GNU Radio Manual and C++ API Reference 3.9.4.0
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lms_dd_equalizer_cc.h
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1/* -*- c++ -*- */
2/*
3 * Copyright 2011,2012 Free Software Foundation, Inc.
4 *
5 * This file is part of GNU Radio
6 *
7 * SPDX-License-Identifier: GPL-3.0-or-later
8 *
9 */
10
11#ifndef INCLUDED_DIGITAL_LMS_DD_EQUALIZER_CC_H
12#define INCLUDED_DIGITAL_LMS_DD_EQUALIZER_CC_H
13
17
18namespace gr {
19namespace digital {
20
21/*!
22 * \brief Least-Mean-Square Decision Directed Equalizer (complex in/out)
23 * \ingroup equalizers_blk
24 * \ingroup deprecated_blk
25 *
26 * \details
27 * This block implements an LMS-based decision-directed equalizer.
28 * It uses a set of weights, w, to correlate against the inputs,
29 * u, and a decisions is then made from this output. The error in
30 * the decision is used to update the weight vector.
31 *
32 * y[n] = conj(w[n]) u[n]
33 * d[n] = decision(y[n])
34 * e[n] = d[n] - y[n]
35 * w[n+1] = w[n] + mu u[n] conj(e[n])
36 *
37 * Where mu is a gain value (between 0 and 1 and usually small,
38 * around 0.001 - 0.01.
39 *
40 * This block uses the digital_constellation object for making the
41 * decision from y[n]. Create the constellation object for
42 * whatever constellation is to be used and pass in the object.
43 * In Python, you can use something like:
44 *
45 * self.constellation = digital.constellation_qpsk()
46 *
47 * To create a QPSK constellation (see the digital_constellation
48 * block for more details as to what constellations are available
49 * or how to create your own). You then pass the object to this
50 * block as an sptr, or using "self.constellation.base()".
51 *
52 * The theory for this algorithm can be found in Chapter 9 of:
53 * S. Haykin, Adaptive Filter Theory, Upper Saddle River, NJ:
54 * Prentice Hall, 1996.
55 */
57{
58protected:
59 virtual gr_complex error(const gr_complex& out) = 0;
60 virtual void update_tap(gr_complex& tap, const gr_complex& in) = 0;
61
62public:
63 // gr::digital::lms_dd_equalizer_cc::sptr
64 typedef std::shared_ptr<lms_dd_equalizer_cc> sptr;
65
66 /*!
67 * Make an LMS decision-directed equalizer
68 *
69 * \param num_taps Number of taps in the equalizer (channel size)
70 * \param mu Gain of the update loop
71 * \param sps Number of samples per symbol of the input signal
72 * \param cnst A constellation derived from class
73 * 'constellation'. Use base() method to get a shared pointer to
74 * this base class type.
75 */
76 static sptr make(int num_taps, float mu, int sps, constellation_sptr cnst);
77
78 virtual void set_taps(const std::vector<gr_complex>& taps) = 0;
79 virtual std::vector<gr_complex> taps() const = 0;
80 virtual float gain() const = 0;
81 virtual void set_gain(float mu) = 0;
82};
83
84} /* namespace digital */
85} /* namespace gr */
86
87#endif /* INCLUDED_DIGITAL_LMS_DD_EQUALIZER_CC_H */
Least-Mean-Square Decision Directed Equalizer (complex in/out)
Definition: lms_dd_equalizer_cc.h:57
std::shared_ptr< lms_dd_equalizer_cc > sptr
Definition: lms_dd_equalizer_cc.h:64
virtual gr_complex error(const gr_complex &out)=0
virtual std::vector< gr_complex > taps() const =0
virtual void set_gain(float mu)=0
virtual float gain() const =0
virtual void set_taps(const std::vector< gr_complex > &taps)=0
static sptr make(int num_taps, float mu, int sps, constellation_sptr cnst)
virtual void update_tap(gr_complex &tap, const gr_complex &in)=0
synchronous N:1 input to output with history
Definition: sync_decimator.h:26
#define DIGITAL_API
Definition: gr-digital/include/gnuradio/digital/api.h:18
std::complex< float > gr_complex
Definition: gr_complex.h:15
static constexpr float taps[NSTEPS+1][NTAPS]
Definition: interpolator_taps.h:9
GNU Radio logging wrapper for log4cpp library (C++ port of log4j)
Definition: basic_block.h:29