Dale J. Mortensen

Hardware Architecture Study for NASA's Space Software Defined Radios

This study defines a hardware architecture approach for software defined radios to enable commonality among NASA space missions. The architecture accommodates a range of reconfigurable processing technologies including general purpose processors, digital signal processors, field programmable date arrays (FPGAs), and application specific integrated circuits (ASICs) in addition to flexible and tunable radio frequency (RF) front ends to satisfy varying mission requirements. The hardware architecture consists of modules, radio functions, and interfaces. The modules are a logical division of common radio functions that comprise a typical communication radio. This paper describes the architecture details, module definitions, the typical functions on each module and the module interfaces. Trade-offs between component-based, custom architecture and a functional-based, open architecture are described. The architecture does not specify a physical implementation internally on each module, nor does the architecture mandate the standards or ratings of the hardware used to construct the radios

Multi-objective reinforcement learning-based deep neural networks for cognitive space communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through ‘virtual environment exploration’. Improvements in the multi-objective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located on-board the International Space Station.

Bandwidth-Efficient Communication through 225 MHz Ka-band Relay Satellite Channel

The communications and navigation space infrastructure of the National Aeronautics and Space Administration (NASA) consists of a constellation of relay satellites (called Tracking and Data Relay Satellites (TDRS)) and a global set of ground stations to receive and deliver data to researchers around the world from mission spacecraft throughout the solar system. Planning is underway to enhance and transform the infrastructure over the coming decade. Key to the upgrade will be the simultaneous and efficient use of relay transponders to minimize cost and operations while supporting science and exploration spacecraft. Efficient use of transponders necessitates bandwidth efficient communications to best use and maximize data throughput within the allocated spectrum. Experiments conducted with NASAs Space Communication and Navigation (SCaN) Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques, such as bandwidth-efficient modulations, in an operational flight system. Demonstrations of these new techniques in realistic flight conditions provides critical experience and reduces the risk of using these techniques in future missions. Efficient use of spectrum is enabled by using high-order modulations coupled with efficient forward error correction codes. This paper presents a high-rate, bandwidth-efficient waveform operating over the 225 MHz Ka-band service of the TDRS System (TDRSS). The testing explores the application of Gaussian Minimum Shift Keying (GMSK), 2/4/8-phase shift keying (PSK) and 16/32- amplitude PSK (APSK) providing over three bits-per-second-per-Hertz (3 b/s/Hz) modulation combined with various LDPC encoding rates to maximize through- put. With a symbol rate of 200 M-band, coded data rates of 1000 Mbps were tested in the laboratory and up to 800 Mbps over the TDRS 225 MHz channel. This paper will present on the high-rate waveform design, channel characteristics, performance results, compensation techniques for filtering and equalization, and architecture considerations going forward for efficient use of NASAs infrastructure.

Variable Coding and Modulation Experiment Using NASA's Space Communication and Navigation Testbed

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.

Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

Previous research on cognitive radios has addressed the performance of various machinelearning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different crosslayer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

Link adaptation for mitigating Earth-to-Space propagation effects on the NASA SCaN testbed

In Earth-to-Space communications, well-known propagation effects such as path loss and atmospheric loss can lead to fluctuations in the strength of the communications link between a satellite and its ground station. Additionally, the typically unconsidered effect of shadowing due to the geometry of the satellite and its solar panels can also lead to link degradation. As a result of these anticipated channel impairments, NASAs communication links have been traditionally designed to handle the worst-case impact of these effects through high link margins and static, lower rate, modulation formats. The work presented in this paper aims to relax these constraints by providing an improved trade-off between data rate and link margin through utilizing link adaptation. More specifically, this work provides a simulation study on the propagation effects impacting NASAs SCaN Testbed flight software-defined radio (SDR) as well as proposes a link adaptation algorithm that varies the modulation format of a communications link as its signal-to-noise ratio fluctuates. Ultimately, the models developed in this work will be utilized to conduct real-time flight experiments on-board the NASA SCaN Testbed.

Lessons Learned in the First Year Operating Software Defined Radios in Space

Operating three unique software defined radios (SDRs) in a space environment aboard the Space Communications and Navigation (SCaN) Testbed for over one year has provided an opportunity to gather knowledge useful for future missions considering using software defined radios. This paper provides recommendations for the development and use of SDRs, and it considers the details of each SDRs approach to software upgrades and operation. After one year, the SCaN Testbed SDRs have operated for over 1000 hours. During this time, the waveforms launched with the SDR were tested on-orbit to assure that they operated in space at the same performance level as on the ground prior to launch to obtain an initial on-orbit performance baseline. A new waveform for each SDR has been developed, implemented, uploaded to the flight system, and tested in the flight environment. Recommendations for SDR-based missions have been gathered from early development through operations. These recommendations will aid future missions to reduce the cost, schedule, and risk of operating SDRs in a space environment. This paper considers the lessons learned as they apply to SDR pre-launch checkout, purchasing space-rated hardware, flexibility in command and telemetry methods, on-orbit diagnostics, use of engineering models to aid future development, and third-party software. Each SDR implements the SCaN Testbed flight computer command and telemetry interface uniquely, allowing comparisons to be drawn. The paper discusses the lessons learned from these three unique implementations, with suggestions on the preferred approach. Also, results are presented showing that it is important to have full system performance knowledge prior to launch to establish better performance baselines in space, requiring additional test applications to be developed pre-launch. Finally, the paper presents the issues encountered with the operation and implementation of new waveforms on each SDR and proposes recommendations to avoid these issues.

Automated Spacecraft Communications Service Demonstration Using NASA's SCaN Testbed

The traditional paradigm for space mission operations relies on inefficient, highly scripted pre-planned activities between space communications & navigation service providers and user ground mission operations centers. Typically, there is limited or nonexistent automation capabilities on the user spacecraft for requesting space communications services, and on the provider network for request dispositioning and service provisioning. In the past, using these processes for space networks was sufficient with the relatively small number of user spacecraft requesting services. However, with an ever increasing number of satellites launched to orbit, more complex event-driven science objectives, exploration missions involving collaborative platforms, and more distant missions, approaches that improve automation, flexibility and efficiency are needed. This paper describes NASA’s recently completed on-orbit demonstration of a new space communications service concept called User Initiated Service, its implementation, results, and a discussion for infusing this innovation into operations.