255 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
Interference and Outage in Clustered Wireless Ad Hoc Networks
In the analysis of large random wireless networks, the underlying node
distribution is almost ubiquitously assumed to be the homogeneous Poisson point
process. In this paper, the node locations are assumed to form a Poisson
clustered process on the plane. We derive the distributional properties of the
interference and provide upper and lower bounds for its CCDF. We consider the
probability of successful transmission in an interference limited channel when
fading is modeled as Rayleigh. We provide a numerically integrable expression
for the outage probability and closed-form upper and lower bounds.We show that
when the transmitter-receiver distance is large, the success probability is
greater than that of a Poisson arrangement. These results characterize the
performance of the system under geographical or MAC-induced clustering. We
obtain the maximum intensity of transmitting nodes for a given outage
constraint, i.e., the transmission capacity (of this spatial arrangement) and
show that it is equal to that of a Poisson arrangement of nodes. For the
analysis, techniques from stochastic geometry are used, in particular the
probability generating functional of Poisson cluster processes, the Palm
characterization of Poisson cluster processes and the Campbell-Mecke theorem.Comment: Submitted to IEEE Transactions on Information Theor
Transmission capacity of wireless ad hoc networks with successive interference cancellation
IEEE Transactions on Information Theory, 53(8): pp. 2799-2814.The transmission capacity (TC) of a wireless ad hoc
network is defined as the maximum spatial intensity of successful
transmissions such that the outage probability does not exceed
some specified threshold. This work studies the improvement in
TC obtainable with successive interference cancellation (SIC), an
important receiver technique that has been shown to achieve the
capacity of several classes of multiuser channels, but has not been
carefully evaluated in the context of ad hoc wireless networks. This
paper develops closed-form upper bounds and easily computable
lower bounds for the TC of ad hoc networks with SIC receivers,
for both perfect and imperfect SIC. The analysis applies to any
multiuser receiver that cancels the K strongest interfering signals
by a factor : E [0; 1]. In addition to providing the first closed-form
capacity results for SIC in ad hoc networks, design-relevant
insights are made possible. In particular, it is shown that SIC
should be used with direct sequence spread spectrum. Also, any
imperfections in the interference cancellation rapidly degrade its
usefulness. More encouragingly, only a few—often just one—interfering
nodes need to be canceled in order to get the vast majority
of the available performance gain
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