20 research outputs found
LiFi Transceiver Designs for 6G Wireless Networks
Due to the dramatic increase in high data rate services, and in order to meet the demands of the sixth-generation (6G) wireless networks, researchers from both academia and industry have been exploring advanced transmission techniques, new network archi-
tectures and new frequency bands, such as the millimeter wave (mmWave), the infrared, and the visible light bands. Light-fdelity (LiFi) particularly is an emerging, novel, bidirectional, high-speed and fully networked optical wireless communication (OWC) technology that has been introduced as a promising solution for 6G networks, especially for indoor connectivity, owing to the large unexploited spectrum that translates to signifcantly high data rates.
Although there has been a big leap in the maturity of the LiFi technology, there is still a considerable gap between the available LiFi technology and the required demands of 6G networks. Motivated by this, this dissertation aims to bridge between the current research literature of LiFi and the expected demands of 6G networks. Specifcally, the key goal of this dissertation is to fll some shortcomings in the LiFi technology, such as channel modeling, transceiver designs, channel state information (CSI) acquisition, localization, quality-of-service (QoS), and performance optimization. Our work is devoted to address and solve some of these limitations. Towards achieving this goal, this dissertation makes signifcant contributions to several areas of LiFi. First, it develops novel and measurements-based channel models for LiFi systems that are required for performance analysis and handover management. Second, it proposes a novel design for LiFi devices that is capable of alleviating the real behaviour of users and the impurities of indoor
propagation environments. Third, it proposes intelligent, accurate and fast joint position and orientation techniques for LiFi devices, which improve the CSI estimation process and boost the indoor location-based and navigation-based services. Then, it proposes novel proactive optimization technique that can provide near-optimal and real-time service for indoor mobile LiFi users that are running some services with high data rates, such as extended reality, video conferencing, and real-time video monitoring. Finally, it proposes advanced multiple access techniques that are capable of cancelling the efects of interference in indoor multi-user settings. The studied problems are tackled using various tools from probability and statistic theory, system design and integration theory, optimization theory, and deep learning. The Results demonstrate the efectiveness of the proposed designs, solutions, and techniques. Nevertheless, the fndings in this dissertation highlight key guidelines for the efective design of LiFi while considering their unique propagation
features
Deep Learning Based Proactive Optimization for Mobile LiFi Systems with Channel Aging
This paper investigates the channel aging problem of mobile light-fidelity
(LiFi) systems. In the LiFi physical layer, the majority of the optimization
problems for mobile users are non-convex and require the use of dual
decomposition or heuristics techniques. Such techniques are based on iterative
algorithms, and often, cause a high processing delay at the physical layer.
Hence, the obtained solutions are no longer optimal since the LiFi channels are
evolving. In this paper, a proactive-optimization (PO) approach that can
alleviate the LiFi channel aging problem is proposed. The core idea is to
design a long-short-term-memory (LSTM) network that is capable of predicting
posterior positions and orientations of mobile users, which can be then used to
predict their channel coefficients. Consequently, the obtained channel
coefficients can be exploited to derive near-optimal transmission-schemes prior
to the intended service-time, which enables real-time service. Through various
simulations, the performance of the designed LSTM model is evaluated in terms
of prediction error and time, as well as its application in a practical LiFi
optimization problem
Invoking Deep Learning for Joint Estimation of Indoor LiFi User Position and Orientation
Light-fidelity (LiFi) is a fully-networked bidirectional optical wireless
communication (OWC) that is considered a promising solution for high-speed
indoor connectivity. Unlike in conventional radio frequency wireless systems,
the OWC channel is not isotropic, meaning that the device orientation affects
the channel gain significantly. However, due to the lack of proper channel
models for LiFi systems, many studies have assumed that the receiver is
vertically upward and randomly located within the coverage area, which is not a
realistic assumption from a practical point of view. In this paper, novel
realistic and measurement-based channel models for indoor LiFi systems are
proposed. Precisely, the statistics of the channel gain are derived for the
case of randomly oriented stationary and mobile LiFi receivers. For stationary
users, two channel models are proposed, namely, the modified truncated Laplace
(MTL) model and the modified Beta (MB) model. For LiFi users, two channel
models are proposed, namely, the sum of modified truncated Gaussian (SMTG)
model and the sum of modified Beta (SMB) model. Based on the derived models,
the impact of random orientation and spatial distribution of LiFi users is
investigated, where we show that the aforementioned factors can strongly affect
the channel gain and system performance
Physical Layer Security for Visible Light Communication Systems:A Survey
Due to the dramatic increase in high data rate services and in order to meet
the demands of the fifth-generation (5G) networks, researchers from both
academia and industry are exploring advanced transmission techniques, new
network architectures and new frequency spectrum such as the visible light
spectra. Visible light communication (VLC) particularly is an emerging
technology that has been introduced as a promising solution for 5G and beyond.
Although VLC systems are more immune against interference and less susceptible
to security vulnerabilities since light does not penetrate through walls,
security issues arise naturally in VLC channels due to their open and
broadcasting nature, compared to fiber-optic systems. In addition, since VLC is
considered to be an enabling technology for 5G, and security is one of the 5G
fundamental requirements, security issues should be carefully addressed and
resolved in the VLC context. On the other hand, due to the success of physical
layer security (PLS) in improving the security of radio-frequency (RF) wireless
networks, extending such PLS techniques to VLC systems has been of great
interest. Only two survey papers on security in VLC have been published in the
literature. However, a comparative and unified survey on PLS for VLC from
information theoretic and signal processing point of views is still missing.
This paper covers almost all aspects of PLS for VLC, including different
channel models, input distributions, network configurations,
precoding/signaling strategies, and secrecy capacity and information rates.
Furthermore, we propose a number of timely and open research directions for
PLS-VLC systems, including the application of measurement-based indoor and
outdoor channel models, incorporating user mobility and device orientation into
the channel model, and combining VLC and RF systems to realize the potential of
such technologies
Measurements-Based Channel Models for Indoor LiFi Systems
Light-fidelity (LiFi) is a fully-networked bidirectional optical wireless
communication (OWC) that is considered a promising solution for high-speed
indoor connectivity. Unlike in conventional radio frequency wireless systems,
the OWC channel is not isotropic, meaning that the device orientation affects
the channel gain significantly. However, due to the lack of proper channel
models for LiFi systems, many studies have assumed that the receiver is
vertically upward and randomly located within the coverage area, which is not a
realistic assumption from a practical point of view. In this paper, novel
realistic and measurement-based channel models for indoor LiFi systems are
proposed. Precisely, the statistics of the channel gain are derived for the
case of randomly oriented stationary and mobile LiFi receivers. For stationary
users, two channel models are proposed, namely, the modified truncated Laplace
(MTL) model and the modified Beta (MB) model. For LiFi users, two channel
models are proposed, namely, the sum of modified truncated Gaussian (SMTG)
model and the sum of modified Beta (SMB) model. Based on the derived models,
the impact of random orientation and spatial distribution of LiFi users is
investigated, where we show that the aforementioned factors can strongly affect
the channel gain and system performance
Caracterisation De La Consommation Des Produits Laitiers Chez Les Etudiants De L’universite Ibn Tofail, Kenitra, Maroc: Etude Descriptive
This work studies the consumption by students of the University Ibn Tofail (Morocco) of a number of dairy products, including milk, yogurt, cheese and butter. The survey sample of the population was random and was composed of 314 students; (58.6% women and 41.4% men). The results of the survey show that 89% of the surveyed population consume dairy products while 11% did not consume them. Of those, 57.3% of the population prefer to consume pasteurized milk and 36% prefer fresh milk, 84% consume yogurt, 84% consume cheese, 55% consume butter and 75% consume milk-based nutraceuticals. The study explored reasons for not consuming more dairy products. 57% of the population surveyed responded that the price of the product is the main reason for not consuming more, 11.8% of this population responded that it is a lack of interest in the product and distrust of the nutritional value of the products, while 19.8% of the population suggested that the lack of availability of these products in the market is the cause
Bidirectional Optical Spatial Modulation for Mobile Users: Towards a Practical design for LiFi Systems
Among the challenges of realizing the full potential of light-fidelity (LiFi)
cellular networks are user mobility, random device orientation and blockage. We
study the impact of those challenges on the performance of LiFi in an indoor
environment using measurement-based channel models. We adopt spatial modulation
(SM), which has been shown to be energy efficient in many applications,
including LiFi. We consider two configurations for placing the photodiodes
(PDs) on the user equipment (UE). The first one is referred to as the screen
receiver (SR) whereby all the PDs are located on one face of the UE, whereas
the other one is a multi-directional receiver (MDR), in which the PDs are
located on different sides of the UE. The latter configuration was motivated by
the fact that SR exhibited poor performance in the presence of random device
orientation and blockage. We show that MDR outperforms SR by over dB at
BER of . Moreover, an adaptive access point (AP) selection
scheme for SM is considered where the number of APs are chosen adaptively in an
effort to achieve the lowest energy requirement for a target BER and spectral
efficiency. The user performance with random orientation and blockage in the
whole room is evaluated for sitting and walking activities. For the latter, we
invoke the orientation-based random waypoint (ORWP) mobility model. We also
study the performance of the underlying system on the uplink channel where the
same techniques are used for the downlink channel. Specifically, as the
transmitted uplink power is constrained, the energy efficiency of SM is
evaluated analytically. It is shown that the multi-directional transmitter
(MDT) with adaptive SM is highly energy efficient. As a benchmark, we compare
the performance of the proposed framework to that of the conventional spatial
multiplexing system, and demonstrate the superiority of the proposed one.Comment: 30 pages, 14 figures, Journal pape