{"product_id":"nonlinear-distortion-in-wireless-systems-9780470661048","title":"Nonlinear Distortion in Wireless Systems","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis resource describes principles of modeling and simulation of nonlinear distortion in single and multichannel wireless communication systems using both deterministic and stochastic signals.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e“It is appropriate for professionals or graduate students.”  (\u003ci\u003eBook News\u003c\/i\u003e, 1 April 2012)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface xv\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eList of Abbreviations xvii\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eList of Figures xix\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eList of Tables xxvii\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAcknowledgements xxix\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Nonlinearity in Wireless Communication Systems 1\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.1.1 Power Amplifiers\u003c\/i\u003e 2\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.1.2 Low-Noise Amplifiers (LNAs)\u003c\/i\u003e 4\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.1.3 Mixers\u003c\/i\u003e 6\u003c\/p\u003e \u003cp\u003e1.2 Nonlinear Distortion in Wireless Systems 6\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.2.1 Adjacent-Channel Interference\u003c\/i\u003e 8\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.2.2 Modulation Quality and Degradation of System Performance\u003c\/i\u003e 9\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.2.3 Receiver Desensitization and Cross-Modulation\u003c\/i\u003e 11\u003c\/p\u003e \u003cp\u003e1.3 Modeling and Simulation of Nonlinear Systems 12\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.3.1 Modeling and Simulation in Engineering\u003c\/i\u003e 12\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.3.2 Modeling and Simulation for Communication System Design\u003c\/i\u003e 14\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.3.3 Behavioral Modeling of Nonlinear Systems\u003c\/i\u003e 15\u003c\/p\u003e \u003cp\u003e\u003ci\u003e1.3.4 Simulation of Nonlinear Circuits\u003c\/i\u003e 16\u003c\/p\u003e \u003cp\u003e1.4 Organization of the Book 19\u003c\/p\u003e \u003cp\u003e1.5 Summary 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Wireless Communication Systems, Standards and Signal Models 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Wireless System Architecture 21\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.1.1 RF Transmitter Architectures\u003c\/i\u003e 23\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.1.2 Receiver Architecture\u003c\/i\u003e 26\u003c\/p\u003e \u003cp\u003e2.2 Digital Signal Processing in Wireless Systems 30\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.2.1 Digital Modulation\u003c\/i\u003e 31\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.2.2 Pulse Shaping\u003c\/i\u003e 37\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.2.3 Orthogonal Frequency Division Multiplexing (OFDM)\u003c\/i\u003e 39\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.2.4 Spread Spectrum Modulation\u003c\/i\u003e 41\u003c\/p\u003e \u003cp\u003e2.3 Mobile System Standards 45\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.3.1 Second-Generation Mobile Systems\u003c\/i\u003e 46\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.3.2 Third-Generation Mobile Systems\u003c\/i\u003e 48\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.3.3 Fourth-Generation Mobile Systems\u003c\/i\u003e 51\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.3.4 Summary\u003c\/i\u003e 51\u003c\/p\u003e \u003cp\u003e2.4 Wireless Network Standards 52\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.4.1 First-Generation Wireless LANs\u003c\/i\u003e 52\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.4.2 Second-Generation Wireless LANs\u003c\/i\u003e 52\u003c\/p\u003e \u003cp\u003e\u003ci\u003e2.4.3 Third-Generation Wireless Networks (WMANs)\u003c\/i\u003e 53\u003c\/p\u003e \u003cp\u003e2.5 Nonlinear Distortion in Different Wireless Standards 55\u003c\/p\u003e \u003cp\u003e2.6 Summary 56\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Modeling of Nonlinear Systems 59\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Analytical Nonlinear Models 60\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.1 General Volterra Series Model\u003c\/i\u003e 60\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.2 Wiener Model\u003c\/i\u003e 62\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.3 Single-Frequency Volterra Models\u003c\/i\u003e 63\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.4 The Parallel Cascade Model\u003c\/i\u003e 65\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.5 Wiener–Hammerstein Models\u003c\/i\u003e 66\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.6 Multi-Input Single-Output (MISO) Volterra Model\u003c\/i\u003e 67\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.7 The Polyspectral Model\u003c\/i\u003e 67\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.8 Generalized Power Series\u003c\/i\u003e 68\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.9 Memory Polynomials\u003c\/i\u003e 69\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.10 Memoryless Models\u003c\/i\u003e 70\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.11 Power-Series Model\u003c\/i\u003e 70\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.1.12 The Limiter Family of Models\u003c\/i\u003e 72\u003c\/p\u003e \u003cp\u003e3.2 Empirical Nonlinear Models 74\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.2.1 The Three-Box Model\u003c\/i\u003e 74\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.2.2 The Abuelma’ati Model\u003c\/i\u003e 75\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.2.3 Saleh Model\u003c\/i\u003e 76\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.2.4 Rapp Model\u003c\/i\u003e 76\u003c\/p\u003e \u003cp\u003e3.3 Parameter Extraction of Nonlinear Models from Measured Data 76\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.3.1 Polynomial Models\u003c\/i\u003e 77\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.3.2 Three-Box Model\u003c\/i\u003e 79\u003c\/p\u003e \u003cp\u003e\u003ci\u003e3.3.3 Volterra Series\u003c\/i\u003e 80\u003c\/p\u003e \u003cp\u003e3.4 Summary 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Nonlinear Transformation of Deterministic Signals 83\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Complex Baseband Analysis and Simulations 84\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.1.1 Complex Envelope of Modulated Signals\u003c\/i\u003e 85\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.1.2 Baseband Equivalent of Linear System Impulse Response\u003c\/i\u003e 89\u003c\/p\u003e \u003cp\u003e4.2 Complex Baseband Analysis of Memoryless Nonlinear Systems 90\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.2.1 Power-Series Model\u003c\/i\u003e 92\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.2.2 Limiter Model\u003c\/i\u003e 92\u003c\/p\u003e \u003cp\u003e4.3 Complex Baseband Analysis of Nonlinear Systems with Memory 94\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.3.1 Volterra Series\u003c\/i\u003e 94\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.3.2 Single-Frequency Volterra Models\u003c\/i\u003e 95\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.3.3 Wiener-Hammerstein Model\u003c\/i\u003e 96\u003c\/p\u003e \u003cp\u003e4.4 Complex Envelope Analysis with Multiple Bandpass Signals 97\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.4.1 Volterra Series\u003c\/i\u003e 97\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.4.2 Single-Frequency Volterra Models\u003c\/i\u003e 99\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.4.3 Wiener-Hammerstein Model\u003c\/i\u003e 100\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.4.4 Multi-Input Single-Output Nonlinear Model\u003c\/i\u003e 103\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.4.5 Memoryless Nonlinearity-Power-Series Model\u003c\/i\u003e 104\u003c\/p\u003e \u003cp\u003e4.5 Examples–Response of Power-Series Model to Multiple Signals 106\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.1 Single Tone\u003c\/i\u003e 107\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.2 Two-Tone Signal\u003c\/i\u003e 107\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.3 Single-Bandpass Signal\u003c\/i\u003e 108\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.4 Two-Bandpass Signals\u003c\/i\u003e 108\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.5 Single Tone and a Bandpass Signal\u003c\/i\u003e 109\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.6 Multisines\u003c\/i\u003e 110\u003c\/p\u003e \u003cp\u003e\u003ci\u003e4.5.7 Multisine Analysis Using the Generalized Power-Series Model\u003c\/i\u003e 111\u003c\/p\u003e \u003cp\u003e4.6 Summary 111\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Nonlinear Transformation of Random Signals 113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Preliminaries 114\u003c\/p\u003e \u003cp\u003e5.2 Linear Systems with Stochastic Inputs 114\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.2.1 White Noise\u003c\/i\u003e 115\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.2.2 Gaussian Processes\u003c\/i\u003e 116\u003c\/p\u003e \u003cp\u003e5.3 Response of a Nonlinear System to a Random Input Signal 116\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.3.1 Power-Series Model\u003c\/i\u003e 116\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.3.2 Wiener–Hammerstein Models\u003c\/i\u003e 118\u003c\/p\u003e \u003cp\u003e5.4 Response of Nonlinear Systems to Gaussian Inputs 119\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.4.1 Limiter Model\u003c\/i\u003e 120\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.4.2 Memoryless Power-Series Model\u003c\/i\u003e 123\u003c\/p\u003e \u003cp\u003e5.5 Response of Nonlinear Systems to Multiple Random Signals 123\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.5.1 Power-Series Model\u003c\/i\u003e 124\u003c\/p\u003e \u003cp\u003e\u003ci\u003e5.5.2 Wiener–Hammerstein Model\u003c\/i\u003e 126\u003c\/p\u003e \u003cp\u003e5.6 Response of Nonlinear Systems to a Random Signal and a Sinusoid 128\u003c\/p\u003e \u003cp\u003e5.7 Summary 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Nonlinear Distortion 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Identification of Nonlinear Distortion in Digital Wireless Systems 132\u003c\/p\u003e \u003cp\u003e6.2 Orthogonalization of the Behavioral Model 134\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.2.1 Orthogonalization of the Volterra Series Model\u003c\/i\u003e 136\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.2.2 Orthogonalization of Wiener Model\u003c\/i\u003e 137\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.2.3 Orthogonalization of the Power-Series Model\u003c\/i\u003e 139\u003c\/p\u003e \u003cp\u003e6.3 Autocorrelation Function and Spectral Analysis of the Orthogonalized Model 140\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.3.1 Output Autocorrelation Function\u003c\/i\u003e 142\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.3.2 Power Spectral Density\u003c\/i\u003e 142\u003c\/p\u003e \u003cp\u003e6.4 Relationship Between System Performance and Uncorrelated Distortion 144\u003c\/p\u003e \u003cp\u003e6.5 Examples 146\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.5.1 Narrowband Gaussian Noise\u003c\/i\u003e 146\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.5.2 Multisines with Deterministic Phases\u003c\/i\u003e 148\u003c\/p\u003e \u003cp\u003e\u003ci\u003e6.5.3 Multisines with Random Phases\u003c\/i\u003e 152\u003c\/p\u003e \u003cp\u003e6.6 Measurement of Uncorrelated Distortion 154\u003c\/p\u003e \u003cp\u003e6.7 Summary 155\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Nonlinear System Figures of Merit 157\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Analogue System Nonlinear Figures of Merit 158\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.1.1 Intermodulation Ratio\u003c\/i\u003e 158\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.1.2 Intercept Points\u003c\/i\u003e 159\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.1.3 1-dB Compression Point\u003c\/i\u003e 160\u003c\/p\u003e \u003cp\u003e7.2 Adjacent-Channel Power Ratio (ACPR) 161\u003c\/p\u003e \u003cp\u003e7.3 Signal-to-Noise Ratio (SNR) 161\u003c\/p\u003e \u003cp\u003e7.4 CDMA Waveform Quality Factor (\u003ci\u003eρ\u003c\/i\u003e) 163\u003c\/p\u003e \u003cp\u003e7.5 Error Vector Magnitude (EVM) 163\u003c\/p\u003e \u003cp\u003e7.6 Co-Channel Power Ratio (CCPR) 164\u003c\/p\u003e \u003cp\u003e7.7 Noise-to-Power Ratio (NPR) 164\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.7.1 NPR of Communication Signals\u003c\/i\u003e 165\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.7.2 NBGN Model for Input Signal\u003c\/i\u003e 166\u003c\/p\u003e \u003cp\u003e7.8 Noise Figure in Nonlinear Systems 167\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.8.1 Nonlinear Noise Figure\u003c\/i\u003e 169\u003c\/p\u003e \u003cp\u003e\u003ci\u003e7.8.2 NBGN Model for Input Signal and Noise\u003c\/i\u003e 171\u003c\/p\u003e \u003cp\u003e7.9 Summary 173\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Communication System Models and Simulation in MATLAB\u003c\/b\u003e® \u003cb\u003e175\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Simulation of Communication Systems 176\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.1.1 Random Signal Generation\u003c\/i\u003e 176\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.1.2 System Models\u003c\/i\u003e 176\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.1.3 Baseband versus Passband Simulations\u003c\/i\u003e 177\u003c\/p\u003e \u003cp\u003e8.2 Choosing the Sampling Rate in MATLAB® Simulations 178\u003c\/p\u003e \u003cp\u003e8.3 Random Signal Generation in MATLAB® 178\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.3.1 White Gaussian Noise Generator\u003c\/i\u003e 178\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.3.2 Random Matrices\u003c\/i\u003e 179\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.3.3 Random Integer Matrices\u003c\/i\u003e 179\u003c\/p\u003e \u003cp\u003e8.4 Pulse-Shaping Filters 180\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.4.1 Raised Cosine Filters\u003c\/i\u003e 180\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.4.2 Gaussian Filters\u003c\/i\u003e 182\u003c\/p\u003e \u003cp\u003e8.5 Error Detection and Correction 183\u003c\/p\u003e \u003cp\u003e8.6 Digital Modulation in MATLAB® 184\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.6.1 Linear Modulation\u003c\/i\u003e 184\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.6.2 Nonlinear Modulation\u003c\/i\u003e 186\u003c\/p\u003e \u003cp\u003e8.7 Channel Models in MATLAB® 188\u003c\/p\u003e \u003cp\u003e8.8 Simulation of System Performance in MATLAB® 188\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.8.1 BER\u003c\/i\u003e 190\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.8.2 Scatter Plots\u003c\/i\u003e 195\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.8.3 Eye Diagrams\u003c\/i\u003e 196\u003c\/p\u003e \u003cp\u003e8.9 Generation of Communications Signals in MATLAB® 198\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.9.1 Narrowband Gaussian Noise\u003c\/i\u003e 198\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.9.2 OFDM Signals\u003c\/i\u003e 199\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.9.3 DS-SS Signals\u003c\/i\u003e 203\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.9.4 Multisine Signals\u003c\/i\u003e 206\u003c\/p\u003e \u003cp\u003e8.10 Example 210\u003c\/p\u003e \u003cp\u003e8.11 Random Signal Generation in Simulink® 211\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.11.1 Random Data Sources\u003c\/i\u003e 211\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.11.2 Random Noise Generators\u003c\/i\u003e 212\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.11.3 Sequence Generators\u003c\/i\u003e 213\u003c\/p\u003e \u003cp\u003e8.12 Digital Modulation in Simulink® 214\u003c\/p\u003e \u003cp\u003e8.13 Simulation of System Performance in Simulink® 214\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.13.1 Example 1: Random Sources and Modulation\u003c\/i\u003e 216\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.13.2 Example 2: CDMA Transmitter\u003c\/i\u003e 217\u003c\/p\u003e \u003cp\u003e\u003ci\u003e8.13.3 Simulation of Wireless Standards in Simulink\u003c\/i\u003e® 220\u003c\/p\u003e \u003cp\u003e8.14 Summary 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Simulation of Nonlinear Systems in MATLAB\u003c\/b\u003e® \u003cb\u003e221\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Generation of Nonlinearity in MATLAB® 221\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.1.1 Memoryless Nonlinearity\u003c\/i\u003e 221\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.1.2 Nonlinearity with Memory\u003c\/i\u003e 222\u003c\/p\u003e \u003cp\u003e9.2 Fitting a Nonlinear Model to Measured Data 224\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.2.1 Fitting a Memoryless Polynomial Model to Measured Data\u003c\/i\u003e 224\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.2.2 Fitting a Three-Box Model to Measured Data\u003c\/i\u003e 228\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.2.3 Fitting a Memory Polynomial Model to a Simulated Nonlinearity\u003c\/i\u003e 234\u003c\/p\u003e \u003cp\u003e9.3 Autocorrelation and Spectrum Estimation 235\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.3.1 Estimation of the Autocorrelation Function\u003c\/i\u003e 235\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.3.2 Plotting the Signal Spectrum\u003c\/i\u003e 237\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.3.3 Power Measurements from a PSD\u003c\/i\u003e 239\u003c\/p\u003e \u003cp\u003e9.4 Spectrum of the Output of a Memoryless Nonlinearity 240\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.4.1 Single Channel\u003c\/i\u003e 240\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.4.2 Two Channels\u003c\/i\u003e 243\u003c\/p\u003e \u003cp\u003e9.5 Spectrum of the Output of a Nonlinearity with Memory 246\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.5.1 Three-Box Model\u003c\/i\u003e 246\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.5.2 Memory Polynomial Model\u003c\/i\u003e 249\u003c\/p\u003e \u003cp\u003e9.6 Spectrum of Orthogonalized Nonlinear Model 251\u003c\/p\u003e \u003cp\u003e9.7 Estimation of System Metrics from Simulated Spectra 256\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.7.1 Signal-to-Noise and Distortion Ratio (SNDR)\u003c\/i\u003e 257\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.7.2 EVM\u003c\/i\u003e 260\u003c\/p\u003e \u003cp\u003e\u003ci\u003e9.7.3 ACPR\u003c\/i\u003e 262\u003c\/p\u003e \u003cp\u003e9.8 Simulation of Probability of Error 263\u003c\/p\u003e \u003cp\u003e9.9 Simulation of Noise-to-Power Ratio 268\u003c\/p\u003e \u003cp\u003e9.10 Simulation of Nonlinear Noise Figure 271\u003c\/p\u003e \u003cp\u003e9.11 Summary 278\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Simulation of Nonlinear Systems in Simulink\u003c\/b\u003e® \u003cb\u003e279\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 RF Impairments in Simulink® 280\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.1.1 Communications Blockset\u003c\/i\u003e 280\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.1.2 The RF Blockset\u003c\/i\u003e 280\u003c\/p\u003e \u003cp\u003e10.2 Nonlinear Amplifier Mathematical Models in Simulink® 283\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.1 The “Memoryless Nonlinearity” Block-Communications Blockset\u003c\/i\u003e 283\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.2 Cubic Polynomial Model\u003c\/i\u003e 284\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.3 Hyperbolic Tangent Model\u003c\/i\u003e 284\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.4 Saleh Model\u003c\/i\u003e 285\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.5 Ghorbani Model\u003c\/i\u003e 285\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.6 Rapp Model\u003c\/i\u003e 285\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.7 Example\u003c\/i\u003e 286\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.2.8 The “Amplifier” Block–The RF Blockset\u003c\/i\u003e 286\u003c\/p\u003e \u003cp\u003e10.3 Nonlinear Amplifier Physical Models in Simulink® 289\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.3.1 “General Amplifier” Block\u003c\/i\u003e 290\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.3.2 “S-Parameter Amplifier” Block\u003c\/i\u003e 296\u003c\/p\u003e \u003cp\u003e10.4 Measurements of Distortion and System Metrics 297\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.4.1 Adjacent-Channel Distortion\u003c\/i\u003e 297\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.4.2 In-Band Distortion\u003c\/i\u003e 297\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.4.3 Signal-to-Noise and Distortion Ratio\u003c\/i\u003e 300\u003c\/p\u003e \u003cp\u003e\u003ci\u003e10.4.4 Error Vector Magnitude\u003c\/i\u003e 300\u003c\/p\u003e \u003cp\u003e10.5 Example: Performance of Digital Modulation with Nonlinearity 301\u003c\/p\u003e \u003cp\u003e10.6 Simulation of Noise-to-Power Ratio 302\u003c\/p\u003e \u003cp\u003e10.7 Simulation of Noise Figure in Nonlinear Systems 304\u003c\/p\u003e \u003cp\u003e10.8 Summary 306\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Basics of Signal and System Analysis 307\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Signals 308\u003c\/p\u003e \u003cp\u003eA.2 Systems 308\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Random Signal Analysis 311\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 Random Variables 312\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.1.1 Examples of Random Variables\u003c\/i\u003e 312\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.1.2 Functions of Random Variables\u003c\/i\u003e 312\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.1.3 Expectation\u003c\/i\u003e 313\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.1.4 Moments\u003c\/i\u003e 314\u003c\/p\u003e \u003cp\u003eB.2 Two Random Variables 314\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.2.1 Independence\u003c\/i\u003e 315\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.2.2 Joint Statistics\u003c\/i\u003e 315\u003c\/p\u003e \u003cp\u003eB.3 Multiple Random Variables 316\u003c\/p\u003e \u003cp\u003eB.4 Complex Random Variables 317\u003c\/p\u003e \u003cp\u003eB.5 Gaussian Random Variables 318\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.1 Single Gaussian Random Variable\u003c\/i\u003e 318\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.2 Moments of Single Gaussian Random Variable\u003c\/i\u003e 319\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.3 Jointly Gaussian Random Variables\u003c\/i\u003e 319\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.4 Price’s Theorem\u003c\/i\u003e 320\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.5 Multiple Gaussian Random Variable\u003c\/i\u003e 320\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.5.6 Central Limit Theorem\u003c\/i\u003e 321\u003c\/p\u003e \u003cp\u003eB.6 Random Processes 321\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.6.1 Stationarity\u003c\/i\u003e 322\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.6.2 Ergodicity\u003c\/i\u003e 323\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.6.3 White Processes\u003c\/i\u003e 323\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.6.4 Gaussian Processes\u003c\/i\u003e 324\u003c\/p\u003e \u003cp\u003eB.7 The Power Spectrum 324\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.7.1 White Noise Processes\u003c\/i\u003e 325\u003c\/p\u003e \u003cp\u003e\u003ci\u003eB.7.2 Narrowband Processes\u003c\/i\u003e 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix C Introduction to MATLAB\u003c\/b\u003e® \u003cb\u003e329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eC.1 MATLAB® Scripts 329\u003c\/p\u003e \u003cp\u003eC.2 MATLAB® Structures 330\u003c\/p\u003e \u003cp\u003eC.3 MATLAB® Graphics 330\u003c\/p\u003e \u003cp\u003eC.4 Random Number Generators 330\u003c\/p\u003e \u003cp\u003eC.5 Moments and Correlation Functions of Random Sequences 332\u003c\/p\u003e \u003cp\u003eC.6 Fourier Transformation 332\u003c\/p\u003e \u003cp\u003eC.7 MATLAB® Toolboxes 333\u003c\/p\u003e \u003cp\u003e\u003ci\u003eC.7.1 The Communication Toolbox\u003c\/i\u003e 334\u003c\/p\u003e \u003cp\u003e\u003ci\u003eC.7.2 The RF Toolbox\u003c\/i\u003e 334\u003c\/p\u003e \u003cp\u003eC.8 Simulink® 335\u003c\/p\u003e \u003cp\u003e\u003ci\u003eC.8.1 The Communication Blockset\u003c\/i\u003e 339\u003c\/p\u003e \u003cp\u003e\u003ci\u003eC.8.2 The RF Blockset\u003c\/i\u003e 339\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReferences 341\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex 347\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402395623767,"sku":"9780470661048","price":85.46,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470661048.jpg?v=1730480271","url":"https:\/\/bookcurl.com\/products\/nonlinear-distortion-in-wireless-systems-9780470661048","provider":"Book Curl","version":"1.0","type":"link"}