Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cognitive Communication”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

CLAIRE: Enabling Heterogeneous Communication Network Optimization for Robust and Resilient Operations

In this paper, we present the capabilities of the CLAIRE System which provides resilient communications for NASA in presence of interference and congestion for a heterogeneous multi-vendor network. CLAIRE increases mission science data return to improve resource efficiencies and ensures resilience in the unpredictable space environment for NASA missions and communication networks. CLAIRE provides technology / waveform agnostic cognitive control plane that is instantiated at the Application Layer (APP) so that it can ride on NASA’s HDTN bundle protocol or any other protocol stack that is used by the network. The cognitive control plane is instantiated using Heartbeats (HTBTs). CLAIRE is assisted by Wideband UHF-Ka Band RF Sensing that leverages advances in the Direct Digital Transceiver (DDTRX) technology. The Wideband RF Sensing is driven by statistical signal processing and machine learning algorithms. Interference is mitigated using Dynamic Spectrum Access (DSA). Finally, CLAIRE addresses congestion using spectrum aware packet forwarding algorithm. CLAIRE provides an extensible protocol that allows passing of RF spectrum situational awareness, cross-layer sensing, delay tolerant networking and dynamic spectrum access information that can help with network optimization. Cross-Layer Sensing (CLS) and CLAIRE Decision Engine (CDE) enable spectrum and delay aware packet forwarding and Dynamic Spectrum Access during cases of severe interference.

cognitive communications↗
NASA NTRS2018

Cognitive Anti-Jamming Satellite-To-Ground Communications on NASA's SCaN Testbed

Machine learning aided cognitive anti-jamming communications is designed, developed and demonstrated on a live satellite-to-ground link. A wideband autonomous cognitive radio (WACR) is designed and implemented as a hardware-in-the- loop (HITL) prototype. The cognitive engine (CE) of the WACR is implemented on a PC while the software-defined radio (SDR) platform utilized two different radios for spectrum sensing and actual communications. The cognitive engine performs spectrum knowledge acquisition over the complete spectrum range available for the SATCOM system operation and learns an anti-jamming communications protocol to avoid both intentional jammers and inadvertent interferers using reinforcement learning. When the current satellite-to-ground link is jammed, the cognitive engine of the ground receiver directs the satellite transmitter to switch to a new channel that is predicted to be jammer-free for the longest possible duration. The end-to-end, closed-loop system was tested on the NASA Space Communications and Navigation (SCaN) Testbed on the International Space Station (ISS). The experimental results demonstrated the feasibility of satellite-to-ground cognitive anti-jamming communications along with excellent anti-jamming capability of machine learning aided cognitive protocols against several different types of jammers.

Jayaweera, Sudharman K.↗
NASA NTRS2018

Cognitive Anti-jamming Satellite-to-Ground Communications on NASA's SCaN Testbed

Machine learning aided cognitive anti-jamming communications is designed, developed and demonstrated on an experimental satellite-to-ground link. A wideband autonomous cognitive radio (WACR) is designed and implemented as a hardware-in the-loop (HITL) prototype. The cognitive engine (CE) of the WACR is implemented on a PC while the software-defined radio (SDR) platform utilized two different radios for spectrum sensing and actual communications. The cognitive engine performs spectrum knowledge acquisition over the complete spectrum range available for the SATCOM system operation and learns an anti-jamming communications protocol to avoid both intentional jammers and inadvertent interferers using reinforcement learning. When the current satellite-to-ground link is jammed, the cognitive engine of the ground receiver directs the satellite transmitter to switch to a new channel that is predicted to be jammer-free for the longest possible duration. The end-to-end, closed-loop system was tested with the NASA's Space Communications and Networking (SCaN) testbed on the International Space Station (ISS). The experimental results demonstrated the feasibility of satellite-to-ground cognitive anti-jamming communications along with excellent anti-jamming capability of machine-learning aided cognitive protocols against several different types of jammers.

Jayaweera, Sudharman K.↗
NASA NTRS2013

Cognitive Networking With Regards to NASA's Space Communication and Navigation Program

This report describes cognitive networking (CN) and its application to NASA's Space Communication and Networking (SCaN) Program. This report clarifies the terminology and framework of CN and provides some examples of cognitive systems. It then provides a methodology for developing and deploying CN techniques and technologies. Finally, the report attempts to answer specific questions regarding how CN could benefit SCaN. It also describes SCaN's current and target networks and proposes places where cognition could be deployed.

machine learning↗
NASA NTRSDate not supplied

Cognitive Tapered Slot Circular Array Antenna for Lunar Surface Communications

In this paper, we present the design of a cognitive tapered slot circular array (TSCA) antenna with multiple electronically switched sector beams for lunar surface communication. The circular array is capable of sensing the frequency, power, and direction of arrival of the RF signals. The design of the TSCA builds on our prior work on the development of a single TSA element with a balanced microstrip/coax feed. The measured return loss of the single TSA element shows wide bandwidth with good impedance match across the 5 to 35 GHz frequency range. Additionally, the single TSA has good radiation patterns. The single TSA serves as the building block for a four-element TSCA with multiple electronically switched sector beams for sensing and communications.

Cognitive communications↗
NASA NTRSDate not supplied

Cognitive Tapered Slot Circular Array Antenna for Lunar Surface Communications

In this paper, we present the design of a cognitive tapered slot circular array (TSCA) antenna with multiple electronically switched sector beams for lunar surface communication. The circular array is capable of sensing the frequency, power, and direction of arrival of the RF signals. The design of the TSCA builds on our prior work on the development of a single TSA element with a balanced microstrip/coax feed. The measured return loss of the single TSA element shows wide bandwidth with good impedance match across the 5 to 35 GHz frequency range. Additionally, the single TSA has good radiation patterns. The single TSA serves as the building block for a four-element TSCA with multiple electronically switched sector beams for sensing and communications.

Antenna↗
NASA NTRSDate not supplied

Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment

To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.

CNN↗
NASA NTRS2005

Introduction to System Health Engineering and Management in Aerospace

This paper provides a technical overview of Integrated System Health Engineering and Management (ISHEM). We define ISHEM as "the paper provides a techniques, and technologies used to design, analyze, build, verify, and operate a system to prevent faults and/or minimize their effects." This includes design and manufacturing techniques as well operational and managerial methods. ISHEM is not a "purely technical issue" as it also involves and must account for organizational, communicative, and cognitive f&ms of humans as social beings and as individuals. Thus the paper will discuss in more detail why all of these elements, h m the technical to the cognitive and social, are necessary to build dependable human-machine systems. The paper outlines a functional homework and architecture for ISHEM operations, describes the processes needed to implement ISHEM in the system life-cycle, and provides a theoretical framework to understand the relationship between the different aspects of the discipline. It then derives from these and the social and cognitive bases a set of design and operational principles for ISHEM.

Johnson, Stephen B.↗
NASA NTRS2021

SmallSat Ka-band Operations User Terminal (SKOUT)

SKOUT is a Ka-band communications system for future NASA mission spacecraft that operates with both NASA and commercial relay satellite constellations in GEO and potentially LEO as well as direct-to-Earth (DTE) networks. This project encompasses the development and demonstration of commercial-off-the-shelf (COTS) 5G, Ka band, phased array technologies compatible with commercial space networks, including actively phases array antennas, software defined modems, power optimization algorithms, and high data rate to ground using the DVB-S2 standard.

space communications↗
NASA NTRSDate not supplied

INSPiRE – An Approach to Mission Quality Management using Network Slicing for Space Applications

Managing traffic between the Earth-Moon and Earth-Mars is a complex process requiring significant investment in resources and expertise at NASA. INSPiRE improves the performance of space networks by enabling a dynamic re-configuration process that works for any mixed topology over a heterogeneous and multi-vendor network. To achieve the desired functionality, INSPiRE incorporates a set of algorithms, machine learning processes, and policy inference to handle unpredictable, disruptive events. INSPiRE draws parallels from the current notion of the 3GPP (5G and beyond) Network Slicing approach, where the same physical network divides into several virtual networks, and for each of these virtual networks, there is a guaranteed Quality of Service for the missions that they serve.

cognitive communications↗
NASA NTRSDate not supplied

TechEdSat-11: Prototyping Autonomous Communications in Orbit

Cognitive Engine 1 (CE-1) is a state-of-the-art automated system designed to manage routine operations and respond to adverse events without requiring human operator input. CE-1 will optimize scheduling capabilities, detect and react to link failures, and ensure data delivery deadlines are met efficiently. Seamless roaming between government and commercial providers will allow for a robust and cost-effective network. TechEdSat-11 will demonstrate two key components of CE-1: User Initiated Services (UIS) and Delay Tolerant Networking (DTN). The first phase of the experiment will use UIS to automate on-demand scheduling of a commercial S-band ground station. Later phases of the experiment will demonstrate DTN store-and-forward and space internetworking capabilities through the TechEdSat-11 S-band radio. This paper will discuss the CE-1 main components relevant to the experiment, the flight and ground software architecture, experiment concept of operations and preliminary results.

Rachel Dudukovich↗
NASA NTRS2016

Architecture for Cognitive Networking within NASAs Future Space Communications Infrastructure

Future space mission concepts and designs pose many networking challenges for command, telemetry, and science data applications with diverse end-to-end data delivery needs. For future end-to-end architecture designs, a key challenge is meeting expected application quality of service requirements for multiple simultaneous mission data flows with options to use diverse onboard local data buses, commercial ground networks, and multiple satellite relay constellations in LEO, MEO, GEO, or even deep space relay links. Effectively utilizing a complex network topology requires orchestration and direction that spans the many discrete, individually addressable computer systems, which cause them to act in concert to achieve the overall network goals. The system must be intelligent enough to not only function under nominal conditions, but also adapt to unexpected situations, and reorganize or adapt to perform roles not originally intended for the system or explicitly programmed. This paper describes architecture features of cognitive networking within the future NASA space communications infrastructure, and interacting with the legacy systems and infrastructure in the meantime. The paper begins by discussing the need for increased automation, including inter-system collaboration. This discussion motivates the features of an architecture including cognitive networking for future missions and relays, interoperating with both existing endpoint-based networking models and emerging information-centric models. From this basis, we discuss progress on a proof-of-concept implementation of this architecture as a cognitive networking on-orbit application on the SCaN Testbed attached to the International Space Station.

space networks↗
NASA NTRS2016

Architecture for Cognitive Networking within NASA's Future Space Communications Infrastructure

Future space mission concepts and designs pose many networking challenges for command, telemetry, and science data applications with diverse end-to-end data delivery needs. For future end-to-end architecture designs, a key challenge is meeting expected application quality of service requirements for multiple simultaneous mission data flows with options to use diverse onboard local data buses, commercial ground networks, and multiple satellite relay constellations in LEO, GEO, MEO, or even deep space relay links. Effectively utilizing a complex network topology requires orchestration and direction that spans the many discrete, individually addressable computer systems, which cause them to act in concert to achieve the overall network goals. The system must be intelligent enough to not only function under nominal conditions, but also adapt to unexpected situations, and reorganize or adapt to perform roles not originally intended for the system or explicitly programmed. This paper describes an architecture enabling the development and deployment of cognitive networking capabilities into the envisioned future NASA space communications infrastructure. We begin by discussing the need for increased automation, including inter-system discovery and collaboration. This discussion frames the requirements for an architecture supporting cognitive networking for future missions and relays, including both existing endpoint-based networking models and emerging information-centric models. From this basis, we discuss progress on a proof-of-concept implementation of this architecture, and results of implementation and initial testing of a cognitive networking on-orbit application on the SCaN Testbed attached to the International Space Station.

space networks↗
NASA NTRS2012

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Hutto, Clayton↗
NASA NTRS1994

Collaboration in Controller-Pilot Communication

Like other forms of dialogue, air traffic control (ATC) communication is an act of collaboration between two or more people. Collaboration progresses more or less smoothly depending on speaker and listener strategies. For example, we have found that the way controllers organize and deliver messages influences how easily pilots understand these messages, which in turn determines how much time and effort is needed to successfully complete the transaction. In this talk, I will introduce a collaborative framework for investigating controller-pilot communication and then describe a set of studies that investigate ATC communication from two complementary directions. First, we focused on the impact of ATC message factors (e.g., length, speech rate) on the cognitive processes involved in ATC: communication. Second, we examined pilot factors that influence the amount of cognitive resources available for these communication processes. These studies also illustrate how the collaborate framework can help analyze the impact of proposed visual data link systems on ATC communication. Examining the joint effects of communication medium, message factors, and pilot/controller factors on performance should help improve air safety and communication efficiency. Increased efficiency is important for meeting the growing demands on the National Air System.

Morrow, Daniel↗
NASA NTRS2020

The Potential Effects of Radiation on the Gut-Brain Axis

Humans may be exposed to different types of radiation in their lifetimes, typically in the form of low linear energy transfer (LET) radiation that is, for example, used as a treatment for cancer. In addition, astronauts may be exposed to high LET radiation in outer space. Here, we propose that alterations to the gastrointestinal (GI) microbiota may occur upon exposure to low or high LET radiation, and that these alterations may perturb important relationships that exist between the GI microbiota and human health. For example, the GI microbiota can communicate with the brain via various pathways and molecules, such as the enteric nervous system, the vagus nerve, microbial metabolites, and the immune system. This relationship has been termed the “gut-brain axis”. Alterations to the composition of the GI microbiome can lead to alterations in its functional metabolic output and means of communication, therefore potentially causing downstream cognitive effects. Consequently, studying how radiation can affect this important network of communication could lead to new and critical interventions, as well as prevention strategies. Herein, we review the evidence supporting a relationship between radiation exposure and disruption of the gut-brain axis as well as summarize strategies that may be used to counter the effects of radiation exposure on the GI microbiome.

Carli B. Jones↗
NASA NTRS2025

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗