27 research outputs found
SRML: Space Radio Machine Learning
Space-based communications systems to be employed by future artificial satellites, or spacecraft during exploration missions, can potentially benefit from software-defined radio adaptation capabilities. Multiple communication requirements could potentially compete for radio resources, whose availability of which may vary during the spacecraft\u27s operational life span. Electronic components are prone to failure, and new instructions will eventually be received through software updates. Consequently, these changes may require a whole new set of near-optimal combination of parameters to be derived on-the-fly without instantaneous human interaction or even without a human in-the-loop. Thus, achieving a sufficiently set of radio parameters can be challenging, especially when the communication channels change dynamically due to orbital dynamics as well as atmospheric and space weather-related impairments. This dissertation presents an analysis and discussion regarding novel algorithms proposed in order to enable a cognition control layer for adaptive communication systems operating in space using an architecture that merges machine learning techniques employing wireless communication principles. The proposed cognitive engine proof-of-concept reasons over time through an efficient accumulated learning process. An implementation of the conceptual design is expected to be delivered to the SDR system located on the International Space Station as part of an experimental program. To support the proposed cognitive engine algorithm development, more realistic satellite-based communications channels are proposed along with rain attenuation synthesizers for LEO orbits, channel state detection algorithms, and multipath coefficients function of the reflector\u27s electrical characteristics. The achieved performance of the proposed solutions are compared with the state-of-the-art, and novel performance benchmarks are provided for future research to reference
Use of V-band geostationary satellites to deliver multimedia services
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Proceedings of the Fifth International Mobile Satellite Conference 1997
Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments
Proceedings of the Third International Mobile Satellite Conference (IMSC 1993)
Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial cellular communications services. While the first and second International Mobile Satellite Conferences (IMSC) mostly concentrated on technical advances, this Third IMSC also focuses on the increasing worldwide commercial activities in Mobile Satellite Services. Because of the large service areas provided by such systems, it is important to consider political and regulatory issues in addition to technical and user requirements issues. Topics covered include: the direct broadcast of audio programming from satellites; spacecraft technology; regulatory and policy considerations; advanced system concepts and analysis; propagation; and user requirements and applications
Satellite Systems in the Era of 5G Internet of Things
In recent years, IoT applications have drawn a great deal of attention, both in academia and industry. A crucial requirement of any infrastructure serving the IoT market will be to guarantee ubiquitous connectivity to the low-cost, low-powered devices distributed all over the globe. It is widely accepted that this requirement will not be met by the terrestrial network alone. There will be, in fact, vast areas of the globe where the terrestrial infrastructure deployment will be unfeasible or not economically viable, thus leaving those areas un- or under-served. For this reason, several studies and projects are addressing the use of a Non-Terrestrial Network component to seamlessly complement and extend the terrestrial network coverage in future systems.
The design of these extremely complex systems requires manifold analyses at different levels of abstraction, from satellite constellation and ground segment architecture aspects, to the evaluation of the air interface behaviour, in order to evaluate the system performance. The aim of this work is to perform a detailed analysis of the SatCom system aspects, trying to be as accurate as possible but without getting lost in unnecessary details, in order to provide a comprehensive set of tools, organised in a simulation platform, to support the design and performance evaluation of the system. Notably, simulation softwares play an important role in this framework; however, a full-featured simulation tool does not yet exist for the evaluation of the described emerging technologies. ESA M2M Simulator (ESiM2M) is a System-Level Simulator, developed in collaboration with the European Space Agency, which is intended for closing this gap, as a tool for the design and analysis, from a system-level point of view, of Satellite-IoT systems. This work is primarily focused on the description of the ESiM2M simulation tool and the results derived with the latter from analyses on Satellite-IoT systems
Interference Management and System Optimization with GNSS and non-GNSS Signals for Enhanced Navigation
In the last few decades, Global Navigation Satellite System (GNSS) has become an indispensable element in our society. Currently, GNSS is used in a wide variety of sectors and situations, some of them offering critical services, such as transportation, telecommunications, and finances. For this reason, and combined with the relative ease an attack on the GNSS wireless signals can be performed nowadays with an Software Defined Radio (SDR) transmitter, GNSS has become more and more a target of wireless attacks of diverse nature and motivations. Nowadays, anyone can buy an interference device (also known as a jammer device) for a few euros. These devices are legal to be bought in many countries, especially online. But at the same time, they are illegal to be used. These devices can interfere with signals in specific frequency bands, used for services such as GNSS. An outage in the GNSS service at a specific location area (which can be even a few km2) could end up in disastrous consequences, such as an economical loss or even putting lives at risk, since many critical services rely on GNSS for their correct functioning.
Fundamentally, this thesis focuses on developing new methods and algorithms for interference management in GNSS. The main focus is on interference detection and classification, but discussions are also made about interference localization and mitigation. The detection and classification algorithms analyzed in this thesis are chosen from the point of view of the aviation domain, in which additional constraints (e.g., antenna placement, number of antennas, vibrations due to movement, etc.) need to be taken into account. The selected detection and classification methods are applied at the pre-correlation level, based on the raw received signal. They apply specific signal transforms in the digital domain (e.g., time-frequency transformations) to the received signal. With such algorithms, interferences can be detected at a level as low as 0 dB Jamming-to-Signal Ratio (JSR). The interference classification combines transformed signals with previously trained signals Convolutional Neural Network (CNN) and/or Support Vector Machine (SVM) to determine the type of interference signal among the studied ones. The accuracy of such a classification methodology is above 90%. Knowing which signal causes interference we can better optimize which mitigation and localization algorithm we should use to obtain the best mitigation results.
Furthermore, this thesis also studies alternative positioning methods, starting from the premise that GNSS may not always be available and/or we are certain that we can not rely on it due to some reason such as high or unmitigated interferences. Therefore, if one needs to get a Position Velocity and Time (PVT) solution, one would have to rely on alternative signals that could offer positioning features, such as the cellular network signals (i.e. 4G, 5G, and further releases) and/or satellite positioning based on Low Earth Orbit (LEO) satellites. Those systems use presumably different frequency bands, which makes it more unlikely that they will be jammed at the same time as the GNSS signal. In this sense, positioning based on LEO satellites is studied in this thesis from the point of view of feasibility and expected performance
Studies of scintillation on earth-space paths
EThOS - Electronic Theses Online ServiceGBUnited Kingdo