Dynamic frequency assignment for mobile users in multibeam satellite constellations

Els nivells de flexibilitat i escalabilitat mai vistos de la propera generació de sistemes de comunicació per satèl·lit exigeixen nous algorismes de gestió de recursos que s'adaptin a contextos dinàmics. El futur entorn dels serveis de comunicació per satèl·lit estarà definit per un nombre més gran d'usuaris, una gran part dels quals correspondrà a usuaris mòbils com avions o vaixells. El repte addicional que introdueixen aquests usuaris és abordar la incertesa espai-temporal que es presenta en forma de retards, canvis en la seva trajectòria, o tots dos. Atès que els usuaris mòbils constituiran un segment important del mercat, els operadors de satèl·lits prioritzen l'aprofitament dels avançats sistemes digitals per desenvolupar estratègies flexibles d'assignació de recursos que siguin robustes davant de les bases d'usuaris dinàmiques. Un dels problemes clau en aquest context és com gestionar l'espectre de freqüències de manera eficient. Mentre que nombroses solucions aborden escenaris d'assignació de dinàmica freqüències, el nivell addicional de complexitat que presenten els usuaris mòbils no ha estat prou estudiat, i no és clar si els nous algorismes d'assignació de freqüències poden abordar la incertesa espai-temporal. Concretament, sostenim que els canvis inesperats en la posició dels usuaris introdueixen noves restriccions en l'assignació de freqüències que els algoritmes la literatura podrien no ser capaços de complir, especialment si les decisions s'han de prendre en temps real i a escala. Per solucionar aquesta limitació, proposem un algorisme de gestió dinàmica de freqüències basat en programació lineal entera que assigna recursos a escenaris amb usuaris tant fixos com mòbils, tenint en compte la incertesa espai-temporal d'aquests últims. El nostre mètode inclou tant la planificació a llarg termini com l'operació en temps real, una sinergia que no ha estat prou explorada per a les comunicacions per satèl·lit i que és crítica quan s'opera sota incertesa. PLos niveles de flexibilidad y escalabilidad nunca vistos de la próxima generación de sistemas de comunicación por satélite exigen nuevos algoritmos de gestión de recursos que se adapten a contextos dinámicos. El futuro entorno de los servicios de comunicación por satélite estará definido por un mayor número de usuarios, una gran parte de los cuales corresponderá a usuarios móviles como aviones o barcos. El reto adicional que introducen estos usuarios es abordar la incertidumbre espacio-temporal que se presenta en forma de retrasos, cambios en su trayectoria, o ambos. Dado que los usuarios móviles constituirán un segmento importante del mercado, los operadores de satélites dan prioridad al aprovechamiento de los avanzadas sistemas digitales para desarrollar estrategias flexibles de asignación de recursos que sean robustas frente a las bases de usuarios dinámicas. Uno de los problemas clave en este contexto es cómo gestionar el espectro de frecuencias de forma eficiente. Mientras que numerosas soluciones abordan escenarios de asignación dinámica de frecuencias, el nivel adicional de complejidad que presentan los usuarios móviles no ha sido suficientemente estudiado, y no está claro si los nuevos algoritmos de asignación de frecuencias pueden abordar la incertidumbre espacio-temporal. En concreto, sostenemos que los cambios inesperados en la posición de los usuarios introducen nuevas restricciones en la asignación de frecuencias que los algoritmos la literatura podrían no ser capaces de cumplir, especialmente si las decisiones deben tomarse en tiempo real y a escala. Para solventar esta limitación, proponemos un algoritmo de gestión dinámica de frecuencias basado en la programación lineal entera que asigna recursos en escenarios con usuarios tanto fijos como móviles, teniendo en cuenta la incertidumbre espacio-temporal de estos últimos. Nuestro método incluye tanto la planificación a largo plazo como la operación en tiempo real, una sinergia que no ha sido suficientThe unprecedented levels of flexibility and scalability of the next generation of communication satellite systems call for new resource management algorithms that adapt to dynamic environments. The upcoming landscape of satellite communication services will be defined by an increased number of unique users, a large portion of which will correspond to mobile users such as planes or ships. The additional challenge introduced by these users is addressing the spatiotemporal uncertainty that comes in the form of delays, changes in their trajectory, or both. Given that mobile users will constitute an important segment of the market, satellite operators prioritize leveraging modern digital payloads to develop flexible resource allocation strategies that are robust against dynamic user bases. One of the key problems in this context is how to manage the frequency spectrum efficiently. While numerous solutions address dynamic frequency assignment scenarios, the additional layer of complexity presented by mobile users has not been sufficiently studied, and it is unclear whether novel frequency assignment algorithms can address spatiotemporal uncertainty. Specifically, we argue that unexpected changes in the position of users introduce new restrictions into the frequency assignment, which previous algorithms in the literature might not be able to meet, especially if decisions need to be made in real-time and at scale. To address this gap, we propose a dynamic frequency management algorithm based on integer linear programming that assigns resources in scenarios with both fixed and mobile users, accounting for the spatiotemporal uncertainty of the latter. Our method includes both long-term planning and real-time operation, a synergy that has not been sufficiently explored for satellite communications and proves to be critical when operating under uncertainty. To fulfill the problem’s scope, we propose different strategies that extend a state-of-the-art frequency management algOutgoin

Machine Learning Applications in Spacecraft State and Environment Estimation

There are some problems in spacecraft systems engineering with highly non-linear characteristics and noise where traditional nonlinear estimation techniques fail to yield accurate results. In this thesis, we consider approaching two such problems using kernel methods in machine learning. First, we present a novel formulation and solution to orbit determination of spacecraft and spacecraft groups which can be applied with very weakly observable and highly noisy scenarios. We present a ground station network architecture that can perform orbit determination using Doppler-only observations over the network. Second, we present a machine learning solution to the spacecraft magnetic field interference cancellation problem using distributed magnetometers paving the way for space magnetometry with boom-less CubeSats. We present an approach to orbit determination under very broad conditions that are satisfied for n-body problems. We show that domain generalization and distribution regression techniques can learn to estimate orbits of a group of satellites and identify individual satellites especially with prior understanding of correlations between orbits and provide asymptotic convergence conditions. The approach presented requires only observability of the dynamical system and visibility of the spacecraft and is particularly useful for autonomous spacecraft operations using low-cost ground stations or sensors. With the absence of linear region constraints in the proposed method, we are able to identify orbits that are 800 km apart and reduce orbit uncertainty by 92.5% to under 60 km with noisy Doppler-only measurements. We present an architecture for collaborative orbit determination using networked ground stations. We focus on clusters of satellites deployed in low Earth orbit and measurements of their Doppler-shifted transmissions made by low-gain antenna systems in a software-defined federated ground station network. We develop a network architecture enabling scheduling and tracking with uncertain orbit information. For the proposed network, we also present scheduling and coordinated tracking algorithms for tracking with the purpose of generating measurements for orbit determination. We validate our algorithms and architecture with its application to high fidelity simulations of different networked orbit determination scenarios. We demonstrate how these low-cost ground stations can be used to provide accurate and timely orbital tracking information for large satellite deployments, which is something that remains a challenge for current tracking systems. Last, we present a novel approach and algorithm to the problem of magnetic field interference cancellation of time-varying interference using distributed magnetometers and spacecraft telemetry with particular emphasis on the computational and power requirements of CubeSats. The spacecraft magnetic field interference cancellation problem involves estimation of noise when the number of interfering sources far exceed the number of sensors required to decouple the noise from the signal. The proposed approach models this as a contextual bandit learning problem and the proposed algorithm learns to identify the optimal low-noise combination of distributed magnetometers based on indirect information gained on spacecraft currents through telemetry. Experimental results based on on-orbit spacecraft telemetry shows a 50% reduction in interference compared to the best magnetometer.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147688/1/srinag_1.pd

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

Air Force Institute of Technology Research Report 2001

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

The role of synchronization in digital communications using chaos - Part II: Chaotic modulation and chaotic synchronization.

For pt. I see ibid., vol. 44, p. 927-36 (1997). In a digital communications system, data are transmitted from one location to another by mapping bit sequences to symbols, and symbols to sample functions of analog waveforms. The analog waveform passes through a bandlimited (possibly time-varying) analog channel, where the signal is distorted and noise is added. In a conventional system the analog sample functions sent through the channel are weighted sums of one or more sinusoids; in a chaotic communications system the sample functions are segments of chaotic waveforms. At the receiver, the symbol may be recovered by means of coherent detection, where all possible sample functions are known, or by noncoherent detection, where one or more characteristics of the sample functions are estimated. In a coherent receiver, synchronization is the most commonly used technique for recovering the sample functions from the received waveform. These sample functions are then used as reference signals for a correlator. Synchronization-based coherent receivers have advantages over noncoherent receivers in terms of noise performance, bandwidth efficiency (in narrow-band systems) and/or data rate (in chaotic systems). These advantages are lost if synchronization cannot be maintained, for example, under poor propagation conditions. In these circumstances, communication without synchronization may be preferable. The theory of conventional telecommunications is extended to chaotic communications, chaotic modulation techniques and receiver configurations are surveyed, and chaotic synchronization schemes are describe

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security