This thesis deals with the problem of estimating the velocity of a mobile station (MS)in a mobile communication system using the instantaneous frequency (IF) of the received signal at the MS antenna. This estimate is essential for satisfactory handover performance, effective dynamic channel assignment, and optimisation of adaptive multiple access wireless receivers. Conventional methods for estimating the MS velocity are based either on the statistics of the envelope or quadrature components of the received signal. In chapter 4 of the thesis, we show that their performance deteriorates in the presence of shadowing. Other velocity estimators have also been proposed which require prior estimation of the channel or the average received power. These are generally difficult to obtain due to the non-stationary nature of the received signal. An appropriate window which depends on the unknown MS velocity must first be applied in order to accurately estimate the required quantities. Using the statistics of the IF of the received signal at the MS antenna given in chapter 3, new velocity estimators are proposed in chapter 4 of this thesis. The proposed estimators are based on the moments, zero-crossing rate, and covariance of the received IF. Since the IF of the received signal is not affected by any amplitude distortion, the proposed IF-based estimators are robust to shadowing and propagation path-loss. The estimators for the MS velocity in a macro- and micro-cellular system are presented separately. A macro-cell system can be considered as a special case of a micro-cell in which there is no line-of-sight component at the receiver antenna. It follows that those estimators which are derived for micro-cells can be used in a macro-cell as well. In chapter 4, we analyse the performance of the proposed velocity estimators in the presence of additive noise, non-isotropic scattering, and shadowing. We also prove analytically that the proposed velocity estimators outperform the existing methods in the presence of shadowing and additive noise. The proposed IF-based estimators need prior estimation of both the IF of the received signal and Ricean K-factor. The IF estimation in a typical wireless environment, can be considered as a special case of a general problem of IF estimation in the presence of multiplicative and additive noise. In chapter 5, we show that current time-frequency approaches to this problem which are based on the peak of a time-frequency distribution (TFD) of the signal, fail because of the special shape of the power spectral density of the multiplicative noise in a wireless environment. To overcome this drawback, the use of the first-order moment of a TFD is studied in chapter 5. Theoretical analysis and simulations show that the IF estimator based on the first-order moment of a TFD exhibits negligible bias when the signal-to-additive noise ratio is more than 10 dB. The Ricean K-factor is not only necessary for velocity estimation in micro-cells, but also is a measure of the severity of fading and a good indicator of the channel quality. Two new methods for estimating the Ricean K-factor based on the first two moments of the envelope of the received signal, are proposed in chapter 6. Performance analysis presented in chapter 6, prove that the proposed K estimators are robust to non-isotropic scattering. Theoretical analysis and simulations which are presented in chapters 4 and 7 of this thesis, prove that the proposed velocity and K estimators outperform existing estimators in the presence of shadowing and additive noise.

Submitted by Livia Mello (liviacmello@yahoo.com.br) on 2016-09-23T19:10:12Z No. of bitstreams: 1 TeseEBS.pdf: 936379 bytes, checksum: a7cd0812b331249755b7a9df5447e035 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T14:48:37Z (GMT) No. of bitstreams: 1 TeseEBS.pdf: 936379 bytes, checksum: a7cd0812b331249755b7a9df5447e035 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T14:48:44Z (GMT) No. of bitstreams: 1 TeseEBS.pdf: 936379 bytes, checksum: a7cd0812b331249755b7a9df5447e035 (MD5) / Made available in DSpace on 2016-10-10T14:48:50Z (GMT). No. of bitstreams: 1 TeseEBS.pdf: 936379 bytes, checksum: a7cd0812b331249755b7a9df5447e035 (MD5) Previous issue date: 2016-02-04 / Não recebi financiamento / In regression models in which a covariate is measured with error, it is common to use structures that correlate the observed covariate with the true non-observed covariate. Such structures are usually additive or multiplicative. In the literature there are several interesting works that deal with regression models having an additive measurement error, many of which are linear models with covariate and measurement error normally distributed. For models having a multiplicative measurement error, one does not find in the literature the same theoretical amount of works as one finds for models in which the measurement error is additive. The same happens in situations where the supositions of normality for the covariates and the measurement errors do not apply. The present work proposes the construction, definition, estimation methods, and diagnostic analysis for the regression models with a multiplicative measurement error in one of the covariates. For these models it is considered that the response variable may belong either to the class of modified power series regression models or to the exponential family. The list of distributions belonging to the family modified power series is rather comprehensive; for this reason this work develops, firstly and in a general way, the models estimation and validation theory, and, as an example, presents the model of negative binomial regression with measurement error. In the case where the response variable belongs to the exponential family, the model of beta regression with multiplicative measurement error is presented. All proposed models were analysed through simulation studies and applied to real data sets. / Em modelos de regressão em que uma covariável é medida com erro, é comum o uso de estruturas que relacionam a covariável observada com a verdadeira covariável não observada. Essas estruturas são usualmente aditivas ou multiplicativas. Na literatura existem diversos trabalhos interessantes que tratam de modelos de regressão com erro de medida aditivo, muitos dos quais são modelos lineares com covariáveis e erro de medida normalmente distribuídos. Para modelos em que o erro de medida é multiplicativo, não se encontra na literatura o mesmo desenvolvimento teórico encontrado para modelos em que o erro de medida é aditivo. O mesmo vale para situações em que as suposições de normalidade para as covariáveis e erro de medida não se aplicam. Este trabalho propõe a construção, definição, métodos de estimação e análise de diagnóstico para modelos de regressão com erro de medida multiplicativo em uma das covariáveis. Para esses modelos, consideramos que a variável resposta possa pertencer ou à classe de modelos de regressão série de potências modificadas ou à família exponencial. O rol de distribuições pertencentes à família série de potências modificada é bem abrangente, portanto, neste trabalho, desenvolvemos a teoria de estimação e validação do modelo primeiramente de forma geral e, para exemplificar, apresentamos o modelo de regressão binomial negativa com erro de medida. Para o caso em que a variável resposta pertença à família exponencial, apresentamos o modelo de regressão beta com erro de medida multiplicativo. Todos os modelos propostos foram analisados através de estudos de simulação e aplicados a conjuntos de dados reais.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-06-08T13:15:08Z No. of bitstreams: 1 dantedonizetipereira.pdf: 460175 bytes, checksum: 092f58c5d71aa77ff03d0ae0604294a1 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-06-26T18:10:56Z (GMT) No. of bitstreams: 1 dantedonizetipereira.pdf: 460175 bytes, checksum: 092f58c5d71aa77ff03d0ae0604294a1 (MD5) / Made available in DSpace on 2017-06-26T18:10:56Z (GMT). No. of bitstreams: 1 dantedonizetipereira.pdf: 460175 bytes, checksum: 092f58c5d71aa77ff03d0ae0604294a1 (MD5) Previous issue date: 2013-07-18 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Nesta tese exploramos diferentes aspectos de teorias clássicas e quânticas de campos. Na parte clássica, examinamos o fenômeno da birrefringência eletro-magneto-óptica em ele-trodinâmica não-linear no contexto de meios materiais dielétricos não-lineares como uma correção efetiva à teoria linear maxwelliana do eletromagnetismo. Na parte quântica, seguindo o método do heat kernel em teoria quântica de campos sobre espaços curvos, derivamos e estudamos a estrutura das divergências a 1-loop para a ação efetiva de diferentes modelos. Em particular, no ramo do modelo de Yukawa, exibimos duas novas formas de ambiguidades as quais tomam lugar na ação efetiva de campos fermiônicos através do fenômeno da anomalia multiplicativa não-local. Além disso, analisamos a estrutura das divergências ultravioletas a 1-loop para um modelo recentemente proposto de gravitação massiva livre de fantasmas, e mostramos que esse modelo encontra sérias dificuldades no nível quântico. / In this thesis we explore different aspects in classical and quantum field theories. In the classical part, we examine the phenomenon of electro-magneto-optical birefringence in nonlinear electrodynamics in the context of nonlinear dielectric media as an effective correction to the linear Maxwellian theory of electromagnetism. In the quantum part, following the heat kernel method in quantum field theory on curved spaces, we derive and study the structure of the 1-loop divergences for the effective action of different models. In particular, through the Yukawa model, we show two new forms of ambiguities which take place in the effective action of fermionic fields through the phenomenon of nonlocal multiplicative anomaly. Moreover, we analyzed the structure of ultraviolet divergences at 1-loop for a recently proposed ghost-free massive gravity model, and we show that this model meets serious difficulties at the quantum level.

Scheduling has always been an indispensable part of resource allocation in wireless networks. Accurate information about channel-state is assumed as a modeling simplification. However, in a real-life network ,e.g., Long Term Evolution(LTE) or IEEE 802.16e WiMAX, the channel-state information feedback to the transmitter can have uncertainty. The primary reason being that although resource allocation is done at the finer granularity of a Physical Resource Block (PRB), channel-state information is still feedback at the coarser granularity of a sub band, which is a group of PRBs. This is done to reduce the feedback traffic from the users to the Base Station. However, this averaging causes information loss and hence, the resulting uncertainty at the scheduler. Moreover, uncertainty might be present in the channel-estimates because of the very process of estimation. In the first part of the thesis, we model the channel-estimate in accuracy and characterize the network stability region. Compared to earlier works, we allow the channel estimates to have dependence among themselves, which is a more realistic situation in a modern LTE or WiMax network. We then propose two simple Max Weight based scheduling schemes that achieve any rate in the interior of the stability region. We also derive an asymptotically tight upper bound on the mean queueing delay in our system under one of the throughput-optimal policies we propose. The above policies ensure stability of the network and we have also obtained bounds on the mean queueing delays. However, different applications may require certain quality of service which may not be satisfied by these policies. Thus, we also propose a throughput-optimal policy for the network under traffic with heterogeneous QoS constraints and present some numerical results studying its performance. In the second part of the thesis, we study the problem of energy-efficient scheduling under average delay constraint. For wireless access technologies, the largest power consumer is the Base Station(BS). Any reduction in the power consumption in a BS will reduce carbon footprint from the Information and Communication Technology sector. We concentrate on the problem of minimizing the total non-renewable power consumed in a Green BS, that is powered by renewable energy sources ,e.g., solar/wind energy and may also be connected to the power grid or diesel generators. Specifically, we consider the problem of minimizing the average grid power consumption of a Green BS downlink in scheduling multiple users with average delay constraints. We have a packetized model for the data packets (i.e., the packets cannot be fragmented) which is a more realistic model for packet-switched networks. The power function is a non-decreasing convex function of the queue-lengths and only one user is allowed to transmit in a slot. We prove the existence of a power optimal policy under delay constraints for multiple users. We analyse the problem and provide some structural results for the optimal policy.

Understanding the functional impact of physical interactions between proteins and DNA on gene expression is important for developing approaches to correct disease-associated gene dysregulation. I conducted a systematic, functional genetic analysis of protein-DNA interactions in the promoter region of the yeast ribonucleotide reductase subunit gene RNR3. I measured the transcriptional impact of systematically perturbing the major transcriptional regulator, Crt1, and three X-box sites on the DNA known to physically bind Crt1. This analysis revealed interactions between two of the three X-boxes in the presence of Crt1, and unexpectedly, a significant functional role of the X-boxes in the absence of Crt1. Further analysis revealed Crt1- independent regulators of RNR3 that were impacted by X-box perturbation. Taken together, these results support the notion that higher-order X-box-mediated interactions are important for RNR3 transcription, and that the X-boxes have unexpected roles in the regulation of RNR3 transcription that extend beyond their interaction with Crt1.

L'objet de cette thèse est l'étude de certaines propriétés arithmétiques et combinatoires de la fonction somme des chiffres. Nous commençons par étudier les sommes d'exponentielles de la forme $dissum_{nleq x}expleft(2ipileft(frac{l}{m}S_q(n)+frac{k}{m'}S_{q}(n+1)+theta nright)right)$ en vue de montrer un résultat d'équirépartition modulo $1$ et un théorème probabiliste d'ErdH{o}s-Kac. Ensuite, on va généraliser un problème dû à Gelfond concernant l'étude de la répartition dans les progressions arithmétiques de la fonction somme des chiffres au cas des nombres ellipséphiques. En particulier, on donne un théorème analogue à celui d'Erdös, Mauduit et S'arközy sur l'uniforme répartition des entiers ellipséphiques dans les progressions arithmétiques sous une contrainte sur la somme des chiffres. Enfin, une étude de l'ordre moyen de certaines fonctions arithmétiques soumises à des contraintes digitales est faite en conséquence des travaux de Mkaouar et Wannès. / The aim of this thesis is the study of some arithmetic and combinatoric properties of the sum of digits function. We start by the study of exponential sums of the form $dissum_{nleq x}expleft(2ipileft(frac{l}{m}S_q(n)+frac{k}{m'}S_q(n+1)+theta nright)right)$ in order to establish a result of equidistribution modulo $1$ in addition to a probabilistic theorem of the kind ErdH{o}s-Kac. Then, we generalize a problem due to Gelfond concerning the distribution in residue classes of the sum of digits function in the case of integers with missing digits. Besides, we give a similar result to that of ErdH{o}s, Mauduit and S'ark"{o}zy on the uniform distribution of integers with missing digits in arithmetic progressions under a constraint on the sum of digits. Finally, a study of the order of magnitude of some arithmetical functions under digital constraints is done as a consequence of the works of Mkaouar and Wannès.

No description available.

Denna kandidatexamen ligger inom området matematisk statistik. I samarbete med försäkringsbolaget Hedvig syftar denna avhandling till att utforska en ny metod för hantering av Hedvigs försäkringsdata genom att bygga en prissättningsmodell för alla riskförsäkringar med generaliserade linjära modeller. Två generaliserade linjära modeller byggdes, där den första förutspår frekvensen för ett anspråk och den andra förutspår svårighetsgraden. De ursprungliga uppgifterna delades in i 9 förklarande variabler. Båda modellerna inkluderade fem förklarande variabler i början och reducerades sedan. Minskningen resulterade i att fyra av fem egenskaper var förklarande signifikanta i frekvensmodellen och endast en av de fem var förklarande signifikanta i svårighetsmodellen. Var och en av modellerna erhöll relativa risker för nivåerna av deras förklarande variabler. De relativa riskerna resulterade i en total risk för varje nivå. Genom multiplicering av en skapad basnivå med en uppsättning kombination av riskparametrar kan premien för en vald kund erhållas. / Det här kandidatexamensarbetet ligger inom ämnet matematisk statistik. Jag samarbete med försäkringsbolaget Hedvig, avser uppsatsen att undersöka en ny metod att hantera Hedvigs försäkringsdata genom att bygga en prissättningsmodell för drulleförsäkring med hjälp av generaliserade linjära modeller. Två modeller skapades varav den första förutsättningen frekvensen av ett försäkringsanspråk och den andra förutsäger storleken. Originaldatan var indelad i 9 förklarande variabler. Båda modellerna innehöll till en början fem förklarande variabler, vilka sedan reducerades till fyra respektive en variabler i de motsvarande modellerna. Från varje modell kunde sedan de relativa riskerna tas fram för varje kategori av de förklarande variablerna. Tillsammans bildades sedan totalrisken för alla grupper.

The research presented in this thesis addresses different aspects of dynamic portfolio construction and portfolio risk measurement. It brings the research on dynamic portfolio optimization, replicating portfolio construction, dynamic portfolio risk measurement and volatility forecast together. The overall aim of this research is threefold. First, it is aimed to examine the portfolio construction and risk measurement performance of a broad set of volatility forecast and portfolio optimization model. Second, in an effort to improve their forecast accuracy and portfolio construction performance, it is aimed to propose new models or new formulations to the available models. Third, in order to enhance the replication performance of hedge fund returns, it is aimed to introduce a replication approach that has the potential to be used in numerous applications, in investment management. In order to achieve these aims, Chapter 2 addresses risk measurement in dynamic portfolio construction. In this chapter, further evidence on the use of multivariate conditional volatility models in hedge fund risk measurement and portfolio allocation is provided by using monthly returns of hedge fund strategy indices for the period 1990 to 2009. Building on Giamouridis and Vrontos (2007), a broad set of multivariate GARCH models, as well as, the simpler exponentially weighted moving average (EWMA) estimator of RiskMetrics (1996) are considered. It is found that, while multivariate GARCH models provide some improvements in portfolio performance over static models, they are generally dominated by the EWMA model. In particular, in addition to providing a better risk-adjusted performance, the EWMA model leads to dynamic allocation strategies that have a substantially lower turnover and could therefore be expected to involve lower transaction costs. Moreover, it is shown that these results are robust across the low - volatility and high-volatility sub-periods. Chapter 3 addresses optimization in dynamic portfolio construction. In this chapter, the advantages of introducing alternative optimization frameworks over the mean-variance framework in constructing hedge fund portfolios for a fund of funds. Using monthly return data of hedge fund strategy indices for the period 1990 to 2011, the standard mean-variance approach is compared with approaches based on CVaR, CDaR and Omega, for both conservative and aggressive hedge fund investors. In order to estimate portfolio CVaR, CDaR and Omega, a semi-parametric approach is proposed, in which first the marginal density of each hedge fund index is modelled using extreme value theory and the joint density of hedge fund index returns is constructed using a copula-based approach. Then hedge fund returns from this joint density are simulated in order to compute CVaR, CDaR and Omega. The semi-parametric approach is compared with the standard, non-parametric approach, in which the quantiles of the marginal density of portfolio returns are estimated empirically and used to compute CVaR, CDaR and Omega. Two main findings are reported. The first is that CVaR-, CDaR- and Omega-based optimization offers a significant improvement in terms of risk-adjusted portfolio performance over mean-variance optimization. The second is that, for all three risk measures, semi-parametric estimation of the optimal portfolio offers a very significant improvement over non-parametric estimation. The results are robust to as the choice of target return and the estimation period. Chapter 4 searches for improvements in portfolio risk measurement by addressing volatility forecast. In this chapter, two new univariate Markov regime switching models based on intraday range are introduced. A regime switching conditional volatility model is combined with a robust measure of volatility based on intraday range, in a framework for volatility forecasting. This chapter proposes a one-factor and a two-factor model that combine useful properties of range, regime switching, nonlinear filtration, and GARCH frameworks. Any incremental improvement in the performance of volatility forecasting is searched for by employing regime switching in a conditional volatility setting with enhanced information content on true volatility. Weekly S&P500 index data for 1982-2010 is used. Models are evaluated by using a number of volatility proxies, which approximate true integrated volatility. Forecast performance of the proposed models is compared to renowned return-based and range-based models, namely EWMA of Riskmetrics, hybrid EWMA of Harris and Yilmaz (2009), GARCH of Bollerslev (1988), CARR of Chou (2005), FIGARCH of Baillie et al. (1996) and MRSGARCH of Klaassen (2002). It is found that the proposed models produce more accurate out of sample forecasts, contain more information about true volatility and exhibit similar or better performance when used for value at risk comparison. Chapter 5 searches for improvements in risk measurement for a better dynamic portfolio construction. This chapter proposes multivariate versions of one and two factor MRSACR models introduced in the fourth chapter. In these models, useful properties of regime switching models, nonlinear filtration and range-based estimator are combined with a multivariate setting, based on static and dynamic correlation estimates. In comparing the out-of-sample forecast performance of these models, eminent return and range-based volatility models are employed as benchmark models. A hedge fund portfolio construction is conducted in order to investigate the out-of-sample portfolio performance of the proposed models. Also, the out-of-sample performance of each model is tested by using a number of statistical tests. In particular, a broad range of statistical tests and loss functions are utilized in evaluating the forecast performance of the variance covariance matrix of each portfolio. It is found that, in terms statistical test results, proposed models offer significant improvements in forecasting true volatility process, and, in terms of risk and return criteria employed, proposed models perform better than benchmark models. Proposed models construct hedge fund portfolios with higher risk-adjusted returns, lower tail risks, offer superior risk-return tradeoffs and better active management ratios. However, in most cases these improvements come at the expense of higher portfolio turnover and rebalancing expenses. Chapter 6 addresses the dynamic portfolio construction for a better hedge fund return replication and proposes a new approach. In this chapter, a method for hedge fund replication is proposed that uses a factor-based model supplemented with a series of risk and return constraints that implicitly target all the moments of the hedge fund return distribution. The approach is used to replicate the monthly returns of ten broad hedge fund strategy indices, using long-only positions in ten equity, bond, foreign exchange, and commodity indices, all of which can be traded using liquid, investible instruments such as futures, options and exchange traded funds. In out-of-sample tests, proposed approach provides an improvement over the pure factor-based model, offering a closer match to both the return performance and risk characteristics of the hedge fund strategy indices.

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