costw207channelmodel.m

无线移动通信中的典型COST207信道的MATLAB仿真程序

% Determine sample (1) echo delay times, (2) norm. Doppler frequencies
% and (3) initial phases of the Rayleigh portions of a (time-variant)
% physical transmission channel according to the European standard COST-
% 207 (COoperation in the field of Science & Technology, Project #207).
%
% function [tau_MHz, fD_norm, psi, tau_pdf] = ...
%                                  COST207 (mPDS[, N_echo[, rseed]]])
% ----------------------------------------------------------------------
% INPUT:
% ----------------------------------------------------------------------
% mPDS    :  String designating the desired propagation environment,
%            i.e. the physical channel, according to COST-207:
%            - 'TU':  "Typical Urban"  (non-hilly urban environment),
%            - 'RA':  "Rural Area"     (non-hilly rural environment),
%            - 'BU':  "Bad Urban"      (hilly urban environment),
%            - 'HT':  "Hilly Terrain"  (hilly rural environment).
%     Note:  These environments correspond to different mean power 
%            delay spectra (PDS, "Verzoegerungsleistungsspektren").
%     N.B.:  To obtain environments NOT standardized by COST-207, mPDS
%            can also be a matrix with entries as in tau_pdf (see o/p).
% [N_echo]:  Desired number of echo paths (Default: 100).
% [rseed] :  If this parameter is given, rseed is used to set the 
%            seeds for the random numbers generator. In this way,
%            the function outputs can be reproduced.
% ----------------------------------------------------------------------
% OUTPUT:
% ----------------------------------------------------------------------
% tau_MHz:  (Length N_out) col. vector of delay times of the echo paths.
%           The values of tau_MHz := tau*1MHz = tau/1us are in the range 
%           0..7 (TU), 0..0.7 (RA), 0..10 (BU), 0..2 and 15..20 (HT).
%           The histogramm of tau_MHz approaches the pdf of tau, which
%           is prop. to the mean power delay spectrum indicated by mPDS.
%    N.B.:  N_out may slightly differ from N_echo to satisfy the relative
%           power ratio between echo clusters (for 'BU' and 'HT', only).
% fD_norm:  (Length N_out) column vector with norm. Doppler frequencies 
%           fD/max{fD} resulting from echos impinging isotropically on
%           the mobile unit. The values are in the range -1.0...1.0 and
%           approximate the Jakes pdf. To unnormalize, multiply by the 
%           maximum Doppler frequency max{fD}:= v*f0/c0, where
%              - v       is the speed of the mobile unit [m/s]
%              - f0      is the carrier frequency [Hertz]
%              - c0=3e8  is the speed of light in empty space [m/s].
% psi    :  (Length N_out) column vector containing the initial phases.
%           The values are uniformly distributed in the range 0..2pi.
% tau_pdf:  Complete set of parameters describing the pdf of echo delay
%           times, where row n refers to the n-th echo cluster:
%           tau_pdf(n,1):  exp. decay factor for the echo delay times,
%           tau_pdf(n,2):  minimum of this cluster's delay times [us],
%           tau_pdf(n,3):  range   of this cluster's delay times [us],
%           tau_pdf(n,4):  total channel energy portion of this cluster.
%           If mPDS was a matrix, tau_pdf is identical to mPDS.
% ----------------------------------------------------------------------
% DERIVATION: M. Benthin, PhD thesis, TU Hamburg-Harburg, 1996, Kap. 3.1
% ----------------------------------------------------------------------
% AUTHOR :  Marcus Benthin,  01.07.92   (name of m-file:  "chan207w.m")
%           Dieter Boss,     01.07.96
% ----------------------------------------------------------------------

% <-------------------------------  max. linewidth for atops  ------------------------------------->|

function [tau_MHz, fD_norm, psi, tau_pdf] = COST207 (mPDS, N_echo, rseed)

                                         % #####  1. Verzoegerungszeiten tau_MHz  #####
  if nargin<2, N_echo = 100; end;        % Das mittlere Verzoegerungs-Leistungsspektrum (mean power
                                         % delay spectrum (mPDS) ist proportional zur Verteilungs-
  if isstr(mPDS)                         % dichte der Echo-Laufzeiten tau_MHz, die durch uc be-
    mPDS = mPDS(find(isletter(mPDS)));   % schrieben wird. Der Prototyp fuer ein einfaches Echo-
    mPDS = upper(mPDS(1:2));             % Cluster hat die Gestalt:  p(tau) = alpha*exp(-beta*tau),
                                         % 0<=tau<=tauD.  Kompliziertere Echo-Profile werden aus  
                                         % mehreren solcher Cluster superponiert (vgl. BU oder HT).

    if strcmp(mPDS,'TU')==1              % COST-207 Mobilfunk-Kanalmodell TYPICAL URBAN
      uc = [ 1.0   0.0    7.0    1.0 ];

    elseif strcmp(mPDS,'RA')==1          % COST-207 Mobilfunk-Kanalmodell RURAL AREA
      uc = [ 9.2   0.0    0.7    1.0 ];

    elseif strcmp(mPDS,'BU')==1          % COST-207 Mobilfunk-Kanalmodell BAD URBAN
      uc = [ 1.0   0.0    5.0    2/3
             1.0   5.0    5.0    1/3 ];  % rel. Amplitude: 0.5

    elseif strcmp(mPDS,'HT')==1          % COST-207 Mobilfunk-Kanalmodell HILLY TERRAIN
      uc = [ 3.5   0.0    2.0    0.88
             1.0  15.0    5.0    0.12];  % rel. Amplitude: 0.04
    else
      error (sprintf('ERROR (COST207.m):  Unknown COST-207 propagation environment "%s"!', mPDS));
    end;
                                         % Beliebige Mobilfunk-Kanalmodelle
  else
    if size(mPDS,2)~=4,
      error('ERROR (COST207.m):  First argument must be a string or a matrix with 4 columns.');
    end;
    uc = mPDS;
  end;

  beta = uc(:,1);                        % Abklingkonstante(n) der Exponentialverteilung(en)
  tauS = uc(:,2);                        % Startzeit(en) der Exponentialverteilung(en) in us
  tauD = uc(:,3);                        % Dauer der/des Echocluster(s) in us
                                         % \int_0^tauD p(tau) dtau = 
                                         % \int_0^tauD alpha*exp(-beta*tau) dtau = 
  alpha = beta./(1-exp(-beta.*tauD));    % alpha(1-exp(-beta*tauD))/beta != 1  =>  alpha.
                                         % s. Marcus Benthin, Diss., Gl. (3.16) 
  N = round(uc(:,4)*N_echo);             % Prozentuale Verteilung von N_echo Exp.Schwingungen
  N_out = sum(N);                        % auf die Echogruppen. Damit ist nur die Leistung
  no_clusters = size(uc,1);              % der Rayleigh-Streuung beruecksichtigt.

  if nargin > 2          
    rand('seed', rseed);                 % Generate reconstructable seeds for the uniform
  end;                                   % random numbers generator (uniformly distributed
  useeds = round(1e8*rand(no_clusters+2,1)); % between 0 and 1e8).
  
  tau_MHz = [];                          % Auswuerfelung von Echozeiten tau in us (Rayleigh-Anteile)
  for cl_no = 1:no_clusters              % cl_no = cluster number
    rand('seed', useeds(cl_no));         % s. Marcus Benthin, Diss., Gl. (3.17) 
    tau_MHz = [tau_MHz; -1/beta(cl_no)*log(1-beta(cl_no)/alpha(cl_no)*rand(N(cl_no),1)) + tauS(cl_no)];
  end; 

  if nargout > 1                         % #####  2. Norm. Dopplerfrequenzen fD_norm  #####
    rand('seed', useeds(no_clusters+1));
    alpha = pi*rand(N_out,1);            % Gleichverteilte Einfallswinkel in (0..pi)
    fD_norm = cos(alpha);                % Jakes-verteilte normierte Dopplerfrequenzen
  end;                                   % im Intervall  -1.0 < fD_norm < 1.0
  if nargout > 2
    rand('seed', useeds(no_clusters+2)); % #####  3. Startphasen psi  #####
    psi = 2*pi*rand(N_out,1);            % Gleichverteilte Startphasen in (0..2pi)
  end
  if nargout > 3                         % #####  4. Parameters describing the pdf of tau #####
    tau_pdf = uc;
  end;
end;

% EOF