def test_002_prune_vectors(self): src_data = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15] expected_result = [3,4,8,9,13,14] src = blocks.vector_source_b(src_data) s2v = blocks.stream_to_vector(gr.sizeof_char, 5) prune_vectors = dab.prune_vectors(gr.sizeof_char,5,2,1) v2s = blocks.vector_to_stream(gr.sizeof_char, 2) dst = blocks.vector_sink_b() self.tb.connect(src, s2v, prune_vectors, v2s, dst) self.tb.run() result_data = dst.data() # print expected_result # print result_data self.assertFloatTuplesAlmostEqual(expected_result, result_data, 6)
def test_002_prune_vectors(self):
src_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
expected_result = [3, 4, 8, 9, 13, 14]
src = blocks.vector_source_b(src_data)
s2v = blocks.stream_to_vector(gr.sizeof_char, 5)
prune_vectors = dab.prune_vectors(gr.sizeof_char, 5, 2, 1)
v2s = blocks.vector_to_stream(gr.sizeof_char, 2)
dst = blocks.vector_sink_b()
self.tb.connect(src, s2v, prune_vectors, v2s, dst)
self.tb.run()
result_data = dst.data()
# print expected_result
# print result_data
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 6)
def __init__(self, dab_params, verbose=True, debug=False):
"""
Hierarchical block for FIC decoding
@param dab_params DAB parameter object (dab.parameters.dab_parameters)
"""
gr.hier_block2.__init__(self,"fic",
gr.io_signature2(2, 2, gr.sizeof_float*dab_params.num_carriers*2, gr.sizeof_char), # input
gr.io_signature(1, 1, gr.sizeof_char*32)) # output signature
self.dp = dab_params
self.verbose = verbose
self.debug = debug
# FIB selection and block partitioning
self.select_fic_syms = dab.select_vectors(gr.sizeof_float, self.dp.num_carriers*2, self.dp.num_fic_syms, 0)
self.repartition_fic = dab.repartition_vectors(gr.sizeof_float, self.dp.num_carriers*2, self.dp.fic_punctured_codeword_length, self.dp.num_fic_syms, self.dp.num_cifs)
# unpuncturing
self.unpuncture = dab.unpuncture_vff(self.dp.assembled_fic_puncturing_sequence,0)
# convolutional coding
# self.fsm = trellis.fsm(self.dp.conv_code_in_bits, self.dp.conv_code_out_bits, self.dp.conv_code_generator_polynomials)
self.fsm = trellis.fsm(1, 4, [0133, 0171, 0145, 0133]) # OK (dumped to text and verified partially)
self.conv_v2s = blocks.vector_to_stream(gr.sizeof_float, self.dp.fic_conv_codeword_length)
# self.conv_decode = trellis.viterbi_combined_fb(self.fsm, 20, 0, 0, 1, [1./sqrt(2),-1/sqrt(2)] , trellis.TRELLIS_EUCLIDEAN)
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, 774, 0, 0, 4, table, trellis.TRELLIS_EUCLIDEAN)
self.conv_s2v = blocks.stream_to_vector(gr.sizeof_char, 774)
self.conv_prune = dab.prune_vectors(gr.sizeof_char, self.dp.fic_conv_codeword_length/4, 0, self.dp.conv_code_add_bits_input)
# energy dispersal
self.prbs_src = blocks.vector_source_b(self.dp.prbs(self.dp.energy_dispersal_fic_vector_length), True)
self.energy_v2s = blocks.vector_to_stream(gr.sizeof_char, self.dp.energy_dispersal_fic_vector_length)
self.add_mod_2 = blocks.xor_bb()
self.energy_s2v = blocks.stream_to_vector(gr.sizeof_char, self.dp.energy_dispersal_fic_vector_length)
self.cut_into_fibs = dab.repartition_vectors(gr.sizeof_char, self.dp.energy_dispersal_fic_vector_length, self.dp.fib_bits, 1, self.dp.energy_dispersal_fic_fibs_per_vector)
# connect all
self.nullsink = blocks.null_sink(gr.sizeof_char)
self.fibout = blocks.stream_to_vector(1,32)
# self.filesink = gr.file_sink(gr.sizeof_char, "debug/fic.dat")
self.fibsink = dab.fib_sink_vb()
# self.connect((self,0), (self.select_fic_syms,0), (self.repartition_fic,0), self.unpuncture, self.conv_v2s, self.conv_decode, self.conv_s2v, self.conv_prune, self.energy_v2s, self.add_mod_2, self.energy_s2v, (self.cut_into_fibs,0), gr.vector_to_stream(1,256), gr.unpacked_to_packed_bb(1,gr.GR_MSB_FIRST), self.filesink)
self.connect((self,0),
(self.select_fic_syms,0),
(self.repartition_fic,0),
self.unpuncture,
self.conv_v2s,
self.conv_decode,
self.conv_s2v,
self.conv_prune,
self.energy_v2s,
self.add_mod_2,
self.energy_s2v,
(self.cut_into_fibs,0),
blocks.vector_to_stream(1,256),
blocks.unpacked_to_packed_bb(1,gr.GR_MSB_FIRST),
self.fibout,
self.fibsink)
self.connect(self.fibout, self)
self.connect(self.prbs_src, (self.add_mod_2,1))
self.connect((self,1), (self.select_fic_syms,1), (self.repartition_fic,1), (self.cut_into_fibs,1), self.nullsink)
if self.debug:
self.connect(self.select_fic_syms, blocks.file_sink(gr.sizeof_float*self.dp.num_carriers*2, "debug/fic_select_syms.dat"))
self.connect(self.repartition_fic, blocks.file_sink(gr.sizeof_float*self.dp.fic_punctured_codeword_length, "debug/fic_repartitioned.dat"))
self.connect(self.unpuncture, blocks.file_sink(gr.sizeof_float*self.dp.fic_conv_codeword_length, "debug/fic_unpunctured.dat"))
self.connect(self.conv_decode, blocks.file_sink(gr.sizeof_char, "debug/fic_decoded.dat"))
self.connect(self.energy_s2v, blocks.file_sink(gr.sizeof_char*self.dp.energy_dispersal_fic_vector_length, "debug/fic_energy_dispersal_undone.dat"))
