Relevant bibliographies by topics / Blind channel estimation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Blind channel estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Blind channel estimation"

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Baykal, B. "Blind Channel Estimation via Combining Autocorrelation and Blind Phase Estimation." IEEE Transactions on Circuits and Systems I: Regular Papers 51, no. 6 (June 2004): 1125–31. http://dx.doi.org/10.1109/tcsi.2004.829235.

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Elkassimi, Said, Said Safi, and B. Manaut. "Blind Channel Estimation and Equalization." International Journal of Multimedia and Ubiquitous Engineering 11, no. 12 (December 31, 2016): 191–206. http://dx.doi.org/10.14257/ijmue.2016.11.12.18.

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Althahab, Awwab Qasim Jumaah, and Sameer Abdul Kadhim Alrufaiaat. "A Comprehensive Review on Various Estimation Techniques for Multi Input Multi Output Channel." Journal of University of Babylon for Engineering Sciences 27, no. 1 (February 11, 2019): 262–74. http://dx.doi.org/10.29196/jubes.v27i1.1995.

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The problem of wireless channel estimation has been evolving due to some undesirable effects of channel physical properties on transmitted signals. At the receiver end, distortions, delays, attenuations, interferences, and phase shifts are the most issues encounter together with the received signals. In order to overcome channel effects and provide almost a perfect quality of data transmission, channel parameter estimation is needed. In Multiple Input-Multiple Output systems (MIMO), channel estimation is a more complicated step as compared with the Single Input-Single Output systems, SISO, because of the fact that the number of sub-channels that needs estimate is much greater than SISO systems. The fundamental objective of this research paper is to go over the famous and efficient algorithms that have been innovated to solve the problem of MIMO channel estimation in wireless communication systems. In this paper, these techniques have been classified into three groups: non-blind, semi-blind and blind estimation. For each group, a brief illustration is presented for familiar estimation algorithms. Finally, we compare between these techniques based on computational complexity, latency and estimation accuracy.
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Yatawatta, S., A. P. Petropulu, and R. Dattani. "Blind Channel Estimation Using Fractional Sampling." IEEE Transactions on Vehicular Technology 53, no. 2 (March 2004): 363–71. http://dx.doi.org/10.1109/tvt.2004.823551.

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Alireza Banani, Seyed, and Rodney G. Vaughan. "OFDM With Iterative Blind Channel Estimation." IEEE Transactions on Vehicular Technology 59, no. 9 (November 2010): 4298–308. http://dx.doi.org/10.1109/tvt.2010.2080295.

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Yih-Jyi Jeng and Chien-Chung Yeh. "Cluster-based blind nonlinear-channel estimation." IEEE Transactions on Signal Processing 45, no. 5 (May 1997): 1161–72. http://dx.doi.org/10.1109/78.575691.

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Xiaohua Li. "Blind sequence detection without channel estimation." IEEE Transactions on Signal Processing 50, no. 7 (July 2002): 1735–46. http://dx.doi.org/10.1109/tsp.2002.1011213.

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Peken, Ture, Garrett Vanhoy, and Tamal Bose. "Blind channel estimation for massive MIMO." Analog Integrated Circuits and Signal Processing 91, no. 2 (February 15, 2017): 257–66. http://dx.doi.org/10.1007/s10470-017-0943-1.

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Tami, Abdelkader, Mokhtar Keche, and Boubaker S. Bouazza. "New OSTBC for Blind Channel Estimation and Tracking in MIMO-OFDM Systems." Journal of Telecommunications and Information Technology 3 (September 30, 2019): 49–57. http://dx.doi.org/10.26636/jtit.2019.133819.

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Applying orthogonal space time block coding (OSTBC) to multiple-input multiple-output (MIMO) systems helps reduce receiver complexity. However, this approach has been applied only to flat fading channels, as when the channel is a frequency selective fading MIMO channel, OSTBC cannot be used directly since its orthogonal propriety may be lost. Furthermore, the MIMO channel is not always known. To deal with this problem, many techniques were proposed to estimate the channel using a training sequence. Unfortunately, these techniques reduce the useful spectral bandwidth. This paper proposes OSTBC for blind channel estimation and data detection in the case of a MIMO frequency selective channel. The aim of this new OSTBC is twofold: to solve the ambiguity of channel estimation and to reduce the complexity of the detector. By exploiting the well-known technique of orthogonal frequency division multiplexing (OFDM), the frequency selective fading MIMO channel is split into a set of flat fading subchannels. Moreover, to accommodate the fact that a MIMO channel can be time varying, the steady state Kalman channel estimator (SS-KCE) is extended to track the channel’s fast variations. The performance of the proposed blind algorithm is related by the adequate choice of the number of subcarriers and it is compared with other existing approaches by means of Monte Carlo simulations.
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Li, Cong Ying, Gao Ming Huang, Jun Gao, Gao Qi Dou, Chun Quan He, and Yu Song Gao. "Semi-Blind Channel Estimation with Orthogonal Superimposed Training for SISO over Doubly Selective Channel." Applied Mechanics and Materials 701-702 (December 2014): 1029–32. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.1029.

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In this paper, a semi-blind estimator based on orthogonal superimposed training (OST) for the case of doubly selecting fading channel is proposed. With the aid of OST, the interference to channel estimation form data symbols can be eliminated completely. Moreover, data symbols can serve as pseudo-pilots to enhance the estimation performance. Simulation results illustrate the benefits of pseudo-pilots method.
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Dissertations / Theses on the topic "Blind channel estimation"

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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 TECNOLÓGICO
O 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 o
Le 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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Books on the topic "Blind channel estimation"

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Jiang, Yufei, Xu Zhu, Eng Gee Lim, Yi Huang, and Hai Lin. Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24984-1.

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Lin, Hai, Xu Zhu, Yi Huang, Eng Gee Lim, and Yufei Jiang. Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization. Springer, 2015.

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Beres, Elzbieta. Blind channel estimation for orthogonal space-time block codes in MISO systems. 2004.

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Book chapters on the topic "Blind channel estimation"

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Park, Hyung-Min, Sang-Hoon Oh, and Soo-Young Lee. "Blind Equalization Using Direct Channel Estimation." In Independent Component Analysis and Blind Signal Separation, 562–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30110-3_72.

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Ahossi, Agbeti Bricos, Ahmed Dooguy Kora, and Roger Marcelin Faye. "Geometric Approach of Blind Channel Estimation." In Innovation and Interdisciplinary Solutions for Underserved Areas, 234–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72965-7_22.

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Tian, Jinfeng, Ting Zhou, Tianheng Xu, Honglin Hu, and Mingqi Li. "Blind Channel Estimation of Doubly Selective Fading Channels." In Communications and Networking, 665–74. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06161-6_65.

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Kammeyer, Karl-Dirk, Thorsten Petermann, and Sven Vogeler. "Iterative Blind Channel Estimation for OFDM Receivers." In Multi-Carrier Spread-Spectrum & Related Topics, 283–92. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3569-7_31.

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Rahim, Abdur, Nemai Chandra Karmakar, and Kazi M. Ahmed. "Blind Channel Estimation in MIMO for MC-CDMA." In Handbook of Smart Antennas for RFID Systems, 539–69. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470872178.ch21.

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Hu, Feng, Jianping Li, and Chaoshi Cai. "Semi-blind MIMO Channel Estimation with Orthogonal Inputs,." In Future Control and Automation, 309–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31006-5_37.

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Chen, Wei, and Wei-le Zhu. "A New Blind Channel Estimation in OFDM Systems." In Recent Advances in Computer Science and Information Engineering, 129–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25769-8_19.

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Prasad, Rajkishore, Hiroshi Saruwatari, and Kiyohiro Shikano. "Single Channel Speech Enhancement: MAP Estimation Using GGD Prior Under Blind Setup." In Independent Component Analysis and Blind Signal Separation, 873–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30110-3_110.

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Xiao-qiang, Zhong. "Blind Channel Estimation of Relaying Cooperative Communication in IoT Systems." In Advances in Intelligent and Soft Computing, 85–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27957-7_11.

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Sarperi, Luciano, Asoke K. Nandi, and Xu Zhu. "Multiuser Detection and Channel Estimation in MIMO OFDM Systems via Blind Source Separation." In Independent Component Analysis and Blind Signal Separation, 1189–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30110-3_150.

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Conference papers on the topic "Blind channel estimation"

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Ozdemir, O., and M. Torlak. "Blind channel estimation without eigendecomposition." In 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577). IEEE, 2004. http://dx.doi.org/10.1109/icc.2004.1313006.

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Wei Kang and B. Champagne. "Generalized blind subspace channel estimation." In 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484). IEEE, 2003. http://dx.doi.org/10.1109/vetecf.2003.1285214.

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Chen, S. "Joint channel estimation and data detection using a blind Bayesian decision feedback equaliser." In IEE Colloquium on `Blind Deconvolution - Algorithms and Applications'. IEE, 1995. http://dx.doi.org/10.1049/ic:19950899.

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Awan, Muhammad Kaleem, Muhammad Faisal Aftab, and Zeeshan. "Channel Order Estimation in Cyclostationarity Based Blind Channel Equalization." In 2005 Pakistan Section Multitopic Conference. IEEE, 2005. http://dx.doi.org/10.1109/inmic.2005.334478.

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Ma, Hualong, Xiande Wang, Yunjun Lu, and Lai Tian. "UWB channel blind estimation method based on channel shortening." In 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC). IEEE, 2017. http://dx.doi.org/10.1109/icsgsc.2017.8038596.

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Yang, Feng, Lin Gui, and Lingna Hu. "Semi-Blind Channel Estimation in OFDM System." In 2007 International Conference on Wireless Communications, Networking and Mobile Computing. IEEE, 2007. http://dx.doi.org/10.1109/wicom.2007.122.

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Boloix-Tortosa, Rafael, Franciso J. Simois-Tirado, and Juan Jose Murillo-Fuentes. "Blind adaptive channel estimation for OFDM systems." In 2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2009. http://dx.doi.org/10.1109/spawc.2009.5161773.

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Zhang, Y. H., W. S. Lu, and T. A. Gulliver. "Blind Polynomial Channel Estimation for OFDM Systems." In 2008 IEEE 68th Vehicular Technology Conference (VTC 2008-Fall). IEEE, 2008. http://dx.doi.org/10.1109/vetecf.2008.154.

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Wang, Xin, and Xuelan Zou. "Blind Channel Estimation with Fewer Data Received." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.508.

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Dean, Thomas, Mary Wootters, and Andrea Goldsmith. "Blind Joint MIMO Channel Estimation and Decoding." In 2017 IEEE Global Communications Conference (GLOBECOM 2017). IEEE, 2017. http://dx.doi.org/10.1109/glocom.2017.8254157.

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