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This book will help the reader understand digital signal processing techniques and their applications to digital communications systems. The content is based on the lecture notes of a graduate-level course in Digital Communications Systems, which has been taught for more than twenty years at US universities and abroad. It was written for students of this course, but has been written in a way that can be understood by readers with little or no experience in the subject. The book covers the fundamentals of digital communications systems providing an introduction to topics like sampling, quantization error, noise shaping and linear prediction coding. The chapters on source coding and channel coding provide simple expositions on source encoding techniques; channel encoder optimization; arithmetic encoder; Huffman coding; run length limited codes; convolutional codes; turbo codes; recursive systematic convolutional codes (RSC). Time permitting, The chapter on Random Access Techniques addresses the use of sliding correlators (like the SIC algorithm), PPM synchronization algorithms, SINR-based synchronization algorithms etc. The book also covers some topics relevant to all theoretical digital communications systems. These include binary decision diagrams, linear programming and basic information theory. This book covers a wide range of topics in basic digital communications systems including both traditional technology and more advanced concepts such as turbo codes and data-centric networks. The author has written the material in a style that is self-contained for readers who have had little or no prior background in these subjects. This book provides an accessible introduction to many algorithmic ideas that can be used to design, implement, analyze and debug practical digital communications systems. The book begins with an overview of digital communications technology before moving on to practical systems design problems. The first part of the book deals with digital communications systems, including physical layer issues such as modulation, analog to digital (ADC) conversion and sampling at the receiver. It then covers digital signal processing, including numerically controlled oscillators (NCOs), interpolation filters for NCOs and adaptive equalizers. The problems then move on to equalizer design via linear prediction coding. The next two chapters cover convolutional codes (including turbo codes). The material is presented in a self-contained way to make the material easier to follow by readers who are not well familiar with it. The last part of the book covers advanced topics including data-centric networks, random access techniques and compressed sensing. The material of the first three chapters is included in all editions of this book, including the first edition. These chapters deal with digital communications systems. The first chapter covers digital communications basics, including signal transmission and various modulation schemes. It discusses systems issues such as analog to digital conversion and a brief introduction to the Nyquist theorem. The second chapter covers linear prediction coding (LPC) and nonlinear predictive coding (NPC). It also covers noise shaping techniques at high data rates by using block codes for LPC analysis at high data rates . cfa1e77820
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