836 research outputs found
On the Feedback Capacity of the Fully Connected -User Interference Channel
The symmetric K user interference channel with fully connected topology is
considered, in which (a) each receiver suffers interference from all other
(K-1) transmitters, and (b) each transmitter has causal and noiseless feedback
from its respective receiver. The number of generalized degrees of freedom
(GDoF) is characterized in terms of \alpha, where the interference-to-noise
ratio (INR) is given by INR=SNR^\alpha. It is shown that the per-user GDoF of
this network is the same as that of the 2-user interference channel with
feedback, except for \alpha=1, for which existence of feedback does not help in
terms of GDoF. The coding scheme proposed for this network, termed cooperative
interference alignment, is based on two key ingredients, namely, interference
alignment and interference decoding. Moreover, an approximate characterization
is provided for the symmetric feedback capacity of the network, when the SNR
and INR are far apart from each other.Comment: 20 pages, 4 figures, to appear in IEEE Transactions on Information
Theor
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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