coef_gaussian_filter.m

基于watterson信道模型的matlab程序

function h = coef_gaussian_filter(F_2_sigma,Ts,order)

% F_2_sigma:Two Sigma Frequency
% Ts:Sample Time

Fs = 1/Ts;
% K_qual = 1.4;  % Shape Quality Constant KQUAL=1.4 (larger the constant, the better the match)
% N = ceil(K_qual*Fs/F_2_sigma)+1; % FIR Length
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% if(N < 50 | N >150)
%     N = 91;
% end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
N = order;
N_half = (N-1)/2;
n=[0:N-1];
sigma = Fs*sqrt(2)/(2*pi*F_2_sigma);
% Gaussian Filter Impulse Response
mult = N_half;
h = (dnorm(n,mult,sigma)/dnorm(0,0,sigma))/(sqrt(2*pi)*sigma);
K_enb = 1/(4*dnorm(0,0,1));  % Equivalent Noise Bandwidth of 1Hz 2 Sigma filter
Gain = sqrt(Fs/(2*F_2_sigma*K_enb)); % Factor to maintain a constant gain of 1 throughout the simulator
h = h*Gain; % Coefficient of Gaussian Filter Impulse Response