close all
clear
clc

S2=0;
S1=1;
msg=randi([S2 S1],1,1e6); %generating random binary sequence
SNR=0:2:30;
threshold=5*sqrt(1/10);

%Transmitter Side
transmitted_signal=reshape(repmat(msg,10,1),1,[]).*sqrt(1/10);  %reapeat matrix m 10 times then reshaping it to 1*10^7 vector
                                                                                                          %replacing each bit with it's waveform 1 turns to ten (1/sqrt(10)) and 0 turns to ten zeros
Ptx = mean(msg.^2) % power of transmitted sequence

[BER_MF,BER_correlator] = calcChannReciev(SNR,transmitted_signal,threshold,msg)

%%% plots
semilogy(SNR,BER_MF)  %Plot the BER curve against SNR
xlim([0 30])
title('BER Of Matched Filter VS SNR');
xlabel('SNR from 0dB to 30dB');
ylabel('BER');

figure
semilogy(SNR,BER_correlator)  %Plot the BER curve against SNR
xlim([0 30])
title('BER Of Correlator VS SNR');
xlabel('SNR from 0dB to 30dB');
ylabel('BER');
figure
%%  comparing with expermint 1
x=msg;
 SNR = 0:2:30;
BER_simple = applyNoise(SNR,x)
semilogy(SNR,[BER_simple(1:16)'  BER_MF'])%Plot the BER curve against SNR
 legend('Simple detector','Matched filter and Correlator')
xlim([0 30])
title('Comparison between Matched filter and simple detector(BER VS SNR) ');
xlabel('SNR from 0dB to 30dB');
ylabel('BER');

function [BER_MF,BER_correlator] = calcChannReciev(SNR,transmitted_signal,threshold,msg)

    for i=1:length(SNR)%calculating channel and reciever side for every snr from 0 to 30 dB with 2 dB steps.

        %AWGN channel effect
        received_signal=awgn(transmitted_signal,SNR(i),'measured'); %adding AWGN noise

        %% Reciever Side

        received_signal=reshape(received_signal,10,[]); %converting the received signal vector into a matrix of 10*10^6 to reduce calculations
        % matched filter
        Hmf=ones(10,1);  %Hmf =c.s1  assuming c=1

        %convoluting received signal with matched filter 10 sample by 10 sample but
        %getting the non-padding zero convoluted only (middle sample).
        afterMF=conv2(received_signal,Hmf,'valid');
        Decision_of_MF=afterMF>=threshold;%decision for MF circuit

        % correlator filter
        g=ones(10,1); %g=s1
        %multiplying received signal with g(n) and summation for every 10 bits
        aftercorrelator=(received_signal'*g)';
        %decision for correlator circuit
        Decision_of_correlator=aftercorrelator>=threshold;


        % counting number of errors and BER for every SNR

        % calculating No error bits and BER for matched filter
        [MF_errors,BER_MF(i)]=biterr(Decision_of_MF,msg);

        %calculating No error bits and BER for correlator
        [correlator_errors,BER_correlator(i)]=biterr(Decision_of_correlator,msg);

    end
end

function BER_simple = applyNoise(SNR,x)

    for i=1:length(SNR)
        Rx_sequence=awgn( x, SNR(i),'measured' );%Apply noise to the signal

           Rx_new=Rx_sequence>0.5;%Decide whether the Rx_sequence is 1 or 0 by comparing the samples with threshold=1/2
           [simple_errors,BER_simple(i)] = biterr(x,Rx_new);%Compare the original bits with the detected bits and calculate number of errors and the ratio
       end

end