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Islamic University of Gaza Electrical Engineering Department Communication I laboratory Submitted by: Adham Abu-Shamla Mohammed Hajjaj 120063320 120063640 Submitted to: Eng. Mohammed kamel Abu-Foul Amplitude modulation DSB-LC (full AM) 1

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Contents: The objective of this experiment. Quick review about the AM modulation and (DSB-LC) Part 1 code and its comments and results (step by step) Part 2 code and its comment and results Conclusion. 2

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Objective: Understanding AM modulation, Double Side Band-Large Carrier (DSB-LC) “known as Full AM”. Using MATLAB to plot the modulated signal. To simulate coherent demodulator and an envelope detector to obtain the real signal using MATLAB. 3

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Quick review about the AM modulation and (DSB-LC) It’s a type of modulation, that’s used to transmit the signal with high frequency. What is AM modulation FDM(frequency division multiplexing) Hard ware limitation ( λ=c/f),(L (Antenna Hight) =λ/10) Why Modulation

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Type of AM Modulation 1. DSB-SC 2. DSB-LC 3. SSB 4. VSB

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(AM) and (FM) : 6

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Part 1 Use MATLAB to simulate this block (AM block) (f(t)=cos(2π2000t),Ac=4,m=0.25,fc=20Khz) X+ f(t) m S(t)=Ac[1+mf(t)]. cos(2.π.fct) Ac.cos(2.π.fct)

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Part 1 (a) code: the input signal fc=20000; % Carrier frequency ts=1/(10*fc); t=[0:2000]*ts; fs=1/ts; % Sampling frequency m=.25; % Modulation index Ac=4; % DC shift x=cos(2*pi*2000*t); % the original signal figure(1) subplot(211) plot(t,x) title('plot of baseband signal x(t)') xlabel('time (t)') ylabel('x(t)') Carrier freqyancySampling period Sampling frequancy Modulation index µ=mp/ADC shift plot the real signal Comment: In the above code we chose ts =1/(10*fs) to avoid overlapping in signal, then we make Fourier transform to plot the magnitude spectrum.

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Code cont. Xf=fftshift(fft(x)); Xf=Xf/length(Xf); deltax=fs/length(Xf); fx=-fs/2:deltax:fs/2-deltax; subplot(212) plot(fx,abs(Xf)) title('the fourier transform of x(t)') xlabel('frequency (f)') ylabel('X(f)') Fourier Transform of a real signal Plot the magnitude spectrum

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The results (part 1a) Two Sym. pulses on the signal frequency

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Code (part 1b): modulated signal y=(1+m*x)*Ac.*cos(2*pi*fc*t); % (Modulated signal) figure(2) subplot(211) plot(t,y) title('the modulated signal y(t)=(1+m*x)*Ac.*cos(2*pi*fc*t)') xlabel('time (t)') ylabel('y(t)') yf=fftshift(fft(y));

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Code (part 1b): modulated signal cont. yf=yf/length(yf); delta=fs/length(yf); f=-fs/2:delta:fs/2-delta; subplot(212) plot(f,abs(yf)) title('the fourier transform of the modulated signal Y(f)') xlabel('frequency (f)') ylabel('Y(f)') Plot the magnitude spectrum

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The results (part 1b) The same signal shifted at fc and the magnitude divided by 2

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Coherent detector LPH S(t)w(t) ) v(t) cos(2.π.fc.t)

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Code (Part 1c-1) coherent demodulator “before filtering”. w=y.*cos(2*pi*fc*t); % Coherent demodulated signal figure(3) subplot(211) plot(t,w) title('plot of demodulated signal w(t) before LPF') xlabel('time (t)') ylabel('w(t)') wf=fftshift(fft(w));

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Code (Part 1c-1) coherent demodulator “before filtering”. wf=wf/length(wf); delta=fs/length(wf); f=-fs/2:delta:fs/2-delta; subplot(212) plot(f,abs(wf)) title('fourier transform of the demodulated signal W(f)') xlabel('frequency (f)') ylabel('W(f)')

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The results (part 1c-1) The modulated signal shifted at 2*fc and the magnitude divided by 2 There are a signal in 0 as real signal

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Code (Part 1c-2) coherent demodulator “after filtering”. Wp=5000/fs; Ws=20000/fs; Rp=-1; Rs=-100; [N, Wn] = BUTTORD(Wp, Ws, Rp, Rs); % [num,den]=butter(N,Wn); % the lower frequency of the transient region ( must be between 0 and 1 ) The Upper frequency of the transient region ( must be between 0 and 1 ) losses due to rippels Fn. that return the order of the filter and the cutt off frequency Fn. that return the transfer function of the Butterworth filter

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Code (Part 1c-2) coherent demodulator “after filtering”. v=filter(num,den,w); figure(4) subplot(211) plot(t,v) title('the demodulated signal after LPF v(t)') xlabel('time (t)') ylabel('v(t)') Filtering process

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Code (Part 1c-2) coherent demodulator “after filtering”. Vf=fftshift(fft(v)); Vf=Vf/length(Vf); deltav=fs/length(Vf); fv=-fs/2:deltav:fs/2-deltav; subplot(212) plot(fv,abs(Vf)) title('the fourier transform of v(t)') xlabel('frequency (f)') ylabel('V(f)')

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The results (part 1c-2) There are a signal in 0 as real signal only

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Envelope detector

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Code (part 1d) %C=0.1e-6F,R=3.2e2%%% c=0.1e-6; r=3.2e2; RC=r*c; Vc=ones*(1:length(y)); Vc(1)=y(1); for i=2:length(y) if y(i)>=Vc(i-1)

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Code (part 1d) Vc(i)=y(i); else Vc(i)=Vc(i-1).*exp(-ts/RC); end figure(5) plot(t,y,t,Vc) %%%%%%%%%%%%%% %%%%%%%% We can explain this code by the following flow chart

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start Vc(i)=y(i) Vc(1)=y(1) i=2 Y(i)>=Vc(i-1) Vc(i)=Vc(i-1).*exp(-ts/RC); i=length(Y) start YES NO YES NO

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The results (C=0.1e-6F,R=3.2e2)

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If we change R R=3.2e(3) R=3.2e(4)

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Part 2 Repeat part 1 with Ac=1, m = 2 After we make the simulation, the result is the same in part 1, but we saw some difference in the envelope detector. we will show the results of this part and comment the reason

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Result of envelope overlap

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Result of envelope Not as real signal

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Comment in part 2 The reason of part 2 become like this becouse the Ac is not enough to alternate the signal up to zero so envelope detector can’t get the real signal

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Conclusion The experiment is a good simulate for AM signals. We must make sure of the code because any error causes fail in compiling

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