Effiziente und robuste, feature-basierte Wiedererkennung langer Zeitreihen in großen Datenbanken

Die Materialverfolgung gewinnt in der Metallindustrie immer mehr an Bedeutung:rnEs ist notwendig, dass ein Metallband im Fertigungsprozess ein festgelegtes Programm durchläuft - erst dann ist die Qualität des Endprodukts garantiert. Die bisherige Praxis besteht darin, jedem Metallband eine Nummer zuzuordnen, mit der dieses Band beschriftet wird. Bei einer tagelangen Lagerung der Bänder zwischen zwei Produktionsschritten erweist sich diese Methode als fehleranfällig: Die Beschriftungen können z.B. verloren gehen, verwechselt, falsch ausgelesen oder unleserlich werden. 2007 meldete die iba AG das Patent zur Identifikation der Metallbänder anhand ihres Dickenprofils an (Anhaus [3]) - damit kann die Identität des Metallbandes zweifelsfrei nachgewiesen werden, eine zuverlässige Materialverfolgung wurde möglich.Es stellte sich jedoch heraus, dass die messfehlerbehafteten Dickenprofile, die als lange Zeitreihen aufgefasst werden können, mit Hilfe von bisherigen Verfahren (z.B. L2-Abstandsminimierung oder Dynamic Time Warping) nicht erfolgreich verglichen werden können.Diese Arbeit stellt einen effizienten feature-basierten Algorithmus zum Vergleichrnzweier Zeitreihen vor. Er ist sowohl robust gegenüber Rauschen und Messausfällen als auch invariant gegenüber solchen Koordinatentransformationen der Zeitreihen wie Skalierung und Translation. Des Weiteren sind auch Vergleiche mit Teilzeitreihen möglich. Unser Framework zeichnet sich sowohl durch seine hohe Genauigkeit als auch durch seine hohe Geschwindigkeit aus: Mehr als 99.5% der Anfragen an unsere aus realen Profilen bestehende Testdatenbank werden richtig beantwortet. Mit mehreren hundert Zeitreihen-Vergleichen pro Sekunde ist es etwa um den Faktor 10 schneller als die auf dem Gebiet der Zeitreihenanalyse etablierten Verfahren, die jedoch nicht im Stande sind, mehr als 90% der Anfragen korrekt zu verarbeiten. Der Algorithmus hat sich als industrietauglich erwiesen. Die iba AG setzt ihn in einem weltweit einzigartigen dickenprofilbasierten Überwachungssystemrnzur Materialverfolgung ein, das in ersten Stahl- und Aluminiumwalzwerkenrnbereits erfolgreich zum Einsatz kommt.

[Osteoporosis - whom to treat? The importance of FRAX® in Switzerland]

The WHO fracture risk assessment tool FRAX® is a computer based algorithm that provides models for the assessment of fracture probability in men and women. The approach uses easily obtained clinical risk factors (CRFs) to estimate 10-year probability of a major osteoporotic fracture (hip, clinical spine, humerus or wrist fracture) and the 10-year probability of a hip fracture. The estimate can be used alone or with femoral neck bone mineral density (BMD) to enhance fracture risk prediction. FRAX® is the only risk engine which takes into account the hazard of death as well as that of fracture. Probability of fracture is calculated in men and women from age, body mass index, and dichotomized variables that comprise a prior fragility fracture, parental history of hip fracture, current tobacco smoking, ever long-term use of oral glucocorticoids, rheumatoid arthritis, other causes of secondary osteoporosis, daily alcohol consumption of 3 or more units daily. The relationship between risk factors and fracture probability was constructed using information of nine population-based cohorts from around the world. CRFs for fracture had been identified that provided independent information on fracture risk based on a series of meta-analyses. The FRAX® algorithm was validated in 11 independent cohorts with in excess of 1 million patient-years, including the Swiss SEMOF cohort. Since fracture risk varies markedly in different regions of the world, FRAX® models need to be calibrated to those countries where the epidemiology of fracture and death is known. Models are currently available for 31 countries across the world. The Swiss-specific FRAX® model was developed very soon after the first release of FRAX® in 2008 and was published in 2009, using Swiss epidemiological data, integrating fracture risk and death hazard of our country. Two FRAX®-based approaches may be used to explore intervention thresholds. They have recently been investigated in the Swiss setting. In the first approach the guideline that individuals with a fracture probability equal to or exceeding that of women with a prior fragility fracture should be considered for treatment is translated into thresholds using 10-year fracture probabilities. In that case the threshold is age-dependent and increases from 16 % at the age of 60 ys to 40 % at the age of 80 ys. The second approach is a cost-effectiveness approach. Using a FRAX®-based intervention threshold of 15 % for both, women and men 50 years and older, should permit cost-effective access to therapy to patients at high fracture probability in our country and thereby contribute to further reduce the growing burden of osteoporotic fractures.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.

Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

EPA-1380 – Coordinated body-movement reflects psychotherapy outcome

Social interaction is a core aspect of human life that affects individuals’ physical and mental health. Social interaction usually leads to mutual engagement in diverse areas of mental, emotional, physiological and physical activity involving both interacting persons and subsequently impacting the outcome of interactions. A common approach to the analysis of social interaction is the study of the verbal content transmitted between sender and receiver. However, additional important processes and dynamics are occurring in other domains too, for example in the area of nonverbal behaviour: In a series of studies, we have looked at nonverbal synchrony – the coordination of two persons’ movement patterns – and it‘s association with relationship quality and with the outcome of interactions. Using a computer-based algorithm (Motion Energy Analysis, MEA: Ramseyer & Tschacher, 2011), which automatically quantifies a person‘s body-movement, we were able to objectively calculate nonverbal synchrony in a large number of dyads interacting in various settings. In a first step, we showed that the phenomenon of nonverbal synchrony exists at a level that is significantly higher than expected by chance. In a second step, we ascertained that across different settings – including patient-therapist dyads and healthy dyads – more synchronized movement was associated with better relationship quality and better interactional outcomes. The quality of a relationship is thus embodied by the synchronized movement patterns emerging between partners. Our studies suggest that embodied cognition is a valuable approach to research in social interaction, providing important clues for an improved understanding of interaction dynamics.

Differentiation of Diabetic Macular Edema From Pseudophakic Cystoid Macular Edema by Spectral-Domain Optical Coherence Tomography.

PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.

Lifetime maximization for beamforming applications in wireless sensor networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Codificador de voz MIDI

El presente proyecto tiene el objetivo de facilitar la composición de canciones mediante la creación de las distintas pistas MIDI que la forman. Se implementan dos controladores. El primero, con objeto de transcribir la parte melódica, convierte la voz cantada o tarareada a eventos MIDI. Para ello, y tras el estudio de las distintas técnicas del cálculo del tono (pitch), se implementará una técnica con ciertas variaciones basada en la autocorrelación. También se profundiza en el segmentado de eventos, en particular, una técnica basada en el análisis de la derivada de la envolvente. El segundo, dedicado a la base rítmica de la canción, permite la creación de la percusión mediante el golpe rítmico de objetos que disponga el usuario, que serán asignados a los distintos elementos de percusión elegidos. Los resultados de la grabación de estos impactos serán señales de corta duración, no lineales y no armónicas, dificultando su discriminación. La herramienta elegida para la clasificación de los distintos patrones serán las redes neuronales artificiales (RNA). Se realizara un estudio de la metodología de diseño de redes neuronales especifico para este tipo de señales, evaluando la importancia de las variables de diseño como son el número de capas ocultas y neuronas en cada una de ellas, algoritmo de entrenamiento y funciones de activación. El estudio concluirá con la implementación de dos redes de diferente naturaleza. Una red de Elman, cuyas propiedades de memoria permiten la clasificación de patrones temporales, procesará las cualidades temporales analizando el ataque de su forma de onda. Una red de propagación hacia adelante feed-forward, que necesitará de robustas características espectrales y temporales para su clasificación. Se proponen 26 descriptores como los derivados de los momentos del espectro: centroide, curtosis y simetría, los coeficientes cepstrales de la escala de Mel (MFCCs), y algunos temporales como son la tasa de cruces por cero y el centroide de la envolvente temporal. Las capacidades de discriminación inter e intra clase de estas características serán evaluadas mediante un algoritmo de selección, habiéndose elegido RELIEF, un método basado en el algoritmo de los k vecinos mas próximos (KNN). Ambos controladores tendrán función de trabajar en tiempo real y offline, permitiendo tanto la composición de canciones, como su utilización como un instrumento más junto con mas músicos. ABSTRACT. The aim of this project is to make song composition easier by creating each MIDI track that builds it. Two controllers are implemented. In order to transcribe the melody, the first controler converts singing voice or humming into MIDI files. To do this a technique based on autocorrelation is implemented after having studied different pitch detection methods. Event segmentation has also been dealt with, to be more precise a technique based on the analysis of the signal's envelope and it's derivative have been used. The second one, can be used to make the song's rhythm . It allows the user, to create percussive patterns by hitting different objects of his environment. These recordings results in short duration, non-linear and non-harmonic signals. Which makes the classification process more complicated in the traditional way. The tools to used are the artificial neural networks (ANN). We will study the neural network design to deal with this kind of signals. The goal is to get a design methodology, paying attention to the variables involved, as the number of hidden layers and neurons in each, transfer functions and training algorithm. The study will end implementing two neural networks with different nature. Elman network, which has memory properties, is capable to recognize sequences of data and analyse the impact's waveform, precisely, the attack portion. A feed-forward network, needs strong spectral and temporal features extracted from the hit. Some descriptors are proposed as the derivates from the spectrum moment as centroid, kurtosis and skewness, the Mel-frequency cepstral coefficients, and some temporal features as the zero crossing rate (zcr) and the temporal envelope's centroid. Intra and inter class discrimination abilities of those descriptors will be weighted using the selection algorithm RELIEF, a Knn (K-nearest neighbor) based algorithm. Both MIDI controllers can be used to compose, or play with other musicians as it works on real-time and offline.

Diseño e implementación de un módulo para la anotación de imágenes médicas

Se comenzó el trabajo recabando información sobre los distintos enfoques que se le había dado a la anotación a lo largo del tiempo, desde anotación de imágenes a mano, pasando por anotación de imágenes utilizando características de bajo nivel, como color y textura, hasta la anotación automática. Tras entrar en materia, se procedió a estudiar artículos relativos a los diferentes algoritmos utilizados para la anotación automática de imágenes. Dado que la anotación automática es un campo bastante abierto, hay un gran numero de enfoques. Teniendo las características de las imágenes en particular en las que se iba a centrar el proyecto, se fueron descartando los poco idoneos, bien por un coste computacional elevado, o porque estaba centrado en un tipo diferente de imágenes, entre otras cosas. Finalmente, se encontró un algoritmo basado en formas (Active Shape Model) que se consideró que podría funcionar adecuadamente. Básicamente, los diferentes objetos de la imagen son identicados a partir de un contorno base generado a partir de imágenes de muestra, siendo modicado automáticamente para cubrir la zona deseada. Dado que las imágenes usadas son todas muy similares en composición, se cree que puede funcionar bien. Se partió de una implementación del algoritmo programada en MATLAB. Para empezar, se obtuvieron una serie de radiografías del tórax ya anotadas. Las imágenes contenían datos de contorno para ambos pulmones, las dos clavículas y el corazón. El primer paso fue la creación de una serie de scripts en MATLAB que permitieran: - Leer y transformar las imágenes recibidas en RAW, para adaptarlas al tamaño y la posición de los contornos anotados - Leer los archivos de texto con los datos de los puntos del contorno y transformarlos en variables de MATLAB - Unir la imagen transformada con los puntos y guardarla en un formato que la implementación del algoritmo entendiera. Tras conseguir los ficheros necesarios, se procedió a crear un modelo para cada órgano utilizando para el entrenamiento una pequeña parte de las imágenes. El modelo obtenido se probó con varias imágenes de las restantes. Sin embargo, se encontro bastante variación dependiendo de la imagen utilizada y el órgano detectado. ---ABSTRACT---The project was started by procuring information about the diferent approaches to image annotation over time, from manual image anotation to automatic annotation. The next step was to study several articles about the diferent algorithms used for automatic image annotation. Given that automatic annotation is an open field, there is a great number of approaches. Taking into account the features of the images that would be used, the less suitable algorithms were rejected. Eventually, a shape-based algorithm (Active Shape Model) was found. Basically, the diferent objects in the image are identified from a base contour, which is generated from training images. Then this contour is automatically modified to cover the desired area. Given that all the images that would be used are similar in object placement, the algorithm would probably work nicely. The work started from a MATLAB implementation of the algorithm. To begin with, a set of chest radiographs already annotated were obtained. These images came with contour data for both lungs, both clavicles and the heart. The first step was the creation of a series of MATLAB scripts to join the RAW images with the annotation data and transform them into a format that the algorithm could read. After obtaining the necessary files, a model for each organ was created using part of the images for training. The trained model was tested on several of the reimaining images. However, there was much variation in the results from one image to another. Generally, lungs were detected pretty accurately, whereas clavicles and the heart gave more problems. To improve the method, a new model was trained using half of the available images. With this model, a significant inprovement of the results can be seen.

DAEDALUS at RepLab 2014: Detecting RepTrak reputation dimensions on tweets

This paper describes our participation at the RepLab 2014 reputation dimensions scenario. Our idea was to evaluate the best combination strategy of a machine learning classifier with a rule-based algorithm based on logical expressions of terms. Results show that our baseline experiment using just Naive Bayes Multinomial with a term vector model representation of the tweet text is ranked second among runs from all participants in terms of accuracy.

Contribución a la caracterización espacial de canales con sistemas MIMO-OFDM en la banda de 2,45 Ghz

La tecnología de múltiples antenas ha evolucionado para dar soporte a los actuales y futuros sistemas de comunicaciones inalámbricas en su afán por proporcionar la calidad de señal y las altas tasas de transmisión que demandan los nuevos servicios de voz, datos y multimedia. Sin embargo, es fundamental comprender las características espaciales del canal radio, ya que son las características del propio canal lo que limita en gran medida las prestaciones de los sistemas de comunicación actuales. Por ello surge la necesidad de estudiar la estructura espacial del canal de propagación para poder diseñar, evaluar e implementar de forma más eficiente tecnologías multiantena en los actuales y futuros sistemas de comunicación inalámbrica. Las tecnologías multiantena denominadas antenas inteligentes y MIMO han generado un gran interés en el área de comunicaciones inalámbricas, por ejemplo los sistemas de telefonía celular o más recientemente en las redes WLAN (Wireless Local Area Network), principalmente por la mejora que proporcionan en la calidad de las señales y en la tasa de transmisión de datos, respectivamente. Las ventajas de estas tecnologías se fundamentan en el uso de la dimensión espacial para obtener ganancia por diversidad espacial, como ya sucediera con las tecnologías FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access) y CDMA (Code Division Multiplexing Access) para obtener diversidad en las dimensiones de frecuencia, tiempo y código, respectivamente. Esta Tesis se centra en estudiar las características espaciales del canal con sistemas de múltiples antenas mediante la estimación de los perfiles de ángulos de llegada (DoA, Direction-of- Arrival) considerando esquemas de diversidad en espacio, polarización y frecuencia. Como primer paso se realiza una revisión de los sistemas con antenas inteligentes y los sistemas MIMO, describiendo con detalle la base matemática que sustenta las prestaciones ofrecidas por estos sistemas. Posteriormente se aportan distintos estudios sobre la estimación de los perfiles de DoA de canales radio con sistemas multiantena evaluando distintos aspectos de antenas, algoritmos de estimación, esquemas de polarización, campo lejano y campo cercano de las fuentes. Así mismo, se presenta un prototipo de medida MIMO-OFDM-SPAA3D en la banda ISM (Industrial, Scientific and Medical) de 2,45 Ghz, el cual está preparado para caracterizar experimentalmente el rendimiento de los sistemas MIMO, y para caracterizar espacialmente canales de propagación, considerando los esquemas de diversidad espacial, por polarización y frecuencia. Los estudios aportados se describen a continuación. Los sistemas de antenas inteligentes dependen en gran medida de la posición de los usuarios. Estos sistemas están equipados con arrays de antenas, los cuales aportan la diversidad espacial necesaria para obtener una representación espacial fidedigna del canal radio a través de los perfiles de DoA (DoA, Direction-of-Arrival) y por tanto, la posición de las fuentes de señal. Sin embargo, los errores de fabricación de arrays así como ciertos parámetros de señal conlleva un efecto negativo en las prestaciones de estos sistemas. Por ello se plantea un modelo de señal parametrizado que permite estudiar la influencia que tienen estos factores sobre los errores de estimación de DoA, tanto en acimut como en elevación, utilizando los algoritmos de estimación de DOA más conocidos en la literatura. A partir de las curvas de error, se pueden obtener parámetros de diseño para sistemas de localización basados en arrays. En un segundo estudio se evalúan esquemas de diversidad por polarización con los sistemas multiantena para mejorar la estimación de los perfiles de DoA en canales que presentan pérdidas por despolarización. Para ello se desarrolla un modelo de señal en array con sensibilidad de polarización que toma en cuenta el campo electromagnético de ondas planas. Se realizan simulaciones MC del modelo para estudiar el efecto de la orientación de la polarización como el número de polarizaciones usadas en el transmisor como en el receptor sobre la precisión en la estimación de los perfiles de DoA observados en el receptor. Además, se presentan los perfiles DoA obtenidos en escenarios quasiestáticos de interior con un prototipo de medida MIMO 4x4 de banda estrecha en la banda de 2,45 GHz, los cuales muestran gran fidelidad con el escenario real. Para la obtención de los perfiles DoA se propone un método basado en arrays virtuales, validado con los datos de simulación y los datos experimentales. Con relación a la localización 3D de fuentes en campo cercano (zona de Fresnel), se presenta un tercer estudio para obtener con gran exactitud la estructura espacial del canal de propagación en entornos de interior controlados (en cámara anecóica) utilizando arrays virtuales. El estudio analiza la influencia del tamaño del array y el diagrama de radiación en la estimación de los parámetros de localización proponiendo, para ello, un modelo de señal basado en un vector de enfoque de onda esférico (SWSV). Al aumentar el número de antenas del array se consigue reducir el error RMS de estimación y mejorar sustancialmente la representación espacial del canal. La estimación de los parámetros de localización se lleva a cabo con un nuevo método de búsqueda multinivel adaptativo, propuesto con el fin de reducir drásticamente el tiempo de procesado que demandan otros algoritmos multivariable basados en subespacios, como el MUSIC, a costa de incrementar los requisitos de memoria. Las simulaciones del modelo arrojan resultados que son validados con resultados experimentales y comparados con el límite de Cramer Rao en términos del error cuadrático medio. La compensación del diagrama de radiación acerca sustancialmente la exactitud de estimación de la distancia al límite de Cramer Rao. Finalmente, es igual de importante la evaluación teórica como experimental de las prestaciones de los sistemas MIMO-OFDM. Por ello, se presenta el diseño e implementación de un prototipo de medida MIMO-OFDM-SPAA3D autocalibrado con sistema de posicionamiento de antena automático en la banda de 2,45 Ghz con capacidad para evaluar la capacidad de los sistemas MIMO. Además, tiene la capacidad de caracterizar espacialmente canales MIMO, incorporando para ello una etapa de autocalibración para medir la respuesta en frecuencia de los transmisores y receptores de RF, y así poder caracterizar la respuesta de fase del canal con mayor precisión. Este sistema incorpora un posicionador de antena automático 3D (SPAA3D) basado en un scanner con 3 brazos mecánicos sobre los que se desplaza un posicionador de antena de forma independiente, controlado desde un PC. Este posicionador permite obtener una gran cantidad de mediciones del canal en regiones locales, lo cual favorece la caracterización estadística de los parámetros del sistema MIMO. Con este prototipo se realizan varias campañas de medida para evaluar el canal MIMO en términos de capacidad comparando 2 esquemas de polarización y tomando en cuenta la diversidad en frecuencia aportada por la modulación OFDM en distintos escenarios. ABSTRACT Multiple-antennas technologies have been evolved to be the support of the actual and future wireless communication systems in its way to provide the high quality and high data rates required by new data, voice and data services. However, it is important to understand the behavior of the spatial characteristics of the radio channel, since the channel by itself limits the performance of the actual wireless communications systems. This drawback raises the need to understand the spatial structure of the propagation channel in order to design, assess, and develop more efficient multiantenna technologies for the actual and future wireless communications systems. Multiantenna technologies such as ‘Smart Antennas’ and MIMO systems have generated great interest in the field of wireless communications, i.e. cellular communications systems and more recently WLAN (Wireless Local Area Networks), mainly because the higher quality and the high data rate they are able to provide. Their technological benefits are based on the exploitation of the spatial diversity provided by the use of multiple antennas as happened in the past with some multiaccess technologies such as FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access), and CDMA (Code Division Multiplexing Access), which give diversity in the domains of frequency, time and code, respectively. This Thesis is mainly focus to study the spatial channel characteristics using schemes of multiple antennas considering several diversity schemes such as space, polarization, and frequency. The spatial characteristics will be study in terms of the direction-of-arrival profiles viewed at the receiver side of the radio link. The first step is to do a review of the smart antennas and MIMO systems technologies highlighting their advantages and drawbacks from a mathematical point of view. In the second step, a set of studies concerning the spatial characterization of the radio channel through the DoA profiles are addressed. The performance of several DoA estimation methods is assessed considering several aspects regarding antenna array structure, polarization diversity, and far-field and near-field conditions. Most of the results of these studies come from simulations of data models and measurements with real multiantena prototypes. In the same way, having understand the importance of validate the theoretical data models with experimental results, a 2,4 GHz MIMO-OFDM-SPAA2D prototype is presented. This prototype is intended for evaluating MIMO-OFDM capacity in indoor and outdoor scenarios, characterize the spatial structure of radio channels, assess several diversity schemes such as polarization, space, and frequency diversity, among others aspects. The studies reported are briefly described below. As is stated in Chapter two, the determination of user position is a fundamental task to be resolved for the smart antenna systems. As these systems are equipped with antenna arrays, they can provide the enough spatial diversity to accurately draw the spatial characterization of the radio channel through the DoA profiles, and therefore the source location. However, certain real implementation factors related to antenna errors, signals, and receivers will certainly reduce the performance of such direction finding systems. In that sense, a parameterized narrowband signal model is proposed to evaluate the influence of these factors in the location parameter estimation through extensive MC simulations. The results obtained from several DoA algorithms may be useful to extract some parameter design for directing finding systems based on arrays. The second study goes through the importance that polarization schemes can have for estimating far-field DoA profiles in radio channels, particularly for scenarios that may introduce polarization losses. For this purpose, a narrowband signal model with polarization sensibility is developed to conduct an analysis of several polarization schemes at transmitter (TX) and receiver (RX) through extensive MC simulations. In addition, spatial characterization of quasistatic indoor scenarios is also carried out using a 2.45 GHz MIMO prototype equipped with single and dual-polarized antennas. A good agreement between the measured DoA profiles with the propagation scenario is achieved. The theoretical and experimental evaluation of polarization schemes is performed using virtual arrays. In that case, a DoA estimation method is proposed based on adding an phase reference to properly track the DoA, which shows good results. In the third study, the special case of near-field source localization with virtual arrays is addressed. Most of DoA estimation algorithms are focused in far-field source localization where the radiated wavefronts are assume to be planar waves at the receive array. However, when source are located close to the array, the assumption of plane waves is no longer valid as the wavefronts exhibit a spherical behavior along the array. Thus, a faster and effective method of azimuth, elevation angles-of-arrival, and range estimation for near-field sources is proposed. The efficacy of the proposed method is evaluated with simulation and validated with measurements collected from a measurement campaign carried out in a controlled propagation environment, i.e. anechoic chamber. Moreover, the performance of the method is assessed in terms of the RMSE for several array sizes, several source positions, and taking into account the effect of radiation pattern. In general, better results are obtained with larger array and larger source distances. The effect of the antennas is included in the data model leading to more accurate results, particularly for range rather than for angle estimation. Moreover, a new multivariable searching method based on the MUSIC algorithm, called MUSA (multilevel MUSIC-based algorithm), is presented. This method is proposed to estimate the 3D location parameters in a faster way than other multivariable algorithms, such as MUSIC algorithm, at the cost of increasing the memory size. Finally, in the last chapter, a MIMO-OFDM-SPAA3D prototype is presented to experimentally evaluate different MIMO schemes regarding antennas, polarization, and frequency in different indoor and outdoor scenarios. The prototype has been developed on a Software-Defined Radio (SDR) platform. It allows taking measurements where future wireless systems will be developed. The novelty of this prototype is concerning the following 2 subsystems. The first one is the tridimensional (3D) antenna positioning system (SPAA3D) based on three linear scanners which is developed for making automatic testing possible reducing errors of the antenna array positioning. A set of software has been developed for research works such as MIMO channel characterization, MIMO capacity, OFDM synchronization, and so on. The second subsystem is the RF autocalibration module at the TX and RX. This subsystem allows to properly tracking the spatial structure of indoor and outdoor channels in terms of DoA profiles. Some results are draw regarding performance of MIMO-OFDM systems with different polarization schemes and different propagation environments.

Advanced receivers for next generation wireless communication systems

Despite extensive progress on the theoretical aspects of spectral efficient communication systems, hardware impairments, such as phase noise, are the key bottlenecks in next generation wireless communication systems. The presence of non-ideal oscillators at the transceiver introduces time varying phase noise and degrades the performance of the communication system. Significant research literature focuses on joint synchronization and decoding based on joint posterior distribution, which incorporate both the channel and code graph. These joint synchronization and decoding approaches operate on well designed sum-product algorithms, which involves calculating probabilistic messages iteratively passed between the channel statistical information and decoding information. Channel statistical information, generally entails a high computational complexity because its probabilistic model may involve continuous random variables. The detailed knowledge about the channel statistics for these algorithms make them an inadequate choice for real world applications due to power and computational limitations. In this thesis, novel phase estimation strategies are proposed, in which soft decision-directed iterative receivers for a separate A Posteriori Probability (APP)-based synchronization and decoding are proposed. These algorithms do not require any a priori statistical characterization of the phase noise process. The proposed approach relies on a Maximum A Posteriori (MAP)-based algorithm to perform phase noise estimation and does not depend on the considered modulation/coding scheme as it only exploits the APPs of the transmitted symbols. Different variants of APP-based phase estimation are considered. The proposed algorithm has significantly lower computational complexity with respect to joint synchronization/decoding approaches at the cost of slight performance degradation. With the aim to improve the robustness of the iterative receiver, we derive a new system model for an oversampled (more than one sample per symbol interval) phase noise channel. We extend the separate APP-based synchronization and decoding algorithm to a multi-sample receiver, which exploits the received information from the channel by exchanging the information in an iterative fashion to achieve robust convergence. Two algorithms based on sliding block-wise processing with soft ISI cancellation and detection are proposed, based on the use of reliable information from the channel decoder. Dually polarized systems provide a cost-and spatial-effective solution to increase spectral efficiency and are competitive candidates for next generation wireless communication systems. A novel soft decision-directed iterative receiver, for separate APP-based synchronization and decoding, is proposed. This algorithm relies on an Minimum Mean Square Error (MMSE)-based cancellation of the cross polarization interference (XPI) followed by phase estimation on the polarization of interest. This iterative receiver structure is motivated from Master/Slave Phase Estimation (M/S-PE), where M-PE corresponds to the polarization of interest. The operational principle of a M/S-PE block is to improve the phase tracking performance of both polarization branches: more precisely, the M-PE block tracks the co-polar phase and the S-PE block reduces the residual phase error on the cross-polar branch. Two variants of MMSE-based phase estimation are considered; BW and PLP.