The work in this thesis concerns the use of reinforcement learning solutions to re-source allocation problems in channelised cellular networks. The methodology of re-inforcement learning techniques was chosen for application to these problems due to its capability of finding efficient policies in a fully on-line, adaptable manner, without requiring specific environment models. All of the presented agent architectures are assumed to simultaneously learn and perform network control functions in a totally on-line and unsupervised manner, and agents are developed with a view to real-world implementability by focussing on techniques that have low resource requirements and make use of only local system information.

This dissertation presents a study of linearization techniques that have been applied to power amplifiers in the cellular communication industry. The objective of this work is to understand the limitations of power amplifiers, specifically the limitations introduced by the use of spectrally efficient modulation schemes. The digitization of communication systems has favored the use of new techniques and technologies capable of increasing the efficiency of costly power amplifiers. The work explores traditional and digital linearization systems; an algorithm based on the principles of natural recombination is proposed to directly address the limitations of previous embodiments. Previous techniques, although effective, have significant implementation costs that increase exponentially with the increasing signal bandwidths. The proposed software-hardware architecture significantly reduces implementation costs and the overall complexity of the design without sacrificing performance. To fulfill the requirements of this study, multiple systems are implemented through simulation and closed-loop hardware. Both simulation and hardware embodiments meet the expected performance metrics, providing validation of the proposed algorithm. The application of the algorithm to memory power amplifier linearization is a new approach to adaptive digital pre-distortion using narrowband feedback. The work will show performance improvements on an amplifier with memory effects suggesting that this technique can be employed as a lower-cost solution to meet requirements when compared to typical system implementations.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 189-194). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 189-194). Also available on the Internet.

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Diss. ETH No. 14577. Eidgenöss. Techn. Hochsch., Diss.--Zürich, 2002.