THESIS
2014
iii leaves, iv-xv, 170 pages : illustrations ; 30 cm
Abstract
Providing performance reliability in uncertain environments is an important task, yet a crucial challenge,
in many engineering problems. Particularly for today’s high speed wireless communication
systems (WCSs), obtaining accurate channel state information at the transmitter (CSIT) for scheduler
design is a difficult task; hence robust design is of critical concern. In this thesis, we study
how to achieve various design objectives in such adverse scenarios by modeling different Chance
Constrained Stochastic Optimization (CCSO) problems; in particular, we introduce three novel
problems and their corresponding solutions as follows. First we study throughput optimization under
heterogeneous delay constraints via our proposed simple queueing theoretical formula for rate
equivalence...[
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Providing performance reliability in uncertain environments is an important task, yet a crucial challenge,
in many engineering problems. Particularly for today’s high speed wireless communication
systems (WCSs), obtaining accurate channel state information at the transmitter (CSIT) for scheduler
design is a difficult task; hence robust design is of critical concern. In this thesis, we study
how to achieve various design objectives in such adverse scenarios by modeling different Chance
Constrained Stochastic Optimization (CCSO) problems; in particular, we introduce three novel
problems and their corresponding solutions as follows. First we study throughput optimization under
heterogeneous delay constraints via our proposed simple queueing theoretical formula for rate
equivalence of delay performance. Second we provide distributive implementation and feedback
reduction techniques via a statistical tool called extreme value theory. While the first two problems
are studied under the classical error distribution model approach, our third contribution proposes a
new CCSO framework, which allows one to get rid of the Cumulative Distribution Function (CDF)
assumption of the uncertainty. Our approach further provides significant performance enhancement
over classical CCSO by introducing an information-adaptive procedure that distinguishes
uncertainty into useful information and noise, instead of the single type of uncertainty presented in the existing literature.
We focus on demonstrating the applicability of these three solutions through a widely deployed
example of a WCS called Orthogonal Frequency Division Multiple Access (OFDMA) system. In
particular, we are the first to provide an optimal joint-subcarrier encoding design, with a jointly
optimal subcarrier and power allocation which satisfies the outage constraint. Furthermore, both in
simulation and theory, we demonstrate the performance enhancements of our schemes over existing
CSIT-error inconsiderate schemes, and their capability to provide the aforementioned novel functionality: providing delay constraints satisfaction, distributive design with low feedback overhead, and online design in the absence of CSIT error statistics, without incurring extra complexity, and with convergence proof for the proposed algorithms.
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