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adaptive DFE and added frequency offset tracking added

This commit is contained in:
cmayer 2018-10-26 22:06:21 +02:00
parent cdbe8dcd88
commit 0fb4b1336f
7 changed files with 2844 additions and 40 deletions

View file

@ -22,6 +22,7 @@
# Project setup
########################################################################
cmake_minimum_required(VERSION 2.6)
set(CMAKE_CXX_STANDARD 11)
project(gr-digitalhf CXX C)
enable_testing()
@ -148,7 +149,7 @@ find_package(Doxygen)
# components required to the list of GR_REQUIRED_COMPONENTS (in all
# caps such as FILTER or FFT) and change the version to the minimum
# API compatible version required.
set(GR_REQUIRED_COMPONENTS RUNTIME DIGITAL)
set(GR_REQUIRED_COMPONENTS RUNTIME DIGITAL VOLK)
find_package(Gnuradio "3.7.2" REQUIRED)
list(INSERT CMAKE_MODULE_PATH 0 ${CMAKE_SOURCE_DIR}/cmake/Modules)
include(GrVersion)

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@ -117,7 +117,7 @@
</param>
<param>
<key>value</key>
<value>10*sps</value>
<value>12*sps</value>
</param>
</block>
<block>
@ -144,7 +144,7 @@
</param>
<param>
<key>value</key>
<value>5*sps</value>
<value>12*sps</value>
</param>
</block>
<block>
@ -395,6 +395,14 @@
<key>id</key>
<value>digitalhf_adaptive_dfe_0</value>
</param>
<param>
<key>maxoutbuf</key>
<value>0</value>
</param>
<param>
<key>minoutbuf</key>
<value>0</value>
</param>
<param>
<key>sps</key>
<value>sps</value>
@ -416,6 +424,373 @@
<value>STANAG_4285</value>
</param>
</block>
<block>
<key>qtgui_time_sink_x</key>
<param>
<key>autoscale</key>
<value>False</value>
</param>
<param>
<key>axislabels</key>
<value>True</value>
</param>
<param>
<key>alias</key>
<value></value>
</param>
<param>
<key>comment</key>
<value></value>
</param>
<param>
<key>ctrlpanel</key>
<value>False</value>
</param>
<param>
<key>affinity</key>
<value></value>
</param>
<param>
<key>entags</key>
<value>True</value>
</param>
<param>
<key>_enabled</key>
<value>True</value>
</param>
<param>
<key>_coordinate</key>
<value>(874, 176)</value>
</param>
<param>
<key>gui_hint</key>
<value></value>
</param>
<param>
<key>_rotation</key>
<value>0</value>
</param>
<param>
<key>grid</key>
<value>False</value>
</param>
<param>
<key>id</key>
<value>qtgui_time_sink_x_0</value>
</param>
<param>
<key>legend</key>
<value>True</value>
</param>
<param>
<key>alpha1</key>
<value>1.0</value>
</param>
<param>
<key>color1</key>
<value>"blue"</value>
</param>
<param>
<key>label1</key>
<value></value>
</param>
<param>
<key>marker1</key>
<value>-1</value>
</param>
<param>
<key>style1</key>
<value>1</value>
</param>
<param>
<key>width1</key>
<value>1</value>
</param>
<param>
<key>alpha10</key>
<value>1.0</value>
</param>
<param>
<key>color10</key>
<value>"blue"</value>
</param>
<param>
<key>label10</key>
<value></value>
</param>
<param>
<key>marker10</key>
<value>-1</value>
</param>
<param>
<key>style10</key>
<value>1</value>
</param>
<param>
<key>width10</key>
<value>1</value>
</param>
<param>
<key>alpha2</key>
<value>1.0</value>
</param>
<param>
<key>color2</key>
<value>"red"</value>
</param>
<param>
<key>label2</key>
<value></value>
</param>
<param>
<key>marker2</key>
<value>-1</value>
</param>
<param>
<key>style2</key>
<value>1</value>
</param>
<param>
<key>width2</key>
<value>1</value>
</param>
<param>
<key>alpha3</key>
<value>1.0</value>
</param>
<param>
<key>color3</key>
<value>"green"</value>
</param>
<param>
<key>label3</key>
<value></value>
</param>
<param>
<key>marker3</key>
<value>-1</value>
</param>
<param>
<key>style3</key>
<value>1</value>
</param>
<param>
<key>width3</key>
<value>1</value>
</param>
<param>
<key>alpha4</key>
<value>1.0</value>
</param>
<param>
<key>color4</key>
<value>"black"</value>
</param>
<param>
<key>label4</key>
<value></value>
</param>
<param>
<key>marker4</key>
<value>-1</value>
</param>
<param>
<key>style4</key>
<value>1</value>
</param>
<param>
<key>width4</key>
<value>1</value>
</param>
<param>
<key>alpha5</key>
<value>1.0</value>
</param>
<param>
<key>color5</key>
<value>"cyan"</value>
</param>
<param>
<key>label5</key>
<value></value>
</param>
<param>
<key>marker5</key>
<value>-1</value>
</param>
<param>
<key>style5</key>
<value>1</value>
</param>
<param>
<key>width5</key>
<value>1</value>
</param>
<param>
<key>alpha6</key>
<value>1.0</value>
</param>
<param>
<key>color6</key>
<value>"magenta"</value>
</param>
<param>
<key>label6</key>
<value></value>
</param>
<param>
<key>marker6</key>
<value>-1</value>
</param>
<param>
<key>style6</key>
<value>1</value>
</param>
<param>
<key>width6</key>
<value>1</value>
</param>
<param>
<key>alpha7</key>
<value>1.0</value>
</param>
<param>
<key>color7</key>
<value>"yellow"</value>
</param>
<param>
<key>label7</key>
<value></value>
</param>
<param>
<key>marker7</key>
<value>-1</value>
</param>
<param>
<key>style7</key>
<value>1</value>
</param>
<param>
<key>width7</key>
<value>1</value>
</param>
<param>
<key>alpha8</key>
<value>1.0</value>
</param>
<param>
<key>color8</key>
<value>"dark red"</value>
</param>
<param>
<key>label8</key>
<value></value>
</param>
<param>
<key>marker8</key>
<value>-1</value>
</param>
<param>
<key>style8</key>
<value>1</value>
</param>
<param>
<key>width8</key>
<value>1</value>
</param>
<param>
<key>alpha9</key>
<value>1.0</value>
</param>
<param>
<key>color9</key>
<value>"dark green"</value>
</param>
<param>
<key>label9</key>
<value></value>
</param>
<param>
<key>marker9</key>
<value>-1</value>
</param>
<param>
<key>style9</key>
<value>1</value>
</param>
<param>
<key>width9</key>
<value>1</value>
</param>
<param>
<key>name</key>
<value>""</value>
</param>
<param>
<key>nconnections</key>
<value>1</value>
</param>
<param>
<key>size</key>
<value>1024</value>
</param>
<param>
<key>srate</key>
<value>samp_rate</value>
</param>
<param>
<key>stemplot</key>
<value>False</value>
</param>
<param>
<key>tr_chan</key>
<value>0</value>
</param>
<param>
<key>tr_delay</key>
<value>0</value>
</param>
<param>
<key>tr_level</key>
<value>0.0</value>
</param>
<param>
<key>tr_mode</key>
<value>qtgui.TRIG_MODE_FREE</value>
</param>
<param>
<key>tr_slope</key>
<value>qtgui.TRIG_SLOPE_POS</value>
</param>
<param>
<key>tr_tag</key>
<value>""</value>
</param>
<param>
<key>type</key>
<value>complex</value>
</param>
<param>
<key>update_time</key>
<value>0.10</value>
</param>
<param>
<key>ylabel</key>
<value>Amplitude</value>
</param>
<param>
<key>yunit</key>
<value>""</value>
</param>
<param>
<key>ymax</key>
<value>1</value>
</param>
<param>
<key>ymin</key>
<value>-1</value>
</param>
</block>
<connection>
<source_block_id>analog_noise_source_x_0</source_block_id>
<sink_block_id>blocks_throttle_0</sink_block_id>
@ -428,4 +803,10 @@
<source_key>0</source_key>
<sink_key>0</sink_key>
</connection>
<connection>
<source_block_id>digitalhf_adaptive_dfe_0</source_block_id>
<sink_block_id>qtgui_time_sink_x_0</sink_block_id>
<source_key>0</source_key>
<sink_key>0</sink_key>
</connection>
</flow_graph>

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examples/test_cc.grc Normal file

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@ -51,8 +51,9 @@
* type
* vlen
* optional (set to 1 for optional inputs) -->
<!-- <source> -->
<!-- <name>out</name> -->
<!-- <type><!-\- e.g. int, float, complex, byte, short, xxx_vector, ...-\-></type> -->
<!-- </source> -->
<source>
<name>out</name>
<type>complex</type>
<!-- byte, short, xxx_vector -->
</source>
</block>

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@ -23,6 +23,7 @@
#endif
#include <gnuradio/io_signature.h>
#include <volk/volk.h>
#include "adaptive_dfe_impl.h"
namespace gr {
@ -31,7 +32,7 @@ namespace digitalhf {
namespace {
class GILLock {
PyGILState_STATE _state;
public:
public:
GILLock()
:_state(PyGILState_Ensure()) {}
~GILLock() {
@ -39,6 +40,7 @@ class GILLock {
}
} ;
}
adaptive_dfe::sptr
adaptive_dfe::make(int sps, // samples per symbol
int nB, // number of forward FIR taps
@ -60,29 +62,35 @@ adaptive_dfe_impl::adaptive_dfe_impl(int sps, // samples per symbol
std::string python_module_name)
: gr::block("adaptive_dfe",
gr::io_signature::make(1, 1, sizeof(gr_complex)),
gr::io_signature::make(0, 0, sizeof(gr_complex)))
gr::io_signature::make(1, 1, sizeof(gr_complex)))
, _sps(sps)
, _nB(nB)
, _nF(nF)
, _nW(nW)
, _mu(0.01)
, _alpha(0.0005)
, _py_module_name(python_module_name)
, _physicalLayer()
, _taps_samples(nB+nF+1)
, _taps_symbols(nW)
, _taps_samples(nullptr)
, _taps_symbols(nullptr)
, _hist_samples(nullptr)
, _hist_symbols(nullptr)
, _hist_sample_index(0)
, _hist_symbol_index(0)
, _sample_counter(0)
, _constellations()
, _constellation_index()
, _symbols()
, _scramble()
, _descrambled_symbols()
, _symbol_counter(0)
, _sum_phase_diff(0)
, _df(0)
, _phase(0)
, _b{0.338187046465954, -0.288839024460507}
, _ud(0)
, _state(WAIT_FOR_PREAMBLE)
{
// make sure python is ready for threading
if( Py_IsInitialized() ){
if(PyEval_ThreadsInitialized() != 1 ){
PyEval_InitThreads();
}
boost::python::numpy::initialize();
} else {
throw std::runtime_error("dont use es_pyhandler without python!");
}
}
/*
@ -95,7 +103,7 @@ adaptive_dfe_impl::~adaptive_dfe_impl()
void
adaptive_dfe_impl::forecast (int noutput_items, gr_vector_int &ninput_items_required)
{
/* <+forecast+> e.g. ninput_items_required[0] = noutput_items */
ninput_items_required[0] = _sps*noutput_items;
}
int
@ -104,21 +112,177 @@ adaptive_dfe_impl::general_work(int noutput_items,
gr_vector_const_void_star &input_items,
gr_vector_void_star &output_items)
{
gr::thread::scoped_lock lock(d_setlock);
gr_complex const* in = (gr_complex const *)input_items[0];
gr_complex *out = (gr_complex *)output_items[0];
int nout = 0;
int i = 0;
for (; i<ninput_items[0] && nout < noutput_items; ++i) {
assert(nout < noutput_items);
_phase += _df;
if (_phase > M_PI)
_phase -= 2*M_PI;
if (_phase < -M_PI)
_phase += 2*M_PI;
_hist_samples[_hist_sample_index] = _hist_samples[_hist_sample_index+_nB+_nF+1] = in[i] * std::exp(gr_complex(0,_phase));
if (++_hist_sample_index == _nB+_nF+1)
_hist_sample_index = 0;
if (_state == WAIT_FOR_PREAMBLE) {
std::vector<tag_t> v;
get_tags_in_window(v, 0, i,i+1);
float phase_est = 0;
float corr_est = 0;
uint64_t offset = 0;
for (int j=0; j<v.size(); ++j) {
std::cout << "tag " << v[j].key << " " << v[j].offset-nitems_read(0) << std::endl;
if (v[j].key == pmt::mp("phase_est")) {
phase_est = pmt::to_double(v[j].value);
std::cout << "phase_est " << v[j].offset <<" " << nitems_read(0) << " " << phase_est << std::endl;
}
if (v[j].key == pmt::mp("corr_est")) {
corr_est = pmt::to_double(v[j].value);
std::cout << "corr_est " << v[j].offset << " " << nitems_read(0) << " "
<< pmt::is_number(v[j].value) << " "
<< pmt::is_integer(v[j].value) << " "
<< pmt::is_real(v[j].value) << " "
<< pmt::to_double(v[j].value)
<< std::endl;
if (corr_est > 130e3) {
offset = v[j].offset - nitems_read(0);
break;
}
}
}
if (corr_est > 130e3) {
_state = DO_FILTER;
_sample_counter = 0;
_symbol_counter = 0;
// _symbols.clear();
// _scramble.clear();
_descrambled_symbols.clear();
// _hist_sample_index = 0;
_hist_symbol_index = 0;
std::fill_n(_hist_symbols, 2*_nW, gr_complex(0));
std::fill_n(_taps_samples, _nB+_nF+1, gr_complex(0));
std::fill_n(_taps_symbols, _nW, gr_complex(0));
//_phase = -phase_est;
_taps_samples[_nB+1] = std::exp(gr_complex(0, -phase_est));
_taps_symbols[0] = 1;
GILLock lock;
// TODO: wait for preamble correlation tag etc...
try {
update_frame_information(_physicalLayer.attr("get_frame")());
update_doppler_information(_physicalLayer.attr("get_doppler")()); // symbols
} catch (boost::python::error_already_set const&) {
PyErr_Print();
}
}
}
if (_state == DO_FILTER) {
gr_complex dot_samples = 0;
// volk_32fc_x2_dot_prod_32fc(&dot_samples,
// &_hist_samples.front()+_hist_sample_index,
// &_taps_samples.front(),
// _taps_samples.size());
gr_complex filter_output = dot_samples;
// if (_sample_counter < 80*5)
// std::cout << "SAMPLE " << _sample_counter << " " << dot_samples << std::endl;
if ((_sample_counter%_sps) == 0) {
if (_symbol_counter == _symbols.size()) {
_symbol_counter = 0;
GILLock lock;
try {
boost::python::numpy::ndarray s = boost::python::numpy::from_data(&_descrambled_symbols.front(),
boost::python::numpy::dtype::get_builtin<gr_complex>(),
boost::python::make_tuple(_descrambled_symbols.size()),
boost::python::make_tuple(sizeof(gr_complex)),
boost::python::object());
update_doppler_information(_physicalLayer.attr("get_doppler")(s));
update_frame_information(_physicalLayer.attr("get_frame")());
} catch (boost::python::error_already_set const&) {
PyErr_Print();
}
}
gr_complex known_symbol = _symbols[_symbol_counter];
bool is_known = true;
for (int k=0; k<1; ++k) {
filter_output = 0;
#if 1
volk_32fc_x2_dot_prod_32fc(&filter_output,
_hist_samples+_hist_sample_index,
_taps_samples,
_nB+_nF+1);
#else
for (int l=0; l<_nB+_nF+1; ++l) {
assert(_hist_sample_index+l < 2*(_nB+_nF+1));
filter_output += _hist_samples[_hist_sample_index+l]*_taps_samples[l];
}
#endif
gr_complex dot_symbols=0;
for (int l=0; l<_nW; ++l) {
assert(_hist_symbol_index+l < 2*_nW);
dot_symbols += _hist_symbols[_hist_symbol_index+l]*_taps_symbols[l];
}
filter_output += dot_symbols;
if (std::abs(known_symbol) < 1e-5) { // not known
is_known = false;
gr_complex descrambled_filter_output = std::conj(_scramble[_symbol_counter]) * filter_output;
gr::digital::constellation_sptr constell = _constellations[_constellation_index];
unsigned int jc = constell->decision_maker(&descrambled_filter_output);
constell->map_to_points(jc, &descrambled_filter_output);
known_symbol = _scramble[_symbol_counter] * descrambled_filter_output;
}
gr_complex err = filter_output - known_symbol;
if (_symbol_counter >= 0) {
for (int j=0; j<_nB+_nF+1; ++j) {
_taps_samples[j] -= _mu*err*std::conj(_hist_samples[_hist_sample_index+j]);
}
for (int j=0; j<_nW; ++j) {
assert(_hist_symbol_index+j < 2*_nW);
_taps_symbols[j] -= _mu*err*std::conj(_hist_symbols[_hist_symbol_index+j]) + _alpha*_taps_symbols[j];
}
}
// std::cout << "filter: " << _symbol_counter << " " << _sample_counter << " " << filter_output << " " << known_symbol << " " << std::abs(err) << std::endl;
}
if (is_known) {
_taps_symbols[_hist_symbol_index] = _taps_symbols[_hist_symbol_index + _nW] = known_symbol;
if (++_hist_symbol_index == _nW)
_hist_symbol_index = 0;
}
_descrambled_symbols[_symbol_counter] = filter_output*std::conj(_scramble[_symbol_counter]);
out[nout++] = filter_output;
++_symbol_counter;
}
_sample_counter += 1;
}
}
consume_each (noutput_items);
consume(0, i);
// Tell runtime system how many output items we produced.
return noutput_items;
return nout;
}
bool adaptive_dfe_impl::start()
{
// make sure python is ready for threading
if( Py_IsInitialized() ){
GILLock lock;
if(PyEval_ThreadsInitialized() != 1 ){
PyEval_InitThreads();
}
boost::python::numpy::initialize();
} else {
throw std::runtime_error("dont use es_pyhandler without python!");
}
_taps_samples = (gr_complex*)(volk_malloc( (_nB+_nF+1)*sizeof(gr_complex), volk_get_alignment()));
_taps_symbols = (gr_complex*)(volk_malloc( _nW*sizeof(gr_complex), volk_get_alignment()));
_hist_samples = (gr_complex*)(volk_malloc(2*(_nB+_nF+1)*sizeof(gr_complex), volk_get_alignment()));
_hist_symbols = (gr_complex*)(volk_malloc( 2*_nW*sizeof(gr_complex), volk_get_alignment()));
_taps_samples[_nB+1] = 1;
_taps_symbols[0] = 1;
std::cout << "adaptive_dfe_impl::start()" << std::endl;
GILLock lock;
try {
@ -137,6 +301,10 @@ bool adaptive_dfe_impl::stop()
std::cout << "adaptive_dfe_impl::stop()" << std::endl;
GILLock lock;
_physicalLayer = boost::python::object();
volk_free(_taps_samples);
volk_free(_taps_symbols);
volk_free(_hist_samples);
volk_free(_hist_symbols);
return true;
}
@ -168,9 +336,11 @@ void adaptive_dfe_impl::update_frame_information(boost::python::object obj)
int const m = array.shape(0);
_symbols.resize(m);
_scramble.resize(m);
_descrambled_symbols.resize(m);
for (int i=0; i<m; ++i) {
std::memcpy(&_symbols[i], data+16*i, sizeof(gr_complex));
std::memcpy(&_scramble[i], data+16*i+8, sizeof(gr_complex));
// std::cout << "get_frame " << i << " " << _symbols[i] << " " << _scramble[i] << std::endl;
}
_constellation_index = boost::python::extract<int>(obj[1]);
}
@ -180,7 +350,17 @@ void adaptive_dfe_impl::update_doppler_information(boost::python::object obj)
assert(n==2);
double const do_continue = boost::python::extract<bool>(obj[0]);
double const doppler = boost::python::extract<float>(obj[1]);
// TODO
float delta_f = doppler/_sps;
if (_df == 0) { // init
_ud = _df = -delta_f;
} else {
const float ud_old = _ud;
_ud = -delta_f;
_df +=_b[0]*_ud + _b[1]*ud_old;
}
std::cout << "PLL: " << _df << " " << delta_f << std::endl;
_sum_phase_diff = 0;
}
} /* namespace digitalhf */

View file

@ -34,19 +34,42 @@ private:
int _sps;
int _nB, _nF, _nW;
float _mu;
float _alpha;
// module name w.r.t. digitalhf.physical_layer containing a PhysicalLayer class
std::string _py_module_name;
boost::python::object _physicalLayer; // class instance of physical layer description
std::vector<gr_complex> _taps_samples;
std::vector<gr_complex> _taps_symbols;
gr_complex* _taps_samples;
gr_complex* _taps_symbols;
gr_complex* _hist_samples;
gr_complex* _hist_symbols;
int _hist_sample_index;
int _hist_symbol_index;
std::size_t _sample_counter;
std::vector<gr::digital::constellation_sptr> _constellations;
int _constellation_index;
std::vector<gr_complex> _symbols;
std::vector<gr_complex> _scramble;
std::vector<gr_complex> _descrambled_symbols;
int _symbol_counter;
int _sample_counter;
// PLL for doppler tracking
float _sum_phase_diff;
float _df; // frequency offset in radians per sample
float _phase; // accumulated phase for frequency correction
const float _b[2];
float _ud;
enum state {
WAIT_FOR_PREAMBLE,
DO_FILTER
} _state;
void update_constellations(boost::python::object obj);
void update_frame_information(boost::python::object obj);

View file

@ -14,8 +14,9 @@ class PhysicalLayer(object):
self._preamble = [PhysicalLayer.get_preamble(), 0] ## BPSK
self._data = [PhysicalLayer.get_data(), mode] ## according to the mode
self._counter = 0
self._preamble_phases = []
def set_mode(self):
def set_mode(self, mode):
"""For STANAG 4258 the mode has to be set manually: mode=0 -> BPSK, mode=1 -> QPSK, mode=2 -> 8PSK"""
self._data[1] = mode
@ -24,17 +25,32 @@ class PhysicalLayer(object):
def get_frame(self):
"""returns the known+unknown symbols and scrambling"""
print('-------------------- get_frame --------------------',self._counter)
if self._counter == 0:
return self._preamble
x= self._preamble
else:
return self._data
x=self._data
print('get_frame end\n')
return x;
def get_doppler(self): ## symbols
def get_doppler(self, s):
"""used for doppler shift update, for determining which frame to provide next,
and for stopping at end of data/when the signal quality is too low"""
print('-------------------- get_doppler --------------------',self._counter)
doppler = 0
if self._counter == 0: ## preamble
corr = s*np.conj(self._preamble[0]['symb'])
self._preamble_phases.extend([np.angle(np.sum(corr))])
if len(self._preamble_phases) == 2 and False:
doppler = 2*(self._preamble_phases[1] - self._preamble_phases[0])/256
print('preamble_phases', self._preamble_phases, 'doppler', doppler)
self._preamble_phases = self._preamble_phases[1:]
else:
phases = np.unwrap(np.angle(corr))
doppler = 2*(np.median(phases[-20:]) - np.median(phases[:20]))/80
print('doppler', doppler,self._preamble_phases)
self._counter = (self._counter+1)&1
## TODO: doppler calculations
doppler = 0.1234
return [True, doppler]
@staticmethod
@ -67,9 +83,9 @@ class PhysicalLayer(object):
## PSK-8 modulation
constellation = PhysicalLayer.make_psk(8,range(8))['points']
a['scramble'] = constellation[p,]
a['symb'][ 32: 48] = 1 ## mini-probe 1
a['symb'][ 80: 96] = 1 ## mini-probe 2
a['symb'][128:144] = 1 ## mini-probe 3
a['symb'][ 32: 48] = a['scramble'][ 32: 48] ## mini-probe 1
a['symb'][ 80: 96] = a['scramble'][ 80: 96] ## mini-probe 2
a['symb'][128:144] = a['scramble'][128:144] ## mini-probe 3
return a
@staticmethod