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From this book, you will learn new concepts, methods, and algorithms for performing signal processing tasks and designing and analyzing communications systems.
Book Synopsis Cyclostationarity in Communications and Signal Processing by : William A. Gardner
Download or read book Cyclostationarity in Communications and Signal Processing written by William A. Gardner and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1994 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: From this book, you will learn new concepts, methods, and algorithms for performing signal processing tasks and designing and analyzing communications systems.
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
Book Synopsis Cyclostationary Processes and Time Series by : Antonio Napolitano
Download or read book Cyclostationary Processes and Time Series written by Antonio Napolitano and published by Academic Press. This book was released on 2019-10-24 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
Book Synopsis Generalizations of Cyclostationary Signal Processing by : Antonio Napolitano
Download or read book Generalizations of Cyclostationary Signal Processing written by Antonio Napolitano and published by John Wiley & Sons. This book was released on 2012-12-07 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
Book Synopsis Cyclostationary Signal Processing for Communication Systems by : Veluppillai Balakrishnar Manimohan
Download or read book Cyclostationary Signal Processing for Communication Systems written by Veluppillai Balakrishnar Manimohan and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
The growing interest in smart grid applications has drawn considerable attention to power line communications (PLC) as a central communications medium for smart grids. Specifically, network control and grid applications are allocated the frequency band of 0 − 500 kHz, commonly referred to as the narrowband PLC channel. As this frequency band is characterized by strong cyclostationary noise, multipath signal propagation, and periodically time varying channel conditions, narrowband PLC channels fall into the class of periodic channels with finite memory. In this dissertation we study communications over periodic channels with finite memory, utilizing the theory of cyclostationary processes to address two major aspects: information-theoretic performance bounds, and practical algorithms for realizing the predicted performance gains. In the first part of the dissertation, we study the fundamental rate limits of periodic channels with finite memory, focusing on the capacity of point-to-point (PtP) periodic channels, i.e., without security constraints, as well as the secrecy capacity of periodic wiretap channels, i.e., with security constraints. By proving a bijection between PtP periodic channels and time-invariant multiple input-multiple output (MIMO) channels with finite memory, we characterize the capacity of periodic channels via the capacity of the equivalent time-invariant MIMO channels. As part of the capacity derivation, we characterize the capacity achieving transmission scheme, which leads to a practical code construction that approaches capacity. Motivated by the bijection between periodic channels and time-invariant MIMO channels with finite memory, we study the secrecy capacity of time-invariant Gaussian MIMO channels with finite memory. Although the time-invariant Gaussian MIMO channel with finite memory is a very common channel model in wireless communications, as well as in wireline communications, this is the first time that the secrecy capacity has been characterized for this channel model. As the resulting secrecy capacity expression is given by a non-convex optimization problem, we derive a simple necessary and sufficient condition for positive secrecy capacity, and obtain an explicit expression for the secrecy capacity in the scalar case. Then, we show how our result directly leads to the secrecy capacity of periodic channels. In the second part of the dissertation, we study practical algorithms which utilize the theory of cyclostationarity to approach the predicted performance gains in periodic channels. First, we propose a receiver algorithm for the recovery of orthogonal frequency division multiplexing (OFDM) modulated signals in periodic channels. The proposed receiver uses frequency-shift filtering to exploit the cyclostationary properties of both the additive channel noise and the information signal. We explicitly derive the coefficients of the filter which minimize the time-averaged mean-squared error (TA-MSE), and propose an adaptive implementation, which is based on the recursive least-squares (RLS) algorithm. Numerical simulations show that the proposed receiver demonstrates a substantial performance gain over previously proposed receivers. Finally, motivated by the fact that most adaptive algorithms, such as the least mean-squares (LMS) and the RLS, are designed for stationary signals, we rigorously study the optimal adaptive filtering of cyclostationary signals. We first identify the relevant objective as the TA-MSE, and obtain an adaptive algorithm, which we refer to as time-averaged LMS (TA-LMS), as the stochastic approximation of the TA-MSE minimizer. We provide a comprehensive transient and steady-state performance analysis, and derive conditions for convergence and stability, which are shown to accurately characterize the performance of the adaptive algorithm in a simulation study.-- abstract.
Book Synopsis Cyclostationary Signal Processing for Narrowband Power Line Communications by : Nir Shlezinger
Download or read book Cyclostationary Signal Processing for Narrowband Power Line Communications written by Nir Shlezinger and published by . This book was released on 2017 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing interest in smart grid applications has drawn considerable attention to power line communications (PLC) as a central communications medium for smart grids. Specifically, network control and grid applications are allocated the frequency band of 0 − 500 kHz, commonly referred to as the narrowband PLC channel. As this frequency band is characterized by strong cyclostationary noise, multipath signal propagation, and periodically time varying channel conditions, narrowband PLC channels fall into the class of periodic channels with finite memory. In this dissertation we study communications over periodic channels with finite memory, utilizing the theory of cyclostationary processes to address two major aspects: information-theoretic performance bounds, and practical algorithms for realizing the predicted performance gains. In the first part of the dissertation, we study the fundamental rate limits of periodic channels with finite memory, focusing on the capacity of point-to-point (PtP) periodic channels, i.e., without security constraints, as well as the secrecy capacity of periodic wiretap channels, i.e., with security constraints. By proving a bijection between PtP periodic channels and time-invariant multiple input-multiple output (MIMO) channels with finite memory, we characterize the capacity of periodic channels via the capacity of the equivalent time-invariant MIMO channels. As part of the capacity derivation, we characterize the capacity achieving transmission scheme, which leads to a practical code construction that approaches capacity. Motivated by the bijection between periodic channels and time-invariant MIMO channels with finite memory, we study the secrecy capacity of time-invariant Gaussian MIMO channels with finite memory. Although the time-invariant Gaussian MIMO channel with finite memory is a very common channel model in wireless communications, as well as in wireline communications, this is the first time that the secrecy capacity has been characterized for this channel model. As the resulting secrecy capacity expression is given by a non-convex optimization problem, we derive a simple necessary and sufficient condition for positive secrecy capacity, and obtain an explicit expression for the secrecy capacity in the scalar case. Then, we show how our result directly leads to the secrecy capacity of periodic channels. In the second part of the dissertation, we study practical algorithms which utilize the theory of cyclostationarity to approach the predicted performance gains in periodic channels. First, we propose a receiver algorithm for the recovery of orthogonal frequency division multiplexing (OFDM) modulated signals in periodic channels. The proposed receiver uses frequency-shift filtering to exploit the cyclostationary properties of both the additive channel noise and the information signal. We explicitly derive the coefficients of the filter which minimize the time-averaged mean-squared error (TA-MSE), and propose an adaptive implementation, which is based on the recursive least-squares (RLS) algorithm. Numerical simulations show that the proposed receiver demonstrates a substantial performance gain over previously proposed receivers. Finally, motivated by the fact that most adaptive algorithms, such as the least mean-squares (LMS) and the RLS, are designed for stationary signals, we rigorously study the optimal adaptive filtering of cyclostationary signals. We first identify the relevant objective as the TA-MSE, and obtain an adaptive algorithm, which we refer to as time-averaged LMS (TA-LMS), as the stochastic approximation of the TA-MSE minimizer. We provide a comprehensive transient and steady-state performance analysis, and derive conditions for convergence and stability, which are shown to accurately characterize the performance of the adaptive algorithm in a simulation study.-- abstract.
Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are often a poor representation of the underlying physics. This book deals with improper and noncircular complex signals, which do not conform to classical assumptions, and it demonstrates how correct treatment of these signals can have significant payoffs. The book begins with detailed coverage of the fundamental theory and presents a variety of tools and algorithms for dealing with improper and noncircular signals. It provides a comprehensive account of the main applications, covering detection, estimation, and signal analysis of stationary, nonstationary, and cyclostationary processes. Providing a systematic development from the origin of complex signals to their probabilistic description makes the theory accessible to newcomers. This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.
Book Synopsis Statistical Signal Processing of Complex-Valued Data by : Peter J. Schreier
Download or read book Statistical Signal Processing of Complex-Valued Data written by Peter J. Schreier and published by Cambridge University Press. This book was released on 2010-02-04 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are often a poor representation of the underlying physics. This book deals with improper and noncircular complex signals, which do not conform to classical assumptions, and it demonstrates how correct treatment of these signals can have significant payoffs. The book begins with detailed coverage of the fundamental theory and presents a variety of tools and algorithms for dealing with improper and noncircular signals. It provides a comprehensive account of the main applications, covering detection, estimation, and signal analysis of stationary, nonstationary, and cyclostationary processes. Providing a systematic development from the origin of complex signals to their probabilistic description makes the theory accessible to newcomers. This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.
Our focus in this ARO research project is to investigate and study the application of cyclostationary signal processing in digital communication systems. We consider several important areas of application including channel equalization, co-channel interference rejection, and antenna beamforming. During this report period, we developed a number of new algorithm for the blind identification and equalization of multiple input multiple output systems. These methods are more robust and accurate than many existing methods. Blind separation of signals using both the higher order and second order (cyclostationary) statistics are studied. Several simple methods are proposed. We also developed a finite window decorrelator receiver for asynchronous CDMA systems. This new algorithm is near far resistant even when the processing window is rather short, overcoming the weakness of the conventional decorrelator that relies on large (almost infinite) window size. In another important study, we investigate the applicability of blind equalization algorithms in practical wireless cellular systems such as the GSM. Since the GSM transmission is nonlinear and is in burst mode, blind equalization algorithms must be adopted for this nonlinear modulation and must converge within each frame of data burst. Using a linearization method, we simplied the nonlinear GMSK signal into an equivalent linear QAM signal. A de-rotation scheme further allowed channel diversity be extracted without the need of additional downlink antennae. Successful blind equalization and semi-blind equalization results for GSM are established.
Book Synopsis Cyclostationary Signal Processing in Digital Communication Systems by :
Download or read book Cyclostationary Signal Processing in Digital Communication Systems written by and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our focus in this ARO research project is to investigate and study the application of cyclostationary signal processing in digital communication systems. We consider several important areas of application including channel equalization, co-channel interference rejection, and antenna beamforming. During this report period, we developed a number of new algorithm for the blind identification and equalization of multiple input multiple output systems. These methods are more robust and accurate than many existing methods. Blind separation of signals using both the higher order and second order (cyclostationary) statistics are studied. Several simple methods are proposed. We also developed a finite window decorrelator receiver for asynchronous CDMA systems. This new algorithm is near far resistant even when the processing window is rather short, overcoming the weakness of the conventional decorrelator that relies on large (almost infinite) window size. In another important study, we investigate the applicability of blind equalization algorithms in practical wireless cellular systems such as the GSM. Since the GSM transmission is nonlinear and is in burst mode, blind equalization algorithms must be adopted for this nonlinear modulation and must converge within each frame of data burst. Using a linearization method, we simplied the nonlinear GMSK signal into an equivalent linear QAM signal. A de-rotation scheme further allowed channel diversity be extracted without the need of additional downlink antennae. Successful blind equalization and semi-blind equalization results for GSM are established.
This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.
Book Synopsis Foundations of Signal Processing by : Martin Vetterli
Download or read book Foundations of Signal Processing written by Martin Vetterli and published by Cambridge University Press. This book was released on 2014-09-04 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.
In the last decade the research in signal analysis was dominated by models that encompass nonstationarity as an important feature. This book presents the results of a workshop held in Grodek—Poland in February 2013 which was dedicated to the investigation of cyclostationary signals. Its main objective is to highlight the strong interactions between theory and applications of cyclostationary signals with the use of modern statistical tools. An important application of cyclostationary signals is the analysis of mechanical signals generated by a vibrating mechanism. Cyclostationary models are very important to perform basic operations on signals in both time and frequency domains. One of the fundamental problems in diagnosis of rotating machine is the identification of significant modulating frequencies that contribute to the cyclostationary nature of the signals. The book shows that there are modern tools available for analyzing cyclostationary signals without the assumption of gaussianity. Those methods are based on the ideas of bootstrap, subsampling and Fraction-of-time (FOT) models. The book is organised in two parts. The first part will be dedicated to pure theory on cyclostationarity. Applications are presented in the second part including several mechanical systems such as bearings, gears, with or without damages.
Book Synopsis Cyclostationarity: Theory and Methods by : Fakher Chaari
Download or read book Cyclostationarity: Theory and Methods written by Fakher Chaari and published by Springer Science & Business Media. This book was released on 2014-01-16 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade the research in signal analysis was dominated by models that encompass nonstationarity as an important feature. This book presents the results of a workshop held in Grodek—Poland in February 2013 which was dedicated to the investigation of cyclostationary signals. Its main objective is to highlight the strong interactions between theory and applications of cyclostationary signals with the use of modern statistical tools. An important application of cyclostationary signals is the analysis of mechanical signals generated by a vibrating mechanism. Cyclostationary models are very important to perform basic operations on signals in both time and frequency domains. One of the fundamental problems in diagnosis of rotating machine is the identification of significant modulating frequencies that contribute to the cyclostationary nature of the signals. The book shows that there are modern tools available for analyzing cyclostationary signals without the assumption of gaussianity. Those methods are based on the ideas of bootstrap, subsampling and Fraction-of-time (FOT) models. The book is organised in two parts. The first part will be dedicated to pure theory on cyclostationarity. Applications are presented in the second part including several mechanical systems such as bearings, gears, with or without damages.
This is volume 1 of a 2 volume set. This volume focuses on "channel estimation and equalization."
Book Synopsis Signal Processing Advances in Wireless and Mobile Communications: Trends in channel estimation and equalization by : Yingbo Hua
Download or read book Signal Processing Advances in Wireless and Mobile Communications: Trends in channel estimation and equalization written by Yingbo Hua and published by Prentice Hall. This book was released on 2001 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is volume 1 of a 2 volume set. This volume focuses on "channel estimation and equalization."
