comparisons of bit error probabilities with increasing number of users.m

随着用户数的增加

m = 3; 
N = 2^m-1; %system processing gain 
maxbits = 20000; 
maxusers = floor(1.5*N); % max number of users 
S_tot = signature_matrix(m,maxusers);%generate signature matrix. 
%S(:,k)=sk normalized to unit energy 
noisevar = 1; 
SNR = 10; %SNR in dB for each user 
for K=1:maxusers % Increasing number of users 
    A = eye(K)*sqrt(10^(SNR/10)); % amplitude (power) of the users 
    S = S_tot(:,1:K); 
    M = zeros(N,K); 
    totalbits = floor(maxbits/K);
    trainbits=0.05*totalbits; 
    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(:,num_bits); %generate received vector (after demodulation) 
        y = awgn(y_noisefree,SNR,'measured'); %add noise to received signal 
         
        % Begin of Adaptive DIC Method 
        w=1; 
        if num_bits<=trainbits % training mode for adaptive DIC 
            [b_ADIC(:,num_bits), w] = MUD_ADIC(y,S,A,w,b_frame,num_bits); 
        else %detection mode for adaptive DIC 
            [b_ADIC(:,num_bits), w] = MUD_ADIC(y,S,A,w); 
        end 
        % End of Adaptive DIC Method 
         
        %  Begin of Adaptive MMSE Method     
        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 
        % End of Adaptive MMSE Method 
         
        b_MF(:,num_bits) = MUD_MF(y,S); %Single User Matched Filter Detection 
        b_PIC(:,num_bits) = MUD_PIC(y,S,A); %Multiuser Optimum Detection 
        b_Dec(:,num_bits) = MUD_Dec(y,S); %Multiuser Decorrelator 
        b_MMSE(:,num_bits) = MUD_MMSE(y,S,A,noisevar);%Multiuser Minimum 
%Mean Square Error Detection 
        b_SIC(:,num_bits) = MUD_SIC(y,S,A); %Multiuser Successive Interference 
%Cancellation 
    end 
     
    e_MF = b-b_MF; % error calculation for MF 
    e_PIC = b-b_PIC; % error calculation for PIC 
    e_Dec = b-b_Dec; % error calculation for Dec 
    e_MMSE = b-b_MMSE; % error calculation for MMSE 
    e_SIC = b-b_SIC; % error calculation for SIC
    e_ADIC = b(:,trainbits+1:totalbits)-b_ADIC(:,trainbits+1:totalbits); % error calculation 
for ADIC 
    e_AMMSE = b(:,trainbits+1:totalbits)-b_AMMSE(:,trainbits+1:totalbits); % error 
%calculation for AMMSE 
     
    Pe_MF(K) = length(find(e_MF))/(K*totalbits); % Probability of error for MF 
    Pe_PIC(K) = length(find(e_PIC))/(K*totalbits); % Probability of error for PIC 
    Pe_Dec(K) = length(find(e_Dec))/(K*totalbits);% Probability of error for Dec 
    Pe_MMSE(K) = length(find(e_MMSE))/(K*totalbits);% Probability of error for 
%MMSE 
    Pe_SIC(K) = length(find(e_SIC))/(K*totalbits);% Probability of error for SIC 
    Pe_ADIC(K) = length(find(e_ADIC))/(K*(totalbits-trainbits));% Probability of error 
%for ADIC 
    Pe_AMMSE(K) = length(find(e_AMMSE))/(K*(totalbits-trainbits));% Probability of 
%error for AMMSE 
     
    K 
    clear b b_MF b_PIC b_Dec b_MMSE b_SIC b_ADIC b_AMMSE n y_noisefree A S 
end
K=1:maxusers; 
semilogy(K,Pe_MF,K,Pe_PIC,K,Pe_Dec,K,Pe_MMSE,K,Pe_SIC,K,Pe_ADIC,K,Pe_AM
MSE) 
legend('MF','PIC','Dec','MMSE','SIC','ADIC','AMMSE'); 
title('Comparison of Bit Error Probabilities'); 
xlabel(['Number of users, SNR=9dB ,K for N = ',num2str(N)]); 
ylabel('Bit error Probability, P_b');