Modeling of Digital Communication Systems Using SIMULINK
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Preface xiii
Acknowledgments xix
About the Companion website xxi
Abbreviations and Acronyms xxiii
1 Getting Started with Simulink 1
1.1 Introduction 1
1.2 Starting a Matlab Session 2
1.3 Simulink Block Libraries 3
1.4 Building a New Simulink Model 6
1.4.1 Inserting Signal Source and Scope 6
1.4.2 Setting the Source Block Parameters 8
1.4.3 Setting Scope Parameters 9
1.5 Executing the Simulink Model 11
1.6 Reconfiguring the Signal Block 14
1.7 Sample-Based Signals 16
1.8 Sending Data to Workspace 18
1.9 Using Model Explorer 19
1.10 Adding Labels to Figures 21
1.11 Selecting Model Configuration Parameters 22
1.12 Summary Discussion 24
Problems 25
2 Sinusoidal Simulink Model 27
2.1 A First Simulink Model 27
2.2 Simulink Model of Sine Wave 27
2.3 Spectrum of a Sine Wave 32
2.4 Summary Discussion 40
Problems 41
3 Digital Communications BER Performance in AWGN (BPSK and QPSK) 43
3.1 BPSK and QPSK Error Rate Performance in AWGN 43
3.2 Construction of a Simulink Model in Simple Steps 44
3.3 Comparison of Simulated and Theoretical BER 56
3.4 Alternate Simulink Model for BPSK 58
3.5 Frame-Based Simulink Model 62
3.6 QPSK Symbol Error Rate Performance 64
3.7 BPSK Fixed Point Performance 68
3.8 Summary Discussion 73
Appendix 3.A Theoretical BER Performance of BPSK in AWGN 73
Problems 75
4 Digital Communications BER Performance in AWGN (MPSK&QAM) 79
4.1 MPSK and QAM Error Rate Performance in AWGN 79
4.2 MPSK Simulink Model 79
4.3 BER for Other Alphabet Sizes 83
4.4 Fixed Point BER for MPSK 83
4.5 QAM Simulink Model 85
4.6 QAM BER for Other Alphabet Sizes Using Average Power 90
4.7 QAM BER Using Peak Power 90
4.8 Power Amplifier Constraint Using Peak Power Selection with QAM 91
4.9 Summary Discussion 99
Problems 100
5 Digital Communications BER Performance in AWGN (FSK and MSK) 101
5.1 FSK and MSK Error Rate Performance in AWGN 101
5.2 BFSK Simulink Model 101
5.3 MFSK Simulink Model 107
5.4 MSK Simulink Model 108
5.5 MSK Power Spectrum 113
5.6 Summary Discussion 116
Problems 117
6 Digital Communications BER Performance in AWGN (BPSK in Fading) 119
6.1 BPSK in Rayleigh and Rician Fading 119
6.2 BPSK BER Performance in Rayleigh Fading 119
6.3 BPSK BER Performance in Rician Fading 124
6.4 BPSK BER Performance in Rician Fading with Multipath 127
6.5 Summary Discussion 137
Appendix 6.A Theoretical BER Performance of BPSK in Rayleigh Fading 137
Appendix 6.B Theoretical BER Performance of BPSK in Rician Fading 138
Problems 139
7 Digital Communications BER Performance in AWGN (FSK in Fading) 141
7.1 FSK in Rayleigh and Rician Fading 141
7.2 BFSK BER Performance in Rayleigh Fading 141
7.3 MFSK BER Performance in Rayleigh Fading 142
7.4 BFSK BER Performance in Rician Fading 147
7.5 BFSK BER Performance in Rician Fading with Multipath 148
7.6 Summary Discussion 150
Appendix 7.A Theoretical BER Performance of FSK in Rayleigh and Rician Fading 152
Rayleigh Fading 152
Rician Fading 153
Problems 154
8 Digital Communications BER Performance (STBC) 157
8.1 Digital Modulations in Rayleigh Fading with STBC 157
8.2 BPSK BER in Rayleigh Fading with STBC 157
8.3 QAM BER in Rayleigh Fading with STBC 163
8.4 Summary Discussion 163
Appendix 8.A Space-Time Block Coding for BPSK 165
Appendix 8.B Space-Time Block Coding for 16-QAM 167
Problems 169
9 Digital Communications BER Performance in AWGN (Block Coding) 171
9.1 Digital Communications with Block Coding in AWGN 171
9.2 BER Performance of BPSK in AWGN with a Binary BCH Block Code 171
9.3 BER Performance of BPSK in AWGN with a Hamming Code 175
9.4 BER Performance of BPSK in AWGN with a Golay(24,12) Block Code 179
9.5 BER Performance of FSK in AWGN with Reed-Solomon Code 181
9.6 BER Performance of QAM in AWGN with Reed-Solomon Coding 186
9.7 Summary Discussion 190
Problems 192
10 Digital Communications BER Performance in AWGN (Block Coding and Fading) 193
10.1 Digital Communications with Block Coding in Fading 193
10.2 BER Performance of BPSK in Rayleigh Fading with Interleaving and a BCH Block Code 194
10.3 BER Performance of BFSK in Rayleigh Fading with Interleaving and a Golay(24,12) Block Code 195
10.4 BER Performance of 32-FSK in Rayleigh Fading with Interleaving and a Reed-Solomon(31,15) Block Code 201
10.5 BER Performance of 16-QAM in Rayleigh Fading with Interleaving and a Reed-Solomon(15,7) Block Code 204
10.6 BER Performance of 16-QAM in Rayleigh and Rician Fading with Interleaving and a Reed-Solomon(15,7) Block Code 208
10.7 BER Performance of BPSK in Rayleigh Fading with Interleaving and a BCH Block Code and Alamouti STBC 210
10.8 BER Performance of BFSK in Rayleigh Fading with Interleaving and a Golay(24,12) Block Code and Alamouti STBC 215
10.9 BER Performance of 32-FSK in Rayleigh Fading with Interleaving and a Reed-Solomon(31,15) Block Code and Alamouti STBC 218
10.10 BER Performance of 16-QAM in Rayleigh Fading with Interleaving and a Reed-Solomon (15,7) Block Code and Alamouti STBC 219
10.11 Summary Discussion 223
Problems 224
11 Digital Communications BER Performance in AWGN and Fading (Convolutional Coding) 225
11.1 Digital Communications with Convolutional Coding in AWGN and Fading 225
11.2 BER Performance of Convolutional Coding and BPSK in AWGN 226
11.2.1 Hard-Decision Decoding 226
11.2.2 Soft-Decision Decoding 229
11.3 BER Performance of Convolutional Coding and BPSK in AWGN and Rayleigh Fading with Interleaving (Soft- and Hard-Decision Decoding) 233
11.4 BER Performance of Convolutional Coding and BPSK and Alamouti STBC in Rayleigh Fading with Interleaving 239
11.5 Summary Discussion 243
Problems 244
12 Adaptive Equalization in Digital Communications 247
12.1 Adaptive Equalization 247
12.2 BER Performance of BPSK in Dispersive Multipath Channel Using an LMS Linear Equalizer 248
12.3 BER Performance of BPSK in Dispersive Multipath Channel Using an LMS Linear Equalizer From the Simulink Library 257
12.4 BER Performance of QPSK in a channel with ISI Using an LMS Linear Equalizer 258
12.5 BER Performance of BPSK in Dispersive Multipath Channel Using a Decision Feedback Equalizer 268
12.6 BER Performance of BPSK in Rayleigh Fading Multipath Channel Using an RLS Equalizer 273
12.6.1 RLS Equalizer Description 273
12.6.2 RLS Equalization in Rayleigh Fading with No Multipath 275
12.6.3 RLS Equalization in Rayleigh Fading with Multipath 279
12.7 Summary Discussion 280
Problems 283
13 Simulink Examples 285
13.1 Linear Predictive Coding (LPC) for Speech Compression 286
13.1.1 Speech Vocal Tract Model 289
13.1.2 Prediction Coefficients Computation 289
13.1.3 Speech Analysis and Synthesis 289
13.2 RLS Interference Cancellation 291
13.2.1 Sinusoidal Interference 291
13.2.2 Low Pass Filtered Gaussian Noise 296
13.3 Spread Spectrum 298
13.3.1 Spread Spectrum Simulink Model without In-Band Interference 298
13.3.2 Spread Spectrum Simulink Model with In-Band Interference 303
13.3.3 Spread Spectrum Simulink Model with In-Band Interference and Excision 309
13.4 Antenna Nulling 313
13.5 Kalman Filtering 320
13.5.1 Scalar Kalman Filter 322
13.5.2 Kalman Equalizer 328
13.5.3 Radar Tracking Using Extended Kalman Filter (EKF) 339
13.6 Orthogonal Frequency Division Multiplexing 343
13.7 Turbo Coding with BPSK 355
Appendix A Principal Simulink Blocks Used In Chapters 1-13 363
Appendix B Further Reading 369
Index 371
Preface
This book is designed to introduce the communications systems engineer to the use of The MathWorks® Simulink®1 for modeling and evaluating the performance of digital communications systems. Simulink is a block-oriented modeling tool that utilizes well-tested MATLAB® code to enable rapid development of simulations for communication systems modeling. This block-oriented approach obviates the need for writing new software routines. The Simulink library provides an extensive array of MathWorks-verified blocks available for assembling any specific model. Upon gaining facility with the use of Simulink, the user will have a robust engineering tool for estimating communication systems performance in instances where analytic results are unavailable, such as nonlinear systems or time-varying channels.
Scope
This book introduces the reader to Simulink, an extension of the widely-used MATLAB2 modeling tool, and the use of Simulink in modeling and simulating digital communication systems, including wireless communications systems. In contrast with other books that treat MATLAB in depth but treat Simulink only at an introductory level, this book enables the communication systems engineer to learn and use the extensive capabilities of Simulink to model a wide selection of digital communications systems and evaluate their performance for many important channel conditions.
The reader is expected to have an understanding of MATLAB and its environment. It is also expected that the reader has a basic knowledge of digital communications including modulation, coding, and channel models, digital signal processing (DSP) such as digital filtering and Fourier transforms and statistical communications. The book is not intended to be a substitute for a course in digital communications but can be a valuable accompaniment to such a course. The presentation in this text is designed to allow the user to gain familiarity with basic Simulink tools, enabling rapid construction of useful communications systems models rather than providing comprehensive Simulink training currently available from The MathWorks.
Another feature of Simulink, not treated in this book, is Simulink's capability to develop a model, produce C/C++ code and migrate the model for incorporation in an field-programmable gate array (FPGA) or DSP devices. The MathWorks Corporation provides training for this capability.
Organization of the Book
The book is organized in two parts. The first 12 chapters address Simulink models of digital communication systems using various modulation, coding, channel type, and receiver processing techniques. These chapters include theoretical results for known conditions, when available, and simulated results in other cases. Problem sets at the end of each chapter accompany topics to be emphasized. Chapter 13 provides an extensive collection of examples designed to acquaint the reader with applications that reveal the power of Simulink modeling. Appendix A summarizes principal Simulink blocks used in chapters 1-13. Appendix B provides a list of references for further reading on MATLAB and Simulink.
Chapter 1
In this chapter, the fundamentals of developing a Simulink model and its relationship to MATLAB are described. Screens encountered in a typical MATLAB session are presented.3 The Simulink library blocks are identified with a focus on the Communications System Toolbox and the DSP System Toolbox.
Chapter 2
This chapter is intended to introduce the user to the first and simplest Simulink model associated with a sinusoidal waveform. Block parameters are identified, the simulation is performed and outputs are sent to the Workspace. Blocks that display data and scopes showing waveforms are employed. A Fast Fourier Transform (FFT) block is used to compute the spectrum and compare with a sinusoid's known spectrum. Two blocks are used to determine the spectrum including a spectrum analyzer that has multiple spectrum settings. Commonly used math blocks are also incorporated into the Simulink model.
Chapter 3
This chapter introduces several topics in Simulink based on binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulations. Communications blocks for BPSK and QPSK are utilized along with communications channel blocks identified as additive white Gaussian noise (AWGN) and Gaussian noise. BPSK and QPSK bit error rate (BER) performance is simulated and compared with the corresponding theoretical BER results. Use of the bertool is shown to be a convenient technique to obtain BER performance over a range of bit energy to noise spectral density values. Sample-based and frame-based computations are presented where it is seen that frame-based computations are vector based and provide faster computation. The chapter concludes with Simulink computations employing fixed-point arithmetic.
Chapter 4
This chapter continues the development of Simulink models for coherent modulations including multi-phase PSK (MPSK) and quadrature amplitude modulation (QAM). Simulink modeling of BER performance for MPSK using floating- and fixed-point arithmetic is obtained for various alphabet sizes. Simulink modeling of QAM BER is performed for both average and peak power conditions, again with various alphabet sizes. Using an example of QAM signaling in conjunction with a nonlinear power amplifier highlights the power of Simulink to model a communication system and determine its performance in a case where theoretical results are not available.
Chapter 5
This chapter continues the development of Simulink models to determine simulated BER results focusing on binary frequency shift keying (BFSK), M-ary frequency shift keying (MFSK), minimum shift keying (MSK), and Gaussian minimum shift keying (GMSK). Comparison of simulated and theoretical performance confirms the facility to reliably estimate performance. The ability of the spectrum analyzer to exhibit a wide selection of spectral estimation techniques and parameters is demonstrated. Spectral efficiencies of BFSK, 4-FSK, MSK, and GMSK are obtained.
Chapter 6
Prior chapters have introduced Simulink models to acquaint the reader and obtain confidence in the results from Simulink model development. This chapter presents several topics in Simulink based on BPSK modulation in fading channels. Specifically both Rayleigh and Rician fading channels are incorporated in the Simulink models and used to simulate BPSK BER performance under a variety of channel conditions. Comparisons of theoretical with simulated results are performed. Simulink models that introduce multipath allow BPSK BER performance to be readily estimated and are examples where BER performance is not easily obtained analytically.
Chapter 7
Chapter 7 continues the investigation of BER performance using Simulink models incorporating Rayleigh and Rician fading channels with FSK modulation and noncoherent detection. BER performance for Simulink models implementing MFSK in Rayleigh fading is determined for a selection of alphabet sizes. This chapter concludes with a Simulink model that investigates the BER performance of coherently detected FSK in a multipath channel with Rician fading.
Chapter 8
Use of diversity is a well-known technique for mitigating the loss in performance due to fading. Space time block coding (STBC) using multiple transmit and/or receive antennas can substantially improve BER performance in these instances. The Simulink models presented here incorporate STBC for compensating for BER degradation due to channel fading. Using STBC, BER performance for BPSK and QAM modulations in Rayleigh fading is determined where it is seen that Simulink obviates the need for theoretical results.
Chapter 9
Block error control coding is an important technique to enhance communication system performance. Simulink models for BPSK in AWGN are used to develop BER performance for operation with common block codes including Hamming, Golay, and Bose-Chadhuri-Hocquenghem (BCH). Simulink models are also developed for FSK and QAM with Reed-Solomon codes. A Simulink example is provided to demonstrate the degradation due to multipath with and without coding.
Chapter 10
This chapter presents topics in Simulink based on block error control coding in a fading channel. Simulink models employing Rayleigh fading are shown for BCH coding with BPSK, Golay coding with BFSK, Reed-Solomon coding with 32-FSK, and Reed-Solomon coding with 16-QAM. In each of these cases, an interleaver is introduced. A Simulink model is also developed for Rician fading and interleaving using Reed-Solomon coding with 16-QAM. A concluding section presents Simulink models for selected block codes and modulations with STBC and interleaving in Rayleigh fading.
Chapter 11
Convolutional coding is another technique utilized to enhance communications system performance. This chapter presents topics in Simulink incorporating convolutional error control coding in an AWGN and a fading channel. Simulink models are developed for computing BER performance of convolutional coding and BPSK in AWGN and Rayleigh fading using both hard- and soft-decision decoding. This chapter concludes with a Simulink model for determining BER performance of convolutional coding and BPSK with STBC and interleaving in Rayleigh fading.
Chapter 12
Adaptive equalization has been used extensively to compensate for the degradations from...
