TECHNISCHE UNIVERSITÄT ILMENAU Fakultät für Elektrotechnik und Informationstechnik

Transcription

1 &v TECHNISCHE UNIVERSITÄT ILMENAU Fakultät für Elektrotechnik und Informationstechnik CRLp W MIMO Channel Modeling in Wireless Communications and its Applications Marko Milojevic Dissertation zur Erlangung des akademischen Grades Doktoringenieur (Dr.-Ing.) Anfertigung im: Gutachter: Vorgelegt am: Verteidigt am: Fachgebiet Nachrichtentechnik Institut für Informationstechnik Fakultät für Elektrotechnik und Informationstechnik Univ.-Prof. Dr.-Ing. Martin Haardt Prof. Dr.-Ing. Albert Heuberger Prof. Dr.-Ing. Armin Dekorsy

2 Contents Preface Abstract Zusammenfassung Contents List of Figures List of Tables i Hi v vii xi xvii 1. Introduction State of the Art Overview and Contributions 4 2. MIMO Systems and MIMO Channels MIMO Systems in Wireless Communications Spatial Processing Techniques The Deterministic Description of the MIMO Channels The First Set of Bello Functions Bello Functions Extended to the Spatial Domain The Full MIMO Channel Description Polarization The Sampled Frequency-Selective Time-Variant MIMO Channel Stochastic Characterization of Multi-path Channels Stochastic Process Theory Stochastic Description of the Full MIMO Channel The Power Delay Spectrum The Autocorrelation Function in Frequency Domain Doppler Power Spectrum The Autocorrelation Function in Time Domain Power Angular Spectrum The Autocorrelation Function in Spatial Domain 35 vii

3 The Sampled Autocorrelation Function of Frequency-Selective Time-Variant MIMO Channel Modeling of the MIMO Channels Channel Models Classification Deterministic Channel Models Analytical Channel Models Full Spatial Correlation Matrix Channel Model for Frequency-Non-Selective Time-Invariant Channels The Kronecker Channel Model The Weichselberger Channel Model A Subspace-Based Channel Model for Frequency-Selective Time-Variant MIMO Channels The Channel Model Validity and Channel Parametrization A Physical Interpretation of the Eigenmodes Correlation in Frequency and Time A Correlation Tensor-Based Model for Frequency-Selective Time-Variant MIMO Channels Hybrid Channel Models COST 259 Directional Channel Model IST METRA Channel Models IEEE n Channel Model The IlmProp Channel Model GPP Spatial Channel Model (SCM) WINNER Spatial Channel Model Extended (SCME) Bandwidth Extension Extension of the Frequency Range LOS Option and Time Evolution WINNER Channel Models (WIM) Introduction to the WINNER Channel Models WIM Modeling Approach The Network Layout Modeling the Time Evolution Inter-Dependence of Large-Scale Parameters Modeling of the Nomadic Channel Condition WIM 3D Antenna Array Model The Description of 3D Antenna Arrays Integration of 3D Antenna Arrays in the WIM Channel Model. 96 viu

4 WIM Models With Reduced Complexity WIM Clustered Delay Line Models Channel Modeling for Multiple Mobile Satellite Broadcasting Systems Satellite Digital Audio Radio Systems ХМ Radio and Sirius XM Radio Sirius Satellite Radio Measurements of XM Radio and Sirius S-DARS Systems Channel Model for Single and Two Satellite Systems Based on the First Order Markov Chains Channel State Model for Single Satellite Systems Channel State Model for the Two Satellite Systems The Channel Amplitude Modeling Ill Correlation and State Duration Properties of the Measured S-DARS Channels Correlation Coefficient Between Two S-DARS Satellites Spatial Autocorrelation Function of S-DARS Satellites Channel State Duration of the S-DARS Systems Environmental Influence on the Noise Power The State Duration of the Markov Chain Based Channel Models The PDFSD Modeling Based on Dynamic Order Markov Chains Dynamic SPTM Model Approximations Partial Dynamic SPTM Model Approximated Partial Dynamic SPTM Model PDFSD Based Channel State Generation Algorithm The PDFSD Modeling for Multiple Satellite Systems Spatio-Temporal Availability in Satellite-to-lndoor Broadcasting Introduction Satellite-to-lndoor Channel Model System Model for Simulation Setup The Ray Tracing Engine WinProp Geometry-Based Channel Modeling Polarization and Different Antenna Configurations Frequency Selectivity of Studied Channels Temporal Variation of the Satellite Link Signal Availability Performance Comparison of Different Receive Antenna Schemes Ray Tracing Results for Vertical Dipole Spatial Correlation of Multi-Antenna Configurations 143

5 Signal Availability for Different Receive Antenna Configurations Influence of Windows on the Availability User Interaction Influence of Temporal Variation on Signal Availability Applications of the Channel Modeling on the Channel Prediction and Channel Interpolation On the Channel Prediction Subspace-Based Framework for the Prediction of Frequency-Selective Time-Variant MIMO Channels Subspace-Based Channel Prediction Framework Filter Structures Propagation Scenario for Simulations Simulation Results Tensor-Based Framework for the Prediction of Frequency-Selective Time-Variant MIMO Channels Tensor-Based Channel Prediction Framework Simulation Results Interpolating the Channel Conclusions 177 Appendix A. Mathematical Operators 179 A.l. The Scalar Product 179 A.2. The Vector Product 179 A.3. The Kronecker Product 180 Appendix B. Higher-Order Signal Processing Calculus 181 B.l. Tensor Properties 181 B.2. The Outer, «-Mode, and»-mode Inner Tensor Products 183 B.3. Higher Order Singular Value Decomposition (HOSVD) 185 Appendix С Generation of WIM Channel Coefficients and WIM Parameters 187 C.l. Generation of WIM Channel Coefficients 187 C.2. WIM Parameters 194 Appendix D. Glossary of Acronyms, Symbols, and Notation 197 Bibliography 203