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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2017 Moritz Luca Schmid, Communications Engineering Lab (CEL) / Karlsruhe Institute of Technology (KIT).
#
# This 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.
#
# This software 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 this software; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
from gnuradio import gr, blocks, trellis, digital
import gnuradio.dab as grdab
from math import sqrt
class msc_decode(gr.hier_block2):
"""
@brief block to extract and decode a sub-channel out of the MSC (Main Service Channel) of a demodulated transmission frame
- get MSC from byte stream
- repartition MSC to CIFs (Common Interleaved Frames)
- select a subchannel and extraxt it (dump rest of CIF)
- do time deinterleaving
- do convolutional decoding
- undo energy dispersal
- output data stream of one subchannel (packed bytes)
"""
def __init__(self, dab_params, address, size, protection, verbose=False, debug=False):
gr.hier_block2.__init__(self,
"msc_decode",
# Input signature
gr.io_signature(1, 1, gr.sizeof_float * dab_params.num_carriers * 2),
# Output signature
gr.io_signature(1, 1, gr.sizeof_char))
self.dp = dab_params
self.address = address
self.size = size
self.protect = protection
self.verbose = verbose
self.debug = debug
# calculate n factor (multiple of 8kbits etc.)
self.n = self.size / self.dp.subch_size_multiple_n[self.protect]
# calculate puncturing factors (EEP, table 33, 34)
self.msc_I = self.n * 192
if (self.n > 1 or self.protect != 1):
self.puncturing_L1 = [6 * self.n - 3, 2 * self.n - 3, 6 * self.n - 3, 4 * self.n - 3]
self.puncturing_L2 = [3, 4 * self.n + 3, 3, 2 * self.n + 3]
self.puncturing_PI1 = [24, 14, 8, 3]
self.puncturing_PI2 = [23, 13, 7, 2]
# calculate length of punctured codeword (11.3.2)
self.msc_punctured_codeword_length = self.puncturing_L1[self.protect] * 4 * self.dp.puncturing_vectors_ones[
self.puncturing_PI1[self.protect]] + self.puncturing_L2[self.protect] * 4 * \
self.dp.puncturing_vectors_ones[
self.puncturing_PI2[self.protect]] + 12
self.assembled_msc_puncturing_sequence = int(self.puncturing_L1[self.protect]) * 4 * self.dp.puncturing_vectors[
self.puncturing_PI1[self.protect]] + int(self.puncturing_L2[self.protect]) * 4 * self.dp.puncturing_vectors[
self.puncturing_PI2[self.protect]] + self.dp.puncturing_tail_vector
self.msc_conv_codeword_length = 4*self.msc_I + 24 # 4*I + 24 ()
# exception in table
else:
self.msc_punctured_codeword_length = 5 * 4 * self.dp.puncturing_vectors_ones[13] + 1 * 4 * \
self.dp.puncturing_vectors_ones[
12] + 12
#sanity check
assert(6*self.n == self.puncturing_L1[self.protect] + self.puncturing_L2[self.protect])
# MSC selection and block partitioning
# select OFDM carriers with MSC
self.select_msc_syms = grdab.select_vectors(gr.sizeof_float, self.dp.num_carriers * 2, self.dp.num_msc_syms,
self.dp.num_fic_syms)
# repartition MSC data in CIFs (left out due to heavy burden for scheduler and not really necessary)
#self.repartition_msc_to_CIFs = grdab.repartition_vectors(gr.sizeof_float, self.dp.num_carriers * 2,
# self.dp.cif_bits, self.dp.num_msc_syms,
# self.dp.num_cifs)
#repartition MSC to CUs
self.repartition_msc_to_cus = grdab.repartition_vectors(gr.sizeof_float, self.dp.num_carriers*2, self.dp.msc_cu_size, self.dp.num_msc_syms, self.dp.num_cus * self.dp.num_cifs)
# select CUs of one subchannel of each CIF and form logical frame vector
self.select_subch = grdab.select_subch_vfvf(self.dp.msc_cu_size, self.dp.msc_cu_size * self.size, self.address, self.dp.num_cus)
# time deinterleaving
self.time_v2s = blocks.vector_to_stream(gr.sizeof_float, int(self.dp.msc_cu_size * self.size))
self.time_deinterleaver = grdab.time_deinterleave_ff(self.dp.msc_cu_size * self.size, self.dp.scrambling_vector)
# unpuncture
self.conv_v2s = blocks.vector_to_stream(gr.sizeof_float, int(self.msc_punctured_codeword_length))
self.unpuncture = grdab.unpuncture_ff(self.assembled_msc_puncturing_sequence, 0)
# convolutional decoding
self.fsm = trellis.fsm(1, 4, [0o133, 0o171, 0o145, 0o133]) # OK (dumped to text and verified partially)
table = [
0, 0, 0, 0,
0, 0, 0, 1,
0, 0, 1, 0,
0, 0, 1, 1,
0, 1, 0, 0,
0, 1, 0, 1,
0, 1, 1, 0,
0, 1, 1, 1,
1, 0, 0, 0,
1, 0, 0, 1,
1, 0, 1, 0,
1, 0, 1, 1,
1, 1, 0, 0,
1, 1, 0, 1,
1, 1, 1, 0,
1, 1, 1, 1
]
assert (len(table) / 4 == self.fsm.O())
table = [(1 - 2 * x) / sqrt(2) for x in table]
self.conv_decode = trellis.viterbi_combined_fb(self.fsm, int(self.msc_I + self.dp.conv_code_add_bits_input), 0, 0, 4, table, digital.TRELLIS_EUCLIDEAN)
self.conv_s2v = blocks.stream_to_vector(gr.sizeof_char, int(self.msc_I + self.dp.conv_code_add_bits_input))
self.conv_prune = grdab.prune(gr.sizeof_char, int(self.msc_conv_codeword_length / 4), 0,
self.dp.conv_code_add_bits_input)
#energy descramble
self.prbs_src = blocks.vector_source_b(self.dp.prbs(int(self.msc_I)), True)
self.energy_v2s = blocks.vector_to_stream(gr.sizeof_char, int(self.msc_I))
self.add_mod_2 = blocks.xor_bb()
#self.energy_s2v = blocks.stream_to_vector(gr.sizeof_char, self.msc_I)
#pack bits
self.pack_bits = blocks.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
# connect blocks
self.connect((self, 0),
(self.select_msc_syms),
#(self.repartition_msc_to_CIFs, 0),
(self.repartition_msc_to_cus),
(self.select_subch, 0),
#(self.repartition_cus_to_logical_frame, 0),
self.time_v2s,
self.time_deinterleaver,
#self.conv_v2s,
self.unpuncture,
self.conv_decode,
#self.conv_s2v,
self.conv_prune,
#self.energy_v2s,
self.add_mod_2,
self.pack_bits,
#self.energy_s2v, #better output stream or vector??
(self))
self.connect(self.prbs_src, (self.add_mod_2, 1))
#debug
if debug is True:
#msc_select_syms
self.sink_msc_select_syms = blocks.file_sink(gr.sizeof_float * self.dp.num_carriers * 2, "debug/msc_select_syms.dat")
self.connect(self.select_msc_syms, self.sink_msc_select_syms)
#msc repartition cus
self.sink_repartition_msc_to_cus = blocks.file_sink(gr.sizeof_float * self.dp.msc_cu_size, "debug/msc_repartitioned_to_cus.dat")
self.connect((self.repartition_msc_to_cus), self.sink_repartition_msc_to_cus)
#data of one sub channel not decoded
self.sink_select_subch = blocks.file_sink(gr.sizeof_float * self.dp.msc_cu_size * self.size, "debug/select_subch.dat")
self.connect(self.select_subch, self.sink_select_subch)
#sub channel time_deinterleaved
self.sink_subch_time_deinterleaved = blocks.file_sink(gr.sizeof_float, "debug/subch_time_deinterleaved.dat")
self.connect(self.time_deinterleaver, self.sink_subch_time_deinterleaved)
#sub channel unpunctured
self.sink_subch_unpunctured = blocks.file_sink(gr.sizeof_float, "debug/subch_unpunctured.dat")
self.connect(self.unpuncture, self.sink_subch_unpunctured)
# sub channel convolutional decoded
self.sink_subch_decoded = blocks.file_sink(gr.sizeof_char, "debug/subch_decoded.dat")
self.connect(self.conv_decode, self.sink_subch_decoded)
# sub channel convolutional decoded
self.sink_subch_pruned = blocks.file_sink(gr.sizeof_char, "debug/subch_pruned.dat")
self.connect(self.conv_prune, self.sink_subch_pruned)
# sub channel energy dispersal undone unpacked
self.sink_subch_energy_disp_undone = blocks.file_sink(gr.sizeof_char, "debug/subch_energy_disp_undone_unpacked.dat")
self.connect(self.add_mod_2, self.sink_subch_energy_disp_undone)
# sub channel energy dispersal undone packed
self.sink_subch_energy_disp_undone_packed = blocks.file_sink(gr.sizeof_char, "debug/subch_energy_disp_undone_packed.dat")
self.connect(self.pack_bits, self.sink_subch_energy_disp_undone_packed)
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