sc_turbodd_pic.m

B3g_phase2_C语言_Matlab程序及说明

            
            for sn=0:Slot_number-1
                R=Rm(:,sn*Slot_length+(1:Slot_length));
                
                %    Receiver: Channel estimation 
                Index_R=Gaurd_length;Fades=zeros(Antenna_number,Path_number*(Subslot_number+1));Index_Fades=0;
                for kk=1:Subslot_number+1
                    Tmp_RP=R(:,Index_R+(1:Pilot_length));
                    Tmp_Fades=Tmp_RP*Pilot_matrix'/Pilot_length;
                    Fades(:,Index_Fades+(1:Path_number))=Tmp_Fades;
                    Index_R=Index_R+Subslot_length;
                    Index_Fades=Index_Fades+Path_number;
                end
                
                for p=1:Path_number
                    tmp_Fades=Fades(:,p:Path_number:end);
                    for na=1:Antenna_number
                        [Coefficients,Structure]=polyfit(0:Subslot_number,tmp_Fades(na,:),3);
                        [tmp_FadesP(na,:),delta]=polyval(Coefficients,0:0.5:Subslot_number,Structure);
                    end
                    Fades(:,p:Path_number:length(Fades))=tmp_FadesP(:,1:2:end);
                    FadesI(:,p:Path_number:length(Fades)-Path_number)=tmp_FadesP(:,2:2:end);
                end
                
                Index_R=Gaurd_length;Index_Fades=0;
                for kk=1:Subslot_number+1
                    Tmp_Fades=Fades(:,Index_Fades+(1:Path_number));
                    Tmp_Noise = R(:,Index_R+(1:Pilot_length))-Tmp_Fades(:,1:Path_number)*Pilot_matrix;
                    Nv(kk)=sum(sum(abs(Tmp_Noise.*Tmp_Noise)))/Pilot_length/Antenna_number;                                    % Estimate of noise variance 
                    Index_R=Index_R+Subslot_length;
                    Index_Fades=Index_Fades+Path_number;
                end
                Noise_var(sn+1)=sum(Nv)/(Subslot_number+1);
                %    Receiver: Equalization in DFT domain
                Index_R=Pilot_length; Index_Fades=0;R_EQ=[];
                for kk=0:Subslot_number-1
                    Tmp_Fades=(FadesI(:,Index_Fades+(1:Path_number)));
                    RM=R(:,Index_R+(1:Subslot_length)); 
                    
                    RMC((sn*Subslot_number+kk)*Subslot_length+(1:Subslot_length))=sum(cyc_cov(RM,Tmp_Fades),1);
                    
                    h_half((sn*Subslot_number+kk)*Path_number+(1:Path_number))=sum(self_cov(Tmp_Fades),1);
                    
                    Index_Fades=Index_Fades+Path_number;
                    Index_R=Index_R+Subslot_length;
                end
            end   
            
            for n=1:nIterDD            
                for sn=0:Slot_number-1 
                    Noise_variance=Noise_var(sn+1);
                    for kk=0:Subslot_number-1
                        
                        Tmp_RMC=RMC((sn*Subslot_number+kk)*Subslot_length+(1:Subslot_length));
                        Tmp_h_half=h_half((sn*Subslot_number+kk)*Path_number+(1:Path_number));                        
                        Tmp_h=[conj(Tmp_h_half(end:-1:2)) 0 Tmp_h_half(2:end)];
                       
                        if n==1
                            
                            x_rake=Tmp_RMC(Gaurd_length+(1:SubslotData_length));
                            Tmp_R_EQ=x_rake.*conj(PN(kk*SubslotData_length+(1:SubslotData_length)));
                            rou=Tmp_h_half(1);
                            x_sigma=ones(1,SubslotData_length)*(Noise_variance*rou+abs(Tmp_h*Tmp_h'));
                            for nn=1:4
                                [x_symbol,x_variance] =Symbol_Decision(Tmp_R_EQ,rou,x_sigma);
                                
                                x_mean=[Gaurd_Pilot(Pilot_length+(Gaurd_length-Path_number+2:Gaurd_length)) x_symbol.*PN(kk*SubslotData_length+(1:SubslotData_length)) Gaurd_Pilot(1:Pilot_length)];
                                x_variance=[zeros(1,Path_number-1) x_variance zeros(1,Pilot_length)];
                                
                                [x_intf, x_sigma]=Intf_Sigma(x_mean,x_variance,Tmp_h,SubslotData_length);
                                
                                Tmp_R_EQ=(x_rake-x_intf).*conj(PN(kk*SubslotData_length+(1:SubslotData_length)));
                                
                                x_sigma=Noise_variance*rou+x_sigma;
                            end
                            LLR_D = Soft_Demod(Tmp_R_EQ, rou,x_sigma ,zeros(4,SubslotData_length), SubslotData_length);
%                             LLR_D=zeros(1,4*SubslotData_length);
%                             for nn=1:4
%                                 
%                                 LLR_P=reshape(LLR_D,4,SubslotData_length);
%                                 [x_mean0, x_variance]=Mean_Var(LLR_P);
%                                 x_mean=[Gaurd_Pilot(Pilot_length+(Gaurd_length-Path_number+2:Gaurd_length)) x_mean0 Gaurd_Pilot(1:Pilot_length)];
%                                 x_variance=[zeros(1,Path_number-1) x_variance zeros(1,Pilot_length)];
%                                 rou =Tmp_h_half(1);
%                                 [x_intf, x_sigma]=Intf_Sigma(x_mean,x_variance,Tmp_h,SubslotData_length);
%                                 x_rake=Tmp_RMC(Gaurd_length+(1:SubslotData_length));
%                                 Tmp_R_EQ=x_rake-x_intf;
%                                 x_sigma=Noise_variance*rou+x_sigma;
%                                 LLR_D = Soft_Demod(Tmp_R_EQ, rou,x_sigma ,LLR_P, SubslotData_length);
%                             end
                            
                        else
                            LLR_P=reshape(LLR_DI((sn*Subslot_number+kk)*SubslotData_length*4+(1:SubslotData_length*4)),4,SubslotData_length); 
                            
                            [x_mean0, x_variance]=Mean_Var(LLR_P);
                            
                            x_mean=[Gaurd_Pilot(Pilot_length+(Gaurd_length-Path_number+2:Gaurd_length)) x_mean0.*PN(kk*SubslotData_length+(1:SubslotData_length)) Gaurd_Pilot(1:Pilot_length)];
                            x_variance=[zeros(1,Path_number-1) x_variance zeros(1,Pilot_length)];
                            rou =Tmp_h_half(1);
                            
                            [x_intf, x_sigma]=Intf_Sigma(x_mean,x_variance,Tmp_h,SubslotData_length);
                            
                            x_rake=Tmp_RMC(Gaurd_length+(1:SubslotData_length));
                            %                             x_rec=x_intf+rou*x_mean0;
                            %                             alpha=abs((x_rake*x_rec')/(x_rake*x_rake'));
                            alpha=1;
                            Tmp_R_EQ=(x_rake-alpha*x_intf).*conj(PN(kk*SubslotData_length+(1:SubslotData_length)));
                            x_sigma=Noise_variance*rou+alpha^2*x_sigma;
                            LLR_D = Soft_Demod(Tmp_R_EQ, rou,x_sigma,LLR_P, SubslotData_length);
                            
                        end
                        
                        [Dem_signal((sn*Subslot_number+kk)*SubslotData_length*4+(1:SubslotData_length*4))]=LLR_D;
                    end
                end
                    
                    Dem_signal(Outer_intl_table)=Dem_signal;
                    Dem_signal_p=vec2mat(Dem_signal,Packet_number)';
                    
                    for np=1:Packet_number
                        
                        [decoded, LLR_all(np,:)] = TuDecLogMapNew(Dem_signal_p(np,:), puncture, nIter, Inner_intl_table, 1, 1, poly_g1, poly_g2);
                        errors(n)=errors(n)+sum(abs(decoded(1:Packet_msg_L)-msg(np,1:Packet_msg_L)));
                        
                    end
                    
                    LLR_DI=reshape(LLR_all,1,Packet_code_L*Packet_number);
                    LLR_DI=LLR_DI(Outer_intl_table);
                end
                
                errors
                ber(:,SNR-SNR1+1)=errors'/k/Packet_msg_L/Packet_number
                
                
                if (errors(nIterDD)>300 & k>3) 
                    break;
                end
            end
            
            if ber(1,SNR-SNR1+1)<1.0*10^(-6)
                break;
            end
            
        end 
        save ber_16QAM200v_1 ber
    end
    semilogy(SNR1:SNR2,ber(:,1:SNR2-SNR1+1)')
    grid
    xlabel('SNR of Received Signal(in dB)')
    ylabel('Bit Error Rate')
    pause(0.2)
    save ber_16QAM200v_1 ber