For the past 70 years, the Federal Communications Commission (FCC) has been the licensing authority for wireless spectrum. Traditionally, spectrum was commercially licensed to primary users with defined uses. With the growth of personal communication systems in the 1990''s, unallocated spectrum has become a scarce commodity. However, since most primary users are active only at certain times and places, much of the allocated spectrum remains underutilized. Substantial holes exist in the spatio-temporal spectrum that could be opportunistically used by unlicensed secondary users. As a result, the FCC is considering allowing secondary users to opportunistically use frequencies that are not being used by primary users. If multiple secondary users are present in the same geographical area, the concept of Dynamic Spectrum Sharing (DSS) allows these users to share the opportunistic spectrum. If several secondary users want to use a limited set of frequency resources, they will very likely interfere with each other. Sensing is a distributed technique where each transmitter/receiver pair senses (both passively and actively) the available channels and uses the channel that provides the best performance. While sensing alone allows sharing of the spectrum, it is not the optimal method in terms of maximizing the capacity in such a shared system. If we allow the secondary users to collaborate and share information, optimal capacity might be reached. However, collaboration adds another level of complexity to the transceivers of the secondary users, since they must now be able to communicate (Note that in general, the secondary users may have completely different communication protocols, e.g., Wi-Fi and Bluetooth). Additionally, optimizing the capacity of the available spectrum could have other negative side effects such as impacting the fairness of sharing the resources. Our primary goal is to explore the benefit of this cost-benefit tradeoff by determining the capacity increase obtainable from collaboration. As a secondary goal, we also wish to determine how this increase in capacity affects fairness. To summarize, the goal of this work is to answer the question: Fundamentally, what is the benefit of collaboration in Dynamic Spectrum Sharing? / Master of Science

The idea of wireless distributed computing (WDC) is rapidly gaining recognition owing to its promising potential in military, public safety and commercial applications. This concept basically entails distributing a computationally intensive task that one radio device is assigned, among its neighboring peer radio devices. The added processing power of multiple radios can be harnessed to significantly reduce the time consumed in obtaining the results of the original complex task. Since the idea of wireless distributed computing depends on a radio device forming a network with its peers, it is imperative and necessary to have a medium access control (MAC) protocol for such networks which is capable of scheduling channel access by multiple radios in the network, ensuring reliable data transfer, incorporating rate adaptation as well as handling link failures. The thesis presented here elaborates the design and implementation of such a MAC protocol for WDC employed in a practical network of radio devices configurable through software. It also brings to light the design and implementation constraints and challenges faced in this endeavor and puts forward viable solutions. / Master of Science

Wireless communication is increasingly ubiquitous. However, mobility depends intrinsically on battery life. Power can be conserved at the Media Access Control (MAC) layer by intelligently adjusting transmission power level and data rate encoding. WirelessUSB is a low-power, low-latency wireless technology developed by Cypress Semiconductor Corporation for human interface devices such as keyboards and mice. WirelessUSB devices conserve power by employing power-efficient hardware, dynamic power level adjustment and dynamic data rate adjustment. We characterize the effects on power consumption of dynamically adjusting node power using two dynamic power negotiation techniques as well as two reactive techniques. We also characterize the effects of dynamically adjusting data rate using three rate adjustment techniques. We further characterize the effects of collaboratively adjusting both power and data rate. We validate our techniques through simulation and find that such collaboration yields the greatest energy conservation for a wide variety of conditions and usage models.

Le nombre et la complexité croissante des applications qui sont intégrées dans des objets mobiles communicants sans fil (téléphone mobile, PDA, etc.) implique une augmentation de la consommation d'énergie. Afin de limiter l'impact de la pollution due aux déchets des batteries et des émissions de CO2, il est important de procéder à une optimisation de la consommation d'énergie de ces appareils communicants. Cette thèse porte sur l'efficacité énergétique dans les réseaux de capteurs. Dans cette étude, nous proposons de nouvelles approches pour gérer efficacement les objets communicants mobiles. Tout d’abord, nous proposons une architecture globale de réseau de capteurs et une nouvelle approche de gestion de la mobilité économe en énergie pour les appareils terminaux de type IEEE 802.15.4/ZigBee. Cette approche est basée sur l'indicateur de la qualité de lien (LQI) et met en œuvre un algorithme spéculatif pour déterminer le prochain coordinateur. Nous avons ainsi proposé et évalué deux algorithmes spéculatifs différents. Ensuite, nous étudions et évaluons l'efficacité énergétique lors de l'utilisation d'un algorithme d'adaptation de débit prenant en compte les conditions du canal de communication. Nous proposons d'abord une approche mixte combinant un nouvel algorithme d'adaptation de débit et notre approche de gestion de la mobilité. Ensuite, nous proposons et évaluons un algorithme d'adaptation de débit hybride qui repose sur une estimation plus précise du canal de liaison. Les différentes simulations effectuées tout au long de ce travail montrent l’efficacité énergétique des approches proposées ainsi que l’amélioration de la connectivité des nœuds. / The increasing number and complexity of applications that are embedded into wireless mobile communicating devices (mobile phone, PDA, etc.) implies an increase of energy consumption. In order to limit the impact of pollution due to battery waste and CO2 emission, it is important to conduct an optimization of the energy consumption of these communicating end devices. This thesis focuses on energy efficiency in sensor networks. It proposes new approaches to handle mobile communicating objects. First, we propose a global sensor network architecture and a new energy-efficient mobility management approach for IEEE 802.15.4/ZigBee end devices. This new approach is based on the link quality estimator (LQI) and uses a speculative algorithm. We propose and evaluate two different speculative algorithms. Then, we study and evaluate the energy efficiency when using a rate adaptation algorithm that takes into account the communication channel conditions. We first propose a mobility-aware rate adaptation algorithm and evaluate its efficiency in our network architecture. Then, we propose and evaluate a hybrid rate adaptation algorithm that relies on more accurate link channel estimation. Simulations conducted all along this study show the energy-efficiency of our proposed approaches and the improvement of the nodes’ connectivity.

Network Utility Maximization (NUM) provides a key conceptual framework to study reward allocation amongst a collection of users/entities in disciplines as diverse as economics, law and engineering. However when the available resources and/or users' utilities vary over time, reward allocations will tend to vary, which in turn may have a detrimental impact on the users' overall satisfaction or quality of experience. In this thesis, we introduce a generalization of the NUM framework which incorporates the detrimental impact of temporal variability in a user's allocated rewards and explicitly incorporates Mean-Variability-Fairness tradeoffs, i.e., tradeoffs amongst the mean and variability in users' reward allocations, as well as fairness across users. We propose a simple online algorithm to realize these tradeoffs, which, under stationary ergodic assumptions, is shown to be asymptotically optimal, i.e., achieves a long term performance equal to that of an offline algorithm with knowledge of the future variability in the system. This substantially extends work on NUM to an interesting class of relevant problems where users/entities are sensitive to temporal variability in their service or allocated rewards. We extend the theoretical framework and tools developed for realizing Mean-Variability-Fairness tradeoffs to develop a simple online algorithm to solve the problem of optimizing video delivery in networks. The tremendous increase in mobile video traffic projected for the future along with insufficiency of available wireless network capacity makes this one of the most important networking problems today. Specifically, we consider a network supporting video clients streaming stored video, and focus on the problem of jointly optimizing network resource allocation and video clients' video quality adaptation. Our objective is to fairly maximize video clients' video Quality of Experience (QoE) realizing Mean-Variability-Fairness tradeoffs, incorporating client preferences on rebuffering time and the cost of video delivery. We present a simple asymptotically optimal online algorithm NOVA (Network Optimization for Video Adaptation) to solve the problem. Our algorithm uses minimal communication, 'distributes' the tasks of network resource allocation to a centralized network controller, and video clients' video quality adaptation to the respective video clients. Further, the quality adaptation is also optimal for standalone video clients, and is an asynchronous algorithm well suited for use in the Dynamic Adaptive Streaming over HTTP (DASH) framework. We also extend NOVA for use with more general video QoE models, and study NOVA accounting for practical considerations like time varying number of video clients, sharing with other types of traffic, performance under legacy resource allocation policies, videos with variable sized segments etc. / text

Les nouvelles générations de radars sont confrontées à des cibles de plus en plus menaçantes. Ces radars doivent effectuer plusieurs tâches en parallèle, dont la veille et la poursuite. Pour cela, ils peuvent être équipés de panneaux fixes, pour éviter les contraintes liées à la rotation de l'antenne. Le pistage du radar doit donc être renouvelé pour répondre à la double difficulté posée par le pistage des cibles très manoeuvrantes et la gestion des ressources. Dans ce contexte, cette thèse étudie de nouvelles méthodes de pistage pour les cibles hyper-manoeuvrantes. Un nouveau modèle de cible, en coordonnées intrinsèques, est proposé. Ce modèle est exprimé directement dans le repère de la cible, afin de décrire au mieux des manoeuvres fortes avec des accélérations normales bien supérieures à la gravité terrestre. Un algorithme de filtrage utilisant la formulation intrinsèque du modèle est développé. Cet algorithme ayant la même structure qu'une filtre de Kalman étendu, il a été testé sur de vraies données. La comparaison avec d'autres algorithmes de filtrage a montré de réelles améliorations sur un ensemble important de trajectoires. Une nouvelle méthode d'estimation, reposant sur la formulation en termes de moindres carrés de l'approche de lissage, et permettant de tenir compte de sauts dans la trajectoire est également proposée, et les bénéfices sur des méthodes plus classiques de sauts entre modèles sont montrés. Indépendamment, le problème de cadence adaptative est également traité. Un algorithme très général permettant d'optimiser la cadence de mesure pour ménager le budget temps du radar pour la surveillance est présenté. / The new generation of radars is facing increasingly threatening targets. These radars are asked to perform several tasks in parallel, including surveillance and tracking. To this aim, they can be equipped with staring antennas, so they overcome the constraints induced by the rotation of the antenna. The tracking function of the radar has thus to be upgraded to respond to the double issue of tracking highly manoeuvring targets and managing the resources to balance time between tasks. In this context, this thesis investigates new means of tracking highly manoeuvring targets. A new target model based on intrinsic coordinates to perform target tracking is proposed. This new target model is expressed in the frame of the target itself, and uses the Frenet-Serret frame, which is well suited to the description of highly dynamic manoeuvres involving normal accelerations that are much larger than earth gravity. A filtering algorithm using the special intrinsic formulation of the target model is developed. This filtering algorithm is very similar in terms of implementation to an Extended Kalman filter, and was implemented using real data. The comparison with standard target models and filtering algorithms show improvements over simple models and algorithms on a large set of trajectories. A new estimation method, relying on the least squares formulation of the smoothing approach, and taking into account kinematic jumps in the trajectory is also developed. This method also shows improvements over a set of common algorithms based on standard manoeuvre detection. And independently, we investigate the issue of update rate adaptation for radar measurements. A very general update rate adaptation algorithm is derived to optimise the time of revisit of each target, allowing to preserve the radar time budget for other tasks simultaneously performed, such as surveillance.

This work is focused on the issue of wireless networks according to the IEEE 802.11 standard. The main subject of research is the Rate Adaptation Algorithms (RAA). The work also contains a description of simulation environments NS-3 and OMNeT in terms of adaptation algorithms. At the end of the work there is a summary of wireless network simulations in NS-3 and OMNeT environments and their comparison with the actual measurement of network parameters.

Low Latency Low Loss Scalable Throughput (L4S) is a technology which aims to provide high throughput and low latency for the IP traffic, lowering also the probability of packet loss. To reach this goal, it relies on Explicit Con- gestion Notification (ECN), a mechanism to signal congestion in the network avoiding packets drop. The congestion signals are then managed at sender and receiver side thanks to scalable congestion control algorithms. Initially, in this work the challenges to implement L4S in a 5G network have been analyzed. Using a proprietary state-of-the-art network simulator, L4S have been imple- mented at the Packed Data Convergence Protocol layer in a 5G network. The 5G network scenario represents a context where the physical layer has a carrier frequency of 600 MHz, a transmission bandwidth of 9 MHz, and the proto- col stack follows the New Radio (NR) specifications. L4S has been adopted to support Augmented Reality (AR) video gaming traffic, using the IETF ex- perimental standard Self-Clocked Rate Adaptation for Multimedia (SCReAM) for congestion control. The results showed that when supported by L4S, the video gaming traffic experiences lower delay than without L4S support. The improvement on latency comes with an intrinsic trade-off between throughput and latency. In all the cases analyzed, L4S yields to average application layer throughput above the minimum requirements of high-rate latency-critical ap- plication, even at high system load. Furthermore, the packet loss rate has been significantly reduced thanks to the introduction of L4S, and if used in combi- nation with a Delay Based Scheduler (DBS), a packet loss rate very close to zero has been reached. / Low Latency Low Loss Scalable Throughput (L4S) är en teknik som syftar till att ge hög bittakt och låg fördröjning för IP-trafik, vilket också minskar sanno- likheten för paketförluster. För att nå detta mål förlitar det sig på Explicit Cong- estion Notification (ECN), en mekanism för att signalera "congestion", det vill säga köuppbyggnad i nätverket för att undvika att paketet kastas. Congestion- signalerna hanteras sedan vid avsändare och mottagarsida där skalbar anpass- ning justerar bittakten efter rådande omständigheter. I detta arbete har utma- ningarna att implementera L4S i ett 5G-nätverk analyserats. Sedan har L4S implementerats på PDCP lagret i ett 5G-nätverkssammanhang genom att an- vända en proprietär nätverkssimulator. För att utvärdera fördelarna med imple- menteringen har L4S-funktionerna använts för att stödja Augmented Reality (AR) videospelstrafik, med IETF-experimentella standard Self-Clocked Rate Adaptation for Multimedia (SCReAM) för bitrate-kontroll. Resultaten visade att med stöd av L4S upplever videospelstrafiken lägre latens än utan stöd av L4S. Förbättringen av latens kommer med nackdelen av en minskning av bit- takt som dikteras av den inneboende avvägningen mellan bittakt och latens. I vilket fall som helst är kapacitetsminskningen med L4S rimlig, eftersom goda kapacitetsprestanda har uppnåtts även vid hög systembelastning. Vidare har paketförlustfrekvensen reducerats avsevärt tack vare införandet av L4S, och om den används i kombination med en Delay baserad schemaläggare (DBS) har en paketförluster mycket nära noll uppnåtts.

Multimedia services and applications became the driving force in the development and widespread deployment of wireless broadband access technologies and high speed local area networks. Mobile phone service providers are offering wide range of multimedia applications over high speed wireless data networks. People can watch live TV, stream on-demand video clips and place videotelephony calls using multimedia capable mobile devices. Mobile devices will soon support capturing and displaying high definition video. Similar evolution is also occurring in the local area domain. The video receiver or storage devices were conventionally connected to display devices using cables. By using wireless local area networking (WLAN) technologies, convenient and cable-free connectivity can be achieved. Media over wireless home networks prevents the cable mess and provides mobility to portable TVs. However, there still exit challenges for improving the quality-of-service (QoS) of multimedia applications. Conventional service architectures, network structures and protocols lack to provide a robust distribution medium since most of them are not designed considering the high data rate and real-time transmission requirements of digital video. In this thesis the challenges of wireless video streaming are addressed in two main categories. Streaming protocol level issues constitute the first category. We will refer to the collection of network protocols that enable transmitting digital compressed video from a source to a receiver as the streaming protocol. The objective of streaming protocol solutions is the high quality video transfer between two networked devices. Novel application-layer video bit-rate adaptation methods are designed for handling short- and long-term bandwidth variations of the wireless local area network (WLAN) links. Both transrating and scalable video coding techniques are used to generate video bit-rate flexibility. Another contribution of this thesis study is an error control method that dynamically adjusts the forward error correction (FEC) rate based on channel bit-error rate (BER) estimation and video coding structure. The second category is the streaming service level issues, which generally surface in large scale systems. Service system solutions target to achieve system scalability and provide low cost / high quality service to consumers. Peer-to-peer assisted video streaming technologies are developed to reduce the load of video servers. Novel video file segment caching strategies are proposed for more efficient peer-to-peer collaboration.

Opportunistic selection and rate adaptation play a vital role in improving the spectral and power efficiency of current multi-node wireless systems. However, time-variations in wireless channels affect the performance of opportunistic selection and rate-adaptation in the following ways. Firstly, the selected node can become sub-optimal by the time data transmission commences. Secondly, the choice of transmission parameters such as rate and power for the selected node become sub-optimal. Lastly, the channel changes during data transmission. In this thesis, we develop a comprehensive and tractable analytical framework that accurately accounts for these effects. It differs from the extensive existing literature that primarily focuses on time-variations until the data transmission starts. Firstly, we develop a novel concept of a time-invariant effective signal-to-noise ratio (TIESNR), which tractably and accurately captures the time-variations during the data transmission phase with partial channel state information available at the receiver. Secondly, we model the joint distribution of the signal-to-noise ratio at the time of selection and TIESNR during the data transmission using generalized bivariate gamma distribution. The above analytical steps facilitate the analysis of the outage probability and average packet error rate (PER) for a given modulation and coding scheme and average throughput with rate adaptation. We also present extensive numerical results to verify the accuracy of each step of our approach and show that ignoring the correlated time variations during the data transmission phase can significantly underestimate the outage probability and average PER, whereas it overestimates the average throughput even for packet durations as low as 1 msec.