Yes / Existing works on energy harvesting wireless systems often assume a constant conversion efficiency for the energy harvester. In practice, the conversion efficiency often varies with the input power. In this work, based on a review of existing energy harvesters in the literature, a heuristic expression for the conversion efficiency as a function of the input power is derived by curve fitting. Using this function, two example energy harvesters are used to analyze the realistic performances of wireless relaying and wireless energy transfer. Numerical results show that the realistic performances of the wireless systems could be considerably different from what predicted by the existing analysis.

Over the past fifteen years, advances in Micro-Electro-Mechanical Systems (MEMS) technology have enabled rapid development of wireless sensor networks (WSNs). A WSN consists of a large number of sensor nodes that are typically powered by batteries. Each sensor node collects useful information from its environment, and forwards this data to a base station through wireless communications. Applications of WSNs include environmental monitoring, industrial monitoring, agriculture, smart home monitoring, military surveillance, to name a few. Due to battery constraint at each sensor node, a fundamental challenge for a WSN is its limited operational lifetime -- the amount of time that the network can remain operational before some or all of the sensor nodes run out of battery. To conserve energy and prolong the lifetime of a WSN, there have been active research efforts across all network layers. Although these efforts help conserve energy usage and prolong network lifetime to some extent, energy and lifetime remain fundamental bottlenecks and are the key factors that hinder the wide-scale deployment of WSNs. This dissertation addresses the energy problem of a WSN by exploiting a recent breakthrough in wireless energy transfer (WET) technology. This breakthrough WET technology is based on the so-called magnetic resonant coupling (MRC), which allows electric energy to be transferred from a source coil to a receive coil without any plugs or wires. The advantages of MRC are high energy transfer efficiency even under omni-direction, not requiring line-of-sight (LOS), and being robust against environmental conditions. Inspired by this enabling WET technology, this dissertation focuses on applying MRC to a WSN and on studying how to optimally use this technology to address lifetime problem for a WSN. The goal is to fundamentally remove lifetime bottleneck for a WSN. The main contributions of this dissertation are summarized as follows: 1. Single-node Charging for a Sparse WSN. We first investigate how MRC can be applied to a WSN so as to remove the lifetime performance bottleneck in a WSN, i.e., allowing a WSN to remain operational forever. We consider the scenario of a mobile wireless charging vehicle (WCV) periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions for a sensor node to maintain its renewable energy cycle. We study an optimization problem, with the objective of maximizing the ratio of the WCV's vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and uncover a number of important properties. Subsequently, we develop a near-optimal solution by a piecewise linear approximation technique and prove its performance guarantee. This first study shows that network lifetime bottleneck can be fundamentally resolved by WET. 2. Multi-node Charging for a Dense WSN. We next exploit recent advances in MRC that allows multiple sensor nodes to be charged at the same time, and show how MRC with multi-node charging capability can address the scalability problem associated with the single-node charging technology. We consider a WCV that periodically travels inside a WSN and can charge multiple sensor nodes simultaneously. Based on the charging range of the WCV, we propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal cells. We pursue a formal optimization framework by jointly optimizing the traveling path of the WCV, flow routing among the sensor nodes, and the charging time with each hexagonal cell. By employing discretization and a novel Reformulation-Linearization Technique (RLT), we develop a provably near-optimal solution for any desired level of accuracy. Through numerical results, we demonstrate that our solution can indeed address the scalability problem for WET in a dense WSN. 3. Bundling Mobile Base Station and Wireless Energy Transfer: The Pre-planned Path Case. Our aforementioned work is based on the assumption that the location of base station is fixed and known in the WSN. On the other hand, it has been recognized that a mobile base station (MBS) can offer significant advantages over a fixed one. But employing two separate vehicles, one for WET and one for MBS, could be expensive and hard to manage. So a natural question to ask is: can we bundle WET and MBS on the same vehicle? This is the focus of this study. Here, our goal is to minimize energy consumption of the entire system while ensuring that none of the sensor nodes runs out of energy. To simplify the problem, we assume that the path for the vehicle is given a priori. We develop a mathematical model for this problem. Instead of studying the general problem formulation (called CoP-t), which is time-dependent, we show that it is sufficient to study a special subproblem (called CoP-s), which only involves space-dependent variables. Subsequently, we develop a provable near-optimal solution to CoP-s with the development of several novel techniques including discretizing a continuous path into a finite number of segments and representing each segment with worst-case energy bounds. 4. Bundling Mobile Base Station and Wireless Energy Transfer: The Unconstrained Path Case. Based on our experience for the pre-planned path case, we further study the problem where the traveling path of the WCV (also carrying the MBS) can be unconstrained. That is, we study an optimization problem that jointly optimizes the traveling path, stopping points, charging schedule, and flow routing. For this problem, we propose a two-step solution. First, we study an idealized problem that assumes zero traveling time, and develop a provably near-optimal solution to this idealized problem. In the second step, we show how to develop a practical solution with non-zero traveling time and quantify the performance gap between this solution and the unknown optimal solution to the original problem. This dissertation offers the first systematic investigation on how WET (in particular, the MRC technology) can be exploited to address lifetime bottleneck of a WSN. It lays the foundation of exploring WET for WSNs and other energy-constrained wireless networks. On the mathematical side, we have developed or applied a number of powerful techniques such as piecewise linear approximation, RLT, time-space transformation, discretization, and logical point representation that may be applicable to address a broad class of optimization problems in wireless networks. We expect that this dissertation will open up new research directions on many interesting networking problems that can take advantage of the WET technology. / Ph. D.

This report is about how to design and fabricated a wireless energy transfer system which is printed on flexible photo paper. That is a technology used to print conducting tracks on paper, or even entire circuit system. The circuit of wireless energy transmission is half bridge converter with spiral coil as the inductance which are etching in primary side and printing in secondary side.The procedure of fabrication will be introduced. While realizing the feasible simulation circuit, the optimal transmission energy system components are mounted according to the requirements. While looking for the best efficiency, it’s also neccessary to consider the appropriate size of the system. In the end of this report there will be some analysis which is aimed to identify where the largest electrical losses are located. Compared with ordinary PCB circuit board, printed circuit on paper makes the whole system very flexible and portable. When the primary side as close with secondary side, The efficiency is almost 72% while the 60Ω as the load. The output power is 10.68w. On the other hand, the ink of printed circuit on paper has high resistivity, which affects the efficiency of radio power system. However, for different paper substrates, the efficiency of wireless charging system will not be affected.

Šiandien neįsivaizduojame savo gyvenimo be daugybės elektrą naudojančių prietaisų, kurie su elektros šaltiniu sujungti elektros laidais. Daugybė besipainiojančių laidų tikrai nepadaro mūsų gyvenimo lengvesnio ir patogesnio. Dar labiau komplikuoja situacijas, kai neįmanoma panaudoti laidų ir prisijungti prie energijos šaltinio. Visi šie nepatogumai skatina ieškoti išeities, kuri galėtų būti energijos perdavimas be laidų. Bevielės elektros idėja buvo iškelta jau prieš daugiau kaip šimtą metų, tai buvo išradėjo Nikola Tesla mintis. Darbui nagrinėti pagamintas bevielės energijos perdavimo demonstracinis modelis. Modelyje nagrinėjama bevielės energijos perdavimo sistema, veikimo principas, siunčiamos energijos nuotolis, perduodamos energijos efektyvumas bei gaunami nuostoliai. / Today can not imagine our life without many electricity using devices are connected to a source of electrical power lines. Numerous trailing wires really does not make our lives easier and more comfortable. Even more complicated situations when there are no opportunities to use wire and to connect to a power source. All these inconveniences are promoting to search the solution wich could be the transfer of energy without wires. Wireless energy idea has been raised for more than a hundred years ago. The thought was inventor inventored by Nikola Tesla. Analyzing this work there was made a demonstration model of wireless power transmission. In this model there is analyzing such things as wireless transmission system, working principal, transmitted energy distance and obtained losses.

Energy harvesting can be used to consume the potential power of the surrounding environment. This harvesting can be done in different ways, some common energy harvesting modalities are vibrations, heat differences, solar power, and RF energy. In this Master Thesis, these different methods for harvesting energy are studied and the one that is the most suitable for an environment inside an embankment dam is further explored. If some energy harvesting modalities can operate well in that environment then it might be possible to monitor the embankment dam from the inside. The hope is to create an energy harvesting platform equipped with some suitable sensors which can be placed inside an embankment dam and collect data for a longer duration of time. Considering how an embankment dam is structured, it was concluded that the best possible energy harvesting method is wireless ultra-high frequency radio signals. An RF energy harvesting platform was created and tested, both in a laboratory and buried underground, mimicking the environment inside an embankment dam. These tests were measured and the results showed some promise that it is possible to use this energy harvesting method to power a sensor platform underground.

This research has its basis in developments within the field of inductive powering and wireless power transfer, WPT, and more specifically one the branch within this field, which is called magnetic resonance coupling. This principle enables efficient power transfer from a transmitting unit to a receiving unit at a distance of some times the unit diameter. The developments within magnetic resonant coupling are together with the possibilities and challenges of today’s smart textile industry the starting point to investigate a novel textile-based product concept for WPT by combining both technologies. Multiple textile samples, consisting of cotton and electrically conductive copper yarns, were produced by weaving technique, additional assembling of electronic components were performed manually and several measurements were carried out to investigate the sample characteristics and the sample performance in terms of power transfer. The produced samples showed to behave similarly to conventional inductors and were able to transfer power over some distance.

A typical model for real-time status update systems consists of a transmitter node that generates real-time status updates about some physical process(es) of interest and sends them through a communication network to a destination node. Such a model can be used to analyze the performance of a plethora of emerging Internet of Things (IoT)-enabled real-time applications including healthcare, factory automation, autonomous vehicles, and smart homes, to name a few. The performance of these applications highly depends upon the freshness of the information status at the destination node about its monitored physical process(es). Because of that, the main design objective of such real-time status update systems is to ensure timely delivery of status updates from the transmitter node to the destination node. To measure the freshness of information at the destination node, the Age of Information (AoI) has been introduced as a performance metric that accounts for the generation time of each status update (which was ignored by conventional performance metrics, specifically throughput and delay). Since then, there have been two main research directions in the AoI research area. The first direction aimed to analyze/characterize AoI in different queueing-theoretic models/disciplines, and the second direction was focused on the optimization of AoI in different communication systems that deal with time-sensitive information. However, the prior queueing-theoretic analyses of AoI have mostly been limited to the characterization of the average AoI and the prior studies developing AoI/age-aware scheduling/transmission policies have mostly ignored the energy constraints at the transmitter node(s). Motivated by these limitations, this dissertation develops new queueing-theoretic methods that allow the characterization of the distribution of AoI in several classes of status updating systems as well as novel AoI-aware scheduling policies accounting for the energy constraints at the transmitter nodes (for several settings of communication networks) in the process of decision-making using tools from optimization theory and reinforcement learning. The first part of this dissertation develops a stochastic hybrid system (SHS)-based general framework to facilitate the analysis of characterizing the distribution of AoI in several classes of real-time status updating systems. First, we study a general setting of status updating systems, where a set of source nodes provide status updates about some physical process(es) to a set of monitors. For this setting, the continuous state of the system is formed by the AoI/age processes at different monitors, the discrete state of the system is modeled using a finite-state continuous-time Markov chain, and the coupled evolution of the continuous and discrete states of the system is described by a piecewise linear SHS with linear reset maps. Using the notion of tensors, we derive a system of linear equations for the characterization of the joint moment generating function (MGF) of an arbitrary set of age processes in the network. Afterwards, we study a general setting of gossip networks in which a source node forwards its measurements (in the form of status updates) about some observed physical process to a set of monitoring nodes according to independent Poisson processes. Furthermore, each monitoring node sends status updates about its information status (about the process observed by the source) to the other monitoring nodes according to independent Poisson processes. For this setup, we develop SHS-based methods that allow the characterization of higher-order marginal/joint moments of the age processes in the network. Finally, our SHS-based framework is applied to derive the stationary marginal and joint MGFs for several queueing disciplines and gossip network topologies, using which we derive closed-form expressions for marginal/joint high-order statistics of age processes, such as the variance of each age process and the correlation coefficients between all possible pairwise combinations of age processes. In the second part of this dissertation, our analysis is focused on understanding the distributional properties of AoI in status updating systems powered by energy harvesting (EH). In particular, we consider a multi-source status updating system in which an EH-powered transmitter node has multiple sources generating status updates about several physical processes. The status updates are then sent to a destination node where the freshness of each status update is measured in terms of AoI. The status updates of each source and harvested energy packets are assumed to arrive at the transmitter according to independent Poisson processes, and the service time of each status update is assumed to be exponentially distributed. For this setup, we derive closed-form expressions of MGF of AoI under several queueing disciplines at the transmitter, including non-preemptive and source-agnostic/source-aware preemptive in service strategies. The generality of our analysis is demonstrated by recovering several existing results as special cases. A key insight from our characterization of the distributional properties of AoI is that it is crucial to incorporate the higher moments of AoI in the implementation/optimization of status updating systems rather than just relying on its average (as has been mostly done in the existing literature on AoI). In the third and final part of this dissertation, we employ AoI as a performance metric for several settings of communication networks, and develop novel AoI-aware scheduling policies using tools from optimization theory and reinforcement learning. First, we investigate the role of an unmanned aerial vehicle (UAV) as a mobile relay to minimize the average peak AoI for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. This optimization problem is subject to the UAV's mobility constraints and the total available energy constraints at the source node and UAV. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytically. A key insight obtained from our results is that the optimal design of the UAV's flight trajectory achieves significant performance gains especially when the available energy at the source node and UAV is limited and/or when the size of the update packet is large. Afterwards, we study a generic system setup for an IoT network in which radio frequency (RF)-powered IoT devices are sensing different physical processes and need to transmit their sensed data to a destination node. For this generic system setup, we develop a novel reinforcement learning-based framework that characterizes the optimal sampling policy for IoT devices with the objective of minimizing the long-term weighted sum of average AoI values in the network. Our analytical results characterize the structural properties of the age-optimal policy, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. They further demonstrate that the structures of the age-optimal and throughput-optimal policies are different. Finally, we analytically characterize the structural properties of the AoI-optimal joint sampling and updating policy for wireless powered communication networks while accounting for the costs of generating status updates in the process of decision-making. Our results demonstrate that the AoI-optimal joint sampling and updating policy has a threshold-based structure with respect to different system state variables. / Doctor of Philosophy / A typical model for real-time status update systems consists of a transmitter node that generates real-time status updates about some physical process(es) of interest and sends them through a communication network to a destination node. Such a model can be used to analyze the performance of a plethora of emerging Internet of Things (IoT)-enabled real-time applications including healthcare, factory automation, autonomous vehicles, and smart homes, to name a few. The performance of these applications highly depends upon the freshness of the information status at the destination node about its monitored physical process(es). Because of that, the main design objective of such real-time status update systems is to ensure timely delivery of status updates from the transmitter node to the destination node. To measure the freshness of information at the destination node, the Age of Information (AoI) has been introduced as a performance metric that accounts for the generation time of each status update (which was ignored by conventional performance metrics, specifically throughput and delay). Since then, there have been two main research directions in the AoI research area. The first direction aimed to analyze/characterize AoI in different queueing-theoretic models/disciplines, and the second direction was focused on the optimization of AoI in different communication systems that deal with time-sensitive information. However, the prior queueing-theoretic analyses of AoI have mostly been limited to the characterization of the average AoI and the prior studies developing AoI/age-aware scheduling/transmission policies have mostly ignored the energy constraints at the transmitter node(s). Motivated by these limitations, this dissertation first develops new queueing-theoretic methods that allow the characterization of the distribution of AoI in several classes of status updating systems. Afterwards, using tools from optimization theory and reinforcement learning, novel AoI-aware scheduling policies are developed while accounting for the energy constraints at the transmitter nodes for several settings of communication networks, including unmanned aerial vehicles (UAVs)-assisted and radio frequency (RF)-powered communication networks, in the process of decision-making. In the first part of this dissertation, a stochastic hybrid system (SHS)-based general framework is first developed to facilitate the analysis of characterizing the distribution of AoI in several classes of real-time status updating systems. Afterwards, this framework is applied to derive the stationary marginal and joint moment generating functions (MGFs) for several queueing disciplines and gossip network topologies, using which we derive closed-form expressions for marginal/joint high-order statistics of age processes, such as the variance of each age process and the correlation coefficients between all possible pairwise combinations of age processes. In the second part of this dissertation, our analysis is focused on understanding the distributional properties of AoI in status updating systems powered by energy harvesting (EH). In particular, we consider a multi-source status updating system in which an EH-powered transmitter node has multiple sources generating status updates about several physical processes. The status updates are then sent to a destination node where the freshness of each status update is measured in terms of AoI. For this setup, we derive closed-form expressions of MGF of AoI under several queueing disciplines at the transmitter. The generality of our analysis is demonstrated by recovering several existing results as special cases. A key insight from our characterization of the distributional properties of AoI is that it is crucial to incorporate the higher moments of AoI in the implementation/optimization of status updating systems rather than just relying on its average (as has been mostly done in the existing literature on AoI). In the third and final part of this dissertation, we employ AoI as a performance metric for several settings of communication networks, and develop novel AoI-aware scheduling policies using tools from optimization theory and reinforcement learning. First, we investigate the role of a UAV as a mobile relay to minimize the average peak AoI for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. This optimization problem is subject to the UAV's mobility constraints and the total available energy constraints at the source node and UAV. A key insight obtained from our results is that the optimal design of the UAV's flight trajectory achieves significant performance gains especially when the available energy at the source node and UAV is limited and/or when the size of the update packet is large. Afterwards, we study a generic system setup for an IoT network in which RF-powered IoT devices are sensing different physical processes and need to transmit their sensed data to a destination node. For this generic system setup, we develop a novel reinforcement learning-based framework that characterizes the optimal sampling policy for IoT devices with the objective of minimizing the long-term weighted sum of average AoI values in the network. Our analytical results characterize the structural properties of the age-optimal policy, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. They further demonstrate that the structures of the age-optimal and throughput-optimal policies are different. Finally, we analytically characterize the structural properties of the AoI-optimal joint sampling and updating policy for wireless powered communication networks while accounting for the costs of generating status updates in the process of decision-making. Our results demonstrate that the AoI-optimal joint sampling and updating policy has a threshold-based structure with respect to different system state variables.

Wireless sensor networks (WSN) are one of the most rapidly evolving technical areas right now. They can be used in a lot of different applications, environmental monitoring and health applications being two examples. The sensors can be placed in hazardous and remote environments since there is no need for cabling or manual maintenance. One of the biggest problems and constraints of today's WSNs is the limited energy capacity of the sensor nodes. Eventually they will be power-depleted, and the network will be dead. A solution to this can be wireless energy transfer technology which makes it possible to recharge sensor nodes with the help of a mobile charger and prolong the lifetime of networks.  This thesis aims to investigate how the charging completion time can be reduced by considering that the charger can charge while moving and by controlling its velocity. The charging completion time is the time from when the charger starts charging the first node until it returns to that starting point.  For this, a two-dimensional WSN was defined that contains sensor nodes and a mobile charger. Anchor nodes, which the charger travels between were defined by choosing the nodes with most neighbors within a defined charging radius. The traveling salesman problem were used to find a path that the charger travels along. A simulation environment was developed in Python to execute tests.  The results show that the charging while moving approach with controlled velocity could reduce the charging completion time with up to 20%. It was also ascertained that this approach works better in dense networks than in sparse. / Trådlösa sensornätverk är ett av de snabbast växande tekniska områdena just nu. De har många olika användningsområden, miljöövervakning och olika hälsotillämpningar är två exempel. Sensorerna kan placeras i farliga och avlägsna miljöer eftersom det inte finns något behov av kablar eller manuellt underhåll. Ett av de största problemen och begränsningarna på dagens trådlösa nätverk är den begränsade energikapaciteten hos sensornoderna. Slutligen kommer de att bli tömda på ström och nätverket kommer att dö. En lösning på detta kan vara trådlös strömöverföring vilket gör det möjligt att ladda sensorerna med hjälp av en mobil laddare och därmed förlänga livstiden på nätverket.  Syftet med detta examensarbete är att undersöka hur slutförandetiden för laddningen kan reduceras i betraktande av att laddaren kan ladda när den rör sig samt att reglera laddaren hastighet. Slutförandetiden för laddningen är den tid det tar från att laddaren börjar ladda den första sensor-noden tills att den kommer tillbaka till punkten den startade på.  För att göra detta definierades ett två-dimensionellt trådlöst sensornätverk som bestod av sensornoder och en mobil laddare. Ankarnoder, vilka laddaren rörde sig emellan, definierades genom att hitta de noder med flest antal grannar inom en bestämd laddningsradie. Handelsresandeproblemet användes för att bestämma rutten som laddaren färdas längs. En simuleringsmiljö utvecklades i Python för att utföra testerna i.  Resultaten visar att med laddaren som laddade när den rörde på sig samt hade reglerad hastighet kunde slutförande-tiden för laddning reduceras med upp till 20%. Det kunde även konstateras att detta tillvägagångssätt fungerar bättre i täta nätverk än i glesa.

Les progrès réalisés durant ces dernières années dans le domaine de la microélectronique et notamment vis-à-vis de l’augmentation exponentielle de la densité d’intégration des composants et des systèmes a participé activement à l’apparition et au développement de systèmes portables communicants de plus en plus performants et polyvalents. La R&D dans les technologies de stockage d’énergie n’a pas suivi cette tendance d’évolution très rapide ; ce qui constitue un handicap majeur dans les évolutions futures des systèmes portables. La transmission d’énergie sans fils sur des distances considérables (plusieurs dizaines de mètres) grâce aux microondes constitue une solution très prometteuse pour pallier aux problèmes d’autonomie dans le cas des systèmes sans fils communicants. De plus, du fait de l’omniprésence des ondes électromagnétiques dans notre environnement avec des niveaux plus ou moins importants, la récupération et l’exploitation de cette énergie libre est également possible. La rectenna (Rectifying Antenna) est le dispositif permettant de capter et de convertir une onde électromagnétique en une tension continue. Plusieurs travaux de thèse axés sur l’étude et l’optimisation de la rectenna ont été réalisés au sein du laboratoire. Ces travaux avaient montré que pour des faibles niveaux de champs les tensions délivrées par la rectenna sont généralement très faibles et inexploitables. Aussi, comme la majorité des micro-sources d’énergie et à cause de son impédance interne, les performances de la rectenna dépendent fortement de sa charge de sortie. Ainsi, le développement d’un système d’interfaçage de la rectenna est nécessaire afin de pallier ces manquements inhérents du convertisseur RF/DC. Ce genre de système d’interfaçage est généralement absent dans la littérature à cause des faibles niveaux de puissance exploités. Par conséquent, la rectenna est très souvent utilisée tel quelle ; ce qui limite fortement le champ applicatif. Dans ce projet de recherche, un système de gestion énergétique de la rectenna complètement autonome a été conçu, développé et optimisé afin de garantir les performances optimales de la rectenna quelques soient les fluctuations de la puissance d’entrée et celles de la charge de sortie. Le circuit d’interfaçage permet également de fournir à la charge des niveaux de tension utilisables. Le système réalisé est basé tout d’abord sur l’utilisation d’un convertisseur DC/DC résonant pouvant fonctionner d’une manière complètement autonome à partir de niveaux très bas de la tension et de la puissance de la source. Ce convertisseur permet donc de garantir l’autonomie du système en éliminant la nécessité d’une source d’énergie auxiliaire. A cause de ses faibles performances énergétiques, ce convertisseur ne sera utilisé que durant la phase de démarrage. L’efficacité du système en termes de rendement énergétique et d’adaptation d’impédance est garantie grâce à l’utilisation d’un convertisseur Flyback fonctionnant dans son régime de conduction discontinu. Ainsi, une adaptation d’impédance très efficace est réalisée entre la rectenna et la charge de sortie. Ce convertisseur principal fonctionnera durant le régime permanent. Les deux convertisseurs ont été optimisés pour des niveaux de tension et de puissance aussi bas que quelques centaines de mV et quelques μW respectivement. Des mesures expérimentales réalisées sur plusieurs prototypes ont démontré le bon fonctionnement et les excellentes performances prédites par la procédure de conception ; ce qui nous permet de valider notre approche. De plus, les performances obtenues se distinguent parfaitement vis-à-vis de l’état de l’art. Enfin, en fonction de l’application désirée, plusieurs synoptiques d’association des deux structures sont proposés. Ceci inclut également la gestion énergétique de la charge de sortie. / Latest advancements in microelectronic technologies and especially with the exponential increase of components and devices integration density have yield novel high technology and polyvalent portable systems. Such polyvalent communication devices need more and more available energy. Nonetheless, research in energy storage technology did not evolve with a similar speed. This constitutes a substantial handicap for the future evolution of portable devices. Wireless energy transfer through large distances such as tens of meters using microwaves is a very promising solution in order to deal with the autonomy problem in portable devices. In addition, since electromagnetic waves are ubiquitous in our environment, harvesting and using this free and available energy is also possible. Rectenna (Rectifying Antenna) is the device that allows to collect and to convert an electromagnetic wave into DC power. Several thesis research projects focusing on studying and optimizing the rectenna was carried-out into the Ampere laboratory. It has been shown that for a low level of the electromagnetic field the voltage provided by the rectenna is ultra-low and thus impractical. Further, as it is the case for the majority of energy harvesting micro-sources, the performances of the rectenna depend highly with the loading conditions. So, the development of an interfacing circuit for the rectenna is a necessary task in order to relieve the RF/DC converter inherent flaws. As it is pointed out into the literature, such power management circuit is in most cases absent due to the ultra-low power levels. In most cases, the rectenna is used as it; which reduces strongly the applications area. Within this research project, an ultra-low power and fully-autonomous power management system dedicated to rectennas was developed and optimized. It allows to guarantee highest performances of the rectenna whatever are the fluctuation of the input power level and the output load conditions. In addition, this power management system allows to provide a conventional voltage level to the load. The first part of the developed system is composed by a resonant DC/DC converter which plays the role of start-up circuit. In this case, no external energy source is required even with low voltage and ultra-low power source conditions. Because of its general poor energetic performances, this resonant converter will be used only during the start-up phase. The second part of the developed system is composed by a Flyback converter operating in its discontinuous conduction mode. Using this mode, the converter realizes static and very effective impedance matching with the rectenna in order to extract the maximum available power whatever are the input and the output conditions. Furthermore, thanks to the optimization procedure, the converter shows excellent efficiency performances even for μW power levels based on a discrete demonstrator. Finally, the converter provides conventional voltage levels allowing to power standard electronics. Experimental tests based on discrete prototypes for the both converters show distinguish results for the start-up voltage, the impedance matching effectiveness and the efficiency as regard to the state of the art.