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Broadcast Strategy for Delay-Limited Communication over Fading ChannelsYoo, Jae Won 03 October 2013 (has links)
Delay is an important quality-of-service measure for the design of next-generation wireless networks. This dissertation considers the problem of delay-limited communication over block-fading channels, where the channel state information is available at the receiver but not at the transmitter. For this communication scenario, the difference between the ergodic capacity and the maximum achievable expected rate (the expected capacity) for coding over a finite number of coherent blocks represents a fundamental measure of the penalty incurred by the delay constraint.
This dissertation introduces a notion of worst-case expected-capacity loss. Focusing on the slow-fading scenario (one-block delay), the worst-case additive and multiplicative expected-capacity losses are precisely characterized for the point-to- point fading channel. Extension to the problem of writing on fading paper is also considered, where both the ergodic capacity and the additive expected-capacity loss over one-block delay are characterized to within one bit per channel use.
The problem with multiple-block delay is considerably more challenging. This dissertation presents two partial results. First, the expected capacity is precisely characterized for the point-to-point two-state fading channel with two-block delay. Second, the optimality of Gaussian superposition coding with indirect decoding is established for a two-parallel Gaussian broadcast channel with three receivers. Both results reveal some intrinsic complexity in characterizing the expected capacity with multiple-block delay.
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Vliv odlišných komunikačních schopností na výkon žáka ve škole / Influence of different communication skills to student performance in schoolBÖHMOVÁ, Ivana January 2015 (has links)
The thesis focuses on different communication skills of elementary school children. Fundamental concepts refer to communication disorders; the disturbed and limited communication ability. The theoretical resource defines the communication from different points of view, namely, how the other branches of science (sociology, linguistics, pedagogy and logopedics) deal with the term of communication. Furthermore, the concept of the disturbed and limited communication abilities are closely specified in this part. The conclusion of the theoretical part includes characteristics of Framework Education Programme for Elementary Education, considered to be a pillar of the Czech education system, and its main goals in terms of fulfilling the key competencies in relation to the integration of learners with special educational needs into a mainstream class. The practical analysis was conducted on the basis of survey questionnaire. The collected data from the pedagogical staff members reflect their experinence with the issue of different communicaton skills. The aim is to describe the relationship between teachers and a pupils with the disturbed or limited communication ability and how they are perceived. In addition, it particularly investigates which language and communication difficulties occur and if they have an impact on learners' achievement.
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Distributed Optimization with Nonconvexities and Limited CommunicationMagnússon, Sindri January 2016 (has links)
In economical and sustainable operation of cyber-physical systems, a number of entities need to often cooperate over a communication network to solve optimization problems. A challenging aspect in the design of robust distributed solution algorithms to these optimization problems is that as technology advances and the networks grow larger, the communication bandwidth used to coordinate the solution is limited. Moreover, even though most research has focused distributed convex optimization, in cyberphysical systems nonconvex problems are often encountered, e.g., localization in wireless sensor networks and optimal power flow in smart grids, the solution of which poses major technical difficulties. Motivated by these challenges this thesis investigates distributed optimization with emphasis on limited communication for both convex and nonconvex structured problems. In particular, the thesis consists of four articles as summarized below. The first two papers investigate the convergence of distributed gradient solution methods for the resource allocation optimization problem, where gradient information is communicated at every iteration, using limited communication. In particular, the first paper investigates how distributed dual descent methods can perform demand-response in power networks by using one-way communication. To achieve the one-way communication, the power supplier first broadcasts a coordination signal to the users and then updates the coordination signal by using physical measurements related to the aggregated power usage. Since the users do not communicate back to the supplier, but instead they only take a measurable action, it is essential that the algorithm remains primal feasible at every iteration to avoid blackouts. The paper demonstrates how such blackouts can be avoided by appropriately choosing the algorithm parameters. Moreover, the convergence rate of the algorithm is investigated. The second paper builds on the work of the first paper and considers more general resource allocation problem with multiple resources. In particular, a general class of quantized gradient methods are studied where the gradient direction is approximated by a finite quantization set. Necessary and sufficient conditions on the quantization set are provided to guarantee the ability of these methods to solve a large class of dual problems. A lower bound on the cardinality of the quantization set is provided, along with specific examples of minimal quantizations. Furthermore, convergence rate results are established that connect the fineness of the quantization and number of iterations needed to reach a predefined solution accuracy. The results provide a bound on the number of bits needed to achieve the desired accuracy of the optimal solution. The third paper investigates a particular nonconvex resource allocation problem, the Optimal Power Flow (OPF) problem, which is of central importance in the operation of power networks. An efficient novel method to address the general nonconvex OPF problem is investigated, which is based on the Alternating Direction Method of Multipliers (ADMM) combined with sequential convex approximations. The global OPF problem is decomposed into smaller problems associated to each bus of the network, the solutions of which are coordinated via a light communication protocol. Therefore, the proposed method is highly scalable. The convergence properties of the proposed algorithm are mathematically and numerically substantiated. The fourth paper builds on the third paper and investigates the convergence of distributed algorithms as in the third paper but for more general nonconvex optimization problems. In particular, two distributed solution methods, including ADMM, that combine the fast convergence properties of augmented Lagrangian-based methods with the separability properties of alternating optimization are investigated. The convergence properties of these methods are investigated and sufficient conditions under which the algorithms asymptotically reache the first order necessary conditions for optimality are established. Finally, the results are numerically illustrated on a nonconvex localization problem in wireless sensor networks. The results of this thesis advocate the promising convergence behaviour of some distributed optimization algorithms on nonconvex problems. Moreover, the results demonstrate the potential of solving convex distributed resource allocation problems using very limited communication bandwidth. Future work will consider how even more general convex and nonconvex problems can be solved using limited communication bandwidth and also study lower bounds on the bandwidth needed to solve general resource allocation optimization problems. / <p>QC 20160203</p>
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Bandwidth Limited Distributed Optimization with Applications to Networked Cyberphysical SystemsMagnússon, Sindri January 2017 (has links)
The emerging technology of Cyberphysical systems consists of networked computing, sensing, and actuator devices used to monitor, connect, and control physical phenomena. In order to economically and sustainably operate Cyberphysical systems, their devices need to cooperate over a communication network to solve optimization problems. For example, in smart power grids, smart meters cooperatively optimize the grid performance, and in wireless sensor networks a number of sensors cooperate to find optimal estimators of real-world parameters. A challenging aspect in the design of distributed solution algorithms to these optimization problems is that while the technology advances and the networks grow larger, the communication bandwidth available to coordinate the solution remains limited. Motivated by this challenge, this thesis investigates the convergence of distributed solution methods for resource allocation optimization problems, where gradient information is communicated at every iteration, using limited communication. This problem is approached from three different perspectives, each presented in a separate paper. The investigation of the three papers demonstrate promises and limits of solving distributed resource allocation problems using limited communication bandwidth. Future work will consider how even more general problems can be solved using limited communication bandwidth and also study different communication constraints. / <p>QC 20170424</p>
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State Estimation and Limited Communication Control for Nonlinear Robotic SystemsRehbinder, Henrik January 2001 (has links)
No description available.
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State Estimation and Limited Communication Control for Nonlinear Robotic SystemsRehbinder, Henrik January 2001 (has links)
No description available.
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Overcoming interference in the beeping communication model / Surmonter les interférences dans le modèle de communication par bipsDufoulon, Fabien 27 September 2019 (has links)
Les petits appareils électroniques peu coûteux et à communication sans fil sont devenus largement disponibles. Bien que chaque entité ait des capacités limitées (par exemple, communication basique ou mémoire de taille constante), un déploiement à grande échelle de telles entités communiquantes constitue un réseau performant, en plus d’être peu coûteux. De tels systèmes distribués présentent toutefois des défis importants en ce qui concerne la conception d'algorithmes simples, efficaces et évolutifs. Dans cette thèse, nous nous intéressons à l’étude de ces systèmes, composés d’appareils dotés de capacités de communication très limitées, à base de simples impulsions d’énergie. Ces systèmes distribués peuvent être modélisés à l'aide du modèle de bips, dans lequel les nœuds communiquent en émettant un bip, un simple signal indifférencié, ou en écoutant leurs voisins (selon un graphe de communication non orienté). Les communications simultanées (c'est-à-dire les collisions) entraînent des interférences non destructives : un nœud, dont deux voisins ou plus émettent simultanément un bip, détecte seulement un bip. Ce mécanisme de communication simple, général et économe en énergie rend les résultats obtenus dans le modèle de bips applicables à de nombreuses situations différentes, avec cependant un challenge. En raison de la faible expressivité des bips et des collisions, la conception des algorithmes est difficile. Tout au long de ce travail, nous surmontons ces deux difficultés afin de fournir des primitives de communication efficaces. La thèse s’intéresse particulièrement aux solutions déterministes, rapides (en temps) et indépendantes des paramètres du graphe de communication (c’est-à-dire uniformes). La première partie de la thèse considère un cadre dans lequel les nœuds se réveillent en même temps (c’est-à-dire que le réseau a été configuré a priori). Pour obtenir des solutions efficaces pour des problèmes fondamentaux de communication distribuée, nous nous concentrons d’abord sur la résolution efficace de problèmes de brisure locale de symétrie : ensemble indépendant maximal et coloration de sommets utilisant au plus Δ + 1 couleurs (où Δ est le degré maximal du graphe de communication). Nous élaborons des solutions à ces problèmes ainsi qu'à leurs variantes à distance deux. Cela nous permet de simuler une communication par messages. Enfin, nous obtenons le premier algorithme de coloration utilisant moins de Δ + 1 couleurs dans le modèle de bips. Ensuite, nous étudions des problèmes définis à l’échelle du réseau, tels que l’élection d'un leader et la diffusion multiple de messages. L'élection d'un leader est un élément essentiel dans la conception d'algorithmes distribués. Nous donnons les deux premiers algorithmes d’élection de leader optimaux en temps pour le modèle de bips. L'un est déterministe, mais nécessite des identifiants uniques. Le second n’a pas besoin d’identifiants (utile pour des raisons de sécurité et de confidentialité), mais est randomisé. S'appuyant sur une élection de leader optimale en temps, plusieurs algorithmes pour la diffusion multiple, efficaces en temps et en calcul, sont présentés. La deuxième partie de la thèse considère un cadre plus difficile mais plus général, dans lequel les nœuds se réveillent de façon asynchrone. Nous nous concentrons sur le problème de désynchronisation à distance deux, qui permet un contrôle de l'accès au support, primordial dans les réseaux sans fil. Nous montrons qu'il est possible pour les nœuds de communiquer de manière cohérente au-delà de leur voisinage immédiat. A cette fin, une primitive permettant aux nœuds de simuler une communication est présentée. Cette primitive est un élément central dans la conception de l'algorithme de désynchronisation à distance deux. Enfin, nous exploitons cette solution afin d'implémenter des primitives de haut niveau pour l’envoi et la réception de messages. / Small inexpensive inter-communicating electronic devices have become widely available. Although the individual device has severely limited capabilities (e.g., basic communication, constant-size memory or limited mobility), multitudes of such weak devices communicating together are able to form a low-cost, easily deployable, yet highly performant network. Such distributed systems present significant challenges however when it comes to the design of efficient, scalable and simple algorithms. In this thesis, we are interested in studying such systems composed of devices with severely limited communication capabilities - using only simple bursts of energy. These distributed systems may be modeled using the beeping model, in which nodes communicate by beeping or listening to their neighbors (according to some undirected communication graph). Simultaneous communications (i.e., collisions) result in non-destructive interference: a node with two or more neighbors beeping simultaneously detects a beep. Its simple, general and energy efficient communication mechanism makes the beeping model widely applicable. However, that simplicity comes at a cost. Due to the poor expressiveness of beeps and the interference caused by simultaneous communications, algorithm design is challenging. Throughout this work, we overcome both difficulties in order to provide efficient communication primitives. A particular focus of the thesis is on deterministic and time-efficient solutions independent of the communication graph's parameters (i.e., uniform). The first part of the thesis considers a setting in which nodes wake up at the same time (i.e., the network has been set up a priori). To obtain efficient solutions to fundamental distributed communication problems, we first focus on efficiently solving problems for local symmetry-breaking: (Δ+1)-vertex coloring and maximal independent set (where Δ is the maximum degree of the communication graph). The solutions we devise are particularly efficient when the communication graph is sparse. They are then used to solve the 2-hop variants of these problems and to simulate message-passing. Finally, combining this simulation with existing results, which assume message-passing, gives the first vertex coloring algorithm using less than Δ+1 colors in the beeping model. Then, we study problems defined on a global scale, such as leader election and multi-broadcast (i.e., information dissemination). Leader election is a crucial building block in the design of distributed algorithms. We give the first two time-optimal leader election algorithms for the beeping model. One is deterministic, but requires unique identifiers. The second one does not need identifiers (useful for security and privacy reasons), but is randomized. Building upon the time-optimal leader election solution, computationally efficient and time-optimal algorithms for multi-broadcast are presented. Although a previous time-optimal solution was available, it required computationally expensive methods. The second part of the thesis considers a more difficult but more general setting, in which nodes wake up at some arbitrary time rounds. We focus on the desynchronization problem, and more precisely on its 2-hop variant, which can be used as medium access control method. We show that it is possible for nodes to communicate in a coherent manner beyond their 1-hop neighborhood. More concretely, a primitive allowing nodes to simulate communication on the square of the communication graph is presented. This primitive is a centerpiece in the design of the 2-hop desynchronization algorithm. Finally, by leveraging this solution, we show that higher-level primitives for sending and receiving messages can be obtained in this difficult setting.
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