10,730 research outputs found
Deep Space Network information system architecture study
The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control
Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts
The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
A High Altitude Platform Station (HAPS) is a network node that operates in
the stratosphere at an of altitude around 20 km and is instrumental for
providing communication services. Precipitated by technological innovations in
the areas of autonomous avionics, array antennas, solar panel efficiency
levels, and battery energy densities, and fueled by flourishing industry
ecosystems, the HAPS has emerged as an indispensable component of
next-generations of wireless networks. In this article, we provide a vision and
framework for the HAPS networks of the future supported by a comprehensive and
state-of-the-art literature review. We highlight the unrealized potential of
HAPS systems and elaborate on their unique ability to serve metropolitan areas.
The latest advancements and promising technologies in the HAPS energy and
payload systems are discussed. The integration of the emerging Reconfigurable
Smart Surface (RSS) technology in the communications payload of HAPS systems
for providing a cost-effective deployment is proposed. A detailed overview of
the radio resource management in HAPS systems is presented along with
synergistic physical layer techniques, including Faster-Than-Nyquist (FTN)
signaling. Numerous aspects of handoff management in HAPS systems are
described. The notable contributions of Artificial Intelligence (AI) in HAPS,
including machine learning in the design, topology management, handoff, and
resource allocation aspects are emphasized. The extensive overview of the
literature we provide is crucial for substantiating our vision that depicts the
expected deployment opportunities and challenges in the next 10 years
(next-generation networks), as well as in the subsequent 10 years
(next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial
SciTech News Volume 71, No. 1 (2017)
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Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects
While monolithic satellite missions still pose significant advantages in terms of accuracy and
operations, novel distributed architectures are promising improved flexibility, responsiveness,
and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite
networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance
satellites are becoming feasible and advantageous alternatives requiring the adoption
of new operation paradigms that enhance their autonomy. While autonomy is a notion that
is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic
in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations
for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy
is also presented as a necessary feature to bring new distributed Earth observation functions
(which require coordination and collaboration mechanisms) and to allow for novel structural
functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission
Planning and Scheduling (MPS) frameworks are then presented as a key component to implement
autonomous operations in satellite missions. An exhaustive knowledge classification explores the
design aspects of MPS for DSS, and conceptually groups them into: components and organizational
paradigms; problem modeling and representation; optimization techniques and metaheuristics;
execution and runtime characteristics and the notions of tasks, resources, and constraints.
This paper concludes by proposing future strands of work devoted to study the trade-offs of
autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that
consider some of the limitations of small spacecraft technologies.Postprint (author's final draft
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