435 research outputs found
Delay-rate tradeoff in ergodic interference alignment
Ergodic interference alignment, as introduced by Nazer et al (NGJV), is a
technique that allows high-rate communication in n-user interference networks
with fast fading. It works by splitting communication across a pair of fading
matrices. However, it comes with the overhead of a long time delay until
matchable matrices occur: the delay is q^n^2 for field size q.
In this paper, we outline two new families of schemes, called JAP and JAP-B,
that reduce the expected delay, sometimes at the cost of a reduction in rate
from the NGJV scheme. In particular, we give examples of good schemes for
networks with few users, and show that in large n-user networks, the delay
scales like q^T, where T is quadratic in n for a constant per-user rate and T
is constant for a constant sum-rate. We also show that half the single-user
rate can be achieved while reducing NGJV's delay from q^n^2 to q^(n-1)(n-2).
This extended version includes complete proofs and more details of good
schemes for small n.Comment: Extended version of a paper presented at the 2012 International
Symposium on Information Theory. 7 pages, 1 figur
Delay-rate tradeoff for ergodic interference alignment in the Gaussian case
In interference alignment, users sharing a wireless channel are each able to
achieve data rates of up to half of the non-interfering channel capacity, no
matter the number of users. In an ergodic setting, this is achieved by pairing
complementary channel realizations in order to amplify signals and cancel
interference. However, this scheme has the possibility for large delays in
decoding message symbols. We show that delay can be mitigated by using outputs
from potentially more than two channel realizations, although data rate may be
reduced. We further demonstrate the tradeoff between rate and delay via a
time-sharing strategy. Our analysis considers Gaussian channels; an extension
to finite field channels is also possible.Comment: 7 pages, 2 figures, presented at 48th Allerton Conference on
Communication Control and Computing, 2010. Includes appendix detailing Markov
chain analysi
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
Ergodic Interference Alignment
This paper develops a new communication strategy, ergodic interference
alignment, for the K-user interference channel with time-varying fading. At any
particular time, each receiver will see a superposition of the transmitted
signals plus noise. The standard approach to such a scenario results in each
transmitter-receiver pair achieving a rate proportional to 1/K its
interference-free ergodic capacity. However, given two well-chosen time
indices, the channel coefficients from interfering users can be made to exactly
cancel. By adding up these two observations, each receiver can obtain its
desired signal without any interference. If the channel gains have independent,
uniform phases, this technique allows each user to achieve at least 1/2 its
interference-free ergodic capacity at any signal-to-noise ratio. Prior
interference alignment techniques were only able to attain this performance as
the signal-to-noise ratio tended to infinity. Extensions are given for the case
where each receiver wants a message from more than one transmitter as well as
the "X channel" case (with two receivers) where each transmitter has an
independent message for each receiver. Finally, it is shown how to generalize
this strategy beyond Gaussian channel models. For a class of finite field
interference channels, this approach yields the ergodic capacity region.Comment: 16 pages, 6 figure, To appear in IEEE Transactions on Information
Theor
Channel Aided Interference Alignment
Interference alignment (IA) techniques mostly attain their degrees of freedom
(DoF) benefits as the number of channel extensions tends to infinity.
Intuitively, the more interfering signals that need to be aligned, the larger
the number of dimensions needed to align them. This requirement poses a major
challenge for IA in practical systems. This work evaluates the necessary and
sufficient conditions on channel structure of a fully connected interference
network with time-varying fading to make perfect IA feasible within limited
number of channel extensions. We propose a method based on the obtained
conditions on the channel structure to achieve perfect IA. For the case of
user interference channel, it is shown that only one condition on channel
coefficients is required to make perfect IA feasible at all receivers. IA
feasibility literature have mainly focused on network topology so far. In
contrast, derived channel aiding conditions in this work can be considered as
the perfect IA feasibility conditions on channel structure.Comment: 20 pages, 4 figure. arXiv admin note: text overlap with
arXiv:0901.4379 by other author
Asymptotic Sum-Capacity of Random Gaussian Interference Networks Using Interference Alignment
We consider a dense n-user Gaussian interference network formed by paired
transmitters and receivers placed independently at random in Euclidean space.
Under natural conditions on the node position distributions and signal
attenuation, we prove convergence in probability of the average per-user
capacity C_Sigma/n to 1/2 E log(1 + 2SNR).
The achievability result follows directly from results based on an
interference alignment scheme presented in recent work of Nazer et al. Our main
contribution comes through the converse result, motivated by ideas of
`bottleneck links' developed in recent work of Jafar. An information theoretic
argument gives a capacity bound on such bottleneck links, and probabilistic
counting arguments show there are sufficiently many such links to tightly bound
the sum-capacity of the whole network.Comment: 5 pages; to appear at ISIT 201
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