Blind Channel Identification and Equalization Using Cyclostationary And/or Higher Order Statistics PDF Download

Author: Ye Li
Publisher:
ISBN:
Category : Data transmission systems
Languages : en
Pages : 262

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Author: Kai He
Publisher:
ISBN:
Category :
Languages : en
Pages : 86

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Author: Zhi Ding
Publisher: CRC Press
ISBN: 9780824704797
Category : Technology & Engineering
Languages : en
Pages : 440

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Book Description
This text seeks to clarify various contradictory claims regarding capabilities and limitations of blind equalization. It highlights basic operating conditions and potential for malfunction. The authors also address concepts and principles of blind algorithms for single input multiple output (SIMO) systems and multi-user extensions of SIMO equalization and identification.

Author: Jing Liang
Publisher:
ISBN:
Category :
Languages : en
Pages : 356

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Book Description

Author: Zhi Ding
Publisher: CRC Press
ISBN: 1482270730
Category : Technology & Engineering
Languages : en
Pages : 418

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Book Description
This text seeks to clarify various contradictory claims regarding capabilities and limitations of blind equalization. It highlights basic operating conditions and potential for malfunction. The authors also address concepts and principles of blind algorithms for single input multiple output (SIMO) systems and multi-user extensions of SIMO equalization and identification.

Author: Chong-Yung Chi
Publisher: Springer Science & Business Media
ISBN: 1846282187
Category : Technology & Engineering
Languages : en
Pages : 479

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Book Description
The absence of training signals from many kinds of transmission necessitates the widespread use of blind equalization and system identification. There have been many algorithms developed for these purposes, working with one- or two-dimensional signals and with single-input single-output or multiple-input multiple-output, real or complex systems. It is now time for a unified treatment of this subject, pointing out the common characteristics of these algorithms as well as learning from their different perspectives. "Blind Equalization and System Identification" provides such a unified treatment presenting theory, performance analysis, simulation, implementation and applications. This is a textbook for graduate courses in discrete-time random processes, statistical signal processing, and blind equalization and system identification. It contains material which will also interest researchers and engineers working in digital communications, source separation, speech processing, and other, similar applications.

Author: Uma Gummadavelli
Publisher:
ISBN:
Category : Data transmission systems
Languages : en
Pages : 138

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Author: Asoke Kumar Nandi
Publisher: Springer Science & Business Media
ISBN: 1475729855
Category : Technology & Engineering
Languages : en
Pages : 290

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In the signal-processing research community, a great deal of progress in higher-order statistics (HOS) began in the mid-1980s. These last fifteen years have witnessed a large number of theoretical developments as well as real applications. Blind Estimation Using Higher-Order Statistics focuses on the blind estimation area and records some of the major developments in this field. Blind Estimation Using Higher-Order Statistics is a welcome addition to the few books on the subject of HOS and is the first major publication devoted to covering blind estimation using HOS. The book provides the reader with an introduction to HOS and goes on to illustrate its use in blind signal equalisation (which has many applications including (mobile) communications), blind system identification, and blind sources separation (a generic problem in signal processing with many applications including radar, sonar and communications). There is also a chapter devoted to robust cumulant estimation, an important problem where HOS results have been encouraging. Blind Estimation Using Higher-Order Statistics is an invaluable reference for researchers, professionals and graduate students working in signal processing and related areas.

Author: Antonio Napolitano
Publisher: Academic Press
ISBN: 0081027370
Category : Technology & Engineering
Languages : en
Pages : 626

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Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology. Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features. Presents the foundations and developments of the second- and higher-order theory of cyclostationary signals Performs signal analysis using both the classical stochastic process approach and the functional approach for time series Provides applications in signal detection and estimation, filtering, parameter estimation, source location, modulation format classification, and biological signal characterization Includes algorithms for cyclic spectral analysis along with Matlab/Octave code Provides generalizations of the classical cyclostationary model in order to account for relative motion between transmitter and receiver and describe irregular statistical cyclicity in the data

Author: Wen Pian Paul Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
One family of blind channel identification and equalization approaches has relied on the cyclostationary property of the communication signal induced at the receiver by fractional sampling. The disadvantages of them are that channels with uniformly-spaced zeros on a circle can not be identified and that they are extremely sensitive to channel order determination. Recently, transmitter-induced cyclostationarity approaches have been proposed and shown to relax the constraint on channel zero locations as well as the requirement of exact order determination. This thesis explores further on this idea and develops several algorithms based on such a scheme. First, a cepstrum-based method is developed and shown through simulations to be more robust to channel order overestimation than existing techniques. In the second part, the general precoding scheme for cyclostationarity induction is studied. Various results are presented for this scheme. Based on these results, several algorithms are developed and simulated to illustrate their effectiveness. Comparison among various schemes is also presented.