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Ultra-wideband (UWB) is a very attractive technology for innovative in-car wireless communications requiring high data rates. A designated antenna, which presents a reflection coefficient (S11) matched band comparable to the band-pass filter (BPF) normally required at the transducers, plays a positive contribution in this in-car application and was validated for the scenario. The inherited BPF-like response of the antenna relaxes the specification of the front-end BPF components of the transceivers. The in-car propagation channel was modelled and used to validate the BPF-like antenna. For the modelling, a comprehensive set of well-defined measurements (using a standard antenna) were used to set-up the in-car channel simulator and simulated results were used to validate the BPF-like antenna. In addition, the performance of the UWB radio system is studied and the probability of errors over the communication channel compared using the standard and the BPF-like antenna by predictions. ; This work has been part-funded by the European Union.

Mobile ad hoc (MANET) network is a collection of wireless mobile nodes dynamically form-ing a temporary network without the use of any existing network infrastructure or centralized administration. To accomplish forwarding a packet to its destination, a routing protocol is used to discover routes between these nodes. This article presents a variety of results for packet-level simulations for the popular protocol—dynamic source routing (DSR)—when different channel models are used. Different radio propagation models representing the wireless channel have been proposed over the years, each one being suitable for a certain situation. The simplest model that represents wireless propagation is the freespace model. Other propagation models are the tworay ground reflection model and the shadowing model. Simulation results show that the performance metrics are highly affected by the channel model used, even the energy left or the number of nodes left alive are also different.

Taking a cue from the Internet of Things, the Internet of Bodies (IoB) can be defined as a network of smart objects placed in, on, and around the human body, allowing for intra- and inter-body communications. This position paper aims to provide a glimpse into the opportunities created by implantable, injectable, ingestible, and wearable IoB devices. The paper starts with a thorough discussion of application-specific design goals, technical challenges, and enabling of communication standards. We discuss the reason that the highly radiative nature of radio frequency (RF) systems results in inefficient systems due to over-extended coverage that causes interference and becomes susceptible to eavesdropping. Body channel communication (BCC) presents an attractive, alternative wireless technology by inherently coupling signals to the human body, resulting in highly secure and efficient communications. The conductive nature of body tissues yields a better channel quality, while the BCC's operational frequency range (1-100 kHz) eliminates the need for radio front-ends. State-of-the-art BCC transceivers can reach several tens of Mbps data rates at pJ/b energy efficiency levels that support IoB devices and applications. Furthermore, as the cyber and biological worlds meet, security risks and privacy concerns take center stage, leading to a discussion of the multi-faceted legal, societal, ethical, and political issues related to technology governance.

In this paper, an enhancement of a hybrid simulation technique based on combining collaborative filtering with deterministic 3D ray launching algorithm is proposed. Our approach implements a new methodology of data depuration from low definition simulations to reduce noisy simulation cells. This is achieved by processing the maximum number of permitted reflections, applying memory based collaborative filtering, using a nearest neighbors' approach. The depuration of the low definition ray launching simulation results consists on discarding the estimated values of the cells reached by a number of rays lower than a set value. Discarded cell values are considered noise due to the high error that they provide comparing them to high definition ray launching simulation results. Thus, applying the collaborative filtering technique both to empty and noisy cells, the overall accuracy of the proposed methodology is improved. Specifically, the size of the data collected from the scenarios was reduced by more than 40% after identifying and extracting noisy/erroneous values. In addition, despite the reduced amount of training samples, the new methodology provides an accuracy gain above 8% when applied to the real-world scenario under test, compared with the original approach. Therefore, the proposed methodology provides more precise results from a low definition dataset, increasing accuracy while exhibiting lower complexity in terms of computation and data storage. The enhanced hybrid method enables the analysis of larger complex scenarios with high transceiver density, providing coverage/capacity estimations in the design of heterogeneous IoT network applications. ; This work was supported in part by the European Commission LOCARD Project under Grant 832735 and under Project RTI2018-095499-B-C32 and Project RTI2018-095499-B-C31, and in part by the Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (MCIU/AEI/FEDER, UE). The work of Agusti Solanas was supported in part by the Government of Catalonia (GC) under Grant 2017-DI-002 and Grant 2017-SGR-896, and in part by the Fundació PuntCAT with the Vinton Cerf Distinction.

In this paper we thoroughly analyze two alternatives to replicate the bursty behavior that characterizes real indoor wireless channels within Network Simulation platforms. First, we study the performance of an improved Hidden Markov Process model, based on a time-wise configuration so as to decouple its operation from any particular traffic pattern. We compare it with the behavior of Bursty Error Model Based on an Auto-Regressive Filter, a previous proposal of ours that emulates the received Signal to Noise Ratio by means of an auto-regressive filter that captures the "memory" assessed in real measurements. We also study the performance of one of the legacy approaches intrinsically offered by most network simulation frameworks. By means of a thorough simulation campaign, we demonstrate that our two models are able to offer a much more realistic behavior, yet maintaining an affordable response in terms of computational complexity. ; The authors would like to express their gratitude to the Spanish government for its funding in the project "Connectivity as a Service: Access for the Internet of the Future", COSAIF (TEC2012-38574-C02-01)

The ability to exchange secret information is critical to many commercial, governmental, and military networks. Wireless sensor intrinsic secrecy is essential for communication confidentiality, health privacy, public safety, information superiority, and economic advantage in the modern information society. Wireless Sensor security schemes have typically evolved from those developed for traditional wire line applications, these schemes do not consider physical properties of the wireless channels. To overcome these problems, this research work develops a foundation for design and analysis of wireless sensor networks with secrecy provided by intrinsic properties such as node spatial distribution, wireless propagation medium, and aggregate network interference.

Transportation systems are critical for society, as the persistent pace of economic growth and increase of demands are closely related to more transportation activity. In this framework, the field of Intelligent Transportation Systems (ITS) has emerged as a research trending topic to enhance and address new traffic-system challenges. Platooning systems represent a relatively simple approach in terms of deployment towards fuel efficient solutions, traffic congestion reduction, and road safety improvements. In particular, vehicle platoon is a specific formation by a group of coordinated vehicles, in which a short inter-vehicle distance is maintained by virtue of automation and vehicular communication technologies. The deployment of such systems are closely related to a careful evaluation of the synergy between both core technologies.In this thesis, we formulate and analyze a class of platooning problems by addressing communication and control aspects with the related challenges introduced by the overlap of both areas. We first evaluate the robustness of the platoon performance under severe conditions for Vehicle-to-Vehicle (V2V) communications, expressed in long bursts of losses and in difficult traffic jamming conditions on the road. We propose a dynamic control mechanism where the parameters of the well-known Predicted Cooperative Adaptive Cruise Control (PCACC) are adapted based on the observed network link quality.The network reliability is of utmost importance as it limits the control system operation. In order to overcome the impact of dropped and delayed messages, we propose an analytical modeling of a novel V2V relaying scheme and a study of the impact of Roadside Unit (RSU) relaying as alternatives to extend the coverage range of the leader message. We start by developing a Markov model for the different communication links, and we carefully evaluate the impact of network parameters (errors and delays) on the controller performance (inter-vehicle distance). This is done by integrating the resulting packet error rate with the delay distribution and evaluating its impact on the platoon performance.The analysis formulated so far is narrowed to improve the performance of the platoon system while carefully considering the presence of a large number of point-to-point V2V links. Despite significant, we lack an explicit evaluation to quantify such developments in terms of fuel consumption, which is the most important aspect from the economical perspective and feasibility of platooning for commercial purposes. In this context, the last objective in this thesis is to address explicitly the fuel consumption problem in platooning systems. We reduce the fuel consumption attainable by the switching of two control policies, Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC), in platooning systems. Among the propositions, we adopt Deep Reinforcement Learning (DRL) techniques as an alternative solution to indirectly control the system. The carried out simulations demonstrate the feasibility of our scheme even under strong traffic congestion. ; Les systèmes de transport sont essentiels pour la société, car le rythme soutenu de la croissance économique est étroitement lié à l'accroissement des activités de transport. Dans ce contexte, le domaine des systèmes de transport intelligents (ITS) est apparu comme un sujet de recherche d'actualité pour améliorer et relever les nouveaux défis des systèmes de circulation. Les systèmes de pelotons représentent une approche relativement simple en termes de déploiement vers des solutions économes en carburant, la réduction de la congestion du trafic et l'amélioration de la sécurité routière. En particulier, le peloton de véhicules est une formation spécifique par un groupe de véhicules coordonnés, dans laquelle une courte distance inter-véhicules est maintenue grâce à l'automatisation et aux technologies de communication entre véhicules. Le déploiement de tels systèmes est étroitement lié à une évaluation minutieuse de la synergie entre les deux technologies de base.Dans cette thèse, nous formulons et analysons une classe de problèmes de platooning en abordant les aspects de communication et de contrôle avec les défis connexes introduits par le chevauchement de ces deux domaines. Nous évaluons d'abord la robustesse de la performance du platoon dans des conditions sévères pour les communications Véhicule-à-Véhicule (V2V), exprimées par de longues rafales de pertes et dans des conditions difficiles de brouillage sur la route. Nous proposons un mécanisme de contrôle dynamique dans lequel les paramètres du schéma de contrôle le plus avancé, le Predicted Cooperative Adaptive Cruise Control (PCACC), sont adaptés en fonction de la qualité observée de l'interface radio. La fiabilité du réseau est de la plus haute importance car elle limite le fonctionnement du système de contrôle. Afin de surmonter l'impact des messages abandonnés et retardés, nous proposons une modélisation analytique d'un nouveau schéma de relais V2V et une étude de l'impact du relais des unités de bord de route (RSU) comme alternatives pour étendre la couverture du message du véhicule en tête du peloton. Nous commençons par développer un modèle de Markov pour les différents liens de communication, et nous évaluons soigneusement l'impact des paramètres du réseau (erreurs et retards) sur la performance du contrôleur (distance inter-véhicules). Pour ce faire, nous intégrons le taux d'erreurs de paquets résultant à la distribution des retards et évaluons son impact sur les performances du peloton.L'analyse formulée jusqu'à présent est limitée à l'amélioration des performances du système de peloton tout en considérant soigneusement la présence d'un grand nombre de liaisons V2V point à point. Malgré cette importance, nous manquons d'une évaluation explicite pour quantifier ces développements en termes de consommation de carburant, qui est l'aspect le plus important du point de vue économique et de la faisabilité du platooning à des fins commerciales. Dans ce contexte, le dernier objectif de cette thèse est d'aborder explicitement le problème de la consommation de carburant dans les systèmes de platooning. Nous réduisons la consommation de carburant atteignable par la commutation de deux politiques de contrôle, le contrôle de vitesse adaptatif (ACC) et le contrôle de vitesse adaptatif coopératif (CACC), dans les systèmes de platooning. Parmi d'autres propositions, nous adoptons des techniques d'apprentissage par renforcement profond (DRL) comme solution alternative pour contrôler indirectement le système. Les simulations effectuées démontrent la faisabilité de notre système, même en cas de forte congestion du trafic.