Problem-Based Learning in Communication Systems Using MATLAB and Simulink
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Problem-Based Learning in Communication Systems Using MATLAB and Simulink

Problem-Based Learning in Communication Systems Using MATLAB and Simulink by Kwonhue Choi and Huaping Liu | PDF Free Download.

Problem-Based Learning Contents 

  • MATLAB and Simulink Basics
  • Numerical Integration and Orthogonal Expansion
  • Fourier Series and Frequency Transfer Function
  • Fourier Transform
  • Convolution
  •  Low Pass Filter and Band Pass Filter Design
  • Sampling and Reconstruction
  • Correlation and Spectral Density
  • Amplitude Modulation
  • Quadrature Multiplexing and Frequency Division Multiplexing
  • Hilbert Transform, Analytic Signal, and SSB Modulation
  •  Voltage-Controlled Oscillator and Frequency Modulation
  •  Phase-Locked Loop and Synchronization
  •  Probability and Random Variables
  • Random Signals
  • Maximum Likelihood Detection for Binary Transmission
  • Signal Vector Space and Maximum Likelihood Detection I 
  • Signal Vector Space and Maximum Likelihood Detection II
  • Correlator-Based Maximum Likelihood Detection
  • Pulse Shaping and Matched Filter
  • BER Simulation at the Waveform Level
  • QPSK and Offset QPSK in Simulink
  • Quadrature Amplitude Modulation in Simulink
  • Convolutional Code
  • Fading, Diversity, and Combining
  • Orthogonal Frequency Division Multiplexing in AWGN Channels
  • Orthogonal Frequency Division Multiplexing over Multipath Fading Channels 
  • MIMO System—Part I: Space-Time Code
  • MIMO System—Part II: Spatial Multiplexing
  • Near-Ultrasonic Wireless Orthogonal Frequency Division Multiplexing Modem Design

Preface to Problem-Based Learning in Communication Systems Using MATLAB

The Challenges Of Learning And Teaching Communications 

Many digital communication topics taught in the traditional way require understanding mathematical expressions and algorithmic procedures to learn abstract concepts.

The majority of existing textbooks facilitate teaching this way with a systematic and thorough explanation of communication theories and concepts, mainly via mathematical models and algorithmic procedures.

This is the natural outcome when computers and software were not so universally accessible decades ago as they are today.

However, most students find such a way of learning digital communications ineffective and often frustrating. And even if they are able to follow the instructors in the classroom, their understanding of the concepts is often superficial.

The accessibility of powerful software like MATLAB/Simulink and the Internet to students could be exploited to revolutionize the teaching of math-intensive subjects such as digital communications.

Through decades of classroom experience, we have learned that students’ learning becomes significantly more effective if they are led to “construct” the system themselves and observe waveforms and statistics at various stages of the system or algorithm, a process called “active” learning here.

However, given the tools and texts available on the market to the instructors, implementing this active learning process is by no means easy.

First, the majority of the textbooks are optimized for instruction in the traditional way. Some recent textbooks provide problems that involve the use of MATLAB/Simulink or similar software and codes or computer models to perform certain simulations.

Readers can replicate these codes/models and conduct simulation, which would certainly reinforce some aspects they have learned.

Such an approach is still far short of encouraging active learning by students. Second, there are some existing hardware training kits designed for educational purposes that can be used for labs/experiments of communications classes.

However, these training kits are often expensive and cover only a limited number of topics of communication.

Additionally, students need to learn hardware design skills such as DSP programming and VHDL to be able to use such a tool.

Unique Features Of This Book

This book is written to encourage the active learning of communication theories and systems by its readers.

Toward this goal, major communication concepts and algorithms are examined through carefully designed MATLAB/Simulink projects. Each project implements the simulation construction and execution steps or sequences that match how an actual communications system or algorithm works.

These steps progressively explore the intermediate results between steps that students can “see” and comprehend what happens behind theories and mathematical expressions. The bulk of MATLAB simulation codes or Simulink models for these projects are provided.

This ensures that students will be able to complete even complex projects such as Viterbi decoding, multiple-input multiple-output (MIMO) detection, and orthogonal frequency division multiplexing (OFDM) demodulation.

However, important parameters and codes lines or model blocks that are critical for learning the algorithm or communications process are left out for students to complete.

This makes mechanically executing a certain completed code without understanding the technical details impossible. Step-by-step instructions are designed for each problem.

Readers can conveniently check the results of each intermediate step and compare the various parameter choices and their effects and are thus led to actively figure out the intended answers and build up a complete system/algorithm.

Summarizing it, this book is written with the following three main goals in mind:

  1. The framework of the codes/models provided in the book efficiently guides students through the simulation and actively engages students in learning the materials.
  2. The codes/blocks provided minimize the number of times students needs to complete their simulations and ensure that they will be able to complete even complex projects without getting lost in the middle and giving up. 
  3. In completing the main algorithm/concept-specific incomplete parts, students will effectively be internalizing the theories.

In Chapters 4, 7, 9, 10, 11, 13, 20, 22, 23, and 30, students will learn how to convert constructed waveforms in simulations into electric signals and then listen to those signals if they are audio signals, or observe the eye-patterns, scatter plots, or signal trajectories by using an oscilloscope for digitally modulated signals.

In Chapters 13 and 30, students are encouraged to complete actual wireless communications in the band near-ultrasonic frequencies, requiring only a mobile phone and a PC with a microphone.

We have found that all such present-day projects that embrace student interests can motivate them to explore more intensely how communication systems work.

Although students are not required to know MATLAB/Simulink to use this book, Chapter 1 provides carefully designed projects that enable students to self-learn the MATLAB/Simulink skills needed for the rest of the projects in this book.

All that a student needs are access to MATLAB, a headphone, and an oscilloscope for some projects.

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