def test_convolutional_encoder(self):
"""
Tests convolutional encoder
"""
src_data = make_transport_stream()
constellation = [.7, .7, .7, -.7, -.7, .7, -.7, -.7]
src = gr.vector_source_b(src_data)
unpack = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
enc = dvb_convolutional_encoder_bb.convolutional_encoder_bb()
repack1 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
repack2 = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST)
mapper = gr.chunks_to_symbols_bf(constellation,
dvb_swig.dimensionality)
viterbi = trellis.viterbi_combined_fb(
trellis.fsm(dvb_swig.k, dvb_swig.n,
dvb_convolutional_encoder_bb.G), dvb_swig.K, -1, -1,
dvb_swig.dimensionality, constellation, digital.TRELLIS_EUCLIDEAN)
pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
dst = gr.vector_sink_b()
self.tb.connect(src, unpack, enc, repack1, repack2, mapper)
self.tb.connect(mapper, viterbi, pack, dst)
self.tb.run()
result_data = dst.data()
self.assertEqual(tuple(src_data[:len(result_data)]), result_data)
def __init__(self): gr.top_block.__init__(self, "Many Rate Changing") ################################################## # Variables ################################################## self.samp_rate = samp_rate = 32000 ################################################## # Blocks ################################################## self.random_source_x_0 = gr.vector_source_b(map(int, numpy.random.randint(0, 256, 1000)), True) self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(2, gr.GR_LSB_FIRST) self.gr_packed_to_unpacked_xx_0 = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST) self.gr_null_sink_0_2 = gr.null_sink(gr.sizeof_char*1) self.blocks_keep_m_in_n_0 = blocks.keep_m_in_n(gr.sizeof_float, 3, 20, 0) self.blocks_float_to_char_0 = blocks.float_to_char(1, 1) self.blocks_char_to_float_0 = blocks.char_to_float(1, 1) ################################################## # Connections ################################################## self.connect((self.blocks_char_to_float_0, 0), (self.blocks_keep_m_in_n_0, 0)) self.connect((self.blocks_keep_m_in_n_0, 0), (self.blocks_float_to_char_0, 0)) self.connect((self.blocks_float_to_char_0, 0), (self.gr_packed_to_unpacked_xx_0, 0)) self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.blocks_char_to_float_0, 0)) self.connect((self.random_source_x_0, 0), (self.gr_unpacked_to_packed_xx_0, 0)) self.connect((self.gr_packed_to_unpacked_xx_0, 0), (self.gr_null_sink_0_2, 0))
def __init__(self, randstring, fill=None, width=None, lrs_len=None):
gr.hier_block2.__init__(
self, "generalized_randomizer", gr.io_signature(1, 1, gr.sizeof_char), gr.io_signature(1, 1, gr.sizeof_char)
)
if lrs_len == None:
lrs_len = width
self.randstring = randstring
myrand = stringtorand(self.randstring)
if randstring.startswith("F"):
self._randomizer = fsblks.randomizer_feedthrough_bb(myrand[1])
self.connect(self, (self._randomizer, 0))
self.connect((self._randomizer, 0), self)
elif randstring.startswith("A"):
self._pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self._randomizer = fsblks.randomizer_additive_bb(myrand[1], lrs_len, width, fill)
self._unpack = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
self.connect(self, self._pack, self._randomizer)
self.connect(self._randomizer, self._unpack, self)
else:
assert False, "Check randomizer string input: only additive or feedthrough allowed."
def __init__(self, sample_rate, symbol_rate):
gr.hier_block2.__init__(
self,
"dvb_s_modulator_bc",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
samples_per_symbol = sample_rate / symbol_rate
if samples_per_symbol < 2:
raise TypeError, "Samples per symbol must be >= 2"
# Form symbols with 2 bits per symbol
self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self.reunpack = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST)
self.mapper = gr.chunks_to_symbols_bc(mod_constellation)
# Design FIR filter taps for square root raised cosine filter
ntaps = 11 * int(samples_per_symbol * nfilts)
rrc_taps = gr.firdes.root_raised_cosine(nfilts, nfilts, 1.0,
dvb_swig.RRC_ROLLOFF_FACTOR,
ntaps)
# Baseband pulse shaping filter
self.rrc_filter = gr.pfb_arb_resampler_ccf(samples_per_symbol,
rrc_taps)
self.connect(self, self.pack, self.reunpack, self.mapper,
self.rrc_filter, self)
def __init__(self,
constellation,
differential,
data_length=None,
src_data=None):
"""
constellation -- a constellation object
differential -- whether differential encoding is used
data_length -- the number of bits of data to use
src_data -- a list of the bits to use
"""
super(rec_test_tb, self).__init__()
# Transmission Blocks
if src_data is None:
self.src_data = tuple(
[random.randint(0, 1) for i in range(0, data_length)])
else:
self.src_data = src_data
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
src = gr.vector_source_b(self.src_data)
mod = generic_mod(constellation, differential=differential)
# Channel
channel = gr.channel_model(NOISE_VOLTAGE, FREQUENCY_OFFSET,
TIMING_OFFSET)
# Receiver Blocks
demod = generic_demod(constellation,
differential=differential,
freq_bw=FREQ_BW,
phase_bw=PHASE_BW)
self.dst = gr.vector_sink_b()
self.connect(src, packer, mod, channel, demod, self.dst)
def __init__(self, randstring, fill=None, width=None, lrs_len=None):
gr.hier_block2.__init__(self, "generalized_randomizer",
gr.io_signature(1, 1, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_char))
if (lrs_len == None):
lrs_len = width
self.randstring = randstring
myrand = stringtorand(self.randstring)
if randstring.startswith("F"):
self._randomizer = fsblks.randomizer_feedthrough_bb(myrand[1])
self.connect(self, (self._randomizer, 0))
self.connect((self._randomizer, 0), self)
elif randstring.startswith("A"):
self._pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self._randomizer = fsblks.randomizer_additive_bb(
myrand[1], lrs_len, width, fill)
self._unpack = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
self.connect(self, self._pack, self._randomizer)
self.connect(self._randomizer, self._unpack, self)
else:
assert (
False
), 'Check randomizer string input: only additive or feedthrough allowed.'
def __init__(self, constellation, differential,
data_length=None, src_data=None):
"""
constellation -- a constellation object
differential -- whether differential encoding is used
data_length -- the number of bits of data to use
src_data -- a list of the bits to use
"""
super(rec_test_tb, self).__init__()
# Transmission Blocks
if src_data is None:
self.src_data = tuple([rndm.randint(0,1) for i in range(0, data_length)])
else:
self.src_data = src_data
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
src = gr.vector_source_b(self.src_data)
mod = generic_mod(constellation, differential=differential)
# Channel
channel = gr.channel_model(NOISE_VOLTAGE, FREQUENCY_OFFSET, TIMING_OFFSET)
# Receiver Blocks
demod = generic_demod(constellation, differential=differential,
freq_bw=FREQ_BW,
phase_bw=PHASE_BW)
self.dst = gr.vector_sink_b()
self.connect(src, packer, mod, channel, demod, self.dst)
def __init__(self):
gr.top_block.__init__(self, "Many Rate Changing")
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 32000
##################################################
# Blocks
##################################################
self.random_source_x_0 = gr.vector_source_b(
map(int, numpy.random.randint(0, 256, 1000)), True)
self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(
2, gr.GR_LSB_FIRST)
self.gr_packed_to_unpacked_xx_0 = gr.packed_to_unpacked_bb(
2, gr.GR_MSB_FIRST)
self.gr_null_sink_0_2 = gr.null_sink(gr.sizeof_char * 1)
self.blocks_float_to_char_0 = blocks.float_to_char(1, 1)
self.blocks_char_to_float_0 = blocks.char_to_float(1, 1)
##################################################
# Connections
##################################################
self.connect((self.blocks_char_to_float_0, 0),
(self.blocks_float_to_char_0, 0))
self.connect((self.blocks_float_to_char_0, 0),
(self.gr_packed_to_unpacked_xx_0, 0))
self.connect((self.gr_unpacked_to_packed_xx_0, 0),
(self.blocks_char_to_float_0, 0))
self.connect((self.random_source_x_0, 0),
(self.gr_unpacked_to_packed_xx_0, 0))
self.connect((self.gr_packed_to_unpacked_xx_0, 0),
(self.gr_null_sink_0_2, 0))
def __init__(self): gr.top_block.__init__(self, "Wmbus Phy2") ################################################## # Variables ################################################## self.frame = frame = [1,1] ################################################## # Blocks ################################################## self.gr_vector_source_x_0 = gr.vector_source_b((frame), False, 1) self.gr_vector_sink_x_1 = gr.vector_sink_b(1) self.gr_vector_sink_x_0 = gr.vector_sink_b(1) self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(4, gr.GR_MSB_FIRST) self.gr_pack_k_bits_bb_0 = gr.pack_k_bits_bb(6) self.digital_map_bb_1 = digital.map_bb(([0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])) self.digital_map_bb_0 = digital.map_bb(([16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 3, 16, 1, 2, 16, 16, 16, 16, 7, 16, 16, 0, 16, 16, 5, 6, 16, 4, 16, 16, 16, 16, 16, 16, 11, 16, 9, 10, 16, 16, 15, 16, 16, 8, 16, 16, 16, 16, 13, 14, 16, 12, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16])) ################################################## # Connections ################################################## self.connect((self.gr_vector_source_x_0, 0), (self.gr_pack_k_bits_bb_0, 0)) self.connect((self.gr_pack_k_bits_bb_0, 0), (self.digital_map_bb_0, 0)) self.connect((self.digital_map_bb_0, 0), (self.gr_unpacked_to_packed_xx_0, 0)) self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_vector_sink_x_0, 0)) self.connect((self.digital_map_bb_0, 0), (self.digital_map_bb_1, 0)) self.connect((self.digital_map_bb_1, 0), (self.gr_vector_sink_x_1, 0))
def __init__(self, constellation, differential, rotation):
if constellation.arity() > 256:
# If this becomes limiting some of the blocks should be generalised so
# that they can work with shorts and ints as well as chars.
raise ValueError("Constellation cannot contain more than 256 points.")
gr.hier_block2.__init__(self, "mod_demod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
arity = constellation.arity()
# TX
self.constellation = constellation
self.differential = differential
import weakref
self.blocks = [weakref.proxy(self)]
# We expect a stream of unpacked bits.
# First step is to pack them.
self.blocks.append(
gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST))
# Second step we unpack them such that we have k bits in each byte where
# each constellation symbol hold k bits.
self.blocks.append(
gr.packed_to_unpacked_bb(self.constellation.bits_per_symbol(),
gr.GR_MSB_FIRST))
# Apply any pre-differential coding
# Gray-coding is done here if we're also using differential coding.
if self.constellation.apply_pre_diff_code():
self.blocks.append(gr.map_bb(self.constellation.pre_diff_code()))
# Differential encoding.
if self.differential:
self.blocks.append(gr.diff_encoder_bb(arity))
# Convert to constellation symbols.
self.blocks.append(gr.chunks_to_symbols_bc(self.constellation.points(),
self.constellation.dimensionality()))
# CHANNEL
# Channel just consists of a rotation to check differential coding.
if rotation is not None:
self.blocks.append(gr.multiply_const_cc(rotation))
# RX
# Convert the constellation symbols back to binary values.
self.blocks.append(digital_swig.constellation_decoder_cb(self.constellation.base()))
# Differential decoding.
if self.differential:
self.blocks.append(gr.diff_decoder_bb(arity))
# Decode any pre-differential coding.
if self.constellation.apply_pre_diff_code():
self.blocks.append(gr.map_bb(
mod_codes.invert_code(self.constellation.pre_diff_code())))
# unpack the k bit vector into a stream of bits
self.blocks.append(gr.unpack_k_bits_bb(
self.constellation.bits_per_symbol()))
# connect to block output
check_index = len(self.blocks)
self.blocks = self.blocks[:check_index]
self.blocks.append(weakref.proxy(self))
self.connect(*self.blocks)
def __init__(self, constellation, differential, rotation):
if constellation.arity() > 256:
# If this becomes limiting some of the blocks should be generalised so
# that they can work with shorts and ints as well as chars.
raise ValueError("Constellation cannot contain more than 256 points.")
gr.hier_block2.__init__(self, "mod_demod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
arity = constellation.arity()
# TX
self.constellation = constellation
self.differential = differential
self.blocks = [self]
# We expect a stream of unpacked bits.
# First step is to pack them.
self.blocks.append(
gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST))
# Second step we unpack them such that we have k bits in each byte where
# each constellation symbol hold k bits.
self.blocks.append(
gr.packed_to_unpacked_bb(self.constellation.bits_per_symbol(),
gr.GR_MSB_FIRST))
# Apply any pre-differential coding
# Gray-coding is done here if we're also using differential coding.
if self.constellation.apply_pre_diff_code():
self.blocks.append(gr.map_bb(self.constellation.pre_diff_code()))
# Differential encoding.
if self.differential:
self.blocks.append(gr.diff_encoder_bb(arity))
# Convert to constellation symbols.
self.blocks.append(gr.chunks_to_symbols_bc(self.constellation.points(),
self.constellation.dimensionality()))
# CHANNEL
# Channel just consists of a rotation to check differential coding.
if rotation is not None:
self.blocks.append(gr.multiply_const_cc(rotation))
# RX
# Convert the constellation symbols back to binary values.
self.blocks.append(digital_swig.constellation_decoder_cb(self.constellation.base()))
# Differential decoding.
if self.differential:
self.blocks.append(gr.diff_decoder_bb(arity))
# Decode any pre-differential coding.
if self.constellation.apply_pre_diff_code():
self.blocks.append(gr.map_bb(
mod_codes.invert_code(self.constellation.pre_diff_code())))
# unpack the k bit vector into a stream of bits
self.blocks.append(gr.unpack_k_bits_bb(
self.constellation.bits_per_symbol()))
# connect to block output
check_index = len(self.blocks)
self.blocks = self.blocks[:check_index]
self.blocks.append(self)
self.connect(*self.blocks)
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") ################################################## # Variables ################################################## self.samp_rate = samp_rate = 25000000 self.dec_rate = dec_rate = 25 ################################################## # Blocks ################################################## self.wxgui_fftsink2_0 = fftsink2.fft_sink_c( self.GetWin(), baseband_freq=0, y_per_div=10, y_divs=10, ref_level=0, ref_scale=2.0, sample_rate=samp_rate/dec_rate, fft_size=1024, fft_rate=15, average=False, avg_alpha=None, title="FFT Plot", peak_hold=False, ) self.Add(self.wxgui_fftsink2_0.win) self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate) self.gr_freq_xlating_fir_filter_xxx_0 = gr.freq_xlating_fir_filter_ccc(dec_rate, (firdes.low_pass(1,samp_rate,1000000,100000)), -1000000, samp_rate) self.gr_file_source_0 = gr.file_source(gr.sizeof_gr_complex*1, "/shampoo/sdr/capture/j9Pro-capture/2400000000-25M-1.cap", False) self.gr_file_sink_0_0 = gr.file_sink(gr.sizeof_char*1, "/shampoo/sdr/projects/gr-nineeagles/gmsk-packed.out") self.gr_file_sink_0_0.set_unbuffered(False) self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char*1, "/shampoo/sdr/projects/gr-nineeagles/gmsk-unpacked.out") self.gr_file_sink_0.set_unbuffered(False) self.digital_gmsk_demod_0 = digital.gmsk_demod( samples_per_symbol=2, gain_mu=0.175, mu=0.5, omega_relative_limit=0.005, freq_error=0.0, verbose=False, log=False, ) ################################################## # Connections ################################################## self.connect((self.gr_file_source_0, 0), (self.gr_throttle_0, 0)) self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_file_sink_0_0, 0)) self.connect((self.digital_gmsk_demod_0, 0), (self.gr_file_sink_0, 0)) self.connect((self.digital_gmsk_demod_0, 0), (self.gr_unpacked_to_packed_xx_0, 0)) self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.wxgui_fftsink2_0, 0)) self.connect((self.gr_throttle_0, 0), (self.gr_freq_xlating_fir_filter_xxx_0, 0)) self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.digital_gmsk_demod_0, 0))
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") _icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png" self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY)) ################################################## # Variables ################################################## self.samp_rate = samp_rate = 1000 ################################################## # Blocks ################################################## self.const_source_x_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0, 0) self.gr_descrambler_bb_0 = gr.descrambler_bb(0x8A, 0x7F, 7) self.gr_float_to_complex_0 = gr.float_to_complex(1) self.gr_packed_to_unpacked_xx_0 = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST) self.gr_scrambler_bb_0 = gr.scrambler_bb(0x8A, 0x7F, 7) self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate) self.gr_throttle_0_0 = gr.throttle(gr.sizeof_char*1, samp_rate) self.gr_throttle_0_0_0 = gr.throttle(gr.sizeof_char*1, samp_rate*8) self.gr_throttle_0_0_0_0 = gr.throttle(gr.sizeof_char*1, samp_rate*8*8) self.gr_uchar_to_float_0 = gr.uchar_to_float() self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) self.gr_vector_source_x_0 = gr.vector_source_b((0, 1, 3,7,255,3,1,0), True, 1) self.wxgui_scopesink2_0 = scopesink2.scope_sink_c( self.GetWin(), title="Scope Plot", sample_rate=samp_rate*32, v_scale=0, v_offset=0, t_scale=0, ac_couple=False, xy_mode=False, num_inputs=1, ) self.Add(self.wxgui_scopesink2_0.win) ################################################## # Connections ################################################## self.connect((self.gr_float_to_complex_0, 0), (self.gr_throttle_0, 0)) self.connect((self.const_source_x_0, 0), (self.gr_float_to_complex_0, 1)) self.connect((self.gr_throttle_0, 0), (self.wxgui_scopesink2_0, 0)) self.connect((self.gr_vector_source_x_0, 0), (self.gr_throttle_0_0, 0)) self.connect((self.gr_throttle_0_0, 0), (self.gr_packed_to_unpacked_xx_0, 0)) self.connect((self.gr_descrambler_bb_0, 0), (self.gr_unpacked_to_packed_xx_0, 0)) self.connect((self.gr_packed_to_unpacked_xx_0, 0), (self.gr_throttle_0_0_0, 0)) self.connect((self.gr_throttle_0_0_0, 0), (self.gr_scrambler_bb_0, 0)) self.connect((self.gr_scrambler_bb_0, 0), (self.gr_throttle_0_0_0_0, 0)) self.connect((self.gr_throttle_0_0_0_0, 0), (self.gr_descrambler_bb_0, 0)) self.connect((self.gr_uchar_to_float_0, 0), (self.gr_float_to_complex_0, 0)) self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_uchar_to_float_0, 0))
def test_convolutional_encoder(self): """ Tests convolutional encoder """ src_data = make_transport_stream() constellation = [.7, .7,.7,-.7,-.7,.7,-.7,-.7] src = gr.vector_source_b(src_data) unpack = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST) enc = dvb_convolutional_encoder_bb.convolutional_encoder_bb() repack1 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) repack2 = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST) mapper = gr.chunks_to_symbols_bf(constellation, dvb_swig.dimensionality) viterbi = trellis.viterbi_combined_fb(trellis.fsm(dvb_swig.k, dvb_swig.n, dvb_convolutional_encoder_bb.G), dvb_swig.K, -1, -1, dvb_swig.dimensionality, constellation, trellis.TRELLIS_EUCLIDEAN) pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) dst = gr.vector_sink_b() self.tb.connect(src, unpack, enc, repack1, repack2, mapper) self.tb.connect(mapper, viterbi, pack, dst) self.tb.run() result_data = dst.data() self.assertEqual(tuple(src_data[:len(result_data)]), result_data)
def test_006(self):
"""
Test stream_to_streams.
"""
src_data = (0,1,0,0,0,0,0,1,0,1,0,1,1,0,1,0)
expected_results = (0x82,0x5a)
src = gr.vector_source_b(src_data,False)
op = gr.unpacked_to_packed_bb(1, gr.GR_LSB_FIRST)
self.fg.connect(src, op)
dst = gr.vector_sink_b()
self.fg.connect(op, dst)
self.fg.run()
self.assertEqual(expected_results, dst.data())
def test_008(self):
"""
Test stream_to_streams.
"""
src_data = (0, 4, 2, 0, 0)
expected_results = (0x11,)
src = gr.vector_source_b(src_data, False)
op = gr.unpacked_to_packed_bb(3, gr.GR_MSB_FIRST)
self.tb.connect(src, op)
dst = gr.vector_sink_b()
self.tb.connect(op, dst)
self.tb.run()
self.assertEqual(expected_results, dst.data())
def test_008(self):
"""
Test stream_to_streams.
"""
src_data = (0, 4, 2,0,0)
expected_results = (0x11,)
src = gr.vector_source_b(src_data,False)
op = gr.unpacked_to_packed_bb(3, gr.GR_MSB_FIRST)
self.tb.connect(src, op)
dst = gr.vector_sink_b()
self.tb.connect(op, dst)
self.tb.run()
self.assertEqual(expected_results, dst.data())
def test_two(self):
tb = gr.top_block()
MTU = 4000
tagname = "length"
packets = (
(0, 0, 0, 0)*32,
#(0, 0, 1, 0)*16,
#(1, 1, 1, 0)*4,
)
data, tags = ofdm.utils.packets_to_vectors(packets, tagname)
constellation = digital.bpsk_constellation()
src = gr.vector_source_b(data, tags, False, 1)
tag_scaler1 = ofdm.scale_tags(1, tagname, 0.125)
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
crc = ofdm.crc32_bb(False, MTU, tagname)
tag_scaler2 = ofdm.scale_tags(1, tagname, 8)
unpacker = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
mod1 = digital.chunks_to_symbols_bc(constellation.points())
mod2 = digital.chunks_to_symbols_bc(constellation.points())
occupied_carriers = ((1, 2, 4, 5),)
fft_len = 16
header = ofdm.ofdm_header_bb(len(occupied_carriers[0]))
mux1 = ofdm.tagged_stream_mux(gr.sizeof_gr_complex, 2, tagname, MTU)
mux2 = ofdm.tagged_stream_mux(gr.sizeof_gr_complex*fft_len, 2, tagname, MTU)
ifft = fft.fft_vcc(fft_len, forward=False, window=[1]*fft_len)
cp_len = 4
rolloff_len = 2
cp = digital.ofdm_cyclic_prefixer(fft_len, fft_len+cp_len, rolloff_len, tagname, MTU)
pilot_symbols = ((1j,),)
pilot_carriers = ((3,),)
alloc = ofdm.carrier_allocator_cvc(fft_len,
occupied_carriers,
pilot_carriers,
pilot_symbols,
tagname)
snk = gr.vector_sink_c()
sync_packet = [0, 1, 0, 1, 0, 1] + [0]*10
sync_data, sync_tags = ofdm.utils.packets_to_vectors([sync_packet], tagname, vlen=fft_len)
sync_header = gr.vector_source_c(sync_data, sync_tags, True, fft_len)
tb.connect(src, tag_scaler1, packer, crc, tag_scaler2, unpacker, mod1, (mux1, 1))
tb.connect(crc, header, mod2, (mux1, 0))
tb.connect(mux1, alloc, (mux2, 1))
tb.connect(sync_header, (mux2, 0))
tb.connect(mux2, ifft, cp, snk)
#tb.connect(src, tag_scaler1, packer, crc, tag_scaler2, unpacker, mod1, alloc, snk)
tb.run()
def __init__(self):
gr.top_block.__init__(self, "Create Vector")
##################################################
# Blocks
##################################################
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char*1, "/media/dimitris/mywork/gr/dimitris/rds/trunk/src/utils/rds_vector.dat")
self.gr_head_0 = gr.head(gr.sizeof_char*1, 13)
self.gr_rds_data_encoder_0 = rds.data_encoder("/media/dimitris/mywork/gr/dimitris/rds/trunk/src/utils/rds_data.xml")
self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
##################################################
# Connections
##################################################
self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_head_0, 0))
self.connect((self.gr_head_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.gr_rds_data_encoder_0, 0), (self.gr_unpacked_to_packed_xx_0, 0))
def __init__(self, constellation, samples_per_symbol,
differential, excess_bw, gray_coded,
verbose, log):
gr.hier_block2.__init__(self, "bert_transmit",
gr.io_signature(0, 0, 0), # Output signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Input signature
# Create BERT data bit stream
self._bits = gr.vector_source_b([1,], True) # Infinite stream of ones
self._scrambler = gr.scrambler_bb(0x8A, 0x7F, 7) # CCSDS 7-bit scrambler
self._mod = digital.generic_mod(constellation, samples_per_symbol,
differential, excess_bw, gray_coded,
verbose, log)
self._pack = gr.unpacked_to_packed_bb(self._mod.bits_per_symbol(), gr.GR_MSB_FIRST)
self.connect(self._bits, self._scrambler, self._pack, self._mod, self)
def __init__(self, constellation, samples_per_symbol,
differential, excess_bw, gray_coded,
verbose, log):
gr.hier_block2.__init__(self, "bert_transmit",
gr.io_signature(0, 0, 0), # Output signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Input signature
# Create BERT data bit stream
self._bits = gr.vector_source_b([1,], True) # Infinite stream of ones
self._scrambler = gr.scrambler_bb(0x8A, 0x7F, 7) # CCSDS 7-bit scrambler
self._mod = digital.generic_mod(constellation, samples_per_symbol,
differential, excess_bw, gray_coded,
verbose, log)
self._pack = gr.unpacked_to_packed_bb(self._mod.bits_per_symbol(), gr.GR_MSB_FIRST)
self.connect(self._bits, self._scrambler, self._pack, self._mod, self)
def test_003_bsc_packed (self):
""" Test on packed data """
src = gr.glfsr_source_b(32) # Create some pseudo-random bits
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
head = gr.head(1, 8 * 1000)
bsc = chancoding.bsc_bb(0.5, 8)
unpacker = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
sink1 = gr.vector_sink_b()
sink2 = gr.vector_sink_b()
self.tb.connect(src, head, packer, bsc, unpacker, sink1)
self.tb.connect(head, sink2)
self.tb.run()
bits1 = sink1.data()
bits2 = sink2.data()
bit_errors = np.sum(np.abs(np.array(bits1) - np.array(bits2)))
self.assert_(bit_errors > 3500 and bit_errors < 4500,
"Due to the statistical nature of the bsc, this can actually fail (though very unlikely). Try again.")
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") ################################################## # Variables ################################################## self.samp_rate = samp_rate = 2000000 self.dec_rate = dec_rate = 4 ################################################## # Blocks ################################################## self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) self.gr_throttle_1 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate/dec_rate) self.gr_freq_xlating_fir_filter_xxx_0 = gr.freq_xlating_fir_filter_ccc(dec_rate, (firdes.low_pass(1,samp_rate,500000,100000)), -535000, samp_rate) self.gr_file_source_0 = gr.file_source(gr.sizeof_gr_complex*1, "/shampoo/sdr/capture/nrf-capture/2410500000-2M-1.cap", False) self.gr_file_sink_0_0 = gr.file_sink(gr.sizeof_char*1, "/shampoo/sdr/projects/gr-nordic/qam-packed.out") self.gr_file_sink_0_0.set_unbuffered(False) self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char*1, "/shampoo/sdr/projects/gr-nordic/qam-unpacked.out") self.gr_file_sink_0.set_unbuffered(False) self.digital_qam_demod_0 = digital.qam.qam_demod( constellation_points=4, differential=False, samples_per_symbol=2, excess_bw=.035, freq_bw=6.28/100.0, timing_bw=6.28/100.0, phase_bw=6.28/100.0, gray_coded=False, verbose=False, log=False, ) ################################################## # Connections ################################################## self.connect((self.gr_file_source_0, 0), (self.gr_freq_xlating_fir_filter_xxx_0, 0)) self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.gr_throttle_1, 0)) self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_file_sink_0_0, 0)) self.connect((self.digital_qam_demod_0, 0), (self.gr_file_sink_0, 0)) self.connect((self.digital_qam_demod_0, 0), (self.gr_unpacked_to_packed_xx_0, 0)) self.connect((self.gr_throttle_1, 0), (self.digital_qam_demod_0, 0))
def test_011(self):
"""
Test stream_to_streams.
"""
random.seed(0)
src_data = []
for i in xrange(56):
src_data.append((random.randint(0, 255)))
src_data = tuple(src_data)
expected_results = src_data
src = gr.vector_source_b(tuple(src_data), False)
op1 = gr.packed_to_unpacked_bb(7, gr.GR_LSB_FIRST)
op2 = gr.unpacked_to_packed_bb(7, gr.GR_LSB_FIRST)
self.tb.connect(src, op1, op2)
dst = gr.vector_sink_b()
self.tb.connect(op2, dst)
self.tb.run()
self.assertEqual(expected_results[0:201], dst.data())
def test_011(self):
"""
Test stream_to_streams.
"""
random.seed(0)
src_data = []
for i in xrange(56):
src_data.append((random.randint(0,255)))
src_data = tuple(src_data)
expected_results = src_data
src = gr.vector_source_b(tuple(src_data),False)
op1 = gr.packed_to_unpacked_bb(7, gr.GR_LSB_FIRST)
op2 = gr.unpacked_to_packed_bb(7, gr.GR_LSB_FIRST)
self.tb.connect(src, op1, op2)
dst = gr.vector_sink_b()
self.tb.connect(op2, dst)
self.tb.run()
self.assertEqual(expected_results[0:201], dst.data())
def test_003_bsc_packed(self):
""" Test on packed data """
src = gr.glfsr_source_b(32) # Create some pseudo-random bits
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
head = gr.head(1, 8 * 1000)
bsc = chancoding.bsc_bb(0.5, 8)
unpacker = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
sink1 = gr.vector_sink_b()
sink2 = gr.vector_sink_b()
self.tb.connect(src, head, packer, bsc, unpacker, sink1)
self.tb.connect(head, sink2)
self.tb.run()
bits1 = sink1.data()
bits2 = sink2.data()
bit_errors = np.sum(np.abs(np.array(bits1) - np.array(bits2)))
self.assert_(
bit_errors > 3500 and bit_errors < 4500,
"Due to the statistical nature of the bsc, this can actually fail (though very unlikely). Try again."
)
def __init__(self, sample_rate, symbol_rate): gr.hier_block2.__init__(self, "dvb_s_modulator_bc", gr.io_signature(1, 1, gr.sizeof_char), # Input signature gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature samples_per_symbol = sample_rate / symbol_rate if samples_per_symbol < 2: raise TypeError, "Samples per symbol must be >= 2" # Form symbols with 2 bits per symbol self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) self.reunpack = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST) self.mapper = gr.chunks_to_symbols_bc(mod_constellation) # Design FIR filter taps for square root raised cosine filter ntaps = 11 * int(samples_per_symbol * nfilts) rrc_taps = gr.firdes.root_raised_cosine(nfilts, nfilts, 1.0, dvb_swig.RRC_ROLLOFF_FACTOR, ntaps) # Baseband pulse shaping filter self.rrc_filter = gr.pfb_arb_resampler_ccf(samples_per_symbol, rrc_taps) self.connect(self, self.pack, self.reunpack, self.mapper, self.rrc_filter, self)
def atest_one(self):
tb = gr.top_block()
MTU = 4000
tagname = "_length"
packets = (
(0, 0, 0, 0)*32,
(0, 0, 1, 0)*16,
(1, 1, 1, 0)*4,
)
data, tags = ofdm.utils.packets_to_vectors(packets, tagname)
constellation = digital.bpsk_constellation()
src = gr.vector_source_b(data, tags, False, 1)
tag_scaler1 = ofdm.scale_tags(1, tagname, 0.125)
packer = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
crc1 = ofdm.crc32_bb(False, MTU, tagname)
crc2 = ofdm.crc32_bb(True, MTU, tagname)
tag_scaler2 = ofdm.scale_tags(1, tagname, 8)
unpacker = gr.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
chunks2symbols = digital.chunks_to_symbols_bc(constellation.points())
snk = gr.vector_sink_b()
#tb.connect(src, packer, crc, tag_scaler, unpacker, chunks2symbols, snk)
tb.connect(src, tag_scaler1, packer, crc1, crc2, tag_scaler2, unpacker, snk)
tb.run()
def __init__(self):
gr.top_block.__init__(self, "Create Vector")
##################################################
# Blocks
##################################################
self.gr_file_sink_0 = gr.file_sink(
gr.sizeof_char * 1,
"/media/dimitris/mywork/gr/dimitris/rds/trunk/src/utils/rds_vector.dat"
)
self.gr_head_0 = gr.head(gr.sizeof_char * 1, 13)
self.gr_rds_data_encoder_0 = rds.data_encoder(
"/media/dimitris/mywork/gr/dimitris/rds/trunk/src/utils/rds_data.xml"
)
self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(
1, gr.GR_MSB_FIRST)
##################################################
# Connections
##################################################
self.connect((self.gr_unpacked_to_packed_xx_0, 0), (self.gr_head_0, 0))
self.connect((self.gr_head_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.gr_rds_data_encoder_0, 0),
(self.gr_unpacked_to_packed_xx_0, 0))
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(0, 0, 0)) # output signature self.dp = dab_params self.verbose = verbose self.debug = debug # FIB selection and block partitioning self.select_fic_syms = dab_swig.select_vectors(gr.sizeof_float, self.dp.num_carriers*2, self.dp.num_fic_syms, 0) self.repartition_fic = dab_swig.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_swig.unpuncture_vff(self.dp.assembled_fic_puncturing_sequence) # 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 = gr.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 = gr.stream_to_vector(gr.sizeof_char, 774) self.conv_prune = dab_swig.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 = gr.vector_source_b(self.dp.prbs(self.dp.energy_dispersal_fic_vector_length), True) self.energy_v2s = gr.vector_to_stream(gr.sizeof_char, self.dp.energy_dispersal_fic_vector_length) self.add_mod_2 = gr.xor_bb() self.energy_s2v = gr.stream_to_vector(gr.sizeof_char, self.dp.energy_dispersal_fic_vector_length) self.cut_into_fibs = dab_swig.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 = gr.null_sink(gr.sizeof_char) # self.filesink = gr.file_sink(gr.sizeof_char, "debug/fic.dat") self.fibsink = dab_swig.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), gr.vector_to_stream(1,256), gr.unpacked_to_packed_bb(1,gr.GR_MSB_FIRST), gr.stream_to_vector(1,32), self.fibsink) 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, gr.file_sink(gr.sizeof_float*self.dp.num_carriers*2, "debug/fic_select_syms.dat")) self.connect(self.repartition_fic, gr.file_sink(gr.sizeof_float*self.dp.fic_punctured_codeword_length, "debug/fic_repartitioned.dat")) self.connect(self.unpuncture, gr.file_sink(gr.sizeof_float*self.dp.fic_conv_codeword_length, "debug/fic_unpunctured.dat")) self.connect(self.conv_decode, gr.file_sink(gr.sizeof_char, "debug/fic_decoded.dat")) self.connect(self.energy_s2v, gr.file_sink(gr.sizeof_char*self.dp.energy_dispersal_fic_vector_length, "debug/fic_energy_dispersal_undone.dat"))
def __init__(self):
grc_wxgui.top_block_gui.__init__(
self, title="Communication System Graphical Analyzer (LAPS/UFCG)")
##################################################
# Default Variables
##################################################
self.sps = 2
self.snr = 20
self.symbol_rate = 140000
self.mod_type = "DBPSK"
self.view = 1
self.band = 200
self.excess_bw = 0.35
self.fading_flag = False
self.fdts = -8
self.fading_state_rx = False
##################################################
# Blocks Definition
##################################################
#A bit stream of 1's is generated at the source, scrambled,
#modulated and sent to the input of an AWGN channel.
#random.seed(42)
#self.source = gr.vector_source_b([random.randint(0, 2) for i in range(0,10^8)], True)
self.source = gr.vector_source_b((1, ), True, 1)
self.thottle = gr.throttle(gr.sizeof_char, 10e5)
self.scrambler = gr.scrambler_bb(0x40801, 0x92F72,
20) #Taxa de simbolos constante
self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self.modulator = utils.mods[self.mod_type](self.sps,
excess_bw=self.excess_bw)
self.channel = utils.channel(1 / 10.0**(self.snr / 10.0), self.band,
self.symbol_rate, self.sps)
#The noisy signal is demodulated, descrambled and the BER
#is estimated by the ber_estim block using the receiver
#density of 0 bits.
self.demodulator = utils.demods[self.mod_type](
self.sps, excess_bw=self.excess_bw)
self.descrambler = gr.descrambler_bb(0x40801, 0x92F72, 20)
self.char2float = gr.char_to_float()
self.mov_average = gr.moving_average_ff(524288, 1 / 524288., 10000)
self.ber = utils.ber_estim()
#self.ber = utils.ber_estim_simple(3)
##################################################
# GUI Elements Definition
##################################################
#Defines an adds FFT Window to GUI
self.fft = fftsink.fft_sink_c(self.GetWin(),
sample_rate=self.symbol_rate * self.sps,
baseband_freq=5e6)
self.GridAdd(self.fft.win, 0, 3, 4, 3)
self.ctr = gr.complex_to_real(1)
#Defines and adds SNR slider to GUI
_snr_sizer = wx.BoxSizer(wx.HORIZONTAL)
self._snr_text_box = forms.text_box(parent=self.GetWin(),
sizer=_snr_sizer,
value=self.snr,
callback=self.callback_snr,
label=" SNR (dB)",
converter=forms.float_converter(),
proportion=0)
self._snr_slider = forms.slider(parent=self.GetWin(),
sizer=_snr_sizer,
value=self.snr,
callback=self.callback_snr,
minimum=0,
maximum=20,
style=wx.RA_HORIZONTAL,
proportion=1)
self.GridAdd(_snr_sizer, 4, 3, 1, 3)
#Defines and adds bandwidth slider to GUI
band_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.band_text_box = forms.text_box(parent=self.GetWin(),
sizer=band_sizer,
value=self.band,
callback=self.callback_band,
label="Bandwidth (kHz)",
converter=forms.float_converter(),
proportion=0)
self.band_slider = forms.slider(parent=self.GetWin(),
sizer=band_sizer,
value=self.band,
callback=self.callback_band,
minimum=30,
maximum=200,
style=wx.RA_HORIZONTAL,
proportion=1)
self.GridAdd(band_sizer, 5, 3, 1, 3)
#Defines and adds Rayleigh GUI elements
fading_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.fading_text_box = forms.text_box(
parent=self.GetWin(),
sizer=fading_sizer,
value=self.fdts,
callback=self.callback_fading,
label='Fading/log(FdTs)',
converter=forms.float_converter(),
proportion=0)
self.fading_slider = forms.slider(parent=self.GetWin(),
sizer=fading_sizer,
value=self.fdts,
callback=self.callback_fading,
minimum=-8,
maximum=-2,
style=wx.RA_HORIZONTAL,
proportion=1)
self.GridAdd(fading_sizer, 6, 3, 1, 3)
#Defines and adds modulation type chooser to GUI
self._mod_type_chooser = forms.radio_buttons(
parent=self.GetWin(),
value=self.mod_type,
callback=self.set_mod_type,
label="Modulation",
choices=["DBPSK", "DQPSK", "D8PSK"],
labels=["DBPSK", "DQPSK", "D8PSK"],
style=wx.RA_HORIZONTAL)
self.GridAdd(self._mod_type_chooser, 7, 4, 1, 2)
#Defines and adds signal source chooser
self.sig_src_chooser = forms.radio_buttons(
parent=self.GetWin(),
value=self.view,
callback=self.callback_view,
label="Signal Source",
choices=[0, 1],
labels=["Transmitter", "Receiver"],
style=wx.RA_VERTICAL)
self.GridAdd(self.sig_src_chooser, 7, 3, 1, 1)
#Definition of the of constellation window and attachment to the GUI
self.constel = constsink.const_sink_c(self.GetWin(),
title="RX Constellation Plot",
sample_rate=self.symbol_rate,
const_size=256,
mod=self.mod_type)
self.GridAdd(self.constel.win, 0, 0, 8, 3)
#Definition of the constellation sink window and attachment to the GUI
self.number_sink = bersink.number_sink_f(self.GetWin(),
sample_rate=self.symbol_rate)
self.GridAdd(self.number_sink.win, 8, 0, 1, 6)
##################################################
# Blocks Connections
##################################################
#The necessary block connections to the system work as described above.
self.connect(self.source, self.scrambler, self.thottle, self.pack)
#self.connect(self.source , self.thottle, self.pack)
self.connect(self.pack, self.modulator, self.channel, self.demodulator)
self.connect(self.channel, self.fft)
self.connect(self.demodulator.diffdec, self.constel)
self.connect(self.demodulator, self.descrambler, self.char2float,
self.mov_average)
self.connect(self.mov_average, self.ber, self.number_sink)
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="Communication System Graphical Analyzer (LAPS/UFCG)")
##################################################
# Default Variables
##################################################
self.sps = 2
self.snr = 20
self.symbol_rate = 140000
self.mod_type = "DBPSK"
self.view = 1
self.band= 200
self.excess_bw=0.35
self.fading_flag = False
self.fdts = -8
self.fading_state_rx = False
##################################################
# Blocks Definition
##################################################
#A bit stream of 1's is generated at the source, scrambled,
#modulated and sent to the input of an AWGN channel.
#random.seed(42)
#self.source = gr.vector_source_b([random.randint(0, 2) for i in range(0,10^8)], True)
self.source = gr.vector_source_b((1,), True, 1)
self.thottle = gr.throttle(gr.sizeof_char,10e5)
self.scrambler = gr.scrambler_bb(0x40801, 0x92F72, 20) #Taxa de simbolos constante
self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self.modulator = utils.mods[self.mod_type](self.sps,excess_bw=self.excess_bw)
self.channel = utils.channel(1/10.0**(self.snr/10.0),self.band,self.symbol_rate,self.sps)
#The noisy signal is demodulated, descrambled and the BER
#is estimated by the ber_estim block using the receiver
#density of 0 bits.
self.demodulator = utils.demods[self.mod_type](self.sps,excess_bw=self.excess_bw)
self.descrambler = gr.descrambler_bb(0x40801, 0x92F72, 20)
self.char2float = gr.char_to_float()
self.mov_average = gr.moving_average_ff(524288, 1/524288., 10000)
self.ber = utils.ber_estim()
#self.ber = utils.ber_estim_simple(3)
##################################################
# GUI Elements Definition
##################################################
#Defines an adds FFT Window to GUI
self.fft = fftsink.fft_sink_c(self.GetWin(), sample_rate=self.symbol_rate*self.sps, baseband_freq=5e6)
self.GridAdd(self.fft.win, 0,3,4,3)
self.ctr= gr.complex_to_real(1)
#Defines and adds SNR slider to GUI
_snr_sizer = wx.BoxSizer(wx.HORIZONTAL)
self._snr_text_box = forms.text_box(parent=self.GetWin(),
sizer=_snr_sizer, value=self.snr, callback=self.callback_snr,
label=" SNR (dB)", converter=forms.float_converter(),
proportion=0)
self._snr_slider = forms.slider(parent=self.GetWin(),
sizer=_snr_sizer, value=self.snr, callback=self.callback_snr,
minimum=0, maximum=20, style=wx.RA_HORIZONTAL, proportion=1)
self.GridAdd(_snr_sizer, 4, 3, 1, 3)
#Defines and adds bandwidth slider to GUI
band_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.band_text_box = forms.text_box(parent=self.GetWin(),
sizer=band_sizer, value=self.band, callback=self.callback_band,
label="Bandwidth (kHz)", converter=forms.float_converter(),
proportion=0)
self.band_slider = forms.slider(parent=self.GetWin(),
sizer=band_sizer, value=self.band, callback=self.callback_band,
minimum=30, maximum=200, style=wx.RA_HORIZONTAL, proportion=1)
self.GridAdd(band_sizer, 5, 3, 1, 3)
#Defines and adds Rayleigh GUI elements
fading_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.fading_text_box = forms.text_box(parent=self.GetWin(),
sizer=fading_sizer, value=self.fdts, callback=self.callback_fading,
label='Fading/log(FdTs)', converter=forms.float_converter(),
proportion=0)
self.fading_slider = forms.slider(parent=self.GetWin(),
sizer=fading_sizer, value=self.fdts, callback=self.callback_fading,
minimum=-8, maximum=-2, style=wx.RA_HORIZONTAL, proportion=1)
self.GridAdd(fading_sizer, 6, 3, 1, 3)
#Defines and adds modulation type chooser to GUI
self._mod_type_chooser = forms.radio_buttons(parent=self.GetWin(),
value=self.mod_type, callback=self.set_mod_type,
label="Modulation", choices=["DBPSK", "DQPSK", "D8PSK"],
labels=["DBPSK", "DQPSK", "D8PSK"], style=wx.RA_HORIZONTAL)
self.GridAdd(self._mod_type_chooser, 7, 4, 1, 2)
#Defines and adds signal source chooser
self.sig_src_chooser = forms.radio_buttons(parent=self.GetWin(),
value=self.view, callback=self.callback_view,
label="Signal Source", choices=[0,1],
labels=["Transmitter","Receiver"], style=wx.RA_VERTICAL)
self.GridAdd(self.sig_src_chooser, 7,3,1,1)
#Definition of the of constellation window and attachment to the GUI
self.constel = constsink.const_sink_c(self.GetWin(),
title="RX Constellation Plot", sample_rate=self.symbol_rate,
const_size=256, mod=self.mod_type)
self.GridAdd(self.constel.win,0,0,8,3)
#Definition of the constellation sink window and attachment to the GUI
self.number_sink = bersink.number_sink_f(self.GetWin(),
sample_rate=self.symbol_rate)
self.GridAdd(self.number_sink.win,8,0,1,6)
##################################################
# Blocks Connections
##################################################
#The necessary block connections to the system work as described above.
self.connect(self.source, self.scrambler , self.thottle, self.pack)
#self.connect(self.source , self.thottle, self.pack)
self.connect(self.pack, self.modulator, self.channel, self.demodulator)
self.connect(self.channel, self.fft)
self.connect(self.demodulator.diffdec, self.constel)
self.connect(self.demodulator, self.descrambler, self.char2float, self.mov_average)
self.connect(self.mov_average, self.ber, self.number_sink)
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="Top Block")
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 25000000
self.dec_rate = dec_rate = 25
##################################################
# Blocks
##################################################
self.wxgui_fftsink2_0 = fftsink2.fft_sink_c(
self.GetWin(),
baseband_freq=0,
y_per_div=10,
y_divs=10,
ref_level=0,
ref_scale=2.0,
sample_rate=samp_rate / dec_rate,
fft_size=1024,
fft_rate=15,
average=False,
avg_alpha=None,
title="FFT Plot",
peak_hold=False,
)
self.Add(self.wxgui_fftsink2_0.win)
self.gr_unpacked_to_packed_xx_0 = gr.unpacked_to_packed_bb(
1, gr.GR_MSB_FIRST)
self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex * 1, samp_rate)
self.gr_freq_xlating_fir_filter_xxx_0 = gr.freq_xlating_fir_filter_ccc(
dec_rate, (firdes.low_pass(1, samp_rate, 1000000, 100000)),
-1000000, samp_rate)
self.gr_file_source_0 = gr.file_source(
gr.sizeof_gr_complex * 1,
"/shampoo/sdr/capture/j9Pro-capture/2400000000-25M-1.cap", False)
self.gr_file_sink_0_0 = gr.file_sink(
gr.sizeof_char * 1,
"/shampoo/sdr/projects/gr-nineeagles/gmsk-packed.out")
self.gr_file_sink_0_0.set_unbuffered(False)
self.gr_file_sink_0 = gr.file_sink(
gr.sizeof_char * 1,
"/shampoo/sdr/projects/gr-nineeagles/gmsk-unpacked.out")
self.gr_file_sink_0.set_unbuffered(False)
self.digital_gmsk_demod_0 = digital.gmsk_demod(
samples_per_symbol=2,
gain_mu=0.175,
mu=0.5,
omega_relative_limit=0.005,
freq_error=0.0,
verbose=False,
log=False,
)
##################################################
# Connections
##################################################
self.connect((self.gr_file_source_0, 0), (self.gr_throttle_0, 0))
self.connect((self.gr_unpacked_to_packed_xx_0, 0),
(self.gr_file_sink_0_0, 0))
self.connect((self.digital_gmsk_demod_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.digital_gmsk_demod_0, 0),
(self.gr_unpacked_to_packed_xx_0, 0))
self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0),
(self.wxgui_fftsink2_0, 0))
self.connect((self.gr_throttle_0, 0),
(self.gr_freq_xlating_fir_filter_xxx_0, 0))
self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0),
(self.digital_gmsk_demod_0, 0))
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
gain_mu=_def_gain_mu,
mu=_def_mu,
costas_alpha=_def_costas_alpha,
omega_relative_limit=_def_omega_relative_limit,
freq_error=_def_freq_error,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for Gaussian Minimum Shift Key (GMSK)
demodulation.
The input is the complex modulated signal at baseband.
The output is a stream of bits packed 1 bit per byte (the LSB)
@param samples_per_symbol: samples per baud
@type samples_per_symbol: integer
@param verbose: Print information about modulator?
@type verbose: bool
@param log: Print modualtion data to files?
@type log: bool
Clock recovery parameters. These all have reasonble defaults.
@param gain_mu: controls rate of mu adjustment
@type gain_mu: float
@param mu: fractional delay [0.0, 1.0]
@type mu: float
@param omega_relative_limit: sets max variation in omega
@type omega_relative_limit: float, typically 0.000200 (200 ppm)
@param freq_error: bit rate error as a fraction
@param float
"""
gr.hier_block2.__init__(
self,
"gmsk_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._gain_mu = gain_mu
self._mu = mu
self._omega_relative_limit = omega_relative_limit
self._freq_error = freq_error
self._costas_alpha = costas_alpha
if samples_per_symbol < 2:
raise TypeError, "samples_per_symbol >= 2, is %f" % samples_per_symbol
self._omega = samples_per_symbol * (1 + self._freq_error)
if not self._gain_mu:
self._gain_mu = 0.175
self._gain_omega = .25 * self._gain_mu * self._gain_mu # critically damped
# Demodulate FM
sensitivity = (pi / 2) / samples_per_symbol
self.fmdemod = gr.quadrature_demod_cf(1.0 / sensitivity)
# the clock recovery block tracks the symbol clock and resamples as needed.
# the output of the block is a stream of soft symbols (float)
self.clock_recovery = gr.clock_recovery_mm_ff(
self._omega, self._gain_omega, self._mu, self._gain_mu,
self._omega_relative_limit)
# slice the floats at 0, outputting 1 bit (the LSB of the output byte) per sample
self.slicer = gr.binary_slicer_fb()
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Costas loop (carrier tracking)
# FIXME: need to decide how to handle this more generally; do we pull it from higher layer?
costas_order = 2
beta = .25 * self._costas_alpha * self._costas_alpha
self.costas_loop = gr.costas_loop_cc(self._costas_alpha, beta, 0.002,
-0.002, costas_order)
# Connect & Initialize base class
self.unpack = gr.unpacked_to_packed_bb(self.bits_per_symbol(),
gr.GR_MSB_FIRST)
#self.connect(self, self.fmdemod, self.clock_recovery, self.slicer,self.unpack, self)
self.connect(self, self.fmdemod, self.slicer, self.unpack, self)
def __init__(self, system, site_uuid, overseer_uuid):
gr.top_block.__init__(self, "edacs receiver")
self.log = logging.getLogger('overseer.edacs_control_demod')
self.system = system
self.instance_uuid = '%s' % uuid.uuid4()
self.log = logging.getLogger('overseer.edacs_control_demod.%s' % self.instance_uuid)
self.protocol_log = logging.getLogger('protocol.%s' % self.instance_uuid)
self.log.info('Initializing instance: %s site: %s overseer: %s' % (self.instance_uuid, site_uuid, overseer_uuid))
self.overseer_uuid = overseer_uuid
self.site_uuid = site_uuid
self.audio_rate = audio_rate = 12500
self.symbol_rate = symbol_rate = system['symbol_rate']
self.channels = channels = system['channels']
self.channels_list = self.channels.keys()
self.control_channel_key = 8
self.control_channel = control_channel = self.channels[self.channels_list[0]]
self.control_source = 0
self.thread_id = '%s-%s' % (self.system['type'], self.system['id'])
self.control_lcn = control_lcn = 1
self.bad_messages = 0
self.total_messages = 0
self.quality = []
self.site_detail = {}
self.is_locked = False
self.enable_capture = True
self.keep_running = True
self.freq_offset = 0
self.connector = frontend_connector()
self.client_redis = client_redis()
################################################
# Blocks
################################################
self.channel_rate = 12500
self.receive_rate = self.channel_rate*2 #Decimation adds 50% on either side
self.source = None
try:
self.control_quad_demod = gr.quadrature_demod_cf(5)
except:
self.control_quad_demod = analog.quadrature_demod_cf(5)
self.control_clock_recovery = digital.clock_recovery_mm_ff(self.receive_rate/symbol_rate, 1.4395919, 0.5, 0.05, 0.005)
self.control_binary_slicer = digital.binary_slicer_fb()
try:
self.control_unpacked_to_packed = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
except:
self.control_unpacked_to_packed = blocks.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self.control_msg_queue = gr.msg_queue(1024000)
try:
self.control_msg_sink = gr.message_sink(gr.sizeof_char, self.control_msg_queue,True)
except:
self.control_msg_sink = blocks.message_sink(gr.sizeof_char, self.control_msg_queue,True)
#offset measurement
moving_sum = blocks.moving_average_ff(10000, 1, 40000)
subtract = blocks.sub_ff(1)
divide_const = blocks.multiply_const_vff((0.0001, ))
self.probe = blocks.probe_signal_f()
################################################
# Connections
################################################
self.connect( self.control_quad_demod,
self.control_clock_recovery,
self.control_binary_slicer,
self.control_unpacked_to_packed,
self.control_msg_sink)
self.connect(self.control_quad_demod, moving_sum, divide_const, self.probe)
###############################################
self.patches = {}
self.patch_timeout = 3 #seconds
self.redis_demod_publisher = redis_demod_publisher(parent_demod=self)
control_decode_0 = threading.Thread(target=self.control_decode)
control_decode_0.daemon = True
control_decode_0.start()
quality_check_0 = threading.Thread(target=self.quality_check)
quality_check_0.daemon = True
quality_check_0.start()
self.tune_next_control_channel()
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
gain_mu=_def_gain_mu,
mu=_def_mu,
costas_alpha=_def_costas_alpha,
omega_relative_limit=_def_omega_relative_limit,
freq_error=_def_freq_error,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for Gaussian Minimum Shift Key (GMSK)
demodulation.
The input is the complex modulated signal at baseband.
The output is a stream of bits packed 1 bit per byte (the LSB)
@param samples_per_symbol: samples per baud
@type samples_per_symbol: integer
@param verbose: Print information about modulator?
@type verbose: bool
@param log: Print modualtion data to files?
@type log: bool
Clock recovery parameters. These all have reasonble defaults.
@param gain_mu: controls rate of mu adjustment
@type gain_mu: float
@param mu: fractional delay [0.0, 1.0]
@type mu: float
@param omega_relative_limit: sets max variation in omega
@type omega_relative_limit: float, typically 0.000200 (200 ppm)
@param freq_error: bit rate error as a fraction
@param float
"""
gr.hier_block2.__init__(self, "gmsk_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._gain_mu = gain_mu
self._mu = mu
self._omega_relative_limit = omega_relative_limit
self._freq_error = freq_error
self._costas_alpha = costas_alpha
if samples_per_symbol < 2:
raise TypeError, "samples_per_symbol >= 2, is %f" % samples_per_symbol
self._omega = samples_per_symbol*(1+self._freq_error)
if not self._gain_mu:
self._gain_mu = 0.175
self._gain_omega = .25 * self._gain_mu * self._gain_mu # critically damped
# Demodulate FM
sensitivity = (pi / 2) / samples_per_symbol
self.fmdemod = gr.quadrature_demod_cf(1.0 / sensitivity)
# the clock recovery block tracks the symbol clock and resamples as needed.
# the output of the block is a stream of soft symbols (float)
self.clock_recovery = gr.clock_recovery_mm_ff(self._omega, self._gain_omega,
self._mu, self._gain_mu,
self._omega_relative_limit)
# slice the floats at 0, outputting 1 bit (the LSB of the output byte) per sample
self.slicer = gr.binary_slicer_fb()
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Costas loop (carrier tracking)
# FIXME: need to decide how to handle this more generally; do we pull it from higher layer?
costas_order = 2
beta = .25 * self._costas_alpha * self._costas_alpha
self.costas_loop = gr.costas_loop_cc(self._costas_alpha, beta, 0.002, -0.002, costas_order)
# Connect & Initialize base class
self.unpack = gr.unpacked_to_packed_bb(self.bits_per_symbol(), gr.GR_MSB_FIRST)
#self.connect(self, self.fmdemod, self.clock_recovery, self.slicer,self.unpack, self)
self.connect(self, self.fmdemod, self.slicer,self.unpack, self)
