Cover image for Physics of multiantenna systems and broadband processing
Title:
Physics of multiantenna systems and broadband processing
Personal Author:
Series:
Wiley series in microwave and optical engineering
Publication Information:
Hoboken, NJ : John Wiley & Sons, 2008
Physical Description:
xxi, 562 p. : ill. ; 25 cm.
ISBN:
9780470190401

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30000010191482 TK7871.6 S27 2008 Open Access Book Book
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30000010170232 TK7871.6 S27 2008 Open Access Book Book
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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

Prefacep. xv
Acknowledgmentsp. xxi
Chapter 1 What Is an Antenna and How Does It Work?p. 1
1.0 Summaryp. 1
1.1 Historical Overview of Maxwell's Equationsp. 2
1.2 Review of Maxwell-Heaviside-Hertz Equationsp. 4
1.2.1 Faraday's Lawp. 4
1.2.2 Generalized Ampere's Lawp. 7
1.2.3 Generalized Gauss's Law of Electrostaticsp. 8
1.2.4 Generalized Gauss's Law of Magnetostaticsp. 9
1.2.5 Equation of Continuityp. 10
1.3 Solution of Maxwell's Equationsp. 10
1.4 Radiation and Reception Properties of a Point Source Antenna in Frequency and in Time Domainp. 15
1.4.1 Radiation of Fields from Point Sourcesp. 15
1.4.2 Reception Properties of a Point Receiverp. 18
1.5 Radiation and Reception Properties of Finite-Sized Dipole-Like Structures in Frequency and in Timep. 20
1.5.1 Radiation Fields from Wire-like Structures in th Frequency Domainp. 20
1.5.2 Radiation Fields from Wire-like Structures in the Time Domainp. 21
1.5.3 Induced Voltage on a Finite-Sized Receive Wire-like Structure Due to a Transient Incident Fieldp. 21
1.6 Conclusionp. 22
Referencesp. 23
Chapter 2 Fundamentals of Antenna Theory in the Frequency Domainp. 25
2.0 Summaryp. 25
2.1 Field Produced by a Hertzian Dipolep. 25
2.2 Concept of Near and Far Fieldsp. 28
2.3 Field Radiated by a Small Circular Loopp. 30
2.4 Field Produced by a Finite-Sized Dipolep. 32
2.5 Radiation Field from a Linear Antennap. 34
2.6 Near- and Far-Field Properties of Antennasp. 36
2.6.1 What Is Beamforming Using Antennasp. 36
2.6.2 Use of Spatial Antenna Diversityp. 43
2.7 The Mathematics and Physics of an Antenna Arrayp. 46
2.8 Propagation Modeling in the Frequency Domainp. 49
2.9 Conclusionp. 57
Referencesp. 57
Chapter 3 Fundamentals of an Antenna in the Time Domainp. 59
3.0 Summaryp. 59
3.1 Introductionp. 59
3.2 UWB Input Pulsep. 61
3.3 Travelling-Wave Antennap. 62
3.4 Reciprocity Relation Between Antennasp. 63
3.5 Antenna Simulationsp. 65
3.6 Loaded Antennasp. 65
3.6.1 Dipolep. 65
3.6.2 Biconesp. 71
3.6.3 TEM Hornp. 74
3.6.4 Log-Periodicp. 78
3.6.5 Spiralp. 80
3.7 Conventional Wideband Antennasp. 83
3.7.1 Volcano Smokep. 83
3.7.2 Diamond Dipolep. 85
3.7.3 Monofilar Helixp. 86
3.7.4 Conical Spiralp. 88
3.7.5 Monoloopp. 90
3.7.6 Quad-Ridged Circular Hornp. 91
3.7.7 Bi-Blade with Century Bandwidthp. 93
3.7.8 Cone-Bladep. 94
3.7.9 Vivaldip. 96
3.7.10 Impulse Radiating Antenna (IRA)p. 97
3.7.11 Circular Disc Dipolep. 99
3.7.12 Bow-Tiep. 100
3.7.13 Planar Slotp. 101
3.8 Experimental Verification of the Wideband Responses from Antennasp. 102
3.9 Conclusionp. 108
Referencesp. 109
Chapter 4 A Look at the Concept of Channel Capacity from a Maxwellian Viewpointp. 113
4.0 Summaryp. 113
4.1 Introductionp. 114
4.2 History of Entropy and Its Evolutionp. 117
4.3 Different Formulations for the Channel Capacityp. 118
4.4 Information Content of a Waveformp. 124
4.5 Numerical Examples Illustrating the Relevance of the Maxwellian Physics in Characterizing the Channel Capacityp. 130
4.5.1 Matched Versus Unmatched Receiving Dipole Antenna with a Matched Transmitting Antenna Operating in Free Spacep. 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 Groundp. 133
4.6 Conclusionp. 146
4.7 Appendix: History of Entropy and Its Evolutionp. 148
Referencesp. 164
Chapter 5 Multiple-Input-Multiple-Output (MIMO) Antenna Systemsp. 167
5.0 Summaryp. 167
5.1 Introductionp. 168
5.2 Diversity in Wireless Communicationsp. 168
5.2.1 Time Diversityp. 169
5.2.2 Frequency Diversityp. 170
5.2.3 Space Diversityp. 170
5.3 Multiantenna Systemsp. 172
5.4 Multiple-Input-Multiple-Output (MIMO) Systemsp. 173
5.5 Channel Capacity of the MIMO Antenna Systemsp. 176
5.6 Channel Known at the Transmitterp. 178
5.6.1 Water-filling Algorithmp. 179
5.7 Channel Unknown at the Transmitterp. 180
5.7.1 Alamouti Schemep. 180
5.8 Diversity-Multiplexing Tradeoffp. 182
5.9 MIMO Under a Vector Electromagnetic Methodologyp. 183
5.9.1 MIMO Versus SISOp. 184
5.10 More Appealing Results for a MIMO systemp. 189
5.10.1 Case Study: 1p. 189
5.10.2 Case Study: 2p. 190
5.10.3 Case Study: 3p. 191
5.10.4 Case Study: 4p. 194
5.10.5 Case Study: 5p. 197
5.11 Physics of MIMO in a Nutshellp. 199
5.11.1 Line-of-Sight (LOS) MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Directionp. 200
5.11.2 Line-of-Sight MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Directionp. 202
5.11.3 Non-line-of-Sight MIMO Systems with Parallel Antenna Elements Oriented Along the Broadside Directionp. 204
5.12 Conclusionp. 206
Referencesp. 207
Chapter 6 Use of the Output Energy Filter in Multiantenna Systems for Adaptive Estimationp. 209
6.0 Summaryp. 209
6.1 Various Forms of the Optimum Filtersp. 210
6.1.1 Matched Filter (Cross-correlation filter)p. 211
6.1.2 A Wiener Filterp. 212
6.1.3 An Output Energy Filter (Minimum Variance Filter)p. 213
6.1.4 Example of the Filtersp. 214
6.2 Direct Data Domain Least Squares Approaches to Adaptive Processing Based on a Single Snapshot of Datap. 215
6.2.1 Eigenvalue Methodp. 218
6.2.2 Forward Methodp. 220
6.2.3 Backward Methodp. 221
6.2.4 Forward-Backward Methodp. 222
6.2.5 Real Time Implementation of the Adaptive Procedurep. 224
6.3 Direct Data Domain Least Squares Approach to Space-Time Adaptive Processingp. 226
6.3.1 Two-Dimensional Generalized Eigenvalue Processorp. 230
6.3.2 Least Squares Forward Processorp. 232
6.3.3 Least Squares Backward Processorp. 236
6.3.4 Least Squares Forward-Backward Processorp. 237
6.4 Application of the Direct Data Domain Least Squares Techniques to Airborne Radar for Space-Time Adaptive Processingp. 238
6.5 Conclusionp. 246
Referencesp. 247
Chapter 7 Minimum Norm Property for the Sum of the Adaptive Weights in Adaptive or in Space-Time Processingp. 249
7.0 Summaryp. 249
7.1 Introductionp. 250
7.2 Review of the Direct Data Domain Least Squares Approachp. 251
7.3 Review of Space-Time Adaptive Processing Based on the D3LS Methodp. 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 STAPp. 255
7.5 Numerical Examplesp. 258
7.6 Conclusionp. 273
Referencesp. 274
Chapter 8 Using Real Weights in Adaptive and Space-Time Processingp. 275
8.0 Summaryp. 275
8.1 Introductionp. 275
8.2 Formulation of a Direct Data Domain Least Squares Approach Using Real Weightsp. 277
8.2.1 Forward Methodp. 277
8.2.2 Backward Methodp. 281
8.2.3 Forward-Backward Methodp. 282
8.3 Simulation Results for Adaptive Processingp. 283
8.4 Formulation of an Amplitude-only Direct Data Domain Least Squares Space-Time Adaptive Processingp. 289
8.4.1 Forward Methodp. 289
8.4.2 Backward Methodp. 291
8.4.3 Forward-Backward Methodp. 292
8.5 Simulation Resultsp. 292
8.6 Conclusionp. 299
Referencesp. 300
Chapter 9 Phase-Only Adaptive and Space-Time Processingp. 303
9.0 Summaryp. 303
9.1 Introductionp. 303
9.2 Formulation of the Direct Data Domain Least Squares Solution for a Phase-Only Adaptive Systemp. 304
9.2.1 Forward Methodp. 304
9.2.2 Backward Methodp. 310
9.2.3 Forward-Backward Methodp. 310
9.3 Simulation Resultsp. 311
9.4 Formulation of a Phase-Only Direct Data Domain Least Squares Space-Time Adaptive Processingp. 318
9.4.1 Forward Methodp. 318
9.4.2 Backward Methodp. 318
9.4.3 Forward-Backward Methodp. 318
9.5 Simulation Resultsp. 319
9.6 Conclusionp. 322
Referencesp. 322
Chapter 10 Simultaneous Multiple Adaptive Beamformingp. 323
10.0 Summaryp. 323
10.1 Introductionp. 323
10.2 Formulation of a Direct Data Domain Approach for Multiple Beamformingp. 324
10.2.1 Forward Methodp. 324
10.2.2 Backward Methodp. 327
10.2.3 Forward-Backward Methodp. 328
10.3 Simulation Resultsp. 328
10.4 Formulation of a Direct Data Domain Least Squares Approach for Multiple Beamforming in Space-Time Adaptive Processingp. 332
10.4.1 Forward Methodp. 332
10.4.2 Backward Methodp. 336
10.4.3 Forward-Backward Methodp. 337
10.5 Simulation Resultsp. 338
10.6 Conclusionp. 345
Referencesp. 345
Chapter 11 Performance Comparison Between Statistical-Based and Direct Data Domain Least Squares Space-Time Adaptive Processing Algorithmsp. 347
11.0 Summaryp. 347
11.1 Introductionp. 347
11.2 Description of the Various Signals of Interestp. 348
11.2.1 Modeling of the Signal-of-Interestp. 349
11.2.2 Modeling of the Clutterp. 349
11.2.3 Modeling of the Jammerp. 350
11.2.4 Modeling of the Discrete Interferersp. 350
11.3 Statistical-Based STAP Algorithmsp. 351
11.3.1 Full-Rank Optimum STAPp. 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 Algorithmsp. 356
11.5 Channel Mismatchp. 356
11.6 Simulation Resultsp. 357
11.7 Conclusionp. 368
Referencesp. 368
Chapter 12 Approximate Compensation for Mutual Coupling Using the In Situ Antenna Element Patternsp. 371
12.0 Summaryp. 371
12.1 Introductionp. 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 Patternsp. 373
12.2.1 Forward Methodp. 373
12.2.3 Backward Methodp. 376
12.2.4 Forward-Backward Methodp. 377
12.3 Simulation Resultsp. 378
12.4 Reason for a Decline in the Performance of the Algorithm When the Intensity of the Jammer Is Increasedp. 386
12.5 Conclusionp. 386
Referencesp. 386
Chapter 13 Signal Enhancement Through Polarization Adaptivity on Transmit in a Near-Field MIMO Environmentp. 389
13.0 Summaryp. 389
13.1 Introductionp. 389
13.2 Signal Enhancement Methodology Through Adaptivity on Transmitp. 391
13.3 Exploitation of the Polarization Properties in the Proposed Methodologyp. 395
13.4 Numerical Simulationsp. 395
13.4.1 Example 1p. 396
13.4.2 Example 2p. 402
13.4.3 Example 3p. 406
13.5 Conclusionp. 410
Referencesp. 411
Chapter 14 Direction of Arrival Estimation by Exploiting Unitary Transform in the Matrix Pencil Method and Its Comparison with ESPRITp. 413
14.0 Summaryp. 413
14.1 Introductionp. 413
14.2 The Unitary Transformp. 415
14.3 1-D Unitary Matrix Pencil Method Revisitedp. 416
14.4 Summary of the 1-D Unitary Matrix Pencil Methodp. 419
14.5 The 2-D Unitary Matrix Pencil Methodp. 419
14.5.1 Pole Pairing for the 2-D Unitary Matrix Pencil Methodp. 425
14.5.2 Computational Complexityp. 426
14.5.3 Summary of the 2-D Unitary Matrix Pencil Methodp. 426
14.6 Simulation Results Related to the 2-D Unitary Matrix Pencil Methodp. 427
14.7 The ESPRIT Methodp. 430
14.8 Multiple Snapshot-Based Matrix Pencil Methodp. 432
14.9 Comparison of Accuracy and Efficiency Between ESPRIT and the Matrix Pencil Methodp. 432
14.10 Conclusionp. 435
Referencesp. 436
Chapter 15 DOA Estimation Using Electrically Small Matched Dipole Antennas and the Associated Cramer-Rao Boundp. 439
15.0 Summaryp. 439
15.1 Introductionp. 440
15.2 DOA Estimation Using a Realistic Antenna Arrayp. 441
15.2.1 Transformation Matrix Techniquep. 441
15.3 Cramer-Rao Bound for DOA Estimationp. 444
15.4 DOA Estimation Using 0.1 [gamma] Long Antennasp. 445
15.5 DOA Estimation Using Different Antenna Array Configurationsp. 448
15.6 Conclusionp. 461
Referencesp. 462
Chapter 16 Non-Conventional Least Squares Optimization for DOA Estimation Using Arbitrary-Shaped Antenna Arraysp. 463
16.0 Summaryp. 463
16.1 Introductionp. 463
16.2 Signal Modelingp. 464
16.3 DFT-Based DOA Estimationp. 465
16.4 Non-conventional Least Squares Optimizationp. 466
16.5 Simulation Resultsp. 467
16.5.1 An Array of Linear Uniformly Spaced Dipolesp. 468
16.5.2 An Array of Linear Non-uniformly Spaced Dipolesp. 470
16.5.3 An Array Consisting of Mixed Antenna Elementsp. 471
16.5.4 An Antenna Array Operating in the Presence of Near-Field Scatterersp. 472
16.5.5 Sensitivity of the Procedure Due to a Small Change in the Operating Environmentp. 473
16.5.6 Sensitivity of the Procedure Due to a Large Change in the Operating Environmentp. 474
16.5.7 An Array of Monopoles Mounted Underneath an Aircraftp. 476
16.5.8 A Non-uniformly Spaced Nonplanar Array of Monopoles Mounted Under an Aircraftp. 477
16.6 Conclusionp. 479
Referencesp. 479
Chapter 17 Broadband Direction of Arrival Estimations Using the Matrix Pencil Methodp. 481
17.0 Summaryp. 481
17.1 Introductionp. 481
17.2 Brief Overview of the Matrix Pencil Methodp. 482
17.3 Problem Formulation for Simultaneous Estimation of DOA and the Frequency of the Signalp. 488
17.4 Cramer-Rao Bound for the Direction of Arrival and Frequency of the Signalp. 494
17.5 Example Using Isotropic Point Sourcesp. 505
17.6 Example Using Realistic Antenna Elementsp. 512
17.7 Conclusionp. 521
Referencesp. 521
Chapter 18 Adaptive Processing of Broadband Signalsp. 523
18.0 Summaryp. 523
18.1 Introductionp. 523
18.2 Formulation of a Direct Data Domain Least Squares Method for Adaptive Processing of Finite Bandwidth Signals Having Different Frequenciesp. 524
18.2.1 Forward Method for Adaptive Processing of Broadband Signalsp. 524
18.2.2 Backward Methodp. 529
18.2.3 Forward-Backward Methodp. 529
18.3 Numerical Simulation Resultsp. 530
18.4 Conclusionp. 535
Referencesp. 535
Chapter 19 Effect of Random Antenna Position Errors on a Direct Data Domain Least Squares Approach for Space-Time Adaptive Processingp. 537
19.0 Summaryp. 537
19.1 Introductionp. 537
19.2 EIRP Degradation of Array Antennas Due to Random Position Errorsp. 540
19.3 Example of EIRP Degradation in Antenna Arraysp. 544
19.4 Simulation Resultsp. 547
19.5 Conclusionp. 551
Referencesp. 551
Indexp. 553