Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine

Timothy M. Hackett, Sven G. Bilen, Paulo Victor Rodrigues Ferreira, Alexander M. Wyglinski, Richard C. Reinhart, Dale J. Mortensen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Cognitive algorithms for communications systems have been presented in literature, but very few have been integrated into a fielded system, especially space communications systems. In this paper, we describe the implementation of a multi-objective reinforcement-learning algorithm using deep artificial neural networks acting as a radio-resource-allocation controller. The developed software core is generic in nature and can be ported readily to another application. The cognitive engine algorithm implementation was characterized through a series of tests using both a ground-based system and a space-based system. The ground system comprised of engineering-model software-defined radios, commercial modems, and RF equipment emulating the targeted space-to-ground channel. The on-orbit communication system, including a space-based, remotely controlled transmitter, resides on the International Space Station and operates with a ground-based receiver at NASA Glenn Research Center. Through a series of on-orbit tests, the cognitive engine was tested in a highly dynamic channel and its performance is discussed and analyzed.

Original languageEnglish (US)
Article number8510837
Pages (from-to)825-842
Number of pages18
JournalIEEE Transactions on Cognitive Communications and Networking
Volume4
Issue number4
DOIs
StatePublished - Dec 1 2018

Fingerprint

Communication systems
Orbits
Engines
Communication
Testing
Antenna grounds
Radio receivers
Reinforcement learning
Modems
Space stations
Learning algorithms
Resource allocation
NASA
Transmitters
Neural networks
Controllers

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Hackett, Timothy M. ; Bilen, Sven G. ; Ferreira, Paulo Victor Rodrigues ; Wyglinski, Alexander M. ; Reinhart, Richard C. ; Mortensen, Dale J. / Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine. In: IEEE Transactions on Cognitive Communications and Networking. 2018 ; Vol. 4, No. 4. pp. 825-842.
@article{5e207e08fc4147389ae6c92242d0081e,
title = "Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine",
abstract = "Cognitive algorithms for communications systems have been presented in literature, but very few have been integrated into a fielded system, especially space communications systems. In this paper, we describe the implementation of a multi-objective reinforcement-learning algorithm using deep artificial neural networks acting as a radio-resource-allocation controller. The developed software core is generic in nature and can be ported readily to another application. The cognitive engine algorithm implementation was characterized through a series of tests using both a ground-based system and a space-based system. The ground system comprised of engineering-model software-defined radios, commercial modems, and RF equipment emulating the targeted space-to-ground channel. The on-orbit communication system, including a space-based, remotely controlled transmitter, resides on the International Space Station and operates with a ground-based receiver at NASA Glenn Research Center. Through a series of on-orbit tests, the cognitive engine was tested in a highly dynamic channel and its performance is discussed and analyzed.",
author = "Hackett, {Timothy M.} and Bilen, {Sven G.} and Ferreira, {Paulo Victor Rodrigues} and Wyglinski, {Alexander M.} and Reinhart, {Richard C.} and Mortensen, {Dale J.}",
year = "2018",
month = "12",
day = "1",
doi = "10.1109/TCCN.2018.2878202",
language = "English (US)",
volume = "4",
pages = "825--842",
journal = "IEEE Transactions on Cognitive Communications and Networking",
issn = "2332-7731",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",

}

Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine. / Hackett, Timothy M.; Bilen, Sven G.; Ferreira, Paulo Victor Rodrigues; Wyglinski, Alexander M.; Reinhart, Richard C.; Mortensen, Dale J.

In: IEEE Transactions on Cognitive Communications and Networking, Vol. 4, No. 4, 8510837, 01.12.2018, p. 825-842.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine

AU - Hackett, Timothy M.

AU - Bilen, Sven G.

AU - Ferreira, Paulo Victor Rodrigues

AU - Wyglinski, Alexander M.

AU - Reinhart, Richard C.

AU - Mortensen, Dale J.

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Cognitive algorithms for communications systems have been presented in literature, but very few have been integrated into a fielded system, especially space communications systems. In this paper, we describe the implementation of a multi-objective reinforcement-learning algorithm using deep artificial neural networks acting as a radio-resource-allocation controller. The developed software core is generic in nature and can be ported readily to another application. The cognitive engine algorithm implementation was characterized through a series of tests using both a ground-based system and a space-based system. The ground system comprised of engineering-model software-defined radios, commercial modems, and RF equipment emulating the targeted space-to-ground channel. The on-orbit communication system, including a space-based, remotely controlled transmitter, resides on the International Space Station and operates with a ground-based receiver at NASA Glenn Research Center. Through a series of on-orbit tests, the cognitive engine was tested in a highly dynamic channel and its performance is discussed and analyzed.

AB - Cognitive algorithms for communications systems have been presented in literature, but very few have been integrated into a fielded system, especially space communications systems. In this paper, we describe the implementation of a multi-objective reinforcement-learning algorithm using deep artificial neural networks acting as a radio-resource-allocation controller. The developed software core is generic in nature and can be ported readily to another application. The cognitive engine algorithm implementation was characterized through a series of tests using both a ground-based system and a space-based system. The ground system comprised of engineering-model software-defined radios, commercial modems, and RF equipment emulating the targeted space-to-ground channel. The on-orbit communication system, including a space-based, remotely controlled transmitter, resides on the International Space Station and operates with a ground-based receiver at NASA Glenn Research Center. Through a series of on-orbit tests, the cognitive engine was tested in a highly dynamic channel and its performance is discussed and analyzed.

UR - http://www.scopus.com/inward/record.url?scp=85059200867&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059200867&partnerID=8YFLogxK

U2 - 10.1109/TCCN.2018.2878202

DO - 10.1109/TCCN.2018.2878202

M3 - Article

AN - SCOPUS:85059200867

VL - 4

SP - 825

EP - 842

JO - IEEE Transactions on Cognitive Communications and Networking

JF - IEEE Transactions on Cognitive Communications and Networking

SN - 2332-7731

IS - 4

M1 - 8510837

ER -