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  • SMART ANTENNAS

    • Dedication

    • Preface

    • Acknowledgments

    • The Author

    • Contents

    • Chapter 01: Introduction

      • 1.1 Antenna Gain

      • 1.2 Phased Array Antenna

      • 1.3 Power Pattern

      • 1.4 Beam Steering

      • 1.5 Degree of Freedom

      • 1.6 Optimal Antenna

      • 1.7 Adaptive Antenna

      • 1.8 Smart Antenna

      • 1.9 Book Outline

      • References

    • Chapter 02: Narrowband Processing

      • 2.1 Signal Model

        • 2.1.1 Steering Vector Representation

        • 2.1.2 Eigenvalue Decomposition

      • 2.2 Conventional Beamformer

        • 2.2.1 Source in Look Direction

        • 2.2.2 Directional Interference

        • 2.2.3 Random Noise Environment

        • 2.2.4 Signal-to-Noise Ratio

      • 2.3 Null Steering Beamformer

      • 2.4 Optimal Beamformer

        • 2.4.1 Unconstrained Beamformer

        • 2.4.2 Constrained Beamformer

        • 2.4.3 Output Signal-to-Noise Ratio and Array Gain

        • 2.4.4 Special Case 1: Uncorrelated Noise Only

        • 2.4.5 Special Case 2: One Directional Interference

      • 2.5 Optimization Using Reference Signal

      • 2.6 Beam Space Processing

        • 2.6.1 Optimal Beam Space Processor

        • 2.6.2 Generalized Side-Lobe Canceler

        • 2.6.3 Postbeamformer Interference Canceler

          • 2.6.3.1 Optimal PIC

          • 2.6.3.2 PIC with Conventional Interference Beamformer

          • 2.6.3.3 PIC with Orthogonal Interference Beamformer

          • 2.6.3.4 PIC with Improved Interference Beamformer

          • 2.6.3.5 Discussion and Comments

            • 2.6.3.5.1 Signal Suppression

            • 2.6.3.5.2 Residual Interference

            • 2.6.3.5.3 Uncorrelated Noise Power

            • 2.6.3.5.4 Signal-to-Noise Ratio

        • 2.6.4 Comparison of Postbeamformer Interference Canceler with Element Space Processor

        • 2.6.5 Comparison in Presence of Look Direction Errors

      • 2.7 Effect of Errors

        • 2.7.1 Weight Vector Errors

          • 2.7.1.1 Output Signal Power

          • 2.7.1.2 Output Noise Power

          • 2.7.1.3 Output SNR and Array Gain

        • 2.7.2 Steering Vector Errors

          • 2.7.2.1 Noise-Alone Matrix Inverse Processor

            • 2.7.2.1.1 Output Signal Power

            • 2.7.2.1.2 Total Output Noise Power

            • 2.7.2.1.3 Output SNR and Array Gain

          • 2.7.2.2 Signal-Plus-Noise Matrix Inverse Processor

            • 2.7.2.2.1 Output Signal Power

            • 2.7.2.2.2 Total Output Noise Power

            • 2.7.2.2.3 Output SNR

          • 2.7.2.3 Discussion and Comments

            • 2.7.2.3.1 Special Case 1: Uncorrelated Noise Only

            • 2.7.2.3.2 Special Case 2: One Directional Interference

        • 2.7.3 Phase Shifter Errors

          • 2.7.3.1 Random Phase Errors

          • 2.7.3.2 Signal Suppression

          • 2.7.3.3 Residual Interference Power

          • 2.7.3.4 Array Gain

          • 2.7.3.5 Comparison with SVE

        • 2.7.4 Phase Quantization Errors

        • 2.7.5 Other Errors

        • 2.7.6 Robust Beamforming

      • Acknowledgments

      • Notation and Abbreviations

      • References

    • Chapter 03: Adaptive Processing

      • 3.1 Sample Matrix Inversion Algorithm

      • 3.2 Unconstrained Least Mean Squares Algorithm

        • 3.2.1 Gradient Estimate

        • 3.2.2 Covariance of Gradient

        • 3.2.3 Convergence of Weight Vector

        • 3.2.4 Convergence Speed

        • 3.2.5 Weight Covariance Matrix

        • 3.2.6 Transient Behavior of Weight Covariance Matrix

        • 3.2.7 Excess Mean Square Error

        • 3.2.8 Misadjustment

      • 3.3 Normalized Least Mean Squares Algorithm

      • 3.4 Constrained Least Mean Squares Algorithm

        • 3.4.1 Gradient Estimate

        • 3.4.2 Covariance of Gradient

        • 3.4.3 Convergence of Weight Vector

        • 3.4.4 Weight Covariance Matrix

        • 3.4.5 Transient Behavior of Weight Covariance Matrix

        • 3.4.6 Convergence of Weight Covariance Matrix

        • 3.4.7 Misadjustment

      • 3.5 Perturbation Algorithms

        • 3.5.1 Time Multiplex Sequence

        • 3.5.2 Single-Receiver System

          • 3.5.2.1 Covariance of the Gradient Estimate

          • 3.5.2.2 Perturbation Noise

        • 3.5.3 Dual-Receiver System

          • 3.5.3.1 Dual-Receiver System with Reference Receiver

          • 3.5.3.2 Covariance of Gradient

        • 3.5.4 Covariance of Weights

          • 3.5.4.1 Dual-Receiver System with Dual Perturbation

          • 3.5.4.2 Dual-Receiver System with Reference Receiver

        • 3.5.5 Misadjustment Results

          • 3.5.5.1 Single-Receiver System

          • 3.5.5.2 Dual-Receiver System with Dual Perturbation

          • 3.5.5.3 Dual-Receiver System with Reference Receiver

      • 3.6 Structured Gradient Algorithm

        • 3.6.1 Gradient Estimate

        • 3.6.2 Examples and Discussion

      • 3.7 Recursive Least Mean Squares Algorithm

        • 3.7.1 Gradient Estimate

        • 3.7.2 Covariance of Gradient

        • 3.7.3 Discussion

      • 3.8 Improved Least Mean Squares Algorithm

      • 3.9 Recursive Least Squares Algorithm

      • 3.10 Constant Modulus Algorithm

      • 3.11 Conjugate Gradient Method

      • 3.12 Neural Network Approach

      • 3.13 Adaptive Beam Space Processing

        • 3.13.1 Gradient Estimate

        • 3.13.2 Convergence of Weights

        • 3.13.3 Covariance of Weights

        • 3.13.4 Transient Behavior of Weight Covariance

        • 3.13.5 Steady State Behavior of Weight Covariance

        • 3.13.6 Misadjustment

        • 3.13.7 Examples and Discussion

      • 3.14 Signal Sensitivity of Constrained Least Mean Squares Algorithm

      • 3.15 Implementation Issues

        • 3.15.1 Finite Precision Arithmetic

        • 3.15.2 Real vs. Complex Implementation

          • 3.15.2.1 Quadrature Filter

          • 3.15.2.2 Analytical Signals

          • 3.15.2.3 Beamformer Structures

          • 3.15.2.4 Real LMS Algorithm

          • 3.15.2.5 Complex LMS Algorithm

          • 3.15.2.6 Discussion

      • Acknowledgments

      • Notation and Abbreviations

      • References

      • Appendices

        • Appendix 3.1

        • Appendix 3.2

        • Appendix 3.3

        • Appendix 3.4

        • Appendix 3.5

        • Appendix 3.6

        • Appendix 3.7

    • Chapter 04: Broadband Processing

      • 4.1 Tapped-Delay Line Structure

        • 4.1.1 Description

        • 4.1.2 Frequency Response

        • 4.1.3 Optimization

        • 4.1.4 Adaptive Algorithm

        • 4.1.5 Minimum Mean Square Error Design

          • 4.1.5.1 Derivation of Constraints

          • 4.1.5.2 Optimization

      • 4.2 Partitioned Realization

        • 4.2.1 Generalized Side-Lobe Canceler

        • 4.2.2 Constrained Partitioned Realization

        • 4.2.3 General Constrained Partitioned Realization

          • 4.2.3.1 Derivation of Constraints

          • 4.2.3.2 Optimization

      • 4.3 Derivative Constrained Processor

        • 4.3.1 First-Order Derivative Constraints

        • 4.3.2 Second-Order Derivative Constraints

        • 4.3.3 Optimization with Derivative Constraints

          • 4.3.3.1 Linear Array Example

        • 4.3.4 Adaptive Algorithm

        • 4.3.5 Choice of Origin

      • 4.4 Correlation Constrained Processor

      • 4.5 Digital Beamforming

      • 4.6 Frequency Domain Processing

        • 4.6.1 Description

        • 4.6.2 Relationship with Tapped-Delay Line Structure Processing

          • 4.6.2.1 Weight Relationship

          • 4.6.2.2 Matrix Relationship

          • 4.6.2.3 Derivation of Rf(k)

          • 4.6.2.4 Array with Presteering Delays

          • 4.6.2.5 Array without Presteering Delays

          • 4.6.2.6 Discussion and Comments

        • 4.6.3 Transformation of Constraints

          • 4.6.3.1 Point Constraints

          • 4.6.3.2 Derivative Constraints

      • 4.7 Broadband Processing Using Discrete Fourier Transform Method

        • 4.7.1 Weight Estimation

        • 4.7.2 Performance Comparison

          • 4.7.2.1 Effect of Filter Length

          • 4.7.2.2 Effect of Number of Elements in Array

          • 4.7.2.3 Effect of Interference Power

        • 4.7.3 Computational Requirement Comparison

        • 4.7.4 Schemes to Reduce Computation

          • 4.7.4.1 Limited Number of Bins Processing

          • 4.7.4.2 Parallel Processing Schemes

            • 4.7.4.2.1 Parallel Processing Scheme 1

            • 4.7.4.2.2 Parallel Processing Scheme 2

            • 4.7.4.2.3 Parallel Processing Scheme 3

        • 4.7.5 Discussion

          • 4.7.5.1 Higher SNR with Less Processing Time

          • 4.7.5.2 Robustness of DFT Method

      • 4.8 Performance

      • Acknowledgments

      • Notation and Abbreviations

      • References

    • Chapter 05: Correlated Fields

      • 5.1 Correlated Signal Model

      • 5.2 Optimal Element Space Processor

      • 5.3 Optimized Postbeamformer Interference Canceler Processor

      • 5.4 Signal-to-Noise Ratio Performance

        • 5.4.1 Zero Uncorrelated Noise

        • 5.4.2 Strong Interference and Large Number of Elements

        • 5.4.3 Coherent Sources

        • 5.4.4 Examples and Discussion

      • 5.5 Methods to Alleviate Correlation Effects

      • 5.6 Spatial Smoothing Method

        • 5.6.1 Decorrelation Analysis

        • 5.6.2 Adaptive Algorithm

      • 5.7 Structured Beamforming Method

        • 5.7.1 Decorrelation Analysis

          • 5.7.1.1 Examples and Discussion

        • 5.7.2 Structured Gradient Algorithm

          • 5.7.2.1 Gradient Comparison

          • 5.7.2.2 Weight Vector Comparison

          • 5.7.2.3 Examples and Discussion

      • 5.8 Correlated Broadband Sources

        • 5.8.1 Structure of Array Correlation Matrix

        • 5.8.2 Correlated Field Model

        • 5.8.3 Structured Beamforming Method

        • 5.8.4 Decorrelation Analysis

          • 5.8.4.1 Examples and Discussion

      • Acknolwedgments

      • Notation and Abbreviations

      • References

    • Chapter 06: Direction-of-Arrival Estimation Methods

      • 6.1 Spectral Estimation Methods

        • 6.1.1 Bartlett Method

      • 6.2 Minimum Variance Distortionless Response Estimator

      • 6.3 Linear Prediction Method

      • 6.4 Maximum Entropy Method

      • 6.5 Maximum Likelihood Method

      • 6.6 Eigenstructure Methods

      • 6.7 MUSIC Algorithm

        • 6.7.1 Spectral MUSIC

        • 6.7.2 Root-MUSIC

        • 6.7.3 Constrained MUSIC

        • 6.7.4 Beam Space MUSIC

      • 6.8 Minimum Norm Method

      • 6.9 CLOSEST Method

      • 6.10 ESPRIT Method

      • 6.11 Weighted Subspace Fitting Method

      • 6.12 Review of Other Methods

      • 6.13 Preprocessing Techniques

      • 6.14 Estimating Source Number

      • 6.15 Performance Comparison

      • 6.16 Sensitivity Analysis

      • Acknowledgments

      • Notation and Abbreviations

      • References

    • Chapter 07: Single-Antenna System in Fading Channels

      • 7.1 Fading Channels

        • 7.1.1 Large-Scale Fading

        • 7.1.2 Small-Scale Fading

        • 7.1.3 Distribution of Signal Power

      • 7.2 Channel Gain

      • 7.3 Single-Antenna System

        • 7.3.1 Noise-Limited System

          • 7.3.1.1 Rayleigh Fading Environment

          • 7.3.1.2 Nakagami Fading Environment

        • 7.3.2 Interference-Limited System

          • 7.3.2.1 Identical Interferences

          • 7.3.2.2 Signal and Interference with Different Statistics

        • 7.3.3 Interference with Nakagami Fading and Shadowing

        • 7.3.4 Error Rate Performance

      • Notation and Abbreviations

      • References

    • Chapter 08: Diversity Combining

      • 8.1 Selection Combiner

        • 8.1.1 Noise-Limited Systems

          • 8.1.1.1 Rayleigh Fading Environment

            • 8.1.1.1.1 Outage Probability

            • 8.1.1.1.2 Mean SNR

            • 8.1.1.1.3 Average BER

          • 8.1.1.2 Nakagami Fading Environment

            • 8.1.1.2.1 Output SNR pdf

            • 8.1.1.2.2 Outage Probability

            • 8.1.1.2.3 Average BER

        • 8.1.2 Interference-Limited Systems

          • 8.1.2.1 Desired Signal Power Algorithm

          • 8.1.2.2 Total Power Algorithm

          • 8.1.2.3 SIR Power Algorithm

      • 8.2 Switched Diversity Combiner

        • 8.2.1. Outage Probability

        • 8.2.2 Average Bit Error Rate

        • 8.2.3 Correlated Fading

      • 8.3 Equal Gain Combiner

        • 8.3.1 Noise-Limited Systems

          • 8.3.1.1 Mean SNR

          • 8.3.1.2 Outage Probability

          • 8.3.1.3 Average BER

          • 8.3.1.4 Use of Characteristic Function

        • 8.3.2 Interference-Limited Systems

          • 8.3.2.1 Outage Probability

          • 8.3.2.2 Mean Signal Power to Mean Interference Power Ratio

      • 8.4 Maximum Ratio Combiner

        • 8.4.1 Noise-Limited Systems

          • 8.4.1.1 Mean SNR

          • 8.4.1.2 Rayleigh Fading Environment

            • 8.4.1.2.1 PDF of Output SNR

            • 8.4.1.2.2 Outage Probability

            • 8.4.1.2.3 Average BER

          • 8.4.1.3 Nakagami Fading Environment

          • 8.4.1.4 Effect of Weight Errors

            • 8.4.1.4.1 Output SNR pdf

            • 8.4.1.4.2 Outage Probability

            • 8.4.1.4.3 Average BER

        • 8.4.2 Interference-Limited Systems

          • 8.4.2.1 Mean Signal Power to Interference Power Ratio

          • 8.4.2.2 Outage Probability

          • 8.4.2.3 Average BER

      • 8.5 Optimal Combiner

        • 8.5.1 Mean Signal Power to Interference Power Ratio

        • 8.5.2. Outage Probability

        • 8.5.3 Average Bit Error Rate

      • 8.6 Generalized Selection Combiner

        • 8.6.1 Moment-Generating Functions

        • 8.6.2 Mean Output Signal-to-Noise Ratio

        • 8.6.3 Outage Probability

        • 8.6.4 Average Bit Error Rate

      • 8.7 Cascade Diversity Combiner

        • 8.7.1 Rayleigh Fading Environment

          • 8.7.1.1 Output SNR pdf

          • 8.7.1.2 Outage Probability

          • 8.7.1.3 Mean SNR

          • 8.7.1.4 Average BER

        • 8.7.2 Nakagami Fading Environment

          • 8.7.2.1 Average BER

      • 8.8 Macroscopic Diversity Combiner

        • 8.8.1 Effect of Shadowing

          • 8.8.1.1 Selection Combiner

          • 8.8.1.2 Maximum Ratio Combiner

        • 8.8.2 Microscopic Plus Macroscopic Diversity

      • Notation and Abbreviations

      • References

Nội dung

[...]... Omnidirectional antennas radiate equal amounts of power in all directions Also known as isotropic antennas, they have equal gain in all directions Directional antennas, on the other hand, have more gain in certain directions and less in others A direction in which the gain is maximum is referred to as the antenna boresight The gain of directional antennas in the boresight is more than that of omnidirectional antennas, ... current demand for smart antennas to increase channel capacity in the fast-growing area of mobile communications has reignited the research and development efforts in this area around the world [God97] This book aims to help researchers and developers by providing a comprehensive and detailed treatment of the subject matter Throughout the book, references are provided in which smart antennas have been... 1.3 Power Pattern 1.4 Beam Steering 1.5 Degree of Freedom 1.6 Optimal Antenna 1.7 Adaptive Antenna 1.8 Smart Antenna 1.9 Book Outline References Widespread interest in smart antennas has continued for several decades due to their use in numerous applications The first issue of IEEE Transactions of Antennas and Propagation, published in 1964 [IEE64], was followed by special issues of various journals... pattern For adaptive antennas, the conventional antenna pattern concepts of beam width, side lobes, and main beams are not used, as the antenna weights are designed to achieve a set performance criterion such as maximization of the output SNR On the other hand, in conventional phase-array design these characteristics are specified at the time of design 1.8 Smart Antenna The term smart antenna incorporates... of Antennas in Wireless Communications, CRC Press, Boca Raton, FL, 2002 Hay85 Haykin, S., Ed., Array Signal Processing, Prentice Hall, New York, 1985 Hay92 Haykin, S et al., Some aspects of array signal processing, IEE Proc., 139, Part F, 1–19, 1992 Hud81 Hudson, J.E., Adaptive Array Principles, Peter Peregrins, New York, 1981 IEE64 IEEE, Special issue on active and adaptive antennas, IEEE Trans Antennas. .. and adaptive antennas, IEEE Trans Antennas Propagat., 12, 1964 IEE76 IEEE, Special issue on adaptive antennas, IEEE Trans Antennas Propagat., 24, 1976 IEE85 IEEE, Special issue on beamforming, IEEE J Oceanic Eng., 10, 1985 IEE86 IEEE, Special issue on adaptive processing antenna systems, IEEE Trans Antennas Propagat., 34, 1986 IEE87a IEEE, Special issue on adaptive systems and applications, IEEE Trans... environment Chapter 8 considers multiple antenna systems and presents various diversity-combining techniques References App76 Applebaum, S.P., Adaptive arrays, IEEE Trans Antennas Propagat., 24, 585–598, 1976 Com88 Compton Jr., R.T., Adaptive Antennas: Concepts and Performances, Prentice Hall, New York, 1988 d’A80 d’Assumpcao, H.A., Some new signal processors for array of sensors, IEEE Trans Inf Theory, 26,... optimal antennas The antenna pattern in this case has a main beam pointed in the desired signal direction, and has a null in the direction of the interference Assume that the interference is not stationary but moving slowly If optimal performance is to be maintained, the antenna pattern needs to adjust so that the null position remains in the moving interference direction A system using adaptive antennas. .. Antenna The term smart antenna incorporates all situations in which a system is using an antenna array and the antenna pattern is dynamically adjusted by the system as required Thus, a system employing smart antennas processes signals induced on a sensor array A block diagram of such a system is shown in Figure 1.2 © 2004 by CRC Press LLC Sensor 1 Sensor 2 Processor Output Sensor L Additional Information... adaptive antenna array processing and their application to mobile communications Included among his many publications are two significant papers in the Proceedings of the IEEE Prof Godara edited Handbook of Antennas for Wireless Communications, published by CRC Press in 2002 Professor Godara is a Senior Member of the IEEE and a Fellow of the Acoustical Society of America He was awarded the University College . Saroj © 2004 by CRC Press LLC Preface Smart antennas involve processing of signals induced on an array of sensors such as antennas, microphones, and hydrophones interference. The smart antenna field has been a very active area of research for over four decades. During this time, many types of processors for smart antennas

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