uwb_sv_channel.m

超宽带系统链路matlab仿真程序 超宽带系统简单仿真平台

function h=UWB_SV_channel(num_channels,cm_num,ts)
% S-V channel model evaluation
% Input Parameters: 1. ts is sampling time (nsec)
%                   2. num_channels is the number of channel impulse responses to generate
%                   3. cm_num is the channel model number from 1 to 4
% Output Parameters: h is the discrete-timeimpulse response at time resolution ts.

no_output_files = 0;  % non-zero: avoids writing output files of continuous-time responses
randn('state',12);    % initialize state of function for repeatability
rand('state',12);     % initialize state of function for repeatability
% get channel model params based on this channel model number
[Lam,lambda,Gam,gamma,std_ln_1,std_ln_2,nlos,std_shdw] = uwb_sv_params( cm_num );
%fprintf(1,['Model Parameters\n' ...
  %'  Lam = %.4f, lambda = %.4f, Gam = %.4f, gamma = %.4f\n' ...
  %'  std_ln_1 = %.4f, std_ln_2 = %.4f, NLOS flag = %d, std_shdw = %.4f\n'], ...
  %Lam, lambda, Gam, gamma, std_ln_1, std_ln_2, nlos, std_shdw);

% get a bunch of realizations (impulse responses)
[h_ct,t_ct,t0,np] = uwb_sv_model_ct( Lam, lambda, Gam, gamma, std_ln_1, std_ln_2, nlos, ...
                  std_shdw, num_channels );
% now reduce continuous-time result to a discrete-time result
[hN,N] = uwb_sv_cnvrt_ct( h_ct, t_ct, np, num_channels, ts );
% if we wanted complex baseband model or to impose some filtering function,
% this would be a good place to do it
if N > 1,
  h = resample(hN, 1, N);  % decimate the columns of hN by factor N
else
  h = hN;
end
% correct for 1/N scaling imposed by decimation
h = h * N;
h=h./(ones(size(h,1),1)*sum(h.*h));%对信道进行能量归一化