An analog circuit for beamforming in a mobile Ku band satellite TV antenna array has been implemented. The circuit performs continuous-time gradient descent using simultaneous perturbation gradient estimation. Simulations were performed using Agilent ADS circuit simulator. Field tests were performed in a realistic scenario using a satellite signal. The results were comparable to the simulation predictions and to results obtained using a digital implementation of a similar stochastic approximation algorithm.

In this thesis, a Neural Network (NN) based beamforming algorithm is proposed for real time target tracking problem. The algorithm is performed for two applications, linear and cylindrical arrays. The linear array application is implemented with equispaced omnidirectional sources. The influence of the number of antenna elements and the angular seperation between the incoming signals on the performance of the beamformer in the linear array beamformer is studied, and it is observed that the algorithm improves its performance by increasing both two parameters in linear array beamformer. The cylindrical array application is implemented with twelve microstrip patch antenna (MPA) elements. The angular range of interest is divided into twelve sectors. Since three MPA elements are used to form the beam in each sector, the input size of the neural network (NN) is reduced in cylindrical array. According to the reduced size of NN, the training time of the beamformer is decreased. The reduced size of the NN has no degradation in forming the beams to the desired directions. The angular separation between the targets is an important parameter in cylindrical array beamformer.

In this thesis, we investigate the use of adaptive antenna algorithms for OFDM systems to suppress interference in various channel conditions including narrowband and wideband interference, flat and frequency selective fading. We propose a novel frequency-domain beamformer, based on the linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm for OFDM systems to improve the performance of interference suppression in AWGN channel with narrowband interference, Rayleigh fast fading channel with phase distortion, and the multipath environment. To verify the merits of the frequency-domain beamformer, the effect due to narrowband interference and random phase distortion are investigated. Moreover, to improve the performance of adaptive beamforming algorithm, the frequency-domain linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm is proposed. Computer simulation results show that the proposed frequency-domain LCMCM-HLMS beamformer has good capability of interference supression in various environment, and can mitigate the phase distortion of channel. However, in the time-domain beamformer based on LMS [33], RLS ,LC-LMS and LC-FLS algorithm for OFDM systems, the performance may severely degraded under some situations. We will show that in terms of output SINR, beampatern, received signal constellation and mean square error (MSE), for narrowband interference suppression in AWGN channel, phase distortion in Rayleigh fast fading channel and the multipath environment.

There is growing interest in developing reliable, high performance, underwater acoustic networks (UWANs). However, the acoustic communication channel, with its slow sound propagation, high signal attenuation, and low bandwidth, presents significant challenges to network designers. One advantage offered by the acoustic channel is the ability to form directional communication beams, which improve signal strength and reduce interference. The work presented here describes a novel medium access control protocol for UWANs designated Beam-Enabled Acoustic Link Establishment (BEALE). BEALE addresses the inherent challenges of the acoustic channel by incorporating two techniques: link-level scheduling and dynamic directional beam steering. BEALE neighbors exchange packets based on a link-level schedule negotiated between the two nodes. This scheduling allows nodes to steer transmit and receive beams in the appropriate direction at the appropriate time while minimizing control overhead. Using steered, directional beams increases the gain between sender and receiver, reduces the senders interference with other nodes, and, at the receiver, rejects possible interference from other nodes and noise sources common in the ocean, resulting in increased spatial reuse. The core protocol has been modeled in a UWAN simulator developed specifically for this research. The results demonstrate significant improvement in throughput and packet loss over two benchmark UWAN random access protocols when evaluated over a variety of spatial node topologies and traffic patterns. The core BEALE protocol is further enhanced herein by a Half-Duplex Sliding Window algorithm. The HDX Sliding window is shown through point-to-point simulation to markedly improve bandwidth utilization and error rate in large Bandwidth Delay Product (BDP) situations. Extension of the HDX Sliding Window to more complex multi-flow, two-way and multi-hop cases requires an additional level of communication coordination provided by the BEALE Sliding Window Scheduler presented here. The functional challenges and novel concept of the scheduler are described in detail. The BEALE protocol performance promotes a rich list of potential future research, such as rigorous characterization of the BEALE Sliding Window Scheduler, BEALE accommodation of mobile nodes, conceptual operability of a BEALE-enabled network of a central multi-beam sink node supporting large numbers of simple source nodes, and rate adaptation. / text

No description available.

Array processing involves manipulation of signals induced on various antenna elements. In an adaptive array system, the radiation pattern is formed according to the signal environment by using signal processing techniques. Adaptive arrays improve the capacity of mobile communication systems by placing nulls in the direction of interfering sources and by directing independent beams toward various users. Adaptive beamforming algorithms process signals induced on each array element that are assumed not to be affected by mutual coupling between the elements. The aim of this thesis is to investigate the effects of mutual coupling on the performance of various adaptive beamforming algorithms. The performance parameters such as signal to interference plus noise ratio and speed of convergence of the adaptive algorithms are studied and compared by both neglecting and considering the mutual coupling for the least mean squares, recursive least squares, conjugate gradient and constant modulus algorithms. Finally, it is concluded that the effect of mutual coupling is major in the performance of blind algorithms rather than non-blind algorithms. The results are obtained by simulations carried out on MATLAB.

ARAÚJO, D. C. Channel estimation techniques applied to massive MIMO systems using sparsity and statistics approaches. 2016. 124 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2016. / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-06-21T13:52:26Z No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Approved for entry into archive by Marlene Sousa (mmarlene@ufc.br) on 2017-06-21T16:17:55Z (GMT) No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Made available in DSpace on 2017-06-21T16:17:55Z (GMT). No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) Previous issue date: 2016-09-29 / Massive MIMO has the potential of greatly increasing the system spectral efficiency by employing many individually steerable antenna elements at the base station (BS). This potential can only be achieved if the BS has sufficient channel state information (CSI) knowledge. The way of acquiring it depends on the duplexing mode employed by the communication system. Currently, frequency division duplexing (FDD) is the most used in the wireless communication system. However, the amount of overhead necessary to estimate the channel scales with the number of antennas which poses a big challenge in implementing massive MIMO systems with FDD protocol. To enable both operating together, this thesis tackles the channel estimation problem by proposing methods that exploit a compressed version of the massive MIMO channel. There are mainly two approaches used to achieve such a compression: sparsity and second order statistics. To derive sparsity-based techniques, this thesis uses a compressive sensing (CS) framework to extract a sparse-representation of the channel. This is investigated initially in a flat channel and afterwards in a frequency-selective one. In the former, we show that the Cramer-Rao lower bound (CRLB) for the problem is a function of pilot sequences that lead to a Grassmannian matrix. In the frequency-selective case, a novel estimator which combines CS and tensor analysis is derived. This new method uses the measurements obtained of the pilot subcarriers to estimate a sparse tensor channel representation. Assuming a Tucker3 model, the proposed solution maps the estimated sparse tensor to a full one which describes the spatial-frequency channel response. Furthermore, this thesis investigates the problem of updating the sparse basis that arises when the user is moving. In this study, an algorithm is proposed to track the arrival and departure directions using very few pilots. Besides the sparsity-based techniques, this thesis investigates the channel estimation performance using a statistical approach. In such a case, a new hybrid beamforming (HB) architecture is proposed to spatially multiplex the pilot sequences and to reduce the overhead. More specifically, the new solution creates a set of beams that is jointly calculated with the channel estimator and the pilot power allocation using the minimum mean square error (MMSE) criterion. We show that this provides enhanced performance for the estimation process in low signal-noise ratio (SNR) scenarios. / Pesquisas em sistemas MIMO massivo (do inglês multiple-input multiple-output) ganha- ram muita atenção da comunidade científica devido ao seu potencial em aumentar a eficiência espectral do sistema comunicações sem-fio utilizando centenas de elementos de antenas na estação de base (EB). Porém, tal potencial só poderá é obtido se a EB possuir suficiente informação do estado de canal. A maneira de adquiri-lo depende de como os recursos de comunicação tempo-frequência são empregados. Atualmente, a solução mais utilizada em sistemas de comunicação sem fio é a multiplexação por divisão na frequência (FDD) dos pilotos. Porém, o grande desafio em implementar esse tipo solução é porque a quantidade de tons pilotos exigidos para estimar o canal aumenta com o número de antenas. Isso resulta na perda do eficiência espectral prometido pelo sistema massivo. Esta tese apresenta métodos de estimação de canal que demandam uma quantidade de tons pilotos reduzida, mas mantendo alta precisão na estimação do canal. Esta redução de tons pilotos é obtida porque os estimadores propostos exploram a estrutura do canal para obter uma redução das dimensões do canal. Nesta tese, existem essencialmente duas abordagens utilizadas para alcançar tal redução de dimensionalidade: uma é através da esparsidade e a outra através das estatísticas de segunda ordem. Para derivar as soluções que exploram a esparsidade do canal, o estimador de canal é obtido usando a teoria de “compressive sensing” (CS) para extrair a representação esparsa do canal. A teoria é aplicada inicialmente ao problem de estimação de canais seletivos e não-seletivos em frequência. No primeiro caso, é mostrado que limitante de Cramer-Rao (CRLB) é definido como uma função das sequências pilotos que geram uma matriz Grassmaniana. No segundo caso, CS e a análise tensorial são combinado para derivar um novo algoritmo de estimatição baseado em decomposição tensorial esparsa para canais com seletividade em frequência. Usando o modelo Tucker3, a solução proposta mapeia o tensor esparso para um tensor cheio o qual descreve a resposta do canal no espaço e na frequência. Além disso, a tese investiga a otimização da base de representação esparsa propondo um método para estimar e corrigir as variações dos ângulos de chegada e de partida, causados pela mobilidade do usuário. Além das técnicas baseadas em esparsidade, esta tese investida aquelas que usam o conhecimento estatístico do canal. Neste caso, uma nova arquitetura de beamforming híbrido é proposta para realizar multiplexação das sequências pilotos. A nova solução consite em criar um conjunto de feixes, que são calculados conjuntamente com o estimator de canal e alocação de potência para os pilotos, usand o critério de minimização erro quadrático médio. É mostrado que esta solução reduz a sequencia pilot e mostra bom desempenho e cenários de baixa relação sinal ruído (SNR).

abstract: Three dimensional (3-D) ultrasound is safe, inexpensive, and has been shown to drastically improve system ease-of-use, diagnostic efficiency, and patient throughput. However, its high computational complexity and resulting high power consumption has precluded its use in hand-held applications. In this dissertation, algorithm-architecture co-design techniques that aim to make hand-held 3-D ultrasound a reality are presented. First, image enhancement methods to improve signal-to-noise ratio (SNR) are proposed. These include virtual source firing techniques and a low overhead digital front-end architecture using orthogonal chirps and orthogonal Golay codes. Second, algorithm-architecture co-design techniques to reduce the power consumption of 3-D SAU imaging systems is presented. These include (i) a subaperture multiplexing strategy and the corresponding apodization method to alleviate the signal bandwidth bottleneck, and (ii) a highly efficient iterative delay calculation method to eliminate complex operations such as multiplications, divisions and square-root in delay calculation during beamforming. These techniques were used to define Sonic Millip3De, a 3-D die stacked architecture for digital beamforming in SAU systems. Sonic Millip3De produces 3-D high resolution images at 2 frames per second with system power consumption of 15W in 45nm technology. Third, a new beamforming method based on separable delay decomposition is proposed to reduce the computational complexity of the beamforming unit in an SAU system. The method is based on minimizing the root-mean-square error (RMSE) due to delay decomposition. It reduces the beamforming complexity of a SAU system by 19x while providing high image fidelity that is comparable to non-separable beamforming. The resulting modified Sonic Millip3De architecture supports a frame rate of 32 volumes per second while maintaining power consumption of 15W in 45nm technology. Next a 3-D plane-wave imaging system that utilizes both separable beamforming and coherent compounding is presented. The resulting system has computational complexity comparable to that of a non-separable non-compounding baseline system while significantly improving contrast-to-noise ratio and SNR. The modified Sonic Millip3De architecture is now capable of generating high resolution images at 1000 volumes per second with 9-fire-angle compounding. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

La sismique pétrolière est un domaine d'innovation continue depuis plus d'un siècle. Une part non négligeable des études concerne la séparation des différentes ondes se propageant dans le milieu exploré, en particulier les ondes de surface. A petite profondeur, les ondes de surfaces servent à la tomographie. Bien les connaître et les modéliser permet d'imager la proche surface. Quand la prospection est tournée vers les grandes profondeurs – soit 95% de l'industrie géophysique - ces ondes masquent les ondes de volume qui contiennent les informations sur les couches profondes. Il est donc fondamental de pouvoir s'en affranchir et l'étape de séparation est des plus importantes. Les ondes de surface peuvent cependant être utilisées pour une meilleure connaissance de la proche surface, ce qui permet d'en déduire après coup des paramètres utilisables pour améliorer l'imagerie en profondeur. La recherche s'est renouvelée dans ce domaine du fait de l'impulsion récente donnée par l'imagerie sismique passive à partir du bruit sismique ambiant ou la mise en place de nouvelles géométries d'acquisition. En parallèle, l'étude des champs pétroliers existants pour une meilleure exploitation tend à se développer dans l'industrie. La maîtrise de l'imagerie 4D (3 dimensions d'espace + le temps, appliqués à la surveillance de réservoir) devient dès lors une activité clé pour la recherche dans laquelle les variations des paramètres du sous-sol sont estimées. Le travail de thèse réalisé est issu des constatations suivantes : - En dépit de travaux très riches, les ondes de surface représentent encore un sujet d'investigation important en exploration géophysique. - Les expérimentations à l'échelle du laboratoire restent relativement peu usitées en géophysiques, en particuliers pour des études impliquant un grand nombre de points de mesure. La première partie de la thèse a permis de valider un environnement de laboratoire adapté à l'étude des ondes de surfaces, en particulier la mise en évidence d'un mélange « ondes de surface – ondes de volume » analogue à celui rencontré lors d' acquisitions terrestres. Ceci a pu être réalisé grâce à des gels d'Agar-agar de forte densité et la mise en place d'une chaine d'acquisition automatisée impliquant des réseaux de sources et de récepteurs denses. Une deuxième partie a permis de séparer les ondes de surface et les ondes de volume à l'aide de traitement d'antennes. Après séparation des ondes, il devient possible de suivre leurs variations de temps d'arrivées en présence de modification du milieu en surface et/ou en profondeur comme dans le cas d'une surveillance de réservoir en sismique pétrolière (4D). Une étude 4D complète a donc été réalisée, permettant de suivre non seulement les variations de temps d'arrivées mais également d'amplitude et de directions de départ et d'arrivées des ondes. Une méthode pour compenser les variations de vitesses parasites de la proche surface à été développée. Cette étude a été complétée par une étude issue de données terrains. Les profils de vitesse rencontrés sur le terrain font état de vitesses relativement faibles en surface. La conséquence en est que les différentes ondes de volume issues de la profondeur arrivent avec des angles d'incidences faibles et voisins les uns des autres. Les méthodes classiques de séparation d'ondes étant souvent inefficaces à ces angles, un chapitre a été consacré à l'étude des algorithmes de haute résolution dans le cadre de l'exploration sismique. Enfin, en tirant partie de la haute densité spatiale de points d'acquisitions rendue possible par l'environnement mise en place, une étude comparée de deux dispositifs - l'un théoriquement idéal mais peu réaliste et l'autre économiquement viable sur le terrain mais moins efficace - a permis de s'attaquer au problème des ondes réfléchies sur des diffractants en surface qui perturbent beaucoup les acquisitions actuelles. Une nouvelle solution de filtrage a été proposée pour le deuxième cas. / Seismic exploration is a continuous innovation domain since more than one century. A significant part of the studies consists in separating the various waves propagating in the medium, especially surface waves. In the near-surface, surface waves are useful for tomography. Near-surface imaging becomes possible if they are well modelised. When exploration is dedicated to depth – meaning more than 95% of the seismic exploration business – the surface waves mainly hide body waves, which contains the informations related to the depth. Body and surface wave separation then becomes a fundamental task. In these situations, the surface waves can nevertheless be used to better know the near surface. It allows computing parameters usable to better the depth imaging. Research knew recent developments in this domain due to the recent impulsion given by the passive seismic imaging from ambient noise and the study of new acquisition designs with high spatial density. In parallel, the oil fields study for better exploitation is growing as a new industrial development axis. 4D (i.e. 3 spatial dilensions + time) imaging mastering becomes a key research activity, in which sub-surface parameters are estimated and monitored. This PhD thesis comes from the following remarks: - Despite rich works, surface waves are still an important research issue in seismic exploration. - Laboratory scale experiments know relatively few investigations, especially for high density acquisition design. The first step has been dedicated to the set up and the validation of a complete acquisition environment in the laboratory, adapted to surface wave study and high spatial density. Using Agar-agar phantoms, a mix of S body waves and Rayleigh surface waves comparable to the on-field P body waves and Rayleigh wave mix has been highlighted. Then, using array processing, wave separation has benne successfully demonstrated. After waves separation, it becomes possible to follow their arrival time variation in presence of surface and/or depth variation in the medium, as in reservoir monitoring conditions. A complete 4D study has been performed, allowing not only the arrival time monitoring but also amplitude and arrival and launch directions. A method has been proposed to compensate the near-surface spurious variations. An adaptation of the method on a field data set is then performed. Generally, velocity profiles on the field show weak velocities in the sub-surface. As a consequence, the various waves coming from the depth have weak and comparable incidences angles. Classical separation method using array processing are usually insufficient to work with such incidence angles set. For this reason, a complete part of this work has been dedicated to the study of high resolution algorithms in the frame of seismic exploration and their adaptation. At the end, taking advantage of the high spatial density allowed by the laboratory environment, a comparative study of two designs – the first one theoretically ideal but somewhat unrealistic and the second one more viable economically but less efficient – has been performed to address the scattered waves filtering issue. For the second design, a new filtering method has been proposed to enhance the scattered waves filtering.

Popularity of speech communication is rapidly increasing in various contexts such as conferencing systems, mobile/fixed electronic devices and laptops thus leading to a heightened demand for new services and improved speech quality. Dictaphones used for dictations usually have one microphone. Single microphone does not give enough degree of freedom to allow estimation of location of the source. Microphone array makes use of multiple microphones for spatial filtering suppressing the background noise. This report aims for speech enhancement utilizing the benefits inherited with microphone arrays to find direction of desired speaker and focus the listening beam in that direction. A comparison is made between Generalized Cross Correlation (GCC) methods for locating the source in real office environment. Beamforming is implemented to make the microphone array listen in the desired direction thus reducing the interference from other sources. Minimum Variance Distortion-less Response (MVDR) approach is shown to give better results compared to more simplistic techniques. Perceptual based Eigen filter incorporating human hearing models in subspace incorporated in the suppressor eliminates the residual noise. Objective system performance is evaluated by estimating Signal-to-Noise-Ratio improvement (SNRI), segmental SNR, signal degradation and noise suppression. Perpetual Evaluation of Speech Quality (PESQ) gives Mean Opinion Score for subjective evaluation. / asim_zolo@yahoo.com, akbarali45@gmail.com