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Karakutuk, Serkan. "Blind And Semi-blind Channel Order Estimation In Simo Systems." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611107/index.pdf.
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Channel order estimation is an important problem in many fields including signal processing,
communications, acoustics, and more. In this thesis, blind channel order estimation problem
is considered for single-input, multi-output (SIMO) FIR systems. The problem is to estimate
the effective channel order for the SIMO system given only the output samples corrupted by
noise. Two new methods for channel order estimation are presented. These methods have
several useful features compared to the currently known techniques. They are guaranteed to
find the true channel order for noise free case and they perform significantly better for noisy
observations. These algorithms show a consistent performance when the number of observations,
channels and channel order are changed. The proposed algorithms are integrated with
the least squares smoothing (LSS) algorithm for blind identification of the channel coefficients. LSS algorithm is selected since it is a deterministic algorithm and has some additional
features suitable for order estimation. The proposed algorithms are compared with a variety
of dierent algorithms including linear prediction (LP) based methods. LP approaches are
known to be robust to channel order overestimation. In this thesis, it is shown that significant
gain can be obtained compared to LP based approaches when the proposed techniques are
used. The proposed algorithms are also compared with the oversampled single-input, single-output (SISO) system with a generic decision feedback equalizer, and better mean-square
error performance is observed for the blind setting.
Channel order estimation problem is also investigated for semi-blind systems where a pilot
signal is used which is known at the receiver. In this case, two new methods are proposed
which exploit the pilot signal in dierent ways. When both unknown and pilot symbols are
used, a better estimation performance can be achieved compared to the proposed blind methods.
The semi-blind approach is especially effective in terms of bit error rate (BER) evaluation
thanks to the use of pilot symbols in better estimation of channel coecients. This approach
is also more robust to ill-conditioned channels. The constraints for these approaches, such
as synchronization, and the decrease in throughput still make the blind approaches a good
alternative for channel order estimation. True and effective channel order estimation topics
are discussed in detail and several simulations are done in order to show the significant performance
gain achieved by the proposed methods.
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Fung, Carrson Chee-Ho. "Eigensystem based techniques for blind channel estimation and equalization /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202005%20FUNG.
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Dietze, Kai. "Blind Identification of MIMO Systems: Signal Modulation and Channel Estimation." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/30060.
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Present trends in communication links between devices have opted for wireless instead of wired solutions. As a consequence, unlicensed bands have seen a rise in the interference level as more and more devices are introduced into the market place that take advantage of these free bands for their communication needs. Under these conditions, the receiver's ability to recognize and identify the presence of interference becomes increasingly important. In order for the receiver to make an optimal decision on the signal-of-interest, it has to be aware of the type (modulation) of interference as well as how the received signals are affected (channel) by these impediments in order to appropriately mitigate them.
This dissertation addresses the blind (unaided) identification of the signal modulations and the channel in a Multiple Input Multiple Output (MIMO) system. The method presented herein takes advantage of the modulation induced periodicities of the signals in the system and uses higher-order cyclostationary statistics to extract the signal and channel unknowns. This method can be used to identify more signals in the system than antenna elements at the receiver (overloaded case). This dissertation presents a system theoretic analysis of the problem as well as describes the development of an algorithm that can be used in the identification of the channel and the modulation of the signals in the system. Linear and non-linear receivers are examined at the beginning of the manuscript in order to review the a priori information that is needed for each receiver configuration to function properly.Ph. D.
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Woo, Wai Lok. "Blind inverse channel estimation using second and higher order statistics." Thesis, University of Newcastle Upon Tyne, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421174.
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BACKX, FABIAN DAVID. "BLIND CHANNEL ESTIMATION AND SIGNAL DETECTION IN OFDM TRANSMISSION SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14375@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOO esquema OFDM (Orthogonal Frequency Division Multiplexing) é um esquema de transmissão de sinais por multiplexação em freqüência e sua adoção vem mostrando-se bastante promissora no que diz respeito à transmissão de sinais em canais seletivos em freqüência. Sua relativa robustez frente a canais com múltiplos percursos é conseguida efetuando-se a transmissão paralela de dados em subportadoras ortogonais estreitas. Os receptores OFDM, de uma forma geral, necessitam de estimativas do canal de comunicação para realizar a detecção coerente dos sinais recebidos. Estimativas do canal podem ser obtidas de forma assistida por meio da utilização de pilotos que consomem preciosa banda, ou de forma cega, valendo-se apenas do conhecimento de características estatísticas dos sinais transmitidos. Esta tese segue a linha de estimação cega de canal. São propostos dois estimadores cegos de canal, para sistemas OFDM com intervalo de guarda ZP ou CP. O primeiro baseia-se no casamento de correlação, a saber: a estimativa do canal corresponde ao argumento que minimiza a norma quadrática de Frobenius da diferença entre a matriz correlação teórica parametrizada dos sinais recebidos e uma estimativa desta matriz obtida por meio das observações no receptor. O segundo estimador é desenvolvido a partir de uma modificação do método de identificação de canal por meio da estimação do subespaço de ruído, lançando mão de uma estimativa para o operador projeção no subespaço de ruído. Técnicas para resolver a ambigüidade complexa presente nas estimativas do canal que resultam dos métodos propostos são abordadas. Os estimadores propostos são estendidos para sistemas OFDM ditos com intervalo de guarda insuficiente. Resultados de simulações ilustram o desempenho, tanto em termos de erro quadrático médio dos estimadores, quanto em taxa de erro de bit dos sistemas.
Orthogonal Frequency Division Multiplexing is a multi-carrier transmission technique suitable for wireless communications through frequency selective channels, thus making it an appealing scheme for next-generation applications demanding high data rates. Its robustness with respect to multipath channels is obtained by modulating a set of closely-spaced orthogonal sub-carriers. In order to coherently detect the received signals, Channel State Information must be available to OFDM receivers. Supervised channel estimation is achieved by multiplexing known pilot symbols and data symbols, thus reducing effective system throughput. On the other hand, unsupervised or blind estimation techniques rely solely on the knowledge of statistical characteristics of the transmitted signal in order to identify the channel. This thesis proposes two blind channel estimators, for OFDM systems with CP or ZP guard interval. The first estimator is based on correlation matching: a channel estimate is obtained as the argument which minimizes the Frobenius quadratic norm of the difference between the parameterized theoretical correlation matrix of the transmitted signals and an estimate of that matrix obtained by means of observations at the receiver. The second estimator is obtained by modifying the noise subspace based channel estimator and using an estimate for the noise subspace projector which relies on powers of the inverse correlation matrix. Techniques to eliminate the inherent complex ambiguity derived from the proposed blind channel estimators are addressed. The porposed estimators’ formulation is also extended to the case of OFDM systems with insufficient guard intervals. Simulation results depict Mean Square Error of the proposed estimators, as well as Bit Error Rate performance of systems using those estimators in various scenarios.
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Dizdar, Onur. "Blind Channel Estimation Based On The Lloyd-max Algorithm Innarrowband Fading Channels And Jamming." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613333/index.pdf.
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In wireless communications, knowledge of the channel coefficients is required for coherent
demodulation. In this thesis, a blind channel estimation method based on the Lloyd-Max
algorithm is proposed for single-tap fading channels. The algorithm estimates the constellation
points for the received signal using an iterative least squares approach. The algorithm is
investigated for fast-frequency hopping systems with small block lengths and operating under
partial-band and partial-time jamming for both detecting the jammer and estimating the
channel. The performance of the Lloyd-Max channel estimation algorithm is compared to the
performance of pilot-based channel estimation algorithms which also use the least squares
approach and non-coherent demodulation and decoding.
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Kang, Wei. "Subspace-based blind channel estimation : generalization, performance analysis and adaptive implementation." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=19683.
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In this thesis, we present a systematic study of the subspace-based blind channel estimation method. We first formulate a general signal model of multiple simultaneous signals transmitted through vector channels, which can be applied to a multitude of modern digital communication systems. Based on this model, we then propose a generalized subspace-based channel estimator by minimizing a novel cost function, which incorporates the set of kernel matrices of the signals sharing the target channel via a weighted sum of projection errors. We investigate the asymptotic performance1 of the proposed estimator, i.e. bias, covariance, mean square error (MSE) and Cramer-Rao bound, for large numbers of independent observations. We show that the performance of the estimator can be optimized by increasing the number of kernel matrices and by using a special set of weights in the cost function. We also propose a novel adaptive implementation of the generalized subspace channel estimator. The low-complexity and numerical robustness of this adaptive implementation make it suitable for online estimation of time1-varying channels over long observation periods. Finally, we consider the application of the proposed estimator to a down-link CDMA system operating in frequency selective fading channel with negligible ISI. The results of the computer simulations fully support our analytical developments.
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Tu, Chao-Cheng. "Subspace-based blind channel estimation and tracking for MIMO-OFDM systems." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=94926.
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Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) is now widely considered as a favored technology for emerging and future generation wireless systems. MIMO-OFDM aims to achieve increased channel capacity limit by exploiting the use of multiple antennas in combination with multi-carrier orthogonal modulation. While the possibility of achieving this limit is bestowed on the invention of capacity-achieving coding and decoding techniques, in reality, this prospect relies heavily on the existence and use of advanced channel estimation techniques. To facilitate fast and reliable channel estimation in MIMO-OFDM systems, pilot symbol insertion is usually considered; however, the channel capacity is greatly reduced by inserting those pilot symbols. Therefore, employing fast-converging and reliable blind channel estimation for MIMO-OFDM seems to be an attractive solution for future wireless systems. To this end, blind channel estimation based on second order statistics (SOS), instead of higher order statistics (HOS), has been widely considered as a suitable candidate. Amid SOS-based blind approaches, subspace-based estimation is attractive since reliable estimates can often be obtained in a simple form by optimizing a quadratic cost function. Nonetheless, the performance of the subspace-based blind channel estimators may still be seriously degraded under time-varying conditions. This problem can generally make overall performance unsatisfactory, especially in MIMO-OFDM systems whose number of subcarriers is large. In order to overcome this limitation and successfully employ subspace-based channel estimation in MIMO-OFDM systems, it is essential to minimize the required length of the underlying time averaging period. In this thesis, we propose a new subspace-based blind channel estimator that requires only a comparably short time averaging period. We consider the design of such an estimator directly in the frequency domain, as oLe multiplexage par répartition en fréquences orthogonales (orthogonal frequency division multiplexing, soit OFDM) à entrées et à sorties multiples (multiple-input multiple-output, soit MIMO) est maintenant généralement considéré comme une technologie à préconiser pour les nouveaux systèmes sans fil et ceux des générations ultérieures. Le MIMO-OFDM vise à augmenter la limite de capacité Shannon en combinant l'utilisation d'antennes multiples et la modulation orthogonale multiporteuse. Bien que la possibilité d'atteindre cette limite soit possible grâce à l'invention de techniques d'encodage et de décodage atteignant la capacité, en réalité, cette perspective d'avenir se base en grande partie sur l'existence et l'utilisation de techniques d'estimation de voie avancées. Pour faciliter l'estimation de voie rapide et fiable dans les systèmes MIMO-OFDM, on songe habituellement à l'insertion de symboles pilotes; cependant, la capacité de la voie est grandement réduite par leur insertion. L'utilisation d'estimation de voie aveugle fiable et à convergence rapide pour les MIMO-OFDM semble donc être une solution attrayante pour les futurs systèmes sans fil. À cette fin, l'estimation de voie aveugle basée sur des statistiques de deuxième ordre, au lieu des statistiques d'ordre supérieur, est généralement considérée comme une candidate acceptable. Parmi les approches aveugles basées sur les statistiques de deuxième ordre, l'estimation basée dans le sous-espace est attrayante, puisque des estimations fiables peuvent souvent être obtenues de façon simple en optimisant une fonction de coût quadratique. Néanmoins, la performance des estimateurs de voie aveugles basés dans le sous-espace peut être gravement dégradée dans des conditions instationnaires. Ce problème peut habituellement rendre la performance globalement insatisfaisante, surtout dans les systèmes MIMO-OFDM avec un nombre de sous-porteuses élevé. Afin de compen
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Su, Borching Vaidyanathan P. P. Vaidyanathan P. P. "Blind channel estimation using redundant precoding : new algorithms, analysis, and theory /." Diss., Pasadena, Calif. : California Institute of Technology, 2008. http://resolver.caltech.edu/CaltechETD:etd-03102008-010821.
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Punnoose, Sonu. "Blind channel estimation and layered space frequency equalisation for MIMO CDMA uplink systems." Thesis, University of Liverpool, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433038.
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Nicolov, Eugene Borislavov. "On blind channel estimation without channel ambiguity for single-rate and multi-rate space-time block coded CDMA systems." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99528.
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In this work we study the downlink transmission of Code Division Multiple Access (CDMA) systems using the Alamouti code in order to provide space time diversity.We will propose a novel spreading signature assignment technique for space-time coded single rate CDMA system, which, compared to other signature assignment methods, allows to reduce the number of spreading signatures necessary in order to solve the channel ambiguity problem while performing blind channel estimation. This encoding method is called "rolling signatures".
We also introduce a new method for combining the Alamouti space-time code with multi-rate CDMA. Instead of block coding entire CDMA symbols we will apply Alamouti coding at the chip-level. Such a coding method is called "chip-level" block coding. We present for our chip-level coding technique, various linear decoding structures both joint and disjoint. In the case of joint decoding, space-time and CDMA filtering at the mobile's end is done simultaneously by a single linear receiver. In the case of disjoint decoding, there are two dedicated receive filters, one performing space-time decoding and the other CDMA filtering. We also introduce a blind channel estimation technique and provide a thorough performance analysis of our estimator, in the form of mean-square-error performance analysis. Finally, we provide the Cramer-Rao Bound for our channel estimator.
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Latva-aho, M. (Matti). "Advanced receivers for wideband CDMA systems." Doctoral thesis, University of Oulu, 1998. http://urn.fi/urn:isbn:9514250397.
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Abstract
Advanced receiver structures capable of suppressing multiple-access interference in code-division multiple-access (CDMA) systems operating in frequency-selective fading channels are considered in this thesis. The aim of the thesis is to develop and validate novel receiver concepts suitable for future wideband cellular CDMA systems. Data detection and synchronization both for downlink and uplink receivers are studied.
The linear minimum mean squared error (LMMSE) receivers are derived and analyzed in frequency-selective fading channels. Different versions of the LMMSE receivers are shown to be suitable for different data rates. The precombining LMMSE receiver, whichis also suitable for relatively fast fading channels, is shown to improve the performance of the conventional RAKE receivers signicantly in the FRAMES wideband CDMA concept. It is observed that the performance of the conventional RAKE receivers is degraded signicantly with highest data rates due to multiple-access interference (MAI) as well as due to inter-path interference.
Based on a general convergence analysis, it is observed that the postcombining LMMSE receivers are mainly suited to the high data rate indoor systems. The blind adaptive LMMSE-RAKE receiverdeveloped for relatively fast fading frequency-selective channels gives superior rate of convergence and bit error rate (BER) performance in comparison to other blind adaptive receivers based on least mean squares algorithms.
The minimum variance method based delay estimation in blind adaptive receivers is shown to result in improved delay acquisition performance in comparison to the conventional matched filter and subspace based acquisition schemes. A novel delay tracking algorithm suitable to blind least squares receivers is also proposed. The analysis shows improved tracking performance in comparison to the standard delay-locked loops.
Parallel interference cancellation (PIC) receivers are developed for the uplink. Data detection, channel estimation, delay acquisition, delay tracking, inter-cell interference suppression, and array processing in PIC receivers are considered. A multistage data detector with the tentative data decision and the channel estimate feedback from the last stage is developed. Adaptive channel estimation filters are used to improve the channel estimation accuracy. The PIC method is also applied to the timing synchronization of the receiver. It is shown that the PIC based delay acquisition and tracking methods can be used to improve the performance of the conventional synchronization schemes.
Although the overall performance of the PIC receiver is relatively good in the single-cell case, its performance is signicantly degraded in a multi-cell environment due to unknown signal components which degrade the MAI estimates and subsequently the cancellation efficiency. The blind receiver concepts developed for the downlink are integrated into the PIC receivers for inter-cell interference suppression. The resulting LMMSE-PIC receiver is capable of suppressing residual interference and results in good BER performance in the presence of unknown signal components.
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Mohammad, Maruf H. "Blind Acquisition of Short Burst with Per-Survivor Processing (PSP)." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/46193.
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This thesis investigates the use of Maximum Likelihood Sequence Estimation (MLSE) in the presence of unknown channel parameters. MLSE is a fundamental problem that is closely related to many modern research areas like Space-Time Coding, Overloaded Array Processing and Multi-User Detection. Per-Survivor Processing (PSP) is a technique for approximating MLSE for unknown channels by embedding channel estimation into the structure of the Viterbi Algorithm (VA). In the case of successful acquisition, the convergence rate of PSP is comparable to that of the pilot-aided RLS algorithm. However, the performance of PSP degrades when certain sequences are transmitted.
In this thesis, the blind acquisition characteristics of PSP are discussed. The problematic sequences for any joint ML data and channel estimator are discussed from an analytic perspective. Based on the theory of indistinguishable sequences, modifications to conventional PSP are suggested that improve its acquisition performance significantly. The effect of tree search and list-based algorithms on PSP is also discussed. Proposed improvement techniques are compared for different channels. For higher order channels, complexity issues dominate the choice of algorithms, so PSP with state reduction techniques is considered. Typical misacquisition conditions, transients, and initialization issues are reported.Master of Science
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Jagannatham, Aditya K. "Bandwidth efficient channel estimation for multiple-input multiple-output (MIMO) wireless communication systems a study of semi-blind and superimposed schemes /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3250071.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed April 4, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 177-183).
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Taiwo, Peter, and Itie Serge Kone Dossongui. "Towards Real-Time CMA Equalization by using FFT for Signal Blocks transmitted over an Aeronautical channel." International Foundation for Telemetering, 2016. http://hdl.handle.net/10150/624260.
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We consider the problem of equalizing data blocks of signals, which have been transmitted over an
aeronautical channel using two different modulation schemes. The equalization is performed using the block-processing
constant modulus algorithm (CMA), and in order to achieve real-time processing a Fast Fourier Transform (FFT) is used
to compute the gradient of this cost function during equalization. The equalizer length is chosen to be five times of the
channel length. For the first experiment, we present the result of equalizing a set of measured data, which was modulated
and transmitted using the iNET packet structure with SOQPSK modulation. In this case, the CMA equalizer is first
initialized using MMSE and the equalizer coefficients are then updated once, using each entire block (iNET packet). In
the second experiment, we apply the FFT-based block processing equalizer to received data blocks of QPSK signals,
which have been randomly generated and transmitted over an aeronautical channel. A modified constant modulus
algorithm and alphabet matched algorithm (CMA + AMA) equalizer is used to recover these data blocks. For this case of
QPSK signals, the equalizer performance is evaluated over 500 Monte Carlo runs, using the average symbol error rate
(SER).
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Anand, K. "Methods for Blind Separation of Co-Channel BPSK Signals Arriving at an Antenna Array and Their Performance Analysis." Thesis, Indian Institute of Science, 1995. http://hdl.handle.net/2005/123.
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Capacity improvement of Wireless Communication Systems is a very important area of current research. The goal is to increase the number of users supported by the system per unit bandwidth allotted. One important way of achieving this improvement is to use multiple antennas backed by intelligent signal processing. In this thesis, we present methods for blind separation of co-channel BPSK signals arriving at an antenna array. These methods consist of two parts, Constellation Estimation and Assignment. We give two methods for constellation estimation, the Smallest Distance Clustering and the Maximum Likelihood Estimation. While the latter is theoretically sound,the former is Computationally simple and intuitively appealing. We show that the Maximum Likelihood Constellation Estimation is well approximated by the Smallest Distance Clustering Algorithm at high SNR. The Assignment Algorithm exploits the structure of the BPSK signals. We observe that both the methods for estimating the constellation vectors perform very well at high SNR and nearly attain Cramer-Rao bounds. Using this fact and noting that the Assignment Algorithm causes negligble error at high SNR, we derive an upper bound on the probability of bit error for the above methods at high SNR. This upper bound falls very rapidly with increasing SNR, showing that our constellation estimation-assignment approach is very efficient. Simulation results are given to demonstrate the usefulness of the bounds.
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Vía, Rodríguez Javier. "Estima e igualación ciega de canales MIMO con y sin redundancia espacial." Doctoral thesis, Universidad de Cantabria, 2007. http://hdl.handle.net/10803/10666.
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La mayor parte de los sistemas de comunicaciones requieren el conocimiento previo del canal, el cual se suele estimar a partir de una secuencia de entrenamiento. Sin embargo, la transmisión de símbolos piloto se traduce en una reducción de la eficiencia espectral del sistema, lo que imposibilita que se alcancen los límites predichos por la Teoría de la Información. Este problema ha motivado el desarrollo de un gran número de técnicas para la estima e igualación ciega de canal, es decir, para la obtención del canal o la fuente sin necesidad de transmitir una señal de entrenamiento. Normalmente, estas técnicas se basan en el conocimiento previo de ciertas características de la señal, tales como su pertenencia a un alfabeto finito, o sus estadísticos de orden superior. Sin embargo, en el caso de sistemas de múltiples entradas y salidas (MIMO), se ha demostrado que los estadísticos de segundo orden de las observaciones proporcionan la información suficiente para resolver el problema ciego.El objetivo de esta Tesis consiste en la obtención de nuevas técnicas para la estima e igualación ciega de canales MIMO, tanto en sistemas con redundancia espacial, como en casos más generales en los que las fuentes no presentan ningún tipo particular de estructura. De manera general, los métodos propuestos se basan en los estadísticos de segundo orden de las observaciones. Sin embargo, las técnicas se presentan desde un punto de vista determinista, es decir, los algoritmos propuestos explotan directamente la estructura de las matrices de datos, lo que permite obtener resultados más precisos cuando se dispone de un número reducido de observaciones. Adicionalmente, la reformulación de los criterios propuestos como problemas clásicos del análisis estadístico de señales, ha permitido la obtención de algoritmos adaptativos eficientes para la estima e igualación de canales MIMO. En primer lugar se aborda el caso de sistemas sin redundancia. Más concretamente, se analiza el problema de igualación ciega de canales MIMO selectivos en frecuencia, el cual se reformula como un conjunto de problemas de análisis de correlaciones canónicas (CCA). La solución de los problemas CCA se puede obtener de manera directa mediante un problema de autovalores generalizado. Además, en esta Tesis se presenta un algoritmo adaptativo basado en la reformulación de CCA como un conjunto de problemas de regresión lineal acoplados. De esta manera, se obtienen nuevos algoritmos bloque y adaptativos para la igualación ciega de canales MIMO de una manera sencilla. Finalmente, el método propuesto se basa, como muchas otras técnicas ciegas, en el conocimiento a priori del orden del canal, lo que constituye un problema casi tan complicado como el de la estima o igualación ciega. Así, en el caso de canales de una entrada y varias salidas (SIMO), la combinación de la técnica propuesta con otros métodos para la estima ciega del canal permite obtener un nuevo criterio para extracción del orden de este tipo de canalesEn segundo lugar se considera el problema de estima ciega de canal en sistemas con algún tipo de redundancia o estructura espacial, con especial interés en el caso de sistemas con codificación espacio-temporal por bloques (STBC). Específicamente, se propone una nueva técnica para la estima ciega del canal, cuya complejidad se reduce a la extracción del autovector principal de una matriz de correlación modificada. El principal problema asociado a este tipo de sistemas viene dado por la existencia de ciertas ambigüedades a la hora de estimar el canal. En esta Tesis se plantea el problema de identificabilidad de una manera general, y en el caso de códigos ortogonales (OSTBCs) se presentan varios nuevos teoremas que aseguran la identificabilidad del canal en un gran número de casos. Adicionalmente, se proponen varias técnicas para la resolución de las ambigüedades, tanto en el caso OSTBC como para códigos más generales. En concreto, se introduce el concepto de diversidad de código, que consiste en la combinación de varios códigos STBC. Esta técnica permite resolver las indeterminaciones asociadas a un gran número de problemas, y en su versión más sencilla se reduce a una precodificación no redundante consistente en una simple rotación o permutación de las antenas transmisoras.En definitiva, en esta Tesis se abordan los problemas de estima e igualación ciega de canal en sistemas MIMO, y se presentan varias técnicas ciegas, cuyas prestaciones se evalúan mediante un gran número de ejemplos de simulación.The majority of communication systems need the previous knowledge of the channel, which is usually estimated by means of a training sequence. However, the transmission of pilot symbols provokes a reduction in bandwidth efficiency, which precludes the system from reaching the limits predicted by the Information Theory. This problem has motivated the development of a large number of blind channel estimation and equalization techniques, which are able to obtain the channel or the source without the need of transmitting a training signal. Usually, these techniques are based on the previous knowledge of certain properties of the signal, such as its belonging to a finite alphabet, or its higher-order statistics. However, in the case of multiple-input multiple-output (MIMO) systems, it has been proven that the second order statistics of the observations provide the sufficient information for solving the blind problem.The aim of this Thesis is the development of new blind MIMO channel estimation and equalization techniques, both in systems with spatial redundancy, and in more general cases where the sources do not have any particular spatial structure. In general, the proposed methods are based on the second order statistics of the observations. However, the techniques are presented from a deterministic point of view, i.e., the proposed algorithms directly exploit the structure of the data matrices, which allows us to obtain more accurate results when only a reduced number of observations is available. Additionally, the reformulation of the proposed criteria as classical statistical signal processing problems is exploited to obtain efficient adaptive algorithms for MIMO channel estimation and equalization.Firstly, we consider the case of systems without spatial redundancy. Specifically, we analyze the problem of blind equalization of frequency selective MIMO channels, which is reformulated as a set of canonical correlation analysis (CCA) problems. The solution of the CCA problems can be obtained by means of a generalized eigenvalue problem. In this Thesis, we present a new adaptive algorithm based on the reformulation of CCA as a set of coupled linear regression problems. Therefore, new batch and adaptive algorithms for blind MIMO channel equalization are easily obtained. Finally, the proposed method, as well as many other blind techniques, is based on the previous knowledge of the channel order, which is a problem nearly as complicated as the blind channel estimation or equalization. Thus, in the case of single-input multiple-output (SIMO) channels, the combination of the proposed technique with other blind channel estimation methods provides a new criterion for the order extraction of this class of channels.Secondly, we consider the problem of blind channel estimation in systems with some kind of redundancy or spatial structure, with special interest in space-time block coded (STBC) systems. Specifically, a new blind channel estimation technique is proposed, whose computational complexity reduces to the extraction of the principal eigenvector of a modified correlation matrix. The main problem in these cases is due to the existence of certain ambiguities associated to the blind channel estimation problem. In this Thesis the general identifiability problem is formulated and, in the case of orthogonal codes (OSTBCs), we present several new theorems which ensure the channel identifiability in a large number of cases. Additionally, several techniques for the resolution of the ambiguities are proposed, both in the OSTBC case as well as for more general codes. In particular, we introduce the concept of code diversity, which consists in the combination of several STBCs. This technique avoids the ambiguities associated to a large number of problems, and in its simplest version it reduces to a non-redundant precoding consisting of a single rotation or permutation of the transmit antennas.In summary, in this Thesis the blind MIMO channel estimation and equalization problems are analyzed, and several blind techniques are presented, whose performance is evaluated by means of a large number of simulation examples.
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Peng, Danilo. "Application of machine learning in 5G to extract prior knowledge of the underlying structure in the interference channel matrices." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252314.
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The data traffic has been growing drastic over the past few years due to digitization and new technologies that are introduced to the market, such as autonomous cars. In order to meet this demand, the MIMO-OFDM system is used in the fifth generation wireless network, 5G. Designing the optimal wireless network is currently the main research within the area of telecommunication. In order to achieve such a system, multiple factors has to be taken into account, such as the suppression of interference from other users. A traditional method called linear minimum mean square error filter is currently used to suppress the interferences. To derive such a filter, a selection of parameters has to be estimated. One of these parameters is the ideal interference plus noise covariance matrix. By gathering prior knowledge of the underlying structure of the interference channel matrices in terms of the number of interferers and their corresponding bandwidths, the estimation of the ideal covariance matrix could be facilitated. As for this thesis, machine learning algorithms were used to extract these prior knowledge. More specifically, a two or three hidden layer feedforward neural network and a support vector machine with a linear kernel was used. The empirical findings implies promising results with accuracies above 95% for each model.Under de senaste åren har dataanvändningen ökat drastiskt på grund av digitaliseringen och allteftersom nya teknologier introduceras på marknaden, exempelvis självkörande bilar. För att bemöta denna efterfrågan används ett s.k. MIMO-OFDM system i den femte generationens trådlösa nätverk, 5G. Att designa det optimala trådlösa nätverket är för närvarande huvudforskningen inom telekommunikation och för att uppnå ett sådant system måste flera faktorer beaktas, bland annat störningar från andra användare. En traditionell metod som används för att dämpa störningarna kallas för linjära minsta medelkvadratfelsfilter. För att hitta ett sådant filter måste flera olika parametrar estimeras, en av dessa är den ideala störning samt bruskovariansmatrisen. Genom att ta reda på den underliggande strukturen i störningsmatriserna i termer av antal störningar samt deras motsvarande bandbredd, är något som underlättar uppskattningen av den ideala kovariansmatrisen. I följande avhandling har olika maskininlärningsalgoritmer applicerats för att extrahera dessa informationer. Mer specifikt, ett neuralt nätverk med två eller tre gömda lager samt stödvektormaskin med en linjär kärna har använts. De slutliga resultaten är lovande med en noggrannhet på minst 95% för respektive modell.
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Nguyen, Linh Trung. "Estimation and separation of linear frequency- modulated signals in wireless communications using time - frequency signal processing." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15984/.
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Signal processing has been playing a key role in providing solutions to key problems encountered in communications, in general, and in wireless communications, in particular. Time-Frequency Signal Processing (TFSP) provides eective tools for analyzing nonstationary signals where the frequency content of signals varies in time as well as for analyzing linear time-varying systems. This research aimed at exploiting the advantages of TFSP, in dealing with nonstationary signals, into the fundamental issues of signal processing, namely the signal estimation and signal separation. In particular, it has investigated the problems of (i) the Instantaneous Frequency (IF) estimation of Linear Frequency-Modulated (LFM) signals corrupted in complex-valued zero-mean Multiplicative Noise (MN), and (ii) the Underdetermined Blind Source Separation (UBSS) of LFM signals, while focusing onto the fast-growing area of Wireless Communications (WCom). A common problem in the issue of signal estimation is the estimation of the frequency of Frequency-Modulated signals which are seen in many engineering and real-life applications. Accurate frequency estimation leads to accurate recovery of the true information. In some applications, the random amplitude modulation shows up when the medium is dispersive and/or when the assumption of point target is not valid; the original signal is considered to be corrupted by an MN process thus seriously aecting the recovery of the information-bearing frequency. The IF estimation of nonstationary signals corrupted by complex-valued zero-mean MN was investigated in this research. We have proposed a Second-Order Statistics approach, rather than a Higher-Order Statistics approach, for IF estimation using Time-Frequency Distributions (TFDs). The main assumption was that the autocorrelation function of the MN is real-valued but not necessarily positive (i.e. the spectrum of the MN is symmetric but does not necessary has the highest peak at zero frequency). The estimation performance was analyzed in terms of bias and variance, and compared between four dierent TFDs: Wigner-Ville Distribution, Spectrogram, Choi-Williams Distribution and Modified B Distribution. To further improve the estimation, we proposed to use the Multiple Signal Classification algorithm and showed its better performance. It was shown that the Modified B Distribution performance was the best for Signal-to-Noise Ratio less than 10dB. In the issue of signal separation, a new research direction called Blind Source Separation (BSS) has emerged over the last decade. BSS is a fundamental technique in array signal processing aiming at recovering unobserved signals or sources from observed mixtures exploiting only the assumption of mutual independence between the signals. The term "blind" indicates that neither the structure of the mixtures nor the source signals are known to the receivers. Applications of BSS are seen in, for example, radar and sonar, communications, speech processing, biomedical signal processing. In the case of nonstationary signals, a TF structure forcing approach was introduced by Belouchrani and Amin by defining the Spatial Time- Frequency Distribution (STFD), which combines both TF diversity and spatial diversity. The benefit of STFD in an environment of nonstationary signals is the direct exploitation of the information brought by the nonstationarity of the signals. A drawback of most BSS algorithms is that they fail to separate sources in situations where there are more sources than sensors, referred to as UBSS. The UBSS of nonstationary signals was investigated in this research. We have presented a new approach for blind separation of nonstationary sources using their TFDs. The separation algorithm is based on a vector clustering procedure that estimates the source TFDs by grouping together the TF points corresponding to "closely spaced" spatial directions. Simulations illustrate the performances of the proposed method for the underdetermined blind separation of FM signals. The method developed in this research represents a new research direction for solving the UBSS problem. The successful results obtained in the research development of the above two problems has led to a conclusion that TFSP is useful for WCom. Future research directions were also proposed.
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Chehade, Tarek. "Optimisation d'un précodeur MIMO-OFDM dans le contexte de l'estimation aveugle et semi-aveugle du canal de communication." Thesis, Brest, 2015. http://www.theses.fr/2015BRES0077/document.
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L’estimation de canal joue un rôle important dans les communications mobiles sans fil et en particulier dans les systèmes multi-antennes MIMO. Contrairement aux techniques classiques d’estimation de canal basées sur des séquences d’apprentissage ou des symboles pilotes, les techniques aveugles ne nécessitent aucune insertion de symboles d'apprentissage et permettent d'augmenter le débit utile. Les principales difficultés des techniques aveugles résident dans l’ambiguïté présente sur les estimées. Les techniques d’estimation semi-aveugles, basées sur les mêmes méthodes que l’estimation aveugle, sont plus robustes. Elles exploitent l’information aveugle ainsi que l’information provenant d’un nombre réduit de symboles d’apprentissage. Cette estimation du canal de communication est très utile dans les systèmes MIMO et permet de précoder le signal MIMO-OFDM en lui appliquant un pré-mélange permettant d'améliorer les performances. De nombreux types de précodeurs existent et leurs performances varient en fonction des critères d'optimisation retenus (Water-Filling, MMSE, Equal Error, max-SNR, max-d min …), mais aussi avec la qualité de l'estimation du canal de communication. Nous étudions dans cette thèse l’impact de l’utilisation de l’information du canal (CSI) provenant des méthodes d’estimation aveugle et semi-aveugle, dans l’application des précodeurs linéaires MIMO. Nous présentons également une étude statistique de l’erreur d’estimation provenant de ces méthodes. L’optimisation de ces précodeurs nous mène par la suite à exploiter un autre procédé permettant l’amélioration des performances : les codes correcteurs d’erreur. Nous nous intéressons particulièrement aux codes LDPC non-binaires et leur association avec les précodeurs linéaires MIMO. Nous montrons qu’une adaptation est possible et s’avère bénéfique dans certains cas. L’optimisation de cette association nous a permis de proposer un nouveau précodeur basé sur la maximisation de l’information mutuelle, robuste et plus performantChannel estimation plays an important role in wireless mobile communications, especially in MIMO systems. Unlike conventional channel estimation techniques based on training sequences or pilot symbols, blind techniques does not require the insertion of training symbols and allow higher throughput. The main problems of the blind lies in the ambiguity over the estimated channel. Based on the same methods as the blind estimation, the semi-blind estimation techniques are more robust. They exploit the blind information along with information provided by a small number of training symbols. The channel estimation is useful in MIMO systems and allows the precoding of the MIMO-OFDM signal by applying a pre-mixture in order to improve performance. Many types of precoders exist and their performance varies depending not only on the optimization criteria (Water-Filling, MMSE, Equal Error, max-SNR, max-d min ...), but also on the estimated channel. In this thesis we study the impact of using the channel information (CSI) from the blind and semi-blind estimation techniques to apply MIMO linear precoders. We also present a statistical study of the estimation error of these methods. The optimization of these precoders leads eventually to use another process allowing more performance improvement: the error correcting codes. We are particularly interested in non-binary LDPC codes and their association with linear MIMO precoders. We show that a matching is possible, and is beneficial in some cases. The optimization of this combination has allowed us to propose a new robust and more efficient precoder based on the maximization of mutual information
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Lassami, Nacerredine. "Représentations parcimonieuses et analyse multidimensionnelle : méthodes aveugles et adaptatives." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0139.
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Au cours de la dernière décennie, l’étude mathématique et statistique des représentations parcimonieuses de signaux et de leurs applications en traitement du signal audio, en traitement d’image, en vidéo et en séparation de sources a connu une activité intensive. Cependant, l'exploitation de la parcimonie dans des contextes de traitement multidimensionnel comme les communications numériques reste largement ouverte. Au même temps, les méthodes aveugles semblent être la réponse à énormément de problèmes rencontrés récemment par la communauté du traitement du signal et des communications numériques tels que l'efficacité spectrale. Aussi, dans un contexte de mobilité et de non-stationnarité, il est important de pouvoir mettre en oeuvre des solutions de traitement adaptatives de faible complexité algorithmique en vue d'assurer une consommation réduite des appareils. L'objectif de cette thèse est d'aborder ces challenges de traitement multidimensionnel en proposant des solutions aveugles de faible coût de calcul en utilisant l'à priori de parcimonie. Notre travail s'articule autour de trois axes principaux : la poursuite de sous-espace principal parcimonieux, la séparation adaptative aveugle de sources parcimonieuses et l'identification aveugle des systèmes parcimonieux. Dans chaque problème, nous avons proposé de nouvelles solutions adaptatives en intégrant l'information de parcimonie aux méthodes classiques de manière à améliorer leurs performances. Des simulations numériques ont été effectuées pour confirmer l’intérêt des méthodes proposées par rapport à l'état de l'art en termes de qualité d’estimation et de complexité calculatoireDuring the last decade, the mathematical and statistical study of sparse signal representations and their applications in audio, image, video processing and source separation has been intensively active. However, exploiting sparsity in multidimensional processing contexts such as digital communications remains a largely open problem. At the same time, the blind methods seem to be the answer to a lot of problems recently encountered by the signal processing and the communications communities such as the spectral efficiency. Furthermore, in a context of mobility and non-stationarity, it is important to be able to implement adaptive processing solutions of low algorithmic complexity to ensure reduced consumption of devices. The objective of this thesis is to address these challenges of multidimensional processing by proposing blind solutions of low computational cost by using the sparsity a priori. Our work revolves around three main axes: sparse principal subspace tracking, adaptive sparse source separation and identification of sparse systems. For each problem, we propose new adaptive solutions by integrating the sparsity information to the classical methods in order to improve their performance. Numerical simulations have been conducted to confirm the superiority of the proposed methods compared to the state of the art
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Carlo, Diego Di. "Echo-aware signal processing for audio scene analysis." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S075.
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La plupart des méthodes de traitement du signal audio considèrent la réverbération et en particulier les échos acoustiques comme une nuisance. Cependant, ceux-ci transmettent des informations spatiales et sémantiques importantes sur les sources sonores et des méthodes essayant de les prendre en compte ont donc récemment émergé.. Dans ce travail, nous nous concentrons sur deux directions. Tout d’abord, nous étudions la manière d’estimer les échos acoustiques à l’aveugle à partir d’enregistrements microphoniques. Deux approches sont proposées, l’une s’appuyant sur le cadre des dictionnaires continus, l’autre sur des techniques récentes d’apprentissage profond. Ensuite, nous nous concentrons sur l’extension de méthodes existantes d’analyse de scènes audio à leurs formes sensibles à l’écho. Le cadre NMF multicanal pour la séparation de sources audio, la méthode de localisation SRP-PHAT et le formateur de voies MVDR pour l’amélioration de la parole sont tous étendus pour prendre en compte les échos. Ces applications montrent comment un simple modèle d’écho peut conduire à une amélioration des performancesMost of audio signal processing methods regard reverberation and in particular acoustic echoes as a nuisance. However, they convey important spatial and semantic information about sound sources and, based on this, recent echo-aware methods have been proposed. In this work we focus on two directions. First, we study the how to estimate acoustic echoes blindly from microphone recordings. Two approaches are proposed, one leveraging on continuous dictionaries, one using recent deep learning techniques. Then, we focus on extending existing methods in audio scene analysis to their echo-aware forms. The Multichannel NMF framework for audio source separation, the SRP-PHAT localization method, and the MVDR beamformer for speech enhancement are all extended to their echo-aware versions
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Fernandes, Carlos EstevÃo Rolim. "MÃtodos estatÃsticos multi-percursos para a identificaÃÃo cega de canais da fonte de aplicaÃÃes Ãs comunicaÃÃes sem fio." Universidade Federal do CearÃ, 2008. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=2136.
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Laboratoire I3S/CNRSOs sistemas de telecomunicaÃÃes atuais oferecem servios que demandam taxas de transmissÃo muito elevadas. O problema da identificaÃÃo de canal aparece nesse contexto com um problema da maior importÃncia. O uso de tÃcnicas cegas tem sido de grande interesse na busca por um melhor compromisso entre uma taxas binÃria adequada e a qualidade da informaÃÃo recuperada. Apoiando-se em propriedades especiais dos cumulantes de 4a ordem dos sinais à saÃda do canal, esta tese introduz novas ferramentas de processamento de sinais com aplicaÃÃes em sistemas de comunicaÃÃo rÃdio-mÃveis. Explorando a estrutura simÃtrica dos cumulantes de saÃda, o problema da identificaÃÃo cega de canais à abordado a partir de um modelo multilinear do tensor de cumulantes 4a ordem, baseado em uma decomposiÃÃo em fatores paralelos (Parafac). No caso SISO, os componentes do novo modelo tensorial apresentam uma estrutura Hankel. No caso de canais MIMO sem memÃria, a redundÃncia dos fatores tensoriais à explorada na estimaÃÃo dos coeficientes dos canal. Neste contexto, novos algoritmos de identificaÃÃo cega de canais sÃo desenvolvidos nesta tese com base em um problema de otimizaÃÃo de mÃnimos quadrados de passo Ãnico (SS-LS). Os mÃtodos propostos exploram plenamente a estrutura multilinear do tensor de cumulantes bem como suas simetrias e redundÃncias, evitando assim qualquer forma de prÃ-processamento. Com efeito, a abordagem SS-LS induz uma soluÃÃo baseada em um Ãnico procedimento de minimizaÃÃo, sem etapas intermediÃrias, contrariamente ao que ocorre na maior parte dos mÃtodos existentes na literatura. Utilizando apenas os cumulantes de ordem 4 e explorando o conceito de Arranjo Virtual, trata-se tambÃm o problema da localizaÃÃo de fontes, num contexto multiusuÃrio. Uma contribuÃÃo original consiste em aumentar o nÃmero de sensores virtuais com base em uma decomposiÃÃo particular do tensor de cumulantes, melhorando assim a resoluÃÃo do arranjo, cuja estrutura à tipicamente obtida quando se usa estatÃsticas de ordem 6. Considera-se ainda a estimaÃÃo dos parÃmetros fÃsicos de um canal de comunicaÃÃo MIMO com muti-percursos. AtravÃs de uma abordagem completamente cega, o canal multi-percurso à primeiramente tratado como um modelo convolutivo e uma nova tÃcnica à proposta para estimar seus coeficientes. Esta tÃcnica nÃo-paramÃtrica generaliza os mÃtodos previamente propostos para os casos SISO e MIMO (sem memÃria). Fazendo uso de um formalismo tensorial para representar o canal de multi-percursos MIMO, seus parÃmetros fÃsicos podem ser obtidos atravÃs de uma tÃcnica combinada de tipo ALS-MUSIC, baseada em um algoritmo de subespaÃo. Por fim, serà considerado o problema da determinaÃÃo de ordem de canais FIR, particularmente no caso de sistemas MISO. Um procedimento completo à introduzido para a detecÃÃo e estimaÃÃo de canais de comunicaÃÃo MISO seletivos em freqÃÃncia. O novo algoritmo, baseado em uma abordagem de deflaÃÃo, detecta sucessivamente cada fonte de sinal, determina a ordem de seu canal de transmissÃo individual e estima os coeficientes associados.
Les systÃmes de tÃlÃcommunications modernes exigent des dÃbits de transmission trÃs ÃlevÃs. Dans ce cadre, le problÃme dâidentification de canaux est un enjeu majeur. Lâutilisation de techniques aveugles est dâun grand intÃrÃt pour avoir le meilleur compromis entre un taux binaire adÃquat et la qualità de lâinformation rÃcupÃrÃe. En utilisant les propriÃtÃs des cumulants dâordre 4 des signaux de sortie du canal, cette thÃse introduit de nouvelles mÃthodes de traitement du signal tensoriel avec des applications pour les systÃmes de communication radio-mobiles. En utilisant la structure symÃtrique des cumulants de sortie, nous traitons le problÃme de lâidentification aveugle de canaux en introduisant un mod`ele multilinÃaire pour le tenseur des cumulants dâordre 4, basà sur une dÃcomposition de type Parafac. Dans le cas SISO, les composantes du modÃle tensoriel ont une structure de Hankel. Dans le cas de canaux MIMO instantanÃs, la redondance des facteurs tensoriels est exploitÃe pour lâestimation des coefficients du canal. Dans ce contexte, nous dÃveloppons des algorithmes dâidentification aveugle basÃs sur une minimisation de type moindres carrÃs à pas unique (SS-LS). Les mÃthodes proposÃes exploitent la structure multilinÃaire du tenseur de cumulants aussi bien que les relations de symÃtrie et de redondance, ce qui permet dâÃviter toute sorte de traitement au prÃalable. En effet, lâapproche SS-LS induit une solution basÃe sur une seule et unique procÃdure dâoptimisation, sans les Ãtapes intermÃdiaires requises par la majorità des mÃthodes existant dans la littÃrature. En exploitant seulement les cumulants dâordre 4 et le concept de rÃseau virtuel, nous abordons aussi le problÃme de la localisation de sources dans le cadre dâun rÃseau dâantennes multiutilisateur. Une contribution originale consiste à augmenter le nombre de capteurs virtuels en exploitant un arrangement particulier du tenseur de cumulants, de maniÃre à amÃliorer la rÃsolution du rÃseau, dont la structure Ãquivaut à celle qui est typiquement issue de lâutilisation des statistiques dâordre 6. Nous traitons par ailleurs le problÃme de lâestimation des paramÃtres physiques dâun canal de communication de type MIMO à trajets multiples. Dans un premier temps, nous considÂerons le canal à trajets multiples comme un modÃle MIMO convolutif et proposons une nouvelle technique dâestimation des coefficients. Cette technique non-paramÃtrique gÃnÃralise les mÃthodes proposÃes dans les chapitres prÃcÃdents pour les cas SISO et MIMO instantanÃ. En reprÃsentant le canal multi-trajet à lâaide dâun formalisme tensoriel, les paramÃtres physiques sont obtenus en utilisant une technique combinÃe de type ALS-MUSIC, basÃe sur un algorithme de sous-espaces. Enfin, nous considÃrons le problÃme de la dÂetermination dâordre de canaux de type RIF, dans le contexte des systÃmes MISO. Nous introduisons une procÃdure complÃte qui combine la dÃtection des signaux avec lâestimation des canaux de communication MISO sÃlectifs en frÃquence. Ce nouvel algorithme, basà sur une technique de dÃflation, est capable de dÃtecter successivement les sources, de dÃterminer lâordre de chaque canal de transmission et dâestimer les coefficients associÂes.
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Chen, Ning. "Bandwidth Efficiency and Power Efficiency Issues for Wireless Transmissions." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/10484.
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As wireless communication becomes an ever-more important and pervasive part of our everyday life, system capacity and quality of service issues are becoming more critical. In order to increase the system capacity and improve the quality of service, it is necessary that we pay closer attention to bandwidth and power efficiency issues.
Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique for high speed data transmission and is generally regarded as bandwidth efficient. However, OFDM signals suffer from high peak-to-average power ratios (PARs) which lead to power inefficiency in the RF portion of the transmitter. Moreover, in OFDM, the well-known pilot tone assisted modulation (PTAM) technique utilizes a number of dedicated training pilots to acquire the channel state information (CSI), resulting in somewhat reduced bandwidth efficiency.
In this dissertation, we will address the above mentioned bandwidth and power efficiency issues in wireless transmissions. To avoid bandwidth efficiency loss due to dedicated training, we will first develop a superimposed training framework that can be used to track the frequency selective as well as the Doppler shift characteristics of a channel. Later on, we will propose a generalized superimposed training framework that allows improved channel estimates. To improve the power efficiency, we adopt the selected mapping (SLM) framework to reduce the PARs for both OFDM and forward link Code Division Multiple Access (CDMA). We first propose a dynamic SLM algorithm to greatly reduce the computational requirement of SLM without sacrificing its PAR reducing capability. We propose a number of blind SLM techniques for OFDM and for forward link CDMA; they require no side information and are easy to implement. Our proposed blind SLM technique for OFDM is a novel joint channel estimation and PAR reduction algorithm, for which bandwidth efficiency power efficiency - complexity - bit error rate tradeoffs are carefully considered.
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Shang, Lei, and lei shang@ieee org. "Modelling of Mobile Fading Channels with Fading Mitigation Techniques." RMIT University. Electrical and Computer Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20061222.113303.
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This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.
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Almeida, Andrà Lima FÃrrer de. "Modelagem tensorial e processamento de sinais por sistemas de comunicaÃÃes de redes." Universidade Federal do CearÃ, 2007. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=2131.
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CoordenaÃÃo de AperfeiÃoamento de NÃvel SuperiorEm 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.
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Kao, Chen-Wei, and 高禎唯. "Nearby Channel V.S. Blind Channel Estimation." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/48584281818353785127.
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碩士國立臺灣海洋大學
通訊與導航工程學系
104
With advancing technology, almost everyone has a mobile phone. Consider a simple and static environment: user A is communicating with base station through channel A by mobile phone and nearby, user B is not using phone. In [13], we know that if a transmitted signal pass through two similar channels, the power distribution of received signals in frequency domain are also similar. Therefore, we hope to abstract some information from user B to support user A. In this paper, we assume the following situation. We estimate channel A by a Blind Subspace Method and obtain channel B information by a Pilot-Assisted Channel Estimation Method. We apply channel B’s information (channel B’s coefficient) to a Blind Subspace Method. The simulation results show that if correlation coefficient is 0.9, i.e. channel A is very similar to channel B, then the converging rates of the Subspace Method is faster. However, while correlation coefficients are 0.6 and 0.1, channel B’s information cannot provide any benefit to channel A because of these are different channels.
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Liang, Chung-Heng, and 梁峻銜. "DSP Implementation for Blind Channel Estimation." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/33876218414752052417.
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Jan, Jui-Hua, and 冉瑞華. "Blind Channel Estimation for OFDM Systems." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/gzznwa.
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碩士國立交通大學
電機與控制工程系所
92
We propose a blind channel estimation method for OFDM systems based on finite alphabet property. The method called ratio is to make use of the property of slow phase change between two adjacent tones to cancel phase ambiguity. The proposed method needs less computation load compared with other existing methods. According to simulations, the proposed method has performances close to other existing ones on both channel estimation error and bit error rate.
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Wu, Tai-Yun, and 吳泰云. "Blind Channel Estimation for Space-Time OFDM." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/xwn8p5.
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碩士國立交通大學
電信工程系所
92
Space time (ST) orthogonal frequency division multiplexing (OFDM) has been well documented as an attractive means of achieving high data rate transmissions with diversity gains. In this thesis, we adopt a blind channel estimation algorithm proposed by Giannakis for ST OFDM, and derive the theoretical mean square error of the estimator. Moreover, we introduce phase direct (PD) and decision direct (DD) methods to further improve the performance of the estimator. DD and PD originally work on conventional OFDM, and PD is not suited for ST OFDM. Then we derive a new algorithm named sum-difference square method to make PD work on ST OFDM. DD is to update our estimated channel from the previous hard decision data, while PD is to solve the phase ambiguities after we’ve got the channel power response. Since the received data in ST OFDM is composed of two different transmitted data, the channel amplitude response is not easy to get. Hence, the aforementioned algorithm is about how to solve this problem. Furthermore, in computer simulations, we can see our algorithm really better the performance.
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Wu, Hua. "Simulations of blind and non-blind channel estimation techniques for bluetooth systems." Thesis, 2004. http://spectrum.library.concordia.ca/8083/1/MQ94715.pdf.
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Only few years after Bluetooth technology emerged as a new wireless technology, it has grasped the focus of top manufacturers in the world and got widespread use. Indeed, it is an excellent solution to replace cumbersome cables, which used to carry information between devices. Like other wireless technologies, fading and time-varying channels greatly degrade the performance of Bluetooth communications. In the first part of this thesis, Bluetooth specifications are introduced. This is followed by channel estimation techniques applicable to Bluetooth systems. Bluetooth adopts slow frequency hopping modulation. Hence, it is possible to implement channel estimation at the hop beginning, and then compensate for the impairment during the later header and payload parts of data packets. Classical channel estimation techniques are discussed and compared in the Bluetooth case, such as LMS, LS, MMSE, and blind channel estimation algorithms. We derive the specific channel estimation equations for each channel estimation technique. In the last chapter, the simulation results of these channel estimation techniques are presented in various fading cases, i.e. slow and fast fading.
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Fan, Yu-Hsiao, and 樊昱孝. "Semi-Blind SFBC OFDM Channel Estimation with an Improved Channel Compensation Scheme." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/10469844345563354612.
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碩士國立中央大學
通訊工程研究所碩士在職專班
98
Channel estimation has been a widely studied research topic in OFDM systems. In this thesis, we consider the semi-blind approach for channel tracking used in space frequency block code (SFBC) MIMO-OFDM. The advantage of the semi-blind method is little occupancy of bandwidth. The proposed algorithm can estimate the channel response by using the conventional decision feedback scheme or a modified constant modulus algorithm (CMA) based on an automatic switching mechanism in terms of the channel status. Besides, a modified channel estimation method is performed by applying the interpolation or the extrapolation scheme for channel compensation. Simulation results show that the proposed switching method in combination with the modified channel compensation scheme outperforms the method using only decision feedback or the modified CMA.
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Cheng, Yu-Ting, and 鄭有廷. "Order Determination and Parameter Estimation of Blind Channel Identification." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/81008352593987053165.
Full textAbstract:
碩士國立交通大學
電機與控制工程系
90
In this thesis, we investigate two blind channel identification methods. The first is the subspace methods for blind channel identification [12], and the second is the least-squares approach to blind channel identification [11]. In the second method, it did not discuss the method of channel order determination. In this aspect, we find that there is a regular relationship between the channel order and the rank of the data matrix formed by output data signals. First, we take an order which is bigger than the true channel order (over-estimated channel order), and use it to form the data matrix. And we use an existent method to estimate the rank of the original data matrix. Then we use it to estimate the channel order and estimate the channel coefficients. Finally, we find that the computations of the least squares approach is less than that of the subspace methods.
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Yeh, Ying-mao, and 葉英茂. "Blind SNR and Channel Length Estimation in OFDM Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/50021075820721348209.
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碩士國立中山大學
通訊工程研究所
97
In many algorithms for Orthogonal Frequency Division Multiplexing (OFDM) systems, the channel estimation is one of the most essential factors. In wireless environment, channel is change very fast, and the channel has multipath effect, the channel length is obtained by channel estimation. In this paper, we estimation the channel length and the SNR by virtual carriers (VC) and Singular value decomposition, when channel estimator known the information for channel length, then calculate complicated can be reduced. Besides, we proposed the estimated method at carriers frequency offset effect. Noise variance (or noise power) can improve performance of channel estimator, e.g. MMSE channel estimator, turbo code or power allocation. In this paper, we were estimate noise variance by using the blind method of property of orthogonality of matrix, which is differed from the traditional method of Pilots.
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Wu, Chao-Yu, and 吳兆宇. "Fast Blind Estimation of Channel for MIMO-OFDM Systems." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/63623778732782179942.
Full textAbstract:
碩士輔仁大學
電機工程學系碩士班
102
Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), intersymbol interference(ISI) is caused by a multipath fading channel. Cyclic prefix (CP) or zero padding (ZP) must be added to solve with this problem. This research investigates the performance of the channel estimation when the virtual carrier (VC) is added in the CP-OFDM systems. In terms of methods used for channel estimation, subspace(ss) blind channel estimation methods have been widely applied. However, the restriction of this method is a large amount of OFDM symbols are required for channel estimation. The subspace channel estimation techniques was used to calculate the correlation matrix in the traditional systems. However, this matrix needs to process a huge amount of data for converging. In the study, a circular matrix was proposed to increase the number of OFDM symbols. We apply this method to the MIMO CP-OFDM systems; then design a equalizer of MIMO OFDM systems . The proposed method also applies to MIMO ZP-OFDM by using the overlap-and-add(OLA) technique. It is found that the proposed method can obtain a low BER close to the one with ideal channel, regardless of CP-OFDM or ZP-OFDM systems. In the study, we propose three methods for channel estimation. The first two methods are traditional subspace channel estimation, and subspace channel estimation that is assisted by a cyclic repetition method(CRM). The last method, we combine subspace channel estimation and semi blind channel estimation. Finally, the simulation results indicated semi blind channel estimation method is better at the low BER and increasing convergence rate than semi blind channel estimation method is better than cyclic repetition method(CRM).
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Wei, Chuang-Yi, and 魏創翌. "Semi-blind Channel Estimation for MIMO SC-FDE Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/81252131826898979020.
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碩士國立中央大學
通訊工程研究所
98
The time-varying channel environment can lead to signal distortion in a wireless system, therefore, how to deal with the effects of a mobile channel has been widely studied. This thesis studies a multiple-input multiple-output (MIMO) constant modulus algorithm based semi-blind single-carrier frequency-domain equalizer (SC-FDE) system which adopts space-time block code (STBC) for MIMO channel equalization. At the receiver, an automatic switching scheme is applied based on the present channel status to switch the channel tracking algorithm between blind channel estimation and decision feedback estimation method in order to improve the system performance. From simulation results, we show that the switching method for channel estimation in the MIMO STBC SC-FDE system can gain better performance than that using only blind channel estimation method or decision feedback method.
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Pan, Chun-Hsien, and 潘俊憲. "Subspace-Based Semi-Blind Channel Estimation in Uplink OFDMA Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/46407458867727101624.
Full textAbstract:
碩士國立中山大學
通訊工程研究所
96
This thesis investigates the semi-blind channel estimation in uplink (UL) of Orthogonal Frequency Division Multiple Access (OFDMA) systems based on subspace decomposition. We exploit the orthogonality between signal subspace and noise subspace induced by virtual carriers (VCs) and cyclic prefix (CP) and the property of that the exclusive sub-carriers set is assigned to each user to estimate and identify the channels for each user individually. In OFDMA systems, when some users don’t communicate with base station, the sub-carriers of non-active user provide extra redundancy for channel estimate to enhance the accuracy of channel estimation. Furthermore, the sufficient channel identifiability condition is developed. Furthermore, a novel scheme, called as virtual carriers recovery (VCR) scheme, is proposed to improve the performance of the subspace-based channel estimation method. It suppresses the noise interference by recovering the VCs to zeros at receiver. The simulation results illustrate that the enhancement of VCR scheme is particularly apparent for the partially loaded OFDMA system at low signal to noise ratio (SNR). In addition, the VCR scheme increases the convergence rate of the subspace-base semi-blind channel estimation.
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"A blind channel estimation method for space-time coding systems." 2003. http://library.cuhk.edu.hk/record=b5891466.
Full textAbstract:
Zheng Ming.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 63-66).
Abstracts in English and Chinese.
Chapter 1. --- Introduction --- p.1
Chapter 1.1 --- Review of space-time coding and blind channel estimation --- p.1
Chapter 1.2 --- Introduction of space-time coding system --- p.4
Chapter 1.3 --- Diversity gain of space-time coding --- p.6
Chapter 1.4 --- Re-estimation --- p.7
Chapter 1.5 --- Notations --- p.8
Chapter 1.6 --- Outline of thesis --- p.8
Chapter 2. --- Estimation for BPSK Signals --- p.10
Chapter 2.1 --- Introduction to maximum likelihood estimation --- p.10
Chapter 2.2 --- System model --- p.11
Chapter 2.3 --- Deterministic ML algorithm --- p.14
Chapter 2.4 --- Re-estimation --- p.16
Chapter 2.5 --- Application to other constellations --- p.18
Chapter 2.6 --- Simulation results --- p.18
Chapter 2.7 --- Summary --- p.21
Chapter 3. --- Estimation for Flat Fading Channels --- p.22
Chapter 3.1 --- Introduction of constant modulus algorithm (CMA) --- p.22
Chapter 3.2 --- System model for flat fading channels --- p.24
Chapter 3.3 --- Blind estimation with CMA --- p.26
Chapter 3.3.1 --- Problem statement --- p.26
Chapter 3.3.2 --- Estimating channel with CMA --- p.28
Chapter 3.3.3 --- Solving the ambiguity problem --- p.32
Chapter 3.4 --- Re-estimation for flat fading channels --- p.39
Chapter 3.5 --- Estimation algorithm --- p.39
Chapter 3.6 --- Application to multi-antenna system --- p.41
Chapter 3.7 --- Simulation results --- p.42
Chapter 3.8 --- Summary --- p.46
Chapter 4. --- Estimation lor Frequency Selective Fading Channels --- p.48
Chapter 4.1 --- Introduction of space-time coded OFDM --- p.48
Chapter 4.2 --- System model --- p.51
Chapter 4.3 --- Estimation Algorithm --- p.54
Chapter 4.4 --- Simulation results --- p.56
Chapter 4.5 --- Summary --- p.59
Chapter 5. --- Conclus ions and Future Work --- p.60
Chapter 5.1 --- Conclusions --- p.60
Chapter 5.2 --- Future work --- p.61
Bibliography: --- p.63
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Chen, Sheng-wen, and 陳聖文. "Semi-blind Channel Estimation Using Orthogonal Precoding in OFDM Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/97546343018125217000.
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碩士國立中山大學
通訊工程研究所
94
In this thesis, a precoding scheme is proposed for channel estimation in orthogonal frequency-division multiplexing (OFDM) systems. The precoding scheme utilizes a special code matrix before the inverse fast Fourier transform (IFFT) at the transmitter. The row vectors of the matrix have constant amplitudes in both time domain and frequency domain. With the prcoding scheme, a semi-blind channel estimation method is proposed by using the characteristics of the row code sequences. In the proposed scheme, the channel frequency responses of all sub-carriers can be obtained by using only one pilot sub-carrier, and the proposed architecture can not only increase the data rate, but also avoid interpolation error in channel estimation. In addition, the normalized mean square error (NMSE) function is derived and parameters are optimized to improve system performance. The proposed precoding architecture and channel estimation scheme are shown to have better performances in bit error rate by conducting computer simulation experiments.
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Wan, Feng. "Signal-perturbation-free semi-blind channel estimation for MIMO-OFDM systems." Thesis, 2009. http://spectrum.library.concordia.ca/976246/1/NR63419.pdf.
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Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been considered as a strong candidate for the beyond 3G (B3G) wireless communication systems, due to its high data-rate wireless transmission performance. It is well known that the advantages promised by MIMO-OFDM systems rely on the precise knowledge of the channel state information (CSI). In real wireless environments, however, the channel condition is unknown. Therefore, channel estimation is of crucial importance in MIMO-OFDM systems. Semi-blind channel estimation as a combination of the training-based or pilot-assisted method and the pure blind approach is considered to be a feasible solution for practical wireless systems due to its better estimation accuracy as well as spectral efficiency. In this thesis, we address the semi-blind channel estimation issue of MIMO-OFDM systems with an objective to develop very efficient channel estimation approaches. In the first part of the dissertation, several nulling-based semi-blind approaches are presented for the estimation of time-domain MIMO-OFDM channels. By incorporating a blind constraint that is derived from MIMO linear prediction (LP) into a training-based least-square method, a semi-blind solution for the time-domain channel estimation is first obtained. It is revealed through a perturbation analysis that the semi-blind solution is not subject to signal perturbation and therefore is superior to pure blind estimation methods. The LP-based semi-blind method is then extended for the channel estimation of MIMO-OFDM systems with pulse-shaping. By exploiting the pulse-shaping filter in the transmitter and the matched filter in the receiver, a very efficient semi-blind approach is developed for the estimation of sampling duration based multipath channels. A frequency-domain correlation matrix estimation algorithm is also presented to facilitate the computation of time-domain second-order statistics required in the LP-based method. The nulling-based semi-blind estimation issue of sparse MIMO-OFDM channels is also addressed. By disclosing and using a relationship between the positions of the most significant taps (MST) of the sparse channel and the lags of nonzero correlation matrices of the received signal, a novel estimation approach consisting of the MST detection and the sparse channel estimation, both in a semi-blind fashion, is developed. An intensive simulation study of all the proposed nulling-based methods with comparison to some existing techniques is conducted, showing a significant superiority of the new methodologies. The second part of the dissertation is dedicated to the development of two signal-perturbation-free (SPF) semi-blind channel estimation algorithms based on a novel transmit scheme that bears partial information of the second-order statistics of the transmitted signal to receiver. It is proved that the new transmit scheme can completely cancel the signal perturbation error in the noise-free case, thereby improving largely the estimation accuracy of correlation matrix for channel estimation in noisy conditions. It is also shown that the overhead caused by the transmission of the 8PF data is negligible as compared to that of regular pilot signals. By using the proposed transmit scheme, a whitening rotation (WR)-based algorithm is first developed for frequency-domain MIMO-OFDM channel estimation. It is shown through both theoretical analysis and simulation study that the new WR-based algorithm significantly outperforms the conventional WR-based method and the nulling-based semi-blind method. By using MIMO linear prediction, the new WR-based algorithm utilizing the 8PF transmit scheme is then extended for time-domain MIMO-OFDM channel estimation. Computer simulations show that the proposed signal-perturbation-free LP-based semi-blind solution performs much better than the LP semi-blind method without using the proposed transmit scheme, the LS method as well as the nulling-based semi-blind method in terms of the MSE of the channel estimate.
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Huang, Lei. "Blind Channel Estimation and Multiuser Detection for Multi-Rate CDMA Communications." 2003. http://eprints.vu.edu.au/267/1/Lei%2C_Huang.pdf.
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The future wireless communications systems should be able to offer wide variety of applications, which have vastly different quality of service (QoS) requirements. The time-variable QoS may require the support of variable bit rates on the wireless links to the individual users. Multi-rate DS/CDMA is a promising basis on which to support the variable bit rates on the individual wireless links. Currently, the study on channel estimation and multiuser detection for multi-rate DS/CDMA, which makes full use of the nature of multi-rate signals, is still at its early stage. The thesis deals with the application of subspace-based techniques to blind channel estimation and multiuser detection for multi-rate DS/CDMA, including single-carrier and multicarrier scenarios. For the single-carrier case, space-time blind linear multiuser detection is investigated for synchronous dual-rate systems over the AWGN channel. The performance is evaluated analytically. The multi-rate generalization and the asynchronous extension are discussed. Two-stage space-time dual-rate blind detectors are also presented. Furthermore, blind adaptive channel estimation and detection schemes for asynchronous dual-rate systems over frequency-selective multipath channels are developed. In the context of multicarrier DS/CDMA, based on a finite-length truncation approximation on the band-limited chip waveform, blind timing acquisition and channel estimation scheme is proposed for multi-rate systems. The channel estimation error due to the finite-length chip waveform truncation is analyzed by exploiting a first-order perturbation approximation.
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Hsu, Yao-Shang, and 許堯勝. "Blind Channel Estimation for Zero-Padding Orthogonal Frequency Division Multiplexing Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/03182687591724833874.
Full textAbstract:
碩士國立交通大學
電機學院IC設計產業專班
97
In this thesis, we proposed a blind channel identification scheme for zero-padding orthogonal frequency division multiplexing systems with periodic modulating sequence. The proposed method uses the block system model and exploits the channel matrix when some zeros are padded into the source block signal. When block signal is received, we can use its autocorrelation matrix to compute the products of channel coefficient. The channel impulse response vector can be identified, up to a scalar ambiguity, by computing the eigenvector associated with the maximal eigenvalue of a Hermitian matrix, which is formed by the products of channel coefficient. To remove the scalar ambiguity, we design the training symbols which are inserted in the data blocks. To minimize the decrease of channel estimation accuracy caused by channel noise, we design the optimal periodic modulating sequence for zero-padding orthogonal frequency division multiplexing by observing the orthogonality between the noise subspace and the channel product coefficient subspace. After applying the optimal periodic modulating sequence to identify the channel impulse response, zero-forcing equalizer is used to recover the symbol. Comparing to the subspace method, the proposed method is simpler in computation. In the low SNR regime and less data blocks, the proposed method has better performance in channel estimation accuracy and lower symbol error rate.
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Kuo, Chien-Ming, and 郭建明. "Blind Channel Estimation for MC-CDMA Systems with Aperiodic Spreading Codes." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/98592018400284404294.
Full textAbstract:
碩士輔仁大學
電子工程學系
91
Multicarrier Code Division Multiple Access (MC-CDMA) System has the principal problems of Inter-Symbol Interference (ISI), Multi-user Interference (MUI) and Multi-path fading. The channel impulse response plays an important role in the estimate of the transmitted symbol. This paper develops the blind channel estimation for MC-CDMA system with aperiodic spreading codes. Due to the aperiodic spreading code, it makes the received signal time-varying effect and makes the channel estimation difficult. Liu solves this problem by finding the channel information matrix of the desired user, which uses the time-varying effect and second-order statistics of the time-domain received signal vector and despreading signal vector. In this thesis, we propose a lower complexity method to estimate channel only using the second-order statistics of despreading signal vector. But the proposed method achieves the lower mean square error of estimated channel. It is analyzed and showed that the channel information matrix is unbiased. The proposed method gets more efficient than that proposed by Liu [1] in the case of finite samples. Comparisons via computer simulations with Liu’s method show that the proposed method has small mean-square channel information error while requiring less computation.
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Chen, Yen-cheng, and 陳彥澄. "A Precoding Scheme for Semi-Blind Channel Estimation in Cooperative Networks." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/61339759156485161139.
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碩士國立中山大學
通訊工程研究所
100
In this thesis, we proposed a precoding scheme for semi-blind channel estimation in amplify-and-forward (AF) multipath two-way relay networks (TWRN), where two terminals exchange their information through multi-relays. The precoding scheme, which diminishes computational complexity of semi-blind channel estimator, is used to distinguish received signal at both terminals from multi-relays. By applying a non-redundant linear precoding scheme at multi-relays, we proposed a semi-blind channel estimation to estimate the channel impulse response (CIR) of direct link and the cascaded source-relay-terminal links. Firstly, semi-blind channel estimation adopts least-square (LS) estimation to find the CIR of direct link between both terminals using a smaller number of training symbols. Secondly, the CIR of the cascaded source-relay-terminal links are obtained through second-order statistics (SOS) of received signals at both terminals. Consequently, the proposed scheme can effectively reduce the computational complexity and enhance the spectral efficiency in overall system. Simulation results corroborate the effectiveness of the proposed scheme.
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Yang, Ju-Chin, and 楊如沁. "Performance Improvement of Semi-Blind Channel Estimation in MIMO-OFDM Systems." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/u29f92.
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碩士國立臺北科技大學
電腦與通訊研究所
100
In this thesis we mainly study the performance improvement of semi-blind channel estimation in MIMO-OFDM systems under the slow Rayleigh fading channel. Generally, the performance of the pilot-aided channel estimation method is better than that of the semi-blind channel estimation method. However, the semi-blind channel estimation method can effectively save the transmission bandwidth due to not using the pilot symbols in transmission data. A new semi-blind channel estimation method is proposed in this thesis. First, the interference to the data signal is reduced by using the superimposed generalized chirp-like (GCL) sequence. Then we use the least square (LS) method to estimate the initial value of the channel frequency response. Based on the previous step, the correct channel frequency response is obtained by repeatedly doing the estimation and the detection steps, which can effectively reduce the effect of noise and increase the accuracy of channel estimation. Experimental results show that considerably improved performance can be achieved in terms of bit error rate (BER), compared with the conventional semi-blind channel estimation method.
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Su, Borching. "Blind Channel Estimation Using Redundant Precoding: New Algorithms, Analysis, and Theory." Thesis, 2008. https://thesis.library.caltech.edu/913/1/thesis.pdf.
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Digital signal processing (DSP) techniques have played an important role in channel equalization and estimation in communication systems. While channel equalization and estimation are usually done by pilot-assisted methods in most systems, algorithms for blind channel estimation have also been largely studied due to high bandwidth efficiency. However, up to date, most blind methods possess disadvantages such as slow convergence speed, high complexity, poor performance, etc., compared to pilot-assisted methods. These drawbacks have made many consider blind methods as inapplicable in modern communication systems which feature fast-varying channels.
In this thesis, we consider the blind channel estimation problem in block transmission systems with linear redundant precoding (LRP) which have been widely adopted in modern communication systems in recent years. The main contribution of this thesis is to considerably reduce the amount of received data required for blind estimation and suggest blind methods which are applicable even in fast-varying environments (e.g., in wireless channels). New algorithms are proposed, performance analysis derived, and theoretical issues studied.
The first part of the thesis focuses on new algorithms for blind channel estimation and blind block synchronization in LRP systems. Two major types of linear redundant precoding, namely zero-padding (ZP) and cyclic prefixing (CP), are considered in this thesis. We first propose a generalized, subspace-based algorithm for blind channel estimation in ZP systems of which two previously reported algorithms are special cases. The generalization uses an integer parameter called {it repetition index} which represents the number of repeated uses of each received block. The number of received blocks required for subspace-based blind estimation is roughly inversely proportional to the repetition index. By choosing a larger repetition index, the amount of received data can be significantly reduced.
The concept of repetition index is also applied in blind channel estimation in CP systems, which are more widely used than ZP systems in many current communication standards such as orthogonal frequency division multiplexing (OFDM) systems. The use of repetition index in CP systems is much less obvious and conceptually more complicated than in ZP systems. By choosing a repetition index larger than unity, the number of received blocks needed for blind estimation is significantly reduced compared to all previously reported methods. Theoretically, the proposed method can perform blind estimation using only three received blocks in absence of noise. In practice, the number of received blocks needed to yield a satisfactory bit error rate performance is usually on the order of half the block size. The proposed algorithm can be directly applied in OFDM systems without any modification of transmitter structure. A semiblind algorithm for channel estimation in OFDM systems is also proposed based on the extension of the blind algorithm.
Another important problem, namely the blind block synchronization, is also studied. Most existing blind estimation methods in LRP systems assume the block boundaries of the received streams are perfectly known to the receiver, but this assumption is usually not true in practice since no extra known samples are transmitted. Two algorithms for blind block synchronization are proposed for ZP and CP systems, respectively. In particular, the block synchronization problem in CP systems is a broader version of the timing synchronization problem in the OFDM systems. The proposed algorithms exploit the concept of repetition index and both theoretical and simulation results suggest their advantages over all previously reported algorithms, especially when the amount of received data is limited.
The second part of the thesis deals with theoretical issues related to blind channel estimation. Performance analysis of the generalized blind channel estimation algorithm in ZP systems is first given and shows that the system performance in terms of channel estimation mean square error (MSE) is very close to the Cramer-Rao bound (CRB), even when only two received blocks are available. Another important theoretical problem, namely the signal richness preservation problem, is also studied. Signal richness is an essential property for input signals in subspace-based blind channel estimation algorithms studied in this thesis. This property, however, may be altered by a linear precoder. Necessary and sufficient conditions for a linear precoder to preserve signal richness are explored. Several relevant interesting mathematical problems are also studied.
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Tseng, Kia-Han, and 曾楷涵. "Blind Channel Estimation Performance Analysis in MIMO Cyclic Prefixed OFDM Systems." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/28566138990024264765.
Full textAbstract:
碩士國立臺灣大學
電信工程學研究所
102
In this thesis, we study blind channel estimation in multi-input, multioutput (MIMO) cyclic prefixed (CP) based orthogonal frequency division multiplexing (OFDM) system. Our main contributions are of theoretical aspects of this problem including a theoretical performance bound and performance analysis of the proposed method. The derived Cramer-Rao bound (CRB) for blind channel estimation bound is valid for arbitrary numbers of transmit antennas, received antennas, and received symbols available for blind channel estimation, and serve as a benchmark of performances for several recently reported subspace-based methods. Computer simulations are conducted to compare the performance of these methods with the derived bound. The results show that there are still rooms for improvement for the currently available blind channel estimation methods, especially in low signal-to-noise (SNR) region. Therefore, we improves the performance of a recently reported subspace-based blind channel method in low SNR region by turning the colored noise matrix into the white one. The theoretical performance analysis of our proposed method is also presented, which is based on the first order approximation in the small perturbation analysis.
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Tseng, Wei-lun, and 曾偉倫. "Blind Channel Estimation Based on Independent Component Analysis for Multicarrier Communications." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/19260082092618083857.
Full textAbstract:
碩士嶺東科技大學
資訊科技應用研究所
98
Abstract Multicarrier communication systems can keep the high speed transmission even in a wireless multipath fading channel. The frequency-selective fading channel in the time domain is converted into several narrowband subchannels in the frequency domain for multicarrier communication systems. With the narrowband of the subcarriers, the frequency-selective fading can be reduced to the limit, so that the signal associated with each subcarrier behaves like one with flat fading. Reliable channel estimation is indispensable for multicarrier communication systems employing coherent detection and adaptive loading in order to achieve high data rate communications. Recently, blind subspace-based channel estimation methods have received considerable attention for multicarrier communication systems with virtual carriers over white Gaussian noises. In this thesis, orthogonal frequency division multiplexing (OFDM) and multicarrier code division multiple access (MC-CDMA) systems are considered. However, no single subspace feature extraction method outperforms others under all circumstances, but applying a dual-space feature extraction method can overcome the limits of single subspace. A robust dual-space feature extraction is put forward based on principle component analysis (PCA) and independent component analysis (ICA) to increase the channel estimate accuracy. Especially, the proposed feature extraction always starts the procedure as a pure-PCA and ends as a pure-ICA. An efficient demixing procedure of complex-valued FastICA (c-FastICA) is presented here, which combines the PCA subspace demixing procedure exploiting individual noise-subspace projection and Newton’s iteration algorithm is utilized to extract the specific feature of the Gaussian noise component from mixtures so that the estimated component is as independent as possible to the other non-Gaussian signal components. Once the new noise basis vectors are obtained, which is as orthogonal as possible to the estimated noise basis vectors especially for highly correlated and impulse noises, the noise subspace can be reconstructed for the subspace-based estimation algorithm. And, this approach can resolve the problems of order ambiguity and identifiability of traditional ICA for the application of wireless communication. Comparison with the conventional PCA-based subspace methods is presented via computer simulations to support the effectiveness of the proposed method.
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Huang, Wei-Chieh, and 黃偉傑. "Semi-Blind Channel Estimation Using Superimposed Perfect Sequences for OFDM Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/59304995356374082640.
Full textAbstract:
碩士國立中山大學
通訊工程研究所
94
A complex array for constructing perfect sequences is presented in this paper. The row sequences and their discrete Fourier transform form two sets of perfect sequences. The column sequences are orthogonal to each other for any cyclic shift. In addition, any combination of the column sequences with complex weighting coefficients of equal amplitude is also a perfect sequence. In addition, a superimposed training scheme is also proposed for channel estimation in OFDM systems. The perfect sequence is adopted since it has a constant magnitude in both the time domain and the frequency domain. Although the derived channel estimator has a slightly worse performance since the unknown data contributes extra noise, the effective data throughput is substantially increased. In addition, the proposed scheme is shown to have a much better peak-to-average power ratio (PAPR) because the added perfect sequence has a constant magnitude in the time domain.
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Cheng, Yu-Yi. "Blind and Semi-Blind Channel Estimation and Receiver Diversity Techniques for Multi-User OFDM Transmission Systems." 2004. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-1407200417000900.
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