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-/* -*- c++ -*- */
-/*
- * Copyright 2011 Free Software Foundation, Inc.
- *
- * This file is part of GNU Radio
- *
- * GNU Radio is free software; you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation; either version 3, or (at your option)
- * any later version.
- *
- * GNU Radio is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with GNU Radio; see the file COPYING. If not, write to
- * the Free Software Foundation, Inc., 51 Franklin Street,
- * Boston, MA 02110-1301, USA.
- */
-#ifndef INCLUDED_DIGITAL_IMPL_MPSK_SNR_EST_H
-#define INCLUDED_DIGITAL_IMPL_MPSK_SNR_EST_H
-
-#include <digital_api.h>
-#include <gr_sync_block.h>
-
-//! Enum for the type of SNR estimator to select
-/*! \ingroup snr_blk
- * \anchor ref_snr_est_types
- *
- * Below are some ROUGH estimates of what values of SNR each of these
- * types of estimators is good for. In general, these offer a
- * trade-off between accuracy and performance.
- *
- * \li SNR_EST_SIMPLE: Simple estimator (>= 7 dB)
- * \li SNR_EST_SKEW: Skewness-base est (>= 5 dB)
- * \li SNR_EST_M2M4: 2nd & 4th moment est (>= 1 dB)
- * \li SNR_EST_SVR: SVR-based est (>= 0dB)
-*/
-enum snr_est_type_t {
- SNR_EST_SIMPLE = 0, // Simple estimator (>= 7 dB)
- SNR_EST_SKEW, // Skewness-base est (>= 5 dB)
- SNR_EST_M2M4, // 2nd & 4th moment est (>= 1 dB)
- SNR_EST_SVR // SVR-based est (>= 0dB)
-};
-
-/*! \brief A parent class for SNR estimators, specifically for M-PSK
- * signals in AWGN channels.
- * \ingroup snr_blk
- */
-class DIGITAL_API digital_impl_mpsk_snr_est
-{
- protected:
- double d_alpha, d_beta;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- */
- digital_impl_mpsk_snr_est(double alpha);
- virtual ~digital_impl_mpsk_snr_est();
-
- //! Get the running-average coefficient
- double alpha() const;
-
- //! Set the running-average coefficient
- void set_alpha(double alpha);
-
- //! Update the current registers
- virtual int update(int noutput_items,
- const gr_complex *in);
-
- //! Use the register values to compute a new estimate
- virtual double snr();
-};
-
-
-//! \brief SNR Estimator using simple mean/variance estimates.
-/*! \ingroup snr_blk
- *
- * A very simple SNR estimator that just uses mean and variance
- * estimates of an M-PSK constellation. This esimator is quick and
- * cheap and accurate for high SNR (above 7 dB or so) but quickly
- * starts to overestimate the SNR at low SNR.
- */
-class DIGITAL_API digital_impl_mpsk_snr_est_simple :
- public digital_impl_mpsk_snr_est
-{
- private:
- double d_y1, d_y2;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- */
- digital_impl_mpsk_snr_est_simple(double alpha);
- ~digital_impl_mpsk_snr_est_simple() {}
-
- int update(int noutput_items,
- const gr_complex *in);
- double snr();
-};
-
-
-//! \brief SNR Estimator using skewness correction.
-/*! \ingroup snr_blk
- *
- * This is an estimator that came from a discussion between Tom
- * Rondeau and fred harris with no known paper reference. The idea is
- * that at low SNR, the variance estimations will be affected because
- * of fold-over around the decision boundaries, which results in a
- * skewness to the samples. We estimate the skewness and use this as
- * a correcting term.
- */
-class DIGITAL_API digital_impl_mpsk_snr_est_skew :
- public digital_impl_mpsk_snr_est
-{
- private:
- double d_y1, d_y2, d_y3;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- */
- digital_impl_mpsk_snr_est_skew(double alpha);
- ~digital_impl_mpsk_snr_est_skew() {}
-
- int update(int noutput_items,
- const gr_complex *in);
- double snr();
-};
-
-
-//! \brief SNR Estimator using 2nd and 4th-order moments.
-/*! \ingroup snr_blk
- *
- * An SNR estimator for M-PSK signals that uses 2nd (M2) and 4th (M4)
- * order moments. This estimator uses knowledge of the kurtosis of
- * the signal (k_a) and noise (k_w) to make its estimation. We use
- * Beaulieu's approximations here to M-PSK signals and AWGN channels
- * such that k_a=1 and k_w=2. These approximations significantly
- * reduce the complexity of the calculations (and computations)
- * required.
- *
- * Reference:
- * D. R. Pauluzzi and N. C. Beaulieu, "A comparison of SNR
- * estimation techniques for the AWGN channel," IEEE
- * Trans. Communications, Vol. 48, No. 10, pp. 1681-1691, 2000.
- */
-class DIGITAL_API digital_impl_mpsk_snr_est_m2m4 :
- public digital_impl_mpsk_snr_est
-{
- private:
- double d_y1, d_y2;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- */
- digital_impl_mpsk_snr_est_m2m4(double alpha);
- ~digital_impl_mpsk_snr_est_m2m4() {}
-
- int update(int noutput_items,
- const gr_complex *in);
- double snr();
-};
-
-
-//! \brief SNR Estimator using 2nd and 4th-order moments.
-/*! \ingroup snr_blk
- *
- * An SNR estimator for M-PSK signals that uses 2nd (M2) and 4th (M4)
- * order moments. This estimator uses knowledge of the kurtosis of
- * the signal (k_a) and noise (k_w) to make its estimation. In this
- * case, you can set your own estimations for k_a and k_w, the
- * kurtosis of the signal and noise, to fit this estimation better to
- * your signal and channel conditions.
- *
- * A word of warning: this estimator has not been fully tested or
- * proved with any amount of rigor. The estimation for M4 in
- * particular might be ignoring effectf of when k_a and k_w are
- * different. Use this estimator with caution and a copy of the
- * reference on hand.
- *
- * The digital_mpsk_snr_est_m2m4 assumes k_a and k_w to simplify the
- * computations for M-PSK and AWGN channels. Use that estimator
- * unless you have a way to guess or estimate these values here.
- *
- * Original paper:
- * R. Matzner, "An SNR estimation algorithm for complex baseband
- * signal using higher order statistics," Facta Universitatis
- * (Nis), no. 6, pp. 41-52, 1993.
- *
- * Reference used in derivation:
- * D. R. Pauluzzi and N. C. Beaulieu, "A comparison of SNR
- * estimation techniques for the AWGN channel," IEEE
- * Trans. Communications, Vol. 48, No. 10, pp. 1681-1691, 2000.
- */
-class DIGITAL_API digital_impl_snr_est_m2m4 :
- public digital_impl_mpsk_snr_est
-{
- private:
- double d_y1, d_y2;
- double d_ka, d_kw;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- * \param ka: estimate of the signal kurtosis (1 for PSK)
- * \param kw: estimate of the channel noise kurtosis (2 for AWGN)
- */
- digital_impl_snr_est_m2m4(double alpha, double ka, double kw);
- ~digital_impl_snr_est_m2m4() {}
-
- int update(int noutput_items,
- const gr_complex *in);
- double snr();
-};
-
-
-//! \brief Signal-to-Variation Ratio SNR Estimator.
-/*! \ingroup snr_blk
- *
- * This estimator actually comes from an SNR estimator for M-PSK
- * signals in fading channels, but this implementation is
- * specifically for AWGN channels. The math was simplified to assume
- * a signal and noise kurtosis (k_a and k_w) for M-PSK signals in
- * AWGN. These approximations significantly reduce the complexity of
- * the calculations (and computations) required.
- *
- * Original paper:
- * A. L. Brandao, L. B. Lopes, and D. C. McLernon, "In-service
- * monitoring of multipath delay and cochannel interference for
- * indoor mobile communication systems," Proc. IEEE
- * Int. Conf. Communications, vol. 3, pp. 1458-1462, May 1994.
- *
- * Reference:
- * D. R. Pauluzzi and N. C. Beaulieu, "A comparison of SNR
- * estimation techniques for the AWGN channel," IEEE
- * Trans. Communications, Vol. 48, No. 10, pp. 1681-1691, 2000.
- */
-class DIGITAL_API digital_impl_mpsk_snr_est_svr :
- public digital_impl_mpsk_snr_est
-{
- private:
- double d_y1, d_y2;
-
- public:
- /*! Constructor
- *
- * Parameters:
- * \param alpha: the update rate of internal running average
- * calculations.
- */
- digital_impl_mpsk_snr_est_svr(double alpha);
- ~digital_impl_mpsk_snr_est_svr() {}
-
- int update(int noutput_items,
- const gr_complex *in);
- double snr();
-};
-
-#endif /* INCLUDED_DIGITAL_IMPL_MPSK_SNR_EST_H */