16,619 research outputs found
Generic Multiuser Coordinated Beamforming for Underlay Spectrum Sharing
The beamforming techniques have been recently studied as possible enablers
for underlay spectrum sharing. The existing beamforming techniques have several
common limitations: they are usually system model specific, cannot operate with
arbitrary number of transmit/receive antennas, and cannot serve arbitrary
number of users. Moreover, the beamforming techniques for underlay spectrum
sharing do not consider the interference originating from the incumbent primary
system. This work extends the common underlay sharing model by incorporating
the interference originating from the incumbent system into generic combined
beamforming design that can be applied on interference, broadcast or multiple
access channels. The paper proposes two novel multiuser beamforming algorithms
for user fairness and sum rate maximization, utilizing newly derived convex
optimization problems for transmit and receive beamformers calculation in a
recursive optimization. Both beamforming algorithms provide efficient operation
for the interference, broadcast and multiple access channels, as well as for
arbitrary number of antennas and secondary users in the system. Furthermore,
the paper proposes a successive transmit/receive optimization approach that
reduces the computational complexity of the proposed recursive algorithms. The
results show that the proposed complexity reduction significantly improves the
convergence rates and can facilitate their operation in scenarios which require
agile beamformers computation.Comment: 30 pages, 5 figure
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
Simulating the tail of the interference in a Poisson network model
Interference among simultaneous transmissions represents the main limitation factor for the capacity and connectivity of dense wireless networks. In this paper we provide efficient simulation laws for the tail of the interference in a simple wireless ad hoc network model. Particularly, we consider node locations distributed according to a Poisson point process and various classes of light-tailed fading distribution
Matching Theory for Future Wireless Networks: Fundamentals and Applications
The emergence of novel wireless networking paradigms such as small cell and
cognitive radio networks has forever transformed the way in which wireless
systems are operated. In particular, the need for self-organizing solutions to
manage the scarce spectral resources has become a prevalent theme in many
emerging wireless systems. In this paper, the first comprehensive tutorial on
the use of matching theory, a Nobelprize winning framework, for resource
management in wireless networks is developed. To cater for the unique features
of emerging wireless networks, a novel, wireless-oriented classification of
matching theory is proposed. Then, the key solution concepts and algorithmic
implementations of this framework are exposed. Then, the developed concepts are
applied in three important wireless networking areas in order to demonstrate
the usefulness of this analytical tool. Results show how matching theory can
effectively improve the performance of resource allocation in all three
applications discussed
- âŠ