Mathworks COMMUNICATIONS BLOCKSET 4 user guide

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Communications Bl

Getting Started Guide

ockset™ 4

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Communications Blockset™ Getting Started Guide

The software described in this document is furnished under a license agreement. The software may be used or copied only under the terms of the license agreement. No part of this manual may be photocopied or reproduced in any form without prior written consent from The MathW orks, Inc.

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Revision History

June 2001 Online only New for Version 2.0.2 (Release 12.1) July 2002 First printing Revised for Version 2.5 (Release 13) June 2004 Online only Revised for Version 3.0 (Release 14) October 2004 Second printing Revised for Version 3.0.1 (Release 14SP1) March 2005 Online only Revised for Version 3.1 (Release 14SP2) August 2005 Third printing Minor Revision for V ersion 3.1 September 2005 Online only Revised for Version 3.2 (Release 14SP3) March 2006 Online only Revised for Version 3.3 (Release 2006a) September 2006 Online only Revised for Version 3.4 (Release 2006b) March 2007 Online only Revised for Version 3.5 (Release 2007a) September 2007 Online only Revised for Version 3.6 (Release 2007b) March 2008 Fourth printing Major Revision for Version 4.0 (Release 2008a) October 2008 Online only Revised for Version 4.1 (Release 2008b) March 2009 Online only Revised for Version 4.2 (Release 2009a) September 2009 Online only Revised for Version 4.3 (Release 2009b) March 2010 Online only Revised for Version 4.4 (Release 2010a)

Introduction

Communications Blockset Product Overview ........ 1-2

Contents

Installing Com munications Blockset Software

....... 1-3

Building Models

Running a Simulink Model ......................... 2-2

Section Overview Opening the Model Overview o f the Model Quadrature Amplitude Modulation Running a Simulation Displaying the Error Rate Setting Block Parameters Displaying a Plot of Phase Noise More Demos

Building a Simple Model

Section Overview Using commstartup to Set Simulation Parameters Opening a New Model Window Opening Block Libraries Moving Blocks into the Model Window Connecting Blocks Setting Block Parameters Setting Simulation Parameters Running the Model Adding Noise to the Model Saving a Model Frames and Frame-Based Processing

.................................. 2-2

................................ 2-2

............................. 2-3

................... 2-4

.............................. 2-5

.......................... 2-6

........................... 2-7

..................... 2-8

...................................... 2-10

........................... 2-11

.................................. 2-11

...... 2-12

...................... 2-12

............................ 2-13

................ 2-14

................................. 2-15

........................... 2-16

...................... 2-17

................................ 2-18

.......................... 2-19

................................... 2-21

................. 2-22

Discrete Signals and Sample Times ................... 2-22

Continuous Signals

................................ 2-22

Building a Channel Noise Model

Section Overview Overview o f the Model Selecting Blocks for the Channel Noise Model Setting Parameters in the Channel Noise Model Connecting the Blocks Running the Channel Noise Model

Reducing the Error Rate Using a Hamming Code

Section Overview Building the Hamming Code Model Using the Hamming Encoder and Decoder Blocks Setting Parameters in the Hamming Code Model Labeling the Display Block Running the Hamming Code Model Displaying Frame Sizes Adding a Scope to the Model Setting Parameters in the Expanded Model Observing Channel Errors with the Scope

Modeling a Channel with Modulation

Section Overview Building the BPSK Model Setting Parameters in the BPSK Model Running the BPSK Model

.................................. 2-24

............................. 2-24

.............................. 2-27

.................................. 2-30

.......................... 2-33

............................ 2-34

.................................. 2-39

........................... 2-39

........................... 2-41

.................... 2-24

.......... 2-25

........ 2-26

................... 2-28

................... 2-31

................... 2-33

........................ 2-34

............ 2-35

............. 2-37

............... 2-39

............... 2-41

..... 2-30

....... 2-32

vi Contents

Reducing the Error Rate with a Cyclic Code

Section Overview Building the Cyclic Code Model Running the Cyclic Code Model Verifying the Symbol Period Using a Probe Block to Determine Symbol Period

Building a Frequency-Shift Keying Model

Section Overview Building the FSK Mo de l Setting Parameters in the FSK Model Running the FSK Model Learning About Delays in the Model

.................................. 2-42

...................... 2-42

...................... 2-44

......................... 2-44

.................................. 2-47

............................ 2-48

................. 2-49

............................ 2-50

.................. 2-51

......... 2-42

....... 2-45

........... 2-47

FindingtheDelayinaModel ........................ 2-51

Learning About Multirate Models Using Sample Time Colors to Check Sample Times

.................... 2-52

...... 2-53

Building a Convolutional Code Model

Section Overview Building the Convolutional Code Model Understanding the Blocks in the Model Setting Parameters in the Convolutional Code Model Running the Convolutional Code Model

.................................. 2-54

............... 2-54

............... 2-55

............... 2-57

Using Communications Blockset Software with

MATLAB

SendingDatatotheMATLABWorkspace ............ 3-2

Section Overview Using a Signal To Workspace Block Configuring the Signal To Workspace Block Viewing the Error Rate Data in the Workspace Sending Signal and Error D ata to the Workspace Viewing the Signal and Error Data in the Workspace Analyzing Signal and Error Data

.................................. 3-2

................... 3-2

............ 3-3

......... 3-3

....... 3-4

..................... 3-6

.... 2-56

.... 3-5

Running Simulations from the Command Line

Section Overview Running a Single Simulation Running Multiple Simulations Plotting the Results of Multiple Simulations Running Multiple Simulations Using BERTool

Importing Data from the MATLAB Workspace

Section Overview Simulating a Signal by Importing Data Simulating Noise with Imported Data Simulating Noise with Specified Error Patterns Setting Sample Times and Samples per Frame

Learning More

.................................. 3-7

........................ 3-7

....................... 3-8

........... 3-10

.................................. 3-13

................ 3-13

................. 3-14

.................................... 3-19

....... 3-7

......... 3-10

....... 3-13

......... 3-15

......... 3-16

vii

Online Help ...................................... 3-19

Demos The MathWorks Online

.......................................... 3-19

............................ 3-20

List of Examples

Getting Started .................................... A-2

Index

viii Contents

Introduction

• “Communications Blockset Product Overview” on page 1-2

• “Installing Communications Blockset Software” on page 1-3

1 Introduction

Communications Blockset Product Overview

The Communications Blockset product extends Simulink®software with a comprehensive library of blocks to design and simulate the physica l layer of communication systems and components. The blockset helps you design communications systems and their semiconductor components, such as commercial or defense wireless and wireline systems.

The key feature s of the blockset are

• Blocks for designing and simulating the physical layer of communications

systems, including modulation, source and channel encoding, channels, and equalization

• The ability to tune models and visualize the results

• Hierarchical, block-based models for visually conveying complex designs

• Integration with Communications Toolbox™ software for posts imulation

analysis

1-2

Installing Communications Blockset™ Software

Installing Communications Blockset Software

To build and run the models in this manual, you mu s t first install Communications Blockset™ software and the products it requires, which are listed below:

• MATLAB

• Simulink Software

• Signal Processing Toolbox™ Software

• Communications Toolbox Software

• Signal Processing Blockset™ Software

You can find instructions for insta ll in g these products in the MATLAB installation documentation for your platform. To determine what products are installed on your system, enter This displays information about the version of MATLAB you are running, including a list of all toolboxes an d blocksets installed on your system.

Software

ver in the MATLAB Command Window.

1-3

1 Introduction

1-4

Building Models

This chapter introduces you to Simulink and Communications Blockset software. The chapter begins by showingyouhowtorunanexistingSimulink model and how to build a simple model. It then explains how to build typical models of communication systems using Communications Blockset software. These models sho w you how to use the blockset and illustrate some of its important features.

• “Running a Simulink Model” on page 2-2

• “Building a Simple Model” on page 2-11

• “Building a Channel Noise Model” on page 2-24

• “Reducing the Error Rate Using a Hamming Code” on page 2-30

• “Modeling a Channel with Modulation” on page 2-39

• “Reducing the Error Rate with a Cyclic Code” on page 2-42

• “Building a Frequency-Shift Keying Model” on page 2-47

• “Building a Convolutional Code Model” on page 2-54

2 Building Models

Running a Simulink Model

In this section...

“Section Overview” on page 2-2

“Opening the M odel” on page 2-2

“Overview of the Model” on page 2-3

“Quadrature Amplitude Modulation” on page 2-4

“Running a Simulation” on page 2-5

“Displaying the Error Rate” on page 2-6

“Setting Block Parameters” on page 2-7

“Displaying a Plot of Phase Noise” on page 2-8

“More Demos” on pag e 2-10

Section Over view

This section describes a demo model of a communications system that comes with Communications Blockset software. The model displays a scatter plot of a signal with added noise. The purpose of this section is to familiarize you with the basics of Simulink models and how they function.

2-2

The section takes you through some key elements of working with this model.

Opening the Model

To open the m odel, first start MATLAB. In the M ATLA B Command Window , enter

commphasenoise at the prompt. This opens the model in a new window,

as shown in the following figure.

Running a Simulink®Model

Overview of the Model

The Simulink model shown in the preceding section, “Opening the Model” on page 2-2, simulates the effect of phase noise on quadrature amplitude modulation (QAM) of a signal. The Simulink model is a graphical representation of a mathematical model of a communication system that generates a random signal, modulates it using QAM, and adds noise to simulate a channel. The model also contains components for displaying the symbol error rate and a scatter plot of the modulated signal.

The blocks and lines in the Simulink model describe mathematical relationships among signals and states:

• The Random Integer Generator block, labeled Random Integer, generates a

signal consisting of a sequence of random integers between zero and 255

• The Rectangular QAM Modulator Baseband block, to the right of the

Random Integer Generator block, modulates the sig nal using b aseband 256-ary QAM.

• The AWGN Channel block models a noisy channel by adding white

Gaussian noise to the modulated signal.

2-3

2 Building Models

• The Phase Noise block introduces noise in the angle of its complex input

signal.

• The Rectangular QAM Demodulator Baseband block, to the right of the

Phase Noise block, demodulates the signal.

In addition, the following blocks in the model help you interpret the simulation:

• The Discrete-Time Scatter Plot Scope block, labeled AWGN plus Phase

Noise, displays a scatter plot of the signal with added noise.

• The Error Rate Calculation block counts symbols that differ between the

received signal and the transmitted signal.

• The Display block, at the far right of the model window, displays the

symbol error rate (SER), the total number of errors, and the total number of symbols processed during the simulation.

All these blocks are included in Communications Blockset and Simulink applications. You can find more detailed information about these blocks by right-clicking the block and selecting Help from the context menu.

2-4

Quadrature Amplitude Modulation

This model simulates quadrature amplitude modulation (QAM), which is amethodforconvertingadigitalsignaltoacomplexsignal. Themodel modulates the signal onto a sequence of complex numbers that lie on a lattice of points in the complex plane, called the constellation of the signal. The constellation for baseband 256-ary QAM is shown in the following figure.

Running a Simulink®Model

Constellation for 256-ary QAM

Running a Simulation

To run a simulation, select Simulation > Start from the top of the model window. The simulation stops automatically at the Stop time,whichis specified in the Configuration Parameters dialog box. You can stop the simulation at any time by selecting Stop from the Simulation menu at the top of the model window (or, on Microsoft Windows, by clicking the Stop buttononthetoolbar).

When you run the model, a new window appears, displaying a scatter p lot of the modulated signal with added noise, as shown in the following figure.

2-5

2 Building Models

2-6

Scatter Plot of Signal Plus Noise

The points in the scatter plot do not lie exactly on the constellation shown in thefigureConstellationfor256-aryQAMonpage2-5becauseoftheadded noise. Theradialpatternofpointsisduetotheadditionofphasenoise,which alters the angle of the complex modulated signal.

Displaying the Error Rate

The Display block displays the number of errors introduced by the channel noise. When you run the simulation, three small boxes appear in the block, as shown in the following figure, displaying the vector output from the Error Rate Calculation block.

Error Rate Display

The block displays th e output as follows:

• The first entry is the symbol error rate ( SER).

• The second entry is the total number of errors.

Running a Simulink®Model

• The third entry is the total number of comparisons made. The notation

1e+004 is shorthand for 10

Setting Block Parameters

You can control the way a Simulink block functions by setting its parameters. To view or change a block’s parameters, double-click the block. This opens a dialog box, sometimes called the block’s mask. For example, the dialog box for the Phase Noise block is shown in the following figure.

Dialog for the Phase Noise Block

To change the am ount of phase noise, click in the Phase noise level (dBc/Hz) field and enter a new value. Then click OK.

Alternatively, you can enter a variable name, such as

phasenoise,inthe

field. You can then set a value for that variable in the MATLAB Command Window, for example by entering

phasenoise = 2. Setting parameters in the

Command Window is convenient if you need to run multiple simulations with different parame ter values. See the section “Running Multiple Simulations” on page 3-8.

2-7

2 Building Models

You can also change the amount of noise in the AWGN Channel block. Double-click the block to open its dialog box, and change the value in the Es/No parameter field. This changes the signal to noise ratio, in dB. Decreasing the value of Es/No increases the noise level.

You can experiment with the model by changing these or other parameters and then running a simulation. For example,

• Change Phase noise level (dBc/Hz) to

Phase Noise block.

• Change Es/No to

This removes nearly all noise from the model. W hen you now run a simulation, the scatter plot appears as in the figure Constellation for 256-ary QAM on page 2-5.

100 in the dialog for the AWGN Channel block.

-150 in the dialog box for the

Displaying a Plot of Phase Noise

Double-click the block labeled “Disp la y Figure” at the bottom left of the model window. Thisdisplaysaplotshowingthe results of multiple simulations.

2-8

Running a Simulink®Model

Plot of BE

Each cur fixed am

You can values Multip scrip

R at Different Noise Levels

ve is a plot of bit error rate as a function of signal to noise ratio for a

ount of phase noise.

create plots like this by running multiple simula tions with different

for the Phase noise level (dBc/Hz) and Es/No parameters. “Running

le Simulations” on page 3-8 describes how to do this with a MATLAB

t, using variables for the parameters.

2-9

2 Building Models

More Demos

You can find Communications Blockset demos in the M A TLAB Help browser.

1 To open the Help browser, type doc at the MATLAB command line.

2 To see a list of demo categories, expand the Communications Blockset

node in the Help browser, then click the Demos node.

The Communications Blockset display in the Help browser.

You can find more demos for the Simulink software by typing MATLAB command line.

demo at the

2-10

Building a Simple Model

In this section...

“Section Overview” on page 2-11

“Using commstartup to Set Simulation Parameters” on page 2-12

“Opening a New Model W indow” on page 2-12

“Opening Block Libraries” on page 2-13

“Moving Blocks into the Model Window” on page 2-14

“Connecting Blocks” on page 2-15

“Setting Block Parameters” on page 2-16

“Setting Simulation Parameters” on page 2-17

“Running the Model” on page 2-18

“Adding Noise to the Model” on page 2-19

“Saving a Model” on page 2-21

Building a Simple Model

“Frames and Frame-Based Processing” on page 2-22

“Discrete Signals and Sample Times” on page 2-22

“Continuous Signals” on page 2-22

Section Over view

In the previous section, you ran a model that was already built. This section explains how to build a simple Simulink model that displays a sine wave in ascope.

Building a model usually involves several iterations, as you decide which blocks to include and what parameter settings to make. In the example in this section, you refine the model by adding noise.

For more detailed information on building models, see the Simulink documentation.

2-11

2 Building Models

Using commstart

Before starting

commstartup

at the M ATLAB p

This

• Sets the Simu

• Sets default

models

Communicat data types types, suc Communica model. Th current M each MATL

If you bu to use Si the mod

ild a model without entering

mulink blocks that output signals with Boolean data types, turn off

el’s Boolean logic signals parameter by entering

to build the model, enter

rompt.

link Boolean logic s ignals parameter to

simulation parameters that are optimal for communications

ions Blockset software does not support signals with Boolean

. If you want to use Simulink b locks that output Boolean data

h as the Logical Operator block, in a model with blocks from

tions Blockset software, enter

commstartup settings apply to any models you create d uring the

ATLAB session. You must enter

AB session to establish these settings.

up to Set Simulation Parameters

Off

commstartup before buildin g the

commstartup at the beginning of

commstartup and subsequently decide

2-12

set_param('my_model', 'BooleanDataType', 'off')

where

Openi

The f sele mode

my_model.mdl is the name of the model.

ng a New Model Window

irst step in building a model is to open a new model window. To do so,

ct File > New > M odel,andthenselectModel. This opens an empty

l window, as shown in the following figure.

Building a Simple Model

Opening Block Libraries

The next step is to select the blocks for the model. These blocks are contained in libraries. To view the libraries for the products you have installed, type

simulink at the MATLAB prompt (or click the Simulink button on the

MATLAB toolbar). The Simulink Library Browser appears.

2-13

2 Building Models

2-14

Simulink Library Browser

The left pane displays the installed products, each of which has i ts own library of blocks. To open a library, click the + signnexttothenameoftheblockset in the left pane. This displays the contents of the library in the right pane.

You can find the blocks you need to build models of communication systems in Communications Blockset, Signal Processing Blockset, and Simulink libraries.

Moving Blocks into the Model Window

The next step in building the model is to move blocks from the Simulink Library Browser into the model window. To do so,

1 Click the + sign next to Signal Processing Blockset intheleftpaneof

the Library Browser. This displays a list of the Signal Processing Blockset libraries.

Building a Simple Model

2 Click Signal Processing Sources in the left pane. This displays a list of

the Signal Processing Sources library blocks in the right pane. If you do not see the Sine Wa ve block, scroll down the list until it is visible.

3 Click the Sine Wave block and drag it into the model window.

4 Click Signal Processing Sinks intheleftpaneoftheLibraryBrowser.

5 Scroll down in the right pane of the Library Browser until you see the

Vector Scope block, and drag the block into the model window to the right oftheSineWaveblock.

Once a block is in the model window, you can move it to another position by dragging the block with the mouse.

Dragging a Block into a Model Window

Connecting Blocks

The small arrowhead pointing outward from the right side of the Sine Wave block is an output port for the data the block generates. The arrowhead pointing inward on the Vector Scope block is an input port. To connect the two blocks, click the output port of the Sine Wave block and drag the mouse toward the input port of the Vector Scope block, as shown in the following figure.

2-15

2 Building Models

When the pointer is on the input port of the Vector Scope block, release the mouse button. You should see a solid arrow appear, as in the following figure.

Ifyoudonotseeasolidarrowhead,youhavenotmadeaconnection. Inthis case, click the arrowhead again, drag it a ll the way to the Vector Scope’s input port, and release the mouse button.

2-16

Setting Block Parameters

To set parameters for the Sine Wave block, double-click the block to open its dialog box, as shown in the following figure. Change the following parameters by clicking in the field next to the parameter, deleting the default setting, and entering the new setting in its place:

1 Set Amplitude to 5.

2 Set Frequency to 30.

3 Set Samples per frame to 100.

4 Click OK.

Note You must set Samples per frame to a value larger than 1 to see an

image of the sine wave in the Scope block.

Building a Simple Model

Dialog Box for the Sine Wave Block

Setting Simulation Parameters

In addition to individual block parameters, the model also has overall simulation parameters. To view the current settings,

1 Select the Simulation menu at the top of the model window.

2 Select Configuration parameters to open the Configuration

Parameters dialog box, as shown in the following figure.

2-17

2 Building Models

Configura

If you typ

inf

set to Setting S stop it b

The Stop run tim and you

The set param

To conserve memory in a model, click Data Import/Export on the left,

Note

lear the boxes next to Time and Output under Save to workspace

and c

eright.

on th

ning the Model

Run

the model by selecting Simulation > Start. When you do so, a scope

Run

ndow appears, displaying a sine wave, as shown in the following figure.

tion Parameters Dialog Box

commstartup before creating the model, the Stop time should be

.TheStop time determinesthetimeatwhichthesimulationends.

top time to

y selecting Stop from the Simulation menu.

time is not the actual time it takes to run a simulation. The actual

e for a simulation depends on factors such as the model’s complexity

r computer’s clock speed.

tings in the Configuration Parameters dialog box affect only the

eters of the current model.

inf causes the simulation to run indefinitely, until you

2-18

Building a Simple Model

Sine Wave Displayed in a Scope

Note If you do not see the sine wave in the scope, make sure that the

Samples per frame parameterfortheSineWaveblockissetto

100.

When you are finished observing the simulation, select Simulation > Stop.

Adding Noise to the Model

You can add noise to the model using the AWGN Channel block, from the Channels library of Communications Blockset software. The block adds white Gaussian noise to the sine wave. Move the block from the Simulink Library Browser into the model window, as described in “Moving Blocks into the Model Window” on page 2-14. You can add the block to the model as follows:

1 Extend the line between the Sine Wave block and the Vector Scope block by

dragging the Vector Scope block to the right, to make room for the AWGN Channel block.

2-19

2 Building Models

2 Click the AWGN block and drag it onto the line. This automatically

connects the Sine Wave block and the Vector Scope block to the AWGN Channel block.

Sine Wave Plus Noise

Double-click the AWGN Channel block to open its dialog box, as shown in the following figure. Click the down arrow in the Mode field and select

to noise ratio (SNR)

Signal

2-20

Dialog for the AWGN Channel Block

Now when you run the model, the scope clearly shows the added noise.

Building a Simple Model

Sine Wave with Noise Added

When you are finished observing the simulation, stop the model by selecting Simulation > Stop.

Saving a Model

To sav e your mo de l for future use, select File > Save.Thefirsttimeyousave the model, this displays the Save As dialog box. In the Save in field, select thefolderwhereyouwanttosavethemodel. Itisbesttokeepyourworkfiles in a separate folder from the files shipped with the product. In the File name field, enter a name for the model, such as

To load the model in a future MATLAB session, first change your working folder to the one where you saved the file. You can do this by selecting the folder in the Current Folder field on the MATL AB toolbar. Then enter in the MATLAB Command Window.

sine.mdl,andclickSave.

sine

2-21

2 Building Models

Frames and Frame

A frame is a seque

Samples per fram

100, so that eac block to displa

Another impor Blockset bloc connect a sou you can set th required val Hamming Cod

In frame-ba simultane processed can greatl blocks, t

sed processing, all the samples in a frame are processed

ously. In sample-based processing,ontheotherhand,samplesare

one at a time. The advantage of frame-based processing is that it

y increase the speed of a simulation. If you see d ouble lines between

he model uses frame-based processing.

Discrete

The Sine

discret

of a fixe this ti In the e

Sample

and Si These syste

Wave block in Signal Processing Blockset software generates a

e signal. This means that it updates the signal at integer multiples

d time interval, called the sample time. Y ou can set the length of

me interval in the Sample time parameter in the block’s dialog box.

xample described in “Building a Simple Model” on page 2-11, the

time has the default value of gnal Processing Blockset source s generate discrete signals exclusively. sources are primarily designed for modeling digital communication

ms.

nce of samples combined into a single vector. By setting

e to

h frame contains 100 samples. This enables the Vector Scope

yenoughdataforagoodpictureofthesinewave.

tant reason to set the frame size is that many Communications

ks require their inputs to be vectors of specific sizes. If you

rce block, such as the Sine Wave block, to one of these blocks,

e input size correctly by setting Samples per frame to the

ue. The model described in “Reducing the Error Rate U sing a

e” on page 2-30 shows how to do this.

Signals and Sample Times

-Based Processing

100 in the Sine W ave block, yo u set th e frame size to

1/1000. All Communications Blockset

2-22

arn more about sample times, see “Building a Frequency-Shift Keying

To le

l” on page 2-47.

Mode

tinuous Signals

Con

Simulink libraries also c on tain blocks that generate continuous signals.

The

s means that they update the signal at variable time intervals, whose

Thi

ngth is determined by the numerical solver the simulation uses. For

Building a Simple Model

example, the Sine Wave block in the Simulink Sources library can generate a continuous sine wave.

Note Many blocks in Communications Blockset software a ccept only discrete signals. To find out whether a block accepts continuous signals, consult the reference page f or the block.

2-23

2 Building Models

Building a Channel Noise Model

In this section...

“Section Overview” on page 2-24

“Overview of the Model” on page 2-24

“Selecting Blocks for the Channel Noise Model” on pag e 2-25

“Setting Parameters in the Channel Noise Model” on page 2-26

“Connecting the Blocks” on page 2-27

“Running the Channel Noise Model” on page 2-28

Section Over view

This section shows how to build a simple model of a communication system. The model, shown in the following figure, contains the most basic elements of a communication system: a source for the signal, a channel with noise, and means of detecting errors caused by noise.

2-24

Channel Noise Model

You are encouraged to build the model for yourself, as this is the best way to learn how to use Communications Blockset software.

Overview of the Model

The channel noise model generates a random binary signal, and then switches the symbols 0 and 1 in the signal, according to a specified error probability, to simulate a channel with noise. The model then calculates the error rate and displays the result. The model contains the following components.

Building a Channel Noise Model

Source

The source for the signal in this model is the Bernoulli Binary G enerator block, which generates a random binary sequence.

Channel

The Binary Sy mmetric Channel blo ck simulates a channel with noise. The block introduces random errors to the signal by changing a 0 to a 1 or the reverse, with a probability specified by the Error probability parameter in the block’s dialog.

Error Rate Calculation

The Error Rate Calculation block calculates the error rate of the channel. The block has two input ports, labeled the received signal. The block compares the two signals and checks for errors. The output of the block is a vector with three entries:

• Bit error rate, which you expect to be approximately .01, because this is the

probability of error in the channel

Tx, for the transmitted signal, and Rx, for

• Number of errors

• Total number of bits that are transmitted

Display

The Display block displays the output of the Error Rate Calculation block, as described in “Displaying the Error Rate” on page 2-6.

Selecting Blocks for the Channel Noise Model

To bu il d the model, f irst move i ts blocks into a new mo del win do w, as fol low s:

1 Type commstartup at the MATLAB prompt to set simulation parameters

for the model.

2 Type simulink attheMATLABprompttoopentheSimulinkLibrary

Browser.

3 From the menu, select File>New>Modelto open a new model window.

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2 Building Models

4 Drag the following blocks from the Simulink Library Browser into the

model window:

• Bernoulli Binary Generator block, from the Random Data Sources

sublibrary of the Comm Sources library

• Binary Symmetric Channel block, from the Channels library

• Error Rate Calculation block, from the Comm Sinks library

• Display block, from the Simulink Sinks library

Setting Parameters in the Channel Noise Model

To set block parameters in the channel noise model, do the following:

1 Double-click the Bin a r y Symmetric Channel b lock and make the following

changes to the default parameters in the block’s dialog:

• Set Error probability to

• Clear the Output error vector check box. This removes the b lo ck’s

lower output port, which is not needed for this model.

2 Double-click the Error Rate Calculation block and make the following

changes to the default parameters in the block’s dialog:

• Set Output data to

• Select Stop simulation.

0.01.

Port to create a n output port for the block.

2-26

Building a Channel Noise Model

Selecting Stop simulation causesthesimulationtostopafterthetarget number of errors occurs or the maximum number of symbols is reached.

Initial Seeds

The Bernoulli Binary Generator block and the Binary Symmetric Channel block both use a random number generator to generate random sequences of bits. In both blocks, the Initial seed parameter initializes the random sequence. The initial seeds in the two blocks should have different values to ensure that the source signal and the channel noise are statistically independent. In general, initial seeds should have different va lu es in all blocks that have an Initial seed parameter.

Connecting the Blocks

Next, connect the blocks as shown in the following figure. Make sure to connect the arrow from the Binary Symmetric Channel block to the input port labeled “Connecting Blocks” on page 2-15.

Rx on the Error Rate Calculation block. To learn how to do this, see

2-27

2 Building Models

The next section explains how to draw the upper branch line in the model.

Drawing a Branch Line

The upper line leading from the Bernoulli Binary Generator block to the Error Rate Calculation block, shown in the following figure, is called a branch line. Branch lines carry the same signal to more than one block.

To draw the branch line, follow these steps:

1 Right-click the line between the Bernoulli Random Generator block and th e

Binary Symmetric Channel block.

2 Whileholdingdowntherightmousebutton,movethemousepointertothe

input port labeled

3 Release the mouse button. The end of the branch line should connect to the

input port of the Error Rate Calculation block.

4 Click the horizontal section of the branch line and drag it upward until the

line is above the Binary Symmetric Channel block.

Tx on the Error Rate Calculation block.

2-28

The model should now appear as in the following figure.

Running the Channel Noise Model

To run the model, select Simulation > Start. After a few seconds, the model stops automatically.

To see all three boxes in the Display block, you must enlarge the block slightly, as follows:

Building a Channel Noise Model

1 Select the Display block and move the mouse pointer to one of the lower

corners of the block, so that a diagonal arrow appears on the corner, as shown.

2 Drag the corn

appear, as sh

er of the block down with the mouse until three windows

own.

The Display block displays the following information:

• Bit error rate

• Number of errors

• Total number of bits that are transmitted

The exact values that appear will vary, depending on the Initial seed parameters in the Bernoulli Binary Generator block and the Binary Symmetric Channel block.

Because the Target number of errors in the dialog box for the Error Rate Calculation block is set to

100, the simulation stops when 100 errors have

been detected.

To save the model, select File > Save, type a name for the model, such as

channelnoise,intheFile name fi eld, and click Save.

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2 Building Models

Reducing the Error Rate Using a Hamming Code

In this section...

“Section Overview” on page 2-30

“Building the Hamming Code M odel” on page 2-31

“Using the Hamming Encoder and Decoder Blocks” on page 2-32

“Setting Parameters in the Hamming Code Model” on page 2-32

“Labeling the Display Block” on page 2-33

“Running the Hamming Code Model” on page 2-33

“Displaying Frame Sizes” on page 2-34

“Adding a Scope to the Model” on page 2-34

“Setting Parameters in the Expanded Model” on page 2-35

“Observing Channel Errors with the Scope” on page 2-37

2-30

Section Over view

This section describes how to reduce theerrorrateinthemodelshowninthe figureChannelNoiseModelonpage2-24 by adding an error-correcting code. The following figure shows an example that uses a Hamming code.

Hamming Code Model

You are encouraged to build the model for yourself. Alternatively, to open a completed version of the model, type

doc_hamming at the MATLAB prompt.

Reducing the E rr or Rate Using a Hamming Code

Building the Ham

You can build the in the figure Cha

1 Type doc_chann

model. Then sa your work file

2 Drag the following two Communications Blockset blocks from the Simulink

Hamming code model by adding blocks to the model shown

nnel Noise Model on page 2-24. To do so, follow these steps:

ve the model as

s. See “Saving a Model” on page 2-21.

ming Code Model

at the MATLAB prompt to open the channel noise

my_hamming in the folder where you keep

Library Browser into the model window:

• Hamming Encoder block, from the Block sublibrary of the Error

Detection and Correction library

• Hamming Decoder block, from the Block sublibrary of the Error

Detection and Correction library

3 Click the right border of the model and drag it to the right to widen the

model window.

4 Move the B

block, an creates blocks n

inary Symmetric Channel block, the Error Rate Calculation

d the Display block to the right by clicking and dragging. This

more space between the Binary Symmetric Channel block and the

ext to it. The model should now look like the following figure.

5 Click the Hamming Encoder block and drag it on top of the line between

the Bernoulli Binary Generator block and the Binary Symmetric Channel block, to the right of the branch point, as shown in the following figure. Then release the mouse button. The Hamming Encoder block should automatically connect to the line from the Bernoulli Binary Generator block to the Binary Symm etric Channel block.

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2 Building Models

6 Click the Hamming Decoder block and drag it on top o f the line between

the Binary Symmetric Channel block and the Error Rate Calculation block.

Using the Hamming Encoder and Decoder Blocks

The Hamming Encoder block encodes the data before it is sent through the channel. The default code is the [7,4] Hamming code, which encodes message words of length 4 into codewords of length 7. As a result, the block converts frames of size 4 into frames of size 7. The code can correct one error in each transmitted codeword.

For an [n,k] code, the input to the Hamming Encoder block must consist of vectors of size k. In this example, k = 4.

2-32

The Hamming Decoder block decodes the data after it is sent through the channel. If at most one error is created in a codeword by the channel, the block decodes the word correctly. However, if more than one error occurs, the Hamming Decoder block might decode incorrectly.

To learn more about the Communications Blockset block coding features, see “Block Coding” in the online documentation for Communications Blockset.

Setting Parameters in the Hamming Code Model

Double-click the Bernoulli Binary Generator block and make the following changestotheparametersettingsintheblock’sdialogbox,asshowninthe following figure:

1 Select the box next to Frame-based outputs.

Samples per frame to

2 Set

mes of size 4, in order to meet the input requirement of the Hamming

fra

coder Block. See “Frames and Frame-Based Processing” on page 2-22

r more information about frames.

4. This converts the output of the block into

Reducing the E rr or Rate Using a Hamming Code

Note Many Communications Blockset blocks, such as the Hamming Encoder block, require their input to be a vector of a specific size. If you connect a source block, such as the Bernoulli Binary Generator block, to one of these blocks, select the box next to Frame-based outputs in the dialog for the source, and set Samples per frame to the required value.

Labeling the Display Block

You can change the label that appears below a block to make it more informative. For example, to change the label below the Display block to “Error Rate Display,” first select the label with the mouse. This causes a box to appear around the text. Enter the changes to the text in the box.

Running the Hamming Code Model

To run the model, select Simulation > Start. The model terminates after 100 errors occur. The error rate, displayed in the top window of the Display block, is approximately .001. You get slightly different results if you change the Initial seed parameters in the model or run a simulation for a different length of time.

You expect an error rate of approximately .001 for the following reason: The probability of two or more errors occurring in a codew ord of length 7 is

1 – (0.99)

–7(0.99)6(0.01) = 0.002

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2 Building Models

If the codewords with two or more errors are decoded randomly, you expect about half the bits in the decoded message words to be incorrect. This indicates that .001 is a reasonable value for the bit error rate.

To obtain a lower error rate for the same probability of error, try using a Hamming code with larger parameters. To do this, change the parameters Codeword length and Message length in the Hamming Encoder and Decoderblockdialogboxes. Youalsohavetomaketheappropriatechanges to the parameters of the Bernoulli Binary Generator block and the Binary Symmetric Channel block.

Displaying Frame Sizes

You can display the sizes of data frames in different parts of the model by selecting Signal Dimensions from the Port/Signal Displays submenu of the Format menu at the top of the model window. This is shown in the following figure. The line leading out of the Bernoulli Binary Generator block is labeled Because the Hamming Encoder block uses a [7,4] code, it converts frames of size 4 into frames of size 7, so its output is l abeled

[4x1], indicat in g that its output consists o f column vectors of size 4.

[7x1].

2-34

Displaying Frame Sizes

Adding a Scope to the Model

To display the channel errors produced by the Binary Symmetric Channel block, add a Scope block to the model. This is a good way to see whether your model is functioning correctly. The exampleshowninthefollowingfigure shows where to insert the Scope block into the m odel.

Reducing the E rr or Rate Using a Hamming Code

To build this model from the one shown in the figure Hamming Code Model on page 2-30, follow these steps:

1 Drag the following blocks from the Simulink Library Browser into the

model window:

• Relational Operator block, from the Simulink Logic and Bit Operations

library

• Scope block, from the Simulink Sinks library

• Two copies of the Unbuffer block, from the Buffers sublibrary of the

Signal Processing Blockset Signal Management library

2 Double-click the Binary Symm etri c Channel block to open its dialog box,

and select Output error vector. This creates a second output port for the block, which carries the error vector.

3 Double-click the Scope block and click the Parameters button on the

toolbar. Set Number of axes to

4 Connect the blocks as shown in the p receding figure. To learn how to do

2 and click OK.

this, see “Connecting Blocks” on page 2-15 and “Drawing a Branch Line” on page 2-28.

Setting Parameters in the Expanded Model

Makethefollowingchangestotheparameters for the blocks you added to the model.

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2 Building Models

Error Rate Calculation Block

Double-click the Error Rate Calculation block and clear the box next to Stop simulation in the block’s dialog box.

Scope Block

The Scope block displays the channel errors and uncorrected errors. To configure the block,

1 Double-click the block to open the scope, if it is not already open.

2 Click the Parameters button on the toolbar.

3 Set Time range to 5000.

4 Click the Data history tab.

5 Type 30000 in the Limit data points to last field, and click OK.

The scope should now appear as shown.

2-36

To configure the axes, follow these steps:

1 Right-click the v ertical axis at the left side of the upper scope.

he context menu, select Axes properties.

2 In t

3 In the Y-min field, type -1.

Reducing the E rr or Rate Using a Hamming Code

4 In the Y-max field, type 2,andclickOK.

5 Repeat the same steps for the vertical axis of the lower scope.

6 Widen the scope window until it is roughly three times as wide as it is high.

You can do this by clicking the right border of the window and dragging the border to the right, while pressing the mouse button.

Relational Operator

Set Relational Operator to ~= in the block’s dialog box. The Relational Operator block compares the transmitted signal, coming from the Bernoulli Random Generator block, with the received signal, coming from the Hamming Decoder block. The block outputs a 0 when the two signals agree and a 1 when they disagree.

Observing Channel Errors with the Scope

When you run the model, the Scope block displays the error d ata. At the end of each 5000 time steps, the scope appears as shown in the following figure. The scope then clears the displayed data and displays the n ext 5000 data points.

e with Model Running

Scop

pper scope shows the channel errors generated by the Binary Sym metric

The u

nnel block. The lower scope shows errors that are not corrected by

Cha

nnel coding.

cha

ick the Stop button on the toolbar at the top of the model window to stop

escope.

2-37

2 Building Models

To zoom in on the scope so that you can see individual errors, first click the middle magnifying glass button at the top left of the Scope window. Then click one of the lines in the lower scope. This zooms in horizontally on the line. Continue clicking the lines in the lower scope until the horizontal scale is fine enough to detect individual errors. A typical example of what you might see is shown in the figure below.

Zooming In on the Scope

2-38

The wider rectangular pulse in the middle of the upper scope represents two 1s. These two errors, w hich occur in a single codeword, are not corrected. This accounts for the uncorrected errors in the lower scope. The narrower rectangular pulse to the right of the upper scope represents a single error, which is corrected.

When you are done observing the errors, select Simulation > Stop.

“Sending Signal and Error Data to the Workspace” on page 3-4 explains how to send the error data to the MATLAB workspace for more detailed analysis.

Modeling a Channel with Modulation

In this section...

“Section Overview” on page 2-39

“Building the BPSK Model” on page 2-39

“Setting Parameters in the BPSK Model” on page 2-41

“Running the BPSK Model” on page 2-41

Section Over view

The Binary Symmetric Channel block, which simulates a channel with noise, is useful for building models of channel coding. For other types of applications, you might want to construct a more realistic model of a channel. For example, you can add modulation and demodulation, and replace the Binary Symmetric Channel block with an AWGN Channel block, which adds white Gaussian noise to the channel. The following figure shows an example that uses binary phase shift keying (BPSK).

Modeling a Channel with Modulation

BPSK Modulation Model

You are encouraged to build the model for yourself. Alternatively, to open a completed version of the model, type

doc_bpsk at the MATLAB prompt.

Building the BPSK Model

You can build the BPSK model from the one shown in the figure Channel Noise Model on page 2-24. To b uild t he model, follow these steps:

1 Enter doc_channel attheMATLABprompttoopenthechannelnoise

model, and then save the model as your work files.

my_bpsk in the folder where you keep

2-39

2 Building Models

2 Delete the Binary Symmetric C hannel block from the model by

right-clicking the block and selecting Clear.

3 Move the following blocks from the Simulink Library Browser into the

model window, and insert them into the model a s shown in the following figure:

• BPSK Modulator Baseband block, from PM in the Digital Baseband

Modulation sublibrary of the M od ulation library

• AWGN Channel block, from the Channels library

• BPSK Demodulator Baseband block, from PM in the Digital Baseband

Modulation sublibrary of the M od ulation library

The model should now appe ar as in the figure below .

2-40

Binary Phase Shift Keying

The BPSK Modulator and Demodulator Baseband blocks implement binary phase shift keying (BPSK) modulation. BPSK is a method for modulating a binary signal onto a complex waveform by shifting the phase of the complex signal. In digital baseband BPSK, the symbols 0 and 1 are modulated to the complex numbers exp(jt) and -exp(jt), respectively, where t is a fixed angle. In this example, t = 0, so these numbers are just 1 and -1.

You can set the value of t in the Phase offset parameter in the dialog boxes for the BPSK Modulator Baseband block and the BPSK Demodulator Baseband block. The default value is

To learn more about the Communications Blockset digital modulation features, see “Digital Modulation” in the online Communications Blockset documentation.

Modeling a Channel with Modulation

Setting Paramet

To set block para

1 Double-click t

2 Double-click the Error Rate Calculation block and make the following

changes to the default parameters in the block’s dialog:

• Set Output data to

• Select the box next to Stop simulation.

meters in the BPSK model, do the following:

he AWGN Channel block and set Es/No to

ers in the BPSK Model

4.2.

Port.

Running the BPSK Model

When you run the model, the Display block shows an error rate of approximately 0.01, the same as in the channel noise model. The BPSK model uses the BPSK Modulator Baseband, the AWGN Channel, and the BPSK Demodulator Baseband blocks to simulate a channel with noise. This provides a more realistic model of a channel than using just the Binary Symmetric Channel block. You can also model other types of channel noise using blocks from the Communications Blockset Channels library.

2-41

2 Building Models

Reducing the Error Rate with a Cyclic Code

In this section...

“Section Overview” on page 2-42

“Building the Cyclic Code Model” on page 2-42

“Running the Cyclic Code Model” on page 2-44

“Verifying the Symbol Period” on page 2-44

“Using a Probe Block to Determine Symbol Period” on page 2-45

Section Over view

YoucanimprovetheerrorrateinthemodelshowninthefigureBPSK Modulation Model on page 2-39, for certain nois e levels, by adding channel coding. An example that uses a binary cyclic code is shown below.

2-42

Building the Cyclic Code Model

You can build the cyclic code model by adding blocks to the BPSK model shown in the figure BPSK Modulation Model on page 2-39. To build the model, follow these steps:

1 Open the BPSK model by entering doc_bpsk at the MATLAB prompt. Save

the model as

2 Double-click the AWGN Channel block and s et Es/No to 7. This value is

chosen for this example to illustrate the benefit of using a code. If E much lower than the value chosen here, then the E by the additional coded bits will be greater than the coding gain provided by the code.

my_cyclic in the folder where you keep your work files.

reduction caused

s/N0

Reducing the Error Rate with a Cyclic Code

3 Run the simulation and note its error rate (for later comparison in

“Running the Cyclic Code Model” on page 2-44). The error rate appears in the top entry of the Display block.

4 To introduce cyclic coding, drag these Communications Blockset blocks

from the Simulink Library Browser into the model window:

• Binary Cyclic Encoder block, from the Block sublibrary of the Error

Detection and Correction library

• Binary Cyclic Decoder block, from the Block sublibrary of the Error

Detection and Correction library

5 Widen the model window and connect the blocks as below.

6 Double-click the Bernoulli Binary Generator block and change these

parameters:

• Select Frame-based outputs.

• Set Samples per frame to

21 to match the input requirement of the

Binary Cyclic Encoder block.

7 Double-click the Binary Cyclic Encoder block and change these parameters:

• Set Codeword length N to

• Set Message length K to

31.

21.

Make the same changes in the Binary Cyclic Decoder block.

8 Double-click the AWGN Channel block and change these parameters:

• Set Es/No to

7+10*log10(21/31). The second term in this sum accounts

for the difference in symbol period compared to the original BPSK model.

• Set Symbol period to

21/31. For more information on setting Symbol

period,see“VerifyingtheSymbol Period” on page 2-44.

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2 Building Models

With these parameter values, the AWGN channel block produces the same amount of noise per symbol as in the BPSK model (without coding) in which Es/No is how much the cyclic code improves the bit error rate.

9 Double-click the Error Rate Calculation block and change this parameter:

7. The equivalence of the noise enables you to determine

• Set Maximum number of symbols to

simulation, producing a more reliable estimate for the error rate .

1e7.Thisextendsthe

Binary Cyclic Encoder and Decoder

The Binary Cyclic Encoder block implements a binary cyclic code. In this example, the block has the following parameter settings:

• Codeword length N =

• Message length K = 21

Thecoderateisgivenby

Code rate

This example uses a rate 21/31 code. The codeword length N must have the form 2 block must be a vector whose length is Message length.

The Binary Cyclic Decoder block decodes the demodulated signal. This block must have the same parameter settings as the Binary Cyclic Encoder block.

- 1, where M is an integer greater than or equal to 3. The input to the

Message length

Codeword length

2-44

Running the Cyclic Code Model

When you run the simulation, the bit error rate is less than one-tenth of the error rate in the model that does not have channel coding.

Verifying the Symbol Period

When you compare the cyclic code model to the BPSK model, which does not have channel coding, the ratio of energy per information symbol to noise spectral density, E

, should be the same in both models. You can u se the

b/N0

Reducing the Error Rate with a Cyclic Code

Symbol period and Es/No parameters in the AWGN Channel block to adjust the amount of channel n oise so that E coding. Because the cyclic code has rate 21/31, set Symbol period to For a BPSK simulation with a rate K / N code, set Symbol period to

isthesameasinthemodelwithout

b/N0

21/31.

K/N

because there are K information symbols for each N channel symbols.

Note that Es/No, the ratio of energy per channel symbol to noise spectral density, is not the same as E

EN EN KN

//log(/)

10=−

. To convert between the two, use the formula

b/N0

where K / N is the ratio of information symbols to channel symbo ls. Changing the Symbol period to

K/N has the same effect as subtracting 10*log10(K / N)

from the Es/No parameter.

Using a Probe Block to Determine Symbol Period

If you are unsure how to set the Symbol period, you can find the correct value using a Probe block. To do so, follow these steps:

1 Drag these blocks from the Simulink Library Browser into the cyclic code

model window:

• Probe block, from the Simulink Signal Attributes library

• Two copies of the Terminator block, from the Simulink Sinks library

2 Double-click the Probe block and change thes e parameters:

• Clear the boxes next to Probe complex signal and Probe signal

dimensions.

• Select the boxes next to Probe width and Probe sample time.The

block now has two output ports.

3 Connect the blocks as shown in the next figure.

4 Select Edit > Update diagram. Simulink updates the display on the

Probe block, as in the next figure.

2-45

2 Building Models

The number after W in the Probe block tells you the frame size, which in this case is 31. The first number after You can determine the symbol period using the following formula.

Tf tells you the frame period, which is 21.

Symbol period

In this example, the symbol period is 21/31.

Frame period

Frame size

2-46

Building a Frequency-Shift Keying Model

In this section...

“Section Overview” on page 2-47

“Building the FSK Model” on page 2-48

“Setting Parameters in the FSK Model” on page 2-49

“Running the FSK Model” on page 2-50

“Learning About Delays in the Model” on page 2-51

“Finding the Delay in a Model” on page 2-51

“Learning About Multirate Models” on page 2-52

“Using Sample Time Colors to Check Sample Times” on page 2-53

Section Over view

Frequency-shift keying (FSK) is a standard modulation technique in which a digital signal is modulated onto a sinusoidal carrier whose frequency shifts between different values. The Bell Telephone System first used this technique in their Model 103 modem. The model shown in the following figure is an example of the baseband representation of FSK.

Building a Frequency-Shift Keying Model

FSK Model

2-47

2 Building Models

To open a completed version of t he model, type doc_fsk at the MATLAB prompt.

Building the FSK Model

You can build the FSK model by adding blocks to the model shown in the figure Channel Noise Model on page 2-24. To open the channel noise model, enter

doc_channel at the MATLAB prompt. Then save the model as my_fsk in

the folder where you keep your work files. See “Saving a Model” on page 2-21.

You need to add the following blocks to the model:

M-FSK Modulator and Demodulator Baseband

The M-FSK Modulator Baseband block, from FM in the Digital Baseband sublibrary of the Modulation library, modulates the binary signal using a baseband representation of FSK modulation.

The M-FSK Demo dulator Baseband block, from FM in the Digital Baseband sublibrary of the Modulation library, demodulates the base band signal.

2-48

AWGN Channe l

The AWGN Channel block, from the Channels library, models a channel using additive white Gaussian noise. In this model, AWGN is more suitable than a binary symmetric channel.

Relational Operator

The Relational Operator block, from the Simulink Logic and Bit Operations library, compares the transmitted signal, from the Bernoulli Binary Generator block, with the received signal, from the M-FSK Demodulator Baseband block. The block outputs a 0 when the two signals agree, and a 1 when they differ.

Scope

The Scope block, from the Simulink Sinks library, displays the transmitted signal, the received signal, and the output of the Relational Operator block. To create three input ports for the block, follow these steps:

1 Double-click the block to open the scope.

Building a Frequency-Shift Keying Model

2 Click the Parameters button on the toolbar.

3 Set Number of axes to 3.

4 Set Time range to 1 and click OK.

To set the limits on the vertical axes,

1 Right-click the v ertical axis at the left side of the upper scope.

2 In the context menu, select Axes properties.

3 In the Y-min field, type -1.

4 In the Y-max field, type 2,andclickOK.

Repeat these steps for the middle and lower vertical axes.

Delay

The Delay block, from the Signal Processing Blocks et Signal Operations library, delays the transmitted signal so that it can be accurately compared with the received signal. Its purpose is explained further in “Learning About Delays in the Model” on page 2-51.

Drag these blocks into the model window and connect them as shown in the figure FSK Model on page 2-47. Remove the Binary Symmetric Channel block becaus e it is no longer needed. The next section explains how to set the parameters for these blocks.

Setting Parameters in the FSK Model

Make the following changes to the default parameter settings in the dialog boxes for the blocks:

1 Double-click the Bernoulli Binary Generator block and make the following

changes to the default parameters in the block’s dialog box:

• Set Probability of a zero to

• Set Sample time to

1/1200.

0.5.

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2 Building Models

2 Double-click the M-FSK Modulator Baseband block and make the following

changes to the default parameters in the block’s dialog box:

• Set M-ary number to

2. This specifies the number of frequencies in

the modulated signal.

• Set Frequency separation to

1000.Thisspecifiestheseparation

between the two frequencies of the modulated signal.

• Set Samples per symbol to

5. This causes the block to oversample

the incoming signal. Oversampling increases the sampling rate by a factor of 5.

3 Double-click the M-FS K Demodulator Baseband block and make the same

changes to the block’s default parameters as for the M-FSK Modulator Baseband block.

4 Double-click the AWGN Channel block and set Symbol period to 1/12 00.

5 Double-click the Error Rate Calculation block and make the following

changes to the default parameters in the block’s dialog box:

• Set Receive delay to

• Set Output data to

Port.

Running the FSK Model

Set the Stop time parameter to 15 and run the model.

2-50

Displaying the Errors in the Scope

Double-click the Scope block to open the scope.

Building a Frequency-Shift Keying Model

The top window displays the transmitted signal. The middle window displays the received signal. The bottom windowdisplaysa0wherethetwosignals agree and a 1 where they differ.

Learning About Delays in the Model

Some blocks cause a signal to be delayed as it passes through a model, because of the way they process data. For example, there is a delay of one symbol period between the input signal to the M-FSK Modulator Baseband block and the output signal from the M-FSK Demodulator Baseband block. As a result, there is a delay of 1 between the transmitted and r eceived signals in the model. “Finding the Delay in a Model” on page 2-51 shows how to find the value of this delay.

Tocomparethesetwosignalsandcalculate the bit error rate correctly, you need to delay the transmitted signal by 1 to synchronize it with the received signal. ThisiswhyyousettheReceive delay to Error Rate Calculation block, and left the Delay at its default value of the Delay block.

1 in the dialog box for the

1 in

Note If the Error Rate Calculation block in a model gives an error rate close to .5 for a random binary signal, you might not have taken into account delays in the model. The block is probably comparing two unsynchronized signals.

Several blocks in the Communications Blockset Modulation library produce delays. A list of these is given in “Delays in Digital Modulation” in the online Communications Blockset documentation. The Viterbi D ecoder block, from the Convolutional sublibrary of the Error Detection and Correction library, also produces a delay equal to its Traceback depth parameter; see the section “Viterbi Decoder” on page 2-56.

Finding the Delay in a Model

To find the delay between the transmitted and received signals in a model, youcanuseaFindDelayblock. Todoso,insertthefollowingblocksinto the FSK model:

• Find Delay, from the Utility Blocks library

2-51

2 Building Models

• Display, from the Simulink Sinks library

Connect the blocks as shown at the top right of the following figure.

2-52

When you run the simulation, the Display block labeled Display shows that the delay is 1. You can use this information to set the Receive delay parameter in the Error Rate Calculation block and the Delay parameter in the Delay block.

Learning About Multirate Models

The model shown in the figure FSK Model on page 2-47 diffe rs from the earlier models in that it contains signals with different sample times. The Bernoulli Binary Generator block has a sample time of Modulator Baseband block receives this signal and upsamples it at a rate of five samples per symbol. As a result, the sample time of the block’s output signal is 1/6000. A m odel that contains signals with different sample times is called a multirate model.

The multiple sample times present in this model do not affect the bit error rate of a simulation. But be aware that in other models, sample times can affect the results of a simulation. This is usually the case when different signals a re combined. See “Setting Sample Times and Samples per Frame” on page 3-16 for an example of this.

1/1200.TheM-FSK

Building a Frequency-Shift Keying Model

Using Sample Tim

You can easily ch selecting: Form Diagram.Wheny according to th

Red blocks and indicates the different sa blocks and li time colors,

For frame-b signals rat

If you need aProbeblo Period” o

her than sample times.

n page 2-45.

eck whether there are different sample times in a model by

at > Sample Time Display.Next,selectEdit > Update

ou do this, blocks and lines in the model are colored

eir sample times.

lines indicate the fastest sample time in the model. Green

second fastest sample time. Yellow blocks contain signals with

mple times. If all sample times in the model are the same, all

nes are colored red. For more information on displaying sample

see the Simu link documentation.

ased signals, the colors correspond to the frame p eriods of the

to determine the actual sample time of a signal, you can use

ck as described in “Using a Probe Block to Determine Symbol

e Colors to Check Sample Tim es

2-53

2 Building Models

Building a Convolutional Code Model

In this section...

“Section Overview” on page 2-54

“Building the Convolutional Code Model” o n page 2-54

“Understanding the Blocks in the Model” on page 2-55

“Setting Param eters in the Convolutional Code Model” on page 2-56

“Running the Convolutional C ode Model” o n page 2-57

Section Over view

The following model simulates the use of convolutional coding to send a signal through a channel with noise.

2-54

Convolutional Code Model

To open a completed version of the model, enter doc_conv at the MATLAB prompt.

Building the Convolutional Code Model

You can build the convolutional code model by adding blocks to the model shown in the figure Channel Noise Model on page 2-24.

To build the model, follow these steps:

1 Enter doc_channel at the MATLAB Help browser to open the channel

noise model. Then save the model as your work files.

elete the Binary Symmetric Channel block.

2 D

my_conv in the f older where y ou keep

Building a Convolutional Code Model

3 Drag the following blocks from the Simulink Library Browser into the

model window, and connect them as shown in the figure Convolutional Code Model on page 2-54:

• Convolutional Encoder, from the Convolutional sublibrary of the Error

Detection and Correction library

• BPSK Modulator Baseband, from PM in the Digital Baseband

Modulation sublibrary of the M od ulation library

• Complex to Real-Imag, from the Simulink Math Operations library

• Viterbi Decoder, from the Convolutional sublibrary of the Error

Detection and Correction library

Understanding the Blocks in the Model

This model contains the blocks discussed in the following subsections.

Convolutional Encoder

The Convolutional Encoder block encodes the signal from the Bernoulli Binary Generator. The example uses the industry standard rate 1/2 convolutional code, with constraint length 7, defined by the following diagram.

First output

Input

-1

Second output

Convolutional Encoder Schematic Block Diagram

The e ncoder structure is described by a pair of binary numbers, having the same le ngth as the code’s constraint length, that specify the connections from the delay cells t o modulo-2 addition nodes. The binary number for the upper addition node is 1111001. A 1 indicates that the bit in the corresponding delay cell (reading from left to right) is sent to the addition node, and a 0

2-55

2 Building Models

indicates that the bit is not sent. The binary number for the lower addition node is 1011011. Converting these two binary numbers to octal gives the pair [171,133]. You can enter this pair into the block’s dialog box by typing

poly2trellis(7, [171 133]) in th e field for Trellis Structure.

To learn more about the Communications Blockset convolutional coding features, see “Convolutional Coding” in the online Communications Blockset documentation.

Complex to Real-Imag

The Complex to Real-Imag block, labeled Re(u), receives the complex signal and outputs its real part. Because the output BPSK Modulator Baseb an d block has zero complex part, all of the signal is carried by the real part. You can set this option by selecting block’s dialog box. It is not necessary to demodulate the signal, because the Viterbi Decoder block can accept unquantized inputs.

Real in the Output parameter fie ld in the

Viterbi Decoder

The Viterbi Decoder block decodes the signal using the Viterbi algorithm. The Decision Type parameter is set to real numbers from the Complex to Real-Imag block. The Traceback depth parameter, which is set to the b lock uses to construct each traceback path. This produces a delay of between the input and output of the block. For more information on delays, see “Finding the Delay in a Model” on page 2-51.

96, is the number of branches in the trellis that

Unquantized so that the block can accept

2-56

For an example of a convolutional coding model that uses soft-decision decoding, see “Example: Soft-Decision Decoding” in the online Communications Blockset documentation.

Setting Parameters in the Convolutional Code Model

To set parameters in the convolutional code model, do the following:

1 Double-click the Bernoulli Binary Generator block and select the box next

to Frame-based outputs in the block’s dialog box.

2 Double-click the AWGN Channel block and make the following changes to

the default parameters in the block’s dialog box:

• Set Es/No to -1.

Building a Convolutional Code Model

• Set Symbol period to

1/2. Becausethecoderateis1/2,thissetting

causes the block to produce the sam e amount of noise per channel symbol as it would without channel coding. For more information, see “Verifying the Symbol Period” on page 2-44.

3 Double-click the Error Rate Calculation block and make the following

changes to the default parameters in the block’s dialog box:

• Set Receive delay to

96. The Viterbi Decoder block creates a delay of

96,duetoitsTraceback depth setting.

• Select the box next to Stop simulation.

• Set Target number of errors to

100.

Running the Convolutional Code Model

When you run the model, you observe an error rate of approximately .003.

2-57

2 Building Models

2-58

Using Communications Blockset Software with MATLAB

This chapter describe s how to use MATLAB to extend the capabilities of Communications Blockset. The chapter explains how to run simulations from the command line, and how to run multiple simulations. It also explains how to transfer data between a modelandtheMATLABworkspace.

• “Sending Data to the MATLAB Workspace” on p age 3-2

• “Running Simulations from the Command Line” on page 3-7

• “Importing Data from the MATL AB Workspace” on page 3-13

• “Learning More” on page 3-19

3 Using Communications Blockset™ Software with MATLAB

Sending D ata to the MATLAB Workspace

In this section...

“Section Overview” on page 3-2

“Using a Signal To Workspace Block” on page 3-2

“Configuring the Signal To Workspace Block” on page 3-3

“Viewing the Error Rate Data in the Workspace” on page 3-3

“Sending Signal and Error Data to the Workspace” on page 3-4

“Viewing the Signal and Error Data in the Workspace” on page 3-5

“Analyzing Signal and Error Data” on page 3-6

Section Over view

This section explains h ow to send data from a Simulink model to the MATLAB workspace so you can analyze the results of simulations in greater detail.

3-2

Using a Signal To Workspace Block

You can use a Signal To Workspace block, from Signal Processing Sinks library of the Signal Processing Blockset application to send data to the MATLAB workspace as a vector. For example, you can send the error rate data from the Hamming code model, described in the section “Reducing the Error Rate Using a Hamming Code” on page 2-30. To insert a Signal to Workspace block into the m ode l, follow these steps:

1 Type doc_h ammi ng at the MATLAB Help browser to open the model.

2 Drag a Signal To Workspace block, from the Signal P rocessing Sinks

library, into the model window and connect it as shown in the following figure.

Sending Data to the MATLAB®Works p ace

Hamming Code Model with a Signal To Workspace Block

Configuring the Signal To Workspace Block

To configure the Signal to Workspace block, follow these steps:

1 Double-click the block to display its dialog box.

2 Type hammcode_BER in the Variable name field.

3 Type 1 in the Limit data points to last field. This limits the output vector

to the values at the final time step of the simulation.

4 Click OK.

When you run a simulation, the model sends the output of the Error Rate Calculation block to the workspace as a vector of size 3, called

hamming_BER.

TheentriesofthisvectorarethesameasthoseshownbytheErrorRate Display block.

Viewing the Error Rate Data in the Workspace

After running a simulation, you can view the output of the Signal to Workspace block by typing the following commands at the MATLAB prompt:

format short e hammcode_BER

The vector output is the following:

hammcode_BER =

5.4066e-003 1.0000e+002 1.8496e+004

3-3

3 Using Communications Blockset™ Software with MATLAB

The command format short e displays the entries of the vector in exponential form. The entries are as follows:

• The first entry is the error rate.

• The second entry is the total number of errors.

• The third entry is the total number of comparisons made.

Sending Signal and Error Data to the Workspace

To analyze the error-correction performance of the Hamming code, send the transmitted signal, the received signal, and the error vectors, created by the Binary Symmetric Channel block, to the workspace. An example of this is shown in the following figure.

3-4

Sending Signal and Error Data to the Workspace

You can build this model from the one shown in the figure Hamming Code Model on page 2-30. To build the model, follow these steps:

1 Type doc_hamming to open the model.

2 Doub

3 Drag three Signal To Workspace blocks, from the Signal Processing Sinks

le-click the Binary Symmetric Channel block to open its dialog box,

elect Output error vector. This creates an output port for the

and s

r data.

erro

library, into the model window and connect them as shown in the preceding figure.

4 Double-click the left Signal To Workspace block.

Sending Data to the MATLAB®Works p ace

• Type Tx in the Variable nam e field in the block’s dialo g box. T he b lock

sends the transmitted signal to the workspace as an array called

Tx.

• In the Frames field, select

preserves each frame as a separate column of the array

Log frames separately (3-D array).This

Tx.

• Click OK.

5 Double-clickthemiddleSignalToWorkspaceblock:

• Type

• In the Frames field, select

errors in the Variable name field.

Log frames separately (3-D array).

• Click OK.

6 Double-click the right Signal To Workspace block:

• Type

• In the Frames field, select

Rx in the Variable name field.

Log frames separately (3-D array).

• Click OK.

Viewing the Signal and Error Data in the Workspace

After running a simulation, you can display individual frames of data. For example, to display the tenth frame of

Tx(:,:,10)

This returns a column vector of length 4, corresponding to the length of a message w ord. Usually, you should not type the entire transmitted signal, which is very large.

Tx, at the M A TLAB prompt type

Tx by itself, because this displays

To display the corresponding frame of errors, type

errors(:,:,10)

This returns a column vector of length 7, corresponding to the length of a codeword.

To display frames 1 through 5 of the transmitted signal, type

Tx(:,:,1:5)

3-5

3 Using Communications Blockset™ Software with MATLAB

Analyzing Signal and Error Data

You can use M ATLA B to analyze the data from a simulation. For example, to identify the differences between the transmitted and received signals, type

diffs = Tx~=Rx;

The vector di ffs is the XOR of the vectors Tx and Rx.A1indiffs indicates that

Tx and Rx differ at that position.

You can determine the indices of frames corresponding to message words that are incorrectly decoded with the following MATLAB command:

error_indices = find(diffs);

A 1 in the vector not_equal indicates that there is at least one difference between the corresponding frame o f records the indices where Tx and Rx differ. To view the first incorrectly decoded word, type

Tx and Rx.Thevectorerror_indices

3-6

Tx(:,:,error_indices(1))

To view the corresponding frame of errors, type

errors(:,:,error_indices(1))

Analyze this data to determine the error patterns that lead to incorrect decoding.

Running Simulations from the Command Line

In this section...

“Section Overview” on page 3-7

“Running a Single Simulation” on page 3-7

“Running Multiple Simulations” on page 3-8

“Plotting the Results of Multiple Simula t ions” on page 3-10

“Running Multiple Simulations Using BERTool” on page 3-10

Section Over view

This section describes how to run simulations from the command line using the

sim command. This is especially useful for running multiple simulations

on a model.

Running a Single Simulation

As an example, to run the phase noise model, described in “Running a Simulink Model” on page 2-2, from the command line, enter

sim('commphasenoise')

in the MATLAB Command Window. This runs the model in the background without opening the model window. While the simulation is running, the MATLAB prompt is unavailable and you cannot enter another MATLAB command.

After the simulation stops, the p rompt reappears. You can then view the results of the simulation by typing

It is not necessary to open the model window when running a simulation from the command line. Usually you want to send the results of the simulation to the MATLAB workspace, for example, if you are running multiple simulations on a single model.

You can also specify simulation parameters from the command line. For example, the command

commphasenoise to open the model.

3-7

3 Using Communications Blockset™ Software with MATLAB

sim('commphasenoise', 1000);

runs the model with a Stop time of 1000. This overrides the Stop time setting in the Configuration Parameters dialog box. For more information on running simulations, see the Simulink documentation.

Running Multiple Simulations

Youcanrunmultiplesimulations,with different parameters, from the command line using a MATLAB script. This section describes how to run the phase noise model with varying amounts of channel noise.

Preparing the Model

1 Type commphasenoise to open the model.

2 Drag a Signal To Workspace block, from the Signal P rocessing Sinks

library, into the model window and connect it as shown in the following figure.

3-8

Phase Noise Model with a Signal To Workspace Block

3 Double-click the Signal To Workspace block and make these changes in

the block’s dialog box:

• Set Variable name to

• Set Limit data points to last to

ect Simulation > Configuration parameters and set Stop time to

4 Sel

inf

phase_err.

Running Simulations from the Command Line

5 Enter the following commands in the MATLAB Command Window. This

creates variables for the simulation’s stopping criteria, as well as a vector of E

6 Double-click the AWGN Channel block and set Es/No to EbNo+10*log10(8)

values.

b/N0

maxNumErrs = 200; maxNumBits = 10^5; EbNoVec = 20:0.5:23;

in the block’s dialog box. The variable EbNo represents the bit energy to noise ratio. The term

10*log10(8) converts EbNo to Es/No,whichisthe

symbol energy to noise ratio. The 8 appears because there are eight bits per channel symbol in 256-QAM.

7 Double-click the Error Rate Calculation block and make the following

changes in the block’s dialog box:

• Select Stop simulation.

• Set Target number of errors to

• Set Maximum number of symbols to

8 Save the model in your working folder under a different file name, such as

my_commphasenoise.

maxNumErrs.

maxNumBits.

Running the Simulation Multiple Times

Now that the model and variables are set up, you can run multiple simulations, each with a different Es/No parameter. The following script runs the simulations in a loop and stores the results in a matrix called The simulations might take several minutes to run.

SER_Vec=[]; for n = 1:length(EbNoVec);

EbNo = EbNoVec(n); sim('my_commphasenoise'); SER_Vec(n,:) = phase_err;

end;

When the simulations have ended and the prompt reappears, enter the following at the MATLAB prompt:

SER_Vec.

3-9

3 Using Communications Blockset™ Software with MATLAB

format short e

SER_Vec

This displays the results in a matrix. Each row is the output of the Error Rate Calculation block for a single simulation. The first column, which gives the error rates for each simulation, decreases, because the n oise level decreases as

EbNo increases. The last column gives the number of symbols processed in

each simulation.

Plotting the Results of Multiple Simulations

Plot the symbol error rates by en tering the following commands.

semilogy(EbNoVec,SER_Vec(:,1),'*'); xlabel('Eb/No (dB)');ylabel('SER'); title('Phase Noise Performance of 256 -QAM'); legend('Phase noise level: -66 dBc/Hz ');

3-10

Running Multiple Simulations Using BERTool

The BERTool graphical user interface in Communications Toolbox can run multiple Simulink simul ati on s and create a BER plot. This section de scrib es

Running Simulations from the Command Line

how to use BERTool with a modified commphasenoise model. For more general instructions on using BERTool, see the BERTool section of the Communications Toolbox documentation.

To create a BER plot for the phase noise model using BERTool, follow these steps:

1 Follow the procedure in “Preparing the Model” on page 3-8, if you have not

already done so.

EbNo, maxNumErrs,andmaxNumBits are special variable

names that BERTool recognizes.

2 Drag two Integer to Bit Converter blocks from the Utility Blocks library

into the model. Insert them before the Error Rate Calculation block, as shown below. This causes the Error Rate Calculation block to compute a bit error rate instead of a symbol error rate. BERTool is designed to compute bit error rates.

3 Double-click each of the Integer to Bit Converter blocks and set Number

of bits per integer to

4 Save the model in your working folder as my_commphasenoise_ber.mdl.

5 Open th

Windo

6 Click the Monte Carlo tab.

7 Make the following changes in the GUI:

e BERTool GUI by entering

• Set Eb/No range to

• Set Simulation M-file or model to

• Set BER variable name to

• Set Number of errors to

8 in the dialog boxes.

bertool in the MATLAB Command

EbNoVec.

my_commphasenoise_ber.mdl.

phase_err.

200.

3-11

3 Using Communications Blockset™ Software with MATLAB

• Set Number of bits to 10^5.

8 Click Run.

BERTool runs the simulation multiple times, gathers bit error rate results, and produces a plot like the following. (Although the shape resembles the plot shown in “Plotting the Results of Mul t iple Si mulations” on page 3-10, the plot there shows symbol error rates while the plot here shows bit error rates.)

3-12

Importing Data from the MATLAB®Works p ace

Importing Data from the MATLAB Workspace

In this section...

“Section Overview” on page 3-13

“Simulating a Signal by Importing Data” on page 3-13

“Simulating Noise with Imported Data” on page 3-14

“Simulating Noise with Specified Error Patterns” on page 3-15

“Setting Sample Times and Samples per Frame” on page 3-16

Section Over view

This section explains how to import data into a model directly from the MATLAB workspace using the Signal From Workspace block, from the Signal Processing Sources library. This enables you to run simulations on data that you create in the workspace or import from outside MATLAB. You can also create specific error patterns, such as burst errors, and import them into a model to test error correction codes.

Simulating a Signal by Importing Data

To import a signal that you create in the workspace, you can use a Signal From Workspace block as a source. An example is the model shown in the following figure. This model is the same as the one shown in the figure Channel Noise Model on page 2-24, except that the Bernoulli Binary Generator block has been replaced with a Signal From Workspace block.

Importing a Signal from the Workspace

To build this model, follow these steps:

3-13

3 Using Communications Blockset™ Software with MATLAB

1 Enter doc_channel attheMATLABprompttoopenthechannelnoise

model. Then save it under a different name in the directory where you keep your work files.

2 Replace the Bernoulli Binary Generator block with a Signal From

Workspace b lock, from the Signal Processing Sources library.

3 In the Signal from Workspace block’s dialog, change the Signal parameter

data (or another variable name).

Before using the model, define the vector For example, type defines

data as a random binary vector of length 10

data=randint(1,10^4); at the MATLAB prompt. This

data in the MATLAB w orkspace.

Next, select Simulation > Configuration Parameters and set the Stop time parameter to imports the random vector

Change the vector

length(data). Whenyourunasimulation,themodel

data into the model.

data in the MATLAB workspace to simulate a less random

signal, or import a signal from outside MATLAB.

Simulating Noise with Imported Data

You can also use the Signal From W orkspace block to simulate channe l noise with specific error patterns, in order to test the performance of an error correcting code. An example of this is shown in the following figure.

3-14

Using Data from the Workspace to Simulate Errors

Importing Data from the MATLAB®Works p ace

This example is similar to the model shown in the figure Hamming Code Model on page 2-30, but instead of using the Binary Symmetric Channel block to simulate noise, the model imports error data from the workspace.

To build this model, follow these steps:

1 Type doc_hamming at the MATLAB prompt to open the Hamming code

model. Then save the model under a different name in the folder where you store your work files.

2 Delete the Binary Symmetric Channel block from the model.

3 Drag the following blocks into the model window:

• A Signal From Workspace block, from the Signal Processing Sources

library

• A Logical Operator block, from the Simulink Math Operations library

4 Connect these blocks as shown in the preceding figure.

5 Select Simulation > Configuration Parameters to open the

Configuration Parameters dialog box.

6 Type length(errors) in the Stop time field and click OK.

7 Double-click the Signal From Workspace block and make the following

changes to the default parameters in the block’s dialog box:

• Set Signal to

• Set Sample time to

• Set Samples per frame to

errors.

4/7.

7, to match the frame size of the signal

coming out of the Hamming Encoder block.

8 Double-click the Logical Operator block and set Operator to XOR in the

block’s dialog box.

Simulating Noise with Specified Error Patterns

To use the model in the figure Using Data from the Workspace to Simulate Errors on page 3-14, you must first create a binary vector called workspace to represent errors in the channel. A 1 in the vector represents

errors in the

3-15

3 Using Communications Blockset™ Software with MATLAB

an error in the channel, while a 0 represents no error. When you run a simulation, the Logical Operator block performs the XOR operation on the vector

errors and the signal.

For example, to create a vector of length 7x10

that contains exactly one 1 in each sequence of entries from 7n + 1 to 7(n + 1), enter the following at the MATLAB prompt:

errors=[]; for n=1:10^4

p=randperm(7); v=[1000000]; errors=[errors v(p)];

end

The function randperm generates a random permutation of the numbers 1 through 7. The vector

v, w hich has exactly one entry that is 1. The result is that the vector errors

v(p) applies the permutation to the entries of the vector

contains exactly one entry that is 1 in each sequence from 7n + 1 to 7(n+1).

Running a Simulation with Imported Error Data

Whenyourunasimulation,thebiterrorrateiszerobecausetheHamming code can correct one error in each codeword.

To test the code with an error vector that creates two errors in each codeword, change the vector

v to v=[1 1 0 0 0 0 0] in the preceding code.

3-16

Setting Sample Times and Samples per Frame

It is important to set the Sample time and Samples per frame parameters correctly in the Signal From Workspace block, so that the block has the same frame size and frame period as the Hamming Encoder block. This ensures that errors coming from the Signal From Workspace block are synchronized with channel symbols coming from the Hamming Encoder block. To determine the correct sample time, use the following relationship:

Sample time

Frame period

Samples per frame

Importing Data from the MATLAB®Works p ace

The frame size of the signal coming from the Hamming Encoder block is 7. You set the frame size by the Codeword length parameter in the block’s dialog box. So you should set the Samples per frame parameter in the Signal From Workspace block to

The frame period of the Hamming Encoder block is 4, because the Bernoulli Binary Generator block has a Sample time of of

4.SosettheSample time parameter in the Signal From Workspace block

4/7 so that the frame period of the block is 4.

1 and a Sam ples per frame

If you are not sure what the frame sizes and frame periods of signals in the model are, you can display them using a Probe block, as described in “Using a Probe Block to Determine Symbol Period” on page 2-45. To do this, attach two Probe blocks, one to the line leading out of the Hamming Encoder block and one to the line leading out of the Signal From Workspace block. In the dialog boxes for both Probe b lo cks, clear the check boxes next to Probe complex signal an d Probe signal dimensions. Next, attach Terminator blocks to the output ports of the Probe blocks. Then select Update diagram from the Edit menu. The model should appear as in the following figure.

Hamming Code Model with Probe Blocks

Both Probe blocks should display a fram e size of 7 and a frame period of 4.

A quick way to check whether the frame periods of two signals are the same is to select Sample time colors from the Port/signal displays submenu

3-17

3 Using Communications Blockset™ Software with MATLAB

of the Format menu. See“UsingSampleTimeColorstoCheckSample Times” on page 2-53.

3-18

Learning More

In this section...

“Online Help” on page 3-19

“Demos” on page 3-19

“The MathWorks Online” on page 3-20

Online Help

To find online documentation, select Product Help from the Help menu in the MATLAB desktop. This launches the Help browser. For a more detailed explanation of any of the topics covered in this book, see the documentation listed under Communications Blockset in the left pane of the Help browser.

Besides this book, Communications Blockset Getting Started Guide, the online documentation contains the following topics:

Learning More

• “Using the Libraries” describes each of the core libraries of the blockset.

• “Modeling Communication Systems” illustrates techniques for modeling a

full communication s ystem .

• “Block Reference” provides descriptions of the Communications Blockset

libraries and lists the blocks in them.

• “Blocks — Alphabetical List” provides a detailed description of the blocks

in C ommunications Blockset software in alphabetical order.

The Help Navigator, in the left pane of the Help browser, supports string searches. You can specify strings and theonlinemanualsthatyouwantto search. To begin a search, click the Search tab. To view the index for the documentation, click the Index tab.

Demos

ToseemoreCommunicationsBlocksetexamples,type

demo

3-19

3 Using Communications Blockset™ Software with MATLAB

at the MATLAB prompt. This opens the MATLAB Demo window. Double-click Blocksets and then s elect Communications to list the available demos.

The MathWorks Online

To find the Communications Blockset documentation on the MathW orks Web site, point your Web browser to

http://www.mathworks.com/access/helpdesk/help/helpdesk.shtml.

3-20

List of Examples

Use this list to find examples in the documentation.

A List of Examples

Getting Started

“Running a Simul “Building a Simple Model” on page 2-11 “Building a Channel Noise Model” on page 2-24 “Modeling a Ch “Reducing the Error Rate with a Cyclic Code” on page 2-42 “Building a Frequency-Shift Keying Model” on page 2-47 “Building a Co “Sending Data to the MATLAB Workspace” on page 3-2 “Running Multiple Simulations” on page 3-8 “Importing

ink Model” on page 2-2

annel with Modulation” on page 2-39

nvolutional Code Model” on page 2-54

Data from the MATLAB Workspace” on page 3-13

A-2

Index

IndexA

adding noise to models 2-19

binary phase shift keying (BPSK) 2-40 block libraries 2-13 block masks 2-7 block parameters 2-7 blocks

connecting 2-15 labeling 2-33

moving into model 2-14 BPSK modulation example 2-39 building models 2-11

channel c oding 2-24 channel noise example 2-24

commstartup usage 2-12

connecting blocks 2-15 constellation 2-4 continuous signals 2-22 convolutional code example 2-54 convolutional encoder 2-55 cyclic code example 2-42

delays 2-51

calculating 2-51 discrete signals 2-22 drawing a branch line 2-28

displaying in a scope 2-34 simulating by importing data 3-15

Find Delay block

FSK model 2-51 frame-based processing 2-22 frames 2-22

displaying sizes of 2-34 frequency-shift keying (FSK) 2-47 FSK model 2-47

Hamming code example 2-30

importing data from MATLAB workspace 3-13

labeling blocks 2-33 Library Browser 2-13

models

building 2-11

multirate 2-52

running 2-18

saving 2-21 moving blocks into a model 2-14 multirate models 2-52

error rate

displaying 2-6

errors

noise

adding to models 2-19

Index-1

Index

online help 3-19

plotting results of multiple simulations 3-10

quadrature amplitude modulation (QAM) 2-4

running simulations 2-5

sample time colors 2-53 sample times 2-22

setting 3-16

sample-based processing 2-22 samples per frame 2-22

setting 3-16 saving models 2-21 sending data to MATLAB workspace 3-2 signals

continuous 2-22

discrete 2-22

displaying in a scope 2-18

simulating by importing data 3-13 simulation parameters 2-17 simulations

plotting results of 3-10

running 2-5

running from command line 3-7 Simulink libraries 2-13 Simulink Library Browser 2-13 symbol periods 2-44

Index-2

Mathworks COMMUNICATIONS BLOCKSET 4 user guide

Specifications and Main Features

Frequently Asked Questions

User Manual