UNDERSTANDING LTE WITH MATLAB
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1 UNDERSTANDING LTE WITH MATLAB FROM MATHEMATICAL MODELING TO SIMULATION AND PROTOTYPING Dr Houman Zarrinkoub MathWorks, Massachusetts, USA WILEY
2 Contents Preface List of Abbreviations 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 OFDM SC-FDM M1MO Turbo Channel Coding 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 Desig 1.12 Organization of This Book References 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 Cyclic Prefix Subcarrier Spacing
3 2.7.3 Resource Block Size Frequency-Domain Scheduling Typical Receiver Operations 2.8 Single-Carrier Frequency Division Multiplexing 2.9 Resource Grid Content 2.10 Physical Channels Downlink Physical Channels Function of Downlink Channels Uplink Physical Channels Function of Uplink Channels 2.11 Physical Signals Reference Signals Synchronization Signals 2.12 Downlink Frame Structures 2.13 Uplink Frame Structures 2.14 MIMO Receive Diversity Transmit Diversity Spatial Multiplexing Beam Forming Cyclic Delay Diversity 2.15 MIMO Modes 2.16 PHY Processing 2.17 Downlink Processing 2.18 Uplink Processing SC-FDM MU-M1MO 2.19 Chapter Summary References (S) 3 MATLAB for Communications System Desig 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 DSP System Toolbox Communications System Toolbox Parallel Computing Toolbox Fixed-Point Designer
4 Contents Vll 3.10 Prototyping and Implementation MATLAB Coder Hardware Implementation Introduction to System Objects System Objects of the Communications System Toolbox Test Benches with System Objects Functions with System Objects Bit Error Rate Simulation MATLAB Channel Coding Examples Error Correction and Detection Convolutional Coding Hard-Decision Viterbi Decoding Soft-Decision Viterbi Decoding Turbo Coding Chapter Summary 68 References 69 4 Modulation and Coding Modulation Schemes of LTE MATLAB Examples BER Measurements Bit-Level Scrambling MATLAB Examples BER Measurements Channel Coding Turbo Coding Turbo Encoders Turbo Decoders MATLAB Examples BER Measurements Early-Termination Mechanism MATLAB Examples BER Measurements Timing Measurements Rate Matching MATLAB Examples BER Measurements Codeblock Segmentation MATLAB Examples LTE Transport-Channel Processing MATLAB Examples BER Measurements Chapter Summary 112 References 113
5 viii Contents OFDM Channel Modeling Large-Scale and Small-Scale Fading Multipath Fading Effects Doppler Effects MATLAB Examples Scope Workflow OFDM and Multipath Fading OFDM and Channel-Response Estimation Frequency-Domain Equalization LTE Resource Grid Configuring the Resource Grid CSR Symbols DCI Symbols BCH Symbols Synchronization Symbols User-Data Symbols Generating Reference Signals Resource Element Mapping OFDM Signal Generation Channel Modeling OFDM Receiver Resource Element Demapping Channel Estimation Equalizer Gain Computation Visualizing the Channel Downlink Transmission Mode The SISO Case The SIMO Case Chapter S ummary 164 References MIMO Definition of MIMO Motivation for MIMO Types of MIMO Receiver-Combining Methods Transmit Diversity Spatial Multiplexing Scope of MIMO Coverage MIMO Channels MATLAB Implementation LTE-Specific Channel Models MATLAB Implementation 175
6 Contents ix Initializing MIMO Channels Adding AWGN Common MIMO Features MIMO Resource Grid Structure Resource-Element Mapping Resource-Element Demapping CSR-Based Channel Estimation Channel-Estimation Function Channel-Estimate Expansion Ideal Channel Estimation Channel-Response Extraction Specific MIMO Features Transmit Diversity Transceiver Setup Functions Downlink Transmission Mode Spatial Multiplexing MIMO Operations in Spatial Multiplexing Downlink Transmission Mode Open-Loop Spatial Multiplexing Downlink Transmission Mode Chapter Summary 260 References Link Adaptation System Model Link Adaptation in LTE Channel Quality Estimation Pre coder Matrix Estimation Rank Estimation MATLAB Examples CQI Estimation PMI Estimation RI Estimation 27'1 7.4 Link Adaptations between Subframes Structure of the Transceiver Model Updating Transceiver Parameter Structures Adaptive Modulation No Adaptation Changing the Modulation Scheme at Random CQI-Based Adaptation Verifying Transceiver Performance Adaptation Results Adaptive Modulation and Coding Rate No Adaptation Changing Modulation Scheme at Random J CQI-Based Adaptation 284
7 X Contents Verifying Transceiver Performance Adaptation Results Adaptive Precoding PMI-Based Adaptation Verifying Transceiver Performance Adaptation Results Adaptive MIMO RI-Based Adaptation Verifying Transceiver Performance Adaptation Results Downlink Control Information MCS Rate of Adaptation DC1Processing Chapter Summary 302 References System-Level Specification System Model Transmitter Model MATLAB Model for a Transmitter Model Channel Model MATLAB Model for a Channel Model Receiver Model MATLAB Model for a Receiver Model System Model in MATLAB Quantitative Assessments Effects of Transmission Modes BER as a Function of SNR Effects of Channel-Estimation Techniques Effects of Channel Models Effects of Channel Delay Spread and Cyclic Prefix Effects of MIMO Receiver Algorithms Throughput Analysis System Model in Simulink Building a Simulink Model Integrating MATLAB Algorithms in Simulink Parameter Initialization Running the Simulation Introducing a Parameter Dialog Qualitative Assessment Voice-Signal Transmission Subjective Voice-Quality Testing Chapter Summary 351 References 352
8 Contents XI 9 Simulation Speeding Up Simulations in MATLAB Workflow Case Study: LTE PDCCH Processing Baseline Algorithm MATLAB Code Profiling MATLAB Code Optimizations Vectorization P reallocation System Objects Using Acceleration Features MATLAB-to-C Code Generation Parallel Computing Using a Simulink Model Creating the Simulink Model Verifying Numerical Equivalence Simulink Baseline Model Optimizing the Simulink Model GPU Processing Setting up GPU Functionality in MATLAB GPU-Optimized System Objects Using a Single GP U System Object Combining Parallel Processing with GPUs Case Study: Turbo Coders on GPU Baseline Algorithm on a CPU Turbo Decoder on a GPU Multiple System Objects on GPU Multiple Frames and Large Data Sizes Using Single-Precision Data Type Chapter Summary Prototyping as C/C++ Code Use Cases Motivations Requirements MATLAB Code Considerations How to Generate Code Case Study: Frequency-Domain Equalization Using a MATLAB Command Using the MATLAB Coder Project Structure of the Generated C Code Supported MATLAB Subset Readiness for Code Generation Case Study: Interpolation of Pilot Signals Complex Numbers and Native C Types 436
9 J Contents 10.9 Support for System Toolboxes Case Study: FFT and Inverse FFT Support for Fixed-Point Data Case Study: FFT Function Support for Variable-Sized Data Case Study: Adaptive Modulation Fixed-sized Code Generation Bounded Variable-Sized Data Unbounded Variable-Sized Data Integration with Existing C/C++ Code Algorithm Executing MATLAB Testbench Generating C Code Entry-Point Functions in C C Main Function Compiling and Linking Executing C Testbench Chapter Summary 471 References Summary Modeling Theoretical Considerations Al A Standard Specifications Al A Algorithms in MATLAB Al A 11.2 Simulation Simulation Acceleration Acceleration Methods All Implementation All 11.3 Directions for Future Work User-Plane Details Control-Plane Processing Hybrid Automatic Repeat Request System-Access Modules Concluding Remarks 480 Index 483
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