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MIMO-OFDM for LTE, Wi-Fi and WiMAX [electronic resource] : coherent versus non-coherent and cooperative turbo-transceivers / Lajos Hanzo ... [et al.].

Contributor(s): Material type: TextTextPublication details: Chichester : Wiley, 2011.Description: 1 online resource (xxxiv, 658 p.) : illISBN:
  • 9780470711750:
  • 9780470711750 (electronic bk.)
  • 0470711752 (electronic bk.)
  • 9780470686690 (cloth)
  • 0470686693 (cloth)
  • 9780470711767 (pdf)
  • 0470711760 (pdf)
Subject(s): Genre/Form: Additional physical formats: Print version:: MIMO-OFDM for LTE, Wi-Fi, and WiMAXDDC classification:
  • 621.38216
LOC classification:
  • .M5 2011
Online resources: Available also in a print ed.
Contents:
Note continued: 9.4.1. Full-Rank Systems -- 9.4.2. Rank-Deficient Systems -- 9.5. Chapter Conclusions -- 10. Reduced-Complexity Iterative Sphere Detection for Channel-Coded SDMA-OFDM Systems -- 10.1. Introduction -- 10.1.1. Iterative Detection and Decoding Fundamentals -- 10.1.1.1. System Model -- 10.1.1.2. MAP Bit Detection -- 10.1.2. Chapter Contributions and Outline -- 10.2. Channel-Coded Iterative Centre-Shifting SD -- 10.2.1. Generation of the Candidate List -- 10.2.1.1. List Generation and Extrinsic LLR Calculation -- 10.2.1.2.Computational Complexity of LSDs -- 10.2.1.3. Simulation Results and 2D EXIT-Chart Analysis -- 10.2.2. Centre-Shifting Theory for SDs -- 10.2.3. Centre-Shifting K-Best SD-Aided Iterative Receiver Architectures -- 10.2.3.1. Direct Hard-Decision Centre-Update-Based Two-Stage Iterative Architecture -- 10.2.3.1.1. Receiver Architecture and EXIT-Chart-Aided Analysis -- 10.2.3.1.2. Simulation Results -- 10.2.3.2. Two-Stage Iterative Architecture Using a Direct Soft-Decision Centre Update -- 10.2.3.2.1. Soft-Symbol Calculation -- 10.2.3.2.2. Receiver Architecture and EXIT-Chart-Aided Analysis -- 10.2.3.2.3. Simulation Results -- 10.2.3.3. Two-Stage Iterative Architecture Using an Iterative SIC-MMSE-Aided Centre Update -- 10.2.3.3.1. SIC-Aided MMSE Algorithm -- 10.2.3.3.2. Receiver Architecture and EXIT-Chart Analysis -- 10.2.3.3.3. Simulation Results -- 10.3.A Priori LLR-Threshold-Assisted Low-Complexity SD -- 10.3.1. Principle of the ALT-Aided Detector -- 10.3.2. Features of the ALT-Assisted K-Best SD Receiver -- 10.3.2.1. BER Performance Gain -- 10.3.2.2.Computational Complexity -- 10.3.2.3. Choice of LLR Threshold -- 10.3.2.4. Non-Gaussian-Distributed LLRs Caused by the ALT Scheme -- 10.3.3. ALT-Assisted Centre-Shifting Hybrid SD -- 10.3.3.1.Comparison of the Centre-Shifting and the ALT Schemes -- 10.3.3.2. ALT-Assisted Centre-Shifting Hybrid SD -- 10.4. URC-Aided Three-Stage Iterative Receiver Employing SD -- 10.4.1. URC-Aided Three-Stage Iterative Receiver -- 10.4.2. Performance of the Three-Stage Receiver Employing the Centre-Shifting SD -- 10.4.3. Irregular Convolutional Codes for Three-Stage Iterative Receivers -- 10.5. Chapter Conclusions -- 11. Sphere-Packing Modulated STBC-OFDM and its Sphere Detection -- 11.1. Introduction -- 11.1.1. System Model -- 11.1.2. Chapter Contributions and Outline -- 11.2. Orthogonal Transmit Diversity Design with SP Modulation -- 11.2.1. STBCs -- 11.2.1.1. STBC Encoding -- 11.2.1.2. Equivalent STBC Channel Matrix -- 11.2.1.3. STBC Diversity Combining and Maximum Likelihood Detection -- 11.2.1.4. Other STBCs and Orthogonal Designs -- 11.2.2. Orthogonal Design of STBC Using SP Modulation -- 11.2.2.1. Joint Orthogonal Space[--]Time Signal Design for Two Antennas Using SP -- 11.2.2.2. SP Constellation Construction -- 11.2.3. System Model for STBC-SP-Aided MU-MIMO Systems -- 11.3. Sphere Detection Design for SP Modulation -- 11.3.1. Bit-Based MAP Detection for SP-Modulated MU-MIMO Systems -- 11.3.2. SD Design for SP Modulation -- 11.3.2.1. Transformation of the ML Metric -- 11.3.2.2. Channel Matrix Triangularization -- 11.3.2.3. User-Based Tree Search -- 11.3.3. Simulation Results and Discussion -- 11.4. Chapter Conclusions -- 12. Multiple-Symbol Differential Sphere Detection for Differentially Modulated Cooperative OFDM Systems -- 12.1. Introduction -- 12.1.1. Differential Phase-Shift Keying and Detection -- 12.1.1.1. Conventional Differential Signalling and Detection -- 12.1.1.2. Effects of Time-Selective Channels on Differential Detection -- 12.1.1.3. Effects of Frequency-Selective Channels on Differential Detection -- 12.1.2. Chapter Contributions and Outline -- 12.2. Principle of Single-Path MSDSD -- 12.2.1. ML Metric for MSDD -- 12.2.2. Metric Transformation -- 12.2.3.Complexity Reduction Using SD -- 12.2.4. Simulation Results -- 12.2.4.1. Time-Differential-Encoded OFDM System -- 12.2.4.2. Frequency-Differential-Encoded OFDM System -- 12.3. Multi-path MSDSD Design for Cooperative Communication -- 12.3.1. System Model -- 12.3.2. Differentially Encoded Cooperative Communication Using CDD -- 12.3.2.1. Signal Combining at the Destination for DAF Relaying -- 12.3.2.2. Signal Combining at Destination for DDF Relaying -- 12.3.2.3. Simulation Results -- 12.3.3. Multi-path MSDSD Design for Cooperative Communication -- 12.3.3.1. Derivation of the Metric for Optimum Detection -- 12.3.3.1.1. Equivalent System Model for the DDF-Aided Cooperative Systems -- 12.3.3.1.2. Equivalent System Model for the DAF-Aided Cooperative System -- 12.3.3.1.3. Optimum Detection Metric -- 12.3.3.2. Transformation of the ML Metric -- 12.3.3.3. Channel-Noise Autocorrelation Matrix Triangularization -- 12.3.3.4. Multi-dimensional Tree-Search-Aided MSDSD Algorithm -- 12.3.4. Simulation Results -- 12.3.4.1. Performance of the MSDSD-Aided DAF-User-Cooperation System -- 12.3.4.2. Performance of the MSDSD-Aided DDF User-Cooperation System -- 12.4. Chapter Conclusions -- 13. Resource Allocation for the Differentially Modulated Cooperation-Aided Cellular Uplink in Fast Rayleigh Fading Channels -- 13.1. Introduction -- 13.1.1. Chapter Contributions and Outline -- 13.1.2. System Model -- 13.2. Performance Analysis of the Cooperation-Aided UL -- 13.2.1. Theoretical Analysis of Differential Amplify-and-Forward Systems -- 13.2.1.1. Performance Analysis -- 13.2.1.2. Simulation Results and Discussion -- 13.2.2. Theoretical Analysis of DDF Systems -- 13.2.2.1. Performance Analysis -- 13.2.2.2. Simulation Results and Discussion -- 13.3. CUS for the Uplink -- 13.3.1. CUS for DAF Systems with APC -- 13.3.1.1. APC for DAF-Aided Systems -- 13.3.1.2. CUS Scheme for DAF-Aided Systems -- 13.3.1.3. Simulation Results and Discussion -- 13.3.2. CUS for DDF Systems with APC -- 13.3.2.1. Simulation Results and Discussion -- 13.4. Joint CPS and CUS for the Differential Cooperative Cellular UL Using APC -- 13.4.1.Comparison Between the DAF- and DDF-Aided Cooperative Cellular UL -- 13.4.1.1. Sensitivity to the Source[-]Relay Link Quality -- 13.4.1.2. Effect of the Packet Length -- 13.4.1.3. Cooperative Resource Allocation -- 13.4.2. Joint CPS and CUS Scheme for the Cellular UL Using APC -- 13.5. Chapter Conclusions -- 14. The Near-Capacity Differentially Modulated Cooperative Cellular Uplink -- 14.1. Introduction -- 14.1.1. System Architecture and Channel Model -- 14.1.1.1. System Model -- 14.1.1.2. Channel Model -- 14.1.2. Chapter Contributions and Outline -- 14.2. Channel Capacity of Non-coherent Detectors -- 14.3. SISO MSDSD -- 14.3.1. Soft-Input Processing -- 14.3.2. Soft-Output Generation -- 14.3.3. Maximum Achievable Rate Versus the Capacity: An EXIT-Chart Perspective -- 14.4. Approaching the Capacity of the Differentially Modulated Cooperative Cellular Uplink -- 14.4.1. Relay-Aided Cooperative Network Capacity -- 14.4.1.1. Perfect-SR-Link DCMC Capacity -- 14.4.1.2. Imperfect-SR-Link DCMC Capacity -- 14.4.2. Ir-DHCD Encoding/Decoding for the Cooperative Cellular Uplink -- 14.4.3. Approaching the Cooperative System's Capacity -- 14.4.3.1. Reduced-Complexity Near-Capacity Design at Relay MS -- 14.4.3.2. Reduced-Complexity Near-Capacity Design at Destination BS -- 14.4.4. Simulation Results and Discussion -- 14.5. Chapter Conclusions -- List of Symbols in Part III -- 15. Multi-stream Detection for SDM-OFDM Systems -- 15.1. SDM/V-BLAST OFDM Architecture -- 15.2. Linear Detection Methods -- 15.2.1. MMSE Detection -- 15.2.1.1. Generation of Soft-Bit Information for Turbo Decoding -- 15.2.1.2. Performance Analysis of the Linear SDM Detector -- 15.3. Nonlinear SDM Detection Methods -- 15.3.1. ML Detection -- 15.3.1.1. Generation of Soft-Bit Information -- 15.3.1.2. Performance Analysis of the ML SDM Detector -- 15.3.2. SIC Detection -- 15.3.2.1. Performance Analysis of the SIC SDM Detector -- 15.3.3. GA-Aided MMSE Detection -- 15.3.3.1. Performance Analysis of the GA-MMSE SDM Detector -- 15.4.
Performance Enhancement Using Space[-]Frequency Interleaving -- 15.4.1. Space[-]Frequency-Interleaved OFDM -- 15.4.1.1. Performance Analysis of the SFI-SDM-OFDM -- 15.5. Performance Comparison and Discussion -- 15.6. Conclusions.
Note continued: 16. Approximate Log-MAP SDM-OFDM Multi-stream Detection -- 16.1. OHRSA-Aided SDM Detection -- 16.1.1. OHRSA-Aided ML SDM Detection -- 16.1.1.1. Search Strategy -- 16.1.1.2. Generalization of the OHRSA-ML SDM Detector -- 16.1.2. Bit-wise OHRSA-ML SDM Detection -- 16.1.2.1. Generalization of the BW-OHRSA-ML SDM Detector -- 16.1.3. OHRSA-Aided Log-MAP SDM Detection -- 16.1.4. Soft-Input, Soft-Output Max-Log-MAP SDM Detection -- 16.1.5. SOPHIE-Aided Approximate Log-MAP SDM Detection -- 16.1.5.1. SOPHIE Algorithm Complexity Analysis -- 16.1.5.2. SOPHIE Algorithm Performance Analysis -- 17. Iterative Channel Estimation and Multi-stream Detection for SDM-OFDM -- 17.1. Iterative Signal Processing -- 17.2. Turbo Forward Error-Correction Coding -- 17.3. Iterative Detection [-] Decoding -- 17.4. Iterative Channel Estimation [-] Detection and Decoding -- 17.4.1. Mitigation of Error Propagation -- 17.4.2. MIMO-PASTD-DDCE Aided SDM-OFDM Performance Analysis -- 17.4.2.1. Number of Channel Estimation[-]Detection Iterations -- 17.4.2.2. Pilot Overhead -- 17.4.2.3. Performance of a Symmetric MIMO System -- 17.4.2.4. Performance of a Rank-Deficient MIMO System -- 17.5. Chapter Summary -- 18. Summary, Conclusions and Future Research -- 18.1. Summary of Results -- 18.1.1. OFDM History, Standards and System Components -- 18.1.2. Channel-Coded STBC-OFDM Systems -- 18.1.3. Coded-Modulation-Assisted Multi-user SDMA-OFDM Using Frequency-Domain Spreading -- 18.1.4. Hybrid Multi-user Detection for SDMA-OFDM Systems -- 18.1.5. DSS and SSCH-Aided Multi-user SDMA-OFDM Systems -- 18.1.6. Channel Estimation for OFDM and MC-CDMA -- 18.1.7. Joint Channel Estimation and MUD for SDMA-OFDM -- 18.1.8. Sphere Detection for Uncoded SDMA-OFDM -- 18.1.8.1. Exploitation of the LLRs Delivered by the Channel Decoder -- 18.1.8.2. EXIT-Chart-Aided Adaptive SD Mechanism -- 18.1.9. Transmit Diversity Schemes Employing SDs.
Note continued: 18.1.9.1. Generalized Multi-layer Tree Search Mechanism -- 18.1.9.2. Spatial Diversity Schemes Using SDs -- 18.1.10. SD-Aided MIMO System Designs -- 18.1.10.1. Resource-Optimized Hybrid Cooperative System Design -- 18.1.10.2. Near-Capacity Cooperative and Non-cooperative System Designs -- 18.1.11. Multi-stream Detection in SDM-OFDM Systems -- 18.1.12. Iterative Channel Estimation and Multi-stream Detection in SDM-OFDM Systems -- 18.1.13. Approximate Log-MAP SDM-OFDM Multi-stream Detection -- 18.2. Suggestions for Future Research -- 18.2.1. Optimization of the GA MUD Configuration -- 18.2.2. Enhanced FD-CHTF Estimation -- 18.2.3. Radial-Basis-Function-Assisted OFDM -- 18.2.4. Non-coherent Multiple-Symbol Detection in Cooperative OFDM Systems -- 18.2.5. Semi-Analytical Wireless System Model -- A.1.A Brief Introduction to Genetic Algorithms -- A.2. Normalization of the Mutation-Induced Transition Probability.
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Note continued: 9.4.1. Full-Rank Systems -- 9.4.2. Rank-Deficient Systems -- 9.5. Chapter Conclusions -- 10. Reduced-Complexity Iterative Sphere Detection for Channel-Coded SDMA-OFDM Systems -- 10.1. Introduction -- 10.1.1. Iterative Detection and Decoding Fundamentals -- 10.1.1.1. System Model -- 10.1.1.2. MAP Bit Detection -- 10.1.2. Chapter Contributions and Outline -- 10.2. Channel-Coded Iterative Centre-Shifting SD -- 10.2.1. Generation of the Candidate List -- 10.2.1.1. List Generation and Extrinsic LLR Calculation -- 10.2.1.2.Computational Complexity of LSDs -- 10.2.1.3. Simulation Results and 2D EXIT-Chart Analysis -- 10.2.2. Centre-Shifting Theory for SDs -- 10.2.3. Centre-Shifting K-Best SD-Aided Iterative Receiver Architectures -- 10.2.3.1. Direct Hard-Decision Centre-Update-Based Two-Stage Iterative Architecture -- 10.2.3.1.1. Receiver Architecture and EXIT-Chart-Aided Analysis -- 10.2.3.1.2. Simulation Results -- 10.2.3.2. Two-Stage Iterative Architecture Using a Direct Soft-Decision Centre Update -- 10.2.3.2.1. Soft-Symbol Calculation -- 10.2.3.2.2. Receiver Architecture and EXIT-Chart-Aided Analysis -- 10.2.3.2.3. Simulation Results -- 10.2.3.3. Two-Stage Iterative Architecture Using an Iterative SIC-MMSE-Aided Centre Update -- 10.2.3.3.1. SIC-Aided MMSE Algorithm -- 10.2.3.3.2. Receiver Architecture and EXIT-Chart Analysis -- 10.2.3.3.3. Simulation Results -- 10.3.A Priori LLR-Threshold-Assisted Low-Complexity SD -- 10.3.1. Principle of the ALT-Aided Detector -- 10.3.2. Features of the ALT-Assisted K-Best SD Receiver -- 10.3.2.1. BER Performance Gain -- 10.3.2.2.Computational Complexity -- 10.3.2.3. Choice of LLR Threshold -- 10.3.2.4. Non-Gaussian-Distributed LLRs Caused by the ALT Scheme -- 10.3.3. ALT-Assisted Centre-Shifting Hybrid SD -- 10.3.3.1.Comparison of the Centre-Shifting and the ALT Schemes -- 10.3.3.2. ALT-Assisted Centre-Shifting Hybrid SD -- 10.4. URC-Aided Three-Stage Iterative Receiver Employing SD -- 10.4.1. URC-Aided Three-Stage Iterative Receiver -- 10.4.2. Performance of the Three-Stage Receiver Employing the Centre-Shifting SD -- 10.4.3. Irregular Convolutional Codes for Three-Stage Iterative Receivers -- 10.5. Chapter Conclusions -- 11. Sphere-Packing Modulated STBC-OFDM and its Sphere Detection -- 11.1. Introduction -- 11.1.1. System Model -- 11.1.2. Chapter Contributions and Outline -- 11.2. Orthogonal Transmit Diversity Design with SP Modulation -- 11.2.1. STBCs -- 11.2.1.1. STBC Encoding -- 11.2.1.2. Equivalent STBC Channel Matrix -- 11.2.1.3. STBC Diversity Combining and Maximum Likelihood Detection -- 11.2.1.4. Other STBCs and Orthogonal Designs -- 11.2.2. Orthogonal Design of STBC Using SP Modulation -- 11.2.2.1. Joint Orthogonal Space[--]Time Signal Design for Two Antennas Using SP -- 11.2.2.2. SP Constellation Construction -- 11.2.3. System Model for STBC-SP-Aided MU-MIMO Systems -- 11.3. Sphere Detection Design for SP Modulation -- 11.3.1. Bit-Based MAP Detection for SP-Modulated MU-MIMO Systems -- 11.3.2. SD Design for SP Modulation -- 11.3.2.1. Transformation of the ML Metric -- 11.3.2.2. Channel Matrix Triangularization -- 11.3.2.3. User-Based Tree Search -- 11.3.3. Simulation Results and Discussion -- 11.4. Chapter Conclusions -- 12. Multiple-Symbol Differential Sphere Detection for Differentially Modulated Cooperative OFDM Systems -- 12.1. Introduction -- 12.1.1. Differential Phase-Shift Keying and Detection -- 12.1.1.1. Conventional Differential Signalling and Detection -- 12.1.1.2. Effects of Time-Selective Channels on Differential Detection -- 12.1.1.3. Effects of Frequency-Selective Channels on Differential Detection -- 12.1.2. Chapter Contributions and Outline -- 12.2. Principle of Single-Path MSDSD -- 12.2.1. ML Metric for MSDD -- 12.2.2. Metric Transformation -- 12.2.3.Complexity Reduction Using SD -- 12.2.4. Simulation Results -- 12.2.4.1. Time-Differential-Encoded OFDM System -- 12.2.4.2. Frequency-Differential-Encoded OFDM System -- 12.3. Multi-path MSDSD Design for Cooperative Communication -- 12.3.1. System Model -- 12.3.2. Differentially Encoded Cooperative Communication Using CDD -- 12.3.2.1. Signal Combining at the Destination for DAF Relaying -- 12.3.2.2. Signal Combining at Destination for DDF Relaying -- 12.3.2.3. Simulation Results -- 12.3.3. Multi-path MSDSD Design for Cooperative Communication -- 12.3.3.1. Derivation of the Metric for Optimum Detection -- 12.3.3.1.1. Equivalent System Model for the DDF-Aided Cooperative Systems -- 12.3.3.1.2. Equivalent System Model for the DAF-Aided Cooperative System -- 12.3.3.1.3. Optimum Detection Metric -- 12.3.3.2. Transformation of the ML Metric -- 12.3.3.3. Channel-Noise Autocorrelation Matrix Triangularization -- 12.3.3.4. Multi-dimensional Tree-Search-Aided MSDSD Algorithm -- 12.3.4. Simulation Results -- 12.3.4.1. Performance of the MSDSD-Aided DAF-User-Cooperation System -- 12.3.4.2. Performance of the MSDSD-Aided DDF User-Cooperation System -- 12.4. Chapter Conclusions -- 13. Resource Allocation for the Differentially Modulated Cooperation-Aided Cellular Uplink in Fast Rayleigh Fading Channels -- 13.1. Introduction -- 13.1.1. Chapter Contributions and Outline -- 13.1.2. System Model -- 13.2. Performance Analysis of the Cooperation-Aided UL -- 13.2.1. Theoretical Analysis of Differential Amplify-and-Forward Systems -- 13.2.1.1. Performance Analysis -- 13.2.1.2. Simulation Results and Discussion -- 13.2.2. Theoretical Analysis of DDF Systems -- 13.2.2.1. Performance Analysis -- 13.2.2.2. Simulation Results and Discussion -- 13.3. CUS for the Uplink -- 13.3.1. CUS for DAF Systems with APC -- 13.3.1.1. APC for DAF-Aided Systems -- 13.3.1.2. CUS Scheme for DAF-Aided Systems -- 13.3.1.3. Simulation Results and Discussion -- 13.3.2. CUS for DDF Systems with APC -- 13.3.2.1. Simulation Results and Discussion -- 13.4. Joint CPS and CUS for the Differential Cooperative Cellular UL Using APC -- 13.4.1.Comparison Between the DAF- and DDF-Aided Cooperative Cellular UL -- 13.4.1.1. Sensitivity to the Source[-]Relay Link Quality -- 13.4.1.2. Effect of the Packet Length -- 13.4.1.3. Cooperative Resource Allocation -- 13.4.2. Joint CPS and CUS Scheme for the Cellular UL Using APC -- 13.5. Chapter Conclusions -- 14. The Near-Capacity Differentially Modulated Cooperative Cellular Uplink -- 14.1. Introduction -- 14.1.1. System Architecture and Channel Model -- 14.1.1.1. System Model -- 14.1.1.2. Channel Model -- 14.1.2. Chapter Contributions and Outline -- 14.2. Channel Capacity of Non-coherent Detectors -- 14.3. SISO MSDSD -- 14.3.1. Soft-Input Processing -- 14.3.2. Soft-Output Generation -- 14.3.3. Maximum Achievable Rate Versus the Capacity: An EXIT-Chart Perspective -- 14.4. Approaching the Capacity of the Differentially Modulated Cooperative Cellular Uplink -- 14.4.1. Relay-Aided Cooperative Network Capacity -- 14.4.1.1. Perfect-SR-Link DCMC Capacity -- 14.4.1.2. Imperfect-SR-Link DCMC Capacity -- 14.4.2. Ir-DHCD Encoding/Decoding for the Cooperative Cellular Uplink -- 14.4.3. Approaching the Cooperative System's Capacity -- 14.4.3.1. Reduced-Complexity Near-Capacity Design at Relay MS -- 14.4.3.2. Reduced-Complexity Near-Capacity Design at Destination BS -- 14.4.4. Simulation Results and Discussion -- 14.5. Chapter Conclusions -- List of Symbols in Part III -- 15. Multi-stream Detection for SDM-OFDM Systems -- 15.1. SDM/V-BLAST OFDM Architecture -- 15.2. Linear Detection Methods -- 15.2.1. MMSE Detection -- 15.2.1.1. Generation of Soft-Bit Information for Turbo Decoding -- 15.2.1.2. Performance Analysis of the Linear SDM Detector -- 15.3. Nonlinear SDM Detection Methods -- 15.3.1. ML Detection -- 15.3.1.1. Generation of Soft-Bit Information -- 15.3.1.2. Performance Analysis of the ML SDM Detector -- 15.3.2. SIC Detection -- 15.3.2.1. Performance Analysis of the SIC SDM Detector -- 15.3.3. GA-Aided MMSE Detection -- 15.3.3.1. Performance Analysis of the GA-MMSE SDM Detector -- 15.4.

Performance Enhancement Using Space[-]Frequency Interleaving -- 15.4.1. Space[-]Frequency-Interleaved OFDM -- 15.4.1.1. Performance Analysis of the SFI-SDM-OFDM -- 15.5. Performance Comparison and Discussion -- 15.6. Conclusions.

Note continued: 16. Approximate Log-MAP SDM-OFDM Multi-stream Detection -- 16.1. OHRSA-Aided SDM Detection -- 16.1.1. OHRSA-Aided ML SDM Detection -- 16.1.1.1. Search Strategy -- 16.1.1.2. Generalization of the OHRSA-ML SDM Detector -- 16.1.2. Bit-wise OHRSA-ML SDM Detection -- 16.1.2.1. Generalization of the BW-OHRSA-ML SDM Detector -- 16.1.3. OHRSA-Aided Log-MAP SDM Detection -- 16.1.4. Soft-Input, Soft-Output Max-Log-MAP SDM Detection -- 16.1.5. SOPHIE-Aided Approximate Log-MAP SDM Detection -- 16.1.5.1. SOPHIE Algorithm Complexity Analysis -- 16.1.5.2. SOPHIE Algorithm Performance Analysis -- 17. Iterative Channel Estimation and Multi-stream Detection for SDM-OFDM -- 17.1. Iterative Signal Processing -- 17.2. Turbo Forward Error-Correction Coding -- 17.3. Iterative Detection [-] Decoding -- 17.4. Iterative Channel Estimation [-] Detection and Decoding -- 17.4.1. Mitigation of Error Propagation -- 17.4.2. MIMO-PASTD-DDCE Aided SDM-OFDM Performance Analysis -- 17.4.2.1. Number of Channel Estimation[-]Detection Iterations -- 17.4.2.2. Pilot Overhead -- 17.4.2.3. Performance of a Symmetric MIMO System -- 17.4.2.4. Performance of a Rank-Deficient MIMO System -- 17.5. Chapter Summary -- 18. Summary, Conclusions and Future Research -- 18.1. Summary of Results -- 18.1.1. OFDM History, Standards and System Components -- 18.1.2. Channel-Coded STBC-OFDM Systems -- 18.1.3. Coded-Modulation-Assisted Multi-user SDMA-OFDM Using Frequency-Domain Spreading -- 18.1.4. Hybrid Multi-user Detection for SDMA-OFDM Systems -- 18.1.5. DSS and SSCH-Aided Multi-user SDMA-OFDM Systems -- 18.1.6. Channel Estimation for OFDM and MC-CDMA -- 18.1.7. Joint Channel Estimation and MUD for SDMA-OFDM -- 18.1.8. Sphere Detection for Uncoded SDMA-OFDM -- 18.1.8.1. Exploitation of the LLRs Delivered by the Channel Decoder -- 18.1.8.2. EXIT-Chart-Aided Adaptive SD Mechanism -- 18.1.9. Transmit Diversity Schemes Employing SDs.

Note continued: 18.1.9.1. Generalized Multi-layer Tree Search Mechanism -- 18.1.9.2. Spatial Diversity Schemes Using SDs -- 18.1.10. SD-Aided MIMO System Designs -- 18.1.10.1. Resource-Optimized Hybrid Cooperative System Design -- 18.1.10.2. Near-Capacity Cooperative and Non-cooperative System Designs -- 18.1.11. Multi-stream Detection in SDM-OFDM Systems -- 18.1.12. Iterative Channel Estimation and Multi-stream Detection in SDM-OFDM Systems -- 18.1.13. Approximate Log-MAP SDM-OFDM Multi-stream Detection -- 18.2. Suggestions for Future Research -- 18.2.1. Optimization of the GA MUD Configuration -- 18.2.2. Enhanced FD-CHTF Estimation -- 18.2.3. Radial-Basis-Function-Assisted OFDM -- 18.2.4. Non-coherent Multiple-Symbol Detection in Cooperative OFDM Systems -- 18.2.5. Semi-Analytical Wireless System Model -- A.1.A Brief Introduction to Genetic Algorithms -- A.2. Normalization of the Mutation-Induced Transition Probability.

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