Advanced Communications Matlab-1
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Transcript of Advanced Communications Matlab-1
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Advance Communications Lab Manual 1
M.Tech DECS II Sem Dept. of ECE
1. Measurement of Bit Error Rate using Binary Data
n=23;
k=12;
dmin=7;
ebno=1:10;
ber_block=bercoding(ebno,'block','hard',n,k,dmin);
berfit(ebno,ber_block)
ylabel('bit error probability');
title('ber vs eb/no');
RESULT:
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Advance Communications Lab Manual 2
M.Tech DECS II Sem Dept. of ECE
2. Verification of minimum distance in Hamming Code
m=3;
n=2^m-1;
k=4;
msg=[0 0 0 0; 0 0 0 1; 0 0 1 0; 0 0 1 1; 0 1 0 0; 0 1 0 1; 0 1 1 0; 0 1 1 1];
code1 =encode(msg,n,k,'hamming/binary');
code2 =num2str(code1);
code= bin2dec(code2);
number1= [];
for i=1:8
for j=i+1:8
[number]=biterr(code(i),code(j),7);
number1=[number1 number];
end
end
minidistance = min(number1)
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Advance Communications Lab Manual 3
M.Tech DECS II Sem Dept. of ECE
3. Determination of output of convolutional Encoder for a given sequence
%convolution encoder;input=1bit output=2bits with 3 memory elements,code
%rate=1/2.
function[encoded_sequence]=convlenc(message)
message=[ 1 0 1 0 1 1 1 0 0 0 1 1 0 1 1 0 0 ];
enco_mem=[ 0 0 0]; %no.of memory elments=3
encoded_sequence=zeros(1,(length(message))*2);
enco_mem(1,3)=enco_mem(1,2);
enco_mem(1,2)=enco_mem(1,1);
enco_mem(1,1)=message(1,1);
temp=xor(enco_mem(1),enco_mem(2));
O1=xor(temp,enco_mem(3));%gener.polynomial=111
O2=xor(enco_mem(1),enco_mem(3));%gener.polynomial=101
encoded_sequence(1,1)=O1;
encoded_sequence(1,2)=O2;
msg_len=length(message);
c=3;
for i=2:msg_len
enco_mem(1,3)=enco_mem(1,2);
enco_mem(1,2)=enco_mem(1,1);
if(i
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Advance Communications Lab Manual 4
M.Tech DECS II Sem Dept. of ECE
RESULT:
ans =
Columns 1 through 17
1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 1
Columns 18 through 34
1 0 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1
ans =
Columns 1 through 17
1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 1
Columns 18 through 34
1 0 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1
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Advance Communications Lab Manual 5
M.Tech DECS II Sem Dept. of ECE
4. Determination of output of convolutional Decoder for a given sequence
tb=2;
t=poly2trellis([3],[7,5]);
encoded_sequence=[ 1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 1 1 0 1 1 0 1 0 1 1 0 1 1 1 ];
decoded=vitdec(encoded_sequence,t,tb,'trunc','hard')
RESULTS:
decoded =
1 0 1 0 1 1 1 0 0 1 0 0 1 1 1
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Advance Communications Lab Manual 6
M.Tech DECS II Sem Dept. of ECE
5. Efficiency of DS Spread Spectrum Technique
%direct sequence spread spectrum
clc
clear all;
%generating the bit pattern with each bit 6 samples long
b=round(rand(1,20));
pattern=[];
for k=1:20
if b(1,k)==0
sig=zeros(1,6);
else
sig=ones(1,6)
end
pattern=[pattern sig];
end
plot(pattern);
axis([-1 130 -0.5 1.5]);
title('\bf\it original bit sequenece');
%generating the psedorandom bit pattern for spreading
spread_sig=round(rand(1,120));
figure,plot(spread_sig);
axis([-1 130 -0.5 1.5]);
title('\bf\it psedorandom bit sequenece');
%xoring the pattern with spread signal
hopped_sig=xor(pattern,spread_sig);
%modulating the hopped signal
dsss_sig=[];
t=[0:100];
fc=0.1;
c1=cos(2*pi*fc*t);
c2=cos(2*pi*fc*t+pi);
for k=1:120
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Advance Communications Lab Manual 7
M.Tech DECS II Sem Dept. of ECE
if hopped_sig(1,k)==0;
dsss_sig=[dsss_sig c1]
else
dsss_sig=[dsss_sig c2]
end
end
figure,plot([1:12120],dsss_sig);
axis([-1 12120 -1.5 1.5]);
title('\bf\ it dss signal');
%plotting the fft of dsss signal
figure,plot([1:12120],abs(fft(dsss_sig)));
RESULT:
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Advance Communications Lab Manual 8
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 9
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 10
M.Tech DECS II Sem Dept. of ECE
6. Simulation of Frequency Hopping (FH) system
clear all;
s=round(rand(1,20));
signal=[];
carrier=[];
t=[0:10000];
fc=.01;
for k=1:20
if s(1,k)==0
sig= -ones(1,10001);
else
sig=ones(1,10001);
end
c=cos(2*pi*fc*t);
carrier=[carrier c];
signal=[signal sig];
end
subplot(2,1,1);
plot(signal);
axis([-1 200050 -1.5 1.5]);
title('/bf/it original bit sequence');
%BPSK modulation of signal
bpsk_sig=signal.*carrier;
subplot(2,1,2);
plot(bpsk_sig);
axis([-1 200050 -1.5 1.5]);
title('/bf/it BPSK modulated signal');
%FFT plot of BPSK modulated signal
figure, plot([1:200020],abs(fft(bpsk_sig)));
title('/bf/it FFT of BPSKmodulated signal');
%preparation of six carrier frequencies
fc1=.01; fc2=.02; fc3=.03;
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Advance Communications Lab Manual 11
M.Tech DECS II Sem Dept. of ECE
fc4=.04; fc5=.05; fc6=.06;
c1=cos(2*pi*fc1*t);c2=cos(2*pi*fc2*t);c3=cos(2*pi*fc3*t);
c4=cos(2*pi*fc4*t);c5=cos(2*pi*fc5*t);c6=cos(2*pi*fc6*t);
%random frequencies hoops to form a spread signal
spread_sig =[];
for n=1:20
c=randint(1,1,[1 6]);
switch(c)
case(1)
spread_sig=[spread_sig c1];
case(2)
spread_sig=[spread_sig c2];
case(3)
spread_sig=[spread_sig c3];
case(4)
spread_sig=[spread_sig c4];
case(5)
spread_sig=[spread_sig c5];
case(6)
spread_sig=[spread_sig c6];
end
end
figure,plot([1:200020],abs(fft(spread_signal)));
freq_hopped_sig=bpsk_sig.*spread_signal;
figure,plot([1:200020],abs(fft(freq_hopped_sig)));
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Advance Communications Lab Manual 12
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 13
M.Tech DECS II Sem Dept. of ECE
7. Histogram of a Image
clc;
clear all;
f=imread('cameraman.tif');
figure,imshow(f);
title('Input Image');
h=imhist(f);
h1=h(1:10:256);
horz=1:10:256;
figure,bar(horz,h1);
figure,plot(horz,h1);
title('Histogram Equalized Image');
Z=adapthisteq(f,'cliplimit',0.9,'distribution','uniform');
imview(Z);
b=imhist(f);
figure,imshow(b);
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Advance Communications Lab Manual 14
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 15
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 16
M.Tech DECS II Sem Dept. of ECE
8. Verification of various Transforms - FT
RGB=imread('peppers.png');
I=rgb2gray(RGB);
J=fft2(I);
k=ifft2(J);
subplot(2,2,1),imshow(RGB);
title('original image');
subplot(2,2,2),imshow(I);
title('gray scale image');
subplot(2,2,3),imshow(J);
title('DFT');
subplot(2,2,4);imshow(k,[0 255]);
title('IDFT');
RESULT:
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Advance Communications Lab Manual 17
M.Tech DECS II Sem Dept. of ECE
9. Verification of various Transforms - DCT
x=imread('lena.png');
subplot(4,1,1);
imshow(x);
title('input image');
%convert rgb to BW image
a=im2bw(x);
subplot(4,1,2);
imshow(a);
title('input BW image')
%convert bw to rgb
b=bw2gray(a);
subplot(4,1,3);
imshow(b);
title('bw to rgb image');
%DCT
d=dct2(a);
subplot(4,1,4);
imshow(d);
title('DCT image');
%Inverse dct
i=idct2(d);
subplot(4,1,5);
h=imshow(i,[0 255]);
title('IDCT image');
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Advance Communications Lab Manual 18
M.Tech DECS II Sem Dept. of ECE
10. Detection techniques using derivative operators - Edge
i=imread('coins.png');
imshow(i);
j=edge(i,'sobel');
figure, imshow(j)
k=edge(i,'prewitt');
figure, imshow(k)
l=edge(i,'robert');
figure, imshow(l)
h=edge(i, 'log');
figure, imshow(h)
RESULT:
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Advance Communications Lab Manual 19
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 20
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 21
M.Tech DECS II Sem Dept. of ECE
Detection techniques using derivative operators - Point
%point detection%
I=imread('circuit.tif');
H=[1 1 1; 1 -8 1; 1 1 1];
B=imfilter(I,H);
subplot(1,2,1),imshow(I),title('Original image');
subplot(1,2,2),imshow(B),title('Point detection');
Detection techniques using derivative operators - Line
f= imread('coins.png');
imshow(f)
g= edge(f,'horizontal');
h= edge(f,'vertical');
figure, imshow(g)
figure, imshow(h)
k=g+h;
figure,imshow(k)
l=g-h;
figure,imshow(l)
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Advance Communications Lab Manual 22
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 23
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 24
M.Tech DECS II Sem Dept. of ECE
11. Implementation of FIR filter
N=60;
R=0.5;
b=firnyquist(N,4,R,0,'nonnegative');
h=firrcos(N,0.25,R,2,'rolloff');
hfvt=fvtool(b,1,h,1);
set(hfvt,'color', [1 1 1]);
legend(hfvt,'FIR NYQUIST DESIGN','FIR RCOS DESIGN');
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Advance Communications Lab Manual 25
M.Tech DECS II Sem Dept. of ECE
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Advance Communications Lab Manual 26
M.Tech DECS II Sem Dept. of ECE
12. Implementation of IIR filter
clc;
N=10; %UNCONSTRAINED NUMERATOR ORDER
M=10; %UNCONSTRAINED DENOMINATOR ORDER
F=[0 0.4 0.5 1]; %FREQUENCY VECTOR
E=F; %FREQUENCY EDGES
A=[1 1 0 0]; %MAGNITUDE VECTOR
W=[1 1 100 100]; %WEIGHT VECTOR
Nc=12; %CONSTRAINED NUMERATOR ORDER
Mc=12; %CONSTRAINED DENOMINATOR ORDER
R=0.92;
[b,a,err,sos,g]=iirlpnorm(N,M,F,E,A,W);
[bc,ac,errc,sosc,gc]=iirlpnormc(Nc,Mc,F,E,A,W,R);
H(1)=dfilt.df1sos(sos,g);
H(2)=dfilt.df1sos(sosc,gc);
[z,p,k]=zpk(H(2)); %FINDS THE POLES AND ZEROS OF CONSTRAINED FILTER
sqrt(real(p).^2+imag(p).^2) %RADII OF ALL POLES
hfvt=fvtool(H);
legend(hfvt,'IIR unconstrained design','IIR constrained design');
set(hfvt,'color',[1 1 1]);