suzuki_type_ii.m

一些非常有用的MATLAB源码,对于提高编程水平和学习通信理论知识还有帮助.

%--------------------------------------------------------------------
% Suzuki_Type_II.m ------------------------------------------------------
%
% Program for the simulation of deterministic extended Suzuki 
% processes of Type II (see Fig. 6.23).
%
% Used m-files: parameter_Jakes.m, parameter_Gauss.m, Mu_i_t.m
%--------------------------------------------------------------------
% eta_t=Suzuki_Type_II(N_1,N_3,sigma_0_2,kappa_0,theta_0,f_max,...
%                  sigma_3,m_3,rho,theta_rho,f_c,T_s,T_sim,PLOT)
%--------------------------------------------------------------------
% Explanation of the input parameters:
%
% N_1, N_3: number of harmonic functions of the real deterministic
%           Gaussian processes nu_0(t) and nu_3(t), respectively
% sigma_0_2: average power of the real deterministic Gaussian 
%            process mu_0(t)  (for kappa_0=1) 
% kappa_0: frequency ratio f_min/f_max (0<=kappa_0<=1)
% theta_0: phase shift between mu_1_n(t) and mu_2_n(t)
% f_max: maximum Doppler frequency
% sigma_3: square root of the average power of the real deterministic 
%          Gaussian process nu_3(t)
% m_3: average value of the real deterministic Gaussian 
%      process mu_3(t)
% rho: amplitude of the LOS component m(t)
% theta_rho: phase of the LOS component m(t)
% f_c: 3-dB-cut-off frequency
% T_s: sampling interval
% T_sim: duration of the simulation
% PLOT: plot of the deterministic extended Suzuki process eta(t) of 
%       Type II, if PLOT==1 

function eta_t=Suzuki_Type_II(N_1,N_3,sigma_0_2,kappa_0,theta_0,...
                            f_max,sigma_3,m_3,rho,theta_rho,f_c,...
                            T_s,T_sim,PLOT)
if nargin==13,
   PLOT=0;
end

N_1_s=ceil(N_1/(2/pi*asin(kappa_0)));
[f1,c1,th1]=parameter_Jakes('es_j',N_1_s,sigma_0_2,f_max,'rand',0);
f1 =f1(1:N_1);
c1 =c1(1:N_1);
th1=th1(1:N_1);

[f3,c3,th3]=parameter_Gauss('es_g',N_3,1,f_max,f_c,'rand',0);
gaMma=(2*pi*f_c/sqrt(2*log(2)))^2;
f3(N_3)=sqrt(gaMma*N_3/(2*pi)^2-sum(f3(1:N_3-1).^2));

N=ceil(T_sim/T_s);
t=(0:N-1)*T_s;

xi_t=abs(Mu_i_t(c1,f1,th1,T_s,T_sim)+rho*cos(theta_rho)+...
         j*(Mu_i_t(c1,f1,th1-theta_0,T_s,T_sim)+...
            rho*sin(theta_rho) ) );

lambda_t=exp(Mu_i_t(c3,f3,th3,T_s,T_sim)*sigma_3+m_3);

eta_t=xi_t.*lambda_t;


if PLOT==1,
   plot(t,20*log10(eta_t),'b-')
   xlabel('t (s)')
   ylabel('20 log eta(t)')
end