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ویرایش:
نویسندگان: Houman Zarrinkoub
سری:
ISBN (شابک) : 9781118443415
ناشر: Wiley
سال نشر: 2014
تعداد صفحات: 510
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 9 مگابایت
در صورت ایرانی بودن نویسنده امکان دانلود وجود ندارد و مبلغ عودت داده خواهد شد
در صورت تبدیل فایل کتاب Understanding LTE with MATLAB: From Mathematical Modeling to Simulation and Prototyping به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب Understanding LTE با MATLAB: از مدل سازی ریاضی تا شبیه سازی و نمونه سازی نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
LTE (تکامل طولانی مدت) و LTE-Advanced از جدیدترین استانداردهای ارتباطات سیار هستند که برای تحقق رویای یک فناوری دسترسی پهن باند تلفن همراه واقعاً جهانی، سریع، مبتنی بر تمام IP و ایمن طراحی شده اند. این کتاب لایه فیزیکی (PHY) استانداردهای LTE را با ترکیب سه عنصر مفهومی بررسی میکند: مروری بر نظریه پشت فنآوریهای کلیدی فعال. بحث مختصر در مورد مشخصات استاندارد؛ و الگوریتم های متلب مورد نیاز برای شبیه سازی استاندارد. استفاده از متلب، یک زبان محاسبات فنی پرکاربرد، یکی از ویژگی های متمایز این کتاب است. نویسنده از طریق مجموعهای از برنامههای MATLAB، هر یک از فناوریهای فعالکننده را بررسی میکند، مدل سیستم LTE PHY را به صورت آموزشی ترکیب میکند و عملکرد سیستم را در هر مرحله ارزیابی میکند. با پیروی از این فرآیند گام به گام، خوانندگان به درک عمیق تری از مفاهیم و مشخصات LTE از طریق شبیه سازی دست خواهند یافت.
The LTE (Long Term Evolution) and LTE-Advanced are among the latest mobile communications standards, designed to realize the dream of a truly global, fast, all-IP-based, secure broadband mobile access technology. This book examines the Physical Layer (PHY) of the LTE standards by incorporating three conceptual elements: an overview of the theory behind key enabling technologies; a concise discussion regarding standard specifications; and the MATLAB algorithms needed to simulate the standard. The use of MATLAB, a widely used technical computing language, is one of the distinguishing features of this book. Through a series of MATLAB programs, the author explores each of the enabling technologies, pedagogically synthesizes an LTE PHY system model, and evaluates system performance at each stage. Following this step-by-step process, readers will achieve deeper understanding of LTE concepts and specifications through simulations.
Cover S Title UNDERSTANDING LTE WITH MATLAB® FROM MATHEMATICAL MODELING TO SIMULATION AND PROTOTYPING Copyright © 2014, John Wiley & Sons, Ltd ISBN 978-1-118-44341-5 TK5103.48325.Z37 2014 621.3845\'6–dc23 LCCN 2013034138 Contents Preface List of Abbreviations Chapter 1 Introduction 1.1 Quick Overview of Wireless Standards 1.2 Historical Profile of Data Rates 1.3 IMT-Advanced Requirements 1.4 3GPP and LTE Standardization 1.5 LTE Requirements 1.6 Theoretical Strategies 1.7 LTE-Enabling Technologies 1.7.1 OFDM 1.7.2 SC-FDM 1.7.3 MIMO 1.7.4 Turbo Channel Coding 1.7.5 Link Adaptation 1.8 LTE Physical Layer (PHY) Modeling 1.9 LTE (Releases 8 and 9) 1.10 LTE-Advanced (Release 10) 1.11 MATLAB® and Wireless System Design 1.12 Organization of This Book References Chapter 2 Overview of the LTE Physical Layer 2.1 Air Interface 2.2 Frequency Bands 2.3 Unicast and Multicast Services 2.4 Allocation of Bandwidth 2.5 Time Framing 2.6 Time-Frequency Representation 2.7 OFDM Multicarrier Transmission 2.7.1 Cyclic Prefix 2.7.2 Subcarrier Spacing 2.7.3 Resource Block Size 2.7.4 Frequency-Domain Scheduling 2.7.5 Typical Receiver Operations 2.8 Single-Carrier Frequency Division Multiplexing 2.9 Resource Grid Content 2.10 Physical Channels 2.10.1 Downlink Physical Channels 2.10.2 Function of Downlink Channels 2.10.3 Uplink Physical Channels 2.10.4 Function of Uplink Channels 2.11 Physical Signals 2.11.1 Reference Signals 2.11.2 Synchronization Signals 2.12 Downlink Frame Structures 2.13 Uplink Frame Structures 2.14 MIMO 2.14.1 Receive Diversity 2.14.2 Transmit Diversity 2.14.3 Spatial Multiplexing 2.14.4 Beam Forming 2.14.5 Cyclic Delay Diversity 2.15 MIMO Modes 2.16 PHY Processing 2.17 Downlink Processing 2.18 Uplink Processing 2.18.1 SC-FDM 2.18.2 MU-MIMO 2.19 Chapter Summary References Chapter 3 MATLAB® for Communications System Design 3.1 System Development Workflow 3.2 Challenges and Capabilities 3.3 Focus 3.4 Approach 3.5 PHY Models in MATLAB 3.6 MATLAB 3.7 MATLAB Toolboxes 3.8 Simulink 3.9 Modeling and Simulation 3.9.1 DSP System Toolbox 3.9.2 Communications System Toolbox 3.9.3 Parallel Computing Toolbox 3.9.4 Fixed-Point Designer 3.10 Prototyping and Implementation 3.10.1 MATLAB Coder 3.10.2 Hardware Implementation 3.11 Introduction to System Objects 3.11.1 System Objects of the Communications System Toolbox 3.11.2 Test Benches with System Objects 3.11.3 Functions with System Objects 3.11.4 Bit Error Rate Simulation 3.12 MATLAB Channel Coding Examples 3.12.1 Error Correction and Detection 3.12.2 Convolutional Coding 3.12.3 Hard-Decision Viterbi Decoding 3.12.4 Soft-Decision Viterbi Decoding 3.12.5 Turbo Coding 3.13 Chapter Summary References Chapter 4 Modulation and Coding 4.1 Modulation Schemes of LTE 4.1.1 MATLAB Examples 4.1.2 BER Measurements 4.2 Bit-Level Scrambling 4.2.1 MATLAB Examples 4.2.2 BER Measurements 4.3 Channel Coding 4.4 Turbo Coding 4.4.1 Turbo Encoders 4.4.2 Turbo Decoders 4.4.3 MATLAB Examples 4.4.4 BER Measurements 4.5 Early-Termination Mechanism 4.5.1 MATLAB Examples 4.5.2 BER Measurements 4.5.3 Timing Measurements 4.6 Rate Matching 4.6.1 MATLAB Examples 4.6.2 BER Measurements 4.7 Codeblock Segmentation 4.7.1 MATLAB Examples 4.8 LTE Transport-Channel Processing 4.8.1 MATLAB Examples 4.8.2 BER Measurements 4.9 Chapter Summary References Chapter 5 OFDM 5.1 Channel Modeling 5.1.1 Large-Scale and Small-Scale Fading 5.1.2 Multipath Fading Effects 5.1.3 Doppler Effects 5.1.4 MATLAB® Examples 5.2 Scope 5.3 Workflow 5.4 OFDM and Multipath Fading 5.5 OFDM and Channel-Response Estimation 5.6 Frequency-Domain Equalization 5.7 LTE Resource Grid 5.8 Configuring the Resource Grid 5.8.1 CSR Symbols 5.8.2 DCI Symbols 5.8.3 BCH Symbols 5.8.4 Synchronization Symbols 5.8.5 User-Data Symbols 5.9 Generating Reference Signals 5.10 Resource Element Mapping 5.11 OFDM Signal Generation 5.12 Channel Modeling 5.13 OFDM Receiver 5.14 Resource Element Demapping 5.15 Channel Estimation 5.16 Equalizer Gain Computation 5.17 Visualizing the Channel 5.18 Downlink Transmission Mode 1 5.18.1 The SISO Case 5.18.2 The SIMO Case 5.19 Chapter Summary References Chapter 6 MIMO 6.1 Definition of MIMO 6.2 Motivation for MIMO 6.3 Types of MIMO 6.3.1 Receiver-Combining Methods 6.3.2 Transmit Diversity 6.3.3 Spatial Multiplexing 6.4 Scope of MIMO Coverage 6.5 MIMO Channels 6.5.1 MATLAB® Implementation 6.5.2 LTE-Specific Channel Models 6.5.3 MATLAB Implementation 6.5.4 Initializing MIMO Channels 6.5.5 Adding AWGN 6.6 Common MIMO Features 6.6.1 MIMO Resource Grid Structure 6.6.2 Resource-Element Mapping 6.6.3 Resource-Element Demapping 6.6.4 CSR-Based Channel Estimation 6.6.5 Channel-Estimation Function 6.6.6 Channel-Estimate Expansion 6.6.7 Ideal Channel Estimation 6.6.8 Channel-Response Extraction 6.7 Specific MIMO Features 6.7.1 Transmit Diversity 6.7.2 Transceiver Setup Functions 6.7.3 Downlink Transmission Mode 2 6.7.4 Spatial Multiplexing 6.7.5 MIMO Operations in Spatial Multiplexing 6.7.6 Downlink Transmission Mode 4 6.7.7 Open-Loop Spatial Multiplexing 6.7.8 Downlink Transmission Mode 3 6.8 Chapter Summary References Chapter 7 Link Adaptation 7.1 System Model 7.2 Link Adaptation in LTE 7.2.1 Channel Quality Estimation 7.2.2 Precoder Matrix Estimation 7.2.3 Rank Estimation 7.3 MATLAB® Examples 7.3.1 CQI Estimation 7.3.2 PMI Estimation 7.3.3 RI Estimation 7.4 Link Adaptations between Subframes 7.4.1 Structure of the Transceiver Model 7.4.2 Updating Transceiver Parameter Structures 7.5 Adaptive Modulation 7.5.1 No Adaptation 7.5.2 Changing the Modulation Scheme at Random 7.5.3 CQI-Based Adaptation 7.5.4 Verifying Transceiver Performance 7.5.5 Adaptation Results 7.6 Adaptive Modulation and Coding Rate 7.6.1 No Adaptation 7.6.2 Changing Modulation Scheme at Random 7.6.3 CQI-Based Adaptation 7.6.4 Verifying Transceiver Performance 7.6.5 Adaptation Results 7.7 Adaptive Precoding 7.7.1 PMI-Based Adaptation 7.7.2 Verifying Transceiver Performance 7.7.3 Adaptation Results 7.8 Adaptive MIMO 7.8.1 RI-Based Adaptation 7.8.2 Verifying Transceiver Performance 7.8.3 Adaptation Results 7.9 Downlink Control Information 7.9.1 MCS 7.9.2 Rate of Adaptation 7.9.3 DCI Processing 7.10 Chapter Summary References Chapter 8 System-Level Specification 8.1 System Model 8.1.1 Transmitter Model 8.1.2 MATLAB Model for a Transmitter Model 8.1.3 Channel Model 8.1.4 MATLAB Model for a Channel Model 8.1.5 Receiver Model 8.1.6 MATLAB Model for a Receiver Model 8.2 System Model in MATLAB 8.3 Quantitative Assessments 8.3.1 Effects of Transmission Modes 8.3.2 BER as a Function of SNR 8.3.3 Effects of Channel-Estimation Techniques 8.3.4 Effects of Channel Models 8.3.5 Effects of Channel Delay Spread and Cyclic Prefix 8.3.6 Effects of MIMO Receiver Algorithms 8.4 Throughput Analysis 8.5 System Model in Simulink 8.5.1 Building a Simulink Model 8.5.2 Integrating MATLAB Algorithms in Simulink 8.5.3 Parameter Initialization 8.5.4 Running the Simulation 8.5.5 Introducing a Parameter Dialog 8.6 Qualitative Assessment 8.6.1 Voice-Signal Transmission 8.6.2 Subjective Voice-Quality Testing 8.7 Chapter Summary References Chapter 9 Simulation 9.1 Speeding Up Simulations in MATLAB 9.2 Workflow 9.3 Case Study: LTE PDCCH Processing 9.4 Baseline Algorithm 9.5 MATLAB Code Profiling 9.6 MATLAB Code Optimizations 9.6.1 Vectorization 9.6.2 Preallocation 9.6.3 System Objects 9.7 Using Acceleration Features 9.7.1 MATLAB-to-C Code Generation 9.7.2 Parallel Computing 9.8 Using a Simulink Model 9.8.1 Creating the Simulink Model 9.8.2 Verifying Numerical Equivalence 9.8.3 Simulink Baseline Model 9.8.4 Optimizing the Simulink Model 9.9 GPU Processing 9.9.1 Setting up GPU Functionality in MATLAB 9.9.2 GPU-Optimized System Objects 9.9.3 Using a Single GPU System Object 9.9.4 Combining Parallel Processing with GPUs 9.10 Case Study: Turbo Coders on GPU 9.10.1 Baseline Algorithm on a CPU 9.10.2 Turbo Decoder on a GPU 9.10.3 Multiple System Objects on GPU 9.10.4 Multiple Frames and Large Data Sizes 9.10.5 Using Single-Precision Data Type 9.11 Chapter Summary Chapter 10 Prototyping as C/C++ Code 10.1 Use Cases 10.2 Motivations 10.3 Requirements 10.4 MATLAB Code Considerations 10.5 How to Generate Code 10.5.1 Case Study: Frequency-Domain Equalization 10.5.2 Using a MATLAB Command 10.5.3 Using the MATLAB Coder Project 10.6 Structure of the Generated C Code 10.7 Supported MATLAB Subset 10.7.1 Readiness for Code Generation 10.7.2 Case Study: Interpolation of Pilot Signals 10.8 Complex Numbers and Native C Types 10.9 Support for System Toolboxes 10.9.1 Case Study: FFT and Inverse FFT 10.10 Support for Fixed-Point Data 10.10.1 Case Study: FFT Function 10.11 Support for Variable-Sized Data 10.11.1 Case Study: Adaptive Modulation 10.11.2 Fixed-sized Code Generation 10.11.3 Bounded Variable-Sized Data 10.11.4 Unbounded Variable-Sized Data 10.12 Integration with Existing C/C++ Code 10.12.1 Algorithm 10.12.2 Executing MATLAB Testbench 10.12.3 Generating C Code 10.12.4 Entry-Point Functions in C 10.12.5 C Main Function 10.12.6 Compiling and Linking 10.12.7 Executing C Testbench 10.13 Chapter Summary References Chapter 11 Summary 11.1 Modeling 11.1.1 Theoretical Considerations 11.1.2 Standard Specifications 11.1.3 Algorithms in MATLAB® 11.2 Simulation 11.2.1 Simulation Acceleration 11.2.2 Acceleration Methods 11.2.3 Implementation 11.3 Directions for Future Work 11.3.1 User-Plane Details 11.3.2 Control-Plane Processing 11.3.3 Hybrid Automatic Repeat Request 11.3.4 System-Access Modules 11.4 Concluding Remarks Index