/******************************************************************************\
* Automatic gain control (AGC) *
\******************************************************************************/
void CAGC::Process(CRealVector& vecrIn)
{
if (eType == AT_NO_AGC)
{
/* No modification of the signal (except of an amplitude
correction factor) */
vecrIn *= AM_AMPL_CORR_FACTOR;
}
else
{
for (int i = 0; i < iBlockSize; i++)
{
/* Two sided one-pole recursion for average amplitude
estimation */
IIR1TwoSided(rAvAmplEst, Abs(vecrIn[i]), rAttack, rDecay);
/* Lower bound for estimated average amplitude */
if (rAvAmplEst < LOWER_BOUND_AMP_LEVEL)
rAvAmplEst = LOWER_BOUND_AMP_LEVEL;
/* Normalize to average amplitude and then amplify to the
desired level */
vecrIn[i] *= DES_AV_AMPL_AM_SIGNAL / rAvAmplEst;
}
}
}
/* Implementation *************************************************************/
void CChannelEstimation::ProcessDataInternal(CParameter& ReceiverParam)
{
int i, j, k;
int iModSymNum;
_COMPLEX cModChanEst;
_REAL rSNRAftTiInt;
_REAL rCurSNREst;
_REAL rOffsPDSEst;
/* Check if symbol ID index has changed by the synchronization unit. If it
has changed, reinit this module */
if ((*pvecInputData).GetExData().bSymbolIDHasChanged == TRUE)
{
SetInitFlag();
return;
}
/* Move data in history-buffer (from iLenHistBuff - 1 towards 0) */
for (j = 0; j < iLenHistBuff - 1; j++)
{
for (i = 0; i < iNumCarrier; i++)
matcHistory[j][i] = matcHistory[j + 1][i];
}
/* Write new symbol in memory */
for (i = 0; i < iNumCarrier; i++)
matcHistory[iLenHistBuff - 1][i] = (*pvecInputData)[i];
/* Time interpolation *****************************************************/
/* Get symbol-counter for next symbol. Use the count from the frame
synchronization (in OFDM.cpp). Call estimation routine */
rSNRAftTiInt =
pTimeInt->Estimate(pvecInputData, veccPilots,
ReceiverParam.matiMapTab[(*pvecInputData).
GetExData().iSymbolID],
ReceiverParam.matcPilotCells[(*pvecInputData).
GetExData().iSymbolID], rSNREstimate);
/* Debar initialization of channel estimation in time direction */
if (iInitCnt > 0)
{
iInitCnt--;
/* Do not put out data in initialization phase */
iOutputBlockSize = 0;
/* Do not continue */
return;
}
else
iOutputBlockSize = iNumCarrier;
/* Define DC carrier for robustness mode D because there is not pilot */
if (iDCPos != 0)
veccPilots[iDCPos] = (CReal) 0.0;
/* -------------------------------------------------------------------------
Use time-interpolated channel estimate for timing synchronization
tracking */
TimeSyncTrack.Process(ReceiverParam, veccPilots,
(*pvecInputData).GetExData().iCurTimeCorr, rLenPDSEst /* out */,
rOffsPDSEst /* out */);
/* Frequency-interploation ************************************************/
switch (TypeIntFreq)
{
case FLINEAR:
/**********************************************************************\
* Linear interpolation *
\**********************************************************************/
/* Set first pilot position */
veccChanEst[0] = veccPilots[0];
for (j = 0, k = 1; j < iNumCarrier - iScatPilFreqInt;
j += iScatPilFreqInt, k++)
{
/* Set values at second time pilot position in cluster */
veccChanEst[j + iScatPilFreqInt] = veccPilots[k];
/* Interpolation cluster */
for (i = 1; i < iScatPilFreqInt; i++)
{
/* E.g.: c(x) = (c_4 - c_0) / 4 * x + c_0 */
veccChanEst[j + i] =
(veccChanEst[j + iScatPilFreqInt] - veccChanEst[j]) /
(_REAL) (iScatPilFreqInt) * (_REAL) i + veccChanEst[j];
}
}
break;
case FDFTFILTER:
/**********************************************************************\
* DFT based algorithm *
\**********************************************************************/
/* ---------------------------------------------------------------------
Put all pilots at the beginning of the vector. The "real" length of
the vector "pcFFTWInput" is longer than the No of pilots, but we
calculate the FFT only over "iNumCarrier / iScatPilFreqInt + 1"
values (this is the number of pilot positions) */
/* Weighting pilots with window */
veccPilots *= vecrDFTWindow;
/* Transform in time-domain */
veccPilots = Ifft(veccPilots, FftPlanShort);
/* Set values outside a defined bound to zero, zero padding (noise
filtering). Copy second half of spectrum at the end of the new vector
length and zero out samples between the two parts of the spectrum */
veccIntPil.Merge(
/* First part of spectrum */
veccPilots(1, iStartZeroPadding),
/* Zero padding in the middle, length: Total length minus length of
the two parts at the beginning and end */
CComplexVector(Zeros(iLongLenFreq - 2 * iStartZeroPadding),
Zeros(iLongLenFreq - 2 * iStartZeroPadding)),
/* Set the second part of the actual spectrum at the end of the new
vector */
veccPilots(iNumIntpFreqPil - iStartZeroPadding + 1,
iNumIntpFreqPil));
/* Transform back in frequency-domain */
veccIntPil = Fft(veccIntPil, FftPlanLong);
/* Remove weighting with DFT window by inverse multiplication */
veccChanEst = veccIntPil(1, iNumCarrier) * vecrDFTwindowInv;
break;
case FWIENER:
/**********************************************************************\
* Wiener filter *
\**********************************************************************/
#ifdef UPD_WIENER_FREQ_EACH_DRM_FRAME
/* Update filter coefficients once in one DRM frame */
if (iUpCntWienFilt > 0)
{
iUpCntWienFilt--;
/* Get maximum delay spread and offset in one DRM frame */
if (rLenPDSEst > rMaxLenPDSInFra)
rMaxLenPDSInFra = rLenPDSEst;
if (rOffsPDSEst < rMinOffsPDSInFra)
rMinOffsPDSInFra = rOffsPDSEst;
}
else
{
#else
/* Update Wiener filter each OFDM symbol. Use current estimates */
rMaxLenPDSInFra = rLenPDSEst;
rMinOffsPDSInFra = rOffsPDSEst;
#endif
/* Update filter taps */
UpdateWienerFiltCoef(rSNRAftTiInt, rMaxLenPDSInFra / iNumCarrier,
rMinOffsPDSInFra / iNumCarrier);
#ifdef UPD_WIENER_FREQ_EACH_DRM_FRAME
/* Reset counter and maximum storage variable */
iUpCntWienFilt = iNumSymPerFrame;
rMaxLenPDSInFra = (_REAL) 0.0;
rMinOffsPDSInFra = rGuardSizeFFT;
}
#endif
/* FIR filter of the pilots with filter taps. We need to filter the
pilot positions as well to improve the SNR estimation (which
follows this procedure) */
for (j = 0; j < iNumCarrier; j++)
{
/* Convolution */
veccChanEst[j] = _COMPLEX((_REAL) 0.0, (_REAL) 0.0);
for (i = 0; i < iLengthWiener; i++)
veccChanEst[j] +=
matcFiltFreq[j][i] * veccPilots[veciPilOffTab[j] + i];
}
break;
}
/* Equalize the output vector ------------------------------------------- */
/* Write to output vector. Take oldest symbol of history for output. Also,
ship the channel state at a certain cell */
for (i = 0; i < iNumCarrier; i++)
{
(*pvecOutputData)[i].cSig = matcHistory[0][i] / veccChanEst[i];
(*pvecOutputData)[i].rChan = SqMag(veccChanEst[i]);
}
/* -------------------------------------------------------------------------
Calculate symbol ID of the current output block and set parameter */
(*pvecOutputData).GetExData().iSymbolID =
(*pvecInputData).GetExData().iSymbolID - iLenHistBuff + 1;
/* SNR estimation ------------------------------------------------------- */
/* Modified symbol ID, check range {0, ..., iNumSymPerFrame} */
iModSymNum = (*pvecOutputData).GetExData().iSymbolID;
while (iModSymNum < 0)
iModSymNum += iNumSymPerFrame;
for (i = 0; i < iNumCarrier; i++)
{
switch (TypeSNREst)
{
case SNR_PIL:
/* Use estimated channel and compare it to the received pilots. This
estimation works only if the channel estimation was successful */
/* Identify pilot positions. Use MODIFIED "iSymbolID" (See lines
above) */
if (_IsScatPil(ReceiverParam.matiMapTab[iModSymNum][i]))
{
/* We assume that the channel estimation in "veccChanEst" is
noise free (e.g., the wiener interpolation does noise
reduction). Thus, we have an estimate of the received signal
power \hat{r} = s * \hat{h}_{wiener} */
cModChanEst = veccChanEst[i] *
ReceiverParam.matcPilotCells[iModSymNum][i];
/* Calculate and average noise and signal estimates --------- */
/* The noise estimation is difference between the noise reduced
signal and the noisy received signal
\tilde{n} = \hat{r} - r */
IIR1(rNoiseEst, SqMag(matcHistory[0][i] - cModChanEst),
rLamSNREstFast);
/* The received signal power estimation is just \hat{r} */
IIR1(rSignalEst, SqMag(cModChanEst), rLamSNREstFast);
/* Calculate final result (signal to noise ratio) */
if (rNoiseEst != 0)
rCurSNREst = rSignalEst / rNoiseEst;
else
rCurSNREst = (_REAL) 1.0;
/* Bound the SNR at 0 dB */
if (rCurSNREst < (_REAL) 1.0)
rCurSNREst = (_REAL) 1.0;
/* Average the SNR with a two sided recursion */
IIR1TwoSided(rSNREstimate, rCurSNREst, rLamSNREstFast,
rLamSNREstSlow);
}
break;
case SNR_FAC:
/* SNR estimation with initialization */
if (iSNREstInitCnt > 0)
{
/* Initial signal estimate. Use channel estimation from all
cells. Apply averaging */
rSignalEst += (*pvecOutputData)[i].rChan;
iSNREstInitCnt--;
}
else
{
/* Only right after initialization phase apply initial SNR
value */
if (bWasSNRInit == TRUE)
{
/* Normalize average */
rSignalEst /= iNumCellsSNRInit;
/* Apply initial SNR value */
rNoiseEst = rSignalEst / rSNREstimate;
bWasSNRInit = FALSE;
}
/* Only use FAC cells for this SNR estimation method */
if (_IsFAC(ReceiverParam.matiMapTab[iModSymNum][i]))
{
/* Get tentative decision for current FAC cell (squared) */
CReal rCurErrPow =
TentativeFACDec((*pvecOutputData)[i].cSig);
/* Use decision together with channel estimate to get
estimates for signal and noise */
IIR1(rNoiseEst, rCurErrPow * (*pvecOutputData)[i].rChan,
rLamSNREstFast);
IIR1(rSignalEst, (*pvecOutputData)[i].rChan,
rLamSNREstFast);
/* Calculate final result (signal to noise ratio) */
if (rNoiseEst != (_REAL) 0.0)
rCurSNREst = rSignalEst / rNoiseEst;
else
rCurSNREst = (_REAL) 1.0;
/* Bound the SNR at 0 dB */
if (rCurSNREst < (_REAL) 1.0)
rCurSNREst = (_REAL) 1.0;
/* The channel estimation algorithms need the SNR normalized
to the energy of the pilots */
rSNREstimate = rCurSNREst / rSNRCorrectFact;
}
}
break;
}
}
}
