Code Matlab

close all

clear all

clc

%%

% Generating and coding data

t_data=randint(9600,1)';

x=1;

si=1; %for BER rows

%%

for d=1:100;

data=t_data(x:x+95);

x=x+96;

k=3;

n=6;

s1=size(data,2);  % Size of input matrix

j=s1/k;

%%

% Convolutionally encoding data 

constlen=7;

codegen = [171 133];    % Polynomial

trellis = poly2trellis(constlen, codegen);

codedata = convenc(data, trellis);

%%

%Interleaving coded data

s2=size(codedata,2);

j=s2/4;

matrix=reshape(codedata,j,4);

intlvddata = matintrlv(matrix',2,2)'; % Interleave.

intlvddata=intlvddata';

%%

% Binary to decimal conversion

dec=bi2de(intlvddata','left-msb');

%%

%16-QAM Modulation

M=16;

y = qammod(dec,M);

 scatterplot(y);

%%

% Pilot insertion

lendata=length(y);

pilt=3+3j;

nofpits=4;

k=1;

for i=(1:13:52)

    pilt_data1(i)=pilt;

    for j=(i+1:i+12);

        pilt_data1(j)=y(k);

        k=k+1;

    end

end

pilt_data1=pilt_data1';   % size of pilt_data =52

pilt_data(1:52)=pilt_data1(1:52);    % upsizing to 64

pilt_data(13:64)=pilt_data1(1:52);   % upsizing to 64

for i=1:52

    pilt_data(i+6)=pilt_data1(i);

end

%%

% IFFT

ifft_sig=ifft(pilt_data',64);

%%

% Adding Cyclic Extension

cext_data=zeros(80,1);

cext_data(1:16)=ifft_sig(49:64);

for i=1:64

    cext_data(i+16)=ifft_sig(i);

end

%%

% Channel

 % SNR

 o=1;

for snr=0:2:50

ofdm_sig=awgn(cext_data,snr,'measured'); % Adding white Gaussian Noise

% figure;

% index=1:80;

% plot(index,cext_data,'b',index,ofdm_sig,'r'); %plot both signals

% legend('Original Signal to be Transmitted','Signal with AWGN');

%%

%                   RECEIVER

%%

%Removing Cyclic Extension

for i=1:64

    rxed_sig(i)=ofdm_sig(i+16);

end

%%

% FFT

ff_sig=fft(rxed_sig,64);

%%

% Pilot Synch%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

for i=1:52

    synched_sig1(i)=ff_sig(i+6);

end

k=1;

for i=(1:13:52)

    for j=(i+1:i+12);

        synched_sig(k)=synched_sig1(j);

        k=k+1;

    end

end

% scatterplot(synched_sig)

%%

% Demodulation

dem_data= qamdemod(synched_sig,16);

%% 

% Decimal to binary conversion

bin=de2bi(dem_data','left-msb');

bin=bin';

%%

% De-Interleaving

deintlvddata = matdeintrlv(bin,2,2); % De-Interleave

deintlvddata=deintlvddata';

deintlvddata=deintlvddata(:)';

%%

%Decoding data

n=6;

k=3;

decodedata =vitdec(deintlvddata,trellis,5,'trunc','hard');  % decoding datausing veterbi decoder

rxed_data=decodedata;

%%

% Calculating BER

rxed_data=rxed_data(:)';

errors=0;

c=xor(data,rxed_data);

errors=nnz(c);

% for i=1:length(data)

%     

%        

%     if rxed_data(i)~=data(i);

%         errors=errors+1;     

%      

%     end

% end

BER(si,o)=errors/length(data);

o=o+1;

 end % SNR loop ends here

 si=si+1;

end % main data loop

%%

% Time averaging for optimum results

for col=1:25;        %%%change if SNR loop Changed

    ber(1,col)=0;  

for row=1:100;

        ber(1,col)=ber(1,col)+BER(row,col);

    end

end

ber=ber./100; 

%%

figure

i=0:2:48;

semilogy(i,ber);

title('BER vs SNR');

ylabel('BER');

xlabel('SNR (dB)');

grid on