Space Lasers Have Bright Future in Communications
NASA scientists and engineers seeking faster connectivity with their data-gathering spacecraft are moving away from radio frequency-based communication and turning to laser communications.
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NASA scientists and engineers seeking faster connectivity with their data-gathering spacecraft are moving away from radio frequency-based communication and turning to laser communications.
A study was performed that evaluated the feasibility of Ka-band communication system to provide CubeSat/SmallSat high rate science data downlink with ground antennas ranging from the small portable 1.2m/2.4m to apertures 5.4M, 7.3M, 11M, and 18M, for Low Earth Orbit (LEO) to Lunar CubeSat missions. This study included link analysis to determine the data rate requirement, based on the current TRL of Ka-band flight hardware and ground support infrastructure. Recent advances in Ka-band transceivers and antennas, options of portable ground stations, and various coverage distances were included in the analysis. The link/coverage analysis results show that Cubesat/Smallsat missions communication requirements including frequencies and data rates can be met by utilizing Near Earth Network (NEN) Ka-band support with 2 W and high gain (>6 dBi) antennas.
The Communications and Intelligent Systems Division provides expertise, plans, conducts and directs research and engineering development in the competency fields of advanced communications and intelligent systems technologies for application in current and future aeronautics and space systems.
National Aeronautics and Space Administration (NASA)'s Space Communication and Navigation Testbed is an advanced integrated communication payload on the International Space Station. This paper presents results from an adaptive coding and modulation (ACM) experiment over S-band using a direct-to-earth link between the SCaN Testbed and the Glenn Research Center. The testing leverages the established Digital Video Broadcasting Second Generation (DVB-S2) standard to provide various modulation and coding options, and uses the Space Data Link Protocol (Consultative Committee for Space Data Systems (CCSDS) standard) for the uplink and downlink data framing. The experiment was con- ducted in a challenging environment due to the multipath and shadowing caused by the International Space Station structure. Several approaches for improving the ACM system are presented, including predictive and learning techniques to accommodate signal fades. Performance of the system is evaluated as a function of end-to-end system latency (round- trip delay), and compared to the capacity of the link. Finally, improvements over standard NASA waveforms are presented.
The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.
NASA Goddard has been investing in technology demonstrations of a beacon service, now called Next Generation Broadcast Services (NGBS). NGBS is a global, space-based, communications and navigation service for users of Global Navigation Satellite Systems (GNSS) and the Tracking and Data Relay Satellite System (TDRSS). NGBS will provide an S-band beacon messaging source and radio navigation available to users at orbital altitudes 1400 km and below, increasing the autonomy and resiliency of onboard communication and navigation. NGBS will deliver both one-way radiometric (Doppler and pseudorange) and fast forward data transport services to users. Portions of the overall forward data volume will be allocated for fixed message types while the remaining data volume will be left for user forward command data. The NGBS signal will reside within the 2106.43 MHz spectrum currently allocated for the Space Networks multiple access forward (MAF) service and a live service demonstration is currently being planned via the 2nd and 3rd generation TDRS satellites.
The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The Glenn Research Center (GRC) team made a software-defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development on an STRS compliant platform to support future space communication systems for advanced exploration missions. Validated STRS compliant applications provided tested code with extensive documentation to potentially reduce risk, cost and efforts in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, the sample waveform, and wrapper development efforts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation SDRs for advance exploration missions.
In a communications channel, the space environment between a spacecraft and an Earth ground station can potentially cause the loss of a data link or at least degrade its performance due to atmospheric effects, shadowing, multipath, or other impairments. In adaptive and coded modulation, the signal power level at the receiver can be used in order to choose a modulation-coding technique that maximizes throughput while meeting bit error rate (BER) and other performance requirements. It is the goal of this research to implement a generalized interacting multiple model (IMM) filter based on Kalman filters for improved received power estimation on software-dened radio (SDR) technology for satellite communications applications. The IMM filter has been implemented in Verilog consisting of a customizable bank of Kalman filters for choosing between performance and resource utilization. Each Kalman filter can be implemented using either solely a Schur complement module (for high area efficiency) or with Schur complement, matrix multiplication, and matrix addition modules (for high performance). These modules were simulated and synthesized for the Virtex II platform on the JPL Radio Experimenter Development System (EDS) at NASA Glenn Research Center. The results for simulation, synthesis, and hardware testing are presented.
National Aeronautics and Space Administration (NASA)'s Space Communication and Navigation Testbed is an advanced integrated communication payload on the International Space Station. This paper presents results from an adaptive coding and modulation (ACM) experiment over S-band using a direct-to-earth link between the SCaN Testbed and the Glenn Research Center. The testing leverages the established Digital Video Broadcasting Second Generation (DVB-S2) standard to provide various modulation and coding options, and uses the Space Data Link Protocol (Consultative Committee for Space Data Systems (CCSDS) standard) for the uplink and downlink data framing. The experiment was conducted in a challenging environment due to the multipath and shadowing caused by the International Space Station structure. Several approaches for improving the ACM system are presented, including predictive and learning techniques to accommodate signal fades. Performance of the system is evaluated as a function of end-to-end system latency (round-trip delay), and compared to the capacity of the link. Finally, improvements over standard NASA waveforms are presented.
This presentation provides an overview of the research and engineering work being performed in the competency fields of advanced communications and intelligent systems with emphasis on advanced technologies, architecture definition, and systems development for application in current and future aeronautics and space communications systems.
This presentation provides an overview of the research and engineering work being performed in the competency fields of advanced communications and intelligent systems with emphasis on advanced technologies, architecture definition, and systems development for application in current and future aeronautics and space communications systems.
National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.
Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).
This presentation provides an overview of the research and engineering work being performed in the competency fields of advanced communications and intelligent systems with emphasis on advanced technologies, architecture definition,and systems development for application in current and future aeronautics and space communications systems.
National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.
Millimeter-wave (mmWave) communications will play a key role in enhancing the throughput, reliability, and security of next generation wireless networks. These advancements are achieved through the large bandwidth available in this band and through the use of highly directional links that will be used to overcome the large pathloss at these frequencies. Although the terrestrial application of mmWave systems is advancing at a rapid pace, the use of mmWave communication systems in aviation systems or airports is still in its infancy. This can be attributed to the challenges related to radio technology and lack of development, and characterization of mmWave wireless channels for the aviation field and the airport environment. Consequently, one of our goals is to develop methodologies that support mmWave air to ground links, and various links at airports, by applying new localization schemes that allow for application of highly directional links that can be deployed over longer distances despite the high path loss at mmWave frequencies. However, a very thorough understanding of the mmWave channel models are needed to enable such new applications. To this end, in this paper, we present a survey of the current channel models in the mmWave band. The 3-dimensional statistical channel model is also reviewed and its parameters and typical characteristics for this model are identified and computed through simulation for the Boise metropolitan area.
This is NASA FAA UTM Research Transition Team Communications and Navigation working group kick off meeting presentation that addresses the followings. Objectives overview Overall timeline and scope Outcomes and expectations Communication method and frequency of meetings Upcoming evaluation Next steps.
Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).