mmse_pic.m

这是一个vblast程序

function LLR_value=MMSE_PIC(rec_sig,channel_matrix,noise_var,mapping,aprior_det)
[R_Antenna,T_Antenna,sig_length]=size(channel_matrix);
M=length(mapping);
K=log2(M);
%关于先验信息
aprior_det=reshape(aprior_det,K*T_Antenna,sig_length);
Prob_0_aprior=1./(1+exp(aprior_det));
Prob_1_aprior=exp(aprior_det)./(1+exp(aprior_det));
%%%%%%%%
LLR_value=zeros(sig_length,T_Antenna*K);   %比特级似然值
for i1=1:sig_length
    single_ch_m=channel_matrix(:,:,i1);
    single_sig=rec_sig(:,i1);
    %%%%%%%%% 比特级先验信息 %%%%%%%%%%%%%%%
    single_0_aprior=Prob_0_aprior(:,i1);
    single_1_aprior=Prob_1_aprior(:,i1);
    single_0_aprior=reshape(single_0_aprior,T_Antenna,K);
    single_1_aprior=reshape(single_1_aprior,T_Antenna,K);
    %%%%%%%%% 计算符号级先验信息 %%%%%%%%%%%%%
    single_symbol_aprior=zeros(T_Antenna,M);
    temp=[0:M-1];
    bit_map=de2bi(temp,K,'left-msb');
    for i2=1:M
        Index_0=find(bit_map(i2,:)==0);
        Index_1=find(bit_map(i2,:)==1);  
        single_symbol_aprior(:,i2)=prod(single_0_aprior(:,Index_0),2).*prod(single_1_aprior(:,Index_1),2);
    end;
    sum_single_symbol_aprior=sum(single_symbol_aprior,2);  % 归一值
    sum_matrix=repmat(sum_single_symbol_aprior,1,M);
    single_symbol_aprior=single_symbol_aprior./sum_matrix; % 归一化
    %%%%%%%%%%% 计算符号级先验信息的期望值 %%%%%%%%%%%%%%%%%
    E_symbol_aprior=single_symbol_aprior*mapping.';
    %%%%%%%%%%%%%%%% 逐层检测 %%%%%%%%%%%%%%%%%%%
    soft_value_vector=zeros(T_Antenna,1);
    noise_var_change_vector=zeros(T_Antenna,1);
    for i2=1:T_Antenna
        deleted_ch_m=single_ch_m;
        deleted_ch_m(:,i2)=[];
        deleted_E_aprior=E_symbol_aprior;
        deleted_E_aprior(i2)=[];
        deleted_interference=deleted_ch_m*deleted_E_aprior;
        deleted_sig=single_sig-deleted_interference;
        %%%%%%%% 计算权重 %%%%%%%%%%%%%%%
        P_Matrix=single_ch_m(:,i2)*single_ch_m(:,i2)';
        temp_Matrix=diag(diag(deleted_E_aprior*deleted_E_aprior'));
        Q_Matrix=deleted_ch_m*(eye(T_Antenna-1)-temp_Matrix)*deleted_ch_m';
        MMSE_weight_vector=inv(P_Matrix+Q_Matrix+noise_var*eye(R_Antenna))*single_ch_m(:,i2);
        soft_value_vector(i2)=MMSE_weight_vector'*deleted_sig;
        noise_var_change_vector(i2)=sum(abs(MMSE_weight_vector).^2)*noise_var;
    end;
    %%%%%%%%%%%%%%%%%% 计算比特级似然值 %%%%%%%%%%%%%%%%%%%%%%%%%
    soft_value_Matrix=repmat(soft_value_vector,1,M/2);   
    mapping_Matrix=repmat(mapping,T_Antenna,1);
    noise_var_change_Matrix=repmat(noise_var_change_vector,1,M/2);
    for i3=1:K
        Index_bit_1=find(bit_map(:,i3)==1);
        Index_bit_0=find(bit_map(:,i3)==0);
        Prob_1=-abs(soft_value_Matrix-mapping_Matrix(:,Index_bit_1)).^2./noise_var_change_Matrix;
        Prob_0=-abs(soft_value_Matrix-mapping_Matrix(:,Index_bit_0)).^2./noise_var_change_Matrix;   
        %判断语句是为了防止高信噪比下出现溢出的情况
        Prob_1(find(Prob_1<-1e300))=-1e300;
        Prob_0(find(Prob_0<-1e300))=-1e300;
        single_LLR_value(:,i3)=max(Prob_1,[],2)-max(Prob_0,[],2);    % 采用了log(exp(x)+exp(y))=max(x,y)的近似公式，有效的避免了计算溢出。
    end;    
    LLR_value(i1,:)=single_LLR_value(:)';
end;
LLR_value=LLR_value.';
LLR_value=LLR_value(:).';
%此步即为了控制似然值的范围
for i1=1:sig_length*T_Antenna*K 
    if LLR_value(1,i1)>10
       LLR_value(1,i1)=10;
    end;
    if LLR_value(1,i1)<-10
       LLR_value(1,i1)=-10;
    end;   
end;