3,463 research outputs found

    Integration of Satellites in 5G through LEO Constellations

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    The standardization of 5G systems is entering in its critical phase, with 3GPP that will publish the PHY standard by June 2017. In order to meet the demanding 5G requirements both in terms of large throughput and global connectivity, Satellite Communications provide a valuable resource to extend and complement terrestrial networks. In this context, we consider a heterogeneous architecture in which a LEO mega-constellation satellite system provides backhaul connectivity to terrestrial 5G Relay Nodes, which create an on-ground 5G network. Since large delays and Doppler shifts related to satellite channels pose severe challenges to terrestrial-based systems, in this paper we assess their impact on the future 5G PHY and MAC layer procedures. In addition, solutions are proposed for Random Access, waveform numerology, and HARQ procedures.Comment: Submitted to IEEE Global Communications Conference (GLOBECOM) 201

    A Survey Examining Neuromorphic Architecture in Space and Challenges from Radiation

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    Inspired by the human brain's structure and function, neuromorphic computing has emerged as a promising approach for developing energy-efficient and powerful computing systems. Neuromorphic computing offers significant processing speed and power consumption advantages in aerospace applications. These two factors are crucial for real-time data analysis and decision-making. However, the harsh space environment, particularly with the presence of radiation, poses significant challenges to the reliability and performance of these computing systems. This paper comprehensively surveys the integration of radiation-resistant neuromorphic computing systems in aerospace applications. We explore the challenges posed by space radiation, review existing solutions and developments, present case studies of neuromorphic computing systems used in space applications, discuss future directions, and discuss the potential benefits of this technology in future space missions.Comment: Submitted to IEEE Journal on Miniaturization for Air and Space System

    SciTech News Volume 71, No. 1 (2017)

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    Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

    Cognitive Communications and Networking Technology Infusion Study Report

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    As the envisioned next-generation SCaN Network transitions into an end-to-end system of systems with new enabling capabilities, it is anticipated that the introduction of machine learning, artificial intelligence, and other cognitive strategies into the network infrastructure will result in increased mission science return, improved resource efficiencies, and increased autonomy and reliability. This enhanced set of cognitive capabilities will be implemented via a space cloud concept to achieve a service-oriented architecture with distributed cognition, de-centralized routing, and shared, on-orbit data processing. The enabling cognitive communications and networking capabilities that may facilitate the desired network enhancements are identified in this document, and the associated enablers of these capabilities, such as technologies and standards, are described in detail

    Empowering Non-Terrestrial Networks with Artificial Intelligence: A Survey

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    6G networks can support global, ubiquitous and seamless connectivity through the convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios, NTNs pose unique challenges including propagation characteristics, latency and mobility, owing to the operations in spaceborne and airborne platforms. To overcome all these technical hurdles, this survey paper presents the use of artificial intelligence (AI) techniques in learning and adapting to the complex NTN environments. We begin by providing an overview of NTNs in the context of 6G, highlighting the potential security and privacy issues. Next, we review the existing AI methods adopted for 6G NTN optimization, starting from machine learning (ML), through deep learning (DL) to deep reinforcement learning (DRL). All these AI techniques have paved the way towards more intelligent network planning, resource allocation (RA), and interference management. Furthermore, we discuss the challenges and opportunities in AI-powered NTN for 6G networks. Finally, we conclude by providing insights and recommendations on the key enabling technologies for future AI-powered 6G NTNs

    The Role of the Internet of Things in Network Resilience

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    Disasters lead to devastating structural damage not only to buildings and transport infrastructure, but also to other critical infrastructure, such as the power grid and communication backbones. Following such an event, the availability of minimal communication services is however crucial to allow efficient and coordinated disaster response, to enable timely public information, or to provide individuals in need with a default mechanism to post emergency messages. The Internet of Things consists in the massive deployment of heterogeneous devices, most of which battery-powered, and interconnected via wireless network interfaces. Typical IoT communication architectures enables such IoT devices to not only connect to the communication backbone (i.e. the Internet) using an infrastructure-based wireless network paradigm, but also to communicate with one another autonomously, without the help of any infrastructure, using a spontaneous wireless network paradigm. In this paper, we argue that the vast deployment of IoT-enabled devices could bring benefits in terms of data network resilience in face of disaster. Leveraging their spontaneous wireless networking capabilities, IoT devices could enable minimal communication services (e.g. emergency micro-message delivery) while the conventional communication infrastructure is out of service. We identify the main challenges that must be addressed in order to realize this potential in practice. These challenges concern various technical aspects, including physical connectivity requirements, network protocol stack enhancements, data traffic prioritization schemes, as well as social and political aspects

    Cryptographic Key Management in Delay Tolerant Networks (DTNs): A survey

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    Since their appearance at the dawn of the second millennium, Delay or Disruption Tolerant Networks (DTNs) have gradually evolved, spurring the development of a variety of methods and protocols for making them more secure and resilient. In this context, perhaps, the most challenging problem to deal with is that of cryptographic key management. To the best of our knowledge, the work at hand is the first to survey the relevant literature and classify the various so far proposed key management approaches in such a restricted and harsh environment. Towards this goal, we have grouped the surveyed key management methods into three major categories depending on whether the particular method copes with a) security initialization, b) key establishment, and c) key revocation. We have attempted to provide a concise but fairly complete evaluation of the proposed up-to-date methods in a generalized way with the aim of offering a central reference point for future research
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