6,685 research outputs found
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
Wireless Secrecy in Large-Scale Networks
The ability to exchange secret information is critical to many commercial,
governmental, and military networks. The intrinsically secure communications
graph (iS-graph) is a random graph which describes the connections that can be
securely established over a large-scale network, by exploiting the physical
properties of the wireless medium. This paper provides an overview of the main
properties of this new class of random graphs. We first analyze the local
properties of the iS-graph, namely the degree distributions and their
dependence on fading, target secrecy rate, and eavesdropper collusion. To
mitigate the effect of the eavesdroppers, we propose two techniques that
improve secure connectivity. Then, we analyze the global properties of the
iS-graph, namely percolation on the infinite plane, and full connectivity on a
finite region. These results help clarify how the presence of eavesdroppers can
compromise secure communication in a large-scale network.Comment: To appear: Proc. IEEE Information Theory and Applications Workshop
(ITA'11), San Diego, CA, Feb. 2011, pp. 1-10, Invited Pape
Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio
Multimedia content especially videos is expected to dominate data traffic in
next-generation mobile networks. Caching popular content at the network edge
has emerged to be a solution for low-latency content delivery. Compared with
the traditional wireless communication, content delivery has a key
characteristic that many signals coexisting in the air carry identical popular
content. They, however, can interfere with each other at a receiver if their
modulation-and-coding (MAC) schemes are adapted to individual channels
following the classic approach. To address this issue, we present a novel idea
of content adaptive MAC (CAMAC) where adapting MAC schemes to content ensures
that all signals carry identical content are encoded using an identical MAC
scheme, achieving spatial MAC alignment. Consequently, interference can be
harnessed as signals, to improve the reliability of wireless delivery. In the
remaining part of the paper, we focus on quantifying the gain CAMAC can bring
to a content-delivery network using a stochastic-geometry model. Specifically,
content helpers are distributed as a Poisson point process, each of which
transmits a file from a content database based on a given popularity
distribution. It is discovered that the successful content-delivery probability
is closely related to the distribution of the ratio of two independent shot
noise processes, named a shot-noise ratio. The distribution itself is an open
mathematical problem that we tackle in this work. Using stable-distribution
theory and tools from stochastic geometry, the distribution function is derived
in closed form. Extending the result in the context of content-delivery
networks with CAMAC yields the content-delivery probability in different closed
forms. In addition, the gain in the probability due to CAMAC is shown to grow
with the level of skewness in the content popularity distribution.Comment: 32 pages, to appear in IEEE Trans. on Wireless Communicatio
Convergence Speed of the Consensus Algorithm with Interference and Sparse Long-Range Connectivity
We analyze the effect of interference on the convergence rate of average
consensus algorithms, which iteratively compute the measurement average by
message passing among nodes. It is usually assumed that these algorithms
converge faster with a greater exchange of information (i.e., by increased
network connectivity) in every iteration. However, when interference is taken
into account, it is no longer clear if the rate of convergence increases with
network connectivity. We study this problem for randomly-placed
consensus-seeking nodes connected through an interference-limited network. We
investigate the following questions: (a) How does the rate of convergence vary
with increasing communication range of each node? and (b) How does this result
change when each node is allowed to communicate with a few selected far-off
nodes? When nodes schedule their transmissions to avoid interference, we show
that the convergence speed scales with , where is the
communication range and is the number of dimensions. This scaling is the
result of two competing effects when increasing : Increased schedule length
for interference-free transmission vs. the speed gain due to improved
connectivity. Hence, although one-dimensional networks can converge faster from
a greater communication range despite increased interference, the two effects
exactly offset one another in two-dimensions. In higher dimensions, increasing
the communication range can actually degrade the rate of convergence. Our
results thus underline the importance of factoring in the effect of
interference in the design of distributed estimation algorithms.Comment: 27 pages, 4 figure
Techniques for Enhanced Physical-Layer Security
Information-theoretic security--widely accepted as the strictest notion of
security--relies on channel coding techniques that exploit the inherent
randomness of propagation channels to strengthen the security of communications
systems. Within this paradigm, we explore strategies to improve secure
connectivity in a wireless network. We first consider the intrinsically secure
communications graph (iS-graph), a convenient representation of the links that
can be established with information-theoretic security on a large-scale
network. We then propose and characterize two techniques--sectorized
transmission and eavesdropper neutralization--which are shown to dramatically
enhance the connectivity of the iS-graph.Comment: Pre-print, IEEE Global Telecommunications Conference (GLOBECOM'10),
Miami, FL, Dec. 201
More is less: Connectivity in fractal regions
Ad-hoc networks are often deployed in regions with complicated boundaries. We
show that if the boundary is modeled as a fractal, a network requiring line of
sight connections has the counterintuitive property that increasing the number
of nodes decreases the full connection probability. We characterise this decay
as a stretched exponential involving the fractal dimension of the boundary, and
discuss mitigation strategies. Applications of this study include the analysis
and design of sensor networks operating in rugged terrain (e.g. railway
cuttings), mm-wave networks in industrial settings and
vehicle-to-vehicle/vehicle-to-infrastructure networks in urban environments.Comment: 5 page
On Modeling Coverage and Rate of Random Cellular Networks under Generic Channel Fading
In this paper we provide an analytic framework for computing the expected
downlink coverage probability, and the associated data rate of cellular
networks, where base stations are distributed in a random manner. The provided
expressions are in computable integral forms that accommodate generic channel
fading conditions. We develop these expressions by modelling the cellular
interference using stochastic geometry analysis, then we employ them for
comparing the coverage resulting from various channel fading conditions namely
Rayleigh and Rician fading, in addition to the fading-less channel.
Furthermore, we expand the work to accommodate the effects of random frequency
reuse on the cellular coverage and rate. Monte-Carlo simulations are conducted
to validate the theoretical analysis, where the results show a very close
match
Downlink Coverage and Rate Analysis of Low Earth Orbit Satellite Constellations Using Stochastic Geometry
As low Earth orbit (LEO) satellite communication systems are gaining
increasing popularity, new theoretical methodologies are required to
investigate such networks' performance at large. This is because deterministic
and location-based models that have previously been applied to analyze
satellite systems are typically restricted to support simulations only. In this
paper, we derive analytical expressions for the downlink coverage probability
and average data rate of generic LEO networks, regardless of the actual
satellites' locality and their service area geometry. Our solution stems from
stochastic geometry, which abstracts the generic networks into uniform binomial
point processes. Applying the proposed model, we then study the performance of
the networks as a function of key constellation design parameters. Finally, to
fit the theoretical modeling more precisely to real deterministic
constellations, we introduce the effective number of satellites as a parameter
to compensate for the practical uneven distribution of satellites on different
latitudes. In addition to deriving exact network performance metrics, the study
reveals several guidelines for selecting the design parameters for future
massive LEO constellations, e.g., the number of frequency channels and
altitude.Comment: Accepted for publication in the IEEE Transactions on Communications
in April 202
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