Applied Signal Processing and Communications

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Course Highlights

This 3-day course is specially designed to provide participants with the essential knowledge to understand and develop applications using Signal Processing and Communications tools in MATLAB and SIMULINK environment.  The training will provide the essential knowledge for simulation and implementation of signal processing algorithms and communication systems with the relevant toolboxes and blocksets.  The course concludes with a mini-project which requires the participants to apply all the important modeling and simulation skills they have learnt.

Prerequisites

Attended "Comprehensive MATLAB " and "Comprehensive SIMULINK", or equivalent experience using MATLAB & SIMULINK. Participants are expected to have some exposure to signal processing & communications techniques prior to taking this course.


Course Outline

Day One

Signals in MATLAB
Objective: Learn how to create and manipulate signals using the command line and the SPTool, a graphical user interface (GUI) in the Signal Processing Toolbox. Throughout the course, we will use the SPTool to analyze digital signals, filters, and spectra.

  • Creating and importing signals
  • Sampling and resampling
  • Visualizing signals
  • Modeling noise

Spectral Analysis
Objective: Gain an understanding of statistical signal processing. Explore visualization and analysis of signals in the time and frequency domains using spectral analysis.

  • Signal statistics
  • Discrete Fourier transform
  • Power spectral density estimation
  • Time-varying spectra

LTI Systems
Objective: Gain an understanding of linear time-independent systems, the basis for filtering applications and the subject of the majority of functions in the Signal Processing Toolbox. We discuss various ways to represent such systems, both mathematically and in MATLAB. Investigation of the basic input/output behavior of these systems introduces filtering.

  • LTI system representations
  • The z-Transform
  • Frequency and impulse response
  • Introduction to filtering

IIR Filter Design
Objective: Apply LTI system analysis to filter design and discuss the use of IIR filters from initial performance specifications to analog prototyping and digital design. The Filter Design and Analysis Tool (FDATool) GUI is introduced, and will be used for the remainder of the course to assist in filter design.

  • Filter specifications
  • Filter design functions
  • Introduction to the Filter Design and Analysis Tool (FDATool)

FIR Filter Design
Objective: Continue the application of LTI system analysis to filter design, and discuss the use of FIR filters from specification to digital design. Explore a variety of specialized filters.

  • FIR design methods
  • Windowing
  • Standard band filters
  • Arbitrary response filters
  • Multiband filters
  • Raised cosine filters
  • Frequency domain filtering

Day Two

Simulink Interface
Objective: This section introduces the Simulink interface and teaches basic concepts that will help new users to get comfortable with the environment.

  • Simulink Library Browser
  • Setting up a model
  • Add and Connect blocks
  • Input from MATLAB workspace
  • Model callbacks
  • Processing vectors and matrices
  • Exploring the time scope
  • Exploring the spectrum scope
  • Initializing parameters and defining data

Signal Analysis
Objective: This section uses a signal processing system to discuss important Simulink concepts such as multichannel frame-based systems, simulation from the command line, and defining system I/O. Following this section, students should be comfortable with how Simulink propagates signals and data during a simulation.

  • Analyzing a signal
  • Building an algorithm
  • Frame-based processing
  • Simulating models from the command line
  • Multichannel signals
  • Buffering
  • Introducing noise
  • Defining the system I/O using the Inport block

Filtering
Objective: This section introduces the various tools and components that help users design filters in Simulink. We introduce these filter components and apply them on various noisy signals.

  • Filtering library
  • Digital filter block
  • Filter architectures
  • Digital filter design block and FDATool
  • Filter realization wizard
  • Filter Design Toolbox library

Multirate Systems
Objective: This section discusses the concept of multirate systems. A basic multirate model is used to illustrate multirate modeling features in Simulink. The section finishes with a case study of a digital audio rate converter.

  • Multirate systems
  • Discrete solvers
  • Resampling
  • Creating subsystems
  • Aliasing and anti-aliasing filter
  • Case study: digital audio rate converter

Day Three


Communication Design with Simulink

Amplitude Modulation Using Simulink
Objective: To review Simulink topics necessary for the training.  An AM system will be built to demonstrate basic concepts in Simulink.

    • Building a simple AM model in Simulink (building a transmitter)
    • Creating a subsystem
    • Visualizing a signal in the time and frequency domain
    • Working with MATLAB data
    • Simulating the model from the command line
    • Exercise: building the AM receiver

    Modeling Using the Communications Blockset
    Objective:  To use the Communications Blockset to build an end-to-end QPSK model and to get familiar with different visualization tools in the Communication Blockset.

    • Communications Blockset Introduction
    • Creating a QPSK Transmitter Model
    • Generating a Random Source
    • Frame-Based Processing
    • QPSK Modulator
    • Scatter Plot
    • Pulse-Shaping Filter
    • Eye Diagram
    • Creating an Equivalent Receiver
    • Calculating System Delay
    • Calculating Error Rate Statistics

    Communication Systems Analysis
    Objective:  To analyze the BER performance of an end-to-end communication system by writing a MATLAB script and BERTool.
    • Performance Analysis and BER Curve
    • Automating Performance Analysis:  Scripts
    • AWGN uncode
    • Adding channel coding
    • Automating Performance Analysis:  BERTool
    • Theory Results
    • Semianalytic Technique
    • Simulation
    • BERTool: m-file Functions

    Channel Impairments and Receiver Algorithm
    Objective:  To add channel impairments and recovery blocks to test receiver performance.


    • Adding Phase and Frequency Offset
    • Correcting Phase and Frequency using DQPSK
    • Phase Recovery Block
    • Adding Timing Offset
    • Squaring Timing Recovery
    • Multi-path Channel Impairments
    • Equalization using the Embedded MATLAB Function Block

    Hands-on Mini Project: Building a General Working OFDM System
    Objective:  To apply all the important modeling and simulation skills learnt in the 3-day through a hands-on mini-project

      • Building the transmitter using IDFT
      • Building the receiver using DFT
      • Employ QPSK modulation technique