This dissertation investigates how to optimize
flow-level performance in
interference dominated wireless networks serving dynamic traffic loads. The
schemes presented in this dissertation adapt to long-term (hours) spatial load
variations, and the main metrics of interest are the file transfer delay or average
flow throughput and the mean power expended by the transmitters.
The first part presents a system level approach to interference management
in an infrastructure based wireless network with full frequency reuse.
The key idea is to use loose base station coordination that is tailored to the
spatial load distribution and the propagation environment to exploit the diversity
in a user population's sensitivity to interference. System architecture
and abstractions to enable such coordination are developed for both the downlink
and the uplink cases, which present differing interference characteristics.
The basis for the approach is clustering and aggregation of traffic loads into classes of users with similar interference sensitivities that enable coarse grained
information exchange among base stations with greatly reduced communication
overheads. The dissertation explores ways to model and optimize the
system under dynamic traffic loads where users come and go resulting in interference
induced performance coupling across base stations. Based on extensive
system-level simulations, I demonstrate load-dependent reductions in
file transfer delay ranging from 20-80% as compared to a simple baseline not
unlike systems used in the field today, while simultaneously providing more
uniform coverage. Average savings in user power consumption of up to 75%
are achieved. Performance results under heterogeneous spatial loads illustrate
the importance of being traffic and environment aware.
The second part studies the impact of policies to associate users with
base stations/access points on
flow-level performance in interference limited
wireless networks. Most research in this area has used static interference models
(i.e., neighboring base stations are always active) and resorted to intuitive
objectives such as load balancing. In this dissertation, it is shown that this can
be counter productive, and that asymmetries in load can lead to significantly
better performance in the presence of dynamic interference which couples the
transmission rates experienced by users at various base stations. A methodology
that can be used to optimize the performance of a class of coupled
systems is proposed, and applied to study the user association problem. It is
demonstrated that by properly inducing load asymmetries, substantial performance
gains can be achieved relative to a load balancing policy (e.g., 15 times reduction in mean delay). A novel measurement based, interference-aware
association policy is presented that infers the degree of interference induced
coupling and adapts to it. Systematic simulations establish that both the
optimized static and interference-sensitive, adaptive association policies substantially
outperform various proposed dynamic policies and that these results
are robust to changes in file size distributions, channel parameters, and spatial
load distributions. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/6590 |
| Date | 21 October 2009 |
| Creators | Rengarajan, Balaji |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Format | electronic |
| Rights | Copyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works. |
Page generated in 0.0022 seconds