Precoding and Signal Shaping for Digital Transmission
|
|
- Elmer Harrington
- 5 years ago
- Views:
Transcription
1 Precoding and Signal Shaping for Digital Transmission Robert F. H. Fischer The Institute of Electrical and Electronics Engineers, Inc., New York WILEY- INTERSCIENCE A JOHN WILEY & SONS, INC., PUBLICATION
2 Contents Preface xi 1 Introduction The Structure of the Book Notation and Definitions Signals and Systems Stochastic Processes Equivalent Complex Baseband Signals Miscellaneous 7 References 8 2 Digital Communications via Linear, Distorting Channels Fundamentals and Problem Description Linear Equalization Zero-Forcing Linear Equalization A General Property of the Receive Filter MMSE Filtering and the Orthogonality Principle MMSE Linear Equalization Joint Transmitter and Receiver Optimization 43
3 Vi CONTENTS 2.3 Noise Prediction and Decision-Feedback Equalization Noise Prediction Zero-Forcing Decision-Feedback Equalization Finite-Length MMSE Decision-Feedback Equalization Infinite-Length MMSE Decision-Feedback Equalization Summary of Equalization Strategies and Discrete- Time Models Summary of Equalization Strategies HR Channel Models Channels with Spectral Nulls Maximum-Likelihood Sequence Estimation Whitened-Matched-Filter Front-End Alternative Derivation 112 References Precoding Schemes Preliminaries Tomlinson-Harashima Precoding Precoder Statistical Characteristics of the Transmit Signal Tomlinson-Harashima Precoding for Complex Channels Precoding for Arbitrary Signal Constellations Multidimensional Generalization of Tomlinson-Harashima Precoding Signal-to-Noise Ratio Combination with Coded Modulation Tomlinson-Harashima Precoding and Feedback Trellis Encoding Combination with Signal Shaping Flexible Precoding Precoder and Inverse Precoder Transmit Power and Signal-to-Noise Ratio Combination with Signal Shaping Straightforward Combination with Coded Modulation Combined Coding and Precoding 161
4 CONTENTS Vii Spectral Zeros Summary and Comparison of Precoding Schemes Finite-Word-Length Implementation of Precoding Schemes Two's Complement Representation Fixed-Point Realization of Tomlinson- Harashima Precoding Nonrecursive Structure for Tomlinson-Harashima Precoding Precoding for IIR Channels Extension to DC-free Channels Information-Theoretical Aspects of Precoding Precoding Designed According to MMSE Criterion MMSE Precoding and Channel Capacity 203 References 211 Signal Shaping Introduction to Shaping Measures of Performance Optimal Distribution for Given Constellation Ultimate Shaping Gain Bounds on Shaping Lattices, Constellations, and Regions Performance of Shaping and Coding Shaping Properties of Hyperspheres Shaping Under a Peak Constraint Shaping on Regions AWGN Channel and Shaping Gain Shell Mapping Preliminaries Sorting and Iteration on Dimensions Shell Mapping Encoder and Decoder Arbitrary Frame Sizes General Cost Functions Shell Frequency Distribution Trellis Shaping Motivation Trellis Shaping on Regions 289
5 WW CONTENTS Practical Considerations and Performance Shaping, Channel Coding, and Source Coding Spectral Shaping Further Shaping Properties Approaching Capacity by Equiprobable Signaling AWGN Channel and Equiprobable Signaling Nonuniform Constellations Warping Modulus Conversion 328 References Combined Precoding and Signal Shaping Trellis Precoding Operation of Trellis Precoding Branch Metrics Calculation Shaping Without Scrambling Basic Principle Decoding and Branch Metrics Calculation Performance of Shaping Without Scrambling Precoding and Shaping under Additional Constraints Preliminaries on Receiver-Side Dynamics Restriction Dynamics Limited Precoding Dynamics Shaping Reduction of the Peak-to-Average Power Ratio Geometrical Interpretation of Precoding and Shaping Combined Precoding and Signal Shaping Limitation of the Dynamic Range Connection to Quantization and Prediction 397 References 400 Appendix A Wirtinger Calculus 405 A. 1 Real and Complex Derivatives 406 A.2 Wirtinger Calculus 407 A.2.1 Examples 408 A.2.2 Discussion 410 A.3 Gradients 411 A.3.1 Examples 411 A.3.2 Discussion 412 References 413
6 CONTENTS ix Appendix В Parameters of the Numerical Examples 415 B.l Fundamentals of Digital Subscriber Lines 415 B. 2 Single-Pair Digital Subscriber Lines 417 B.3 Asymmetric Digital Subscriber Lines 418 References 420 Appendix С Introduction to Lattices 421 C.l Definition of Lattices 421 C.2 Some Important Parameters of Lattices 425 C.3 Modifications of Lattices 428 C.4 Sublattices, Cosets, and Partitions 430 C.5 Some Important Lattices and Their Parameters 434 References 437 Appendix D Calculation of Shell Frequency Distribution 439 D.l Partial Histograms 440 D.2 Partial Histograms for General Cost Functions 444 D.3 Frequencies of Shells 445 References 453 Appendix E Preceding for MIMO Channels 455 E.l Centralized Receiver 456 E.l.l Multiple-lnput/Multiple-Output Channel 456 E.l.2 Equalization Strategies for MIMO Channels 457 E.1.3 Matrix DFE 459 E.l.4 Tomlinson-Harashima Preceding 460 E.2 Decentralized Receivers 465 E.2.1 Channel Model 465 E.2.2 Centralized Receiver and Decision-Feedback Equalization 466 E.2.3 Decentralized Receivers and Preceding 466 E.3 Discussion 468 E.3.1 ISI Channels 468 E.3.2 Application of Channel Coding 469 E.3.3 Application of Signal Shaping 470 E.3.4 Rate and Power Distribution 470 References 471 Appendix F List of Symbols, Variables, and Acronyms 475
7 X CONTENTS F.l Important Sets of Numbers and Constants 475 F.2 Transforms, Operators, and Special Functions 476 F.3 Important Variables 478 F.4 Acronyms 479 Index 483
Adaptive Wireless. Communications. gl CAMBRIDGE UNIVERSITY PRESS. MIMO Channels and Networks SIDDHARTAN GOVJNDASAMY DANIEL W.
Adaptive Wireless Communications MIMO Channels and Networks DANIEL W. BLISS Arizona State University SIDDHARTAN GOVJNDASAMY Franklin W. Olin College of Engineering, Massachusetts gl CAMBRIDGE UNIVERSITY
More informationCoding for MIMO Communication Systems
Coding for MIMO Communication Systems Tolga M. Duman Arizona State University, USA Ali Ghrayeb Concordia University, Canada BICINTINNIAL BICENTENNIAL John Wiley & Sons, Ltd Contents About the Authors Preface
More informationChapter 9. Digital Communication Through Band-Limited Channels. Muris Sarajlic
Chapter 9 Digital Communication Through Band-Limited Channels Muris Sarajlic Band limited channels (9.1) Analysis in previous chapters considered the channel bandwidth to be unbounded All physical channels
More informationDetection and Estimation of Signals in Noise. Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia
Detection and Estimation of Signals in Noise Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia Vancouver, August 24, 2010 2 Contents 1 Basic Elements
More informationIN AN MIMO communication system, multiple transmission
3390 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL 55, NO 7, JULY 2007 Precoded FIR and Redundant V-BLAST Systems for Frequency-Selective MIMO Channels Chun-yang Chen, Student Member, IEEE, and P P Vaidyanathan,
More informationWireless Communications Over Rapidly Time-Varying Channels
Wireless Communications Over Rapidly Time-Varying Channels Edited by Franz Hlawatsch Gerald Matz ELSEVIER AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY
More informationLecture 8 Multi- User MIMO
Lecture 8 Multi- User MIMO I-Hsiang Wang ihwang@ntu.edu.tw 5/7, 014 Multi- User MIMO System So far we discussed how multiple antennas increase the capacity and reliability in point-to-point channels Question:
More informationCOMMUNICATION SYSTEMS
COMMUNICATION SYSTEMS 4TH EDITION Simon Hayhin McMaster University JOHN WILEY & SONS, INC. Ш.! [ BACKGROUND AND PREVIEW 1. The Communication Process 1 2. Primary Communication Resources 3 3. Sources of
More informationChannel Precoding for Indoor Radio Communications Using Dimension Partitioning. Yuk-Lun Chan and Weihua Zhuang, Member, IEEE
98 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 48, NO. 1, JANUARY 1999 Channel Precoding for Indoor Radio Communications Using Dimension Partitioning Yuk-Lun Chan and Weihua Zhuang, Member, IEEE Abstract
More informationFILTER BANK TRANSCEIVERS FOR OFDM AND DMT SYSTEMS
FILTER BANK TRANSCEIVERS FOR OFDM AND DMT SYSTEMS YUAN-PEI LIN National Chiao Tung University, Taiwan SEE-MAY PHOONG National Taiwan University P. P. VAIDYANATHAN California Institute of Technology CAMBRIDGE
More informationMU-MIMO in LTE/LTE-A Performance Analysis. Rizwan GHAFFAR, Biljana BADIC
MU-MIMO in LTE/LTE-A Performance Analysis Rizwan GHAFFAR, Biljana BADIC Outline 1 Introduction to Multi-user MIMO Multi-user MIMO in LTE and LTE-A 3 Transceiver Structures for Multi-user MIMO Rizwan GHAFFAR
More informationChapter 3 Convolutional Codes and Trellis Coded Modulation
Chapter 3 Convolutional Codes and Trellis Coded Modulation 3. Encoder Structure and Trellis Representation 3. Systematic Convolutional Codes 3.3 Viterbi Decoding Algorithm 3.4 BCJR Decoding Algorithm 3.5
More informationBlind Equalization for Tomlinson-Harashima Precoded Systems
Blind Equalization for Tomlinson-Harashima Precoded Systems Rubyet Adnan A thesis submitted in partial fulfilment of the requirements for the degree of Master of Engineering in Electrical and Electronic
More informationSPACE TIME coding for multiple transmit antennas has attracted
486 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 50, NO. 3, MARCH 2004 An Orthogonal Space Time Coded CPM System With Fast Decoding for Two Transmit Antennas Genyuan Wang Xiang-Gen Xia, Senior Member,
More informationINTERSYMBOL interference (ISI) is a significant obstacle
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 1, JANUARY 2005 5 Tomlinson Harashima Precoding With Partial Channel Knowledge Athanasios P. Liavas, Member, IEEE Abstract We consider minimum mean-square
More informationDepartment of Electronics and Communication Engineering 1
UNIT I SAMPLING AND QUANTIZATION Pulse Modulation 1. Explain in detail the generation of PWM and PPM signals (16) (M/J 2011) 2. Explain in detail the concept of PWM and PAM (16) (N/D 2012) 3. What is the
More informationPerformance Comparison of MIMO Systems over AWGN and Rician Channels using OSTBC3 with Zero Forcing Receivers
www.ijcsi.org 355 Performance Comparison of MIMO Systems over AWGN and Rician Channels using OSTBC3 with Zero Forcing Receivers Navjot Kaur, Lavish Kansal Electronics and Communication Engineering Department
More informationEnabling Improved DSP Based Receivers for 100G Backplane
Enabling Improved DSP Based Receivers for 100G Backplane Dariush Dabiri 802.3bj Task Force IEEE 802.3 Interim September 2011 1 Agenda Goals Introduction Partial Response Channel (PRC) Signaling Quasi-catastrophic
More informationMODULATION AND CODING TECHNIQUES IN WIRELESS COMMUNICATIONS
MODULATION AND CODING TECHNIQUES IN WIRELESS COMMUNICATIONS Edited by Evgenii Krouk Dean of the Information Systems and Data Protection Faculty, St Petersburg State University of Aerospace Instrumentation,
More informationTHE idea behind constellation shaping is that signals with
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 3, MARCH 2004 341 Transactions Letters Constellation Shaping for Pragmatic Turbo-Coded Modulation With High Spectral Efficiency Dan Raphaeli, Senior Member,
More informationMultiple Antennas. Mats Bengtsson, Björn Ottersten. Basic Transmission Schemes 1 September 8, Presentation Outline
Multiple Antennas Capacity and Basic Transmission Schemes Mats Bengtsson, Björn Ottersten Basic Transmission Schemes 1 September 8, 2005 Presentation Outline Channel capacity Some fine details and misconceptions
More information3542 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 6, JUNE 2011
3542 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 6, JUNE 2011 MIMO Precoding With X- and Y-Codes Saif Khan Mohammed, Student Member, IEEE, Emanuele Viterbo, Fellow, IEEE, Yi Hong, Senior Member,
More information124 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 45, NO. 1, JANUARY 1997
124 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 45, NO. 1, JANUARY 1997 Blind Adaptive Interference Suppression for the Near-Far Resistant Acquisition and Demodulation of Direct-Sequence CDMA Signals
More informationa) Abasebanddigitalcommunicationsystemhasthetransmitterfilterg(t) thatisshowninthe figure, and a matched filter at the receiver.
DIGITAL COMMUNICATIONS PART A (Time: 60 minutes. Points 4/0) Last Name(s):........................................................ First (Middle) Name:.................................................
More informationERROR CONTROL CODING From Theory to Practice
ERROR CONTROL CODING From Theory to Practice Peter Sweeney University of Surrey, Guildford, UK JOHN WILEY & SONS, LTD Contents 1 The Principles of Coding in Digital Communications 1.1 Error Control Schemes
More informationd[m] = [m]+ 1 2 [m 2]
DIGITAL COMMUNICATIONS PART A (Time: 60 minutes. Points 4/0) Last Name(s):........................................................ First (Middle) Name:.................................................
More informationUNIT I Source Coding Systems
SIDDHARTH GROUP OF INSTITUTIONS: PUTTUR Siddharth Nagar, Narayanavanam Road 517583 QUESTION BANK (DESCRIPTIVE) Subject with Code: DC (16EC421) Year & Sem: III-B. Tech & II-Sem Course & Branch: B. Tech
More informationDigital Signal Processing
Digital Signal Processing Fourth Edition John G. Proakis Department of Electrical and Computer Engineering Northeastern University Boston, Massachusetts Dimitris G. Manolakis MIT Lincoln Laboratory Lexington,
More informationDIGITAL SIGNAL PROCESSING LABORATORY
DIGITAL SIGNAL PROCESSING LABORATORY SECOND EDITION В. Preetham Kumar CRC Press Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Croup, an informa business
More informationBER Analysis of OSTBC in MIMO using ZF & MMSE Equalizer
BER Analysis of OSTBC in MIMO using ZF & MMSE Equalizer Abhijit Singh Thakur Scholar, ECE, IPS Academy, Indore, India Prof. Nitin jain Prof, ECE, IPS Academy, Indore, India Abstract - In this paper, a
More informationMultiple Input Multiple Output Dirty Paper Coding: System Design and Performance
Multiple Input Multiple Output Dirty Paper Coding: System Design and Performance Zouhair Al-qudah and Dinesh Rajan, Senior Member,IEEE Electrical Engineering Department Southern Methodist University Dallas,
More informationComputer Exercises in. Communication Theory SMS016
Luleå Tekniska Universitet Avd. för Signalbehandling Jan-Jaap van de Beek Frank Sjöberg Computer Exercises in Communication Theory SMS016 November 2001 Computer Exercises to be carried out in groups of
More informationCOMBINED TRELLIS CODED QUANTIZATION/CONTINUOUS PHASE MODULATION (TCQ/TCCPM)
COMBINED TRELLIS CODED QUANTIZATION/CONTINUOUS PHASE MODULATION (TCQ/TCCPM) Niyazi ODABASIOGLU 1, OnurOSMAN 2, Osman Nuri UCAN 3 Abstract In this paper, we applied Continuous Phase Frequency Shift Keying
More informationMULTILEVEL CODING (MLC) with multistage decoding
350 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 3, MARCH 2004 Power- and Bandwidth-Efficient Communications Using LDPC Codes Piraporn Limpaphayom, Student Member, IEEE, and Kim A. Winick, Senior
More informationIEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 5, MAY
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 51, NO 5, MAY 2005 1691 Maximal Diversity Algebraic Space Time Codes With Low Peak-to-Mean Power Ratio Pranav Dayal, Student Member, IEEE, and Mahesh K Varanasi,
More informationDesign of Coded Modulation Schemes for Orthogonal Transmit Diversity. Mohammad Jaber Borran, Mahsa Memarzadeh, and Behnaam Aazhang
1 esign of Coded Modulation Schemes for Orthogonal Transmit iversity Mohammad Jaber orran, Mahsa Memarzadeh, and ehnaam Aazhang ' E E E E E E 2 Abstract In this paper, we propose a technique to decouple
More informationModern Quadrature Amplitude Modulation Principles and Applications for Fixed and Wireless Channels
1 Modern Quadrature Amplitude Modulation Principles and Applications for Fixed and Wireless Channels W.T. Webb, L.Hanzo Contents PART I: Background to QAM 1 Introduction and Background 1 1.1 Modulation
More informationThe Case for Optimum Detection Algorithms in MIMO Wireless Systems. Helmut Bölcskei
The Case for Optimum Detection Algorithms in MIMO Wireless Systems Helmut Bölcskei joint work with A. Burg, C. Studer, and M. Borgmann ETH Zurich Data rates in wireless double every 18 months throughput
More informationUNDERSTANDING LTE WITH MATLAB
UNDERSTANDING LTE WITH MATLAB FROM MATHEMATICAL MODELING TO SIMULATION AND PROTOTYPING Dr Houman Zarrinkoub MathWorks, Massachusetts, USA WILEY Contents Preface List of Abbreviations 1 Introduction 1.1
More informationUnderstanding Digital Signal Processing
Understanding Digital Signal Processing Richard G. Lyons PRENTICE HALL PTR PRENTICE HALL Professional Technical Reference Upper Saddle River, New Jersey 07458 www.photr,com Contents Preface xi 1 DISCRETE
More informationUNIVERSITY OF SOUTHAMPTON
UNIVERSITY OF SOUTHAMPTON ELEC6014W1 SEMESTER II EXAMINATIONS 2007/08 RADIO COMMUNICATION NETWORKS AND SYSTEMS Duration: 120 mins Answer THREE questions out of FIVE. University approved calculators may
More informationUNIVERSITY OF CALIFORNIA College of Engineering Department of Electrical Engineering and Computer Sciences EECS 121 FINAL EXAM
Name: UNIVERSIY OF CALIFORNIA College of Engineering Department of Electrical Engineering and Computer Sciences Professor David se EECS 121 FINAL EXAM 21 May 1997, 5:00-8:00 p.m. Please write answers on
More informationInterleaved PC-OFDM to reduce the peak-to-average power ratio
1 Interleaved PC-OFDM to reduce the peak-to-average power ratio A D S Jayalath and C Tellambura School of Computer Science and Software Engineering Monash University, Clayton, VIC, 3800 e-mail:jayalath@cssemonasheduau
More informationMIMO CONFIGURATION SCHEME WITH SPATIAL MULTIPLEXING AND QPSK MODULATION
MIMO CONFIGURATION SCHEME WITH SPATIAL MULTIPLEXING AND QPSK MODULATION Yasir Bilal 1, Asif Tyagi 2, Javed Ashraf 3 1 Research Scholar, 2 Assistant Professor, 3 Associate Professor, Department of Electronics
More information3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 53, NO. 10, OCTOBER 2007
3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 53, NO 10, OCTOBER 2007 Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution Yingbin Liang, Member, IEEE, Venugopal V Veeravalli, Fellow,
More informationSPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS
SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS RASHMI SABNUAM GUPTA 1 & KANDARPA KUMAR SARMA 2 1 Department of Electronics and Communication Engineering, Tezpur University-784028,
More informationPRINCIPLES OF COMMUNICATIONS
PRINCIPLES OF COMMUNICATIONS Systems, Modulation, and Noise SIXTH EDITION INTERNATIONAL STUDENT VERSION RODGER E. ZIEMER University of Colorado at Colorado Springs WILLIAM H. TRANTER Virginia Polytechnic
More informationMULTIPATH fading could severely degrade the performance
1986 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 12, DECEMBER 2005 Rate-One Space Time Block Codes With Full Diversity Liang Xian and Huaping Liu, Member, IEEE Abstract Orthogonal space time block
More informationAnalysis of Convolutional Encoder with Viterbi Decoder for Next Generation Broadband Wireless Access Systems
International Journal of Engineering and Technical Research (IJETR) ISSN: 2321-0869, Volume-3, Issue-4, April 2015 Analysis of Convolutional Encoder with Viterbi Decoder for Next Generation Broadband Wireless
More informationIntro to coding and convolutional codes
Intro to coding and convolutional codes Lecture 11 Vladimir Stojanović 6.973 Communication System Design Spring 2006 Massachusetts Institute of Technology 802.11a Convolutional Encoder Rate 1/2 convolutional
More informationUniversal Space Time Coding
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 49, NO. 5, MAY 2003 1097 Universal Space Time Coding Hesham El Gamal, Member, IEEE, and Mohamed Oussama Damen, Member, IEEE Abstract A universal framework
More informationImproving the Generalized Likelihood Ratio Test for Unknown Linear Gaussian Channels
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 49, NO 4, APRIL 2003 919 Improving the Generalized Likelihood Ratio Test for Unknown Linear Gaussian Channels Elona Erez, Student Member, IEEE, and Meir Feder,
More informationTHOMAS PANY SOFTWARE RECEIVERS
TECHNOLOGY AND APPLICATIONS SERIES THOMAS PANY SOFTWARE RECEIVERS Contents Preface Acknowledgments xiii xvii Chapter 1 Radio Navigation Signals 1 1.1 Signal Generation 1 1.2 Signal Propagation 2 1.3 Signal
More informationSTUDY OF THE PERFORMANCE OF THE LINEAR AND NON-LINEAR NARROW BAND RECEIVERS FOR 2X2 MIMO SYSTEMS WITH STBC MULTIPLEXING AND ALAMOTI CODING
International Journal of Electrical and Electronics Engineering Research Vol.1, Issue 1 (2011) 68-83 TJPRC Pvt. Ltd., STUDY OF THE PERFORMANCE OF THE LINEAR AND NON-LINEAR NARROW BAND RECEIVERS FOR 2X2
More informationB SCITEQ. Transceiver and System Design for Digital Communications. Scott R. Bullock, P.E. Third Edition. SciTech Publishing, Inc.
Transceiver and System Design for Digital Communications Scott R. Bullock, P.E. Third Edition B SCITEQ PUBLISHtN^INC. SciTech Publishing, Inc. Raleigh, NC Contents Preface xvii About the Author xxiii Transceiver
More informationDigital Communications I: Modulation and Coding Course. Term Catharina Logothetis Lecture 12
Digital Communications I: Modulation and Coding Course Term 3-8 Catharina Logothetis Lecture Last time, we talked about: How decoding is performed for Convolutional codes? What is a Maximum likelihood
More information6. FUNDAMENTALS OF CHANNEL CODER
82 6. FUNDAMENTALS OF CHANNEL CODER 6.1 INTRODUCTION The digital information can be transmitted over the channel using different signaling schemes. The type of the signal scheme chosen mainly depends on
More informationRobust MMSE Tomlinson-Harashima Precoder for Multiuser MISO Downlink with Imperfect CSI
Robust MMSE Tomlinson-Harashima Precoder for Multiuser MISO Downlink with Imperfect CSI P. Ubaidulla and A. Chockalingam Department of ECE, Indian Institute of Science, Bangalore 560012, INDIA Abstract
More informationTowards 100G over Copper
IEEE 8.3 Higher Speed Study Group Towards G over Copper Faculty Investigator: Dr. M. Kavehrad Graduate Researchers: Mr. A. Enteshari Mr. J. Fadlullah The Pennsylvania State University Center for Information
More informationSystem analysis and signal processing
System analysis and signal processing with emphasis on the use of MATLAB PHILIP DENBIGH University of Sussex ADDISON-WESLEY Harlow, England Reading, Massachusetts Menlow Park, California New York Don Mills,
More informationMIMO Interference Management Using Precoding Design
MIMO Interference Management Using Precoding Design Martin Crew 1, Osama Gamal Hassan 2 and Mohammed Juned Ahmed 3 1 University of Cape Town, South Africa martincrew@topmail.co.za 2 Cairo University, Egypt
More informationPerformance Analysis of Maximum Likelihood Detection in a MIMO Antenna System
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 2, FEBRUARY 2002 187 Performance Analysis of Maximum Likelihood Detection in a MIMO Antenna System Xu Zhu Ross D. Murch, Senior Member, IEEE Abstract In
More informationHardware implementation of Zero-force Precoded MIMO OFDM system to reduce BER
Hardware implementation of Zero-force Precoded MIMO OFDM system to reduce BER Deepak Kumar S Nadiger 1, Meena Priya Dharshini 2 P.G. Student, Department of Electronics & communication Engineering, CMRIT
More informationTHE computational complexity of optimum equalization of
214 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 2, FEBRUARY 2005 BAD: Bidirectional Arbitrated Decision-Feedback Equalization J. K. Nelson, Student Member, IEEE, A. C. Singer, Member, IEEE, U. Madhow,
More informationLayered Space-Time Codes
6 Layered Space-Time Codes 6.1 Introduction Space-time trellis codes have a potential drawback that the maximum likelihood decoder complexity grows exponentially with the number of bits per symbol, thus
More informationCompound precoding: a pre-equalisation technique for the bandlimited Gaussian channel M.F. Flanagan 1 M. McLaughlin 2 A.D. Fagan 1
Published in IET Communications Received on 30th July 2008 Revised on 13th February 2009 ISSN 1751-8628 Compound precoding: a pre-equalisation technique for the bandlimited Gaussian channel M.F. Flanagan
More informationWITH the introduction of space-time codes (STC) it has
IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 59, NO. 6, JUNE 2011 2809 Pragmatic Space-Time Trellis Codes: GTF-Based Design for Block Fading Channels Velio Tralli, Senior Member, IEEE, Andrea Conti, Senior
More informationPerformance Evaluation of different α value for OFDM System
Performance Evaluation of different α value for OFDM System Dr. K.Elangovan Dept. of Computer Science & Engineering Bharathidasan University richirappalli Abstract: Orthogonal Frequency Division Multiplexing
More informationSPACE-TIME coding techniques are widely discussed to
1214 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 4, NO. 3, MAY 2005 Some Super-Orthogonal Space-Time Trellis Codes Based on Non-PSK MTCM Aijun Song, Student Member, IEEE, Genyuan Wang, and Xiang-Gen
More informationCourse Specifications
Development Cluster Computer and Networking Engineering (CNE) Cluster Lead Developer Amir Asif Module Names Module 1: Baseband and Bandpass Communications (40 characters or less Module 2: Channel Coding
More informationConvolutional Coding Using Booth Algorithm For Application in Wireless Communication
Available online at www.interscience.in Convolutional Coding Using Booth Algorithm For Application in Wireless Communication Sishir Kalita, Parismita Gogoi & Kandarpa Kumar Sarma Department of Electronics
More informationSyllabus. osmania university UNIT - I UNIT - II UNIT - III CHAPTER - 1 : INTRODUCTION TO DIGITAL COMMUNICATION CHAPTER - 3 : INFORMATION THEORY
i Syllabus osmania university UNIT - I CHAPTER - 1 : INTRODUCTION TO Elements of Digital Communication System, Comparison of Digital and Analog Communication Systems. CHAPTER - 2 : DIGITAL TRANSMISSION
More informationDigital Communication Systems Engineering with
Digital Communication Systems Engineering with Software-Defined Radio Di Pu Alexander M. Wyglinski ARTECH HOUSE BOSTON LONDON artechhouse.com Contents Preface xiii What Is an SDR? 1 1.1 Historical Perspective
More informationNONCOHERENT detection of digital signals is an attractive
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 47, NO. 9, SEPTEMBER 1999 1303 Noncoherent Sequence Detection of Continuous Phase Modulations Giulio Colavolpe, Student Member, IEEE, and Riccardo Raheli, Member,
More informationTHE Shannon capacity of state-dependent discrete memoryless
1828 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 52, NO. 5, MAY 2006 Opportunistic Orthogonal Writing on Dirty Paper Tie Liu, Student Member, IEEE, and Pramod Viswanath, Member, IEEE Abstract A simple
More informationA Capacity Achieving and Low Complexity Multilevel Coding Scheme for ISI Channels
A Capacity Achieving and Low Complexity Multilevel Coding Scheme for ISI Channels arxiv:cs/0511036v1 [cs.it] 8 Nov 2005 Mei Chen, Teng Li and Oliver M. Collins Dept. of Electrical Engineering University
More informationIndex. Cambridge University Press Fundamentals of Wireless Communication David Tse and Pramod Viswanath. Index.
ad hoc network 5 additive white Gaussian noise (AWGN) 29, 30, 166, 241 channel capacity 167 capacity-achieving AWGN channel codes 170, 171 packing spheres 168 72, 168, 169 channel resources 172 bandwidth
More informationThe Optimal Employment of CSI in COFDM-Based Receivers
The Optimal Employment of CSI in COFDM-Based Receivers Akram J. Awad, Timothy O Farrell School of Electronic & Electrical Engineering, University of Leeds, UK eenajma@leeds.ac.uk Abstract: This paper investigates
More informationNotes 15: Concatenated Codes, Turbo Codes and Iterative Processing
16.548 Notes 15: Concatenated Codes, Turbo Codes and Iterative Processing Outline! Introduction " Pushing the Bounds on Channel Capacity " Theory of Iterative Decoding " Recursive Convolutional Coding
More informationSystems. Advanced Radar. Waveform Design and Diversity for. Fulvio Gini, Antonio De Maio and Lee Patton. Edited by
Waveform Design and Diversity for Advanced Radar Systems Edited by Fulvio Gini, Antonio De Maio and Lee Patton The Institution of Engineering and Technology Contents Waveform diversity: a way forward to
More informationAdaptive Sequence Detection of Channel-Interleaved Trellis-Coded Modulation Signals over Multipath Fading ISI Channels
1/6 Adaptive Sequence Detection of Channel-Interleaved Trellis-Coded Modulation Signals over Multipath Fading ISI Channels Heung-No Lee and Gregory J. Pottie Electrical Engineering Department, University
More informationSynchronization in Digital Communications
Synchronization in Digital Communications Volume 1 Phase-, Frequency-Locked Loops, and Amplitude Control Heinrich Meyr Aachen University of Technology (RWTH) Gerd Ascheid CADIS GmbH, Aachen WILEY A Wiley-lnterscience
More informationDepartment of Electronic Engineering FINAL YEAR PROJECT REPORT
Department of Electronic Engineering FINAL YEAR PROJECT REPORT BEngECE-2009/10-- Student Name: CHEUNG Yik Juen Student ID: Supervisor: Prof.
More informationOutline. Communications Engineering 1
Outline Introduction Signal, random variable, random process and spectra Analog modulation Analog to digital conversion Digital transmission through baseband channels Signal space representation Optimal
More informationORTHOGONAL space time block codes (OSTBC) from
1104 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 55, NO. 3, MARCH 2009 On Optimal Quasi-Orthogonal Space Time Block Codes With Minimum Decoding Complexity Haiquan Wang, Member, IEEE, Dong Wang, Member,
More informationLinear block codes for frequency selective PLC channels with colored noise and multiple narrowband interference
Linear block s for frequency selective PLC s with colored noise and multiple narrowband interference Marc Kuhn, Dirk Benyoucef, Armin Wittneben University of Saarland, Institute of Digital Communications,
More informationTABLE OF CONTENTS CHAPTER TITLE PAGE
TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS i i i i i iv v vi ix xi xiv 1 INTRODUCTION 1 1.1
More informationPerformance Evaluation of Multiple Antenna Systems
University of Wisconsin Milwaukee UWM Digital Commons Theses and Dissertations December 2013 Performance Evaluation of Multiple Antenna Systems M-Adib El Effendi University of Wisconsin-Milwaukee Follow
More informationIMPROVED QR AIDED DETECTION UNDER CHANNEL ESTIMATION ERROR CONDITION
IMPROVED QR AIDED DETECTION UNDER CHANNEL ESTIMATION ERROR CONDITION Jigyasha Shrivastava, Sanjay Khadagade, and Sumit Gupta Department of Electronics and Communications Engineering, Oriental College of
More informationAdvanced Signal Processing and Digital Noise Reduction
Advanced Signal Processing and Digital Noise Reduction Advanced Signal Processing and Digital Noise Reduction Saeed V. Vaseghi Queen's University of Belfast UK ~ W I lilteubner L E Y A Partnership between
More informationA Sphere Decoding Algorithm for MIMO
A Sphere Decoding Algorithm for MIMO Jay D Thakar Electronics and Communication Dr. S & S.S Gandhy Government Engg College Surat, INDIA ---------------------------------------------------------------------***-------------------------------------------------------------------
More informationOn the Design of Finite-State Shaping Encoders for Partial-Response Channels
On the Design of Finite-State Shaping Encoders for Partial-Response Channels Joseph B. Soriaga 2 and Paul H. Siegel Center for Magnetic Recording Research University of California, San Diego Information
More informationAdvances in Direction-of-Arrival Estimation
Advances in Direction-of-Arrival Estimation Sathish Chandran Editor ARTECH HOUSE BOSTON LONDON artechhouse.com Contents Preface xvii Acknowledgments xix Overview CHAPTER 1 Antenna Arrays for Direction-of-Arrival
More informationQUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61)
QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61) Module 1 1. Explain Digital communication system with a neat block diagram. 2. What are the differences between digital and analog communication systems?
More informationModulation and Coding Tradeoffs
0 Modulation and Coding Tradeoffs Contents 1 1. Design Goals 2. Error Probability Plane 3. Nyquist Minimum Bandwidth 4. Shannon Hartley Capacity Theorem 5. Bandwidth Efficiency Plane 6. Modulation and
More informationDigital Signal Processing
Digital Signal Processing System Analysis and Design Paulo S. R. Diniz Eduardo A. B. da Silva and Sergio L. Netto Federal University of Rio de Janeiro CAMBRIDGE UNIVERSITY PRESS Preface page xv Introduction
More informationChannel Estimation for MIMO-OFDM Systems Based on Data Nulling Superimposed Pilots
Channel Estimation for MIMO-O Systems Based on Data Nulling Superimposed Pilots Emad Farouk, Michael Ibrahim, Mona Z Saleh, Salwa Elramly Ain Shams University Cairo, Egypt {emadfarouk, michaelibrahim,
More informationOptical Intensity-Modulated Direct Detection Channels: Signal Space and Lattice Codes
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 49, NO. 6, JUNE 2003 1385 Optical Intensity-Modulated Direct Detection Channels: Signal Space and Lattice Codes Steve Hranilovic, Student Member, IEEE, and
More informationOFDM and MC-CDMA A Primer
OFDM and MC-CDMA A Primer L. Hanzo University of Southampton, UK T. Keller Analog Devices Ltd., Cambridge, UK IEEE PRESS IEEE Communications Society, Sponsor John Wiley & Sons, Ltd Contents About the Authors
More informationCapacity-Approaching Bandwidth-Efficient Coded Modulation Schemes Based on Low-Density Parity-Check Codes
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 49, NO. 9, SEPTEMBER 2003 2141 Capacity-Approaching Bandwidth-Efficient Coded Modulation Schemes Based on Low-Density Parity-Check Codes Jilei Hou, Student
More information