Title: Pulse Amplitude Modulation.

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1 Title: Pulse Amplitude Modulation. AIM Write a program to take input Frequency of Message Signal and find out the Aliased and Anti-Aliased wave, and also the Carrier Signal, Message Signal and their Fourier Transformation Spectrum. Apparatus Required: Matlab to be installed in the computer or in the laptop. Theory: Pulse amplitude modulation is the pulse analog modulation scheme in which the amplitude of train of carrier pulses are varied according to the instantaneous amplitude of the message signal. Pulse-amplitude modulation (PAM), is a form of signal modulation where the message information is encoded in the amplitude of a series of signal pulse. It is an analog pulse modulation scheme in which the amplitudes of a train of carrier pulses are varied according to the sample value of the message signal. Demodulation is performed by detecting the amplitude level of the carrier at every single period. PAM is a technique that is also used in PCM. Aliasing is an effect that causes different signals to become indistinguishable from each other during sampling. Aliasing is characterized by the altering of output compared to the original signal because resampling or interpolation resulted in a lower resolution in images, a slower frame rate in terms of video or a lower wave resolution in audio. Anti-aliasing filters can be used to correct this problem. In pam pulse by pulse transmission is occurred. Each of the pulse to be transmitted corresponding baseband signal and can be directly transmitted through baseband channel. There are three types of sampling: 1. Instantaneous sampling 2. Natural Sampling 3. Flat top Sampling(We can retrieve the signal by ejecting the noise, if noise is induced by accident) We use stem function to discrete the signal. 1) PAM (INSTANTANEOUS SAMPLING)

2 Code: clc clear close all fm= input('enter the frequency of message signal'); t=-1:0.01:1; x=(t==0); y=sin(2*pi*fm*t); fs=100; N=length(t); xf=fftshift(fft(x,n)/n) f=linspace(-fs/2,fs/2,n) yf=fftshift(fft(y,n)/n); subplot(2,2,1) plot(t,x) xlabel('time') title('impluswe Function') subplot(2,2,2) plot( f, ceil(abs(xf))) xlabel('frequency') title('frequency Response') subplot(2,2,3) plot(t,y) xlabel('frequency') title('sine Function') subplot(2,2,4) plot(f,abs(yf)) xlabel('frequency') title('frequency Response') subplot(2,1,1) Fs=5*fm; t1=-1:1/fs:1; y1=sin(2*pi*fm*t1); plot(t,y) xlabel('time') title('no Aliasing') hold on stem(t1,y1) hold off subplot(2,1,2) Fs=1.5*fm; t1=-1:1/fs:1;

3 y1=sin(2*pi*fm*t1); plot(t,y) xlabel('time') title('aliasing') hold on stem(t1,y1) hold off Output:

4 2) PAM (Natural Sampling) : AIM- Write a Program to show the Carrier Signal, Message Signal, The PAM signal, and it s Demodulated Signal. CODE: clc; clear close all fc=100; fm=fc/10; fs=100*fc; t=0:1/fs:4/fm; mt=cos(2*pi*fm*t); ct=0.5*square(2*pi*fc*t)+0.5; st=mt.*ct; figure(1) subplot(4,1,1); plot(t,mt); title('message signal'); xlabel('timeperiod'); subplot(4,1,2); plot(t,ct); title('carrier signal'); xlabel('timeperiod');

5 subplot(4,1,3); plot(t,st); title('modulated signal'); xlabel('timeperiod'); % Demodulation % dt=st.*ct; filter=fir1(200,fm/fs,'low'); % FIR filter demod_signal=conv(filter,dt); % Convolution between filter coefficient and dt %t1=0:1/(length(demod_signal)-1):1; t1=linspace(0,1,length(demod_signal)); subplot(4,1,4); plot(t1,demod_signal); title('demodulated signal'); xlabel('timeperiod'); Output: 3) PAM(Flat top sampling): AIM- Write a Program to show the Impulse train, Message Signal, Modulated and it s Demodulated Signal. Code: clc

6 close all; fc = 20; fm = 2; fs = 1000; t = 1; n = [0:1/fs:t]; n = n(1:end - 1); duty = 20; s = square(2*pi*fc*n,duty); s(find(s<0)) = 0; m = sin(2*pi*fm*n); period_samp = length(n)/fc; ind = [1:period_samp:length(n)]; on_samp = ceil(period_samp * duty/100); pam=zeros(1,length(n)); for i = 1 : length(ind) pam(ind(i):ind(i) + on_samp) = m(ind(i)); end subplot(2,2,1);plot(n,s);ylim([ ]); title('impulse train') xlabel('time'); subplot(2,2,2);plot(n,m);ylim([ ]); title('mesage signal') xlabel('time'); subplot(2,2,3);plot(n,pam);ylim([ ]); title('modulated signal'); xlabel('time'); dt=s.*pam; filter=fir1(200,fm/fs,'low'); demod_signal=conv(filter,dt); t1=linspace(0,1,length(demod_signal)); subplot(2,2,4) plot(t1,demod_signal); title('demodulated signal'); xlabel('timeperiod');

7 Output: Conclusion: In the non-alias the sinusoidal wave is expected, and the stem is our output. We can see that if we reconstruct the non alias using the stems, we can get the sinusoidal wave back. But in case of alias the stem are so distorted that original sinusoidal wave cannot be reconstructed. Title: Pulse width modulation. (PWM SAWTOOTH) AIM Write a Program to Generate a PWM wave, find it s Sawtooth representation, and find it s Message Signal. Apparatus Required: Matlab to be installed in the computer or in the laptop.

8 Theory: In case of Pam amplitude of carrier pulse is varying with the amplitude of message signal, in this case the width of the carrier pulse will be varying with the instantaneous amplitude of message signal. Pulse-width modulation (PWM), or pulse-duration modulation (PDM), is a modulation technique used to encode a message into a pulsing signal. Although this modulation technique can be used to encode information for transmission, its main use is to allow the control of the power supplied to electrical devices, especially to inertial loads such as motors. In addition, PWM is one of the two principal algorithms used in photovoltaic solar battery chargers,the other being maximum power point tracking. As the amplitude of message is getting larger, the width of the carrier pulse will increase, and in accordance with the message signal, as the amplitude gets lower, the width of the carrier will also decrease. We have used saw-tooth signal as the carrier, so the amplitude of message should be preferably less than the carrier signal. The sawtooth wave (or saw wave) is a kind of non-sinusoidal waveform. It is so named based on its resemblance to the teeth of a plain-toothed saw with a zero rake angle. The convention is that a sawtooth wave ramps upward and then sharply drops. However, in a "reverse (or inverse) sawtooth wave", the wave ramps downward and then sharply rises. It can also be considered the extreme case of an asymmetric triangle wave. Applications: Sawtooth waves are known for their use in music. The sawtooth and square waves are among the most common waveforms used to create sounds with subtractive analog and virtual analog music synthesizers. Sawtooth waves are used in switched-mode power supplies. In the regulator chip the feedback signal from the output is continuously compared to a high frequency sawtooth to generate a new duty cycle PWM signal on the output of the comparator. The main advantage of PWM is that power loss in the switching devices is very low. When a switch is off there is practically no current, and when it is on and power is being transferred to the load, there is almost no voltage drop across the switch. Power loss, being the product of voltage and current, is thus in both cases close to zero. PWM also works well with digital controls, which, because of their on/off nature, can easily set the needed duty cycle. Code:

9 clc clear all; close all; F2=input('Message signal'); F1=input('carrier signal'); A=5; t=0:0.001:1; c=a.*sawtooth(2*pi*f1*t);%carrier sawtooth subplot(3,1,1); plot(t,c); xlabel('time'); title('carrier sawtooth wave'); ; m=0.75*a.*sin(2*pi*f2*t);%message amplitude must be less than sawtooth carrier subplot(3,1,2); plot(t,m); xlabel('time'); title('message signal'); ; n=length(c);%length of carrier sawtooth is sorted to 'n' for i =1:n%comparing message and sawtooth amplitudes if(m(i)>=c(i)) pwm(i)=1; else pwm(i) =0; end end subplot(3,1,3); plot(t,pwm); xlabel('time'); title('plot of pwm'); axis([ ]);%x-axis varies from 0 to 1 & y axis from 0 to 2 ; Output:

10 Conclusion: The main advantage of PWM is that power loss in the switching devices is very low. The amplitude of message should be preferably less than the carrier signal. PWM also works well with digital controls, which, because of their on/off nature, can easily set the needed duty cycle. The PWM switching frequency has to be much higher than what would affect the load (the device that uses the power), which is to say that the resultant waveform perceived by the load must be as smooth as possible

Department of Electronics & Communication Engineering LAB MANUAL

Department of Electronics & Communication Engineering LAB MANUAL SUBJECT: DIGITAL COMMUNICATION [06BEC201] B.Tech III Year VI Semester (Branch: ECE) BHAGWANT UNIVERSITY SIKAR ROAD, AJMER DIGITAL COMMUNICATION