21,299 research outputs found
CHARACTERIZATION OF FUNDAMENTAL COMMUNICATION LIMITS OF STATE-DEPENDENT INTERFERENCE NETWORKS
Interference management is one of the key techniques that drive evolution of wireless networks from one generation to another. Techniques in current cellular networks to deal with interference follow the basic principle of orthogonalizing transmissions in time, frequency, code, and space. My PhD work investigate information theoretic models that represent a new perspective/technique for interference management. The idea is to explore the fact that an interferer knows the interference that it causes to other users noncausally and can/should exploit such information for canceling the interference. In this way, users can transmit simultaneously and the throughput of wireless networks can be substantially improved. We refer to the interference treated in such a way as ``dirty interference\u27\u27 or noncausal state .
Towards designing a dirty interference cancelation framework, my PhD thesis investigates two classes of information theoretic models and develops dirty interference cancelation schemes that achieve the fundamental communication limits. One class of models (referred to as state-dependent interference channels) capture the scenarios that users help each other to cancel dirty interference. The other class of models (referred to as state-dependent channels with helper) capture the scenarios that one dominate user interferes a number of other users and assists those users to cancel its dirty interference. For both classes of models, we develop dirty interference cancelation schemes and compared the corresponding achievable rate regions (i.e., inner bounds on the capacity region) with the outer bounds on the capacity region. We characterize the channel parameters under which the developed inner bounds meet the outer bounds either partially of fully, and thus establish the capacity regions or partial boundaries of the capacity regions
Beyond Geometry : Towards Fully Realistic Wireless Models
Signal-strength models of wireless communications capture the gradual fading
of signals and the additivity of interference. As such, they are closer to
reality than other models. However, nearly all theoretic work in the SINR model
depends on the assumption of smooth geometric decay, one that is true in free
space but is far off in actual environments. The challenge is to model
realistic environments, including walls, obstacles, reflections and anisotropic
antennas, without making the models algorithmically impractical or analytically
intractable.
We present a simple solution that allows the modeling of arbitrary static
situations by moving from geometry to arbitrary decay spaces. The complexity of
a setting is captured by a metricity parameter Z that indicates how far the
decay space is from satisfying the triangular inequality. All results that hold
in the SINR model in general metrics carry over to decay spaces, with the
resulting time complexity and approximation depending on Z in the same way that
the original results depends on the path loss term alpha. For distributed
algorithms, that to date have appeared to necessarily depend on the planarity,
we indicate how they can be adapted to arbitrary decay spaces.
Finally, we explore the dependence on Z in the approximability of core
problems. In particular, we observe that the capacity maximization problem has
exponential upper and lower bounds in terms of Z in general decay spaces. In
Euclidean metrics and related growth-bounded decay spaces, the performance
depends on the exact metricity definition, with a polynomial upper bound in
terms of Z, but an exponential lower bound in terms of a variant parameter phi.
On the plane, the upper bound result actually yields the first approximation of
a capacity-type SINR problem that is subexponential in alpha
On the Catalyzing Effect of Randomness on the Per-Flow Throughput in Wireless Networks
This paper investigates the throughput capacity of a flow crossing a
multi-hop wireless network, whose geometry is characterized by general
randomness laws including Uniform, Poisson, Heavy-Tailed distributions for both
the nodes' densities and the number of hops. The key contribution is to
demonstrate \textit{how} the \textit{per-flow throughput} depends on the
distribution of 1) the number of nodes inside hops' interference sets, 2)
the number of hops , and 3) the degree of spatial correlations. The
randomness in both 's and is advantageous, i.e., it can yield larger
scalings (as large as ) than in non-random settings. An interesting
consequence is that the per-flow capacity can exhibit the opposite behavior to
the network capacity, which was shown to suffer from a logarithmic decrease in
the presence of randomness. In turn, spatial correlations along the end-to-end
path are detrimental by a logarithmic term
On Capacity and Delay of Multi-channel Wireless Networks with Infrastructure Support
In this paper, we propose a novel multi-channel network with infrastructure
support, called an MC-IS network, which has not been studied in the literature.
To the best of our knowledge, we are the first to study such an MC-IS network.
Our proposed MC-IS network has a number of advantages over three existing
conventional networks, namely a single-channel wireless ad hoc network (called
an SC-AH network), a multi-channel wireless ad hoc network (called an MC-AH
network) and a single-channel network with infrastructure support (called an
SC-IS network). In particular, the network capacity of our proposed MC-IS
network is times higher than that of an SC-AH network and an
MC-AH network and the same as that of an SC-IS network, where is the number
of nodes in the network. The average delay of our MC-IS network is times lower than that of an SC-AH network and an MC-AH network, and
times lower than the average delay of an SC-IS network, where
and denote the number of channels dedicated for infrastructure
communications and the number of interfaces mounted at each infrastructure
node, respectively. Our analysis on an MC-IS network equipped with
omni-directional antennas only has been extended to an MC-IS network equipped
with directional antennas only, which are named as an MC-IS-DA network. We show
that an MC-IS-DA network has an even lower delay of compared with an SC-IS network and our
MC-IS network. For example, when and , an
MC-IS-DA network can further reduce the delay by 24 times lower that of an
MC-IS network and reduce the delay by 288 times lower than that of an SC-IS
network.Comment: accepted, IEEE Transactions on Vehicular Technology, 201
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