Thesis (M.S. in Management of Technology)--Vanderbilt University, May 2006. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 127-140).

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 128-133). Also available in electronic version.

Made available in DSpace on 2014-06-12T15:50:41Z (GMT). No. of bitstreams: 1 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / A popularização da Internet e a demanda por acesso de alta velocidade levou ao desenvolvimento da Broadband Wireless Access. Apesar do seu grande potencial, a comunicação via rádio impõe alguns desafios. Uma grande limitação é o próprio meio de transmissão devido a efeitos inerentes à propagação de radio como o path loss, frequency selective fading, espalhamento Doppler e multipath delay-spread. Nesse contexto, o OFDM é uma tecnologia promissora por causa de sua tolerância a problemas de perdas e multi-caminho. Devido à combinação de canais independentes, é possível usar diferentes modulações em cada sub-carrier, de acordo com as condições do canal. Esta técnica é conhecida como adaptive modulation and coding. Além disso, em uma arquitetura ponto a multi-ponto, múltiplos usuários podem compartilhar o espectro ao se atribuir diferentes conjuntos de sub-carriers, tirando vantagem do um efeito conhecido como diversidade multi-usuário. Em comparação com outras técnicas de múltiplo acesso, o OFDMA permite um melhor aproveitamento da diversidade multi-usuário com a possibilidade de uma alocação com alta granularidade. Muitas pesquisas têm investigado técnicas adaptativas capazes de melhorar a eficiência espectral em sistemas multi-usuário. Essas técnicas são normalmente formuladas como constraint optimization problems, conhecidos por serem NP-hard. Neste trabalho, adotamos uma abordagem heurística para lidar com esse tipo de problema. O objetivo principal é desenvolver uma estratégia de alocação fazendo uso eficiente dos recursos disponíveis e maximizando a eficiência espectral total. Entretanto, um estratégia que apenas procura maximizar a eficiência espectral pode gerar um problema relacionado à justiça no compartilhamento de recursos. Outrossim, com a popularização das redes sem fio, é esperado que elas sejam capazes de prover uma maior variedade de serviços com diferentes requisites de QoS e largura de banda. Portanto, procuramos desenvolver um algoritmo que permita ao operador da rede definir esses requisitos. De acordo com eles, o algoritmo deve fornecer o maior throughput possível dentro dos limites estabelecidos por essas restrições

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In this dissertation, we discuss various aspects of scheduling and resource allocation in multi-user wireless systems. This work starts from how to utilize advanced physical-layer technology to improve the system performance in a multi-user environment. We show that by using superposition coding (SPC) and successive interference cancellation, the system performance can be greatly improved with utility-based scheduling. Several observations are made as the design guideline for such system. Scheduling algorithms are designed for a system with hierarchical modulation which is a practical implementation of SPC. However, when the utility-based scheduling is designed, it is based on the assumption that the system is saturated, {\em i.e.}, users in the system always have data to transmit. It is pointed out in the literature that in a system with stochastic traffic, even if the arrival rate lies inside the capacity region, the system in terms of queue might not be stable with the utility-based scheduling. Motivated by this, we have studied the stability region of a general utility-based scheduling in a multi-user system with stochastic traffic. We show that the stability region is generally less than the capacity region, depends on how to interpret an intermediate control variable, and the resultant stability region may be even non-convex and exhibits undesirable properties which should be avoided. As the utility-based scheduling cannot achieve throughput-optimal, we turn our attentions to the throughput-optimal scheduling algorithms, whose stability region is identical to the capacity region. The limiting properties of an overloaded wireless system with throughput-optimal scheduling algorithms are studied. The results show that the queue length is unstable however the scheduling function of the queue length is stable, and the average throughput of the system converges. Finally we study how to schedule users in a multi-user wireless system with information-theoretic security support, which is focused on the secrecy outage probability. The problem is essentially about how to schedule users, and allocate resources to stabilize the system and minimize the secrecy outage probability. We show that there is a tradeoff between the arrival rate of the traffic and the secrecy outage probability. The relative channel condition of the eavesdropper also plays an important role to the secrecy outage probability. In summary, we showed utility-based scheduling using SPC can improve the system performance greatly, but the utility-based scheduling has limitations: the stability region might not have desired properties. On the contrary throughput-optimal scheduling has its own drawbacks: the traffic cannot be handled properly if the system is overloaded. The further study on the secrecy outage probability gives guideline on how to design a scheduler in a system with information-theoretic security support. / Graduate

The primary objective of this study was to examine changes in resource productivity and factor shares as irrigation was introduced on small rice farms using traditional management techniques. Average output on irrigated farms was double that of dry farms. This was because irrigated farms produced two crops as opposed to one crop on farms without irrigation. Examination of marginal products showed that farmers with irrigation could profitably use more land. Dry farmers could profitably use more labor. The low labor input and high MP of labor on dry farms occurs because these farmers are undercapitalized and are obliged to accept off-farm employment at crucial periods of the rice . growing season. On both farm types, irrigated and dry, factor shares of land were high suggesting that a redistribution of land would also redistribute income. This information provides criteria for formation of rice production policy in Ecuador.

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Traditionally, space situational awareness (SSA) sensor networks have relied on dynamic programming theory to generate tasking plans which govern how sensors are allocated to observe resident space objects. Deep reinforcement learning (DRL) techniques, with their ability to be trained on simulated environments, which are readily available for the SSA sensor allocation problem, and demonstrated performance in other fields, have potential to exceed performance of deterministic methods. The research presented in this dissertation develops techniques for encoding an SSA environment model to apply DRL to the sensor allocation problem. This dissertation is the compilation of two separate but related studies. The first study compares two alternative invalid action handling techniques, penalization and masking. The second study examines the performance of policies that have forecast state knowledge incorporated in the observation space. / Doctor of Philosophy / Resident space objects (RSOs) are typically tracked by ground-based sensors (telescopes and radar). Determining how to allocate sensors to RSOs is a complex problem traditionally performed by dynamic programming techniques. Deep reinforcement learning (DRL), a subset of machine learning, has demonstrated performance in other fields, and has the potential to exceed performance of traditional techniques. The research presented in this dissertation develops techniques for encoding a space situational awareness environment model to apply DRL to the sensor allocation problem. This dissertation is the compilation of two separate but related studies. The first study compares two alternative invalid action handling techniques, penalization and masking. The second study examines the performance of policies that have forecast state knowledge incorporated in the observation space.