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Ber V/S SNR Plot For BPSK and QPSK

This Matlab code simulates the bit error rate (BER) of binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulation schemes over an additive white Gaussian noise (AWGN) channel. It generates binary data, modulates it using BPSK and QPSK, adds AWGN noise, and performs hard decision decoding to calculate the BER for each modulation scheme over a range of signal-to-noise ratio (SNR) values. The simulated BER values are plotted along with theoretical BER curves calculated using the complementary error function to verify the simulation results.

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abhijeetsahu21119907617
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599 views3 pages

Ber V/S SNR Plot For BPSK and QPSK

This Matlab code simulates the bit error rate (BER) of binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulation schemes over an additive white Gaussian noise (AWGN) channel. It generates binary data, modulates it using BPSK and QPSK, adds AWGN noise, and performs hard decision decoding to calculate the BER for each modulation scheme over a range of signal-to-noise ratio (SNR) values. The simulated BER values are plotted along with theoretical BER curves calculated using the complementary error function to verify the simulation results.

Uploaded by

abhijeetsahu21119907617
Copyright
© Attribution Non-Commercial (BY-NC)
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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BER V/S SNR PLOT FOR BPSK AND QPSK

Matlab code

%This program simulates BER of BPSK and QPSK in AWGN channel%

clear all; close all; clc;

num_bit=10000; %Signal length

max_run=10; %Maximum number of iterations for a single SNR

Eb=1; %signal power

SNRdB=0:1:20; %Signal to Noise Ratio (in dB)

SNR=10.^(SNRdB/10);

for count=1:length(SNR) %Beginning of loop for different SNR

totalError=0;

totalError1=0;

No=Eb/SNR(count); %Calculate noise power from SNR

for run_time=1:max_run %Beginning of loop for different runs

Error=0;
Error1=0;

data=randint(1,num_bit); %Generate binary data source

%------Baseband BPSK modulation------

s=2*data-1;

%------Baseband QPSK modulation-------

data1=reshape(data,num_bit/2,2);

data1=2*data1-1;

s1 = (data1(:,1) + j*data1(:,2))/sqrt(2);

N=sqrt(No/2)*[randn(1,num_bit)+j*randn(1,num_bit)]; %Generate WGN for BPSK

N1=sqrt(No/2)*[randn(num_bit/2,1)+j*randn(num_bit/2,1)]; %Generate WGN for QPSK

Y=s+N; %Received Signal

Y1=s1+N1;

Y=real(Y);

%Decision device taking hard decision and deciding error

for k=1:num_bit

if ((Y(k)>0 && data(k)==0)||(Y(k)<0 && data(k)==1))

Error=Error+1;

end

end

Error=Error/num_bit; %Calculate error/bit

totalError=totalError+Error; %Calculate total error/bit for different runs

%-----decision device for QPSk------

for k=1:num_bit/2

if((data1(k,1)==0 && real(Y1(k))>0)||(data1(k,2)==0 && imag(Y1(k))>0)||(data1(k,1)==1 &&


real(Y1(k))<0)||(data1(k,2)==1 && imag(Y1(k))<0))

Error1=Error1+1;

end
end

Error1=2*Error1/num_bit;

totalError1=totalError1+Error1;

end %Termination of loop for different runs

avgError1=totalError1/max_run;

BER_sim1(count)=avgError1;

avgError=totalError/max_run; %calculate average error over total no of runs

BER_sim(count)=avgError; %Calculate BER for a particular SNR

end %Termination of loop for different SNR

BER_th1=.5*erfc(sqrt(SNR/2));

BER_th=.5*erfc(sqrt(SNR)); %Calculate analytical BER

semilogy(SNRdB,BER_th1,'g',SNRdB,BER_sim1,'g*',SNRdB,BER_th,'k',SNRdB,BER_sim,'k*');

legend('Theoretical','Simulation',3);

axis([min(SNRdB) max(SNRdB) 10^(-5) 1]);

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