Future spacecraft communication subsystems will potentially benefit from software-defined radios controlled by artificial intelligence algorithms. In this paper, we propose a novel radio resource allocation algorithm leveraging multiobjective reinforcement learning and artificial neural network ensembles able to manage available resources and conflicting mission-based goals. The uncertainty in the performance of thousands of possible radio parameter combinations and the dynamic behavior of the radio channel over time producing a continuous multidimensional state–action space requires a fixed-size memory continuous state–action mapping instead of the traditional discrete mapping. In addition, actions need to be decoupled from states in order to allow for online learning, performance monitoring, and resource allocation prediction. The proposed approach leverages the authors’ previous research on constraining decisions predicted to have poor performance through ”virtual environment exploration.” The simulation results show the performance for different communication mission profiles, and accuracy benchmarks are provided for the future research reference. The proposed approach constitutes part of the core cognitive engine proof-of-concept delivered to the NASA John H. Glenn Research Center’s SCaN Testbed radios on-board the International Space Station.

NASA is developing an architecture standard for software-defined radios used in space- and ground-based platforms to enable commonality among radio developments to enhance capability and services while reducing mission and programmatic risk. Transceivers (or transponders) with functionality primarily defined in software (e.g., firmware) have the ability to change their functional behavior through software alone. This radio architecture standard offers value by employing common waveform software interfaces, method of instantiation, operation, and testing among different compliant hardware and software products. These common interfaces within the architecture abstract application software from the underlying hardware to enable technology insertion independently at either the software or hardware layer. This paper presents the initial Space Telecommunications Radio System architecture for NASA missions to provide the desired software abstraction and flexibility while minimizing the resources necessary to support the architecture.

This paper presents the tool chain, methodology, and initial results of a study to provide a thorough, objective, and quantitative analysis of the design alternatives for space software defined radio (SDR) transceivers. The approach taken was to develop a set of models and tools for describing communications requirements, the algorithm resource requirements, the available hardware, and the alternative software architectures, and generate analysis data necessary to compare alternative designs. The space transceiver analysis tool (STAT) was developed to help users identify and select representative designs, calculate the analysis data, and perform a comparative analysis of the representative designs. The tool allows the design space to be searched quickly while permitting incremental refinement in regions of higher payoff

The Advanced Communications Technology Satellite (ACTS) was conceived at the National Aeronautics and Space Administration (NASA) in the late 1970s as a follow-on program to ATS and CTS to continue NASA's long history of satellite communications projects. The ACTS project set the stage for the C-band satellites that started the industry, and later the ACTS project established the use of Ku-band for video distribution and direct-to-home broadcasting. ACTS, launched in September 1993 from the Space Shuttle, created a revolution in satellite system architecture by using digital communications techniques employing key technologies such as a fast hopping multibeam antenna, an on-board baseband processor, a wide-band microwave switch matrix, adaptive rain fade compensation, and the use of 900 MHz transponders operating at Ka-band frequencies. This paper describes the lessons learned in each of the key ACTS technology areas, as well as in propagation investigations.