LEADER 01176nas 2200349 a 450 001 9910143859603321 005 20180322132532.0 011 $a1793-7019 035 $a(OCoLC)11878005 035 $a(CKB)954921380786 035 $a(CONSER) 84942114 035 $a(EXLCZ)99954921380786 100 $a19850402a19849999 uy a 101 0 $aeng 200 00$aAsia-Pacific journal of operational research 210 $aSingapore $cOperational Research Society of Singapore$d1984- 215 $av. $cill. ;$d25 cm 300 $aTitle from cover. 300 $aRefereed/Peer-reviewed 311 $a0217-5959 606 $aManagement$xSimulation methods$vPeriodicals 606 $aOperations research$vPeriodicals 615 0$aManagement$xSimulation methods 615 0$aOperations research 676 $a658.4/034/05 712 02$aOperational Research Society of Singapore. 712 02$aAssociation of Asian-Pacific Operational Research Societies within IFORS. 712 02$aOperational Research Society of New Zealand. 906 $aJOURNAL 912 $a9910143859603321 996 $aAsia-Pacific journal of operational research$92125723 997 $aUNINA LEADER 14957nam 2200793 450 001 9910141173203321 005 20230125185419.0 010 $a1-119-96411-3 010 $a1-299-18959-8 010 $a1-119-96173-4 010 $a1-119-96172-6 024 7 $a10.1002/9781119961734 035 $a(CKB)2670000000134021 035 $a(EBL)826877 035 $a(SSID)ssj0000571059 035 $a(PQKBManifestationID)11335619 035 $a(PQKBTitleCode)TC0000571059 035 $a(PQKBWorkID)10611240 035 $a(PQKB)10466806 035 $a(CaBNVSL)mat06542367 035 $a(IDAMS)0b00006481da1aab 035 $a(IEEE)6542367 035 $a(Au-PeEL)EBL826877 035 $a(CaPaEBR)ebr10522316 035 $a(CaONFJC)MIL450209 035 $a(OCoLC)773300998 035 $a(MiAaPQ)EBC826877 035 $a(PPN)165282460 035 $a(EXLCZ)992670000000134021 100 $a20151222d2011 uy 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNonlinear distortion in wireless systems $emodeling and simulation with MATLAB /$fKhaled M. Gharaibeh 205 $a2nd ed. 210 1$aChichester, West Sussex, U.K. :$cIEEE Press/Wiley,$d2012 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2011] 215 $a1 online resource (387 p.) 225 1 $aWiley - IEEE 300 $aDescription based upon print version of record. 311 $a0-470-66104-6 320 $aIncludes bibliographical references and index. 327 $aPreface xv -- List of Abbreviations xvii -- List of Figures xix -- List of Tables xxvii -- Acknowledgements xxix -- 1 Introduction 1 -- 1.1 Nonlinearity in Wireless Communication Systems 1 -- 1.1.1 Power Amplifiers 2 -- 1.1.2 Low-Noise Amplifiers (LNAs) 4 -- 1.1.3 Mixers 6 -- 1.2 Nonlinear Distortion in Wireless Systems 6 -- 1.2.1 Adjacent-Channel Interference 8 -- 1.2.2 Modulation Quality and Degradation of System Performance 9 -- 1.2.3 Receiver Desensitization and Cross-Modulation 11 -- 1.3 Modeling and Simulation of Nonlinear Systems 12 -- 1.3.1 Modeling and Simulation in Engineering 12 -- 1.3.2 Modeling and Simulation for Communication System Design 14 -- 1.3.3 Behavioral Modeling of Nonlinear Systems 15 -- 1.3.4 Simulation of Nonlinear Circuits 16 -- 1.4 Organization of the Book 19 -- 1.5 Summary 20 -- 2 Wireless Communication Systems, Standards and Signal Models 21 -- 2.1 Wireless System Architecture 21 -- 2.1.1 RF Transmitter Architectures 23 -- 2.1.2 Receiver Architecture 26 -- 2.2 Digital Signal Processing in Wireless Systems 30 -- 2.2.1 Digital Modulation 31 -- 2.2.2 Pulse Shaping 37 -- 2.2.3 Orthogonal Frequency Division Multiplexing (OFDM) 39 -- 2.2.4 Spread Spectrum Modulation 41 -- 2.3 Mobile System Standards 45 -- 2.3.1 Second-Generation Mobile Systems 46 -- 2.3.2 Third-Generation Mobile Systems 48 -- 2.3.3 Fourth-Generation Mobile Systems 51 -- 2.3.4 Summary 51 -- 2.4 Wireless Network Standards 52 -- 2.4.1 First-Generation Wireless LANs 52 -- 2.4.2 Second-Generation Wireless LANs 52 -- 2.4.3 Third-Generation Wireless Networks (WMANs) 53 -- 2.5 Nonlinear Distortion in Different Wireless Standards 55 -- 2.6 Summary 56 -- 3 Modeling of Nonlinear Systems 59 -- 3.1 Analytical Nonlinear Models 60 -- 3.1.1 General Volterra Series Model 60 -- 3.1.2 Wiener Model 62 -- 3.1.3 Single-Frequency Volterra Models 63 -- 3.1.4 The Parallel Cascade Model 65 -- 3.1.5 Wiener-Hammerstein Models 66 -- 3.1.6 Multi-Input Single-Output (MISO) Volterra Model 67 -- 3.1.7 The Polyspectral Model 67. 327 $a3.1.8 Generalized Power Series 68 -- 3.1.9 Memory Polynomials 69 -- 3.1.10 Memoryless Models 70 -- 3.1.11 Power-Series Model 70 -- 3.1.12 The Limiter Family of Models 72 -- 3.2 Empirical Nonlinear Models 74 -- 3.2.1 The Three-Box Model 74 -- 3.2.2 The Abuelma'ati Model 75 -- 3.2.3 Saleh Model 76 -- 3.2.4 Rapp Model 76 -- 3.3 Parameter Extraction of Nonlinear Models from Measured Data 76 -- 3.3.1 Polynomial Models 77 -- 3.3.2 Three-Box Model 79 -- 3.3.3 Volterra Series 80 -- 3.4 Summary 80 -- 4 Nonlinear Transformation of Deterministic Signals 83 -- 4.1 Complex Baseband Analysis and Simulations 84 -- 4.1.1 Complex Envelope of Modulated Signals 85 -- 4.1.2 Baseband Equivalent of Linear System Impulse Response 89 -- 4.2 Complex Baseband Analysis of Memoryless Nonlinear Systems 90 -- 4.2.1 Power-Series Model 92 -- 4.2.2 Limiter Model 92 -- 4.3 Complex Baseband Analysis of Nonlinear Systems with Memory 94 -- 4.3.1 Volterra Series 94 -- 4.3.2 Single-Frequency Volterra Models 95 -- 4.3.3 Wiener-Hammerstein Model 96 -- 4.4 Complex Envelope Analysis with Multiple Bandpass Signals 97 -- 4.4.1 Volterra Series 97 -- 4.4.2 Single-Frequency Volterra Models 99 -- 4.4.3 Wiener-Hammerstein Model 100 -- 4.4.4 Multi-Input Single-Output Nonlinear Model 103 -- 4.4.5 Memoryless Nonlinearity-Power-Series Model 104 -- 4.5 Examples-Response of Power-Series Model to Multiple Signals 106 -- 4.5.1 Single Tone 107 -- 4.5.2 Two-Tone Signal 107 -- 4.5.3 Single-Bandpass Signal 108 -- 4.5.4 Two-Bandpass Signals 108 -- 4.5.5 Single Tone and a Bandpass Signal 109 -- 4.5.6 Multisines 110 -- 4.5.7 Multisine Analysis Using the Generalized Power-Series Model 111 -- 4.6 Summary 111 -- 5 Nonlinear Transformation of Random Signals 113 -- 5.1 Preliminaries 114 -- 5.2 Linear Systems with Stochastic Inputs 114 -- 5.2.1 White Noise 115 -- 5.2.2 Gaussian Processes 116 -- 5.3 Response of a Nonlinear System to a Random Input Signal 116 -- 5.3.1 Power-Series Model 116 -- 5.3.2 Wiener-Hammerstein Models 118 -- 5.4 Response of Nonlinear Systems to Gaussian Inputs 119. 327 $a5.4.1 Limiter Model 120 -- 5.4.2 Memoryless Power-Series Model 123 -- 5.5 Response of Nonlinear Systems to Multiple Random Signals 123 -- 5.5.1 Power-Series Model 124 -- 5.5.2 Wiener-Hammerstein Model 126 -- 5.6 Response of Nonlinear Systems to a Random Signal and a Sinusoid 128 -- 5.7 Summary 129 -- 6 Nonlinear Distortion 131 -- 6.1 Identification of Nonlinear Distortion in Digital Wireless Systems 132 -- 6.2 Orthogonalization of the Behavioral Model 134 -- 6.2.1 Orthogonalization of the Volterra Series Model 136 -- 6.2.2 Orthogonalization of Wiener Model 137 -- 6.2.3 Orthogonalization of the Power-Series Model 139 -- 6.3 Autocorrelation Function and Spectral Analysis of the Orthogonalized Model 140 -- 6.3.1 Output Autocorrelation Function 142 -- 6.3.2 Power Spectral Density 142 -- 6.4 Relationship Between System Performance and Uncorrelated Distortion 144 -- 6.5 Examples 146 -- 6.5.1 Narrowband Gaussian Noise 146 -- 6.5.2 Multisines with Deterministic Phases 148 -- 6.5.3 Multisines with Random Phases 152 -- 6.6 Measurement of Uncorrelated Distortion 154 -- 6.7 Summary 155 -- 7 Nonlinear System Figures of Merit 157 -- 7.1 Analogue System Nonlinear Figures of Merit 158 -- 7.1.1 Intermodulation Ratio 158 -- 7.1.2 Intercept Points 159 -- 7.1.3 1-dB Compression Point 160 -- 7.2 Adjacent-Channel Power Ratio (ACPR) 161 -- 7.3 Signal-to-Noise Ratio (SNR) 161 -- 7.4 CDMA Waveform Quality Factor (?) 163 -- 7.5 Error Vector Magnitude (EVM) 163 -- 7.6 Co-Channel Power Ratio (CCPR) 164 -- 7.7 Noise-to-Power Ratio (NPR) 164 -- 7.7.1 NPR of Communication Signals 165 -- 7.7.2 NBGN Model for Input Signal 166 -- 7.8 Noise Figure in Nonlinear Systems 167 -- 7.8.1 Nonlinear Noise Figure 169 -- 7.8.2 NBGN Model for Input Signal and Noise 171 -- 7.9 Summary 173 -- 8 Communication System Models and Simulation in MATLABª 175 -- 8.1 Simulation of Communication Systems 176 -- 8.1.1 Random Signal Generation 176 -- 8.1.2 System Models 176 -- 8.1.3 Baseband versus Passband Simulations 177 -- 8.2 Choosing the Sampling Rate in MATLABª Simulations 178. 327 $a8.3 Random Signal Generation in MATLABª 178 -- 8.3.1 White Gaussian Noise Generator 178 -- 8.3.2 Random Matrices 179 -- 8.3.3 Random Integer Matrices 179 -- 8.4 Pulse-Shaping Filters 180 -- 8.4.1 Raised Cosine Filters 180 -- 8.4.2 Gaussian Filters 182 -- 8.5 Error Detection and Correction 183 -- 8.6 Digital Modulation in MATLABª 184 -- 8.6.1 Linear Modulation 184 -- 8.6.2 Nonlinear Modulation 186 -- 8.7 Channel Models in MATLABª 188 -- 8.8 Simulation of System Performance in MATLABª 188 -- 8.8.1 BER 190 -- 8.8.2 Scatter Plots 195 -- 8.8.3 Eye Diagrams 196 -- 8.9 Generation of Communications Signals in MATLABª 198 -- 8.9.1 Narrowband Gaussian Noise 198 -- 8.9.2 OFDM Signals 199 -- 8.9.3 DS-SS Signals 203 -- 8.9.4 Multisine Signals 206 -- 8.10 Example 210 -- 8.11 Random Signal Generation in Simulinkª 211 -- 8.11.1 Random Data Sources 211 -- 8.11.2 Random Noise Generators 212 -- 8.11.3 Sequence Generators 213 -- 8.12 Digital Modulation in Simulinkª 214 -- 8.13 Simulation of System Performance in Simulinkª 214 -- 8.13.1 Example 1: Random Sources and Modulation 216 -- 8.13.2 Example 2: CDMA Transmitter 217 -- 8.13.3 Simulation of Wireless Standards in Simulinkª 220 -- 8.14 Summary 220 -- 9 Simulation of Nonlinear Systems in MATLABª 221 -- 9.1 Generation of Nonlinearity in MATLABª 221 -- 9.1.1 Memoryless Nonlinearity 221 -- 9.1.2 Nonlinearity with Memory 222 -- 9.2 Fitting a Nonlinear Model to Measured Data 224 -- 9.2.1 Fitting a Memoryless Polynomial Model to Measured Data 224 -- 9.2.2 Fitting a Three-Box Model to Measured Data 228 -- 9.2.3 Fitting a Memory Polynomial Model to a Simulated Nonlinearity 234 -- 9.3 Autocorrelation and Spectrum Estimation 235 -- 9.3.1 Estimation of the Autocorrelation Function 235 -- 9.3.2 Plotting the Signal Spectrum 237 -- 9.3.3 Power Measurements from a PSD 239 -- 9.4 Spectrum of the Output of a Memoryless Nonlinearity 240 -- 9.4.1 Single Channel 240 -- 9.4.2 Two Channels 243 -- 9.5 Spectrum of the Output of a Nonlinearity with Memory 246. 327 $a9.5.1 Three-Box Model 246 -- 9.5.2 Memory Polynomial Model 249 -- 9.6 Spectrum of Orthogonalized Nonlinear Model 251 -- 9.7 Estimation of System Metrics from Simulated Spectra 256 -- 9.7.1 Signal-to-Noise and Distortion Ratio (SNDR) 257 -- 9.7.2 EVM 260 -- 9.7.3 ACPR 262 -- 9.8 Simulation of Probability of Error 263 -- 9.9 Simulation of Noise-to-Power Ratio 268 -- 9.10 Simulation of Nonlinear Noise Figure 271 -- 9.11 Summary 278 -- 10 Simulation of Nonlinear Systems in Simulinkª 279 -- 10.1 RF Impairments in Simulinkª 280 -- 10.1.1 Communications Blockset 280 -- 10.1.2 The RF Blockset 280 -- 10.2 Nonlinear Amplifier Mathematical Models in Simulinkª 283 -- 10.2.1 The ?Memoryless Nonlinearity? Block-Communications Blockset 283 -- 10.2.2 Cubic Polynomial Model 284 -- 10.2.3 Hyperbolic Tangent Model 284 -- 10.2.4 Saleh Model 285 -- 10.2.5 Ghorbani Model 285 -- 10.2.6 Rapp Model 285 -- 10.2.7 Example 286 -- 10.2.8 The ?Amplifier? Block-The RF Blockset 286 -- 10.3 Nonlinear Amplifier Physical Models in Simulinkª 289 -- 10.3.1 ?General Amplifier? Block 290 -- 10.3.2 ?S-Parameter Amplifier? Block 296 -- 10.4 Measurements of Distortion and System Metrics 297 -- 10.4.1 Adjacent-Channel Distortion 297 -- 10.4.2 In-Band Distortion 297 -- 10.4.3 Signal-to-Noise and Distortion Ratio 300 -- 10.4.4 Error Vector Magnitude 300 -- 10.5 Example: Performance of Digital Modulation with Nonlinearity 301 -- 10.6 Simulation of Noise-to-Power Ratio 302 -- 10.7 Simulation of Noise Figure in Nonlinear Systems 304 -- 10.8 Summary 306 -- Appendix A Basics of Signal and System Analysis 307 -- A.1 Signals 308 -- A.2 Systems 308 -- Appendix B Random Signal Analysis 311 -- B.1 Random Variables 312 -- B.1.1 Examples of Random Variables 312 -- B.1.2 Functions of Random Variables 312 -- B.1.3 Expectation 313 -- B.1.4 Moments 314 -- B.2 Two Random Variables 314 -- B.2.1 Independence 315 -- B.2.2 Joint Statistics 315 -- B.3 Multiple Random Variables 316 -- B.4 Complex Random Variables 317 -- B.5 Gaussian Random Variables 318. 327 $aB.5.1 Single Gaussian Random Variable 318 -- B.5.2 Moments of Single Gaussian Random Variable 319 -- B.5.3 Jointly Gaussian Random Variables 319 -- B.5.4 Price's Theorem 320 -- B.5.5 Multiple Gaussian Random Variable 320 -- B.5.6 Central Limit Theorem 321 -- B.6 Random Processes 321 -- B.6.1 Stationarity 322 -- B.6.2 Ergodicity 323 -- B.6.3 White Processes 323 -- B.6.4 Gaussian Processes 324 -- B.7 The Power Spectrum 324 -- B.7.1 White Noise Processes 325 -- B.7.2 Narrowband Processes 326 -- Appendix C Introduction to MATLABª 329 -- C.1 MATLABª Scripts 329 -- C.2 MATLABª Structures 330 -- C.3 MATLABª Graphics 330 -- C.4 Random Number Generators 330 -- C.5 Moments and Correlation Functions of Random Sequences 332 -- C.6 Fourier Transformation 332 -- C.7 MATLABª Toolboxes 333 -- C.7.1 The Communication Toolbox 334 -- C.7.2 The RF Toolbox 334 -- C.8 Simulinkª 335 -- C.8.1 The Communication Blockset 339 -- C.8.2 The RF Blockset 339 -- References 341 -- Index 347. 330 $a"Nonlinear Distortion in Wireless Systems: Modelling and Simulation with Matlab(r) describes the principles of modelling and simulation of nonlinear distortion in single and multichannel wireless communication systems using both deterministic and stochastic signals. Models and simulation methods of nonlinear amplifiers explain in detail how to analyze and evaluate the performance of data communication links under nonlinear amplification. The book deals with the analysis of nonlinear systems with stochastic inputs and establishes the performance metrics of communication systems with regard to nonlinearity. The relationship between nonlinear system parameters (which are model dependent) and system performance figures of merit is established when the input to the system consists of real-world communication signals. The book also addresses the problem of how to embed models of distortion in system-level simulators such as MATLAB™ and MATLAB Simulink™ where practical techniques that professionals can use immediately on their projects are presented. The book explores simulation and programming issues and provides a comprehensive reference of simulation tools for nonlinearity in wireless communication systems"--$cProvided by publisher. 410 0$aWiley - IEEE 606 $aSignal processing$xComputer simulation 606 $aElectric distortion$xComputer simulation 606 $aNonlinear systems$xComputer simulation 606 $aWireless communication systems$xComputer simulation 615 0$aSignal processing$xComputer simulation. 615 0$aElectric distortion$xComputer simulation. 615 0$aNonlinear systems$xComputer simulation. 615 0$aWireless communication systems$xComputer simulation. 676 $a621.382/2028553 700 $aGharaibeh$b Khaled M.$0900397 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910141173203321 996 $aNonlinear distortion in wireless systems$92011571 997 $aUNINA