OFDM for underwater acoustic communications

OFDM for underwater acoustic communications /

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Bibliographic Details
Main Authors: Zhou, Shengli (Author), Wang, Zhaohui (Electrical engineer) (Author)
Corporate Author: Ebooks Corporation
Format: Electronic eBook
Language:English
Published: Chichester, West Sussex, United Kingdom : Wiley, 2014.
Subjects:
Underwater acoustic telemetry.
Orthogonal frequency division multiplexing.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
Table of Contents:
  • Machine generated contents note: 1. Introduction
  • 1.1. Background and Context
  • 1.1.1. Early Exploration of Underwater Acoustics
  • 1.1.2. Underwater Communication Media
  • 1.1.3. Underwater Systems and Networks
  • 1.2. UWA Channel Characteristics
  • 1.2.1. Sound Velocity
  • 1.2.2. Propagation Loss
  • 1.2.3. Time-Varying Multipath
  • 1.2.4. Acoustic Propagation Models
  • 1.2.5. Ambient Noise and External Interference
  • 1.3. Passband Channel Input--Output Relationship
  • 1.3.1. Linear Time-Varying Channel with Path-Specific Doppler Scales
  • 1.3.2. Linear Time-Varying Channels with One Common Doppler Scale
  • 1.3.3. Linear Time-Invariant Channel
  • 1.3.4. Linear Time-Varying Channel with Both Amplitude and Delay Variations
  • 1.3.5. Linear Time-Varying Channel with Frequency-Dependent Attenuation
  • 1.4. Modulation Techniques for UWA Communications
  • 1.4.1. Frequency Hopped FSK
  • 1.4.2. Direct Sequence Spread Spectrum
  • 1.4.3. Single Carrier Modulation
  • 1.4.4. Sweep-Spread Carrier (S2C) Modulation
  • 1.4.5. Multicarrier Modulation
  • 1.4.6. Multi-Input Multi-Output Techniques
  • 1.4.7. Recent Developments on Underwater Acoustic Communications
  • 1.5. Organization of the Book
  • 2. OFDM Basics
  • 2.1. Zero-Padded OFDM
  • 2.1.1. Transmitted Signal
  • 2.1.2. Receiver Processing
  • 2.2. Cyclic-Prefixed OFDM
  • 2.2.1. Transmitted Signal
  • 2.2.2. Receiver Processing
  • 2.3. OFDM Related Issues
  • 2.3.1. ZP-OFDM versus CP-OFDM
  • 2.3.2. Peak-to-Average-Power Ratio
  • 2.3.3. Power Spectrum and Bandwidth
  • 2.3.4. Subcarrier Assignment
  • 2.3.5. Overall Data Rate
  • 2.3.6. Design Guidelines
  • 2.4. Implementation via Discrete Fourier Transform
  • 2.5. Challenges and Remedies for OFDM
  • 2.5.1. Benefits of Diversity Combining and Channel Coding
  • 2.6. MIMO OFDM
  • 2.7. Bibliographical Notes
  • 3. Nonbinary LDPC Coded OFDM
  • 3.1. Channel Coding for OFDM
  • 3.1.1. Channel Coding
  • 3.1.2. Coded Modulation
  • 3.1.3. Coded OFDM
  • 3.2. Nonbinary LDPC Codes
  • 3.2.1. Nonbinary Regular Cycle Codes
  • 3.2.2. Nonbinary Irregular LDPC Codes
  • 3.3. Encoding
  • 3.4. Decoding
  • 3.4.1. Initialization
  • 3.4.2. Variable-to-Check-Node Update
  • 3.4.3. Check-to-Variable-Node Update
  • 3.4.4. Tentative Decision and Decoder Outputs
  • 3.5. Code Design
  • 3.5.1. Design of Regular Cycle codes
  • 3.5.2. Design of Irregular LDPC Codes
  • 3.5.3. Quasi-Cyclic Nonbinary LDPC codes
  • 3.6. Simulation Results of Coded OFDM
  • 3.7. Bibliographical Notes
  • 4. PAPR Control
  • 4.1. PAPR Comparison
  • 4.2. PAPR Reduction
  • 4.2.1. Clipping
  • 4.2.2. Selective Mapping
  • 4.2.3. Peak Reduction Subcarriers
  • 4.3. Bibliographical Notes
  • 5. Receiver Overview and Preprocessing
  • 5.1. OFDM Receiver Overview
  • 5.2. Receiver Preprocessing
  • 5.2.1. Receiver Preprocessing
  • 5.2.2. Digital Implementation
  • 5.2.3. Frequency-Domain Oversampling
  • 5.3. Frequency-Domain Input-Output Relationship
  • 5.3.1. Single-input Single-Output Channel
  • 5.3.2. Single-Input Multi-Output Channel
  • 5.3.3. Multi-Input Multi-Output Channel
  • 5.3.4. Channel Matrix Structure
  • 5.4. OFDM Receiver Categorization
  • 5.4.1. ICI-Ignorant Receiver
  • 5.4.2. ICI-Aware Receiver
  • 5.4.3. Block-by-Block Processing
  • 5.4.4. Block-to-Block Processing
  • 5.4.5. Discussion
  • 5.5. Receiver Performance Bound with Simulated Channels
  • 5.5.1. Simulating Underwater Acoustic Channels
  • 5.5.2. ICI Effect in Time-Varying Channels
  • 5.5.3. Outage Performance of SISO Channel
  • 5.6. Extension to CP-OFDM
  • 5.6.1. Receiver Preprocessing
  • 5.6.2. Frequency-Domain Input--Output Relationship
  • 5.7. Bibliographical Notes
  • 6. Detection, Synchronization and Doppler Scale Estimation
  • 6.1. Cross-Correlation Based Methods
  • 6.1.1. Cross-Correlation Based Detection
  • 6.1.2. Cross-Correlation Based Synchronization and Doppler Scale Estimation
  • 6.2. Detection, Synchronization and Doppler Scale Estimation with CP-OFDM
  • 6.2.1. CP-OFDM Preamble with Self-Repetition
  • 6.2.2. Self-Correlation Based Detection, Synchronization and Doppler Scale Estimation
  • 6.2.3. Implementation
  • 6.3. Synchronization and Doppler Scale Estimation for One ZP-OFDM Block
  • 6.3.1. Null-Subcarrier based Blind Estimation
  • 6.3.2. Pilot-Aided Estimation
  • 6.3.3. Decision-Aided Estimation
  • 6.4. Simulation Results for Doppler Scale Estimation
  • 6.4.1. RMSE Performance with CP-OFDM
  • 6.4.2. RMSE Performance with ZP-OFDM
  • 6.4.3. Comparison of Blind Methods of CP- and ZP-OFDM
  • 6.5. Design Examples in Practical Systems
  • 6.6. Residual Doppler Frequency Shift Estimation
  • 6.6.1. System Model after Resampling
  • 6.6.2. Impact of Residual Doppler Shift Compensation
  • 6.6.3. Two Residual Doppler Shift Estimation Methods
  • 6.6.4. Simulation Results
  • 6.7. Bibliographical Notes
  • 7. Channel and Noise Variance Estimation
  • 7.1. Problem Formulation for ICI-Ignorant Channel Estimation
  • 7.1.1. Input--Output Relationship
  • 7.1.2. Dictionary Based Formulation
  • 7.2. ICI-Ignorant Sparse Channel Sensing
  • 7.2.1. Dictionary Resolution versus Channel Sparsity
  • 7.2.2. Sparsity Factor
  • 7.2.3. Number of Pilots versus Number of Paths
  • 7.3. ICI-Aware Sparse Channel Sensing
  • 7.3.1. Problem Formulation
  • 7.3.2. ICI-Aware Channel Sensing
  • 7.3.3. Pilot Subcarrier Distribution
  • 7.3.4. Influence of Data Symbols
  • 7.4. Sparse Recovery Algorithms
  • 7.4.1. Matching Pursuit
  • 7.4.2. E1-Norm Minimization
  • 7.4.3. Matrix-Vector Multiplication via FFT
  • 7.4.4. Computational Complexity
  • 7.5. Extension to Multi-Input Channels
  • 7.5.1. ICI-Ignorant Sparse Channel Sensing
  • 7.5.2. ICI-Aware Sparse Channel Sensing
  • 7.6. Noise Variance Estimation
  • 7.7. Noise Prewhitening
  • 7.7.1. Noise Spectrum Estimation
  • 7.7.2. Whitening in the Frequency Domain
  • 7.8. Bibliographical Notes
  • 8. Data Detection
  • 8.1. Symbol-by-Symbol Detection in ICI-Ignorant OFDM Systems
  • 8.1.1. Single-Input Single-Output Channel
  • 8.1.2. Single-Input Multi-Output Channel
  • 8.2. Block-Based Data Detection in ICI-Aware OFDM Systems
  • 8.2.1. MAP Equalizer
  • 8.2.2. Linear MMSE Equalizer with A Priori Information
  • 8.2.3. Extension to the Single-Input Multi-Output Channel
  • 8.3. Data Detection for OFDM Systems with Banded ICI
  • 8.3.1. BCJR Algorithm and Log-MAP Implementation
  • 8.3.2. Factor-Graph Algorithm with Gaussian Message Passing
  • 8.3.3. Computations related to Gaussian Messages
  • 8.3.4. Extension to SIMO Channel
  • 8.4. Symbol Detectors for MIMO OFDM
  • 8.4.1. ICI-Ignorant MIMO OFDM
  • 8.4.2. Full-ICI Equalization
  • 8.4.3. Banded-ICI Equalization
  • 8.5. MCMC Method for Data Detection in MIMO OFDM
  • 8.5.1. MCMC Method for ICI-Ignorant MIMO Detection
  • 8.5.2. MCMC Method for Banded-ICI MIMO Detection
  • 8.6. Bibliographical Notes
  • 9. OFDM Receivers with Block-by-Block Processing
  • 9.1. Noniterative ICI-Ignorant Receiver
  • 9.1.1. Noniterative ICI-Ignorant Receiver Structure
  • 9.1.2. Simulation Results: ICI-Ignorant Receiver
  • 9.1.3. Experimental Results: ICI-Ignorant Receiver
  • 9.2. Noniterative ICI-Aware Receiver
  • 9.2.1. Noniterative ICI-Aware Receiver Structure
  • 9.2.2. Simulation Results: ICI-Aware Receiver
  • 9.2.3. Experimental Results: ICI-Aware Receiver
  • 9.3. Iterative Receiver Processing
  • 9.3.1. Iterative ICI-Ignorant Receiver
  • 9.3.2. Iterative ICI-Aware Receiver
  • 9.4. ICI-Progressive Receiver
  • 9.5. Simulation Results: ICI-Progressive Receiver
  • 9.6. Experimental Results: ICI-Progressive Receiver
  • 9.6.1. BLER Performance
  • 9.6.2. Environmental Impact
  • 9.6.3. Progressive versus Iterative ICI-Aware Receivers
  • 9.7. Discussion
  • 9.8. Bibliographical Notes
  • 10. OFDM Receiver with Clustered Channel Adaptation
  • 10.1. Illustration of Channel Dynamics
  • 10.2. Modeling Cluster-Based Block-to-Block Channel Variation
  • 10.3. Cluster-Adaptation Based Block-to-Block Receiver
  • 10.3.1. Cluster Offset Estimation and Compensation
  • 10.3.2. Cluster-Adaptation Based Sparse Channel Estimation
  • 10.3.3. Channel Re-estimation and Cluster Variance Update
  • 10.4. Experimental Results: MACE10
  • 10.4.1. BLER Performance with an Overall Resampling
  • 10.4.2. BLER Performance with Refined Resampling
  • 10.5. Experimental Results: SPACE08
  • 10.6. Discussion
  • 10.7. Bibliographical Notes
  • 11. OFDM in Deep Water Horizontal Communications
  • 11.1. System Model for Deep Water Horizontal Communications
  • 11.1.1. Transmitted Signal
  • 11.1.2. Modeling Clustered Multipath Channel
  • 11.1.3. Received Signal
  • 11.2. Decision-Feedback Based Receiver Design
  • 11.3. Factor-Graph Based Joint IBI/ICI Equalization
  • 11.3.1. Probabilistic Problem Formulation
  • 11.3.2. Factor-Graph Based Equalization
  • 11.4. Iterative Block-to-Block Receiver Processing
  • 11.5. Simulation Results
  • 11.6. Experimental Results in the AUTEC Environment
  • 11.7. Extension to Underwater Broadcasting Networks
  • 11.7.1. Underwater Broadcasting Networks
  • 11.7.2. Emulated Experimental Results: MACE10
  • 11.8. Bibliographical Notes
  • 12. OFDM Receiver with Parameterized External Interference Cancellation
  • 12.1. Interference Parameterization
  • 12.2. Iterative OFDM Receiver with Interference Cancellation
  • 12.2.1. Initialization
  • 12.2.2. Interference Detection and Estimation
  • 12.2.3. Channel Estimation, Equalization and Channel Decoding
  • Contents note continued: 12.2.4. Noise Variance Estimation
  • 12.3. Simulation Results
  • 12.3.1. Time-Invariant Channels
  • 12.3.2. Time-Varying Channels
  • 12.3.3. Performance of the Proposed Receiver with Different SIRs
  • 12.3.4. Interference Detection and Estimation
  • 12.4. Experimental Results: AUTEC10
  • 12.5. Emulated Results: SPACE08
  • 12.6. Discussion
  • 12.7. Bibliographical Notes
  • 13. Co-located MIMO OFDM
  • 13.1. ICI-Ignorant MIMO-OFDM System Model
  • 13.2. ICI-Ignorant MIMO-OFDM Receiver
  • 13.2.1. Noniterative ICI-Ignorant MIMO-OFDM Receiver
  • 13.2.2. Iterative ICI-Ignorant MIMO-OFDM Receiver
  • 13.3. Simulation Results: ICI-Ignorant MIMO OFDM
  • 13.4. SPACE08 Experimental Results: ICI-Ignorant MIMO OFDM
  • 13.5. ICI-Aware MIMO-OFDM System Model
  • 13.6. ICI-Progressive MIMO-OFDM Receiver
  • 13.6.1. Receiver Overview
  • 13.6.2. Sparse Channel Estimation and Noise Variance Estimation
  • 13.6.3. Joint ICI/CCI Equalization
  • 13.7. Simulation Results: ICI-Progressive MIMO OFDM
  • 13.8. SPACE08 Experiment: ICI-Progressive MIMO OFDM
  • 13.9. MACE10 Experiment: ICI-Progressive MIMO OFDM
  • 13.9.1. BLER Performance with Two Transmitters
  • 13.9.2. BLER Performance with Three and Four Transmitters
  • 13.10. Initialization for the ICI-Progressive MIMO OFDM
  • 13.11. Bibliographical Notes
  • 14. Distributed MIMO OFDM
  • 14.1. System Model
  • 14.2. Multiple-Resampling Front-End Processing
  • 14.3. Multiuser Detection (MUD) Based Iterative Receiver
  • 14.3.1. Pre-processing with Frequency-Domain Oversampling
  • 14.3.2. Joint Channel Estimation
  • 14.3.3. Multiuser Data Detection and Channel Decoding
  • 14.4. Single-User Detection (SUD) Based Iterative Receiver
  • 14.4.1. Single-User Decoding
  • 14.4.2. MUI Construction
  • 14.5. Emulated Two-User System Using MACE10 Data
  • 14.5.1. MUD-Based Receiver with and without Frequency-Domain Oversampling
  • 14.5.2. Performance of SUD- and MUD-Based Receivers
  • 14.6. Emulated MIMO OFDM with MACE10 and SPACE08 Data
  • 14.6.1. One Mobile Single-Transmitter User plus One Stationary Two-Transmitter User
  • 14.6.2. One Mobile Single-Transmitter User plus One Stationary Three-Transmitter User
  • 14.6.3. Two Mobile Single-Transmitter Users plus One Stationary Two-Transmitter User
  • 14.7. Bibliographical Notes
  • 15. Asynchronous Multiuser OFDM
  • 15.1. System Model for Asynchronous Multiuser OFDM
  • 15.2. Overlapped Truncation and Interference Aggregation
  • 15.2.1. Overlapped Truncation
  • 15.2.2. Interference Aggregation
  • 15.3. Asynchronous Multiuser OFDM Receiver
  • 15.3.1. Overall Receiver Structure
  • 15.5.2. Interblock Interference Subtraction
  • 15.3.3. Time-to-Frequency-Domain Conversion
  • 15.3.4. Iterative Multiuser Reception and Residual Interference Cancellation
  • 15.3.5. Interference Reconstruction
  • 15.4. Investigation on Multiuser Asynchronism in an Example Network
  • 15.5. Simulation Results
  • 15.5.1. Two-User Systems with Time-Varying Channels
  • 15.5.2. Multiuser Systems with Time-Invariant Channels
  • 15.6. Emulated Results: MACE10
  • 15.7. Bibliographical Notes
  • 16. OFDM in Relay Channels
  • 16.1. Dynamic Coded Cooperation in a Single-Relay Network
  • 16.1.1. Relay Operations
  • 16.1.2. Receiver Processing at the Destination
  • 16.1.3. Discussion
  • 16.2. Design Example Based on Rate-Compatible Channel Coding
  • 16.2.1. Code Design
  • 16.2.2. Simulation Results
  • 16.3. Design Example Based on Layered Erasure- and Error-Correction Coding
  • 16.3.1. Code Design
  • 16.3.2. Implementation
  • 16.3.3. Experiment in Swimming Pool
  • 16.3.4. Sea Experiment
  • 16.4. Dynamic Block Cycling over a Line Network
  • 16.4.1. Hop-by-Hop Relay and Turbo Relay
  • 16.4.2. Dynamic Block-Cycling Transmissions
  • 16.4.3. Discussion
  • 16.5. Bibliographical Notes
  • 17. OFDM-Modulated Physical-Layer Network Coding
  • 17.1. System Model for the OFDM-Modulated PLNC
  • 17.2. Three Iterative OFDM Receivers
  • 17.2.1. Iterative Separate Detection and Decoding
  • 17.2.2. Iterative XOR-ed PLNC Detection and Decoding
  • 17.2.3. Iterative Generalized PLNC Detection and Decoding
  • 17.3. Outage Probability Bounds in Time-Invariant Channels
  • 17.4. Simulation Results
  • 17.4.1. Single-Path Time-Invariant Channel
  • 17.4.2. Multipath Time-Invariant Channel
  • 17.4.3. Multipath Time-Varying Channel
  • 17.5. Experimental Results: SPACE08
  • 17.6. Bibliographical Notes
  • 18. OFDM Modem Development
  • 18.1. Components of an Acoustic Modem
  • 18.2. OFDM Acoustic Modem in Air
  • 18.3. OFDM Lab Modem
  • 18.4. AquaSeNT OFDM Modem
  • 18.5. Bibliographical Notes
  • 19. Underwater Ranging and Localization
  • 19.1. Ranging
  • 19.1.1. One-Way Signaling
  • 19.1.2. Two-Way Signaling
  • 19.1.3. Challenges for High-Precision Ranging
  • 19.2. Underwater GPS
  • 19.2.1. System Overview
  • 19.2.2. One-Way Travel Time Estimation
  • 19.2.3. Localization
  • 19.2.4. Tracking Algorithms
  • 19.2.5. Simulation Results
  • 19.2.6. Field Test in a Local Lake
  • 19.3. On-Demand Asynchronous Localization
  • 19.3.1. Localization Procedure
  • 19.3.2. Localization Algorithm for the Initiator
  • 19.3.3. Localization Algorithm for a Passive Node
  • 19.3.4. Localization Performance Results in a Lake
  • 19.4. Bibliographical Notes
  • Appendix A Compressive Sensing
  • A.1. Compressive Sensing
  • A.1.1. Sparse Representation
  • A.1.2. Exactly and Approximately Sparse Signals
  • A.1.3. Sensing
  • A.1.4. Signal Recovery and RIP
  • A.1.5. Sensing Matrices
  • A.2. Sparse Recovery Algorithms
  • A.2.1. Matching Pursuits
  • A.2.2. e1-Norm Minimization
  • A.3. Applications of Compressive Sensing
  • A.3.1. Applications of Compressive Sensing in Communications
  • A.3.2. Compressive Sensing in Underwater Acoustic Channels
  • Appendix B Experiment Description
  • B.1. SPACE08 Experiment
  • B.2. MACE10 Experiment
  • B.2.1. Experiment Setup
  • B.2.2. Mobility Estimation.

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