Dans un environnement intérieur, le problème de l'extraction du composant l'Angle de Arrivée de la Line-of-Sight entre un émetteur et un récepteur Wi-Fi utilisant un lien SIMO est la principale préoccupation de cette thèse. Un des principaux défis à relever est dû au riche canal multipath que les environnements intérieurs apprécient. C'est ainsi parce que multipath résulte du fait que le canal de propagation se compose de plusieurs obstacles et réflecteurs. Ainsi, le signal reçu arrive comme un ensemble imprévisible de réflexions et / ou d'ondes directes avec son degré d'atténuation et de retard. D'autres défis sont la limitation des ressources, telles que le nombre d'antennes, la bande passante disponible et le rapport Signal / Bruit; sans parler des «imperfections» Wi-Fi, telles que les disparités de gain / phase entre les antennes et les problèmes de synchronisation entre l'émetteur et le récepteur. Dans cette thèse, notre objectif principal est de mettre en place un système en temps réel qui pourrait mesurer l'angle entre un émetteur et un récepteur en présence de tous les défis. En particulier, nous avons pris en compte tous les facteurs qui perturbent le problème d'estimation de l'angle articulaire et du délai et formulé un modèle de système en conséquence. Ces facteurs sont les suivants: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), et Phase/Delay offsets à chaque antenne. Pour compenser l'efficacité de ces facteurs critiques, nous proposons une méthode d'étalonnage optimale pour compenser tous leurs effets. Cette thèse comprendra également d'autres méthodes théoriques qui doivent faire face au problème d'estimation de l'angle d'arrivée, à partir du point de vue de la compression et du traitement du signal. / In an indoor environment, the problem of extracting the Angle-of-Arrival of the Line-of-Sight component between a transmitter and Wi-Fi receiver using a SIMO link is the main concern of this thesis. One main challenge in doing so is due to the rich multipath channel that indoor environments enjoy. This is so because multipath results from the fact that the propagation channel consists of several obstacles and reflectors. Thus, the received signal arrives as an unpredictable set of reflections and/or direct waves each with its own degree of attenuation and delay. Other challenges are limitation of resources, such as number of antennas, available bandwidth, and Signal-to-Noise-Ratio; not to mention the Wi-Fi ”imperfections”, such as gain/phase mismatches between antennas and synchronisation issues between transmitter and receiver. In this thesis, our main focus is implementing a real-time system that could measure the angle between a transmitter and receiver in the presence of all challenges. In particular, we have taken into account all factors that perturb the Joint Angle and Delay estimation problem and formulated a system model accordingly. These factors are: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), Phase and Delay offsets at each antenna. To compensate for the effect of these critical factors, we propose an offline calibration method to compensate for all their effects. This thesis will also include other theoretical methods that have to deal with Angle-of-Arrival Estimation problem from compressed sensing and signal processing point of views.

The demand for efficient and reliable high rate communication is ever increasing. In this thesis we study different challenges in such systems, and their possible solutions. A goal for many years has been to implement as much as possible of a radio system in the digital domain, the ultimate goal being so called software defined radio (SDR) where the inner workings of a radio standard can be changed completely by changing the software. One important part of an SDR receiver is the high speed analog-to-digital converter (ADC) and one path to reach this high speed is to use a number of parallel, time-interleaved, ADCs. Such ADCs are, however, sensitive to sampling instant offsets, DC level offsets and gain offsets. This thesis discusses estimators based on fractional-delay filters and one application of these estimmators is to estimate and calibrate the relative delay, gain, and DC level offset between the ADCs comprising the time interleaved ADC. In this thesis we also present a technique for carrier frequency offset (CFO) estimation in orthogonal frequency division multiplexing (OFDM) systems. OFDM has gone from a promising digital radio transmission technique to become a mainstream technique used in several current and future standards. The main attractive property of OFDM is that it is inherently resilient to multipath reflections because of its long symbol time. However, this comes at the cost of a relatively high sensitivity to CFO. The proposed estimator is based on locating the spectral minimas within so-called null or virtual subcarriers embedded in the spectrum.~The spectral minimas are found iteratively over a number of symbols and is therefore mainly useful for frequency offset tracking or in systems where an estimate is not immediately required, such as in TV or radio broadcasting systems. However, complexity-wise the estimator is relatively easy to implement and it does not need any extra redundancy beside a nonmodulated subcarrier. The estimator performance is studied both in a channel with additive white Gaussian noise and in a multipath frequency selective channel environment. Interpolators and decimators are an important part of many systems, e.g. radio systems, audio systems etc. Such interpolation (decimation) is often performed using cascaded interpolators (decimators) to reduce the speed requirements in different parts of the system. In a fixed-point implementation, scaling is needed to maximize the use of the available word lengths and to prevent overflow. In the final part of the thesis, we present a method for scaling of multistage interpolators/decimators using multirate signal processing techniques. We also present a technique to estimate the output roundoff noise caused by the internal quantization.

Advances in the development of simple and cheap sensors give new possibilities with large sensor network deployments in monitoring and surveillance applications. Commonly, the sensor positions are not known, specifically, when sensors are randomly spread in a big area. Low cost sensors are constructed with as few components as possible to keep price and energy consumption down. This implies that self-positioning and communication capabilities are low. So the question: “How do you localize such sensors with good precision with a feasible approach?” is central. When no information is available a stable and robust localization algorithm is needed. In this thesis an acoustic sensor network is considered. With a movable acoustic source a well-defined and audible signal is transmitted at different spots. The sensors measure the time of arrival which corresponds to distance. A two-step sensor localization approach is applied that utilizes the estimated distances. A novel approach in the first step is presented to incorporate more measurements and gain more position information. Localization and ranging performance is evaluated with simulations and data collected at field trials. The results show that the novel approach attains higher accuracy and robustness.

n the problem of time delay estimation (TDE), the desired source signals of interest are correlated and with a specific spectral distribution. In such cases, the convergence speed using the conventional approaches, viz., time domain adaptive constrained and unconstrained LMS TDE algorithms, becomes slowly and the performance of TDE will be degraded, dramatically. In fact, the convergence rate depends highly on the distribution of spectral density of the desired signal sources. Also, the performance of TDE is affected by the background noises, accordingly. To circumvent the problem described above, in this thesis, a transformed domain adaptive constrained filtering scheme, refers to the constrained adaptive DCT-LMS algorithm, for TDE is devised. We show that this new proposed constrained algorithm, with the so-called direct delay estimation formula, for non-integer TDE does perform better than the conventional time domain adaptive constrained and unconstrained LMS TDE algorithms and the unconstrained adaptive DCT-LMS TDE algorithm. Finally, to further reduce the spread of eigenvalue in the unconstrained adaptive DCT-LMS algorithm, the Gram-Schmidt orthogonalizer approach realizing by the adaptive Escalator is investigated. It indicates that bias of TDE will occur without using the constraint of weight vector. That is, it could not be used to alleviate the effect due to background noises.

The convergence speed using the conventional approaches, viz., time-domain adaptive constrained and unconstrained LMS algorithms, becomes slowly, when dealing with the correlated source signals. In consequence, the performance of time delay estimation (TDE) will be degraded, dramatically. To improve this problem, the so-called transform-domain adaptive constrained filtering scheme, i.e., the adaptive constrained discrete-cosine-transform (DCT) LMS algorithm, has been proposed in [15]. However, the use of any one orthogonal transform will not result in a completely diagonal the input signal auto-correlation matrix for all types of input signals. In fact, the significant non-diagonal entries in the transform-domain auto-correlation matrix, will deteriorate the convergence performance of the algorithm. To further overcome the problem described above, in this thesis, a modified approach, referred as the adaptive constrained modified DCT-LMS (CMDCT-LMS) algorithm, is devised for TDE under a wide class of input processes. In addition, based on the orthogonal discrete wavelet transform (DWT), an adaptive constrained modified DMT-LMS (CMDWT-LMS) algorithm is also devised and applied to the problem of TDE. We show that the proposed two modified constrained approaches for TDE does perform well than the unmodified approaches under different source signal models. Moreover, the adaptive CMDCT-LMS filtering algorithm does perform slightly better than the adaptive CMDWT-LMS filtering algorithm as observed from the simulation results.

The objective of this thesis is to develop circuit-aware interconnect technology optimization for network-on-chip based many-core architectures. The dimensions of global interconnects in many-core chips are optimized for maximum bandwidth density and minimum delay taking into account network-on-chip router latency and size effects of copper. The optimal dimensions thus obtained are used to characterize different network-on-chip topologies based on wiring area utilization, maximum core-to-core channel width, aggregate chip bandwidth and worse case latency. Finally, the advantages of many-core many-tier chips are evaluated for different network-on-chip topologies. Area occupied by a router within a core is shown to be the bottleneck to achieve higher performance in network-on-chip based architectures.

In this thesis I focus on finding the position of computers on the Internet. This need for locating computers originated in the last several years through the creation of overlay networks. For this activity there are many algorithms. This paper describes the King method that estimated the distance between communicating stations by using the domain name system. The aim of this work is to verify the accuracy of the King method in experimental PlanetLab network. This network provides access for more than 1000 stations worldwide.

Synchronization of distributed time difference of arrival (TDOA) sensor networks can be performed using reference signals from GPS satellites. This method provides high accuracy, but is vulnerable to jamming, and is not reliable enough to be used in military applications. A solution that does not depend on any signals transmitted from external actors is preferred. One way to achieve this is to use reference signals transmitted from a UAV. A UAV is suitable since only local synchronization for a geographically restricted area is necessary. The local synchronization is achieved by estimating the time-delay between the transmission and reception of a reference signal. The estimated time-delay can be used to detect drifts in the clocks of the TDOA sensors. This thesis analyzes com- mon reference signals, to evaluate which provide high accuracy for time-delay estimation, and what properties of the signals influence the estimation accuracy the most. The simulations show that the time-delay estimation performance can reach the same accuracy as synchronization against GPS for different types of signals. An increased bandwidth is more important than an increased signal length or signal-to-noise ratio to improve the estimation accuracy.

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Dentre os fatores limitantes dos sistemas de controle, o tempo morto está entre os mais críticos e de difícil detecção sem testes intrusivos. O conhecimento do seu valor é essencial para a identificação de modelos e na auditoria de desempenho de sistemas de controle. Em virtude disto, o presente trabalho propõe uma metodologia eficaz para estimá-lo utilizando apenas dados históricos de processo em malha fechada. A principal vantagem frente a técnicas disponíveis na literatura é a não necessidade de testes intrusivos. A metodologia é baseada em um tratamento de sinal para remoção dos efeitos do distúrbio não medido e dos erros de modelo. O tratamento de sinal consiste na minimização das oscilações do sinal erro em malha aberta suavizado como função do tempo morto. Diversas formulações de função objetivo e procedimentos de suavização foram estudados visando facilitar a estimação do parâmetro. A qualidade da metodologia é ilustrada através de simulações em uma série de cenários, os quais simulam processos lineares de diferentes características sob o efeito de distúrbios distintos. A metodologia também é testada frente a estudo de casos com dados reais de processo industrial em malhas de nível e temperatura. Os resultados são comparados com métodos da literatura e demonstram que o método proposto foi eficaz na estimação do tempo morto para a maioria dos casos. / Among the limiting factors of control systems, the pure time delay is one of the most critical and difficult to estimate without an intrusive perturbation. The knowledge of its value is essential for model identification and control loop performance assessment. This work proposes a methodology to determine dead time using ordinary closed loop operating data. The main advantage over available techniques is the non-necessity of intrusive plant tests. The proposed approach is based on a signal processing for removing the effects of the unmeasured disturbances and the model-plant mismatches. The signal processing consists of the minimization of the oscillations of the smoothing open loop error as a function of the pure time delay. Several objective function formulations and smoothing procedures were studied in order to facilitate parameter estimation. The quality of the methodology is illustrated by simulations in a series of scenarios, which simulate linear processes of different characteristics under the effect of different disturbances. The methodology is also tested in case studies with real industrial process data. Results are compared to literature approaches and show the method was effective to estimate the pure time delay for most cases.