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#!/usr/bin/env python
#
# Copyright 2015 Free Software Foundation, Inc.
#
# 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.
#
import numpy as np
from common import PolarCommon
# for dev
from encoder import PolarEncoder
from matplotlib import pyplot as plt
class PolarDecoder(PolarCommon):
def __init__(self, n, k, frozen_bit_position, frozenbits=None):
PolarCommon.__init__(self, n, k, frozen_bit_position, frozenbits)
self.error_probability = 0.1 # this is kind of a dummy value. usually chosen individually.
self.bsc_lr = ((1 - self.error_probability) / self.error_probability, self.error_probability / (1 - self.error_probability))
self.bsc_llrs = np.log(self.bsc_lr)
def _llr_bit(self, bit):
return self.bsc_llrs[bit]
def _llr_odd(self, la, lb):
# this functions uses the min-sum approximation
# exact formula: np.log((np.exp(la + lb) + 1) / (np.exp(la) + np.exp(lb)))
return np.sign(la) * np.sign(lb) * np.minimum(np.abs(la), np.abs(lb))
_f_vals = np.array((1.0, -1.0), dtype=float)
def _llr_even(self, la, lb, f):
return (la * self._f_vals[f]) + lb
def _llr_bit_decision(self, llr):
if llr < 0.0:
ui = int(1)
else:
ui = int(0)
return ui
def _retrieve_bit_from_llr(self, lr, pos):
f_index = np.where(self.frozen_bit_position == pos)[0]
if not f_index.size == 0:
ui = self.frozenbits[f_index][0]
else:
ui = self._llr_bit_decision(lr)
return ui
def _lr_bit(self, bit):
return self.bsc_lr[bit]
def _lr_odd(self, la, lb):
# la is upper branch and lb is lower branch
return (la * lb + 1) / (la + lb)
def _lr_even(self, la, lb, f):
# la is upper branch and lb is lower branch, f is last decoded bit.
return (la ** (1 - (2 * f))) * lb
def _lr_bit_decision(self, lr):
if lr < 1:
return int(1)
return int(0)
def _get_even_indices_values(self, u_hat):
# looks like overkill for some indexing, but zero and one based indexing mix-up gives you haedaches.
return u_hat[1::2]
def _get_odd_indices_values(self, u_hat):
return u_hat[0::2]
def _calculate_lrs(self, y, u):
ue = self._get_even_indices_values(u)
uo = self._get_odd_indices_values(u)
ya = y[0:y.size//2]
yb = y[(y.size//2):]
la = self._lr_decision_element(ya, (ue + uo) % 2)
lb = self._lr_decision_element(yb, ue)
return la, lb
def _lr_decision_element(self, y, u):
if y.size == 1:
return self._llr_bit(y[0])
if u.size % 2 == 0: # use odd branch formula
la, lb = self._calculate_lrs(y, u)
return self._llr_odd(la, lb)
else:
ui = u[-1]
la, lb = self._calculate_lrs(y, u[0:-1])
return self._llr_even(la, lb, ui)
def _retrieve_bit_from_lr(self, lr, pos):
f_index = np.where(self.frozen_bit_position == pos)[0]
if not f_index.size == 0:
ui = self.frozenbits[f_index][0]
else:
ui = self._lr_bit_decision(lr)
return ui
def _lr_sc_decoder(self, y):
# this is the standard SC decoder as derived from the formulas. It sticks to natural bit order.
u = np.array([], dtype=int)
for i in range(y.size):
lr = self._lr_decision_element(y, u)
ui = self._retrieve_bit_from_llr(lr, i)
u = np.append(u, ui)
return u
def _llr_retrieve_bit(self, llr, pos):
f_index = np.where(self.frozen_bit_position == pos)[0]
if not f_index.size == 0:
ui = self.frozenbits[f_index][0]
else:
ui = self._llr_bit_decision(llr)
return ui
def _butterfly_decode_bits(self, pos, graph, u):
bit_num = u.size
llr = graph[pos][0]
ui = self._llr_retrieve_bit(llr, bit_num)
# ui = self._llr_bit_decision(llr)
u = np.append(u, ui)
lower_right = pos + (self.N // 2)
la = graph[pos][1]
lb = graph[lower_right][1]
graph[lower_right][0] = self._llr_even(la, lb, ui)
llr = graph[lower_right][0]
# ui = self._llr_bit_decision(llr)
ui = self._llr_retrieve_bit(llr, u.size)
u = np.append(u, ui)
return graph, u
def _lr_sc_decoder_efficient(self, y):
graph = np.full((self.N, self.power + 1), np.NaN, dtype=float)
for i in range(self.N):
graph[i][self.power] = self._llr_bit(y[i])
decode_order = self._vector_bit_reversed(np.arange(self.N), self.power)
decode_order = np.delete(decode_order, np.where(decode_order >= self.N // 2))
u = np.array([], dtype=int)
for pos in decode_order:
graph = self._butterfly(pos, 0, graph, u)
graph, u = self._butterfly_decode_bits(pos, graph, u)
return u
def _stop_propagation(self, bf_entry_row, stage):
# calculate break condition
modulus = 2 ** (self.power - stage)
# stage_size = self.N // (2 ** stage)
# half_stage_size = stage_size // 2
half_stage_size = self.N // (2 ** (stage + 1))
stage_pos = bf_entry_row % modulus
return stage_pos >= half_stage_size
def _butterfly(self, bf_entry_row, stage, graph, u):
if not self.power > stage:
return graph
if self._stop_propagation(bf_entry_row, stage):
upper_right = bf_entry_row - self.N // (2 ** (stage + 1))
la = graph[upper_right][stage + 1]
lb = graph[bf_entry_row][stage + 1]
ui = u[-1]
graph[bf_entry_row][stage] = self._llr_even(la, lb, ui)
return graph
# activate right side butterflies
u_even = self._get_even_indices_values(u)
u_odd = self._get_odd_indices_values(u)
graph = self._butterfly(bf_entry_row, stage + 1, graph, (u_even + u_odd) % 2)
lower_right = bf_entry_row + self.N // (2 ** (stage + 1))
graph = self._butterfly(lower_right, stage + 1, graph, u_even)
la = graph[bf_entry_row][stage + 1]
lb = graph[lower_right][stage + 1]
graph[bf_entry_row][stage] = self._llr_odd(la, lb)
return graph
def decode(self, data, is_packed=False):
if not len(data) == self.N:
raise ValueError("len(data)={0} is not equal to n={1}!".format(len(data), self.N))
if is_packed:
data = np.unpackbits(data)
data = self._lr_sc_decoder_efficient(data)
data = self._extract_info_bits(data)
if is_packed:
data = np.packbits(data)
return data
def test_reverse_enc_dec():
n = 16
k = 8
frozenbits = np.zeros(n - k)
frozenbitposition = np.array((0, 1, 2, 3, 4, 5, 8, 9), dtype=int)
bits = np.random.randint(2, size=k)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
encoded = encoder.encode(bits)
print 'encoded:', encoded
rx = decoder.decode(encoded)
print 'bits:', bits
print 'rx :', rx
print (bits == rx).all()
def compare_decoder_impls():
print '\nthis is decoder test'
n = 8
k = 4
frozenbits = np.zeros(n - k)
# frozenbitposition16 = np.array((0, 1, 2, 3, 4, 5, 8, 9), dtype=int)
frozenbitposition = np.array((0, 1, 2, 4), dtype=int)
bits = np.random.randint(2, size=k)
print 'bits:', bits
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
encoded = encoder.encode(bits)
print 'encoded:', encoded
rx_st = decoder._lr_sc_decoder(encoded)
rx_eff = decoder._lr_sc_decoder_efficient(encoded)
print 'standard :', rx_st
print 'efficient:', rx_eff
print (rx_st == rx_eff).all()
def main():
power = 3
n = 2 ** power
k = 4
frozenbits = np.zeros(n - k, dtype=int)
frozenbitposition = np.array((0, 1, 2, 4), dtype=int)
frozenbitposition4 = np.array((0, 1), dtype=int)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
bits = np.ones(k, dtype=int)
print "bits: ", bits
evec = encoder.encode(bits)
print "froz: ", encoder._insert_frozen_bits(bits)
print "evec: ", evec
evec[1] = 0
deced = decoder._lr_sc_decoder(evec)
print 'SC decoded:', deced
test_reverse_enc_dec()
compare_decoder_impls()
if __name__ == '__main__':
main()
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