m = 3; % number of LSRs 
N = 2^m-1; %processing gain %processing gain 
maxusers = floor(2*N); % max number of users 
noisevar = 1; 
SNR_dB = 12; % SNR in dB 
SNR = 10^(SNR_dB/10); 
totalbits = 10000; 
overhead = .05; %ratio of training bits to total transmitted number of bits. 
trainbits = totalbits*overhead; % Choosing number of training bits 
for K=1:maxusers 
    A = eye(maxusers)*sqrt(10^(SNR_dB/10)); % Amplitude of each User 
    M = zeros(N,K); % initilizing the weight matrix 
    S =signature_matrix(m,K); %generate signature matrix.
for num_bits=1:totalbits 
  b(:,num_bits) = sign(normrnd(zeros(K,1),1)); %generate random bit values for each user 
        b_frame = b(:,num_bits); %bits of users in num_bits'th frame duration 
        n = normrnd(0,sqrt(noisevar),N,1); %Assume zero mean AWGN 
        y_noisefree = S*A*b_frame; %generate received vector (after demodulation) 
        y = y_noisefree+n; %add noise to received signal 
        if num_bits<=trainbits %training mode for adaptive MMSE 
            [b_AMMSE(:,num_bits), M, mse(num_bits)] = 
MUD_AMMSE(y,M,b_frame,num_bits); 
        else %detection mode for adaptive MMSE 
            [b_AMMSE(:,num_bits), M, temp] = MUD_AMMSE(y,M); 
            mse(num_bits) = (temp-b_frame)'*(temp-b_frame); %calculate actual squared 
%error 
        end
        b_MMSE(:,num_bits) = MUD_MMSE(y,S,A,noisevar); %Multiuser Minimum 
%Mean Square Error Detection 
        b_MF(:,num_bits) = MUD_MF(y,S); %Single User Matched Filter Detection 
        b_Dec(:,num_bits) = MUD_Dec(y,S); %Multiuser Decorrelator 
    end 
    %Find all the errors made 
    e_MF = b-b_MF; 
    e_Dec = b-b_Dec; 
    e_MMSE = b-b_MMSE; 
    e_AMMSE = b(:,trainbits+1:totalbits)-b_AMMSE(:,trainbits+1:totalbits); 
    %Determine BER's 
    Pe_MF(K) = length(find(e_MF))/(K*totalbits); 
    Pe_Dec(K) = length(find(e_Dec))/(K*totalbits); 
    Pe_MMSE(K) = length(find(e_MMSE))/(K*totalbits); 
    Pe_AMMSE(K) = length(find(e_AMMSE))/(K*(totalbits-trainbits)); 
    clear b b_frame n y_noisefree b_MMSE b_MF b_Dec b_AMMSE  
    K %print out where the iteration is for control purposes 
end
%Plot the BER 
K=1:maxusers; 
semilogy(K,Pe_MF,K,Pe_Dec,K,Pe_MMSE,K,Pe_AMMSE) 
legend('MF','Dec','MMSE','AMMSE'); 
title('Probability of Error'); 
xlabel(['Number of users, K for N = ',num2str(N)]); 
ylabel('BER'); 
beep %signal end of simulation