47,605 research outputs found
Estimation over Communication Networks: Performance Bounds and Achievability Results
This paper considers the problem of estimation over communication networks. Suppose a sensor is taking measurements of a dynamic process. However the process needs to be estimated at a remote location connected to the sensor through a network of communication links that drop packets stochastically. We provide a framework for computing the optimal performance in the sense of expected error covariance. Using this framework we characterize the dependency of the performance on the topology of the network and the packet dropping process. For independent and memoryless packet dropping processes we find the steady-state error for some classes of networks and obtain lower and upper bounds for the performance of a general network. Finally we find a necessary and sufficient condition for the stability of the estimate error covariance for general networks with spatially correlated and Markov type dropping process. This interesting condition has a max-cut interpretation
Optimal CSMA-based Wireless Communication with Worst-case Delay and Non-uniform Sizes
Carrier Sense Multiple Access (CSMA) protocols have been shown to reach the
full capacity region for data communication in wireless networks, with
polynomial complexity. However, current literature achieves the throughput
optimality with an exponential delay scaling with the network size, even in a
simplified scenario for transmission jobs with uniform sizes. Although CSMA
protocols with order-optimal average delay have been proposed for specific
topologies, no existing work can provide worst-case delay guarantee for each
job in general network settings, not to mention the case when the jobs have
non-uniform lengths while the throughput optimality is still targeted. In this
paper, we tackle on this issue by proposing a two-timescale CSMA-based data
communication protocol with dynamic decisions on rate control, link scheduling,
job transmission and dropping in polynomial complexity. Through rigorous
analysis, we demonstrate that the proposed protocol can achieve a throughput
utility arbitrarily close to its offline optima for jobs with non-uniform sizes
and worst-case delay guarantees, with a tradeoff of longer maximum allowable
delay
A time dependent performance model for multihop wireless networks with CBR traffic
In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid flow queueing modeling and a time varying connectivity matrix. Network queues are modeled using fluid-flow based differential equation models which are solved using numerical methods, while node mobility is modeled using deterministic or stochastic modeling of adjacency matrix elements. Numerical and simulation experiments show that the new approach can provide reasonably accurate results with significant improvements in the computation time compared to standard simulation tools. © 2010 IEEE
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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