% function AdjustForISCI()
% Copyright (C):
%       2002 by Alcatel Bell NV, Belgium
%       2002-2003 by Forschungszentrum Telekommunikation Wien, Austria;
%                                                         All rights reserved.
%
% Description : 
%   AdjustForISCI function calculates a parabolic approximation of the
%   ISI/ICI on the upstream tones in the FDD ADSL/ISDN implementation
%   of Alcatel. It is quite rough approximation and gives idea about
%   the limitation on the SNR on each tone due to ISI/ICI. Although
%   the tone mask of the upstream that is provided as input argument
%   may vary, it is matched to the band 33-56 and using it for other
%   bands requires changing the parameters definition.
%
% Intention for usage:
%   When calculating the signal and the noise PSD (from noise floor
%   and/or crosstalk) at the end of the line (before entering the
%   modem and the SNR calculations), call this function in order to
%   get the ISI/ICI "noise" level. Then compare it with the sum of the
%   other noises (with analog nature, like crosstalk) per tone bases.
%   For each tone, take the maximum of the two - the sum of the others
%   and the ISI/ICI. Thus received "noise" use in the SNR calculations
%   that compute the bitloading and the data rate.
%
% Project       : FTW's xDSLsimu
% Author(s)     : Vladimir Ivanov (Vladimir.Ivanov@alcatel.be)
%                 Tomas Nordstrom (Tomas.Nordstrom@FTW.at)
%
% Reference:
%    ETSI TM6 021t31r1, Torino, Italy, 4th-8th Feb., 2002
%
% CVS:       $Id: AdjustForISCI.m,v 3.3 2003/12/23 10:35:07 tono Exp $
%% ===========================================================================
% Change History
%      2002-02-01 (Vladimir Ivanov) Created
%      2002-02-02 (ToNo) Modified for FTW xDSL simulator
%      2003-11-03 (ToNo) Lists now use cell arrays for both Octave and Matlab
%      2003-12-22 (ToNo) Changed names concerning down- and upstream parameters
%% ===========================================================================
global ex;
global result;
    
% Tones used
ToneMask  = [zeros(1,min(us.tones)) ...
             ones(1,max(us.tones)-min(us.tones)+1)...
             zeros(1,64-max(us.tones))];

% SNR parameter definition
maxSNR    = isci.maxSNR;% dB, the maximal achievable SNR on the
                        % center tone in the band
deltaSNR1 = isci.lowdeltaSNR;  % dB, the SNR drop at the first tone of the
                        % band w.r.t to the maximum
                        % It depends mainly on the order and
                        % the type of the highpass ISDN splitters.
deltaSNR2 = isci.highdeltaSNR;% dB, the SNR drop at the last tone of the
                        % band w.r.t to the maximum
                        % It depends mainly on the order and
                        % the type of the FDM filters - Tx and Rx,
                        % digital and analog.

                        
% Input arguments validation
maxTones  = 64;
df        = 4.3125e3;           % Carrier spacing in Hz
ToneMask  = ToneMask(:);
ToneMask  = ToneMask(1:maxTones+1);
ToneFreq  = (0:maxTones)*df;

% Parabolic curve fitting on 3 points - one in the center tone(x0)
% and two at the edge tones (x1 and x2)

% Definfition of the tones
x1 = min(us.tones);
x2 = max(us.tones);
x=[0:maxTones]';

x0 = (x1+x2)/2;                     % The tone at the center

% Calculating the SNR
y0    = maxSNR;                     % On tone x0, dB
ylow  = -160;                       % Very low background noise
                                    % power in order to avoid 0, dBm/Hz

y1    = y0 - deltaSNR1;
y2    = y0 - deltaSNR2;

% Simple parabolic fit:  [ P ] * [ q ] = [ R ];
P = [
  x1^2  x1  1;...
  x0^2  x0  1;...
  x2^2  x2  1;...
];

R = [y1  y0  y2]';

q = inv(P)*R;                % The vector with the coefficients of the parabola

y = q(1)*x.^2 + q(2)*x + q(3);  % SNR, dB

% Now we adjust our result to this ISI/ICI model
yl = ( y.*ToneMask - ylow.*~ToneMask );
ylust = interp1(ToneFreq,yl,ex.param.frequency.f,'cubic');

rlen = length(result);
for pos = 1:rlen,
    rr=result{pos};

ISCIN=rr.LT.Rx_signal./(10.^(ylust./10));

rr.LT.Tot_noise.up   = rr.LT.Tot_noise.up+ISCIN;
rr.LT.Tot_noise.down = rr.LT.Tot_noise.down+ISCIN;

if 0, % If 1, plot some of the temporary values
    S=10*log10(Rx_LTpt(us.tones))
    N=10*log10(Noise_LTpt(us.tones))
    SN=10*log10(Rx_LTpt(us.tones))-10*log10(Noise_LTpt(us.tones))
    SM=yl(us.tones+1)'
    
    plot(ex.param.frequency.f,10*log10(ISCIN),...
         ex.param.frequency.f,10*log10(rr.LT.Tot_noise.up));
    duf=us.tones*df;
    plot(duf,S,duf,N,duf,SN,duf,SM)
end;

    result{pos}=rr;
end; % pos

% End of function