Études des systèmes de communications sans-fil dans un environnement rural difficile

Les systèmes de communication sans fil, ayant de nombreux avantages pour les zones rurales, peuvent aider la population à bien s'y établir au lieu de déménager vers les centres urbains, accentuant ainsi les problèmes d’embouteillage, de pollution et d’habitation. Pour une planification et un déploiement efficace de ces systèmes, l'atténuation du signal radio et la réussite des liens d’accès doivent être envisagées. Ce travail s’intéresse à la provision d’accès Internet sans fil dans le contexte rural canadien caractérisé par sa végétation dense et ses variations climatiques extrêmes vu que les solutions existantes sont plus concentrées sur les zones urbaines. Pour cela, nous étudions plusieurs cas d’environnements difficiles affectant les performances des systèmes de communication. Ensuite, nous comparons les systèmes de communication sans fil les plus connus. Le réseau sans fil fixe utilisant le Wi-Fi ayant l’option de longue portée est choisi pour fournir les communications aux zones rurales. De plus, nous évaluons l'atténuation du signal radio, car les modèles existants sont conçus, en majorité, pour les technologies mobiles en zones urbaines. Puis, nous concevons un nouveau modèle empirique pour les pertes de propagation. Des approches utilisant l’apprentissage automatique sont ensuite proposées, afin de prédire le succès des liens sans fil, d’optimiser le choix des points d'accès et d’établir les limites de validité des paramètres des liens sans fil fiables. Les solutions proposées font preuve de précision (jusqu’à 94 % et 8 dB RMSE) et de simplicité, tout en considérant une multitude de paramètres difficiles à prendre en compte tous ensemble avec les solutions classiques existantes. Les approches proposées requièrent des données fiables qui sont généralement difficiles à acquérir. Dans notre cas, les données de DIGICOM, un fournisseur Internet sans fil en zone rurale canadien, sont utilisées. Wireless communication systems have many advantages for rural areas, as they can help people settle comfortably and conveniently in these regions instead of relocating to urban centers causing various overcrowding, habitation, and pollution problems. For effective planning and deployment of these technologies, the attenuation of the radio signal and the success of radio links must be precisely predicted. This work examines the provision of wireless internet access in the Canadian rural context, characterized by its dense vegetation and its extreme climatic variations, since existing solutions are more focused on urban areas. Hence, we study several cases of difficult environments affecting the performances of communication systems. Then, we compare the best-known wireless communication systems. The fixed wireless network using Wi-Fi, having the long-range option, is chosen to provide wireless access to rural areas. Moreover, we evaluate the attenuation of the radio signal, since the existing path loss models are generally designed for mobile technologies in urban areas. Then, we design a new path loss empirical model. Several approaches are then proposed by using machine learning to predict the success of wireless links, optimize the choice of access points and establish the validity limits for the pertinent parameters of reliable wireless connections. The proposed solutions are characterized by their accuracy (up to 94% and 8 dB RMSE) and simplicity while considering a wide range of parameters that are difficult to consider all together with conventional solutions. These approaches require reliable data, which is generally difficult to acquire. In our case, the dataset from DIGICOM, a rural Canadian wireless internet service provider, is used

Modelling of propagation path loss using adaptive hybrid artificial neural network approach for outdoor environments.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal. Durban, 2018.Prediction of signal power loss between transmitter and receiver with minimal error is an important issue in telecommunication network planning and optimization process. Some of the basic available conventional models in literature for signal power loss prediction includes the Free space, Lee, COST 234 Hata, Hata, Walficsh- Bertoni, Walficsh-Ikegami, dominant path and ITU models. But, due to poor prediction accuracy and lack of computational efficiency of these traditional models with propagated signal data in different cellular network environments, many researchers have shifted their focus to the domain of Artificial Neural Networks (ANNs) models. Different neural network architectures and models exist in literature, but the most popular one among them is the Multi-Layer Perceptron (MLP) ANN which can be attributed to its superb architecture and comparably clear algorithm. Though standard MLP networks have been employed to model and predict different signal data, they suffer due to the following fundamental drawbacks. Firstly, conventional MLP networks perform poorly in handling noisy data. Also, MLP networks lack capabilities in dealing with incoherence datasets which contracts with smoothness. Firstly, in this work, an adaptive neural network predictor which combines MLP and Adaptive Linear Element (ADALINE) is developed for enhanced signal power prediction. This is followed with a resourceful predictive model, built on MLP network with vector order statistic filter based pre-processing technique for improved prediction of measured signal power loss in different micro-cellular urban environments. The prediction accuracy of the proposed hybrid adaptive neural network predictor has been tested and evaluated using experimental field strength data acquired from Long Term Evolution (LTE) radio network environment with mixed residential, commercial and cluttered building structures. By means of first order statistical performance evaluation metrics using Correlation Coefficient, Root Mean Squared Error, Standard Deviation and Mean Absolute Error, the proposed adaptive hybrid approach provides a better prediction accuracy compared to the conventional MLP ANN prediction approach. The superior performance of the hybrid neural predictor can be attributed to its capability to learn, adaptively respond and predict the fluctuating patterns of the reference propagation loss data during training

Aspects of Critical Communications in Disturbance Scenarios

Infrastructures are the foundations of modern societies. The most important ones are the so-called critical infrastructures: mobile networks and electricity networks. If these networks are damaged or otherwise unavailable, the functionality of the whole society is at risk and can result even in public safety hazards. Furthermore, people expect all the time ubiquitous access to internet through mobile networks as many services rely on these wireless networks. The dependence is growing all the time as the number of worldwide subscriptions has already exceeded the world population and the amount of internet of things (IoT) and other connected devices continues to increase exponentially.This thesis focuses on the critical communications aspects of mobile networks during disturbance scenarios. These are defined as situations where, e.g. there is a power blackout in the electricity network, which affects the functionality of the mobile network.The contributions of this thesis can be divided into three main themes. The first one is the actual functionality of mobile networks during disturbance scenarios. This includes finding out how the behavior of subscribers changes when there is an uncommon disturbance scenario in the mobile network and how to prolong the disturbance time functionality of the existing networks. The results show that subscribers utilize mobile networks more than usual already before the power blackout starts when they try to find out information about the status of an upcoming storm. Immediately after the disturbance scenario starts, the subscribers within the blackout area are more active as the statistics show 73 % increase in the number of new calls and 84 % in the amount of short message service (SMS) messages. The results show also that the majority of mobile network availability is lost after 3–4 hours from the start of the incident. In order to prolong this availability time, simulations are performed to find out how utilizing only a portion of the available base station (BS) sites affects the service coverage. The results show that around 20 % of BS sites would be enough to cover 75 % of the original service coverage. Therefore, the operational time of the so-called mobile network backup coverage could be increased several times given that core network (CN) and backhaul network are also operational.The second main theme in this thesis presents a new developed situation awareness system (SAS) that combines the outage information of both mobile and electricity networks. This is an important tool for monitoring the networks and performing disaster and disturbance management. The user interface of the developed SAS is a map view showing the outage information, i.e. the faults, in both networks. It utilizes operational data from both networks such as the coverage outage areas of the mobile network and the outages of transformers in the electricity network in near real-time. The developed SAS helps to prioritize maintenance and repair work to the most critical areas as well as help to form a better overall situation awareness that fire and rescue services and authorities could utilize for improving public safety actions.The last main theme in the thesis considers innovative solutions in order to find out methods to improve the performance, i.e., to mitigate the outage of mobile networks in disturbance scenarios. The three different approaches presented are the indirect guidance of subscribers, the concept of a temporary low altitude platform (LAP) network with the help of drones, and the concept of a macro sensor network (MSN). First, the energy and capacity aspects of mobile networks can be improved when the subscribers are indirectly guided to self-optimize their location in the serving cell area. This can result in serving more user equipment (UEs) within a cell or to decrease the amount of energy needed for transmissions. Next, the coverage aspects of a LAP system are studied in order to find out the suitability of forming a temporary emergency coverage with a wireless local area network (WLAN) equipped drones. The results show that this kind of approach could provide a suitable emergency coverage for a limited area with a reasonable number of drones. Finally, a framework for MSN is studied to investigate the possibility of bringing wireless sensor network (WSN) functionalities into mobile networks. The results show that the concept of MSN could remarkably improve the resilience of mobile networks in situations where the backhaul connection is broken. However, implementing and further developing this kind of functionality will require changes in the 3rd Generation Partnership Project (3GPP) specifications and self-organizing network (SON) features within the network.Overall, this thesis provides insight on how to develop the current and future mobile networks toward more resilient infrastructures. It highlights the importance of critical communications as a fundamental part of modern societies. Thus, securing the functionality and performance of mobile networks in all situations is crucial. As a result, the contributions in this thesis can be utilized as a starting point in the future research to develop new functionalities for mobile networks. One of such approaches can be a safety mode, which would improve the mobile network resiliency during disasters and disturbance scenarios

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Proceedings of the Fifth International Mobile Satellite Conference 1997

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium