225,363 research outputs found
Sidelobe Control in Collaborative Beamforming via Node Selection
Collaborative beamforming (CB) is a power efficient method for data
communications in wireless sensor networks (WSNs) which aims at increasing the
transmission range in the network by radiating the power from a cluster of
sensor nodes in the directions of the intended base station(s) or access
point(s) (BSs/APs). The CB average beampattern expresses a deterministic
behavior and can be used for characterizing/controling the transmission at
intended direction(s), since the mainlobe of the CB beampattern is independent
on the particular random node locations. However, the CB for a cluster formed
by a limited number of collaborative nodes results in a sample beampattern with
sidelobes that severely depend on the particular node locations. High level
sidelobes can cause unacceptable interference when they occur at directions of
unintended BSs/APs. Therefore, sidelobe control in CB has a potential to
increase the network capacity and wireless channel availability by decreasing
the interference. Traditional sidelobe control techniques are proposed for
centralized antenna arrays and, therefore, are not suitable for WSNs. In this
paper, we show that distributed, scalable, and low-complexity sidelobe control
techniques suitable for CB in WSNs can be developed based on node selection
technique which make use of the randomness of the node locations. A node
selection algorithm with low-rate feedback is developed to search over
different node combinations. The performance of the proposed algorithm is
analyzed in terms of the average number of trials required to select the
collaborative nodes and the resulting interference. Our simulation results
approve the theoretical analysis and show that the interference is
significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin
Connectivity in Sub-Poisson Networks
We consider a class of point processes (pp), which we call {\em sub-Poisson};
these are pp that can be directionally-convexly () dominated by some
Poisson pp. The order has already been shown useful in comparing various
point process characteristics, including Ripley's and correlation functions as
well as shot-noise fields generated by pp, indicating in particular that
smaller in the order processes exhibit more regularity (less clustering,
less voids) in the repartition of their points. Using these results, in this
paper we study the impact of the ordering of pp on the properties of two
continuum percolation models, which have been proposed in the literature to
address macroscopic connectivity properties of large wireless networks. As the
first main result of this paper, we extend the classical result on the
existence of phase transition in the percolation of the Gilbert's graph (called
also the Boolean model), generated by a homogeneous Poisson pp, to the class of
homogeneous sub-Poisson pp. We also extend a recent result of the same nature
for the SINR graph, to sub-Poisson pp. Finally, as examples we show that the
so-called perturbed lattices are sub-Poisson. More generally, perturbed
lattices provide some spectrum of models that ranges from periodic grids,
usually considered in cellular network context, to Poisson ad-hoc networks, and
to various more clustered pp including some doubly stochastic Poisson ones.Comment: 8 pages, 10 figures, to appear in Proc. of Allerton 2010. For an
extended version see http://hal.inria.fr/inria-00497707 version
Interference between a large number of independent Bose-Einstein condensates
We study theoretically the interference patterns produced by the overlap of
an array of Bose-Einstein condensates that have no phase coherence among them.
We show that density-density correlations at different quasimomenta, which play
an important role in two-condensate interference, become negligible for large
, where is the number of overlapping condensates. In order to understand
the physics of this phenomenon, it is sufficient to consider the periodicity of
the lattice and the statistical probability distribution of a random-walk
problem. The average visibility of such interference patterns decreases as
for large .Comment: 9 pages, 2 figure
Interference Mitigation in Large Random Wireless Networks
A central problem in the operation of large wireless networks is how to deal
with interference -- the unwanted signals being sent by transmitters that a
receiver is not interested in. This thesis looks at ways of combating such
interference.
In Chapters 1 and 2, we outline the necessary information and communication
theory background, including the concept of capacity. We also include an
overview of a new set of schemes for dealing with interference known as
interference alignment, paying special attention to a channel-state-based
strategy called ergodic interference alignment.
In Chapter 3, we consider the operation of large regular and random networks
by treating interference as background noise. We consider the local performance
of a single node, and the global performance of a very large network.
In Chapter 4, we use ergodic interference alignment to derive the asymptotic
sum-capacity of large random dense networks. These networks are derived from a
physical model of node placement where signal strength decays over the distance
between transmitters and receivers. (See also arXiv:1002.0235 and
arXiv:0907.5165.)
In Chapter 5, we look at methods of reducing the long time delays incurred by
ergodic interference alignment. We analyse the tradeoff between reducing delay
and lowering the communication rate. (See also arXiv:1004.0208.)
In Chapter 6, we outline a problem that is equivalent to the problem of
pooled group testing for defective items. We then present some new work that
uses information theoretic techniques to attack group testing. We introduce for
the first time the concept of the group testing channel, which allows for
modelling of a wide range of statistical error models for testing. We derive
new results on the number of tests required to accurately detect defective
items, including when using sequential `adaptive' tests.Comment: PhD thesis, University of Bristol, 201
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