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

By: Zarrinkoub, Houman.
Material type: materialTypeLabelBookSeries: Wiley Desktop Editions: Publisher: Chichester, West Sussex, United Kingdom : John Wiley & * Sons, Inc., [2014]Description: 1 online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781118443453; 1118443454; 9781118443439; 1118443438; 9781118443446; 1118443446; 1118443411; 9781118443415.Subject(s): MATLAB | Long-Term Evolution (Telecommunications) -- Computer simulation | Long-Term Evolution (Telecommunications) -- Computer simulation | TECHNOLOGY & ENGINEERING -- Mobile & Wireless CommunicationsGenre/Form: Electronic books. | Electronic books.Additional physical formats: Print version:: Understanding LTE with MATLAB.DDC classification: 621.3845/6 Other classification: TEC061000 Online resources: Wiley Online Library
Contents:
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.
Summary: "An introduction to the technical details related to physical layer modeling of the LTE standard with MATLAB"-- Provided by publisher.
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"An introduction to the technical details related to physical layer modeling of the LTE standard with MATLAB"-- Provided by publisher.

Includes bibliographical references and index.

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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.

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