Affiliation:
1. Australian National University
2. University of California, Santa Cruz
3. The University of Auckland
4. University of Canterbury
Abstract
Network capacity and reliability for free space optical communication
(FSOC) is strongly driven by ground station availability, which is
dominated by local cloud cover causing an outage. Here, we combine
remote sensing data and novel methods to provide a generalized
framework for assessing and optimizing optical ground station
networks. This work is guided by an example network of eight
Australian and New Zealand optical communication ground stations that
span approximately 60° in longitude and 20° in latitude.
Utilizing time-dependent cloud cover data from five satellites, we
present a detailed analysis that determines the network availability
and diversity, which showed that the Australasian region is
well-suited for an optical network with a 69% average site
availability and low spatial cloud cover correlations. Employing
methods from computational neuroscience, we provide a Monte Carlo
method for sampling the joint probability distribution of site
availabilities for an arbitrarily sized and point-wise correlated
network of ground stations. Furthermore, we develop a general
heuristic for site selection under availability and correlation
optimizations and combine it with orbital propagation simulations to
compare the data capacity between optimized networks and the example
network. We show that the example network may be capable of providing
tens of terabits per day to a low Earth orbit satellite and up to
99.97% reliability to geostationary satellites. We therefore used the
Australasian region to demonstrate, to the best of our knowledge,
novel, generalized tools for assessing and optimizing FSOC ground
station networks, as well as the suitability of the region for hosting
such a network.
Funder
Australian Government Research Training
Program
Commonwealth Scientific and Industrial
Research Organisation
Australian National
University
Ministry of Business, Innovation and
Employment
Subject
Computer Networks and Communications
Cited by
3 articles.
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