The subject of this work deals with the problem of channel estimation for CDMA systems. This method of multiple access when individual users share the same full bandwidth simultaneously and are differentiated with any of pseudorandom sequences, is now the most perspective method. That is proved by its wide implementation in mobile networks of the third generation and higher systems. This work describes basic theory principles of spread spectrum, above all DS-CDMA (Direct Sequence-CDMA) and furthermore some phenomena of radio wireless channel that affect changes in transmitted signal in its way from transmitter to receiver. Terms of fading, multipath propagation, loss, refraction, scattering of the wave and Rice and Rayleigh probability density functions are mentioned. The third chapter deals with yet known and used capabilities of channel estimation. Differences, advantages and disadvantages of so-called blind estimation or training-based estimation are discussed. Two algorithms: LS method and sliding correlator are analyzed in more detail. There is also description of their simulations in Matlab and some results of these simulations are discussed. The last chapter deals with comparison of main characteristics and achievable accuracy of wireless channel impulse response estimation by both methods, and their possible utilization in real live.

[pt] Os sistemas de múltiplas entradas e múltiplas saídas (MIMO) empregam um número crescente de antenas, o que leva a relevantes consumo de energia e custo de hardware dos front-ends correspondentes. Nesse contexto, o uso de conversores analógico-digitais (ADCs) de baixa resolução é promovido como uma solução promissora para este problema. Neste estudo consideramos um receptor MIMO de baixa resolução que implica que os sinais recebidos são processados simultaneamente pelos 1-bit ADCs e pela rede comparadora. Os sinais de entrada da rede comparadora podem vir de antenas diferentes, de modo que a extensão da rede comparadora pode ser interpretada como canais virtuais com saídas binárias. Com base nesses receptores MIMO de baixa resolução, desenvolvemos um estimador de canal e detector lineares de baixa resolução baseados no critério de mínimo erro médio quadrático (LRA-LMMSE) de acordo com o teorema de Bussgang. Duas redes de comparação são propostas, nomeadas, redes total e parcialmente conectadas. Também desenvolvemos uma rede parcialmente conectada baseada em busca gananciosa que usa muito menos comparadores para obter um desempenho bem próximo ao da rede totalmente conectada. Os resultados numéricos mostram que adicionar canais virtuais pode ser melhor do que adicionar canais físicos extras que correspondem a antenas de recepção adicionais em termos de taxa de erro de bit (BER). Além disso, ao empregar o estimador de canal proposto e seu erro de estimativa correspondente, construímos um limite inferior na taxa de soma ergódica para o receptor LRA-MMSE. Os resultados de simulação mostram que os sistemas com a proposta sistemas MIMO auxiliados por rede com quantização de 1-bit no receptor superam o convencional sistema MIMO de 1-bit em termos de desempenho de BER e erro quadrático médio (MSE). Além disso, as simulações numéricas confirmam uma vantagem significativa em termos de taxa de soma para o sistema proposto. / [en] Multiple-input multiple-output (MIMO) systems employs an increasing number of antennas, which leads to relevant energy consumption and hardware cost of the corresponding front ends. In this context, the use of lowresolution analog to digital converters (ADCs) is promoted as a promising solution to this problem. In this study we consider a low-resolution MIMO receiver which implies that the received signals simultaneously are processed by the 1-bit ADCs and the comparator network. The input signals for the comparator network can come from different antennas, such that the comparator network extension can be interpreted as virtual channels with binary outputs. Based on such low-resolution MIMO receivers, we develop low-resolution aware linear minimum mean-squared error (LRA-LMMSE) channel estimator and detector according to the Bussgang theorem. Two comparator networks are proposed, namely, fully and partially connected networks. We also devise a greedy search-based partially connected network that can use much less comparators to approach the performance of the fully connected network. Numerical results shows that adding virtual channels can be better than adding extra physical channels which corresponds to additional receive antennas in terms of bit error rate (BER). Furthermore, by employing the proposed channel estimator and its corresponding estimation error, we build up a lower bound on the ergodic sum rate for the LRA-LMMSE receiver. Simulation results show that the systems with the proposed network-aided MIMO systems with 1-bit quantization at the receiver outperforms the conventional 1-bit MIMO system in terms of BER and mean-square error (MSE) performances. Moreover, numerical simulations confirm a significant advantage in terms of sum rate for the proposed system.

[pt] Sistemas de múltiplas antenas de larga escala são técnicas fundamentais para sistemas de comunicação sem fio do futuro, que deverão servir dezenas de usuários por estação rádio-base. Neste contexto, um problema chave é o aumento do consumo de energia à medida que o número de antenas cresce. Recentemente, CADs de baixa resolução têm atraído grande interesse de pesquisa. Em particular, CADs de 1 bit são adequados para sistemas de larga escala devido ao seu baixo custo e consumo de energia. Nesta tese, CADs de 1 bit são usados em três diferentes abordagens de projeto, que operam a taxa de Nyquist e a taxas superiores a taxa de Nyquist com estratégias de amostragem uniforme e dinâmica. Nos sistemas operando a taxa de Nyquist, algoritmos de estimação de canal que exploram o conhecimento da baixa resolução e um novo esquema de detecção e decodificação iterativas são propostos, em que códigos low-density paritycheck de bloco curto são considerados para evitar alta latência. Nos sistemas operando a taxas superiores a taxa de Nyquist com sobreamostragem uniforme, algoritmos eficientes de estimação de canal e de detecção com janela deslizante com exploração da baixa resolução são propostos. Além disso, são deduzidas expressões analíticas associadas aos limitantes de Cramér-Rao para os sistemas com sobreamostragem. Resultados numéricos ilustram o desempenho dos algoritmos de estimação de canal propostos e existentes e os limitantes teóricos deduzidos. Nos sistemas operando com sobreamostragem dinâmica, duas abordagens de projeto são desenvolvidas: uma técnica baseada na maximização da soma das taxas e uma técnica baseada na minimização do erro médio quadrático. Em seguida, três algoritmos de redução de dimensão são apresentados e investigados. Resultados de simulações mostram que os sistemas com sobreamostragem dinâmica têm melhor desempenho do que os sistemas com sobreamostragem uniforme em termos de soma das taxas alcançáveis e de taxa de erro de símbolos, enquanto o custo computacional das técnicas examinadas é comparável. / [en] Large-scale multiple-antenna systems are a key technique for future wireless communications, which will serve tens of users per base station (BS). In this scenario, one problem faced is the large energy consumption as the number of receive antennas scales up. Recently, low-resolution analogto-digital converters (ADCs) have attracted much attention. Specifically, 1-bit ADCs in the front-end are suitable for such systems due to their low cost and low energy consumption. In this thesis, 1-bit ADCs are applied in three different system designs, which operate at the Nyquist rate and faster than Nyquist rates along with uniform and dynamic strategies. In the Nyquist-sampling system, low-resolution-aware channel estimation algorithms and a novel iterative detection and decoding scheme are proposed, where short block length low-density parity-check codes are considered for avoiding high latency. In the faster than Nyquist rates with uniform oversampling system, lowresolution-aware channel estimation and sliding window based detection algorithms are proposed due to their low computational cost and high detection accuracy. Particularly, analytical expressions associated with the Bayesian Cramér-Rao bounds for the oversampled systems are presented. Numerical results are provided to illustrate the performance of the proposed channel estimation algorithms and the derived theoretical bounds. In the dynamic-oversampling system, two different system designs are devised, namely, sum rate and mean square error based. Three different dimension reduction algorithms are presented and thoroughly investigated. Simulation results show that the systems with the proposed dynamic oversampling outperform the uniformly oversampled system in terms of the computational cost, achievable sum rate and symbol error rate performance.

A wide range of services and applications become possible when accurate position information for a radio terminal is available. These include: location-based services; navigation; safety and security applications. The commercial, industrial and military value of radio-location is such that considerable research effort has been directed towards developing related technologies, using satellite, cellular or local area network infrastructures or stand-alone equipment. This work studies and investigates two location techniques. The first one presents an implementation scheme for a wideband transmission and direction finding system using OFDM multi-carrier communications systems. This approach takes advantage of delay discrimination to improve angle-of-arrival estimation in a multipath channel with high levels of additive white Gaussian noise. A new methodology is interpreted over the multi carrier modulation scheme in which the simulation results of the estimated channel improves the performance of OFDM signal by mitigating the effect of frequency offset synchronization to give error-free data at the receiver, good angle of arrival accuracy and improved SNR performance. The full system simulation to explore optimum values such as channel estimation and AoA including the antenna array model and prove the operational performance of the OFDM system as implemented in MATLAB. The second technique proposes a low cost-effective method of tracking and monitoring objects (examples: patient, device, medicine, document) by employing passive radio frequency identification (RFID) systems. A multi-tag, (totalling fifty-six tags) with known ID values are attached to the whole patient’s body to achieve better tracking and monitoring precision and higher accuracy. Several tests with different positions and movements are implemented on six patients. The aim is to be able to track the patient if he/she is walking or sitting; therefore, the tests considered six possible movements for the patient including walking, standing, sitting, resting, laying on the floor and laying on the bed, these placements are important to monitor the status of the patient like if he collapsed and fall on the ground so that the help will be quick. The collected data from the RFID Reader in terms of Time Stamp, RSS, Tag ID, and a number of channels are processed using the MATLAB code.

<p dir="ltr">With the increasing availability of inexpensive computing power in wireless radio network nodes, machine learning based models are being deployed in operations that traditionally relied on rule-based or statistical methods. Contemporary high bandwidth networks enable easy availability of significant amounts of training data in a comparatively short time, aiding in the development of better deep learning models. Specialized deep learning models developed for wireless networks have been shown to consistently outperform traditional methods in a variety of wireless network applications.</p><p><br></p><p dir="ltr">We aim to address some of the unique challenges inherent in the wireless radio communication domain. Firstly, as data is transmitted over the air, data privacy and adversarial attacks pose heightened risks. Secondly, due to the volume of data and the time-sensitive nature of the processing that is required, the speed of the machine learning model becomes a significant factor, often necessitating operation within a latency constraint. Thirdly, the impact of diverse and time-varying wireless environments means that any machine learning model also needs to be generalizable. The increasing computing power present in wireless nodes provides an opportunity to offload some of the deep learning to the edge, which also impacts data privacy.</p><p><br></p><p dir="ltr">Towards this goal, we work on deep learning methods that operate along different aspects of a wireless network—on network packets, error prediction, modulation classification, and channel estimation—and are able to operate within the latency constraint, while simultaneously providing better privacy and security. After proposing solutions that work in a traditional centralized learning environment, we explore edge learning paradigms where the learning happens in distributed nodes.</p>

Tesis por compendio / Desde comienzos del siglo XXI, los sistemas de radiodifusión terrestre han sido culpados de un uso ineficiente del espectro asignado. Para aumentar la eficiencia espectral, los organismos de estandarización de TV digital comenzaron a desarrollar la evolución técnica de los sistemas de TDT de primera generación. Entre otros, uno de los objetivos principales de los sistemas de TDT de próxima generación (DVB-T2 y ATSC 3.0) es proporcionar simultáneamente servicios de TV a dispositivos móviles y fijos. El principal inconveniente de esta entrega simultánea son los diferentes requisitos de cada condición de recepción. Para abordar estas limitaciones, se han considerado diferentes técnicas de multiplexación. Mientras que DVB-T2 acomete la entrega simultánea de los dos servicios mediante TDM, ATSC 3.0 adoptó la Multiplexación por División en Capas (LDM). LDM puede superar a TDM y a FDM al aprovechar la relación de Protección de Error Desigual (UEP), ya que ambos servicios, llamados capas, utilizan todos los recursos de frecuencia y tiempo con diferentes niveles de potencia. En el lado del receptor, se distinguen dos implementaciones, de acuerdo con la capa a decodificar. Los receptores móviles solo están destinados a obtener la capa superior, conocida como Core Layer (CL). Para no aumentar su complejidad en comparación con los receptores de capa única, la capa inferior, conocida como Enhanced Layer (EL), es tratada como un ruido adicional en la decodificación. Los receptores fijos aumentan su complejidad, ya que deben realizar un proceso de Cancelación de Interferencia (SIC) sobre la CL para obtener la EL. Para limitar la complejidad adicional de los receptores fijos, las capas de LDM en ATSC 3.0 están configuradas con diferentes capacidades de corrección, pero comparten el resto de bloques de la capa física, incluido el TIL, el PP, el tamaño de FFT, y el GI. Esta disertación investiga tecnologías avanzadas para optimizar el rendimiento de LDM. Primero se propone una optimización del proceso de demapeo para las dos capas de LDM. El algoritmo propuesto logra un aumento de capacidad, al tener en cuenta la forma de la EL en el proceso de demapeo de la CL. Sin embargo, el número de distancias Euclidianas a computar puede aumentar significativamente, conduciendo no solo a receptores fijos más complejos, sino también a receptores móviles más complejos. A continuación, se determina la configuración de piloto ATSC 3.0 más adecuada para LDM. Teniendo en cuenta que las dos capas comparten el mismo PP, surge una contrapartida entre la densidad de pilotos (CL) y la redundancia sobre los datos (EL). A partir de los resultados de rendimiento, se recomienda el uso de un PP no muy denso, ya que ya han sido diseñados para hacer frente a ecos largos y altas velocidades. La amplitud piloto óptima depende del estimador de canal en los receptores (ej., se recomienda la amplitud mínima para una implementación Wiener, mientras que la máxima para una implementación FFT). También se investiga la potencial transmisión conjunta de LDM con tres tecnologías avanzadas adoptadas en ATSC 3.0: las tecnologías de agregación MultiRF, los esquemas de MISO distribuido y los de MIMO colocalizado. Se estudian los potenciales casos de uso, los aspectos de implementación del transmisor y el receptor, y las ganancias de rendimiento de las configuraciones conjuntas para las dos capas de LDM. Las restricciones adicionales de combinar LDM con las tecnologías avanzadas se consideran admisibles, ya que las mayores demandas ya están contempladas en ATSC 3.0 (ej., una segunda cadena de recepción). Se obtienen ganancias significativas en condiciones de recepción peatonal gracias a la diversidad en frecuencia proporcionada por las tecnologías MultiRF. La conjunción de LDM con esquemas de MISO proporciona ganancias de rendimiento significativas en redes SFN para la capa fija con el esquema de Alamouti. / Since the beginning of the 21st century, terrestrial broadcasting systems have been blamed of an inefficient use of the allocated spectrum. To increase the spectral efficiency, digital television Standards Developing Organizations settled to develop the technical evolution of the first-generation DTT systems. Among others, a primary goal of next-generation DTT systems (DVB-T2 and ATSC 3.0) is to simultaneously provide TV services to mobile and fixed devices. The major drawback of this simultaneous delivery is the different requirement of each reception condition. To address these constraints different multiplexing techniques have been considered. While DVB-T2 fulfilled the simultaneous delivery of the two services by TDM, ATSC 3.0 adopted the LDM technology. LDM can outperform TDM and FDM by taking advantage of the UEP ratio, as both services, namely layers, utilize all the frequency and time resources with different power levels. At receiver side, two implementations are distinguished, according to the intended layer. Mobile receivers are only intended to obtain the upper layer, known as CL. In order not to increase their complexity compared to single layer receivers, the lower layer, known as EL is treated as an additional noise on the CL decoding. Fixed receivers, increase their complexity, as they should performed a SIC process on the CL for getting the EL. To limit the additional complexity of fixed receivers, the LDM layers in ATSC 3.0 are configured with different error correction capabilities, but share the rest of physical layer parameters, including the TIL, the PP, the FFT size, and the GI. This dissertation investigates advanced technologies to optimize the LDM performance. A demapping optimization for the two LDM layers is first proposed. A capacity increase is achieved by the proposed algorithm, which takes into account the underlying layer shape in the demapping process. Nevertheless, the number of Euclidean distances to be computed can be significantly increased, contributing to not only more complex fixed receivers, but also more complex mobile receivers. Next, the most suitable ATSC 3.0 pilot configuration for LDM is determined. Considering the two layers share the same PP a trade-off between pilot density (CL) and data overhead (EL) arises. From the performance results, it is recommended the use of a not very dense PP, as they have been already designed to cope with long echoes and high speeds. The optimum pilot amplitude depends on the channel estimator at receivers (e.g. the minimum amplitude is recommended for a Wiener implementation, while the maximum for a FFT implementation). The potential combination of LDM with three advanced technologies that have been adopted in ATSC 3.0 is also investigated: MultiRF technologies, distributed MISO schemes, and co-located MIMO schemes. The potential use cases, the transmitter and receiver implementations, and the performance gains of the joint configurations are studied for the two LDM layers. The additional constraints of combining LDM with the advanced technologies is considered admissible, as the greatest demands (e.g. a second receiving chain) are already contemplated in ATSC 3.0. Significant gains are found for the mobile layer at pedestrian reception conditions thanks to the frequency diversity provided by MultiRF technologies. The conjunction of LDM with distributed MISO schemes provides significant performance gains on SFNs for the fixed layer with Alamouti scheme. Last, considering the complexity in the mobile receivers and the CL performance, the recommended joint configuration is MISO in the CL and MIMO in the EL. / Des de començaments del segle XXI, els sistemes de radiodifusió terrestre han sigut culpats d'un ús ineficient de l'espectre assignat. Per a augmentar l'eficiència espectral, els organismes d'estandardització de TV digital van començar a desenvolupar l'evolució tècnica dels sistemes de TDT de primera generació. Entre altres, un dels objectius principals dels sistemes de TDT de pròxima generació (DVB-T2 i el ATSC 3.0) és proporcionar simultàniament serveis de TV a dispositius mòbils i fixos. El principal inconvenient d'aquest lliurament simultani són els diferents requisits de cada condició de recepció. Per a abordar aquestes limitacions, s'han considerat diferents tècniques de multiplexació. Mentre que DVB-T2 escomet el lliurament simultani dels dos serveis mitjançant TDM, ATSC 3.0 va adoptar la Multiplexació per Divisió en Capes (LDM). LDM pot superar a TDM i a FDM en aprofitar la relació de Protecció d'Error Desigual (UEP), ja que tots dos serveis, cridats capes, utilitzen tots els recursos de freqüència i temps amb diferents nivells de potència. En el costat del receptor, es distingeixen dues implementacions, d'acord amb la capa a decodificar. Els receptors mòbils solament estan destinats a obtenir la capa superior, coneguda com Core Layer (CL). Per a no augmentar la seua complexitat en comparació amb els receptors de capa única, la capa inferior, coneguda com Enhanced Layer (EL), és tractada com un soroll addicional en la decodificació. Els receptors fixos augmenten la seua complexitat, ja que han de realitzar un procés de Cancel·lació d'Interferència (SIC) sobre la CL per a obtenir l'EL. Per a limitar la complexitat addicional dels receptors fixos, les capes de LDM en ATSC 3.0 estan configurades amb diferents capacitats de correcció, però comparteixen la resta de blocs de la capa física, inclòs el TIL, el PP, la grandària de FFT i el GI. Aquesta dissertació investiga tecnologies avançades per a optimitzar el rendiment de LDM. Primer es proposa una optimització del procés de demapeo per a les dues capes de LDM. L'algoritme proposat aconsegueix un augment de capacitat, en tenir en compte la forma de l'EL en el procés de demapeo de la CL. No obstant açò, el nombre de distàncies Euclidianes a computar pot augmentar significativament, conduint NO sols a receptors fixos més complexos, sinó també a receptors mòbils més complexos. A continuació, es determina la configuració de pilot ATSC 3.0 més adequada per a LDM. Tenint en compte que les dues capes comparteixen el mateix PP, es produeix una contrapartida entre la densitat de pilots (CL) i la redundància sobre les dades (EL). A partir dels resultats de rendiment, es recomana l'ús d'un PP no gaire dens, ja que ja han sigut dissenyats per a fer front a ecos llargs i altes velocitats. L'amplitud pilot òptima depèn de l'estimador de canal en els receptors (ex., es recomana l'amplitud mínima per a una implementació Wiener, mentre que la màxima per a una implementació FFT). També s'investiga la potencial transmissió conjunta de LDM amb tres tecnologies avançades adoptades en ATSC 3.0: les tecnologies d'agregació de MultiRF, els esquemes de MISO distribuït i els de MIMO colocalitzat. S'estudien els potencials casos d'ús, els principals aspectes d'implementació del transmissor i el receptor, i els guanys de rendiment de les configuracions conjuntes per a les dues capes de LDM. Les restriccions addicionals de combinar LDM amb les tecnologies avançades es consideren admissibles, ja que les majors demandes ja estan contemplades en ATSC 3.0 (ex., una segona cadena de recepció). S'obtenen guanys significatius per a la capa mòbil en condicions de recepció per als vianants gràcies a la diversitat en freqüència proporcionada per les tecnologies MultiRF. La conjunció de LDM amb esquemes MISO distribuïts proporciona guanys de rendiment significatius en xarxes SFN per a la capa fixa amb l'esquema d'Alamouti. / Garro Crevillén, E. (2018). Advanced Layered Divsion Multiplexing Technologies for Next-Gen Broadcast [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/105559 / Compendio

Approved for public release; distribution is unlimited / OFDM systems have experienced increased attention in recent years and have found applications in a number of diverse areas including telephone-line based ADSL links, digital audio and video broadcasting systems, and wireless local area networks (WLAN). Orthogonal frequency-division multiplexing (OFDM) is a powerful technique for high data-rate transmission over fading channels. However, to deploy OFDM in a WLAN environment, precise frequency synchronization must be maintained and tricky frequency offsets must be handled. In this thesis, various techniques to improve the data throughput of OFDM WLAN are investigated. A simulation tool was developed in Matlab to evaluate the performance of the IEEE 802.11a physical layer. We proposed a rapid time and frequency synchronization algorithm using only the short training sequence of the IEEE 802.11a standard, thus reducing the training overhead to 50%. Particular attention was paid to channel coding, block interleaving and antenna diversity. Computer simulation showed that drastic improvement in error rate performance is achievable when these techniques are deployed. / Lieutenant, Hellenic Navy

Les réseaux radio actuelles utilisent le spectre inefficacement, car une bande de fréquence est allouée de façon permanente à une technologie spécifique. Vu que le spectre est une ressource limitée, cette attribution statique ne pourra bientôt plus combler les besoins des systèmes de transmission qui ne cessent de croître. On peut toutefois optimiser l'utilisation du spectre en permettant des transmissions secondaires (SU) dans les espaces libres du primaire (PU). Cette vision constitue l'objectif principal de la radio cognitive. Nous proposons d'évaluer les stratégies de transmission pour la coexistence des systèmes primaires (PU) et SU dans les mêmes réseaux. Plus concrètement, nous nous focalisons sur un scénario spatial interweave en émettant les signaux SU dans les espaces vides du PU à l'aide d'un précodeur linéaire. Néanmoins, ce précodage nécessite une connaissance a priori des canaux interférents. L'échange d'informations entre le PU et le SU étant proscrit, nous exploitons l'hypothèse de la réciprocité du canal. Cette hypothèse compense l'absence de coopération, mais elle n'est pas si évidente à exploiter en pratique à cause des perturbations des circuits radio fréquence. Nous suggérons de compenser ces perturbations par des méthodes de calibration relative. Nous proposons ensuite une implémentation temps-réel des solutions sur une plateforme LTE. Pour finir, nous généralisons l'approche RC à un système de transmission multi-utilisateurs, à travers une combinaison des techniques RC et massive MIMO, cette approche constitue s’établit comme une solution à la progression exponentielle du trafic. / The accelerated evolution of wireless transmission in recent years has dramatically increased the spectrum overcrowding. Indeed, the spectrum is inefficiently used in the conventional networks, since a frequency band is statically allocated to a specific technology called primary (PU). Whereas the radio spectrum is limited, this static frequency allocation will no longer be able to meet the increasing needs of bandwidth. However, the spectrum can be optimally used in enabling secondary (SU) transmissions, provided the latters do not harm the PU. This opportunistic vision of wireless transmissions is the main aim of Cognitive Radio (CR). CR enables smart use of wireless resources and is a key ingredient to perform high spectral efficiency. We focus on a spatial interweave (SIW) CR scenario which exploits the spatial white spaces to enable SU transmissions. The latter forms spatial beams using precoders, so that there is no interference towards the primary. Nevertheless, this precoding requires acquisition of the crosslink channel. However, due to the lack of cooperation between PU and SU, we acquire the channel thanks to channel reciprocity. Furthermore, the practical use of the reciprocity is not as straightforward as in theory, because it is is jeopardized by the nonreciprocal radio frequency front-ends. These perturbations are compensated in our study by relative calibration algorithms. Subsequently, we propose an implementation of our solutions in a real-time LTE platform. Eventually, we extend the CR model to a MU system in suggesting a combination of SIW and massive MIMO techniques. This scheme is an interesting candidate to overcome the exponential traffic growth.

CoordenaÃÃo de AperfeiÃoamento de NÃvel Superior / Em diversas aplicaÃÃes do processamento de sinais em sistemas de comunicaÃÃo sem-fio, o sinal recebido à de natureza multidimensional, possuindo uma estrutura algÃbrica multilinear. Neste contexto, a decomposiÃÃo tensorial PARAFAC tem sido utilizada em vÃrios trabalhos ao longo dos Ãltimos seis anos. Observa-se, entretanto, que decomposiÃÃes tensoriais generalizadas sÃo necessÃrias para modelar uma classe mais ampla de sistemas de comunicaÃÃo, caracterizada pela presenÃa de estruturas de transmissÃo mais complexas, por modelos de canal mais realistas, e por tÃcnicas de processamento de sinais mais eficientes no receptor. Esta tese investiga novas abordagens tensorias e suas aplicaÃÃes em modelagem de sistemas MIMO, equalizaÃÃo, separaÃÃo de sinais e estimaÃÃo paramÃtrica de canal. Inicialmente, duas novas decomposiÃÃes tensoriais (PARAFAC em blocos com restriÃÃes e CONFAC) sÃo desenvolvidas e estudadas em termos de identificabilidade. Em uma segunda parte do trabalho, novas aplicaÃÃes destas decomposiÃÃes tensoriais sÃo propostas. A decomposiÃÃo PARAFAC em blocos com restriÃÃes à aplicada, primeiramente, Âa modelagem unificada de sistemassuperamostrados, DS-CDMA e OFDM, com aplicaÃÃo em equalizaÃÃo multiusuÃria. Em seguida, esta decomposiÃÃo à utilizada na modelagem de sistemas de transmissÃo MIMO com espalhamento espaÃo-temporal e detecÃÃo conjunta. Em seguida, a decomposiÃÃo CONFAC à explorada na concepÃÃo de uma nova arquitetura generalizada de transmissÃo MIMO/CDMA que combina diversidade e multiplexagem. As propriedades de unicidade desta decomposiÃÃo permitem o uso do processamento nÃo-supervisionado no receptor, visando a reconstruÃÃo dos sinais transmitidos e a estimaÃÃo do canal. Na terceira e Ãltima parte deste trabalho, explora-se a decomposiÃÃo PARAFAC no contexto de duas aplicaÃÃes diferentes. Na primeira, uma nova estrutura de transmissÃo espaÃo-temporal-freqÃencial à proposta para sistemas MIMO multiportadora. A segunda aplicaÃÃo consiste em um novo estimador paramÃtrico para canais multipercursos. / In several signal processing applications for wireless communications, the received signal is multidimensional in nature and may exhibit a multilinear algebraic structure. In this context, the PARAFAC tensor decomposition has been the subject of several works in the past six years. However, generalized tensor decompositions are necessary for covering a wider class of wireless communication systems with more complex transmission structures, more realistic channel models and more efficient receiver signal processing. This thesis investigates tensor modeling approaches for multiple-antenna systems, channel equalization, signal separation and parametric channel estimation. New tensor decompositions, namely, the block-constrained PARAFAC and CONFAC decompositions, are developed and studied in terms of identifiability. First, the block-constrained PARAFAC decomposition is applied for a uniÂed tensor modeling of oversampled, DS-CDMA and OFDM systems with application to blind multiuser equalization. This decomposition is also used for modeling multiple-antenna (MIMO) transmission systems with block space-time spreading and blind detection, which generalizes previous tensor-based MIMO transmission models. The CONFAC decomposition is then exploited for designing new MIMO-CDMA transmission schemes combining spatial diversity and multiplexing. Blind symbol/code/channel recovery is discussed from the uniqueness properties of this decomposition. This thesis also studies new applications of third-order PARAFAC decomposition. A new space-time-frequency spreading system is proposed for multicarrier multiple-access systems, where this decomposition is used as a joint spreading and multiplexing tool at the transmitter using tridimensional spreading code with trilinear structure. Finally, we present a PARAFAC modeling approach for the parametric estimation of SIMO and MIMO multipath wireless channels with time-varying structure.

Τα τελευταία χρόνια χαρακτηρίζονται από μια αλματώδη ανάπτυξη των προϊόντων και υπηρεσιών που βασίζονται στα δίκτυα ασύρματης επικοινωνίας, ενώ προκύπτουν σημαντικές ερευνητικές προκλήσεις. Τα συστήματα πολλαπλών κεραιών στον πομπό και στο δέκτη, γνωστά και ως συστήματα MIMO (multi-input multi-output), καθώς και η τεχνολογία πολλαπλής προσπέλασης με χρήση κωδικών (code division multiple access, CDMA) αποτελούν δύο από τα βασικά μέτωπα ανάπτυξης των ασύρματων τηλεπικοινωνιών. Στα πλαίσια της παρούσας διδακτορικής διατριβής, ασχοληθήκαμε με την ανάπτυξη και μελέτη αλγορίθμων επεξεργασίας σήματος για τα δύο παραπάνω συστήματα, όπως περιγράφεται αναλυτικά παρακάτω. Σχετικά με τα συστήματα MIMO, η πρωτοποριακή έρευνα που πραγματοποιήθηκε στα Bell Labs γύρω στα 1996, όπου αναπτύχθηκε η αρχιτεκτονική BLAST (Bell Labs Layered Space-Time), απέδειξε ότι η χρήση πολλαπλών κεραιών μπορεί να οδηγήσει σε σημαντική αύξηση της χωρητικότητας των ασύρματων συστημάτων. Προκειμένου να αξιοποιηθούν οι παραπάνω δυνατότητες, απαιτείται η σχεδίαση σύνθετων δεκτών MIMO. Προς αυτήν την κατεύθυνση, έχει προταθεί ένας μεγάλος αριθμός μεθόδων ισοστάθμισης του καναλιού. Ωστόσο, οι περισσότερες από αυτές υποθέτουν ότι το ασύρματο κανάλι είναι: 1) χρονικά σταθερό, 2) συχνοτικά επίπεδο (δεν εισάγει διασυμβολική παρεμβολή), και κυρίως 3) ότι είναι γνωστό στο δέκτη. Δεδομένου ότι σε ευρυζωνικά συστήματα μονής φέρουσας οι παραπάνω υποθέσεις είναι δύσκολο να ικανοποιηθούν, στραφήκαμε προς τις προσαρμοστικές μεθόδους ισοστάθμισης. Συγκεκριμένα, αναπτύξαμε τρεις βασικούς αλγορίθμους. Ο πρώτος αλγόριθμος αποτελεί έναν προσαρμοστικό ισοσταθμιστή ανάδρασης αποφάσεων (decision feedback equalizer, DFE) για συχνοτικά επίπεδα κανάλια ΜΙΜΟ. Ο προτεινόμενος MIMO DFE ακολουθεί την αρχιτεκτονική BLAST, και ανανεώνεται με βάση τον αλγόριθμο αναδρομικών ελαχίστων τετραγώνων (RLS) τετραγωνικής ρίζας. Ο ισοσταθμιστής μπορεί να παρακολουθήσει ένα χρονικά μεταβαλλόμενο κανάλι, και, από όσο γνωρίζουμε, έχει τη χαμηλότερη πολυπλοκότητα από όλους τους δέκτες BLAST που έχουν προταθεί έως σήμερα. Ο δεύτερος αλγόριθμος αποτελεί την επέκταση του προηγούμενου σε συχνοτικά επιλεκτικά κανάλια. Μέσω κατάλληλης μοντελοποίησης του προβλήματος ισοστάθμισης, οδηγηθήκαμε σε έναν αποδοτικό DFE για ευρυζωνικά κανάλια MIMO. Τότε, η διαδικασία της ισοστάθμισης εμφανίζει προβλήματα αριθμητικής ευστάθειας, που λόγω της υλοποίησης RLS τετραγωνικής ρίζας αντιμετωπίστηκαν επιτυχώς. Κινούμενοι προς την κατεύθυνση περαιτέρω μείωσης της πολυπλοκότητας, προτείναμε έναν προσαρμοστικό MIMO DFE που ανανεώνεται με βάση τον αλγόριθμο ελαχίστων μέσων τετραγώνων (LMS) υλοποιημένο εξ ολοκλήρου στο πεδίο της συχνότητας. Με χρήση του ταχύ μετασχηματισμού Fourier (FFT), μειώνεται η απαιτούμενη πολυπλοκότητα. Παράλληλα, η μετάβαση στο πεδίο των συχνοτήτων έχει ως αποτέλεσμα την προσεγγιστική διαγωνοποίηση του συστήματος, προσφέροντας ανεξάρτητη ανανέωση των φίλτρων ανά συχνοτική συνιστώσα και επιτάχυνση της σύγκλισης του αλγορίθμου. Ο προτεινόμενος ισοσταθμιστής πετυχαίνει μια καλή ανταλλαγή μεταξύ απόδοσης και πολυπλοκότητας. Παράλληλα με τα παραπάνω, ασχοληθήκαμε με την εκτίμηση του ασύρματου καναλιού σε ένα ασύγχρονο σύστημα CDMA. Το βασικό σενάριο είναι ότι ο σταθμός βάσης γνωρίζει ήδη τους ενεργούς χρήστες, και καλείται να εκτιμήσει τις παραμέτρους του καναλιού ανερχόμενης ζεύξης ενός νέου χρήστη που εισέρχεται στο σύστημα. Το πρόβλημα περιγράφεται από μια συνάρτηση ελαχίστων τετραγώνων, η οποία είναι γραμμική ως προς τα κέρδη του καναλιού, και μη γραμμική ως προς τις καθυστερήσεις του. Αποδείξαμε ότι το πρόβλημα έχει μια προσεγγιστικά διαχωρίσιμη μορφή, και προτείναμε μια επαναληπτική μέθοδο υπολογισμού των παραμέτρων. Ο προτεινόμενος αλγόριθμος δεν απαιτεί κάποια ειδική ακολουθία διάχυσης και λειτουργεί αποδοτικά ακόμη και για περιορισμένη ακολουθία εκπαίδευσης. Είναι εύρωστος στην παρεμβολή πολλαπλών χρηστών και περισσότερο ακριβής από μια υπάρχουσα μέθοδο εις βάρος μιας ασήμαντης αύξησης στην υπολογιστική πολυπλοκότητα. / Over the last decades, a dramatic progress in the products and services based on wireless communication networks has been observed, while, at the same time, new research challenges arise. The systems employing multiple antennas at the transmitter and the receiver, known as MIMO (multi-input multi-output) systems, as well as code division multiple access (CDMA) systems, are two of the main technologies employed for the evolution of wireless communications. During this PhD thesis, we worked on the design and analysis of signal processing algorithms for the two above systems, as it is described in detail next. Concerning the MIMO systems, the pioneering work performed at Bell Labs around 1996, where the BLAST (Bell Labs Layered Space-Time) architecture has been developed, proved that by using multiple antennas can lead to a significant increase in wireless systems capacity. To exploit this potential, sophisticated MIMO receivers should be designed. To this end, a large amount of channel equalizers has been proposed. However, most of these methods assume that the wireless channel is: 1) static, 2) frequency flat (no intersymbol interference is introduced), and mainly 3) it is perfectly known at the receiver. Provided that in high rate single carrier systems these assumptions are difficult to be met, we focused our attention on adaptive equalization methods. More specifically, three basic algorithms have been developed. The first algorithm is an adaptive decision feedback equalizer (DFE) for frequency flat MIMO channels. The proposed MIMO DFE implements the BLAST architecture, and it is updated by the recursive least squares (RLS) algorithm in its square root form. The new equalizer can track time varying channels, and, to the best of our knowledge, it has the lowest computational complexity among the BLAST receivers that have been proposed up to now. The second algorithm is an extension of the previous one to the frequency selective channel case. By proper modeling of the equalization problem, we arrived at an efficient DFE for wideband MIMO channels. In this case, the equalization process encounters numerical instability problems, which were successfully treated by the square root RLS implementation employed. To further reduce complexity, we proposed an adaptive MIMO DFE that is updated by the least mean square (LMS) algorithm, fully implemented in the frequency domain. By using the fast Fourier transform (FFT), the complexity required is considerably reduced. Moreover, the frequency domain implementation leads to an approximate decoupling of the equalization problem at each frequency bin. Thus, an independent update of the filters at each frequency bin allows for a faster convergence of the algorithm. The proposed equalizer offers a good performance - complexity tradeoff. Furthermore, we worked on channel estimation for an asynchronous CDMA system. The assumed scenario is that the base station has already acquired all the active users, while the uplink channel parameters of a new user entering the system should be estimated. The problem can be described via a least squares cost function, which is linear with respect to the channel gains, and non linear to its delays. We proved that the problem is approximately decoupled, and a new iterative parameter estimation method has been proposed. The suggested method does not require any specific pilot sequence and performs well even for a short training interval. It is robust to multiple access interference and more accurate compared to an existing method, at the expense of an insignificant increase in computational complexity.