Communications satellite technology in the next decade
Network analysis of television communication satellites for future decade
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Network analysis of television communication satellites for future decade
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Due to the rapidly evolving field of image processing and networking, video information promises to be an important part of telecommunication systems. Although up to now video transmission has been transported mainly over circuit-switched networks, it is likely that packet-switched networks will dominate the communication world in the near future. Asynchronous transfer mode (ATM) techniques in broadband-ISDN can provide a flexible, independent and high performance environment for video communication. For this paper, the network simulator was used only as a channel in this simulation. Mixture blocking coding with progressive transmission (MBCPT) has been investigated for use over packet networks and has been found to provide high compression rate with good visual performance, robustness to packet loss, tractable integration with network mechanics and simplicity in parallel implementation.
This presentation focuses on the activities at JPL on the integration of satellite and terrestrial networks for mobile and personal communications. Activities fall into two categories: 1)advanced systems work, and 2)laboratory and field experimentation. Results of a workshop held at JPL on PCS integration and interoperability will be presented. Experiments will be described.
Short-block low-density parity-check (LDPC) codes of a special type are intended to be especially well suited for potential applications that include transmission of command and control data, cellular telephony, data communications in wireless local area networks, and satellite data communications. [In general, LDPC codes belong to a class of error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels.] The codes of the present special type exhibit low error floors, low bit and frame error rates, and low latency (in comparison with related prior codes). These codes also achieve low maximum rate of undetected errors over all signal-to-noise ratios, without requiring the use of cyclic redundancy checks, which would significantly increase the overhead for short blocks. These codes have protograph representations; this is advantageous in that, for reasons that exceed the scope of this article, the applicability of protograph representations makes it possible to design highspeed iterative decoders that utilize belief- propagation algorithms.
The growing popularity of small cost effective satellites (SmallSats, CubeSats, etc.) creates the potential for a variety of new science applications involving multiple nodes functioning together or independently to achieve a task, such as swarms and constellations. As this technology develops and is deployed for missions in Low Earth Orbit and beyond, the use of delay tolerant networking (DTN) techniques may improve communication capabilities within the network. In this paper, a network hierarchy is developed from heterogeneous networks of SmallSats, surface vehicles, relay satellites and ground stations which form an integrated network. There is a tradeoff between complexity, flexibility, and scalability of user defined schedules versus autonomous routing as the number of nodes in the network increases. To address these issues, this work proposes a machine learning classifier based on DTN routing metrics. A framework is developed which will allow for the use of several categories of machine learning algorithms (decision tree, random forest and deep learning) to be applied to a dataset of historical network statistics, which allows for the evaluation of algorithm complexity versus performance to be explored. We develop the emulation of a hierarchical network, consisting of tens of nodes which form a cognitive network architecture. CORE (Common Open Research Emulator) is used to emulate the network using bundle protocol and DTN IP neighbor discovery.
The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.
The Space Communications and Navigation (SCaN) Program is planning to integrate its individual networks into a unified network which will function as a single entity to provide services to user missions. This integrated network architecture is expected to provide SCaN customers with the capabilities to seamlessly use any of the available SCaN assets to support their missions to efficiently meet the collective needs of Agency missions. One potential optimal application of these assets, based on this envisioned architecture, is that of arraying across existing networks to significantly enhance data rates and/or link availabilities. As such, this document provides an analysis of the transmit and receive performance of a proposed SCaN inter-network antenna array. From the study, it is determined that a fully integrated internetwork array does not provide any significant advantage over an intra-network array, one in which the assets of an individual network are arrayed for enhanced performance. Therefore, it is the recommendation of this study that NASA proceed with an arraying concept, with a fundamental focus on a network-centric arraying.
Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices’ contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol’s time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G.
To enable the rapid, widespread commercial availability of secondary distribution grid voltage and phase angle data, the DOE OE Technology Commercialization Fund (TCF) project: 1) created a new American National Standard for next-generation grid power quality sensing and communications, 2) created a new prototype broadband-based standard-compliant grid power sensing system for use by utilities and others, and 3) improved by several orders of magnitude the spatiotemporal scale of the in-progress DOE CESER project: Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics.
The dispersed sensor processing mesh (DSPM) is part of an experimental system used to pursue a proof of concept for an advanced fault-tolerant communication strategy. The DSPM experiments incorporate sensors and effectors into an ultra-reliable nodal network in which a central bus controller performs algorithms to grow and maintain the network. The experiments demonstrate that DSPM is an achievable communication network that can sustain failures and continue to function properly. The results of the experiment give insights into the unique characteristics of the DSPM network and the network's capacity to limit physical damage propagation, limit damaged-data propagation, and to survive cyclic communication paths. This paper describes the concept, mechanization, and performance of the DSPM system in a real-time flight-critical environment.
Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a macroscopic perspective.
NASA has initiated at Jet Propulsion Laboratory the design of a Communications and Navigation Network at Mars.
The trans-Pacific high data rate (TP-HDR) satellite communications experiment was proposed at the Japan-U.S. Cooperation in Space (JUCS) Program Workshop held in Hawaii in 1993 and remote high definition video post-production was demonstrated as the first phase trial. ATM-based 45 Mbps trans-Pacific link was established in the first phase, and the following experiments with 155 Mbps was planned as the phase 2. This paper describes the experimental network configuration and project plan of TP-HDR experiment phase 2. Additional information is provided in the original.
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
Wireless communications plays a pivotal role in multiple complex domains such as tactical networks or space communications. Traditional physical (PHY) layer protocols for digital communications contain chains of signal processing blocks that have been mathematically optimized to transmit information bits efficiently over noisy channels. Unfortunately, the ongoing advancement of hardware and software design, and algorithm development, makes it difficult for some domains to keep up with the constant change in modern communication systems. It has been shown previously that combining deep learning with digital modulation (deepmod) allows a system to learn communications on its own rather than requiring human-invented protocols. This is particularly attractive to space communications where updating PHY layer technologies may be prohibitively complex or expensive. A link using deepmod is able to learn both waveform synthesis (transmit) and analysis (receive) that is self-taught. When deepmod is first initiated it has no knowledge of the channel medium but quickly learns to communicate by synthesizing waveforms that can be successfully decoded at the other end of the link. This is accomplished by a custom deep neural network especially suited for this particular task of learning. In this current work, we show that deepmod learns in both traditional point-to-point channels as well as the more abstract multi-hop amplify-and-forward relay channel. In the experimental results, even though no direct link between transmitter and receiver exists, deepmod-enabled nodes still create latent information bearing waveforms that can be used for communications.