Download or read book The Expectation maximization Viterbi Algorithm for Blind Channel Identification and Equalization written by Hoang Nguyen and published by . This book was released on 2003 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Principles of Signal Detection and Parameter Estimation written by Bernard C. Levy and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and current understanding of signal detection and estimation, including problems and solutions for each chapter. Signal detection plays an important role in fields such as radar, sonar, digital communications, image processing, and failure detection. The book explores both Gaussian detection and detection of Markov chains, presenting a unified treatment of coding and modulation topics. Addresses asymptotic of tests with the theory of large deviations, and robust detection. This text is appropriate for students of Electrical Engineering in graduate courses in Signal Detection and Estimation.

Download or read book Wireless Communications written by Giorgio A. Vitetta and published by John Wiley & Sons. This book was released on 2013-03-29 with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated. Comprehensive wireless specific guide to algorithmic techniques Provides a detailed analysis of channel equalization and channel coding for wireless applications Unique conceptual approach focusing in single user systems Covers algebraic decoding, modulation techniques, channel coding and channel equalisation

Download or read book Conference Record written by and published by . This book was released on 2001 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Adaptive and Iterative Signal Processing in Communications written by Jinho Choi and published by Cambridge University Press. This book was released on 2006-11-16 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2006 book describes the fundamental theory and practical aspects of using ASP, and ISP, to improve receiver performance.

Download or read book Self correcting Multi channel Bussgang Blind Deconvolution Using Expectation Maximization EM Algorithm and Feedback written by Sze Ho Tang and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A Bussgang based blind deconvolution algorithm called self-correcting multi-channel Bussgang (SCMB) blind deconvolution algorithm was proposed. Unlike the original Bussgang blind deconvolution algorithm where the probability density function (pdf) of the signal being recovered is assumed to be completely known, the proposed SCMB blind deconvolution algorithm relaxes this restriction by parameterized the pdf with a Gaussian mixture model and expectation maximization (EM) algorithm, an iterative maximum likelihood approach, is employed to estimate the parameter side by side with the estimation of the equalization filters of the original Bussgang blind deconvolution algorithm. A feedback loop is also designed to compensate the effect of the parameter estimation error on the estimation of the equalization filters. Application of the SCMB blind deconvolution framework for binary image restoration, multi-pass synthetic aperture radar (SAR) autofocus and inverse synthetic aperture radar (ISAR) autofocus are exploited with great results.

Download or read book SUPERCOMM ICC 92 written by and published by . This book was released on 1992 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Blind Channel Identification and Equalization Using Cyclostationary And or Higher Order Statistics written by Ye Li and published by . This book was released on 1994 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Conference Record of the Thirty Seventh Asilomar Conference on Signals Systems Computers November 9 12 2003 Pacific Grove California written by Michael B. Matthews and published by . This book was released on 2003 with total page 1104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Blind Channel Identification Using Higher Order Statistics written by Jing Liang and published by . This book was released on 2002 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Communications fusing Command Control and Intelligence written by and published by . This book was released on 1992 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Journal of Communications and Networks written by and published by . This book was released on 2004 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Simultaneous Data Detection and Channel Estimation with the Viterbi Algorithm written by and published by . This book was released on 1993 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Wireless Communications Over Rapidly Time Varying Channels written by Franz Hlawatsch and published by Academic Press. This book was released on 2011-05-04 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a result of higher frequencies and increased user mobility, researchers and systems designers are shifting their focus from time-invariant models to channels that vary within a block. Wireless Communications Over Rapidly Time-Varying Channels explains the latest theoretical advances and practical methods to give an understanding of rapidly time varying channels, together with performance trade-offs and potential performance gains, providing the expertise to develop future wireless systems technology. As well as an overview of the issues of developing wireless systems using time-varying channels, the book gives extensive coverage to methods for estimating and equalizing rapidly time-varying channels, including a discussion of training data optimization, as well as providing models and transceiver methods for time-varying ultra-wideband channels. An introduction to time-varying channel models gives in a nutshell the important issues of developing wireless systems technology using time-varying channels Extensive coverage of methods for estimating and equalizing rapidly time-varying channels, including a discussion of training data optimization, enables development of high performance wireless systems Chapters on transceiver design for OFDM and receiver algorithms for MIMO communication channels over time-varying channels, with an emphasis on modern iterative turbo-style architectures, demonstrates how these important technologies can optimize future wireless systems

Download or read book Blind Channel Identification of QAM Signals Via Fixed Stochastic Gradient Estimation written by Edmund Li and published by . This book was released on 2000 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Adaptive Signal Processing written by Simon S. Haykin and published by . This book was released on 1991 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Batch Algorithms for Blind Channel Equalization and Blind Channel Shortening Using Convex Optimization written by Dung Huy Han and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present novel batch algorithms to tackle the multi-path fading effect of the wireless channels using convex optimization tools. We consider two major problems: channel equalization and channel shortening. Blind channel equalization has been widely investigated in the past decade. Blind algorithms are preferred because of their ability to equalize the channel without spending extra bandwidth. Existing works have proposed various blind channel equalization costs and characterized their convergence. Most of the blind signal recovery algorithms are implemented as stochastic gradient descent based adaptive schemes making them attractive to applications where the channel is slow varying. However, existing solutions for blind channel equalization often suffer from slow convergence and require long data samples. On the other hand, packet based data transmission in many practical digital communication systems makes it attractive to develop steepest descent implementation in order to speed up convergence. We focus on developing steepest decent implementation of several well-known blind signal recovery algorithms for multi-channel equalization and source separation. Our steepest descent formulation is more amenable to additional parametric and signal subspace constraints for faster convergence and superior performance. Most of the well-known blind channel equalization algorithms are based on higher-order statistics making the corresponding cost non-linear non-convex functions of the equalizer parameters. Therefore, the steepest descent implementations often converge to local optima. We develop batch algorithms that use modern optimization tools so that the global optima can be found in polynomial time. We convert our blind costs of interest into fourth-order functions and apply a semi-definite formulation to convert them into convex optimization problems so that they can be solved globally. Our algorithms work well not only for removing multipath fading effect in channel equalization problem but also for mitigating inter-channel interference in source separation problem. Nevertheless, in practical communication systems, pilot symbols are inserted to the packet for various purposes including channel estimation and equalization. Hence, the use of the pilot in conjunction with blind algorithms is more preferred. We investigate simple and practical means for performance enhancement for equalizing wireless packet transmission bursts that rely on short sequence as equalization pilots. Utilizing both the pilot symbols and additional statistical and constellation information about user data symbols, we develop efficient means for improving the performance of linear channel equalizers. We present two convex optimization algorithms that are both effective in performance enhancement and can be solved efficiently. We also propose a fourth-order training based cost so that it can be combined with other fourth-order blind costs and be solved efficiently using semi-definite programming. The simulation results show that with the help of very few pilots, the equalization can be done under very short packet length. Many modern communication systems adopt multicarrier modulation for optimum utilization of multi-path fading channel. Under this scenario, a cyclic prefix which is not shorter than the channel length is added to enable equalization. We study the problem of channel shortening in multicarrier modulation systems when this assumption is not met. We reformulate two existing second-order statistic based methods into semidefinite programming to overcome their shortcoming of local convergence. Our batch processor is superior to the conventional stochastic gradient algorithms in terms of achievable bit rate and signal to interference and noise ratio (SINR). Addressing the shortcoming of second-order statistic based costs, we propose a new criterion for blind channel shortening based on high order statistical information. The optimization criterion can be achieved through either a gradient descent algorithm or a batch algorithm using the aforementioned convex optimization for global convergence.