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EC6512 Communication system laboratory Dept of Electronics and Communication Engg

DMI college of Engineering 1

DMI COLLEGE OF ENGINEERING

PALANCHUR CHENNAI – 600 123

DEPARTMENT OF ELECTRONICS AND COMMUNICATION

ENGINEERING

LABORATORY MANUAL

SUB CODE : EC6512

SUBJECT TITLE: COMMUNICATION SYSTEMS LABORATORY

SEMESTER : V

YEAR : III

DEPARTMENT : ELECTRONICS AND COMMUNICATION ENGINEERING



Vision of the Department

To develop committed and competent technologists in electronics and communication

engineering to be on par with global standards coupled with cultivating the innovations and ethical

values.

Mission of the Department:

DM 1: To be a centre of excellence in teaching learning process promoting active learning with

critical thinking.

DM 2: To strengthen the student’s core domain and to sustain collaborative industry interaction with

internship and incorporating entrepreneur skills.

DM 3: To prepare the students for higher education and research oriented activities imbibed with

ethical values for addressing the social need.

PROGRAM EDUCATIONAL OBJECTIVES (PEOs):

PEO1. CORE COMPETENCY WITH EMPLOYABILITY SKILLS: Building on fundamental

knowledge, to analyze, design and implement electronic circuits and systems in Electronics and

Communication Engineering by applying knowledge of mathematics and science or in closely related

fields with employability skills.

PEO2. PROMOTE HIGHER EDUCATION AND RESEARCH AND DEVELOPMENT: To

develop the ability to demonstrate technical competence and innovation that initiates interest for

higher studies and research.

PEO3. INCULCATING ENTREPRENEUR SKILLS: To motivate the students to become

Entrepreneurs in multidisciplinary domain by adapting to the latest trends in technology catering the

social needs.

PEO4. ETHICAL PROFESSIONALISM: To develop the graduates to attain professional

excellence with ethical attitude, communication skills, team work and develop solutions to the

problems and exercise their capabilities.



PROGRAM OUTCOMES (POs)

The Program Outcomes (POs) are described as.

1. Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals

and an engineering specialization to the solution of complex engineering problems.

2. Problem Analysis: Identify, formulate, review research literature, and analyze complex engineering

problems reaching substantiated conclusions using first principles of mathematics, natural sciences,

and engineering sciences.

3. Design / Development of solutions: Design solutions for complex engineering problems and

design system components or processes that meet the specified needs with appropriate consideration

for the public health and safety, and the cultural, societal, and environmental considerations.

4. Conduct investigations of complex problems: Use research-based knowledge and research

methods including design of experiments, analysis and interpretation of data, and synthesis of the

information to provide valid conclusions.

5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern

engineering and IT tools including prediction and modeling to complex engineering activities with

an understanding of the limitations.

6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess

societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the

professional engineering practice.

7. Environment and sustainability: Understand the impact of the professional engineering

solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for

sustainable development.

8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms

of the engineering practice.

9. Individual and team work: Function effectively as an individual and as a member or leader in

diverse teams, and in multidisciplinary settings.

10. Communication: Communicate effectively on complex engineering activities with the

engineering community and with society at large, such as, being able to comprehend and write

effective reports and design documentation, make effective presentations, and give and receive clear

instructions.



11. Project management and finance: Demonstrate knowledge and understanding of the

engineering management principles and apply these to one’s own work, as a member and leader in a

team, to manage projects and in multidisciplinary environments.

12. Life-long learning: Recognize the need for and have the preparation and ability to engage in

independent and lifelong learning in the broadest context of technological change.

PROGRAM SPECIFIC OUTCOMES (PSOs):

PSO1. Analyze and design the analog and digital circuits or systems for a given specification and

function.

PSO2. Implement functional blocks of hardware-software co-designs for signal processing and

communication applications.

PSO3. Design, develop and test electronic and embedded systems for applications with real time

constraint and to develop managerial skills with ethical behavior to work in a sustainable environment.



INSTRUCTIONS TO STUDENTS FOR WRITING THE RECORD

In the record, the index page should be filled properly by writing the corresponding experiment

number, experiment name, date on which it was done and the page number.

On the right side page of the record following has to be written:

1. Title: The title of the experiment should be written in the page in capital letters. In the left top

margin, experiment number and date should be written.

2. Aim: The purpose of the experiment should be written clearly.

3. Apparatus/Tools/Equipments/Components used: A list of the Apparatus/Tools/ Equipments/

Components used for doing the experiment should be entered.

4. Theory: Simple working of the circuit/experimental set up/algorithm should be written.

5. Procedure: Steps for doing the experiment and recording the readings should be briefly

described(flow chart/ Circuit Diagrams / programs in the case of computer/processor related

experiments)

6. Results: The results of the experiment must be summarized in writing and should be fulfilling

the aim.

On the Left side page of the record following has to be recorded:

a) Circuit/Program: Neatly drawn circuit diagrams for the experimental set up.

b) Design: The design of the circuit components for the experimental set up for selecting the

components should be clearly shown if necessary.

Observations:

i. Data should be clearly recorded using Tabular Columns.

ii. Unit of the observed data should be clearly mentioned

iii. Relevant calculations should be shown. If repetitive calculations are needed, only show a

sample calculation and summarize the others in a table.



EC 6512 COMMUNICATION SYSTEMS LABORATORY L T P C

0 0 3 2

LIST OF EXPERIMENTS:

1. Signal Sampling and Reconstruction

2. Time Division Multiplexing

3. AM Modulator and Demodulator

4. FM Modulator and Demodulator

5. Pulse Code Modulation and Demodulation

6. Delta Modulation and Demodulation

7. Observation (simulation) of signal constellations of BPSK, QPSK and QAM

8. Line coding schemes

9. FSK, PSK and DPSK schemes (Simulation)

10. Error control coding schemes - Linear Block Codes (Simulation)

11. Communication link simulation

12. Equalization – Zero Forcing & LMS algorithms(simulation)



Course outcomes

CO1 Simulate end-to-end Communication Link

CO2 Demonstrate their knowledge in base band signaling schemes through implementation of

FSK, PSK and DPSK

CO3 Apply various channel coding schemes &demonstrate their capabilities towards the

improvement of the noise performance of communication system

CO4 Simulate & validate the various functional modules of a Communication systems.

CO5 To implement Equalization algorithms

CO PO, PSO Mappings.

Course Code

and Course

name

CO Program Outcomes PSO

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3

EC6512

Communication

Systems

Laboratory

CO1 2 3 2 2 2 2 - - 2 3 - 2 3 3 2

CO2 2 3 2 3 2 2 - - 3 2 - 3 3 3 2

CO3 3 2 3 2 3 2 - - 2 2 - 2 3 2 3

CO4 3 2 3 2 3 2 - - 2 2 - 2 3 2 3

CO5 3 3 2 2 3 3 - - 2 3 - 2 3 3 2

Average 3 2.6 2 2.2 3 2 - - 2 2 - 2.2 3 3 2



Ex. No NAME OF THE EXPERIMENT PAGE NO

1 SIGNAL SAMPLING AND RECONSTRUCTION 9

2 TIME DIVISION MULTIPLEXING 12

3 AM - MODULATOR AND DEMODULATOR 15

4 FM - MODULATOR AND DEMODULATOR 20

5 PULSE CODE MODULATION AND DEMODULATION 24

6 DELTA MODULATION AND DEMODULATION 28

7 OBSERVATION OF SIGNAL CONSTELLATION OF

BPSK,QPSK & QAM 32

8 LINE CODING SCHEMES 35

9.a SIMULATION OF FSK USING MATLAB 40

9.b SIMULATION OF PSK USING MATLAB 42

9.c SIMULATION OF DPSK USING MATLAB 44

10 ERROR CONTROL CODING SCHEMES- LINEAR BLOCK

CODES (SIMULATION) 46

11 COMMUNICATION LINK SIMULATION 48

12.a SIMULATION OF ZERO FORCING EQUALIZER USING

MATLAB 52

12.b SIMULATION OF LMS ALGORITHM USING MATLAB 55



CONTENT BEYOND THE SYLLABUS

Ex.No NAME OF THE EXPERIMENT PAGE NO

13 GENERATION AND DETECTION OF GMSK 58



Ex. No. 1 SAMPLING AND RECONSTRUCTION

AIM:

To sample a signal with different sampling frequencies and to reconstruct the same.

COMPONENTS REQUIRED:

THEORY:

The analog signal can be converted to a discrete time signal by a process called sampling. The

sampling theorem for a band limited signal of finite energy can be stated as,” A band limited signal of

finite energy, which has no frequency component higher than W Hz is completely described by

specifying the values of the signal at instants of time separated by 1/2W seconds.‟‟ It can be recovered from knowledge of samples taken at the rate of 2W per second.Sampling is the process of splitting the

given analog signal into different samples of equal amplitudes with respect to time. There are two

types of sampling namely natural sampling, flat top sampling. Sampling should follow strictly the

Nyquist Criterion i.e. the sampling frequency should be twice higher than that of the highest frequency

signal.

f s > 2 f m

Where,

f s - Minimum Nyquist Sampling rate (Hz)

f m - Maximum analog input frequency (Hz).

S.No. Name of the Equipment

/ Component

Range Quantity

1 Sampling trainer kit - 1

2 CRO 20MHz 1



TABULATION:

MODULATING SIGNAL:

Amplitude(V) Time period(ms) Frequency(KHz)

SAMPLED SIGNAL:

Amplitude

(V)

Sampling

frequency

(KHz)

Duty

Cycle (%)

No. of

Samples

Time period (ms)

(for each sample)

Total

Time

period

(ms)

Frequency

(KHz)

T on T off

SAMPLING:

AMPLITUDE(V)

TIME PERIOD(ms)

FREQUENCY(KHz)

INPUT SIGNAL

Duty cycle calculation:

D = Ton / (Ton + Toff) = ---------- %



PROCEDURE:

1. Give the connections as per the block diagram.

2. Apply the modulating signal and measure its amplitude and time period.

3. Set the sampling frequency to 80 KHz and note down the amplitude and time period of the

sampled signal.

4. Give the sampled signal to the reconstruction circuit and observe the reconstructed signal.

5. Note down the amplitude and time period of the reconstructed signal.

6. Repeat the same procedure for different sampling frequencies.

7. Plot the above waveforms in the graph.

MODEL GRAPH:

RESULT:

Thus the given signal is sampled with different sampling frequencies and the waveforms are

plotted.



Ex. No. 2 TIME DIVISION MULTIPLEXING

AIM:

To perform four channel Time Division multiplexing and De multiplexing.


BLOCK DIAGRAM:


/ Component

Range Quantity

1 Time Division Multiplexing kit - 1

2 CRO 20MHz 1



THEORY:

In PAM, PPM the pulse is present for a short duration and for most of the time between the

two pulses no signal is present. This free space between the pulses can be occupied by pulses from

other channels. This is known as Time Division Multiplexing. Thus, time division multiplexing makes

maximum utilization of the transmission channel. Each channel to be transmitted is passed through the

low pass filter. The outputs of the low pass filters are connected to the rotating sampling switch (or)

commutator. It takes the sample from each channel per revolution and rotates at the rate of f s.

Thus the sampling frequency becomes fs the single signal composed due to multiplexing of

input channels. These channels signals are then passed through low pass reconstruction filters. If the

highest signal frequency present in all the channels is fm, then by sampling theorem, the sampling

frequency fs must be such that fs≥2fm. Therefore, the time space between successive samples from any

one input will be Ts=1/fs, and Ts =1/2fm.

TABULATION:

1.TRANSMITTED SIGNALS:

Channel Amplitude(V) Time period(ms) Frequency(KHz)

2. SAMPLED SIGNAL:

Amplitude

(V)

No. of

Samples

Time period (ms)

(for each sample) Total Time

period(ms)

Frequency

(KHz)

Channel

Ton Toff



3. RECEIVED SIGNALS:

Signal Amplitude (V) Time period(ms) Frequency(KHz)

MODEL GRAPH:

PROCEDURE:


2. Apply the four input sinusoidal signals of different frequency to four channels and measure

the amplitude and time period of each signal.

3. Observe and measure the amplitude and frequency of the sampled signal for each channel

individually.

4. Then observe the multiplexed waveform in the CRO.

5. Apply the multiplexed signal to the de-multiplexer circuit and observe the original signals

transmitted.

6. Measure the amplitude and time period of de-multiplexed signal for each channel

individually.

7. Plot all the waveforms in the graph.

RESULT:

Thus the Time division multiplexing and de multiplexing waveforms are obtained.



Ex. No. 3 AMPLITUDE MODULATION AND DEMODULATION

AIM:

To determine the performance of Amplitude Modulation and Demodulation and analyses

the input and output waveforms.


THEORY:

Amplitude modulation is the process by which amplitude of the carrier signal is varied in

according with instantaneous value of the modulated signal. But frequency and phase of the

carrier wave is remains constant.

Modulation process in which the characteristics of carrier wave is varied (or) altered in

accordance with the instantaneous amplitude of the modulating signal usually low frequency

signal or audio frequency signal.

Let the sinusoidal carrier wave is usually Modulation,

V (t) = Vc Sin (Wç + C)

Amplitude modulation signal is greater than the carrier signal. Therefore test portion of

envelop of the modulating signal across the axis. So both Positive and Negative extension of

Modulation signal as concealed or clipped signal.


/ Component

Range Quantity

1

Amplitude Modulation / Demodulation

kit - 1

2 Patch chords. 10

3 CRO 20MHz 1



BLOCK DIAGRAM:

WAVEFORM:



TABULAR COLUMN:

Signal

Amplitude(V)

Frequency(KHz)

Message Signal

Modulated Signal

Demodulated

Signal

OUTPUT WAVEFORM:



PROCEDURE:

1. Refer to the FIG. & Carry out the following connections.

2. Connect o/p of FUNCTION GENERATOR section (ACL-01) OUT post to the i/p of

Balance Modulator1 (ACL-01) SIGNAL IN post.

3. Connect o/p of VCO (ACL-01) OUT post to the input of Balance modulator 1(ACL-01)

CARRIER IN post.

4. Connect the power supply with proper polarity to the kit ACL-01 & ACL -02,While

connecting this, ensure that the power supply is OFF.

5. Switch on the power supply and Carry out the following presetting:

• FUNCTION GENERATOR: Sine LEVEL about 0.5 Vpp; FREQ. about 1KHz.

• VCO: LEVEL about 2Vpp; FREQ. about 850 KHz, Switch on 1500KHz.

• BALANCED MODULATOR1: CARRIER NULL completely rotates Clockwise or counter

clockwise, so that the modulator is “unbalanced” and an AM signal with not suppressed

carrier is obtained across the output: adjust OUTLEVEL to obtain an AM signal across the

output whose amplitude is about 100mVpp.

• LOCAL OSCILLATOR (ACL-02): 1300KHz, 2V.

6. Connect local oscillator OUT post to LO IN of the mixer section.

7. Connect balance modulator1 out to RF IN of mixer section in ACL-02.

8. Connect mixer OUT to IF IN of 1st IF AMPLIFIER in ACL-02.

9. Connect IF OUT1 of 1st IF to IF IN 1 and IF OUT2 of 1st IF to IFIN 2 of 2ND IF AMPLIFIER.

10. Connect OUT post of 2nd IF amplifier to IN post of envelope detector.

11. Connect post AGC1 to post AGC2 and jumper position as per diagram.

12. Observe the modulated signal envelope, which corresponds to the waveform of the

modulating signal at OUT post of the balanced modulator1 of ACL-01.Connect the

oscilloscope to the IN and OUT post of envelope detector and detect the AM signal and the

detected one . If the central frequency of the amplifier and the carrier frequency of the AM

signal and local oscillator frequency coincides, you obtain two signals

13. Check that the detected signal follows the behavior of the AM signal envelope. Vary the

frequency and amplitude of the modulating signal, and check the corresponding variations

of the demodulated signal.



RESULT:

Thus the Amplitude Modulation and Demodulation has been performed and its output

waveforms are obtained.



Ex. No. 4 FREQUENCY MODULATION AND DEMODULATION

AIM:

To determine the performance of Frequency Modulation and Demodulation and analyses

the input and output waveforms.


THEORY:

Frequency modulation is the process by which amplitude of the carrier signal is varied in

accordance with instantaneous value of the modulated signal. But frequency and phase of the

carrier wave is remains constant.

Modulation process in which the characteristics of carrier wave is varied (or) altered in

accordance with the instantaneous amplitude of the modulating signal usually low frequency

signal or audio frequency signal.

Frequency modulation signal is greater than the carrier signal. Therefore test portion of

envelop of the modulating signal across the axis. So both Positive and Negative extension of

Modulation signal as concealed or clipped signal.

F (K) = AC

B Modulated signal index

Depend on the ‘B’ the FM signal is Classified as

1. Narrow Band FM (B < 1)

2. Wide Band FM (B > 1)


/ Component

Range Quantity

1 Frequency Modulation / Demodulation

kit - 1

2 Patch chords. - 10

3 CRO 20MHz 1



BLOCK DIAGRAM:

TABULAR COLUMN:

Signal Amplitude(V) Frequency(KHz)

Message

Modulated Signal

De-modulated Signal

WAVEFORM:



PROCEDURE:

1) Connect the output of function generator ( ACL-03) OUT post to the MOD IN (ACL-

03)post.

2) Connect the output of frequency modulator FM/RF OUT post to the input of RF IIN of

mixer in ACL-03.

3) Connect the power supply with proper polarity to the kit ACL-03 & ACL-04, while

connecting this; ensure that the power supply is OFF.

4) Switch ON the power supply and carry out the following presetting:

Frequency Modulator: Switch on 500khz; level about 1 Vpp; freq.about 450khz.

Frequency demodulator in foster-seeley mode ( Jumpers in FS position).

Function generator: Sine wave (JP1); Level about 100mVpp;Freq.about 500hz.

Local oscillator : Level about 1Vpp; freq. about 1000khz on(center).

5) Connect the local oscillator OUT to the LO IN of the mixer and mixer OUT to the

Limiter IN post with the help of shorting links.

6) Then connect the limiter OUT post to the FM IN of Fooster–seeley detector and Fs OUT

to the IN of Low pass filter.

7) Then observe the frequency modulated signal at FM/RF OUT post of frequency

modulator and achieve the same signal by setting frequency of local oscillator at OUT

post of Mixer,then observe Limiter OUT post where output is clear from moise and

stabilize around a value of about 1.5Vpp.

8) Connect the oscilloscope across post FS OUT of ALC-04(detected signal) and Function

generator OUT post(modulating signal) of ACL-04. If the central frequency of the

discriminator and the carrier frequency of the FM signal and the local oscillator

frequency coincide,you obtain two signals.



The fact that there is still some high frequencyripple at the output of the FOSTER-SEELEY detector

block indicates that the passive low pass filter circuit at the blocks output is not sufficient to remove

this unwanted high frequency components.

9) The demodulated signal has null continuous component. Vary the amplitude of FM

Signal and check that the amplitude of the detected signal varies, too.

10) Increase the carrier frequency and note that positive voltages added to the detected signal.

11) Reduce the carrier frequency towards the proper value ( 450 Khz). Increase the amplitude

of modulating signal to generate FM Signal with frequency deviation over the linear zone

of the discriminator.

RESULT:

Thus the Frequency modulation and demodulation has been performed and its output

waveforms are obtained



Ex. No. 5 PULSE CODE MODULATION AND DEMODULATION

AIM:

To obtain Pulse Code Modulated and demodulated signals using PCM trainer kit.


THEORY:

Pulse code modulation is known as digital pulse modulation technique. It is the process in

which the message signal is sampled and the amplitude of each sample is rounded off to the nearest

one of the finite set of allowable values. It consists of three main parts transmitter, transmitter path and

receiver. The essential operation in the transmitter of a PCM system are sampling, Quantizing and

encoding. The band pass filter limits the frequency of the analog input signal. The sample and hold

circuit periodically samples the analog input signal and converts those to a multi level PAM signal.

The ADC converts PAM samples to parallel PCM codes which are converted to serial binary data in

parallel to serial converter and then outputted on the transmission line as serial digital pulse. The

transmission line repeaters are placed at prescribed distance to regenerate the digital pulse.

In the receiver serial to parallel converter converts serial pulse received from the transmission

line to parallel PCM codes. The DAC converts the parallel PCM codes to multi level PAM signals.

The hold circuit is basically a Low Pass Filter that converts the PAM signal back to its original analog

form.


/ Component

Range Quantity

1 PCM trainer kit - 1

2 CRO 20MHz 1



BLOCK DIAGRAM:

TABULATION:

TRANSMITTED SIGNAL:

Amplitude (V) Time period (ms) Frequency (KHz)



SAMPLED SIGNAL:

Amplitude

(V)

No. of

Samples

Time period (ms)

(for each sample) Total Time

Period (ms)

Frequency

(KHz) Channel

Ton Toff

RECEIVED SIGNAL:

PROCEDURE:


2. Measure the amplitude and time period of the input signal.

3. Measure the amplitude and time period of the sampled signal.

4. Apply the input signal to the PCM kit and observe and measure the PCM output.

5. Plot the waveforms in the graph.

Amplitude (V) Time period (ms) Frequency (KHz)



RESULT:

Thus the Pulse Code Modulated signals are obtained and the waveforms are plotted.



Ex. No. 6 DELTA MODULATION AND DEMODULATION

AIM:

To obtain Delta Modulated and Adaptive Delta modulated waveforms.


S.No. Name of the Equipment /

Component

Range Quantity

1 Delta Modulation & Adaptive

Delta modulationTrainer kit

- 1

2 CRO 10 MHz 1

3 Patch cords - 10

4 Power Supply (0-30) V 1

THEORY:

Delta modulation uses a single bit PCM code to achieve digital transmission of analog signal.

With conventional PCM, each code is a binary representative of both the sign and magnitude of a

particular sample. The algorithm of delta modulation is simple if the current sample is smaller than the

previous sample a logic0 is transmitted. If the current sample is larger than the previous sample a logic

1 is transmitted.



MODEL GRAPH:

TABULAR COLUMN:

S.No

Type of Signal

Amplitude (V)

Time Period (ms)



BLOCK DIAGRAM:



PROCEDURE:

1. Connections are to be given as per the block diagram.

2. Observe the modulated waveforms.

3. Measure the amplitude and time period of both the waveforms.

4. Plot the graph.

RESULT:

Thus delta modulation waveform are obtained and results are tabulated .



Ex. No. 7 OBSERVATION OF SIGNAL CONSTELLATION OF

BPSK, QPSK & QAM

AIM:

To plot the constellation diagram of digital modulation system BPSK, QPSK & QAM

using MATLAB.

SOFTWARE REQUIRED:

MATLAB

THEORY:

A constellation diagram is a representation of a signal modulated by an arbitrary digital

modulation scheme. It displays the signal as a two dimensional scatter diagram in the complex plane at

symbol sampling instants. It can also be viewed as the possible symbols that may be selected by a

given modulation scheme as points in the complex plane.

PROGRAM: BPSK

clc; clear all; close all; M=2; k=log2(M); n=3*1e5; nsamp=8; X=randint(n,1); xsym = bi2de(reshape(X,k,length(X)/k).','left-msb');

Y_psk= modulate(modem.pskmod(M),xsym); Ytx psk =

Y psk; EbNo=30; SNR=EbNo+10*log10(k)-10*log10(nsamp); Ynoisy psk = awgn(Ytx psk,SNR,'measured'); Yrx psk = Ynoisy psk; h1=scatterplot(Yrx psk(1:nsamp*5e3),nsamp,0,'r.'); hold

on; scatterplot(Yrx psk(1:5e3),1,0,'k*',h1); title('constellation diagram BPSK'); legend('Received signal' ,'signal constellation'); axis([-5 5 -5 5]);

hold off;



QPSK QAM

PROGRAM FOR QPSK & QAM:

clc; clear all; close all; M=16; k=log2(M); n=3*1e5; nsamp=8; X=randint(n,1); xsym = bi2de(reshape(X,k,length(X)/k).','left-msb'); Y_qam= modulate(modem.qammod(M),xsym); Y_qpsk= modulate(modem.pskmod(M),xsym); Ytx_qam = Y_qam; Ytx_qpsk = Y_qpsk; EbNo=30; SNR=EbNo+10*log10(k)-10*log10(nsamp); Ynoisy_qam = awgn(Ytx_qam,SNR,'measured'); Ynoisy_qpsk = awgn(Ytx_qpsk,SNR,'measured'); Yrx_qam = Ynoisy_qam; Yrx_qpsk = Ynoisy_qpsk; h1=scatterplot(Yrx_qam(1:nsamp*5e3),nsamp,0,'r.'); hold on; scatterplot(Yrx_qam(1:5e3),1,0, 'k*',h1); title('constellation diagram 16 QAM'); legend('Received signal' ,'signal constellation'); axis([-5 5 -5 5]); hold off;



h2=scatterplot(Yrx qpsk(1:nsamp*5e3),nsamp,0,'r.'); hold

on; scatterplot(Yrx qpsk(1:5e3),1,0,'k*',h2); title('constellation diagram 16 PSK'); legend('Received signal' ,'signal constellation'); axis([-5 5 -5 5]); hold off;

RESULT:

Thus the constellation diagrams of digital modulation system BPSK, QPSK & QAM are

simulated & plotted in MATLAB.



Ex. No. 8 LINE CODING SCHEMES

AIM:

To Analyze line coding and decoding techniques.


S.No Name of the Equipment Range Quantity

1 Line coding & decoding kit - 1

2 Connecting plugs - 1

3 CRO 10 MHz 1

THEORY:

NON-RETURN TO ZERO signal are the easiest formats that can be generated. These signals

do not return to zero with the clock. The frequency component associated with these signals are half

that of the clock frequency. The following data formats come under this category. Non-return to zero

encoding is commonly used in slow speed communications interfaces for both synchronous and

asynchronous transmission. Using NRZ, logic 1 bit is sent as a high value and a logic 0 bit is sent as a

low value.

a) NON-RETURN TO ZERO-LEVEL (NRZ-L)

This is the most extensively used waveform in digital logics. All „ones‟ are represented by

„high‟ and all „zeros‟ by „low‟. The data format is directly available at the output of all digital data

generation logics and hence very easy to generate. Here all the transitions take place at the rising edge

of the clock.

b) NON-RETURN TO ZERO-MARK (NRZ-M)

These waveforms are extensively used in tape recording. All „ones‟ are marked by change in

levels and all‟zeros‟ by no transitions, and the transitions take place at the rising edge of the clock.



LINE CODING WAVE FORM:

c) NON-RETURN TO ZERO-SPACE (NRZ-S)

This type of waveform is marked by change in levels for „zeros‟ and no transition for „ones‟

and the transitions take place at the rising edge of the clock. This format is also used in magnetic tape

recording.

d) UNIPOLAR AND BIPOLAR

Unipolar signals are those signals, which have transition between 0 to +VCC. Bipolar

signals are those signals, which have transition between +VCC to –VCC.

e) BIPHASE – LINE CODING(BIPHASE -L):

With the Biphase – L one is represented by a half bit wide pulse positioned during the first

half of the bit interval and a zero is represented by a half bit wide pulse positioned during the

second half of the bit interval.

f) BIPHASE MARK CODING(BIPHASE-M):

With the Biphase-M, a transition occurs at the beginning of every bit interval. A „one‟ is

represented by a second transition, half bit later, whereas a zero has no second transition.



g) BIPHASE SPACE CODING(BIPHASE-S):

With a Biphase-S, a transition occurs at the beginning of every bit interval. A „zero‟ is marked by a second transition, one half bit later; „one‟ has no second transition.

h) RETURN TO ZERO SIGNALS:

These signals are called “Return to Zero signals” since they return to „zero‟ with the clock. In

this category, only one data format, i.e, the unipolar return to zero(URZ); With the URZ a „one‟ is

represented by a half bit wide pulse and a „zero‟ is represented by the absence of pulse.

i) MULTILEVEL SIGNALS:

Multilevel signals use three or more levels of voltages to represent the binary digits, „one‟ and

„zero‟ – instead of normal „highs‟ and „lows‟ Return to zero – alternative mark inversion (RZ -

AMI) is the most commonly used multilevel signal. This coding scheme is most often used in

telemetry systems. In this scheme, „one‟ are represented by equal amplitude of alternative pulses,

which alternate between a +5 and -5. These alternating pulses return to 0 volt, after every half bit

interval. The „Zeros‟ are marked by absence of pulses.

PROCEDURE:

UNIPOLAR RZ ENCODING AND DECODING

1. Connect the PRBS to test point p7

2. Connect the test point p8 to p18

3. Set the SW1 in RZ position

4. Set the potentiometer p1 in minimum position

5. Switch ON the power supply.

6. Press the switch SW2 once

7. Display the encoded signal at test point p8 on one channel of cro and decoded signal at test

point p20 on second channel of CRO.



UNIPOLAR NRZ ENCODING AND DECODING

1. Connect the PRBS (P3)to test point p7






7. Display the encoded signal at test point p8 on channel 1 of cro and decoded signal at test point

p20 on second channel of CRO.

POLAR NRZ ENCODING AND DECODING

8. Connect the PRBS to test point p9 and PRBS to P10








BI-POLAR RZ ENCODING AND DECODING

15. Connect the PRBS to test point p12 and CLK to P13 point.










BI-POLAR NRZ ENCODING AND DECODING



24. Set the SW1 in NRZ position






MANCHESTER ENCODING AND DECODING:



3. Set the SW1 in NRZ position




7. Display the encoded signal at test point p14 on one channel of CRO and decoded signal at test


RESULT:

Thus the line coding and decoding techniques were analyzed and observed and the graph is plotted.



Ex. No. 9 a SIMULATION OF FSK USING MATLAB

AIM:

To Implement FSK using MATLAB.

SOFTWARE REQUIRED:

MATLAB

PROGRAM:

clc; t = 0:0.0001: 0.15; m = square (2*pi*10*t); c1 = sin (2*pi*60*t); c2 = sin (2*pi*120*t); s1 = (m.*c1); for i = 1 : 1500 if(m(i)==1) s1(i)=c2(i); else s1(i)=c1(i); end end figure(2); subplot(411); plot(m); subplot(412); plot(c1); subplot(413); plot(c2); subplot(414); plot(s1);



SIMULATED WAVEFORM:

RESULT:

Thus FSK was implemented using MATLAB.



Ex. No. 9 b SIMULATION OF PSK USING MATLAB

AIM:

To implement PSK using MATLAB.

SOFTWARE REQUIRED:

MATLAB

PROGRAM:

clc; c11 = sin(2*pi*60*t); t = 0:0.0001:0.15; m = square (2*pi*10*t); c22 = sin((2*pi*60*t)+ pi); s2 = (m.*c11); for i = 1:1500 if(m(i)==1)

s2(i)=c11(i); else s2(i)=c22(i); end end figure(3); subplot(411); plot(m); subplot (412); plot(c11); subplot (413); plot (c22); subplot(414); plot(s2);



SIMULATED WAVEFORM:

RESULT:

Thus PSK was implemented using MATLAB



Ex. No. 9 c SIMULATION OF DPSK USING MATLAB

AIM:

To implement DPSK using MATLAB.

SOFTWARE REQUIRED:

MATLAB

PROGRAM:

clc;

clear all;

close all;

N=10^4

rand('state',100); rand('state',200); ip=rand(1,N)>0.5,ipD=mod(filter(1,[1 -1],ip),2); s=2*ipD-1; n=1/sqrt(2)*[randn(1,N)+j*randn(1,N)]; Eb N0 db=[-3:10]; for ii=1:length(Eb_N0_db) y=s+10^(-Eb_N0_db(ii)/20)*n; ipDHat_coh=real(y)>0; ipHat_coh=mod(filter([1 -1],1,ipDHat coh),2); nErr_dbpsk_coh(ii)=size(find([ip-ipHat coh]),2); end

simBer_dbpsk_coh=nErr_dbpsk_coh/N; theoryBer dbpsk coh=erfc(sqrt(10.^(Eb_N0_db/10))).*(1-5*erfc(sqrt(10.^(Eb_N0_db/10)))); close all; figure

semilogy(Eb N0 db,theoryBer_dbpsk_coh,'b.-'); hold

on;semilogy(Eb N0 db,simBer dbpsk_coh,'mx-'); aixs([-2 10 10^-6 0.5]);grid on;

legend('theory','simulation'); xlabel('Eb/N0,db');ylabel('bit error rate'); title('bit error probability curve for coherent demodulation of dbpsk');



WAVEFORM OUTPUT:

RESULT:

Thus DPSK was implemented using MATLAB.



Ex. No. 10 ERROR CONTROL CODING SCHEMES-LINEAR BLOCK CODE

AIM:

a. To generate parity check matrix & generator matrix for a (7,4) Hamming code.

b. To generate parity check matrix given generator polynomial g(x) = 1+x+x3.

c. To determine the code vectors.

d. To perform syndrome decoding

PROGRAM:

Generation of parity check matrix and generator matrix for a (7,4) Hamming code.

[h,g,n,k] = hammgen(3);

Generation of parity check matrix for the generator polynomial g(x) = 1+x+x3.

h1 = hammgen(3,[1011]);

Computation of code vectors for a cyclic code

clc; close all;

n=7;

k=4;

msg=[1 0 0 1; 1 0 1 0; 1 0 1 1];

code = encode(msg,n,k,'cyclic');

msg

code

SYNDROME DECODING

clc;

close all;

q=3;

n=2^q-1;

k=n-q;

parmat = hammgen(q); % produce parity-check matrix trt =

syndtable(parmat); % produce decoding table recd = [1 0 1

1 1 1 0 ] %received vector syndrome = rem(recd *

parmat',2);

syndrome de = bi2de(syndrome, 'left-msb'); %convert to

decimal disp(['Syndrome =

',num2str(syndrome_de),.....decimal), ',num2str(syndrome),'



(binary) ']); corrvect = trt(1+syndrome_de, :);%correction

vector correctedcode= rem(corrvect+recd,2);

parmat corrvect

corrected code

SIMULATED OUTPUT:

RESULT:

Thus Encoding and decoding of block codes are performed using MATLAB.



Ex. No. 11 COMMUNICATION LINK SIMULATION

AIM:

To study Digital Modulation techniques using Matlab (Simulink).

SOFTWARE REQUIRED:

MATLAB (SIMULINK )

THEORY:

AMPLITUDE PHASE SHIFT KEYING

ASK is the simplest modulation technique, where a binary information signal directly

modulates the amplitude of an analog carrier. ASK is similar to standard amplitude modulation except

there are 2 output amplitudes possible. It is also referred as on-off keying

FREQUENCY SHIFT KEYING

In FSK, modulating signal is a binary signal that varies between two discrete voltage levels

rather than a continuously changing analog waveform.

BINARY PHASE SHIFT KEYING

The simplest form of PSK is binary phase shift keying( N=1 and M=2). 2 phases are possible

for the carrier. One phase represents logic 1 & other phase represents logic 0. As the input signal

changes state, the phase of the output carrier shifts between two angles that are separated by 180°

BPSK is a form of square wave modulation of a continuous wave (CW) signal.

PROCEDURE:

AMPLITUDE SHIFT KEYING:

1. Open Simulink library Browser by Click on the Simulink in command window.

2. Click on the file.

3. Click on the Communication Block Set and drag PN Sequence and a sine wave generator block for carrier.

4. Click on the Math Operation and drag Product in the file.

5. Click on the Sink tab and drag out the scope to the file.

6. Now connect PN sequence an a sine wave generator to the product and a output with scope.

7. Double click on the PN sequence generator then PN sequence generator screen opens as shown below.



ASK USING PRODUCT ASK USING SWITCH

SIMULATED WAVEFORM:



FREQUENCY SHIFT KEYING (FSK):

Repeat Procedure 1,2,3,4,5,6,7 only difference is that in place of one sine wave generator two

sine wave generator are used.

SIMULATED WAVEFORM:



PHASE SHIFT KEYING (PSK):

SIMULATED WAVEFORM:

RESULT:

Thus Digital Modulation techniques was designed and performed using MATLAB

SIMULINK



Ex.No. 12 a

SIMULATION OF ZERO FORCING EQUALIZER USING MATLAB

AIM:

To simulate the Zero Forcing Equalizer using MATLAB.

SOFTWARE USED:

MATLAB

THEORY:

Equalizer can be employed to mitigate the ISI for a smooth recovery of transmitted symbols and to improve the receiver performance.

Zero forcing (or) linear equalizer which processes the incoming signal with a linear filter. It is classified into two

(a) Symbol spaced equalizer

(b) Fractionally spaced equalizer

SYMBOL SPACED EQUALIZER:

A symbol spaced linear equalizer consist of a tapped delay line that stores samples from the

input signal. Here the sample rates of both input & output signals are equal to 1/T. Fractionally spaced

equalizer:

A Fractionally spaced linear equalizer is similar to a symbol spaced equalizer,but the former

receives K input samples before it produces one output sample & updates the weights, where K is an

integer. Here the output sample rates is 1/T,while that of input sample is K/T.



PROGRAM:

clc;

clear all;

close all;

M=4;

msg=randint(1500,1,M);

modmsg=pskmod(msg,M);

sigconst=pskmod([0:M-1],M);

trainlen=500;

chan=[.986;.845;.237;.123+.31i];

filtmsg=filter(chan,1,modmsg);

eqobj =lineareq(8,lms(0.01),sigconst,1);

[symbolest,yd]=equalize(eqobj,filtmsg,modmsg(1:trainlen));

h=scatterplot(filtmsg,1,trainlen,'bx');hold on;

scatterplot(symbolest,1,trainlen,'r.',h);

scatterplot(sigconst,1,0,'k*',h);

legend('fitered signal','equalized signal','ideal signal constellation'); hold

off;

demodmsg noeq=pskdemod(filtmsg,M);

demodmsg =pskdemod(yd,M);

[nnoeq,rnoeq]=symerr(demodmsg_noeq(trainlen+1:end),msg(trainlen+1:end));

[neq,req] = symerr(demodmsg(trainlen+1:end),msg(trainlen+1:end));

disp('symbol error rate with equalizer:');

disp(req);

disp('symbol error rate without equalizer:');

disp(rnoeq)



SIMULATED OUTPUT:

Enter the system order, N=5

Enter the number of iterations, M=200

RESULT:

Thus the Zero Forcing Equalizer is simulated in MATLAB.


DMI college of Engineering

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Ex.No.12 b

SIMULATION OF LMS ALGORITHM USING MATLAB

AIM:

To simulate Least Mean Square (LMS) algorithm to adaptively adjust the coefficients of an FIR filter.

SOFTWARE REQUIRED:

MATLAB

THEORY:

The LMS recursive algorithm used for adjusting the filter coefficients adaptively so as to

minimize the sum of squared error is described below.

Let x[n] be the input sequence and y[n] be the output sequence of an FIR filter. Then,the

output is given by the expression

Y[n]=∑ h[k]x[n-k], n=0,1,……M

Where h[n] is the adjustable coefficients of FIR filter.

Let the desired sequence be d[n].Then, the error sequence e[n] is given by

e[n] = d[n] – y[n] , n=0,1,……M

The LMS algorithm starts with any arbitrary choice of h[k],say h0[k].For example, we may

begin with h0[k]=0,0 ≤ k ≤ N-1.After that each new sample x[n] enters the adaptive filter ,we

compute the corresponding output, say y[n], form the error signal e[n]=d[n]-y[n],and update the

filter coefficients according to the equation

hn[k] = hn-1[k] +µ.e[n].x[n-k], 0 ≤ k ≤ N-1,n=0,1…..where µ is called step size parameter, x[n-k]

is the sample of input signal located at the kth tap of the filter at time n and e[n]x[n-k] is an

approximation(estimate) of the negative of the gradient for the kth filter coefficients.

The step size parameter µ controls the rate of convergence. Large value of µ leads to rapid

convergence and smaller value leads to slower convergence.



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If µ is made too large,the algorithm becomes unstable.In order to ensure convergence and

good tracking capabilities in slowly varying channels, the step size parameters is given by

µ=1/5NPx where N is the length of the adaptive FIR filter and Px is the average power in the input

signal.

PROGRAM:

clc;

clear all;

close all; N=input('enter the system order,N='); M=input('enter the number of iterations,M='); if((N>=2)&&(M>=2)) x=rand(M,1); b=fir1(N-1,0.5); n=0.1*randn(M,1); d=filter(b,1,x)+n; h=zeros(N,1); Px=(1/length(x))*sum(x.^2); mu=1/(5*N*Px); for n=N:M u=x(n:-1:n-N+1); y(n)=h'*u; e(n)=d(n)-y(n); h=h+mu*u*e(n); end hold on;plot(d,'g'); plot(y(),'r');

semilogy((abs(e())),'m'); title('system output'); xlabel('number of iterations'); ylabel('true and estimated output'); legend('desired','output','error' ); hold off; figure, plot(b','k+'); hold on, plot(h,'r*'); legend('actual weights','estimated weights'); hold off; title('comparison of actual weights and estimated weights'); else('system order and number of iterations should be greater than 1'); end



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SIMULATED OUTPUT:

RESULT:

Thus the Least Mean Square (LMS) algorithm is simulated in MATLAB.



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CONTENT BEYOND SYLLABUS

Ex. No. 13 GENERATION AND DETECTION OF GMSK

AIM:

To simulate GMSK Modulation and demodulation using Matlab

SOFTWARE REQUIRED:

MATLAB

PROGRAM:



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61

SIMULATED WAVEFORM:



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RESULT:

Hence generation and detection of GMSK is performed and results are plotted.

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