无线与移动通信中的信号处理新技术(第2册) (平装)

出版时间：2002-11  出版社：第1版 (2002年11月1日)  作者：贾纳科斯  页数：438  
Tag标签：无  

内容概要

《无线与移动通信中的信号处理新技术》丛书，介绍了近年来无线与移动通信中使用的信号处理（SP）工具的最新的重要进展，以及世界范围内该领域的领先者的贡献。本书是两本书中的第2册。本丛书的内容涵盖了范围广泛的技术和方法论，包括噪声与干扰消除、调制解调器设计、移动互联网业务、下一代音频/视频广播、蜂窝移动电话和无线多媒体网络等。本书（第2册）重点阐述单用户与多用户通信系统。本书内容包括下列专题的最新成果：    ·单个或多个传感器阵列的盲同步    ·空一时收发分集合并系统    ·时变信道的建模    ·恒模约束的信号分离    ·并行因子分析工具    ·CDMA与多载波系统物理层中的多用户干扰删除及多径影响减轻的新方法    ·网络层的关键信号处理技术    本书介绍了在世界范围内各种期刊中的研究成果，为通信工程师、研究人员、管理人员、通信系统设计人员和参与最新通信系统设计或构造的同行全面汇集了用于优化单用户点对点链路的先进信号处理技术。

书籍目录

1  TIME-VARYING FADING CHANNELS  1  1.1  Channel Model  4    1.1.1  Deterministic Models  4    1.1.2  Stochastic Models  10    1.1.3  Channel Singular Functions  12    1.1.4  Time-Frequency Analysis of LTV Channels' Eigenfunctions  16    1.2  Coding Strategies for Transmissions over LTV Channels  20    1.2.1  Perfect CSI Available at both Transmit and Receive Sides  21    1.2.2  Comparisons and Asymptotic Bounds  24    1.2.3  Adaptive OFDM  30    1.2.4  Coding with Partial CSI  32  1.3  Channel Estimation and Prediction  35    1.3.1  Cramer-Rao Bound for LTV Multipath Channels  37    1.3.2  Channel Prediction  40    1.3.3  Channel Parameter Estimation  42  1.4  Conclusion  43  1.5  Appendices  45    1.5.1  Eigenfunction Model  45    1.5.2  Time-frequency Representations  48    1.5.3  Cramer-Rao Bounds 49  Bibliography  502  SPACE-TIME DIVERSITY  59  2.1  Introduction  59    2.1.1  Diversity  59  2.2  The Set-Up  60  2.3  General Framework for Detection  62    2.3.1 A Bound on the SNR  63  2.4  Space-Only Processing  64  2.5  Space-Time Processing  65    2.5.1  Trace Constraint  65    2.5.2  Eigenvalue Constraint  65    2.5.3  Comparison of the Schemes  66  2.6  Bit Error Rate  67    2.6.1  BER for a Non-fading Channel  67    2.6.2  BER for a Rayleigh Fading Channel  68    2.6.3  BER for other Modulation Schemes  71  2.7  Data Rate  72    2.7.1  Real Symbols  72    2.7.2  Complex Symbols  79  2.8  Discussion  84    2.8.1  Space-only vs. Space- Time Processing  84    2.8.2  Capacity vs. Diversity  85    2.8.3  The Rank One Channel  85    2.8.4  Soft Failure  86  2.9  Conclusions  86  Bibliography  863  ALGEBRAIC CONSTANT MODULUS ALGORITHMS  89  3.1  Introduction  89  3.2  Preliminaries  94  3.3  Derivation of the ACMA  99  3.4  Analysis of the Noise-free Case  103  3.5  ACMA in Noise  106  3.6  Asymptotic Behavior  108  3.7  Weighted ACMA  113  3.8  Binary Source Separation  115  3.9  Simulations  117  3.10  Joint Diagonalization  117  3.11  Concluding Remarks  125  Bibliography  1264  PARAFAC TECHNIQUES FOR SIGNAL SEPQRATION  131  4.1  Introduction  131    4.1.1  Historical Remarks  133  4.2  Theory  133    4.2.1  Notation and Preliminaries  133    4.2.2  k-Rank  136    4.2.3  Identifiability  137  4.3  Algorithms for Fitting the PARAFAC Model  140    4.3.1  Eigenanalysis-Based: GRAM/ESPRIT  141    4.3.2  Alternating Least Squares  142    4.3.3  Separable LS, Gauss-Newton and Levenberg-Marquardt  143    4.3.4  Compression/COMFAC  143  4.4  Determining Three - Way Array Rank  147  4.5  Applications - Part I: Data Modeling  151     4.5.1  Extracting Trilinear Structure out of Bilinear-Vandermonde Data  151     4.5.2  CDMA  152     4.5.3  Multiple-Invariance Array Processing  156     4.5.4  Deterministic Blind Beamforming  159     4.5.5  Fluorescence Spectroscopy  161     4.5.6  Sensory Profiling  162  4.6  Applications -Part II: Examples  164     4.6.1  Numerical Example: COMFAC Performance and the CRB  164     4.6.2  OFDMA with Base Station Antenna Array Example   164     4.6.3  Fluorescence Spectroscopy Example  166     4.6.4  Sensory Profiling Example  167  4.7  PARAFAC Extensions: PARAFCA2  170  4.8  Conclusions  171  Bibliography  1725  MULTIPATH MITIGATION IN CDMA SYSTEMS  181  5.1  Introduction  181  5.2  Signal Model  183    5.2.1  Vector Models  186    5.2.2  Analogies with Array Processing Models  187  5.3  Receiver Design  188    5.3.1  Matched Filter and RAKE Receivers  188    5.3.2  MMSE Receivers  189  5.4  Minimum Variance Receivers  189    5.4.1  The Multipath Case  190    5.4.2  Performance Analysis  192    5.4.3  Illustrative Examples  197    5.4.4  Time Recursive Implementations  198    5.4.5  Convergence  203    5.4.6  Numerical Examples  205  5.5  Multipath Mitigation in Long Code Systems  207    5.5.1  Parameter Estimation in Long Code Systems  208    5.5.2  Blind Channel Estimation  210    5.5.3  Idenfifiability Issues  213    5.5.4  Single-User Receivers  213    5.5.5  Numerical Examples  214  5.6  Conclusions  216  Bibliography  2176  BLOCK SPREADING FOR MULTIPATH-RESILIENT GENERALIZED MULTI-CARRIER CDMA  223  6.1  Block Spreading Model  225    6.1.1  Filterbank Block Precoding  226    6.1.2  Asynchronous Multirate Receiver Design  229    6.1.3  Quasi-Synchronous Model  231    6.1.4  AII-Digital Unitication of Multi-carrier CDMA  232  6.2  GMC-CDMA for MUI/ISI-free Multirate Transmissions  237    6.2.1  Single Rate GMC-CDMA: AMOUR  237    6.2.2  GMC-CDMA: Multirate Case  247    6.2.3  Receiver Design: Blind Equalization  249    6.2.4  Underloaded Systems  251  6.3  Performance and Comparisons  251  6.4  Conclusions and Discussion  157  Appendix 6.A Dual Vandermonde-Lagrange Transceivers  257  Appendix 6.B Modulo-Interpretation of GMC-CDMA  259     6.B.1  The Modulo Interpretation  259     6.B.2  Re-designing the Codes  260  Bibliography  2617  MULTISTAGE INTERFERENCE CANCELLATION ALGORITHMS FOR DS/CDMA SIGNALS  267  7.1  Introduction  267  7.2  Multiuser Signal Model  268  7.3  Overview of CDMA Receivers  270    7.3.1  Conventional Detector 270    7.3.2  Optimum Detector  272    7.3.3  Linear Detectors  273    7.3.4  Decision-Feedback Detectors  274  7.4  Successive Interference Canceler (SIC)  274    7.4.1  SIC Computer Simulations: Synchronous Signals  277    7.4.2  SIC Computer Simulations: Asynchronous Signals  280  7.5  Exact BER Analysis  281    7.5.1  Synchronous Signal Model for Two Users  282    7.5.2  Exact BER of the SIC Receiver  283    7.5.3  Exact BER of the SIC with Amplitude Mismatch  287    7.5.4  Numerical Example: Exact Analysis  288  7.6  Approximate BER Analysis  288    7.6.1  Approximate BER of the SIC Receiver  289    7.6.2  Approximate BER of the SIC with Amplitude Mismatch  291    7.6.3  Numerical Example: Approximate Analysis  292  7.7  Adaptive SIC (ASIC)  293    7.7.1  ASIC Implementation  293    7.7.2  ASIC Computer Simulations  295  7.8  Parallel Interference Canceler (PIC)  297  7.9  BER Analysis for the PIC  299    7.9.1  BER for Stage 1: Exact Analysis  299    7.9.2  BER for Stage 2: Exact Analysis  300    7.9.3  BER from Stage j-1 to Stage j: Approximate Analysis  303    7.9.4  PIC Computer Simulations  305  7.10  State-Space Analysis  308    7.10.1  Convergence of the Error Probabilities  308    7.10.2  IC Receiver Design  311  7.11  Conclusion  311  Bibliography  3138  SIGNAL PROCESSING BASED COLLISION RESOLUTION  315  8.1  Packet Collision in Access Aloha Ad Hoc Networks  317    8.1.1  Random Access Ad Hoc Networks  317    8.1.2  Packet Collision  318  8.2  Packet Collision Model  320    8.2.1  Channel Model  320    8.2.2  Signal Structure  322    8.2.3  Assumptions and Properties  323  8.3  The Training-based Zero Forcing Receiver  324  8.4  The Semi-blind Least Squares Smoothing Receiver  326    8.4.1  The Elimination of ISI  327    8.4.2  The Reduction of MAI  331  8.5  Blind Receivers  333  8.6  Resolvability Analysis  335    8.6.1  Collision Resolvability  335    8.6.2  Resolvability of the Training-based ZF Receiver  336    8.6.3  Resolvability of the Semi-blind LSS Receivers  338    8.6.4  Resolvability Comparisons  339  8.7  Network Performance Analysis  341    8.7.1  Network Model  341    8.7.2  Node and Network Reception Matrices  342    8.7.3  The Markov-Chain Characterization of the Network  344    8.7.4  Throughput, Delay and Stability Analysis  345  8.8  Numerical Examples  347    8.8.1  Resolvability Comparison  347    8.8.2  Network Performance Comparison  347  8.9  Concluding Remarks  351  Appendix  351  Bibliography  3549  NON-DATA-AIDED DIGITAL SYNCHRONIZATION  357  9.1  Introduction  357    9.1.1  Classical Approaches to NDA Synchronization  358    9.1.2  Chapter Summary  360  9.2  Signal Model  360  9.3  Classical Unconditional Maximum Likelihood (UML) Approach  365    9.3.1  NDA Symbol Timing Estimation  367  9.4  Conditional Maximum Likelihood (CML) Approach  371    9.4.1  Joint Parameter Estimation  375    9.4.2  CML-based NDA Synchronization  376    9.4.3  CML Timing and Frequency Synchronizers for Linear Modulations  377    9.4.4  CML Timing and Frequency Synchronizers for Binary CPM Signals  382  9.5  Minimum Conditioned Variance Compressed Likelihood Function (MCV-CML) Approach  384  9.6  Bounds and Performance Evaluation  389    9.6.1  The Modified Cramer-Rao Bound (MCRB)  390    9.6.2  The Unconditional CRB (UCRB)  393    9.6.3  The Conditional CRB (CCEB)  395  9.7  Conclusions  398  Bibliography  40010  EXPLOITING ANTENNA ARRAYS FOR SYNCHRONIZATION  403  10.1  Introduction  403  10.2  Data Model  406  10.3  Maximum Likelihood Estimator  409    10.3.1  Consistency  411    10.3.2  Cramer-Rao Bound  412    10.3.3  Computation of the Estimates  413  10.4  An Asymptotically Equivalent Estimator  414    10.4.1  Proof of the Asymptotic Equivalence  414    10.4.2  Calculation of the Weighting Matrix  415  10.5  Heuristic Derivations  416    10.5.1  Series Expansion of the Logarithm  416    10.5.2  Eigenvalue Weighting  417    10.5.2  First-Order Approximation  417  10.6  Calculating the Estimates with IQML and ESPRIT  418    10.6.1  IQML Algorithm  419    10.6.2  EAPRIT Algorithm  420  10.7  Simulation Results  421    10.7.1  Simulation Parameters  421    10.7.2  Effect of the Number of Samples  422    10.7.3  Effect of the Number of Sensors  424    10.7.4  Effect of the SIR  425    10.7.5  Closely Spaced Signals  425    10.7.6  Performance Using a Search  426  10.8  Conclusions  428  Appendix 10.A  429  Bibliography  430