eqber_adaptive.m

Adaptive Filter. This script shows the BER performance of several types of equalizers in a static ch

%% EQBER_ADAPTIVE - Simulation of linear and DFE equalizers
% This script runs a simulation loop for either a linear or a DFE equalizer.  It
% uses the RLS algorithm to initially set the weights, then uses LMS thereafter
% to minimize execution time.  It plots the equalized signal spectrum, then
% generates and plots BER results over a range of Eb/No values. It also fits a
% curve to the simulated BER points, and plots the burst error performance of
% the linear and DFE equalizers. The adaptive equalizer objects automatically
% retain their state between invocations of their "equalize" method.
%
% This script uses another script, <eqber_siggen.html eqber_siggen> to
% generate a noisy, channel-filtered signal.

%   Copyright 1996-2004 The MathWorks, Inc.
%   $Revision: 1.1.4.1 $  $Date: 2004/06/30 23:03:08 $


% Set parameters based on linear or DFE equalizer setting
if (strcmpi(eqType, 'linear'))
    refTap     = linEq1.RefTap; % set reference tap
    eq1        = linEq1;        % set RLS equalizer for first data block
    eq2        = linEq2;        % set LMS equalizer for remaining data blocks
    hSpecPlot  = hLinSpec;      % set spectrum plot line handle
elseif (strcmpi(eqType, 'dfe'))
    refTap     = dfeEq1.RefTap;
    eq1        = dfeEq1;
    eq2        = dfeEq2;
    hSpecPlot  = hDfeSpec;
end

firstErrPlot = true;   % for burst error plot - reset for each eq method

% Main simulation loop
for EbNoIdx = 1 : length(EbNo)
    
    % Initialize channel and error collection parameters 
    chanState = [];
    numErrs   = 0;
    numBits   = 0;
    firstBlk = true;  % RLS for first data block, LMS thereafter
    
    while (numErrs < maxErrs && numBits < maxBits)
        
        eqber_siggen;  % generate a noisy, channel-filtered signal
        
        if (numErrs < maxErrs)
            
            % Equalize the signal with an adaptive equalizer.  Use a truncated
            % version of the transmitted signal as the training signal.  Use RLS
            % to initially set the weights in the first data block, and LMS
            % thereafter, for speed purposes.
            trainSig = txSig(1 : end-refTap+1);
            if (firstBlk)
                [PreD, PostD] = equalize(eq1, noisySig, trainSig);
                
                % Set the weights and weight inputs of the LMS equalizer to
                % those of the RLS equalizer for future data blocks.
                eq2.Weights = eq1.Weights;
                eq2.WeightInputs = eq1.WeightInputs;
            end
            
            % Equalize all blocks, including a re-equalization of the first
            % block.  Do not use a training sequence.  The performance of the
            % DFE equalizer will be enhanced if called with a training sequence,
            % but a real system would be implemented without the training
            % sequence.
            [PreD, PostD] = equalize(eq2, noisySig);
                        
            % Plot the spectrum of the equalized signal
            hSpecPlot = eqber_graphics('sigspec', eqType, hSpecPlot, ...
                nBits, PreD);

            % Demodulate the signal
            demodSig = (1-sign(real(PostD)))/2;

            range1 = 1 : length(msg)-refTap+1;
            range2 = refTap : length(demodSig);
            [currErrs, ratio] = biterr(msg(range1), demodSig(range2));
            numErrs = numErrs + currErrs;       % cumulative
            numBits = numBits + length(range1); % cumulative
            BER(EbNoIdx) = numErrs / numBits;

            % Plot the burst error performance for this data block
            [hErrs, hText1, hText2] = eqber_graphics('bursterrors', eqType, ...
                mlseType, firstErrPlot, msg(range1), demodSig(range2), ...
                nBits, hErrs, hText1, hText2);
            firstErrPlot = false;
        end
                
        % Update the BER plot
        [hBER, hLegend, legendString] = eqber_graphics('simber', eqType, ...
            mlseType, firstBlk, EbNoIdx, EbNo, BER, hBER, hLegend, ...
            legendString);
        firstBlk = false;  % done processing first data block
        
    end     % end of simulation while loop
    
    % Fit a plot to the new BER points
    hFit = eqber_graphics('fitber', eqType, mlseType, hFit, EbNoIdx, EbNo, BER);
    
    % Reset the RLS equalizer for the next Eb/No
    if (strcmpi(eqType, 'linear'))
        eq1 = lineareq(nWts, alg1);
        eq1.RefTap = round(nWts/2);
    elseif (strcmpi(eqType, 'dfe'))
        eq1 = dfe(nFwdWts, nFbkWts, alg1);
        eq1.RefTap = round(nFwdWts/2);
    end
    eq1.ResetBeforeFiltering = 0;
           
end     % end of 'for EbNoIdx' loop