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[EBook] (2004 CRC) Smart.Antennas.pdf
(2004 CRC) Smart.Antennas.pdf
Lal Chand Godara
1 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
2 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
Notation and Abbreviations
References
3 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 Estimates
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
Notation and Abbreviations
References
Appendices |
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