Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000010191482 | TK7871.6 S27 2008 | Open Access Book | Book | Searching... |
Searching... | 30000010170232 | TK7871.6 S27 2008 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
An analysis of the physics of multiantenna systems
Multiple-Input Multiple-Output (MIMO) technology is one of the current hot topics in emerging wireless technologies. This book fills the important need for an authoritative reference on the merits of MIMO systems based on physics and provides a sound theoretical basis for its practical implementation. The book also addresses the important issues related to broadband adaptive processing.
Written by three internationally known researchers, Physics of Multiantenna Systems and Broadband Processing:
Provides a thorough discussion of the physical and mathematical principles involved in MIMO and adaptive systems
Examines the electromagnetic framework of wireless communications systems
Uses Maxwell's theory to provide a system-based framework for the abstract concept of channel capacity
Performs various numerical simulations to observe how a typical system will behave in practice
Provides a mathematical formulation for broadband adaptive processing and direction-of-arrival estimation using real antenna arrays
Integrates signal processing and electromagnetics to address the performance of realistic multiantenna systems
With Physics of Multiantenna Systems and Broadband Processing, communication systems engineers, graduate students, researchers, and developers will gain a thorough, scientific understanding of this important new technology.
Author Notes
Magdalena Salazar-Palma obtained a Ph.D. from the Universidad Politecnica de Madrid, Spain.
She is a professor titular in the Departmento de Senales, Sistemas y Radiocommunicaciones at the Universidad Politecnica de Madrid, Spain. She is a co-author of Iterative and Self-Adaptive Finite-Elements in Electromagnetic Modeling (Artech House, 1998). She is the chairperson of the Spain section of IEEE.
050
Table of Contents
Preface | p. xv |
Acknowledgments | p. xxi |
Chapter 1 What Is an Antenna and How Does It Work? | p. 1 |
1.0 Summary | p. 1 |
1.1 Historical Overview of Maxwell's Equations | p. 2 |
1.2 Review of Maxwell-Heaviside-Hertz Equations | p. 4 |
1.2.1 Faraday's Law | p. 4 |
1.2.2 Generalized Ampere's Law | p. 7 |
1.2.3 Generalized Gauss's Law of Electrostatics | p. 8 |
1.2.4 Generalized Gauss's Law of Magnetostatics | p. 9 |
1.2.5 Equation of Continuity | p. 10 |
1.3 Solution of Maxwell's Equations | p. 10 |
1.4 Radiation and Reception Properties of a Point Source Antenna in Frequency and in Time Domain | p. 15 |
1.4.1 Radiation of Fields from Point Sources | p. 15 |
1.4.2 Reception Properties of a Point Receiver | p. 18 |
1.5 Radiation and Reception Properties of Finite-Sized Dipole-Like Structures in Frequency and in Time | p. 20 |
1.5.1 Radiation Fields from Wire-like Structures in th Frequency Domain | p. 20 |
1.5.2 Radiation Fields from Wire-like Structures in the Time Domain | p. 21 |
1.5.3 Induced Voltage on a Finite-Sized Receive Wire-like Structure Due to a Transient Incident Field | p. 21 |
1.6 Conclusion | p. 22 |
References | p. 23 |
Chapter 2 Fundamentals of Antenna Theory in the Frequency Domain | p. 25 |
2.0 Summary | p. 25 |
2.1 Field Produced by a Hertzian Dipole | p. 25 |
2.2 Concept of Near and Far Fields | p. 28 |
2.3 Field Radiated by a Small Circular Loop | p. 30 |
2.4 Field Produced by a Finite-Sized Dipole | p. 32 |
2.5 Radiation Field from a Linear Antenna | p. 34 |
2.6 Near- and Far-Field Properties of Antennas | p. 36 |
2.6.1 What Is Beamforming Using Antennas | p. 36 |
2.6.2 Use of Spatial Antenna Diversity | p. 43 |
2.7 The Mathematics and Physics of an Antenna Array | p. 46 |
2.8 Propagation Modeling in the Frequency Domain | p. 49 |
2.9 Conclusion | p. 57 |
References | p. 57 |
Chapter 3 Fundamentals of an Antenna in the Time Domain | p. 59 |
3.0 Summary | p. 59 |
3.1 Introduction | p. 59 |
3.2 UWB Input Pulse | p. 61 |
3.3 Travelling-Wave Antenna | p. 62 |
3.4 Reciprocity Relation Between Antennas | p. 63 |
3.5 Antenna Simulations | p. 65 |
3.6 Loaded Antennas | p. 65 |
3.6.1 Dipole | p. 65 |
3.6.2 Bicones | p. 71 |
3.6.3 TEM Horn | p. 74 |
3.6.4 Log-Periodic | p. 78 |
3.6.5 Spiral | p. 80 |
3.7 Conventional Wideband Antennas | p. 83 |
3.7.1 Volcano Smoke | p. 83 |
3.7.2 Diamond Dipole | p. 85 |
3.7.3 Monofilar Helix | p. 86 |
3.7.4 Conical Spiral | p. 88 |
3.7.5 Monoloop | p. 90 |
3.7.6 Quad-Ridged Circular Horn | p. 91 |
3.7.7 Bi-Blade with Century Bandwidth | p. 93 |
3.7.8 Cone-Blade | p. 94 |
3.7.9 Vivaldi | p. 96 |
3.7.10 Impulse Radiating Antenna (IRA) | p. 97 |
3.7.11 Circular Disc Dipole | p. 99 |
3.7.12 Bow-Tie | p. 100 |
3.7.13 Planar Slot | p. 101 |
3.8 Experimental Verification of the Wideband Responses from Antennas | p. 102 |
3.9 Conclusion | p. 108 |
References | p. 109 |
Chapter 4 A Look at the Concept of Channel Capacity from a Maxwellian Viewpoint | p. 113 |
4.0 Summary | p. 113 |
4.1 Introduction | p. 114 |
4.2 History of Entropy and Its Evolution | p. 117 |
4.3 Different Formulations for the Channel Capacity | p. 118 |
4.4 Information Content of a Waveform | p. 124 |
4.5 Numerical Examples Illustrating the Relevance of the Maxwellian Physics in Characterizing the Channel Capacity | p. 130 |
4.5.1 Matched Versus Unmatched Receiving Dipole Antenna with a Matched Transmitting Antenna Operating in Free Space | p. 131 |
4.5.2 Use of Directive Versus Nondirective Matched Transmitting Antennas Located at Different Heights above the Earth for a Fixed Matched Receiver Height above Ground | p. 133 |
4.6 Conclusion | p. 146 |
4.7 Appendix: History of Entropy and Its Evolution | p. 148 |
References | p. 164 |
Chapter 5 Multiple-Input-Multiple-Output (MIMO) Antenna Systems | p. 167 |
5.0 Summary | p. 167 |
5.1 Introduction | p. 168 |
5.2 Diversity in Wireless Communications | p. 168 |
5.2.1 Time Diversity | p. 169 |
5.2.2 Frequency Diversity | p. 170 |
5.2.3 Space Diversity | p. 170 |
5.3 Multiantenna Systems | p. 172 |
5.4 Multiple-Input-Multiple-Output (MIMO) Systems | p. 173 |
5.5 Channel Capacity of the MIMO Antenna Systems | p. 176 |
5.6 Channel Known at the Transmitter | p. 178 |
5.6.1 Water-filling Algorithm | p. 179 |
5.7 Channel Unknown at the Transmitter | p. 180 |
5.7.1 Alamouti Scheme | p. 180 |
5.8 Diversity-Multiplexing Tradeoff | p. 182 |
5.9 MIMO Under a Vector Electromagnetic Methodology | p. 183 |
5.9.1 MIMO Versus SISO | p. 184 |
5.10 More Appealing Results for a MIMO system | p. 189 |
5.10.1 Case Study: 1 | p. 189 |
5.10.2 Case Study: 2 | p. 190 |
5.10.3 Case Study: 3 | p. 191 |
5.10.4 Case Study: 4 | p. 194 |
5.10.5 Case Study: 5 | p. 197 |
5.11 Physics of MIMO in a Nutshell | p. 199 |
5.11.1 Line-of-Sight (LOS) MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Direction | p. 200 |
5.11.2 Line-of-Sight MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Direction | p. 202 |
5.11.3 Non-line-of-Sight MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Direction | p. 204 |
5.12 Conclusion | p. 206 |
References | p. 207 |
Chapter 6 Use of the Output Energy Filter in Multiantenna Systems for Adaptive Estimation | p. 209 |
6.0 Summary | p. 209 |
6.1 Various Forms of the Optimum Filters | p. 210 |
6.1.1 Matched Filter (Cross-correlation filter) | p. 211 |
6.1.2 A Wiener Filter | p. 212 |
6.1.3 An Output Energy Filter (Minimum Variance Filter) | p. 213 |
6.1.4 Example of the Filters | p. 214 |
6.2 Direct Data Domain Least Squares Approaches to Adaptive Processing Based on a Single Snapshot of Data | p. 215 |
6.2.1 Eigenvalue Method | p. 218 |
6.2.2 Forward Method | p. 220 |
6.2.3 Backward Method | p. 221 |
6.2.4 Forward-Backward Method | p. 222 |
6.2.5 Real Time Implementation of the Adaptive Procedure | p. 224 |
6.3 Direct Data Domain Least Squares Approach to Space-Time Adaptive Processing | p. 226 |
6.3.1 Two-Dimensional Generalized Eigenvalue Processor | p. 230 |
6.3.2 Least Squares Forward Processor | p. 232 |
6.3.3 Least Squares Backward Processor | p. 236 |
6.3.4 Least Squares Forward-Backward Processor | p. 237 |
6.4 Application of the Direct Data Domain Least Squares Techniques to Airborne Radar for Space-Time Adaptive Processing | p. 238 |
6.5 Conclusion | p. 246 |
References | p. 247 |
Chapter 7 Minimum Norm Property for the Sum of the Adaptive Weights in Adaptive or in Space-Time Processing | p. 249 |
7.0 Summary | p. 249 |
7.1 Introduction | p. 250 |
7.2 Review of the Direct Data Domain Least Squares Approach | p. 251 |
7.3 Review of Space-Time Adaptive Processing Based on the D3LS Method | p. 253 |
7.4 Minimum Norm Property of the Adaptive Weights at the DOA of the SOI for the 1-D Case and at Doppler Frequency and DOA for STAP | p. 255 |
7.5 Numerical Examples | p. 258 |
7.6 Conclusion | p. 273 |
References | p. 274 |
Chapter 8 Using Real Weights in Adaptive and Space-Time Processing | p. 275 |
8.0 Summary | p. 275 |
8.1 Introduction | p. 275 |
8.2 Formulation of a Direct Data Domain Least Squares Approach Using Real Weights | p. 277 |
8.2.1 Forward Method | p. 277 |
8.2.2 Backward Method | p. 281 |
8.2.3 Forward-Backward Method | p. 282 |
8.3 Simulation Results for Adaptive Processing | p. 283 |
8.4 Formulation of an Amplitude-only Direct Data Domain Least Squares Space-Time Adaptive Processing | p. 289 |
8.4.1 Forward Method | p. 289 |
8.4.2 Backward Method | p. 291 |
8.4.3 Forward-Backward Method | p. 292 |
8.5 Simulation Results | p. 292 |
8.6 Conclusion | p. 299 |
References | p. 300 |
Chapter 9 Phase-Only Adaptive and Space-Time Processing | p. 303 |
9.0 Summary | p. 303 |
9.1 Introduction | p. 303 |
9.2 Formulation of the Direct Data Domain Least Squares Solution for a Phase-Only Adaptive System | p. 304 |
9.2.1 Forward Method | p. 304 |
9.2.2 Backward Method | p. 310 |
9.2.3 Forward-Backward Method | p. 310 |
9.3 Simulation Results | p. 311 |
9.4 Formulation of a Phase-Only Direct Data Domain Least Squares Space-Time Adaptive Processing | p. 318 |
9.4.1 Forward Method | p. 318 |
9.4.2 Backward Method | p. 318 |
9.4.3 Forward-Backward Method | p. 318 |
9.5 Simulation Results | p. 319 |
9.6 Conclusion | p. 322 |
References | p. 322 |
Chapter 10 Simultaneous Multiple Adaptive Beamforming | p. 323 |
10.0 Summary | p. 323 |
10.1 Introduction | p. 323 |
10.2 Formulation of a Direct Data Domain Approach for Multiple Beamforming | p. 324 |
10.2.1 Forward Method | p. 324 |
10.2.2 Backward Method | p. 327 |
10.2.3 Forward-Backward Method | p. 328 |
10.3 Simulation Results | p. 328 |
10.4 Formulation of a Direct Data Domain Least Squares Approach for Multiple Beamforming in Space-Time Adaptive Processing | p. 332 |
10.4.1 Forward Method | p. 332 |
10.4.2 Backward Method | p. 336 |
10.4.3 Forward-Backward Method | p. 337 |
10.5 Simulation Results | p. 338 |
10.6 Conclusion | p. 345 |
References | p. 345 |
Chapter 11 Performance Comparison Between Statistical-Based and Direct Data Domain Least Squares Space-Time Adaptive Processing Algorithms | p. 347 |
11.0 Summary | p. 347 |
11.1 Introduction | p. 347 |
11.2 Description of the Various Signals of Interest | p. 348 |
11.2.1 Modeling of the Signal-of-Interest | p. 349 |
11.2.2 Modeling of the Clutter | p. 349 |
11.2.3 Modeling of the Jammer | p. 350 |
11.2.4 Modeling of the Discrete Interferers | p. 350 |
11.3 Statistical-Based STAP Algorithms | p. 351 |
11.3.1 Full-Rank Optimum STAP | p. 351 |
11.3.2 Reduced-Rank STAP (Relative Importance of the Eigenbeam Method) | p. 352 |
11.3.3 Reduced-Rank STAP (Based on the Generalized Sidelobe Canceller) | p. 353 |
11.4 Direct Data Domain Least Squares STAP Algorithms | p. 356 |
11.5 Channel Mismatch | p. 356 |
11.6 Simulation Results | p. 357 |
11.7 Conclusion | p. 368 |
References | p. 368 |
Chapter 12 Approximate Compensation for Mutual Coupling Using the In Situ Antenna Element Patterns | p. 371 |
12.0 Summary | p. 371 |
12.1 Introduction | p. 371 |
12.2 Formulation of the New Direct Data Domain Least Squares Approach Approximately Compensating for the Effects of Mutual Coupling Using the In Situ Element Patterns | p. 373 |
12.2.1 Forward Method | p. 373 |
12.2.3 Backward Method | p. 376 |
12.2.4 Forward-Backward Method | p. 377 |
12.3 Simulation Results | p. 378 |
12.4 Reason for a Decline in the Performance of the Algorithm When the Intensity of the Jammer Is Increased | p. 386 |
12.5 Conclusion | p. 386 |
References | p. 386 |
Chapter 13 Signal Enhancement Through Polarization Adaptivity on Transmit in a Near-Field MIMO Environment | p. 389 |
13.0 Summary | p. 389 |
13.1 Introduction | p. 389 |
13.2 Signal Enhancement Methodology Through Adaptivity on Transmit | p. 391 |
13.3 Exploitation of the Polarization Properties in the Proposed Methodology | p. 395 |
13.4 Numerical Simulations | p. 395 |
13.4.1 Example 1 | p. 396 |
13.4.2 Example 2 | p. 402 |
13.4.3 Example 3 | p. 406 |
13.5 Conclusion | p. 410 |
References | p. 411 |
Chapter 14 Direction of Arrival Estimation by Exploiting Unitary Transform in the Matrix Pencil Method and Its Comparison with ESPRIT | p. 413 |
14.0 Summary | p. 413 |
14.1 Introduction | p. 413 |
14.2 The Unitary Transform | p. 415 |
14.3 1-D Unitary Matrix Pencil Method Revisited | p. 416 |
14.4 Summary of the 1-D Unitary Matrix Pencil Method | p. 419 |
14.5 The 2-D Unitary Matrix Pencil Method | p. 419 |
14.5.1 Pole Pairing for the 2-D Unitary Matrix Pencil Method | p. 425 |
14.5.2 Computational Complexity | p. 426 |
14.5.3 Summary of the 2-D Unitary Matrix Pencil Method | p. 426 |
14.6 Simulation Results Related to the 2-D Unitary Matrix Pencil Method | p. 427 |
14.7 The ESPRIT Method | p. 430 |
14.8 Multiple Snapshot-Based Matrix Pencil Method | p. 432 |
14.9 Comparison of Accuracy and Efficiency Between ESPRIT and the Matrix Pencil Method | p. 432 |
14.10 Conclusion | p. 435 |
References | p. 436 |
Chapter 15 DOA Estimation Using Electrically Small Matched Dipole Antennas and the Associated Cramer-Rao Bound | p. 439 |
15.0 Summary | p. 439 |
15.1 Introduction | p. 440 |
15.2 DOA Estimation Using a Realistic Antenna Array | p. 441 |
15.2.1 Transformation Matrix Technique | p. 441 |
15.3 Cramer-Rao Bound for DOA Estimation | p. 444 |
15.4 DOA Estimation Using 0.1 [gamma] Long Antennas | p. 445 |
15.5 DOA Estimation Using Different Antenna Array Configurations | p. 448 |
15.6 Conclusion | p. 461 |
References | p. 462 |
Chapter 16 Non-Conventional Least Squares Optimization for DOA Estimation Using Arbitrary-Shaped Antenna Arrays | p. 463 |
16.0 Summary | p. 463 |
16.1 Introduction | p. 463 |
16.2 Signal Modeling | p. 464 |
16.3 DFT-Based DOA Estimation | p. 465 |
16.4 Non-conventional Least Squares Optimization | p. 466 |
16.5 Simulation Results | p. 467 |
16.5.1 An Array of Linear Uniformly Spaced Dipoles | p. 468 |
16.5.2 An Array of Linear Non-uniformly Spaced Dipoles | p. 470 |
16.5.3 An Array Consisting of Mixed Antenna Elements | p. 471 |
16.5.4 An Antenna Array Operating in the Presence of Near-Field Scatterers | p. 472 |
16.5.5 Sensitivity of the Procedure Due to a Small Change in the Operating Environment | p. 473 |
16.5.6 Sensitivity of the Procedure Due to a Large Change in the Operating Environment | p. 474 |
16.5.7 An Array of Monopoles Mounted Underneath an Aircraft | p. 476 |
16.5.8 A Non-uniformly Spaced Nonplanar Array of Monopoles Mounted Under an Aircraft | p. 477 |
16.6 Conclusion | p. 479 |
References | p. 479 |
Chapter 17 Broadband Direction of Arrival Estimations Using the Matrix Pencil Method | p. 481 |
17.0 Summary | p. 481 |
17.1 Introduction | p. 481 |
17.2 Brief Overview of the Matrix Pencil Method | p. 482 |
17.3 Problem Formulation for Simultaneous Estimation of DOA and the Frequency of the Signal | p. 488 |
17.4 Cramer-Rao Bound for the Direction of Arrival and Frequency of the Signal | p. 494 |
17.5 Example Using Isotropic Point Sources | p. 505 |
17.6 Example Using Realistic Antenna Elements | p. 512 |
17.7 Conclusion | p. 521 |
References | p. 521 |
Chapter 18 Adaptive Processing of Broadband Signals | p. 523 |
18.0 Summary | p. 523 |
18.1 Introduction | p. 523 |
18.2 Formulation of a Direct Data Domain Least Squares Method for Adaptive Processing of Finite Bandwidth Signals Having Different Frequencies | p. 524 |
18.2.1 Forward Method for Adaptive Processing of Broadband Signals | p. 524 |
18.2.2 Backward Method | p. 529 |
18.2.3 Forward-Backward Method | p. 529 |
18.3 Numerical Simulation Results | p. 530 |
18.4 Conclusion | p. 535 |
References | p. 535 |
Chapter 19 Effect of Random Antenna Position Errors on a Direct Data Domain Least Squares Approach for Space-Time Adaptive Processing | p. 537 |
19.0 Summary | p. 537 |
19.1 Introduction | p. 537 |
19.2 EIRP Degradation of Array Antennas Due to Random Position Errors | p. 540 |
19.3 Example of EIRP Degradation in Antenna Arrays | p. 544 |
19.4 Simulation Results | p. 547 |
19.5 Conclusion | p. 551 |
References | p. 551 |
Index | p. 553 |