Coverart for item
The Resource MIMO-OFDM for LTE, Wi-Fi, and WiMAX : coherent versus non-coherent and cooperative turbo-transceivers, by Prof. Lajos Hanzo, Dr. Yosef (Jos) Akhtman and Dr. Li Wang, Dr. Ming Jiang, (electronic resource)

MIMO-OFDM for LTE, Wi-Fi, and WiMAX : coherent versus non-coherent and cooperative turbo-transceivers, by Prof. Lajos Hanzo, Dr. Yosef (Jos) Akhtman and Dr. Li Wang, Dr. Ming Jiang, (electronic resource)

Label
MIMO-OFDM for LTE, Wi-Fi, and WiMAX : coherent versus non-coherent and cooperative turbo-transceivers
Title
MIMO-OFDM for LTE, Wi-Fi, and WiMAX
Title remainder
coherent versus non-coherent and cooperative turbo-transceivers
Statement of responsibility
by Prof. Lajos Hanzo, Dr. Yosef (Jos) Akhtman and Dr. Li Wang, Dr. Ming Jiang
Contributor
Subject
Genre
Language
eng
Cataloging source
IEEEE
Illustrations
illustrations
Index
index present
LC call number
TK5103.484
LC item number
.H36 2011
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
  • 1952-
  • 1982-
http://library.link/vocab/relatedWorkOrContributorName
  • Hanzo, Lajos
  • Akhtman, J.
  • Wang, L.
  • Jiang, Ming
http://library.link/vocab/subjectName
  • Orthogonal frequency division multiplexing
  • MIMO systems
  • Wireless LANs
  • IEEE 802.11 (Standard)
  • IEEE 802.16 (Standard)
  • Radio
Label
MIMO-OFDM for LTE, Wi-Fi, and WiMAX : coherent versus non-coherent and cooperative turbo-transceivers, by Prof. Lajos Hanzo, Dr. Yosef (Jos) Akhtman and Dr. Li Wang, Dr. Ming Jiang, (electronic resource)
Link
http://libraries.ou.edu/access.aspx?url=http://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5713285
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Color
multicolored
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
Dimensions
unknown
Extent
1 online resource (xxxiv, 658 p.)
Form of item
online
Isbn
9780470686690
Isbn Type
(cloth)
Other control number
9786612782688
Other physical details
ill.
Specific material designation
remote
Stock number
9780470711750
System control number
  • 3890380-01okla_normanlaw
  • (SIRSI)3890380
  • (Sirsi) o715372452
  • (OCoLC)715372452
Label
MIMO-OFDM for LTE, Wi-Fi, and WiMAX : coherent versus non-coherent and cooperative turbo-transceivers, by Prof. Lajos Hanzo, Dr. Yosef (Jos) Akhtman and Dr. Li Wang, Dr. Ming Jiang, (electronic resource)
Link
http://libraries.ou.edu/access.aspx?url=http://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5713285
Publication
Bibliography note
Includes bibliographical references and index
Color
multicolored
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
Dimensions
unknown
Extent
1 online resource (xxxiv, 658 p.)
Form of item
online
Isbn
9780470686690
Isbn Type
(cloth)
Other control number
9786612782688
Other physical details
ill.
Specific material designation
remote
Stock number
9780470711750
System control number
  • 3890380-01okla_normanlaw
  • (SIRSI)3890380
  • (Sirsi) o715372452
  • (OCoLC)715372452

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  • Bizzell Memorial LibraryBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Boorstin CollectionBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Chinese Literature Translation ArchiveBorrow it
    401 W. Brooks St., RM 414, Norman, OK, 73019, US
    35.207487 -97.447906
  • Engineering LibraryBorrow it
    Felgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US
    35.205706 -97.445050
  • Fine Arts LibraryBorrow it
    Catlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US
    35.210371 -97.448244
  • Harry W. Bass Business History CollectionBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • History of Science CollectionsBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • John and Mary Nichols Rare Books and Special CollectionsBorrow it
    401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • Library Service CenterBorrow it
    2601 Technology Place, Norman, OK, 73019, US
    35.185561 -97.398361
  • Price College Digital LibraryBorrow it
    Adams Hall 102 307 West Brooks St., Norman, OK, 73019, US
    35.210371 -97.448244
  • Western History CollectionsBorrow it
    Monnet Hall 630 Parrington Oval, Rm. 300, Norman, OK, 73019, US
    35.209584 -97.445414
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