Joint optimization of Beam Placement and Shaping for Multi-Beam High Throughput Satellite systems using Gradient Descent

El mercat de les comunicacions per satèl·lit està canviant i la nova generació de satèl·lits tindrà nivells de flexibilitat i escalabilitat sense precedents: s'espera que els futurs Satèl·lits d'Alt Rendiment de múltiples feixos (HTS, per les sigles en anglès) puguin operar milers de feixos simultàniament, cadascun amb un conjunt de paràmetres completament dinàmics per sintonitzar. Això planteja nous reptes quan es tracta d'administrar eficientment la creixent quantitat de recursos. Dos d'aquests reptes estan vinculats a: la ubicació del feix (és a dir, definint la direcció de cada feix) i la forma del feix (és a dir, optimitzant la distribució de guany entre els usuaris coberts). Comprendre com explotar aquestes dues flexibilitats podria millorar l'eficiència, reduïr la potència requerida i permetre l'allotjament de nous usuaris al sistema. Per tant, aquesta tesi es centra en l'optimització conjunta de la posició i forma dels feixos.El mercado de las comunicaciones por satélite está cambiando y la nueva generación de satélites tendrá niveles de flexibilidad y escalabilidad sin precedentes: se espera que los futuros Satélites de Alto Rendimiento de múltiples haces (HTS, por las siglas en inglés) puedan operar miles de haces simultáneamente, cada uno con un conjunto de parámtetros completamente dinámicos para sintonizar. Esto plantea nuevos desafíos cuando se trata de administrar eficientemente la creciente cantidad de recursos. Dos de estos desafíos están vinculados a: la ubicación del haz (es decir, definiendo la dirección para cada haz) y a la forma del haz (es decir, optimizando la distribución de ganancia entre los usuarios cubiertos). Comprender cómo explotar estas dos flexibilidades podría mejorar la eficiencia, reducir la potencia requerida y permitir el alojamiento de nuevos usuarios en el sistema. Por lo tanto, esta tesis se centra en la optimización conjunta de la posición y forma de los haces.The satellite communications market is changing and new generation of satellites will have unprecedented levels of flexibility and scalability: future multi-beam High Throughput Satellites (HTS) are expected to be able to operate thousands of beams simultaneously, each with a set of fully-dynamic parameters to tune. This poses new challenges when it comes to efficiently managing the increasing amount of resources. Two of these challenges are linked to the beam placement (i.e., defining the pointing direction for each beam) and beam shape (i.e., optimizing the gain distribution among covered users) problems. Understanding how to exploit these two flexibilities could improve the efficiency, reducing the required RF power and enabling the accommodation of new users into the system. Thus, this Thesis focuses on the joint beam placement and shaping optimization.Outgoin

Mobile backbone architecture for wireless ad-hoc networks : algorithms and performance analysis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.Includes bibliographical references (p. 181-189).In this thesis, we study a novel hierarchical wireless networking approach in which some of the nodes are more capable than others. In such networks, the more capable nodes can serve as Mobile Backbone Nodes and provide a backbone over which end-to-end communication can take place. The main design problem considered in this thesis is that of how to (i) Construct such Mobile Backbone Networks so as to optimize a network performance metric, and (ii) Maintain such networks under node mobility. In the first part of the thesis, our approach consists of controlling the mobility of the Mobile Backbone Nodes (MBNs) in order to maintain network connectivity for the Regular Nodes (RNs). We formulate this problem subject to minimizing the number of MBNs and refer to it as the Connected Disk Cover (CDC) problem. We show that it can be decomposed into the Geometric Disk Cover (GDC) problem and the Steiner Tree Problem with Minimum Number of Steiner Points (STP-MSP). We prove that if these subproblems are solved separately by y- and 5-approximation algorithms, the approximation ratio of the joint solution is y1+6. Then, we focus on the two subproblems and present a number of distributed approximation algorithms that maintain a solution to the GDC problem under mobility. A new approach to the solution of the STP-MSP is also described. We show that this approach can be extended in order to obtain a joint approximate solution to the CDC problem. Finally, we evaluate the performance of the algorithms via simulation and show that the proposed GDC algorithms perform very well under mobility and that the new approach for the joint solution can significantly reduce the number of Mobile Backbone Nodes.(cont.) In the second part of the thesis, we address the the joint problem of placing a fixed number K MBNs in the plane, and assigning each RN to exactly one MBN. In particular, we formulate and solve two problems under a general communications model. The first is the Maximum Fair Placement and Assignment (MFPA) problem in which the objective is to maximize the throughput of the minimum throughput RN. The second is the Maximum Throughput Placement and Assignment (MTPA) problem, in which the objective is to maximize the aggregate throughput of the RNs. Due to the change in model (e.g. fixed number of MBNs,general communications model) from the first part of the thesis, the problems of this part of the thesis require a significantly different approach and solution methodology. Our main result is a novel optimal polynomial time algorithm for the MFPA problem for fixed K. For a restricted version of the MTPA problem, we develop an optimal polynomial time algorithm for K < 2. We also develop two heuristic algorithms for both problems, including an approximation algorithm for which we bound the worst case performance loss. Finally, we present simulation results comparing the performance of the various algorithms developed in the paper. In the third part of the thesis, we consider the problem of placing the Mobile Backbone Nodes over a finite time horizon. In particular, we assume complete a-priori knowledge of each of the RNs' trajectories over a finite time interval, and consider the problem of determining the optimal MBN path over that time interval. We consider the path planning of a single MBN and aim to maximize the time-average system throughput. We also assume that the velocity of the MBN factors into the performance objective (e.g. as a constraint/penalty).(cont.) Our first approach is a discrete one, for which our main result is a dynamic programming based approximation algorithm for the path planning problem. We provide worst case analysis of the performance of the algorithm. Additionally, we develop an optimal algorithm for the 1-step velocity constrained path planning problem. Using this as a sub-routine, we develop a greedy heuristic algorithm for the overall path planning problem. Next, we approach the path-planning problem from a continuous perspective. We formulate the problem as an optimal control problem, and develop interesting insights into the structure of the optimal solution. Finally, we discuss extensions of the base discrete and continuous formulations and compare the various developed approaches via simulation.by Anand Srinivas.Ph.D