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+/* -*- c++ -*- */
+/*
+ * Copyright 2011,2012 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_MPSK_SNR_EST_H
+#define INCLUDED_DIGITAL_MPSK_SNR_EST_H
+
+#include <digital/api.h>
+#include <gr_complex.h>
+
+namespace gr {
+  namespace digital {
+
+    //! 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 mpsk_snr_est
+    {
+    protected:
+      double d_alpha, d_beta;
+
+    public:
+      /*! Constructor
+       *
+       *  Parameters:
+       *  \param alpha: the update rate of internal running average
+       *  calculations.
+       */
+      mpsk_snr_est(double alpha);
+      virtual ~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 *input);
+
+      //! 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 mpsk_snr_est_simple :
+      public mpsk_snr_est
+    {
+    private:
+      double d_y1, d_y2;
+  
+    public:
+      /*! Constructor
+       *
+       *  Parameters:
+       *  \param alpha: the update rate of internal running average
+       *  calculations.
+       */
+      mpsk_snr_est_simple(double alpha);
+      ~mpsk_snr_est_simple() {}
+
+      int update(int noutput_items,
+		 const gr_complex *input);
+      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 mpsk_snr_est_skew :
+      public mpsk_snr_est
+    {
+    private:
+      double d_y1, d_y2, d_y3;
+  
+    public:
+      /*! Constructor
+       *
+       *  Parameters:
+       *  \param alpha: the update rate of internal running average
+       *  calculations.
+       */
+      mpsk_snr_est_skew(double alpha);
+      ~mpsk_snr_est_skew() {}
+
+      int update(int noutput_items,
+		 const gr_complex *input);
+      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 mpsk_snr_est_m2m4 :
+      public mpsk_snr_est
+    {
+    private:
+      double d_y1, d_y2;
+  
+    public:
+      /*! Constructor
+       *
+       *  Parameters:
+       *  \param alpha: the update rate of internal running average
+       *  calculations.
+       */
+      mpsk_snr_est_m2m4(double alpha);
+      ~mpsk_snr_est_m2m4() {}
+
+      int update(int noutput_items,
+		 const gr_complex *input);
+      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 snr_est_m2m4 :
+      public 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)
+       */
+      snr_est_m2m4(double alpha, double ka, double kw);
+      ~snr_est_m2m4() {}
+
+      int update(int noutput_items,
+		 const gr_complex *input);
+      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 mpsk_snr_est_svr :
+      public mpsk_snr_est
+    {
+    private:
+      double d_y1, d_y2;
+  
+    public:
+      /*! Constructor
+       *
+       *  Parameters:
+       *  \param alpha: the update rate of internal running average
+       *  calculations.
+       */
+      mpsk_snr_est_svr(double alpha);
+      ~mpsk_snr_est_svr() {}
+
+      int update(int noutput_items,
+		 const gr_complex *input);
+      double snr();
+    };
+
+  } /* namespace digital */
+} /* namespace gr */
+
+#endif /* INCLUDED_DIGITAL_MPSK_SNR_EST_H */