19 research outputs found
Disruptive events in high-density cellular networks
Stochastic geometry models are used to study wireless networks, particularly
cellular phone networks, but most of the research focuses on the typical user,
often ignoring atypical events, which can be highly disruptive and of interest
to network operators. We examine atypical events when a unexpected large
proportion of users are disconnected or connected by proposing a hybrid
approach based on ray launching simulation and point process theory. This work
is motivated by recent results using large deviations theory applied to the
signal-to-interference ratio. This theory provides a tool for the stochastic
analysis of atypical but disruptive events, particularly when the density of
transmitters is high. For a section of a European city, we introduce a new
stochastic model of a single network cell that uses ray launching data
generated with the open source RaLaNS package, giving deterministic path loss
values. We collect statistics on the fraction of (dis)connected users in the
uplink, and observe that the probability of an unexpected large proportion of
disconnected users decreases exponentially when the transmitter density
increases. This observation implies that denser networks become more stable in
the sense that the probability of the fraction of (dis)connected users
deviating from its mean, is exponentially small. We also empirically obtain and
illustrate the density of users for network configurations in the disruptive
event, which highlights the fact that such bottleneck behaviour not only stems
from too many users at the cell boundary, but also from the near-far effect of
many users in the immediate vicinity of the base station. We discuss the
implications of these findings and outline possible future research directions.Comment: 8 pages, 11 figure
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Disruptive events in high-density cellular networks
Stochastic geometry models are used to study wireless networks,
particularly cellular phone networks, but most of the research focuses on the
typical user, often ignoring atypical events, which can be highly disruptive
and of interest to network operators. We examine atypical events when a
unexpected large proportion of users are disconnected or connected by
proposing a hybrid approach based on ray launching simulation and point
process theory. This work is motivated by recent results [12] using large
deviations theory applied to the signal-to-interference ratio. This theory
provides a tool for the stochastic analysis of atypical but disruptive
events, particularly when the density of transmitters is high. For a section
of a European city, we introduce a new stochastic model of a single network
cell that uses ray launching data generated with the open source RaLaNS
package, giving deterministic path loss values. We collect statistics on the
fraction of (dis)connected users in the uplink, and observe that the
probability of an unexpected large proportion of disconnected users decreases
exponentially when the transmitter density increases. This observation
implies that denser networks become more stable in the sense that the
probability of the fraction of (dis)connected users deviating from its mean,
is exponentially small. We also empirically obtain and illustrate the density
of users for network configurations in the disruptive event, which highlights
the fact that such bottleneck behaviour not only stems from too many users at
the cell boundary, but also from the near-far effect of many users in the
immediate vicinity of the base station. We discuss the implications of these
findings and outline possible future research directions
Galactic SNR candidates in the ROSAT all-sky survey
Identified radio supernova remnants (SNRs) in the Galaxy comprise an
incomplete sample of the SNR population due to various selection effects. ROSAT
performed the first all-sky survey with an imaging X-ray telescope, and thus
provides another window for finding SNRs and compact objects that may reside
within them. Performing a search for extended X-ray sources in the ROSAT
all-sky survey database about 350 objects were identified as SNR candidates in
recent years (Busser 1998). Continuing this systematic search, we have
reanalysed the ROSAT all-sky survey (RASS) data of these candidates and
correlated the results with radio surveys like NVSS, ATNF, Molonglo and
Effelsberg. A further correlation with SIMBAD and NED was performed for
subsequent identification purposes. About 50 of the 350 candidates turned out
to be likely galaxies or clusters of galaxies. We found 14 RASS sources which
are very promising SNR candidates and are currently subject of further
follow-up studies. We will provide the details of the identification campaign
and present first results.Comment: 4 pages, 1 figures, appears in "Neutron Stars in Supernova Remnants"
(ASP Conference Proceedings), eds P. O. Slane and B. M. Gaensler, 2002, p.39
Disruptive events in high-density cellular networks
Stochastic geometry models are used to study wireless networks, particularly cellular phone networks, but most of the research focuses on the typical user, often ignoring atypical events, which can be highly disruptive and of interest to network operators. We examine atypical events when a unexpected large proportion of users are disconnected or connected by proposing a hybrid approach based on ray launching simulation and point process theory. This work is motivated by recent results [12] using large deviations theory applied to the signal-to-interference ratio. This theory provides a tool for the stochastic analysis of atypical but disruptive events, particularly when the density of transmitters is high. For a section of a European city, we introduce a new stochastic model of a single network cell that uses ray launching data generated with the open source RaLaNS package, giving deterministic path loss values. We collect statistics on the fraction of (dis)connected users in the uplink, and observe that the probability of an unexpected large proportion of disconnected users decreases exponentially when the transmitter density increases. This observation implies that denser networks become more stable in the sense that the probability of the fraction of (dis)connected users deviating from its mean, is exponentially small. We also empirically obtain and illustrate the density of users for network configurations in the disruptive event, which highlights the fact that such bottleneck behaviour not only stems from too many users at the cell boundary, but also from the near-far effect of many users in the immediate vicinity of the base station. We discuss the implications of these findings and outline possible future research directions
Near-infrared flares from accreting gas around the supermassive black hole at the Galactic Centre
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