An abstracted constellation object. More...
#include <gnuradio/digital/constellation.h>
Public Types | |
enum | normalization_t { NO_NORMALIZATION , POWER_NORMALIZATION , AMPLITUDE_NORMALIZATION } |
Public Member Functions | |
constellation (std::vector< gr_complex > constell, std::vector< int > pre_diff_code, unsigned int rotational_symmetry, unsigned int dimensionality, normalization_t normalization=AMPLITUDE_NORMALIZATION, float npwr=1.0) | |
constellation () | |
virtual | ~constellation () |
void | normalize (normalization_t normalization) |
Normalizes the constellation. More... | |
void | map_to_points (unsigned int value, gr_complex *points) |
Returns the constellation points for a symbol value. More... | |
std::vector< gr_complex > | map_to_points_v (unsigned int value) |
virtual unsigned int | decision_maker (const gr_complex *sample)=0 |
Returns the constellation point that matches best. More... | |
unsigned int | decision_maker_v (std::vector< gr_complex > sample) |
Takes a vector rather than a pointer. Better for SWIG wrapping. More... | |
unsigned int | decision_maker_pe (const gr_complex *sample, float *phase_error) |
Also calculates the phase error. More... | |
virtual void | calc_metric (const gr_complex *sample, float *metric, gr::digital::trellis_metric_type_t type) |
Calculates distance. More... | |
virtual void | calc_euclidean_metric (const gr_complex *sample, float *metric) |
virtual void | calc_hard_symbol_metric (const gr_complex *sample, float *metric) |
std::vector< gr_complex > | points () |
Returns the set of points in this constellation. More... | |
std::vector< gr_complex > | s_points () |
Returns the vector of points in this constellation. Raise error if dimensionality is not one. More... | |
std::vector< std::vector< gr_complex > > | v_points () |
Returns a vector of vectors of points. More... | |
bool | apply_pre_diff_code () |
Whether to apply an encoding before doing differential encoding. (e.g. gray coding) More... | |
void | set_pre_diff_code (bool a) |
Whether to apply an encoding before doing differential encoding. (e.g. gray coding) More... | |
std::vector< int > | pre_diff_code () |
Returns the encoding to apply before differential encoding. More... | |
unsigned int | rotational_symmetry () |
Returns the order of rotational symmetry. More... | |
unsigned int | dimensionality () |
Returns the number of complex numbers in a single symbol. More... | |
unsigned int | bits_per_symbol () |
unsigned int | arity () |
constellation_sptr | base () |
pmt::pmt_t | as_pmt () |
void | gen_soft_dec_lut (int precision, float npwr=-1) |
Generates the soft decision LUT based on constellation and symbol map. More... | |
virtual std::vector< float > | calc_soft_dec (gr_complex sample, float npwr=-1) |
Calculate soft decisions for the given sample . More... | |
void | set_soft_dec_lut (const std::vector< std::vector< float >> &soft_dec_lut, int precision) |
Define a soft decision look-up table. More... | |
void | set_npwr (float npwr) |
Sets the constellation noise power and recalculates LUT given npwr . More... | |
bool | has_soft_dec_lut () |
Returns True if the soft decision LUT has been defined, False otherwise. More... | |
std::vector< std::vector< float > > | soft_dec_lut () |
std::vector< float > | soft_decision_maker (gr_complex sample) |
Returns the soft decisions for the given sample . More... | |
Protected Member Functions | |
float | get_distance (unsigned int index, const gr_complex *sample) |
unsigned int | get_closest_point (const gr_complex *sample) |
void | calc_arity () |
void | max_min_axes () |
Protected Attributes | |
std::vector< gr_complex > | d_constellation |
std::vector< int > | d_pre_diff_code |
bool | d_apply_pre_diff_code |
unsigned int | d_rotational_symmetry |
unsigned int | d_dimensionality |
unsigned int | d_arity |
float | d_scalefactor |
The factor by which the user given constellation points were scaled by to achieve an average amplitude of 1. More... | |
float | d_maxamp |
float | d_re_min |
float | d_re_max |
float | d_im_min |
float | d_im_max |
std::vector< std::vector< float > > | d_soft_dec_lut |
int | d_lut_precision |
float | d_lut_scale |
float | d_npwr |
float | d_padding |
bool | d_use_external_lut |
An abstracted constellation object.
The constellation objects hold the necessary information to pass around constellation information for modulators and demodulators. These objects contain the mapping between the bits and the constellation points used to represent them as well as methods for slicing the symbol space. Various implementations are possible for efficiency and ease of use.
Standard constellations (BPSK, QPSK, QAM, etc) can be inherited from this class and overloaded to perform optimized slicing and constellation mappings.
gr::digital::constellation::constellation | ( | std::vector< gr_complex > | constell, |
std::vector< int > | pre_diff_code, | ||
unsigned int | rotational_symmetry, | ||
unsigned int | dimensionality, | ||
normalization_t | normalization = AMPLITUDE_NORMALIZATION , |
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float | npwr = 1.0 |
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gr::digital::constellation::constellation | ( | ) |
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Whether to apply an encoding before doing differential encoding. (e.g. gray coding)
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References pmt::make_any().
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Calculates distance.
Calculates metrics for all points in the constellation. For use with the viterbi algorithm.
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Calculate soft decisions for the given sample
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Calculate the soft decisions from the given sample
at the given noise power npwr
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This is a very costly algorithm (especially for higher order modulations) and should be used sparingly. It uses the gen_soft_dec_lut function to generate the LUT, which should be done once or if a large change in the noise floor is detected.
Instead of using this function, generate the LUT using the gen_soft_dec_lut after creating the constellation object and then use the soft_decision_maker function to return the answer from the LUT.
sample | The complex sample to get the soft decisions. |
npwr | estimate of the noise power, defaults to -1 which will use class member. |
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Returns the constellation point that matches best.
Implemented in gr::digital::constellation_16qam, gr::digital::constellation_8psk_natural, gr::digital::constellation_8psk, gr::digital::constellation_dqpsk, gr::digital::constellation_qpsk, gr::digital::constellation_bpsk, gr::digital::constellation_sector, and gr::digital::constellation_calcdist.
unsigned int gr::digital::constellation::decision_maker_pe | ( | const gr_complex * | sample, |
float * | phase_error | ||
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Also calculates the phase error.
unsigned int gr::digital::constellation::decision_maker_v | ( | std::vector< gr_complex > | sample | ) |
Takes a vector rather than a pointer. Better for SWIG wrapping.
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Returns the number of complex numbers in a single symbol.
void gr::digital::constellation::gen_soft_dec_lut | ( | int | precision, |
float | npwr = -1 |
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Generates the soft decision LUT based on constellation and symbol map.
Generates the soft decision LUT based on constellation and symbol map. It can be given a estimate of the noise power in the channel as npwr
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precision | Number of bits of precision on each axis. |
npwr | Estimate of the noise power (if known), defaults to -1 which will use class member. |
This is expensive to compute.
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bool gr::digital::constellation::has_soft_dec_lut | ( | ) |
Returns True if the soft decision LUT has been defined, False otherwise.
void gr::digital::constellation::map_to_points | ( | unsigned int | value, |
gr_complex * | points | ||
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Returns the constellation points for a symbol value.
std::vector<gr_complex> gr::digital::constellation::map_to_points_v | ( | unsigned int | value | ) |
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void gr::digital::constellation::normalize | ( | normalization_t | normalization | ) |
Normalizes the constellation.
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Returns the set of points in this constellation.
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Returns the encoding to apply before differential encoding.
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Returns the order of rotational symmetry.
std::vector<gr_complex> gr::digital::constellation::s_points | ( | ) |
Returns the vector of points in this constellation. Raise error if dimensionality is not one.
void gr::digital::constellation::set_npwr | ( | float | npwr | ) |
Sets the constellation noise power and recalculates LUT given npwr
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Sets the constellation noise power and recalculates LUT given npwr
. If a LUT was defined via manual entry of a table, it will be a left alone. Otherwise, the LUT will be recalculated with the new noise power. This member is used by calc_soft_dec primarily.
npwr | The noise power to use for soft decisions |
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Whether to apply an encoding before doing differential encoding. (e.g. gray coding)
void gr::digital::constellation::set_soft_dec_lut | ( | const std::vector< std::vector< float >> & | soft_dec_lut, |
int | precision | ||
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Define a soft decision look-up table.
Define a soft decision look-up table (LUT). Because soft decisions can be calculated in various ways with various levels of accuracy and complexity, this function allows users to create a LUT in their own way.
Setting the LUT here means that has_soft_dec_lut will return true. Decision vectors returned by soft_decision_maker will be calculated using this LUT.
soft_dec_lut | The soft decision LUT as a vector of tuples (vectors in C++) of soft decisions. Each element of the LUT is a vector of k-bit floats (where there are k bits/sample in the constellation). |
precision | The number of bits of precision used when generating the LUT. |
std::vector<std::vector<float> > gr::digital::constellation::soft_dec_lut | ( | ) |
std::vector<float> gr::digital::constellation::soft_decision_maker | ( | gr_complex | sample | ) |
Returns the soft decisions for the given sample
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Returns the soft decisions for the given sample
. If a LUT is defined for the object, the decisions will be calculated from there. Otherwise, this function will call calc_soft_dec directly to calculate the soft decisions.
sample | The complex sample to get the soft decisions. |
std::vector<std::vector<gr_complex> > gr::digital::constellation::v_points | ( | ) |
Returns a vector of vectors of points.
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The factor by which the user given constellation points were scaled by to achieve an average amplitude of 1.
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