Digital communications techniques Interim report, 15 Sep. 1969 - 15 Feb. 1970
Convolutional codes and recursive signal processing for digital communications
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Convolutional codes and recursive signal processing for digital communications
Textbook on communication engineering emphasizing random processes, information and detection theory, statistical communication theory, applications, etc
The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.
The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.
Systems, apparatuses, and methods for performing network packet templating for graphics processing unit (GPU)-initiated communication are disclosed. A central processing unit (CPU) creates a network packet according to a template and populates a first subset of fields of the network packet with static data. Next, the CPU stores the network packet in a memory. A GPU initiates execution of a kernel and detects a network communication request within the kernel and prior to the kernel completing execution. Responsive to this determination, the GPU populates a second subset of fields of the network packet with runtime data. Then, the GPU generates a notification that the network packet is ready to be processed. A network interface controller (NIC) processes the network packet using data retrieved from the first subset of fields and from the second subset of fields responsive to detecting the notification.
This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry.
This is the second volume of papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools; systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development; perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; and robotics technologies.
Finding the numerical solution of moderate and high-fidelity aerodynamics problems on modern computer architectures involves, 1) decomposing the domain into smaller regions of nearly equal size, and 2) allocating computational resources for calculations on each domain and communication between domains. Modern computer clusters are composed from hierarchies of processing, memory, and communication resources with varying capabilities and latencies.This paper focuses on the combination of domain decomposition provided by ParMETIS [1]and Newton-Krylov Methods [2–5] for the solution of Computational Aerodynamics problems of interest to NASA. Herein, trade-offs encountered when mapping aerodynamics problems to modern computer architectures are explored through examples and discussions of trade-offs in parallelism from MPI [6], Open MP [7], and vectorization as partition sizes and computational resources are varied. An example of the impact that domain decomposition and MPI+OpenMPresource allocation can have on an adjoint calculation is presented in this abstract. The full paper will include more detailed examples, discussions of difficulties and potential methods to overcome them, and topics identified for future study.
Libraries like PVM and MPI send typed messages to allow for heterogeneous cluster computing. Lower-level libraries, such as GAM, provide more efficient access to communication by removing the need to copy messages between the interface and user space in some cases. still lower-level interfaces, such as UNET, get right down to the hardware level to provide maximum performance. However, these are all still interfaces for passing messages from one process to another, and have limited utility in a shared-memory environment, due primarily to the fact that message passing is just another term for copying. This drawback is made more pertinent by today's hybrid architectures (e.g. clusters of SMPs), where it is difficult to know beforehand whether two communicating processes will share memory. As a result, even portable language tools (like HPF compilers) must either map all interprocess communication, into message passing with the accompanying performance degradation in shared memory environments, or they must check each communication at run-time and implement the shared-memory case separately for efficiency. Cooperative Data Sharing (CDS) is a single user-level API which abstracts all communication between processes into the sharing and access coordination of memory regions, in a model which might be described as "distributed shared messages" or "large-grain distributed shared memory". As a result, the user programs to a simple latency-tolerant abstract communication specification which can be mapped efficiently to either a shared-memory or message-passing based run-time system, depending upon the available architecture. Unlike some distributed shared memory interfaces, the user still has complete control over the assignment of data to processors, the forwarding of data to its next likely destination, and the queuing of data until it is needed, so even the relatively high latency present in clusters can be accomodated. CDS does not require special use of an MMU, which can add overhead to some DSM systems, and does not require an SPMD programming model. unlike some message-passing interfaces, CDS allows the user to implement efficient demand-driven applications where processes must "fight" over data, and does not perform copying if processes share memory and do not attempt concurrent writes. CDS also supports heterogeneous computing, dynamic process creation, handlers, and a very simple thread-arbitration mechanism. Additional support for array subsections is currently being considered. The CDS1 API, which forms the kernel of CDS, is built primarily upon only 2 communication primitives, one process initiation primitive, and some data translation (and marshalling) routines, memory allocation routines, and priority control routines. The entire current collection of 28 routines provides enough functionality to implement most (or all) of MPI 1 and 2, which has a much larger interface consisting of hundreds of routines. still, the API is small enough to consider integrating into standard os interfaces for handling inter-process communication in a network-independent way. This approach would also help to solve many of the problems plaguing other higher-level standards such as MPI and PVM which must, in some cases, "play OS" to adequately address progress and process control issues. The CDS2 API, a higher level of interface roughly equivalent in functionality to MPI and to be built entirely upon CDS1, is still being designed. It is intended to add support for the equivalent of communicators, reduction and other collective operations, process topologies, additional support for process creation, and some automatic memory management. CDS2 will not exactly match MPI, because the copy-free semantics of communication from CDS1 will be supported. CDS2 application programs will be free to carefully also use CDS1. CDS1 has been implemented on networks of workstations running unmodified Unix-based operating systems, using UDP/IP and vendor-supplied high- performance locks. Although its inter-node performance is currently unimpressive due to rudimentary implementation technique, it even now outperforms highly-optimized MPI implementation on intra-node communication due to its support for non-copy communication. The similarity of the CDS1 architecture to that of other projects such as UNET and TRAP suggests that the inter-node performance can be increased significantly to surpass MPI or PVM, and it may be possible to migrate some of its functionality to communication controllers.
Engineers are an extraordinarily diverse group of professionals, but an attribute common to all engineers is their use of information. Engineering can be conceptualized as an information processing system that must deal with work-related uncertainty through patterns of technical communications. Throughout the process, data, information, and tacit knowledge are being acquired, produced, transferred, and utilized. While acknowledging that other models exist, we have chosen to view the information-seeking behavior of engineers within a conceptual framework of the engineer as an information processor. This article uses the chosen framework to discuss information-seeking behavior of engineers, reviewing selected literature and empirical studies from library and information science, management, communications, and sociology. The article concludes by proposing a research agenda designed to extend our current, limited knowledge of the way engineers process information.
Most wireless sensor network (comprising of thousands of WSNs) applications require operation over extended periods of time beginning with their deployment. Network lifetime is extremely critical for most applications and is one of the limiting factors for energy-constrained networks. Based on applications, there are wide ranges of different energy sources suitable for powering WSNs. A battery is traditionally used to power WSNs. The deployed WSN is required to last for long time. Due to finite amount of energy present in batteries, it is not feasible to replace batteries. Recently there has been a new surge in the area of energy harvesting were ambient energy in the environment can be utilized to prolong the lifetime of WSNs. Some of the sources of ambient energies are solar power, thermal gradient, human motion and body heat, vibrations, and ambient RF energy. The design and development of TEGs to power WSNs that would remain active for a long period of time requires comprehensive understanding of WSN operational. This motivates the research in modeling the lifetime, i.e., power consumption, of a WSN by taking into consideration various node and network level activities. A WSN must perform three essential tasks: sense events, perform quick local information processing of sensed events, and wirelessly exchange locally processed data with the base station or with other WSNs in the network. Each task has a power cost per unit tine and an additional cost when switching between tasks. There are number of other considerations that must also be taken into account when computing the power consumption associated with each task. The considerations includes: number of events occurring in a fixed active time period and the duration of each event, event-information processing time, total communication time, number of retransmission, etc. Additionally, at the network level the communication of information data packets between WSNs involves collisions, latency, and retransmission, which result in unanticipated power losses. This report focuses rigorous stochastic modeling of power demand for a schedule-driven WSN utilizing Institute of Electrical and Electronics Engineers 802.11 and 802.15.4 communication protocols. The model captures the generic operation of a schedule-driven WSN when an external event occurs, i.e., sensing, following by processing, and followed by communication. The report will present development of an expression to compute the expected energy consumption per operational cycle of a schedule-driven WSN by taking into consideration the node level activities, i.e., sensing and processing, and the network level activities, i.e., channel access, packet collision, retransmission attempts, and transmission of a data packet.
Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.
In safety critical I/O and intercomputer communication networks, reliable message transmission is an important concern. Difficulties of communication and fault identification in networks arise primarily because the sender of a transmission cannot be identified with certainty, an intermediate node can corrupt a message without certainty of detection, and a babbling node cannot be identified and silenced without lengthy diagnosis and reconfiguration . Authentication protocols use digital signature techniques to verify the authenticity of messages with high probability. Such protocols appear to provide an efficient solution to many of these problems. The objective of this program is to develop, demonstrate, and evaluate intercomputer communication architectures which employ authentication. As a context for the evaluation, the authentication protocol-based communication concept was demonstrated under this program by hosting a real-time flight critical guidance, navigation and control algorithm on a distributed, heterogeneous, mixed redundancy system of workstations and embedded fault-tolerant computers.
A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.
No abstract available
A computing device for controlling the operation of an additive manufacturing machine comprises a memory element and a processing element. The memory element is configured to store a three-dimensional model of a part to be manufactured, wherein the three-dimensional model defines a plurality of cross sections of the part. The processing element is in communication with the memory element. The processing element is configured to receive the three-dimensional model, determine a path across a surface of each cross section, wherein the path includes a plurality of parallel lines, calculate a power for a radiation beam to scan each of the lines, such that the power varies from line to line non-linearly according to a length of the line, and calculate a scan speed for the radiation beam for each of the lines, such that the scan speed varies line to line non-linearly according to the power of the radiation beam.
A computing device for controlling the operation of an additive manufacturing machine comprises a memory element and a processing element. The memory element is configured to store a three-dimensional model of a part to be manufactured, wherein the three-dimensional model defines a plurality of cross sections of the part. The processing element is in communication with the memory element. The processing element is configured to receive the three-dimensional model, determine a plurality of paths, each path including a plurality of parallel lines, determine a radiation beam power for each line, such that the radiation beam power varies non-linearly according to a length of the line, and determine a radiation beam scan speed for each line, such that the radiation beam scan speed is a function of a temperature of a material used to manufacture the part, the length of the line, and the radiation beam power for the line.
A computing device for controlling the operation of an additive manufacturing machine comprises a memory element and a processing element. The memory element is configured to store a three-dimensional model of a part to be manufactured, wherein the three-dimensional model defines a plurality of cross sections of the part. The processing element is in communication with the memory element. The processing element is configured to receive the three-dimensional model, determine a plurality of paths, each path including a plurality of parallel lines, determine a radiation beam power for each line, such that the radiation beam power varies non-linearly according to a length of the line, and determine a radiation beam scan speed for each line, such that the radiation beam scan speed is a function of a temperature of a material used to manufacture the part, the length of the line, and the radiation beam power for the line.