Understanding LTE with MATLAB : from mathematical foundation to simulation, performance evaluation and implementation /

• Κύριος συγγραφέας: Zarrinkoub, Houman
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Chichester, West Sussex, United Kingdom : John Wiley & * Sons, Inc., [2014]
• Σειρά: Wiley Desktop Editions.
• Θέματα: MATLAB.; Long-Term Evolution (Telecommunications) > Computer simulation.; TECHNOLOGY & ENGINEERING > Mobile & Wireless Communications.; Electronic books.

"An introduction to the technical details related to physical layer modeling of the LTE standard with MATLAB"--

Πίνακας περιεχομένων:

• 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
• 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
• 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
• 5.1. Channel Modeling
• 5.1.1. Large-Scale and Small-Scale Fading
• 5.1.2. Multipath Fading Effects
• 5.1.3. Doppler Ejects
• 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
• 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
• 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. Bank 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
• 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
• 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
• 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
• 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.