%% EQBER_MLSE - Simulation of MLSE equalizers with and without perfect channel knowledge% This script runs a simulation loop for an MLSE equalizer with and without a% perfect channel estimate.  It also dynamically plots the spectrum estimate for% the imperfect MLSE equalizer.  It also plots the burst error performance of% the MLSE equalizers.  It also generates and plots BER results over a range of% Eb/No values, and fits a curve to the simulated BER points.%% The channel estimation technique uses a cyclic prefix prepended to the% transmitted data.  The resulting augmented sequence is then looks periodic to% an FFT, and such techniques can be used to accurately estimate the spectrum.% Specifically, the FFT of the noisy, channel-filtered signal is divided by the% FFT of the transmitted signal to give a noisy estimate of the channel% frequency response. Although this technique is not ideal, and is highly% dependent on the spectral characteristics of the data, it is a straightforward% implementation of classic linear system theory.%% 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 23:03:10 $firstEstPlot = true;   % for channel estimate plotfirstErrPlot = true;   % for burst error plot - reset for imperfect MLSE% Main simulation loopfor EbNoIdx = 1 : length(EbNo)        % Initialize channel and error collection parameters    chanState = [];    numErrs = 0;    numBits = 0;        % Reset the equalizer initial data    [mlseMetric, mlseStates, mlseInputs] = deal([]);        % Preallocate a buffer for the MLSE    lastMsg = zeros(tbLen, 1);        firstBlk = true;       % counter for processing multiple data blocks        while (numErrs < maxErrs && numBits < maxBits)                eqber_siggen;  % generate a noisy, channel-filtered signal                if (strcmp(mlseType,'imperfect'))                        % Set an initial channel estimate.            chnlEst = [chnl; zeros(excessEst,1)];            % Perform a channel estimate.  Prepend a cyclic prefix to the            % transmitted signal, then run it through the noisy channel and            % truncate it to the estimated length.  The estimated frequency            % response is the FFT of the noisy signal divided by the FFT of the            % transmitted signal.            augTx = [txSig(end-prefixLen+1:end); txSig];   % create cyclic prefix            augFilt = filter(chnl, 1, augTx);            augFilt = awgn(augFilt, SNR, 'measured');            augFilt = augFilt(prefixLen+1:end);            HEstNum = fft(augFilt); HEstDen = fft(txSig);                        % Test to avoid dividing by zero.  If the test passes, perform the            % division to generate the channel estimate.            if (all(abs(real(HEstDen))>eps) && all(abs(imag(HEstDen))>eps))                HEst = HEstNum ./ HEstDen;                chnlEst = ifft(HEst);                chnlEst = chnlEst(1:chnlLen+excessEst); % truncation w/error            end                            % Plot the spectrum of the channel estimate            hEstPlot = eqber_graphics('chnlest', chnlEst, chnlLen, ...                excessEst, nBits, firstEstPlot, hEstPlot);            firstEstPlot = false;                    end        if (numErrs < maxErrs)                        % Equalize the signal with an MLSE equalizer and initialize the            % equalizer states for the next block of data.            [eqSig, mlseMetric mlseStates mlseInputs] = ...                mlseeq(noisySig, chnlEst, const, tbLen, mlseMode, nSamp, ...                       mlseMetric, mlseStates, mlseInputs);            % Demodulate the signal            demodSig = (1-sign(real(eqSig)))/2;            % Update the error statistics.  Account for the delay in the            % first block of processed data.            currMsg = msg(1:end-tbLen);            fullMsg = [lastMsg; currMsg];                        [currErrs, ratio] = biterr(fullMsg, demodSig);            numErrs = numErrs + currErrs;            if (firstBlk)                numBits = numBits + nBits - tbLen;            else                numBits = numBits + nBits;            end            BER(EbNoIdx) = numErrs / numBits;                        % Retain the end of the current message for the next block of            % data            lastMsg = msg(end-tbLen+1 : end);                        % Plot the error vector for this frame of data            [hErrs, hText1, hText2] = eqber_graphics('bursterrors', eqType, ...                mlseType, firstErrPlot, fullMsg, demodSig, 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);    end     % end of 'for EbNoIdx' loop