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digital signal processing for wireless communication using matlab: Introduction to Digital Signal Processing Using MATLAB with Application to Digital Communications K.S. Thyagarajan, 2018-05-28 This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego. |
digital signal processing for wireless communication using matlab: Digital Signal Processing for Wireless Communication using Matlab E.S. Gopi, 2015-08-21 This book examines signal processing techniques used in wireless communication illustrated by using the Matlab program. The author discusses these techniques as they relate to Doppler spread, Delay spread, Rayleigh and Rician channel modeling, rake receiver, diversity techniques, MIMO and OFDM based transmission techniques, and array signal processing. Related topics such as detection theory, Link budget, Multiple access techniques, spread spectrum, are also covered. • Illustrates signal processing techniques involved in wireless communication • Discusses multiple access techniques such as Frequency division multiple access, Time division multiple access, and Code division multiple access • Covers band pass modulation techniques such as Binary phase shift keying, Differential phase shift keying, Quadrature phase shift keying, Binary frequency shift keying, Minimum shift keying, and Gaussian minimum shift keying. |
digital signal processing for wireless communication using matlab: Digital Signal Processing for Wireless Communication Using Matlab E.S. Gopi, 2021 The updated book presents Matlab illustrations on various digital signal processing (DSP) techniques such as random process, time varying wireless system model, and detection and estimation theory used in wireless communication. The book also covers recent wireless techniques like OFDM, massive MIMO techniques, non-orthogonal multiple access, millimeter wave MIMO, full duplex, cognitive radio, co-operating communication, unmanned aerial vehicles etc. This book is suitable for those who are doing basic and applied research in digital signal processing for wireless communication. Presents a updated guide to signal processing techniques involved in wireless communication; Discusses multiple access techniques such as random process, time varying wireless system model and estimation theory; Ideal for those doing basic and applied research in digital signal processing for wireless communication. |
digital signal processing for wireless communication using matlab: Digital Signal Processing for Wireless Communication using Matlab E.S. Gopi, 2021-10-21 The updated book presents Matlab illustrations on various digital signal processing (DSP) techniques such as random process, time varying wireless system model, and detection and estimation theory used in wireless communication. The book also covers recent wireless techniques like OFDM, massive MIMO techniques, non-orthogonal multiple access, millimeter wave MIMO, full duplex, cognitive radio, co-operating communication, unmanned aerial vehicles etc. This book is suitable for those who are doing basic and applied research in digital signal processing for wireless communication. |
digital signal processing for wireless communication using matlab: Signals, Systems, Transforms, and Digital Signal Processing with MATLAB Michael Corinthios, 2018-09-03 Signals, Systems, Transforms, and Digital Signal Processing with MATLAB® has as its principal objective simplification without compromise of rigor. Graphics, called by the author, the language of scientists and engineers, physical interpretation of subtle mathematical concepts, and a gradual transition from basic to more advanced topics are meant to be among the important contributions of this book. After illustrating the analysis of a function through a step-by-step addition of harmonics, the book deals with Fourier and Laplace transforms. It then covers discrete time signals and systems, the z-transform, continuous- and discrete-time filters, active and passive filters, lattice filters, and continuous- and discrete-time state space models. The author goes on to discuss the Fourier transform of sequences, the discrete Fourier transform, and the fast Fourier transform, followed by Fourier-, Laplace, and z-related transforms, including Walsh–Hadamard, generalized Walsh, Hilbert, discrete cosine, Hartley, Hankel, Mellin, fractional Fourier, and wavelet. He also surveys the architecture and design of digital signal processors, computer architecture, logic design of sequential circuits, and random signals. He concludes with simplifying and demystifying the vital subject of distribution theory. Drawing on much of the author’s own research work, this book expands the domains of existence of the most important transforms and thus opens the door to a new world of applications using novel, powerful mathematical tools. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Using MATLAB Vinay K. Ingle, John G. Proakis, 2007 This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB® in the study of DSP concepts. In this book, MATLAB® is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB® makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated second edition includes new homework problems and revises the scripts in the book, available functions, and m-files to MATLAB® V7. |
digital signal processing for wireless communication using matlab: Wireless Communication Systems in Matlab Mathuranathan Viswanathan, 2020-06-08 * A learner-friendly, practical and example driven book, Wireless Communication Systems in Matlab gives you a solid background in building simulation models for wireless systems in Matlab. This book, an essential guide for understanding the basic implementation aspects of a wireless system, shows how to simulate and model such a system from scratch. The implemented simulation models shown in this book, provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a wireless communication system. It presents the following key topics with the required theoretical background, along with the implementation details in the form of Matlab scripts. * Random variables for simulating probabilistic systems and applications like Jakes filter design and colored noise generation. * Models for Shannon's channel capacity, unconstrained awgn channel, binary symmetric channel (BSC), binary erasure channel (BEC), constellation constrained capacities and ergodic capacity over fading channel. The theory of linear block codes, decoding techniques using soft-decisions and hard-decisions, and their performance simulations. * Monte Carlo simulation for ascertaining performance of digital modulation techniques in AWGN and fading channels - Eb/N0 Vs BER curves. Pulse shaping techniques, matched filtering and partial response signaling, Design and implementation of linear equalizers - zero forcing and MMSE equalizers, using them in a communication link and modulation systems with receiver impairments. * Large-scale propagation models like Friis free space model, log distance model, two ray ground reflection model, single knife-edge diffraction model, Hata Okumura model. * Essentials of small-scale propagation models for wireless channels, such as, power delay profile, Doppler power spectrum, Rayleigh and Rice processes. Modeling flat fading and frequency selective channels. * Diversity techniques for multiple antenna systems: Alamouti space-time coding, maximum ratio combining, equal gain combining and selection combining. * Simulation models for direct sequence spread spectrum, frequency hopping spread spectrum and OFDM. |
digital signal processing for wireless communication using matlab: Digital Signal Processing K. Deergha Rao, M.N.S. Swamy, 2018-04-14 The book provides a comprehensive exposition of all major topics in digital signal processing (DSP). With numerous illustrative examples for easy understanding of the topics, it also includes MATLAB-based examples with codes in order to encourage the readers to become more confident of the fundamentals and to gain insights into DSP. Further, it presents real-world signal processing design problems using MATLAB and programmable DSP processors. In addition to problems that require analytical solutions, it discusses problems that require solutions using MATLAB at the end of each chapter. Divided into 13 chapters, it addresses many emerging topics, which are not typically found in advanced texts on DSP. It includes a chapter on adaptive digital filters used in the signal processing problems for faster acceptable results in the presence of changing environments and changing system requirements. Moreover, it offers an overview of wavelets, enabling readers to easily understand the basics and applications of this powerful mathematical tool for signal and image processing. The final chapter explores DSP processors, which is an area of growing interest for researchers. A valuable resource for undergraduate and graduate students, it can also be used for self-study by researchers, practicing engineers and scientists in electronics, communications, and computer engineering as well as for teaching one- to two-semester courses. |
digital signal processing for wireless communication using matlab: Digital Speech Processing Using Matlab E. S. Gopi, 2013-12-03 Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Using MATLAB Vinay K. Ingle, John G. Proakis, 2012 |
digital signal processing for wireless communication using matlab: Digital Signal Processing for Medical Imaging Using Matlab E.S. Gopi, 2012-09-13 This book describes medical imaging systems, such as X-ray, Computed tomography, MRI, etc. from the point of view of digital signal processing. Readers will see techniques applied to medical imaging such as Radon transformation, image reconstruction, image rendering, image enhancement and restoration, and more. This book also outlines the physics behind medical imaging required to understand the techniques being described. The presentation is designed to be accessible to beginners who are doing research in DSP for medical imaging. Matlab programs and illustrations are used wherever possible to reinforce the concepts being discussed. |
digital signal processing for wireless communication using matlab: Digital Communications and Signal Processing (Second Edition) Ke Vāsudēvan, 2010 |
digital signal processing for wireless communication using matlab: Digital Signal Processing in Modern Communication Systems (Edition 2) Andreas Schwarzinger, 2022-01-13 The second edition of Digital Signal Processing in Modern Communication Systems (www.signal-processing.net) takes you on a journey that starts with basic DSP principles and ends with a treatment of modern wireless modems such as single-tone and OFDM transceivers which are found in GSM, WLAN, LTE and 5G technologies. Throughout this journey, we will cover signal processing topics that are applicable not just to the field of communications but to many engineering disciplines. This text steps outside the often dry mathematical presentation of more traditional DSP books and provides a more intuitive approach to this fascinating topic. Some of this book's uniqueness can be summarized as follows: - An intuitive approach to the topic of digital signal processing. - Working in-book MatLab examples supporting all important concepts. - A large scope covering basic concepts (correlation, convolution, DFT, FIR filters ...) as well as advanced topics (optimization, adaptive signal processing, equalization, OFDM, MIMO ... ). - MatLab modeling of analog/RF effects (multipath channel, thermal noise, phase noise, IQ imbalances, DC and frequency offsets) that must be addressed and solved in modern modem design. - Real world topics that go beyond the ordinary communication textbooks such as signal synchronization, modem rate management, and fixed-point effects. All in all, this book is a must-have for students and practicing engineers who want to build upon the principles of Digital Signal Processing, enrich their understanding with advanced topics, and then apply that knowledge to the design of modern wireless modems. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Using MATLAB & Wavelets Michael Weeks, 2011 Although Digital Signal Processing (DSP) has long been considered an electrical engineering topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware circles. Designed for upper division engineering and computer science students as well as practicing engineers and scientists, Digital Signal Processing Using MATLAB & Wavelets, Second Edition emphasizes the practical applications of signal processing. Over 100 MATLAB examples and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound. This Second Edition also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to MATLAB programming, it moves through filters, sinusoids, sampling, the Fourier transform, the z-transform and other key topics. Two chapters are dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects for each chapter, and the figures from the book. |
digital signal processing for wireless communication using matlab: Modeling of Digital Communication Systems Using SIMULINK Arthur A. Giordano, Allen H. Levesque, 2015-03-03 A comprehensive and detailed treatment of the program SIMULINK® that focuses on SIMULINK® for simulations in Digital and Wireless Communications Modeling of Digital Communication Systems Using SIMULINK® introduces the reader to SIMULINK®, an extension of the widely-used MATLAB modeling tool, and the use of SIMULINK® in modeling and simulating digital communication systems, including wireless communication systems. Readers will learn to model a wide selection of digital communications techniques and evaluate their performance for many important channel conditions. Modeling of Digital Communication Systems Using SIMULINK® is organized in two parts. The first addresses Simulink® models of digital communications systems using various modulation, coding, channel conditions and receiver processing techniques. The second part provides a collection of examples, including speech coding, interference cancellation, spread spectrum, adaptive signal processing, Kalman filtering and modulation and coding techniques currently implemented in mobile wireless systems. Covers case examples, progressing from basic to complex Provides applications for mobile communications, satellite communications, and fixed wireless systems that reveal the power of SIMULINK modeling Includes access to useable SIMULINK® simulations online All models in the text have been updated to R2018a; only problem sets require updating to the latest release by the user Covering both the use of SIMULINK® in digital communications and the complex aspects of wireless communication systems, Modeling of Digital Communication Systems UsingSIMULINK® is a great resource for both practicing engineers and students with MATLAB experience. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Using MATLAB for Students and Researchers John W. Leis, 2011-10-14 Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges. Following an introductory chapter, the text explores: Sampled signals and digital processing Random signals Representing signals and systems Temporal and spatial signal processing Frequency analysis of signals Discrete-time filters and recursive filters Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth. Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed. |
digital signal processing for wireless communication using matlab: Signals and Systems Using MATLAB Luis F. Chaparro, Aydin Akan, 2018-10-29 Signals and Systems Using MATLAB, Third Edition, features a pedagogically rich and accessible approach to what can commonly be a mathematically dry subject. Historical notes and common mistakes combined with applications in controls, communications and signal processing help students understand and appreciate the usefulness of the techniques described in the text. This new edition features more end-of-chapter problems, new content on two-dimensional signal processing, and discussions on the state-of-the-art in signal processing. - Introduces both continuous and discrete systems early, then studies each (separately) in-depth - Contains an extensive set of worked examples and homework assignments, with applications for controls, communications, and signal processing - Begins with a review on all the background math necessary to study the subject - Includes MATLAB® applications in every chapter |
digital signal processing for wireless communication using matlab: Optical Wireless Communications Z. Ghassemlooy, W. Popoola, S. Rajbhandari, 2017-07-12 Detailing a systems approach, Optical Wireless Communications: System and Channel Modelling with MATLAB®, is a self-contained volume that concisely and comprehensively covers the theory and technology of optical wireless communications systems (OWC) in a way that is suitable for undergraduate and graduate-level students, as well as researchers and professional engineers. Incorporating MATLAB® throughout, the authors highlight past and current research activities to illustrate optical sources, transmitters, detectors, receivers, and other devices used in optical wireless communications. They also discuss both indoor and outdoor environments, discussing how different factors—including various channel models—affect system performance and mitigation techniques. In addition, this book broadly covers crucial aspects of OWC systems: Fundamental principles of OWC Devices and systems Modulation techniques and schemes (including polarization shift keying) Channel models and system performance analysis Emerging visible light communications Terrestrial free space optics communication Use of infrared in indoor OWC One entire chapter explores the emerging field of visible light communications, and others describe techniques for using theoretical analysis and simulation to mitigate channel impact on system performance. Additional topics include wavelet denoising, artificial neural networks, and spatial diversity. Content also covers different challenges encountered in OWC, as well as outlining possible solutions and current research trends. A major attraction of the book is the presentation of MATLAB simulations and codes, which enable readers to execute extensive simulations and better understand OWC in general. |
digital signal processing for wireless communication using matlab: Introduction to Wireless Digital Communication Robert W. Heath Jr., 2017-04-04 The Accessible Guide to Modern Wireless Communication for Undergraduates, Graduates, and Practicing Electrical Engineers Wireless communication is a critical discipline of electrical engineering and computer science, yet the concepts have remained elusive for students who are not specialists in the area. This text makes digital communication and receiver algorithms for wireless communication broadly accessible to undergraduates, graduates, and practicing electrical engineers. Notably, the book builds on a signal processing foundation and does not require prior courses on analog or digital communication. Introduction to Wireless Digital Communication establishes the principles of communication, from a digital signal processing perspective, including key mathematical background, transmitter and receiver signal processing algorithms, channel models, and generalizations to multiple antennas. Robert Heath’s “less is more” approach focuses on typical solutions to common problems in wireless engineering. Heath presents digital communication fundamentals from a signal processing perspective, focusing on the complex pulse amplitude modulation approach used in most commercial wireless systems. He describes specific receiver algorithms for implementing wireless communication links, including synchronization, carrier frequency offset estimation, channel estimation, and equalization. While most concepts are presented for systems with single transmit and receive antennas, Heath concludes by extending those concepts to contemporary MIMO systems. To promote learning, each chapter includes previews, bullet-point summaries, examples, and numerous homework problems to help readers test their knowledge. Basics of wireless communication: applications, history, and the central role of signal processing Digital communication essentials: components, channels, distortion, coding/decoding, encryption, and modulation/demodulation Signal processing: linear time invariant systems, probability/random processes, Fourier transforms, derivation of complex baseband signal representation and equivalent channels, and multi-rate signal processing Least-squared estimation techniques that build on the linear algebra typically taught to electrical engineering undergraduates Complex pulse amplitude modulation: symbol mapping, constellations, signal bandwidth, and noise Synchronization, including symbol, frame, and carrier frequency offset Frequency selective channel estimation and equalization MIMO techniques using multiple transmit and/or receive antennas, including SIMO, MISO, and MIMO-OFDM Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Laboratory B. Preetham Kumar, 2016-04-19 Considering the rapid evolution of digital signal processing (DSP), those studying this field require an easily understandable text that complements practical software and hardware applications with sufficient coverage of theory. Designed to keep pace with advancements in the field and elucidate lab work, Digital Signal Processing Laboratory, |
digital signal processing for wireless communication using matlab: Digital Signal Processing Techniques and Applications in Radar Image Processing Bu-Chin Wang, 2008-08-29 A self-contained approach to DSP techniques and applications in radar imaging The processing of radar images, in general, consists of three major fields: Digital Signal Processing (DSP); antenna and radar operation; and algorithms used to process the radar images. This book brings together material from these different areas to allow readers to gain a thorough understanding of how radar images are processed. The book is divided into three main parts and covers: * DSP principles and signal characteristics in both analog and digital domains, advanced signal sampling, and interpolation techniques * Antenna theory (Maxwell equation, radiation field from dipole, and linear phased array), radar fundamentals, radar modulation, and target-detection techniques (continuous wave, pulsed Linear Frequency Modulation, and stepped Frequency Modulation) * Properties of radar images, algorithms used for radar image processing, simulation examples, and results of satellite image files processed by Range-Doppler and Stolt interpolation algorithms The book fully utilizes the computing and graphical capability of MATLAB? to display the signals at various processing stages in 3D and/or cross-sectional views. Additionally, the text is complemented with flowcharts and system block diagrams to aid in readers' comprehension. Digital Signal Processing Techniques and Applications in Radar Image Processing serves as an ideal textbook for graduate students and practicing engineers who wish to gain firsthand experience in applying DSP principles and technologies to radar imaging. |
digital signal processing for wireless communication using matlab: Digital Signal Processing 101 Michael Parker, 2010-05-26 Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples and a minimum of mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems. This book is intended for those who have absolutely no previous experience with DSP, but are comfortable with high-school-level math skills. It is also for those who work in or provide components for industries that are made possible by DSP. Sample industries include wireless mobile phone and infrastructure equipment, broadcast and cable video, DSL modems, satellite communications, medical imaging, audio, radar, sonar, surveillance, and electrical motor control. - Dismayed when presented with a mass of equations as an explanation of DSP? This is the book for you! - Clear examples and a non-mathematical approach gets you up to speed with DSP - Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems |
digital signal processing for wireless communication using matlab: Digital Modulations Using Matlab Mathuranathan Viswanathan, 2017-06-14 Digital Modulations using Matlab is a learner-friendly, practical and example driven book, that gives you a solid background in building simulation models for digital modulation systems in Matlab. This book, an essential guide for understanding the implementation aspects of a digital modulation system, shows how to simulate and model a digital modulation system from scratch. The implemented simulation models shown in this book, mostly will not use any of the inbuilt communication toolbox functions and hence provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a digital modulation system. It presents the following key topics with required theoretical background along with the implementation details in the form of Matlab scripts.* Basics of signal processing essential for implementing digital modulation techniques - generation of test signals, interpreting FFT results, power and energy of a signal, methods to compute convolution, analytic signal and applications.* Waveform and complex equivalent baseband simulation models.* Digital modulation techniques covered: BPSK and its variants, QPSK and its variants, M-ary PSK, M-ary QAM, M-ary PAM, CPM, MSK, GMSK, M-ary FSK. * Monte Carlo simulation for ascertaining performance of digital modulation techniques in AWGN and fading channels - Eb/N0 Vs BER curves.* Design and implementation of linear equalizers - Zero forcing and MMSE equalizers, using them in a communication link.* Simulation and performance of modulation systems with receiver impairments |
digital signal processing for wireless communication using matlab: Real-time Digital Signal Processing Sen-Maw Kuo, 2003 |
digital signal processing for wireless communication using matlab: Discrete Systems and Digital Signal Processing with MATLAB Taan S. ElAli, Taan ElAli, 2003-09-29 Books on linear systems typically cover both discrete and continuous systems together in one book. However, with coverage of this magnitude, not enough information is presented on either of the two subjects. Discrete linear systems warrant a book of their own, and Discrete Systems and Digital Signal Processing with MATLAB provides just that. It offers comprehensive coverage of both discrete linear systems and signal processing in one volume. This detailed book is firmly rooted in basic mathematical principles, and it includes many problems solved first by using analytical tools, then by using MATLAB. Examples that illustrate the theoretical concepts are provided at the end of each chapter. |
digital signal processing for wireless communication using matlab: Digital Modulations Using Python Mathuranathan Viswanathan, 2019-12-02 This paperback is a black & white edition. Link to the color edition: https: //www.amazon.com/dp/1712321633 . A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3. This book, an essential guide for understanding the implementation aspects of a digital modulation system, shows how to simulate and model a digital modulation system from scratch. The implemented simulation models shown in this book, provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a digital modulation system. It presents the key topics with required theoretical background along with the implementation details in the form of Python scripts. Key topics: ► Basics of signal processing, essential for implementing digital modulation techniques - generation of test signals, interpreting FFT results, power and energy of a signal, methods to compute convolution, analytic signal and applications. ► Waveform and complex baseband equivalent simulation models. ► Digital modulation techniques covered: BPSK and its variants, QPSK and its variants, M-ary PSK, M-ary QAM, M-ary PAM, CPM, MSK, GMSK, M-ary FSK. ► Simulation for ascertaining performance of digital modulation techniques in AWGN and fading channels - Eb/N0 Vs BER curves. ► Design and implementation of linear equalizers - zero forcing and MMSE equalizers, using them in a communication link, LMS algorithm for adaptive equalization. ► Simulation and performance of modulation systems with receiver impairments. ► Examples using object oriented programming. ► Simulation scripts using SciPy, Numpy and Matplotlib packages. |
digital signal processing for wireless communication using matlab: Introduction to Digital Signal Processing and Filter Design B. A. Shenoi, 2005-11-07 A practical and accessible guide to understanding digital signal processing Introduction to Digital Signal Processing and Filter Design was developed and fine-tuned from the author's twenty-five years of experience teaching classes in digital signal processing. Following a step-by-step approach, students and professionals quickly master the fundamental concepts and applications of discrete-time signals and systems as well as the synthesis of these systems to meet specifications in the time and frequency domains. Striking the right balance between mathematical derivations and theory, the book features: * Discrete-time signals and systems * Linear difference equations * Solutions by recursive algorithms * Convolution * Time and frequency domain analysis * Discrete Fourier series * Design of FIR and IIR filters * Practical methods for hardware implementation A unique feature of this book is a complete chapter on the use of a MATLAB(r) tool, known as the FDA (Filter Design and Analysis) tool, to investigate the effect of finite word length and different formats of quantization, different realization structures, and different methods for filter design. This chapter contains material of practical importance that is not found in many books used in academic courses. It introduces students in digital signal processing to what they need to know to design digital systems using DSP chips currently available from industry. With its unique, classroom-tested approach, Introduction to Digital Signal Processing and Filter Design is the ideal text for students in electrical and electronic engineering, computer science, and applied mathematics, and an accessible introduction or refresher for engineers and scientists in the field. |
digital signal processing for wireless communication using matlab: Fundamentals of Wireless Communication David Tse, Pramod Viswanath, 2005-05-26 The past decade has seen many advances in physical layer wireless communication theory and their implementation in wireless systems. This textbook takes a unified view of the fundamentals of wireless communication and explains the web of concepts underpinning these advances at a level accessible to an audience with a basic background in probability and digital communication. Topics covered include MIMO (multi-input, multi-output) communication, space-time coding, opportunistic communication, OFDM and CDMA. The concepts are illustrated using many examples from real wireless systems such as GSM, IS-95 (CDMA), IS-856 (1 x EV-DO), Flash OFDM and UWB (ultra-wideband). Particular emphasis is placed on the interplay between concepts and their implementation in real systems. An abundant supply of exercises and figures reinforce the material in the text. This book is intended for use on graduate courses in electrical and computer engineering and will also be of great interest to practising engineers. |
digital signal processing for wireless communication using matlab: Signals and Systems Laboratory with MATLAB Alex Palamides, Anastasia Veloni, 2010-08-13 Developed as a textbook for the laboratory part of the course Signals and Systems, this book introduces students to theory through analytical examples implemented in Matlab code. Thus every theoretical equation is accompanied by the corresponding code implementation. Instead of using big M-Files or author-written functions with comments, the commands are executed one-by-one at the Matlab command line and the results, dong with comments are given side-by side in two or three column tables. This is very helpful and popular to students in Electrical Engineering, since the nature of this course includes detailed mathematical derivations and demands a strong mathematical background. |
digital signal processing for wireless communication using matlab: Signal Processing for 5G Fa-Long Luo, Charlie Jianzhong Zhang, 2016-10-17 A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture, physical-layer (down-link and up-link), protocols and air interface, to cell acquisition, scheduling and rate adaption, access procedures and relaying to spectrum allocations. All technology aspects and major roadmaps of global 5G standard development and deployments are included in the book. Key Features: Offers step-by-step guidance on bringing 5G technology into practice, by applying algorithms and design methodology to real-time circuit implementation, taking into account rapidly growing applications that have multi-standards and multi-systems. Addresses spatial signal processing for 5G, in particular massive multiple-input multiple-output (massive-MIMO), FD-MIMO and 3D-MIMO along with orbital angular momentum multiplexing, 3D beamforming and diversity. Provides detailed algorithms and implementations, and compares all multicarrier modulation and multiple access schemes that offer superior data transmission performance including FBMC, GFDM, F-OFDM, UFMC, SEFDM, FTN, MUSA, SCMA and NOMA. Demonstrates the translation of signal processing theories into practical solutions for new spectrum opportunities in terms of millimeter wave, full-duplex transmission and license assisted access. Presents well-designed implementation examples, from individual function block to system level for effective and accurate learning. Covers signal processing aspects of emerging system and network architectures, including ultra-dense networks (UDN), software-defined networks (SDN), device-to-device (D2D) communications and cloud radio access network (C-RAN). |
digital signal processing for wireless communication using matlab: Digital Signal Processing with Matlab Examples, Volume 1 Jose Maria Giron-Sierra, 2016-11-19 This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals. |
digital signal processing for wireless communication using matlab: Communication Systems Principles Using MATLAB John W. Leis, 2018-10-16 Discover the basic telecommunications systems principles in an accessible learn-by-doing format Communication Systems Principles Using MATLAB covers a variety of systems principles in telecommunications in an accessible format without the need to master a large body of theory. The text puts the focus on topics such as radio and wireless modulation, reception and transmission, wired networks and fiber optic communications. The book also explores packet networks and TCP/IP as well as digital source and channel coding, and the fundamentals of data encryption. Since MATLAB® is widely used by telecommunications engineers, it was chosen as the vehicle to demonstrate many of the basic ideas, with code examples presented in every chapter. The text addresses digital communications with coverage of packet-switched networks. Many fundamental concepts such as routing via shortest-path are introduced with simple and concrete examples. The treatment of advanced telecommunications topics extends to OFDM for wireless modulation, and public-key exchange algorithms for data encryption. Throughout the book, the author puts the emphasis on understanding rather than memorization. The text also: Includes many useful take-home skills that can be honed while studying each aspect of telecommunications Offers a coding and experimentation approach with many real-world examples provided Gives information on the underlying theory in order to better understand conceptual developments Suggests a valuable learn-by-doing approach to the topic Written for students of telecommunications engineering, Communication Systems Principles Using MATLAB® is the hands-on resource for mastering the basic concepts of telecommunications in a learn-by-doing format. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Paulo S. R. Diniz, Eduardo A. B. da Silva, Sergio L. Netto, 2002-04-18 Digital signal processing lies at the heart of the communications revolution and is an essential element of key technologies such as mobile phones and the Internet. This book covers all the major topics in digital signal processing (DSP) design and analysis, supported by MatLab examples and other modelling techniques. The authors explain clearly and concisely why and how to use digital signal processing systems; how to approximate a desired transfer function characteristic using polynomials and ratio of polynomials; why an appropriate mapping of a transfer function on to a suitable structure is important for practical applications; and how to analyse, represent and explore the trade-off between time and frequency representation of signals. An ideal textbook for students, it will also be a useful reference for engineers working on the development of signal processing systems. |
digital signal processing for wireless communication using matlab: Applied Digital Signal Processing Dimitris G. Manolakis, Vinay K. Ingle, 2011-11-21 Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors. |
digital signal processing for wireless communication using matlab: Digital Signal Processing Thomas Holton, 2020 Combining clear explanations of elementary principles, advanced topics, and applications, with step-by-step mathematical derivations, this textbook provides a comprehensive yet accessible introduction to digital signal processing. All the key topics are covered, including discrete-time Fourier transform, z-transform, discrete Fourier transform, and A/D conversion, as well as more advanced topics such as FIR and IIR filtering algorithms, multi-rate systems, the discrete cosine transform, and spectral signal processing. Over 600 full-color illustrations, 200 fully worked examples, hundreds of end-of-chapter homework problems, and detailed computational examples of DSP algorithms implemented in Matlab and C aid understanding and help put knowledge into practice. A wealth of supplementary material accompanies the book online, including interactive programs for instructors, a full set of solutions, and Matlab laboratory exercises, making this the ideal text for senior undergraduate and graduate courses on digital signal processing-- |
digital signal processing for wireless communication using matlab: Software Defined Radio Using MATLAB & Simulink and the RTL-SDR Robert W Stewart, Kenneth W Barlee, Dale S W Atkinson, 2015-09-11 The availability of the RTL-SDR device for less than $20 brings software defined radio (SDR) to the home and work desktops of EE students, professional engineers and the maker community. The RTL-SDR can be used to acquire and sample RF (radio frequency) signals transmitted in the frequency range 25MHz to 1.75GHz, and the MATLAB and Simulink environment can be used to develop receivers using first principles DSP (digital signal processing) algorithms. Signals that the RTL-SDR hardware can receive include: FM radio, UHF band signals, ISM signals, GSM, 3G and LTE mobile radio, GPS and satellite signals, and any that the reader can (legally) transmit of course! In this book we introduce readers to SDR methods by viewing and analysing downconverted RF signals in the time and frequency domains, and then provide extensive DSP enabled SDR design exercises which the reader can learn from. The hands-on SDR design examples begin with simple AM and FM receivers, and move on to the more challenging aspects of PHY layer DSP, where receive filter chains, real-time channelisers, and advanced concepts such as carrier synchronisers, digital PLL designs and QPSK timing and phase synchronisers are implemented. In the book we will also show how the RTL-SDR can be used with SDR transmitters to develop complete communication systems, capable of transmitting payloads such as simple text strings, images and audio across the lab desktop. |
digital signal processing for wireless communication using matlab: Digital Signal Processing and Statistical Classification George J. Miao, Mark A. Clements, 2002 This is the first book to introduce and integrate advanced digital signal processing (DSP) and classification together, and the only volume to introduce state-of-the-art transforms including DFT, FFT, DCT, DHT, PCT, CDT, and ODT together for DSP and communication applications. You get step-by-step guidance in discrete-time domain signal processing and frequency domain signal analysis; digital filter design and adaptive filtering; multirate digital processing; and statistical signal classification. It also helps you overcome problems associated with multirate A/D and D/A converters. |
digital signal processing for wireless communication using matlab: Software-Defined Radio for Engineers Alexander M. Wyglinski, Robin Getz, Travis Collins, Di Pu, 2018-04-30 Based on the popular Artech House classic, Digital Communication Systems Engineering with Software-Defined Radio, this book provides a practical approach to quickly learning the software-defined radio (SDR) concepts needed for work in the field. This up-to-date volume guides readers on how to quickly prototype wireless designs using SDR for real-world testing and experimentation. This book explores advanced wireless communication techniques such as OFDM, LTE, WLA, and hardware targeting. Readers will gain an understanding of the core concepts behind wireless hardware, such as the radio frequency front-end, analog-to-digital and digital-to-analog converters, as well as various processing technologies. Moreover, this volume includes chapters on timing estimation, matched filtering, frame synchronization message decoding, and source coding. The orthogonal frequency division multiplexing is explained and details about HDL code generation and deployment are provided. The book concludes with coverage of the WLAN toolbox with OFDM beacon reception and the LTE toolbox with downlink reception. Multiple case studies are provided throughout the book. Both MATLAB and Simulink source code are included to assist readers with their projects in the field. |
digital signal processing for wireless communication using matlab: Emerging Technologies for Health and Medicine Dac-Nhuong Le, Chung Van Le, Jolanda G. Tromp, Gia Nhu Nguyen, 2018-10-16 Showcases the latest trends in new virtual/augmented reality healthcare and medical applications and provides an overview of the economic, psychological, educational and organizational impacts of these new applications and how we work, teach, learn and provide care. With the current advances in technology innovation, the field of medicine and healthcare is rapidly expanding and, as a result, many different areas of human health diagnostics, treatment and care are emerging. Wireless technology is getting faster and 5G mobile technology allows the Internet of Medical Things (IoMT) to greatly improve patient care and more effectively prevent illness from developing. This book provides an overview and review of the current and anticipated changes in medicine and healthcare due to new technologies and faster communication between users and devices. The groundbreaking book presents state-of-the-art chapters on many subjects including: A review of the implications of Virtual Reality (VR) and Augmented Reality (AR) healthcare applications A review of current augmenting dental care An overview of typical human-computer interaction (HCI) that can help inform the development of user interface designs and novel ways to evaluate human behavior to responses in VR and other new technologies A review of telemedicine technologies Building empathy in young children using augmented reality AI technologies for mobile health of stroke monitoring & rehabilitation robotics control Mobile doctor brain AI App An artificial intelligence mobile cloud computing tool Development of a robotic teaching aid for disabled children Training system design of lower limb rehabilitation robot based on virtual reality |
digital signal processing for wireless communication using matlab: Digital Signal Processing in Audio and Acoustical Engineering Francis F. Li, Trevor J. Cox, 2019-04-02 Starting with essential maths, fundamentals of signals and systems, and classical concepts of DSP, this book presents, from an application-oriented perspective, modern concepts and methods of DSP including machine learning for audio acoustics and engineering. Content highlights include but are not limited to room acoustic parameter measurements, filter design, codecs, machine learning for audio pattern recognition and machine audition, spatial audio, array technologies and hearing aids. Some research outcomes are fed into book as worked examples. As a research informed text, the book attempts to present DSP and machine learning from a new and more relevant angle to acousticians and audio engineers. Some MATLAB® codes or frameworks of algorithms are given as downloads available on the CRC Press website. Suggested exploration and mini project ideas are given for proof of concept type of exercises and directions for further study and investigation. The book is intended for researchers, professionals, and senior year students in the field of audio acoustics. |
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