advantages and disadvantages, identify some of the open issues, and motivate the readers toward future trends