9,226 research outputs found
Interference in Poisson Networks with Isotropically Distributed Nodes
Practical wireless networks are finite, and hence non-stationary with nodes
typically non-homo-geneously deployed over the area. This leads to a
location-dependent performance and to boundary effects which are both often
neglected in network modeling. In this work, interference in networks with
nodes distributed according to an isotropic but not necessarily stationary
Poisson point process (PPP) are studied. The resulting link performance is
precisely characterized as a function of (i) an arbitrary receiver location and
of (ii) an arbitrary isotropic shape of the spatial distribution. Closed-form
expressions for the first moment and the Laplace transform of the interference
are derived for the path loss exponents and , and simple
bounds are derived for other cases. The developed model is applied to practical
problems in network analysis: for instance, the accuracy loss due to neglecting
border effects is shown to be undesirably high within transition regions of
certain deployment scenarios. Using a throughput metric not relying on the
stationarity of the spatial node distribution, the spatial throughput locally
around a given node is characterized.Comment: This work was presented in part at ISIT 201
Performance of Optimum Combining in a Poisson Field of Interferers and Rayleigh Fading Channels
This paper studies the performance of antenna array processing in distributed
multiple access networks without power control. The interference is represented
as a Poisson point process. Desired and interfering signals are subject to both
path-loss fading (with an exponent greater than 2) and to independent Rayleigh
fading. Using these assumptions, we derive the exact closed form expression for
the cumulative distribution function of the output
signal-to-interference-plus-noise ratio when optimum combining is applied. This
results in a pertinent measure of the network performance in terms of the
outage probability, which in turn provides insights into the network capacity
gain that could be achieved with antenna array processing. We present and
discuss examples of applications, as well as some numerical results.Comment: Submitted to IEEE Trans. on Wireless Communication (Jan. 2009
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina
Laplace Functional Ordering of Point Processes in Large-scale Wireless Networks
Stochastic orders on point processes are partial orders which capture notions
like being larger or more variable. Laplace functional ordering of point
processes is a useful stochastic order for comparing spatial deployments of
wireless networks. It is shown that the ordering of point processes is
preserved under independent operations such as marking, thinning, clustering,
superposition, and random translation. Laplace functional ordering can be used
to establish comparisons of several performance metrics such as coverage
probability, achievable rate, and resource allocation even when closed form
expressions of such metrics are unavailable. Applications in several network
scenarios are also provided where tradeoffs between coverage and interference
as well as fairness and peakyness are studied. Monte-Carlo simulations are used
to supplement our analytical results.Comment: 30 pages, 5 figures, Submitted to Hindawi Wireless Communications and
Mobile Computin
On Scaling Limits of Power Law Shot-noise Fields
This article studies the scaling limit of a class of shot-noise fields
defined on an independently marked stationary Poisson point process and with a
power law response function. Under appropriate conditions, it is shown that the
shot-noise field can be scaled suitably to have a -stable limit,
intensity of the underlying point process goes to infinity. It is also shown
that the finite dimensional distributions of the limiting random field have
i.i.d. stable random components. We hence propose to call this limte the
- stable white noise field. Analogous results are also obtained for the
extremal shot-noise field which converges to a Fr\'{e}chet white noise field.
Finally, these results are applied to the analysis of wireless networks.Comment: 17 pages, Typos are correcte
Analysis of Static Cellular Cooperation between Mutually Nearest Neighboring Nodes
Cooperation in cellular networks is a promising scheme to improve system
performance. Existing works consider that a user dynamically chooses the
stations that cooperate for his/her service, but such assumption often has
practical limitations. Instead, cooperation groups can be predefined and
static, with nodes linked by fixed infrastructure. To analyze such a potential
network, we propose a grouping method based on node proximity. With the
Mutually Nearest Neighbour Relation, we allow the formation of singles and
pairs of nodes. Given an initial topology for the stations, two new point
processes are defined, one for the singles and one for the pairs. We derive
structural characteristics for these processes and analyse the resulting
interference fields. When the node positions follow a Poisson Point Process
(PPP) the processes of singles and pairs are not Poisson. However, the
performance of the original model can be approximated by the superposition of
two PPPs. This allows the derivation of exact expressions for the coverage
probability. Numerical evaluation shows coverage gains from different signal
cooperation that can reach up to 15% compared to the standard noncooperative
coverage. The analysis is general and can be applied to any type of cooperation
in pairs of transmitting nodes.Comment: 17 pages, double column, Appendices A-D, 9 Figures, 18 total
subfigures. arXiv admin note: text overlap with arXiv:1604.0464
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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