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
