pdfplot.m

基于OFDM的无线宽带系统仿真It contains mainly two parts, i.e. link-level simulator and system-level simulator.

% to calculate the PDF for discrete data values
% use hist to collect the values belonging to a certain range
function [X,N,handlePDF,stats] = pdfplot(xin, nbins,nvec)
% pdfplot(X, nbins) 
%   displays a histogram of the empirical probability density function (PDF) 
%   for the data in the input array X using nbins number of bins 
%   (by default pdfplot sets nbins to 20).
%   If input X is a matrix, then pdfplot(X) parses it to the vector and 
%   displays PDF of all values.
%   For complex input X, pdfplot(X) displays PDF of abs(X).
%
%   Example:
%    y = randn( 1, 1e5 );
%    pdfplot( y );
%    pdfplot( y, 100 );

% Version 1.0
% Alex Bur-Guy, September 2003
% [e-mail]
%
% Revisions:
%       Version 1.0 -   initial version

if nargin == 1, nbins = 20; end
xin = reshape( xin, numel(xin), 1 );
if ~isreal( xin ), xin = abs( xin ); end
minXin = min(xin); maxXin = max(xin); 
if floor( nbins ) ~= nbins, error( 'Number of bins should be integer value' ); end
if nbins < 1, error( 'Number of bins should be positive integer greater than 1 ' ); end
if minXin == maxXin
     bar(minXin,1);
     axis([minXin - 10, minXin + 10, 0, 1]);
else
     step = (maxXin - minXin) / (nbins-1);
     binc = minXin : step : maxXin;     
     if nargin == 3, 
        binc = nvec;
     end
     [N, X] = hist(xin, binc);
     handlePDF = bar(X, N/sum(N));
end
xlabel('X', 'FontWeight','b','FontSize',12);
title(['PDF(X) based on ' num2str(length(xin)) ' data samples @ ' num2str(nbins) ' bins'], 'FontWeight','b','FontSize',12);
grid on;
if nargout > 1
   stats.min    =  min(xin);
   stats.max    =  max(xin);
   stats.mean   =  mean(xin);
   stats.median =  median(xin);
   stats.std    =  std(xin);
end