jakes.m

此文件包括jake信道仿真模型的过程程序

%Jakes 模型仿真

clear all;
f_max=30;                        %最大多谱勒频移
M=8;                             %低频振荡器个数
N=4*M+2;                         %入射角度个数
sq=2/sqrt(N);                    
sigma=1;
theta=0;                        %固定相移
count=0;

  for t=0:1.042e-04:1,          
      t1=0.025;
      t2=0.05;
      t3=0.1;
      count=count+1;
      for n=1:M+1,
          if n<=M
              c_i(count,n)=2*sigma*cos(pi*n/M);      %同相分量的幅度增益
              c_q(count,n)=2*sigma*sin(pi*n/M);      %正交分量的幅度增益
              f_i(count,n)=f_max*cos(2*pi*n/N);      %同相分量的多普勒频移
              f_q(count,n)=f_max*cos(2*pi*n/N);      %正交分量的多普勒频移
          else                                       %入射角度为0和180度时的幅度和频移
              c_i(count,n)=sqrt(2)*cos(pi/4);        
              c_q(count,n)=sqrt(2)*sin(pi/4);
              f_i(count,n)=f_max;
              f_q(count,n)=f_max;
          end;
              g_i(count,n)=c_i(count,n)*cos(2*pi*f_i(count,n)*(t-t1)+theta);    %每一个同相分量
              g_q(count,n)=c_q(count,n)*cos(2*pi*f_i(count,n)*(t-t1)+theta);    %每一个正交分量
              g_i2(count,n)=c_i(count,n)*cos(2*pi*f_i(count,n)*(t-t2)+theta);
              g_i3(count,n)=c_i(count,n)*cos(2*pi*f_i(count,n)*(t-t3)+theta);
      end;
      
      tp_i(count)=sq*sum(g_i(count,1:M+1));             %整个同相分量
      tp_q(count)=sq*sum(g_q(count,1:M+1));             %整个正交分量
      tp_i2(count)=sq*sum(g_i2(count,1:M+1));        
      tp_i3(count)=sq*sum(g_i3(count,1:M+1)); 
  end;
  
  [corrx_i,lag_i]=xcorr(tp_i,'coeff');
  [yy,ii]=max(corrx_i);
  [ee,bb]=max(lag_i);
  auto_i=corrx_i(ii:bb);                               %时间为t1的同相分量自相关
  
  [corrx_i2,lag_i2]=xcorr(tp_i2,'coeff');
  [yy2,ii2]=max(corrx_i2);
  [ee2,bb2]=max(lag_i2);
  auto_i2=corrx_i2(ii2:bb2);                           %时间为t2的同相分量自相关
  
  [corrx_i3,lag_i3]=xcorr(tp_i3,'coeff');
  [yy3,ii3]=max(corrx_i3);
  [ee3,bb3]=max(lag_i3);
  auto_i3=corrx_i3(ii3:bb3);                           %时间为t3的同相分量自相关
    
  [corrx_q,lag_q]=xcorr(tp_q,'coeff');
  [yyq,iiq]=max(corrx_q);
  [eeq,bbq]=max(lag_q);
  auto_q=corrx_q(iiq:bbq);                             %正交分量自相关
  
  [corrx_iq,lag_iq]=xcorr(tp_i,tp_q,'coeff');          %同相分量与正交分量互相关
  aa=(bb-2*ii+1:ii-1);
  aa2=(bb2-2*ii2+1:ii2-1);
  aa3=(bb3-2*ii3+1:ii3-1);
  figure(1);
  plot(aa(1:1000)*1.042e-04,auto_i(1:1000),aa2(1:1000)*1.042e-04,auto_i2(1:1000),aa3(1:1000)*1.042e-04,auto_i3(1:1000));
  title('不同时间的同相分量自相关');
  
  figure(2);
  plot(((bb-2*ii+1:ii-1)*1.042e-04),auto_i,((bbq-2*iiq+1:iiq-1)*1.042e-04),auto_q);
  title('同相分量与正交分量自相关');
    
  figure(3);
  plot((mean(lag_iq):max(lag_iq))*1.042e-04,corrx_iq(9597:19193));
  title('同相分量与正交分量互相关');