mka_m_series.m

用于产生m序列

%  产生生成矩阵A;
%%%  there is 4095 points of the m series;
clear all;
A=zeros(12,12);
for i=1:11
    A(i,i+1)=1;
end;
    A(12,1)=1; A(12,7)=1;  A(12,9)=1;  A(12,12)=1;
% originate the vector;
  x=zeros(12,1);  x(1)=1;
% makeout the m series;
   y=zeros(1,4095);
for i=1:4095
    y(i)=x(1);
    x=A*x;
    x(12)=mod(x(12),2);
end;
     y;
     for i=1:4095
         if y(i)>=1
            y(i)=1;
        elseif y(i)<=0
               y(i)=-1;
         end;
     end;
         
           Mm=y;   %%%   define a new variable easiely to memory
            %%%%   随机序列产生完毕；
     %%%  计算自相关函数；
     %%%  先计算自身的相关函数，在计算与信道响应卷积后的自身的相关函数；
           
           delay=4095;
           A=zeros(delay,4095);
       for i=1:delay
           y1=zeros(size(y));
           y1(i:4095)=y(1:4095-i+1);
           y1(1:i-1)=y(4095-i+2:4095);
           A(i,:)=y1;
           
       end;
           figure; subplot(211);  %%%%    y'  must be a column vector;
           b1=multiply(A,y');
           plot(b1);   
           title('corelation of itself');
           
         %%%%%%  corelation after   convolution;   
              Hn =[0.8783   -0.5806    0.6537   -0.3223    0.6577   -0.0582   0.2895   -0.2710    0.1278   -0.1508    0.0238   -0.1814   0.2519   -0.0396    0.0423   -0.0152    0.1664   -0.0245   0.1463   -0.0770    0.1304   -0.0148    0.0054   -0.0381    0.0374   -0.0329    0.0313   -0.0253    0.0552  -0.0369   0.0479   -0.0073    0.0305   -0.0138    0.0152   -0.0012  0.0154   -0.0092    0.0177   -0.0161    0.0070   -0.0042  0.0051   -0.0131    0.0059   -0.0041    0.0077   -0.0034   0.0074   -0.0014    0.0025   -0.0056    0.0028   -0.0005   0.0033   -0.0000    0.0022   -0.0032    0.0012   -0.0020   0.0017   -0.0022    0.0004   -0.0011      0          0   ];
              Hn=Hn(1:64);
              y=conv(y,Hn);
             y=y(1:4095);
              delay=4095;
           A=zeros(delay,4095);
       for i=1:delay
           y1=zeros(size(y));
           y1(i:4095)=y(1:4095-i+1);
           y1(1:i-1)=y(4095-i+2:4095);
           A(i,:)=y1;
           
       end;
           hold on;
           subplot(212);  %%%%    y'  must be a column vector;
           b2=multiply(A,y');
           plot(b2);   
           title('corelation of convolution');