def test_003(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2,) + padding + \
(3.2, 4.2, 5.5,) + padding + \
(-1.1, -2.2, -3.2,) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([6, 8, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -6])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_c()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_003(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2,) + padding + \
(3.2, 4.2, 5.5,) + padding + \
(-1.1, -2.2, -3.2,) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([6, 8, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -6])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_c()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
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.blks2_ofdm_mod_0 = grc_blks2.packet_mod_b(blks2.ofdm_mod( options=grc_blks2.options( modulation="bpsk", fft_length=1024, occupied_tones=256, cp_length=512, pad_for_usrp=True, log=None, verbose=None, ), ), payload_length=0, ) self.gr_float_to_char_0 = gr.float_to_char() self.gr_sig_source_x_0 = gr.sig_source_f(samp_rate, gr.GR_SIN_WAVE, 100, 127, 0) self.gr_throttle_0 = gr.throttle(gr.sizeof_char*1, samp_rate) self.wxgui_fftsink2_0 = fftsink2.fft_sink_c( self.GetWin(), baseband_freq=0, y_per_div=10, y_divs=10, ref_level=50, ref_scale=2.0, sample_rate=samp_rate*1000, fft_size=1024, fft_rate=30, average=False, avg_alpha=None, title="FFT Plot", peak_hold=False, ) self.Add(self.wxgui_fftsink2_0.win) ################################################## # Connections ################################################## self.connect((self.gr_throttle_0, 0), (self.blks2_ofdm_mod_0, 0)) self.connect((self.gr_sig_source_x_0, 0), (self.gr_float_to_char_0, 0)) self.connect((self.gr_float_to_char_0, 0), (self.gr_throttle_0, 0)) self.connect((self.blks2_ofdm_mod_0, 0), (self.wxgui_fftsink2_0, 0))
def test_001(self):
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.5, -1.1, -2.2, -3.3)
expected_result = [0, 1, 2, 3, 4, 5, 255, 254, 253]
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_b()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_001(self):
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.5, -1.1, -2.2, -3.3)
expected_result = [0, 1, 2, 3, 4, 5, 255, 254, 253]
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_b()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_002(self):
src_data = ( 126.0, 127.0, 128.0)
expected_result = [ 126, 127, 127 ]
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
# Note: vector_sink_b returns uchar
dst = gr.vector_sink_b()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_002(self):
src_data = (126.0, 127.0, 128.0)
expected_result = [126, 127, 127]
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
# Note: vector_sink_b returns uchar
dst = gr.vector_sink_b()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_001(self):
# Need to add padding
padding = tuple([0 for i in range(23)])
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.4, -1.1, -2.2, -3.3) + padding
expected_result = [0, 1, 2, 3, 4, 5, -1, -2, -3]
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_001(self):
# Need to add padding
padding = tuple([0 for i in range(23)])
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.4, -1.1, -2.2, -3.3) + padding
expected_result = [0, 1, 2, 3, 4, 5, -1, -2, -3]
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") _icon_path = "/home/pfb/.local/share/icons/hicolor/32x32/apps/gnuradio-grc.png" self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY)) ################################################## # Variables ################################################## self.samp_rate = samp_rate = 16000000 ################################################## # Blocks ################################################## self.M_Sequence = gr.vector_source_f((-1, -1, 1, 1, -1, 1, 1, 1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, -1, -1, -1, -1, 1, -1, 1, -1, 1, 1, -1, -1, -1, 1, 1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, 1, -1, -1, 1, -1, 1, -1, 1, -1, -1, 1, -1, -1, -1, -1, -1, 1, -1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, 1, 1, 1, -1, 1, 1, -1, -1, -1, -1, 1, 1, -1, -1, -1, 1, -1, -1, 1, 1, -1, -1, -1, -1, -1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, 1, 1, -1, 1, -1, 1, -1, -1, -1, -1, 1, -1, 1, 1, 1, -1, -1, 1, 1, 1, 1, -1, 1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, 1, -1, 1, -1, -1, -1, 1, 1, 1, 1, -1, -1, -1, -1, 1, -1, -1, 1, -1, -1, 1, -1, 1, 1, 1, 1, -1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, -1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, -1, 1, 1, -1, -1, 1, 1, -1, -1, 1, -1, 1, 1, -1, 1, 1, -1, -1, 1, -1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, 1, -1, 1, -1, 1, 1, -1, 1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1), True, 1) self.M_Sequence_Baseband_Modulator = blks2.dbpsk_mod( samples_per_symbol=2, excess_bw=0.35, gray_code=False, verbose=False, log=False, ) self.blks2_dxpsk_mod_0 = blks2.dbpsk_mod( samples_per_symbol=2, excess_bw=0.35, gray_code=True, verbose=False, log=False, ) self.gr_add_xx_0 = gr.add_vcc(1) self.gr_delay_0 = gr.delay(gr.sizeof_char*1, 16) self.gr_file_sink_0 = gr.file_sink(gr.sizeof_gr_complex*1, "../M_Sequence_Baseband.cmplx") self.gr_float_to_char_0 = gr.float_to_char() self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc((0, )) self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate) ################################################## # Connections ################################################## self.connect((self.gr_throttle_0, 0), (self.gr_file_sink_0, 0)) self.connect((self.gr_delay_0, 0), (self.blks2_dxpsk_mod_0, 0)) self.connect((self.blks2_dxpsk_mod_0, 0), (self.gr_multiply_const_vxx_0, 0)) self.connect((self.gr_multiply_const_vxx_0, 0), (self.gr_add_xx_0, 1)) self.connect((self.M_Sequence_Baseband_Modulator, 0), (self.gr_add_xx_0, 0)) self.connect((self.gr_add_xx_0, 0), (self.gr_throttle_0, 0)) self.connect((self.M_Sequence, 0), (self.gr_float_to_char_0, 0)) self.connect((self.gr_float_to_char_0, 0), (self.M_Sequence_Baseband_Modulator, 0)) self.connect((self.gr_float_to_char_0, 0), (self.gr_delay_0, 0))
def test_002(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
src_data = (126.0, 127.0, 128.0) + padding
expected_result = [126, 127, 127]
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_003(self):
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.5, -1.1, -2.2, -3.3)
expected_result = [0, 2, 4, 6, 8, 11, 254, 252, 250]
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_b()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_003(self):
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2, 3.3, 4.4, 5.5, -1.1, -2.2, -3.3)
expected_result = [0, 2, 4, 6, 8, 11, 254, 252, 250]
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_b()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_002(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
src_data = ( 126.0, 127.0, 128.0) + padding
expected_result = [ 126, 127, 127 ]
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
op = gr.float_to_char()
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def __init__(self):
gr.top_block.__init__(self, "CC1101 Burst Detector")
def rx_callback():
print "Callback Fired"
# Variables
self.samp_rate = samp_rate = 125e3
self.f_center = f_center = 510e6
self.bandwidth = bandwidth = 200e3
self.gain = gain = 25
# Blocks
self.uhd_sink = uhd.usrp_sink(
device_addr="serial=E4R11Y0B1", #cheetara
stream_args=uhd.stream_args(
cpu_format="fc32",
channels=range(1),
),
)
self.uhd_sink.set_samp_rate(samp_rate)
self.uhd_sink.set_center_freq(f_center, 0)
self.uhd_sink.set_gain(gain, 0)
self.uhd_sink.set_antenna("TX/RX", 0)
self.uhd_sink.set_bandwidth(bandwidth, 0)
self.uhd_sink.set_samp_rate(self.samp_rate)
self.uhd_sink.set_center_freq(self.f_center, 0)
self.uhd_sink.set_gain(self.gain, 0)
self.src = gr.sig_source_f(samp_rate, gr.GR_COS_WAVE, 1000, 1, 0)
self.f_to_b = gr.float_to_char()
self.msk = level.msk_mod_bc()
# Connections
self.connect(self.src, self.f_to_b, self.msk, self.uhd_sink)
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__(self, frame, panel, vbox, argv)
self.frame = frame
self.panel = panel
parser = OptionParser(option_class=eng_option)
parser.add_option("-R", "--rx-subdev-spec", type="subdev", default=(0, 0),
help="select USRP Rx side A or B (default=A)")
parser.add_option("-d", "--decim", type="int", default=16,
help="set fgpa decimation rate to DECIM [default=%default]")
parser.add_option("-f", "--freq", type="eng_float", default=None,
help="set frequency to FREQ", metavar="FREQ")
parser.add_option("-Q", "--observing", type="eng_float", default=0.0,
help="set observing frequency to FREQ")
parser.add_option("-a", "--avg", type="eng_float", default=1.0,
help="set spectral averaging alpha")
parser.add_option("-V", "--favg", type="eng_float", default=2.0,
help="set folder averaging alpha")
parser.add_option("-g", "--gain", type="eng_float", default=None,
help="set gain in dB (default is midpoint)")
parser.add_option("-l", "--reflevel", type="eng_float", default=30.0,
help="Set pulse display reference level")
parser.add_option("-L", "--lowest", type="eng_float", default=1.5,
help="Lowest valid frequency bin")
parser.add_option("-e", "--longitude", type="eng_float", default=-76.02, help="Set Observer Longitude")
parser.add_option("-c", "--latitude", type="eng_float", default=44.85, help="Set Observer Latitude")
parser.add_option("-F", "--fft_size", type="eng_float", default=1024, help="Size of FFT")
parser.add_option ("-t", "--threshold", type="eng_float", default=2.5, help="pulsar threshold")
parser.add_option("-p", "--lowpass", type="eng_float", default=100, help="Pulse spectra cutoff freq")
parser.add_option("-P", "--prefix", default="./", help="File prefix")
parser.add_option("-u", "--pulsefreq", type="eng_float", default=0.748, help="Observation pulse rate")
parser.add_option("-D", "--dm", type="eng_float", default=1.0e-5, help="Dispersion Measure")
parser.add_option("-O", "--doppler", type="eng_float", default=1.0, help="Doppler ratio")
parser.add_option("-B", "--divbase", type="eng_float", default=20, help="Y/Div menu base")
parser.add_option("-I", "--division", type="eng_float", default=100, help="Y/Div")
parser.add_option("-A", "--audio_source", default="plughw:0,0", help="Audio input device spec")
parser.add_option("-N", "--num_pulses", default=1, type="eng_float", help="Number of display pulses")
(options, args) = parser.parse_args()
if len(args) != 0:
parser.print_help()
sys.exit(1)
self.show_debug_info = True
self.reflevel = options.reflevel
self.divbase = options.divbase
self.division = options.division
self.audiodev = options.audio_source
self.mult = int(options.num_pulses)
# Low-pass cutoff for post-detector filter
# Set to 100Hz usually, since lots of pulsars fit in this
# range
self.lowpass = options.lowpass
# What is lowest valid frequency bin in post-detector FFT?
# There's some pollution very close to DC
self.lowest_freq = options.lowest
# What (dB) threshold to use in determining spectral candidates
self.threshold = options.threshold
# Filename prefix for recording file
self.prefix = options.prefix
# Dispersion Measure (DM)
self.dm = options.dm
# Doppler shift, as a ratio
# 1.0 == no doppler shift
# 1.005 == a little negative shift
# 0.995 == a little positive shift
self.doppler = options.doppler
#
# Input frequency and observing frequency--not necessarily the
# same thing, if we're looking at the IF of some downconverter
# that's ahead of the USRP and daughtercard. This distinction
# is important in computing the correct de-dispersion filter.
#
self.frequency = options.freq
if options.observing <= 0:
self.observing_freq = options.freq
else:
self.observing_freq = options.observing
# build the graph
self.u = usrp.source_c(decim_rate=options.decim)
self.u.set_mux(usrp.determine_rx_mux_value(self.u, options.rx_subdev_spec))
#
# Recording file, in case we ever need to record baseband data
#
self.recording = gr.file_sink(gr.sizeof_char, "/dev/null")
self.recording_state = False
self.pulse_recording = gr.file_sink(gr.sizeof_short, "/dev/null")
self.pulse_recording_state = False
#
# We come up with recording turned off, but the user may
# request recording later on
self.recording.close()
self.pulse_recording.close()
#
# Need these two for converting 12-bit baseband signals to 8-bit
#
self.tofloat = gr.complex_to_float()
self.tochar = gr.float_to_char()
# Need this for recording pulses (post-detector)
self.toshort = gr.float_to_short()
#
# The spectral measurer sets this when it has a valid
# average spectral peak-to-peak distance
# We can then use this to program the parameters for the epoch folder
#
# We set a sentimental value here
self.pulse_freq = options.pulsefreq
# Folder runs at this raw sample rate
self.folder_input_rate = 20000
# Each pulse in the epoch folder is sampled at 128 times the nominal
# pulse rate
self.folding = 128
#
# Try to find candidate parameters for rational resampler
#
save_i = 0
candidates = []
for i in range(20,300):
input_rate = self.folder_input_rate
output_rate = int(self.pulse_freq * i)
interp = gru.lcm(input_rate, output_rate) / input_rate
decim = gru.lcm(input_rate, output_rate) / output_rate
if (interp < 500 and decim < 250000):
candidates.append(i)
# We didn't find anything, bail!
if (len(candidates) < 1):
print "Couldn't converge on resampler parameters"
sys.exit(1)
#
# Now try to find candidate with the least sampling error
#
mindiff = 999.999
for i in candidates:
diff = self.pulse_freq * i
diff = diff - int(diff)
if (diff < mindiff):
mindiff = diff
save_i = i
# Recompute rates
input_rate = self.folder_input_rate
output_rate = int(self.pulse_freq * save_i)
# Compute new interp and decim, based on best candidate
interp = gru.lcm(input_rate, output_rate) / input_rate
decim = gru.lcm(input_rate, output_rate) / output_rate
# Save optimized folding parameters, used later
self.folding = save_i
self.interp = int(interp)
self.decim = int(decim)
# So that we can view N pulses in the pulse viewer window
FOLD_MULT=self.mult
# determine the daughterboard subdevice we're using
self.subdev = usrp.selected_subdev(self.u, options.rx_subdev_spec)
self.cardtype = self.u.daughterboard_id(0)
# Compute raw input rate
input_rate = self.u.adc_freq() / self.u.decim_rate()
# BW==input_rate for complex data
self.bw = input_rate
#
# Set baseband filter bandwidth if DBS_RX:
#
if self.cardtype == usrp_dbid.DBS_RX:
lbw = input_rate / 2
if lbw < 1.0e6:
lbw = 1.0e6
self.subdev.set_bw(lbw)
#
# We use this as a crude volume control for the audio output
#
#self.volume = gr.multiply_const_ff(10**(-1))
#
# Create location data for ephem package
#
self.locality = ephem.Observer()
self.locality.long = str(options.longitude)
self.locality.lat = str(options.latitude)
#
# What is the post-detector LPF cutoff for the FFT?
#
PULSAR_MAX_FREQ=int(options.lowpass)
# First low-pass filters down to input_rate/FIRST_FACTOR
# and decimates appropriately
FIRST_FACTOR=int(input_rate/(self.folder_input_rate/2))
first_filter = gr.firdes.low_pass (1.0,
input_rate,
input_rate/FIRST_FACTOR,
input_rate/(FIRST_FACTOR*20),
gr.firdes.WIN_HAMMING)
# Second filter runs at the output rate of the first filter,
# And low-pass filters down to PULSAR_MAX_FREQ*10
#
second_input_rate = int(input_rate/(FIRST_FACTOR/2))
second_filter = gr.firdes.band_pass(1.0, second_input_rate,
0.10,
PULSAR_MAX_FREQ*10,
PULSAR_MAX_FREQ*1.5,
gr.firdes.WIN_HAMMING)
# Third filter runs at PULSAR_MAX_FREQ*20
# and filters down to PULSAR_MAX_FREQ
#
third_input_rate = PULSAR_MAX_FREQ*20
third_filter = gr.firdes_band_pass(1.0, third_input_rate,
0.10, PULSAR_MAX_FREQ,
PULSAR_MAX_FREQ/10.0,
gr.firdes.WIN_HAMMING)
#
# Create the appropriate FFT scope
#
self.scope = ra_fftsink.ra_fft_sink_f (panel,
fft_size=int(options.fft_size), sample_rate=PULSAR_MAX_FREQ*2,
title="Post-detector spectrum",
ofunc=self.pulsarfunc, xydfunc=self.xydfunc, fft_rate=200)
#
# Tell scope we're looking from DC to PULSAR_MAX_FREQ
#
self.scope.set_baseband_freq (0.0)
#
# Setup stripchart for showing pulse profiles
#
hz = "%5.3fHz " % self.pulse_freq
per = "(%5.3f sec)" % (1.0/self.pulse_freq)
sr = "%d sps" % (int(self.pulse_freq*self.folding))
times = " %d Pulse Intervals" % self.mult
self.chart = ra_stripchartsink.stripchart_sink_f (panel,
sample_rate=1,
stripsize=self.folding*FOLD_MULT, parallel=True, title="Pulse Profiles: "+hz+per+times,
xlabel="Seconds @ "+sr, ylabel="Level", autoscale=True,
divbase=self.divbase, scaling=1.0/(self.folding*self.pulse_freq))
self.chart.set_ref_level(self.reflevel)
self.chart.set_y_per_div(self.division)
# De-dispersion filter setup
#
# Do this here, just before creating the filter
# that will use the taps.
#
ntaps = self.compute_disp_ntaps(self.dm,self.bw,self.observing_freq)
# Taps for the de-dispersion filter
self.disp_taps = Numeric.zeros(ntaps,Numeric.Complex64)
# Compute the de-dispersion filter now
self.compute_dispfilter(self.dm,self.doppler,
self.bw,self.observing_freq)
#
# Call constructors for receive chains
#
#
# Now create the FFT filter using the computed taps
self.dispfilt = gr.fft_filter_ccc(1, self.disp_taps)
#
# Audio sink
#
#print "input_rate ", second_input_rate, "audiodev ", self.audiodev
#self.audio = audio.sink(second_input_rate, self.audiodev)
#
# The three post-detector filters
# Done this way to allow an audio path (up to 10Khz)
# ...and also because going from xMhz down to ~100Hz
# In a single filter doesn't seem to work.
#
self.first = gr.fir_filter_fff (FIRST_FACTOR/2, first_filter)
p = second_input_rate / (PULSAR_MAX_FREQ*20)
self.second = gr.fir_filter_fff (int(p), second_filter)
self.third = gr.fir_filter_fff (10, third_filter)
# Detector
self.detector = gr.complex_to_mag_squared()
self.enable_comb_filter = False
# Epoch folder comb filter
if self.enable_comb_filter == True:
bogtaps = Numeric.zeros(512, Numeric.Float64)
self.folder_comb = gr.fft_filter_ccc(1,bogtaps)
# Rational resampler
self.folder_rr = blks2.rational_resampler_fff(self.interp, self.decim)
# Epoch folder bandpass
bogtaps = Numeric.zeros(1, Numeric.Float64)
self.folder_bandpass = gr.fir_filter_fff (1, bogtaps)
# Epoch folder F2C/C2F
self.folder_f2c = gr.float_to_complex()
self.folder_c2f = gr.complex_to_float()
# Epoch folder S2P
self.folder_s2p = gr.serial_to_parallel (gr.sizeof_float,
self.folding*FOLD_MULT)
# Epoch folder IIR Filter (produces average pulse profiles)
self.folder_iir = gr.single_pole_iir_filter_ff(1.0/options.favg,
self.folding*FOLD_MULT)
#
# Set all the epoch-folder goop up
#
self.set_folding_params()
#
# Start connecting configured modules in the receive chain
#
# Connect raw USRP to de-dispersion filter, detector
self.connect(self.u, self.dispfilt, self.detector)
# Connect detector output to FIR LPF
# in two stages, followed by the FFT scope
self.connect(self.detector, self.first,
self.second, self.third, self.scope)
# Connect audio output
#self.connect(self.first, self.volume)
#self.connect(self.volume, (self.audio, 0))
#self.connect(self.volume, (self.audio, 1))
# Connect epoch folder
if self.enable_comb_filter == True:
self.connect (self.first, self.folder_bandpass, self.folder_rr,
self.folder_f2c,
self.folder_comb, self.folder_c2f,
self.folder_s2p, self.folder_iir,
self.chart)
else:
self.connect (self.first, self.folder_bandpass, self.folder_rr,
self.folder_s2p, self.folder_iir, self.chart)
# Connect baseband recording file (initially /dev/null)
self.connect(self.u, self.tofloat, self.tochar, self.recording)
# Connect pulse recording file (initially /dev/null)
self.connect(self.first, self.toshort, self.pulse_recording)
#
# Build the GUI elements
#
self._build_gui(vbox)
# Make GUI agree with command-line
self.myform['average'].set_value(int(options.avg))
self.myform['foldavg'].set_value(int(options.favg))
# Make spectral averager agree with command line
if options.avg != 1.0:
self.scope.set_avg_alpha(float(1.0/options.avg))
self.scope.set_average(True)
# set initial values
if options.gain is None:
# if no gain was specified, use the mid-point in dB
g = self.subdev.gain_range()
options.gain = float(g[0]+g[1])/2
if options.freq is None:
# if no freq was specified, use the mid-point
r = self.subdev.freq_range()
options.freq = float(r[0]+r[1])/2
self.set_gain(options.gain)
#self.set_volume(-10.0)
if not(self.set_freq(options.freq)):
self._set_status_msg("Failed to set initial frequency")
self.myform['decim'].set_value(self.u.decim_rate())
self.myform['fs@usb'].set_value(self.u.adc_freq() / self.u.decim_rate())
self.myform['dbname'].set_value(self.subdev.name())
self.myform['DM'].set_value(self.dm)
self.myform['Doppler'].set_value(self.doppler)
#
# Start the timer that shows current LMST on the GUI
#
self.lmst_timer.Start(1000)
def __init__(self, fft_length, cp_length, kstime, logging=False):
"""
OFDM synchronization using PN Correlation and initial cross-correlation:
F. Tufvesson, O. Edfors, and M. Faulkner, "Time and Frequency Synchronization for OFDM using
PN-Sequency Preambles," IEEE Proc. VTC, 1999, pp. 2203-2207.
This implementation is meant to be a more robust version of the Schmidl and Cox receiver design.
By correlating against the preamble and using that as the input to the time-delayed correlation,
this circuit produces a very clean timing signal at the end of the preamble. The timing is
more accurate and does not have the problem associated with determining the timing from the
plateau structure in the Schmidl and Cox.
This implementation appears to require that the signal is received with a normalized power or signal
scalling factor to reduce ambiguities intorduced from partial correlation of the cyclic prefix and
the peak detection. A better peak detection block might fix this.
Also, the cross-correlation falls apart as the frequency offset gets larger and completely fails
when an integer offset is introduced. Another thing to look at.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pnac",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
symbol_length = fft_length + cp_length
# PN Sync with cross-correlation input
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime[0:fft_length//2]]
kstime.reverse()
self.crosscorr_filter = filter.fir_filter_ccc(1, kstime)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the input
self.mag = gr.complex_to_mag_squared()
movingsum_taps = (fft_length//1)*[1.0,]
self.power = filter.fir_filter_fff(1,movingsum_taps)
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.compare = gr.sub_ff()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.threshold = gr.threshold_ff(0,0,0) # threshold detection might need to be tweaked
self.peaks = gr.float_to_char()
self.connect(self, self.input)
# Cross-correlate input signal with known preamble
self.connect(self.input, self.crosscorr_filter)
# use the output of the cross-correlation as input time-shifted correlation
self.connect(self.crosscorr_filter, self.delay)
self.connect(self.crosscorr_filter, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.c2mag)
self.connect(self.corr, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
# Get the power of the input signal to compare against the correlation
self.connect(self.crosscorr_filter, self.mag, self.power)
# Compare the power to the correlator output to determine timing peak
# When the peak occurs, it peaks above zero, so the thresholder detects this
self.connect(self.c2mag, (self.compare,0))
self.connect(self.power, (self.compare,1))
self.connect(self.compare, self.threshold)
self.connect(self.threshold, self.peaks, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.peaks, (self,1))
if logging:
self.connect(self.compare, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-compare_f.dat"))
self.connect(self.c2mag, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-theta_f.dat"))
self.connect(self.power, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-inputpower_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-epsilon_f.dat"))
self.connect(self.threshold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-threshold_f.dat"))
self.connect(self.peaks, gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pnac-input_c.dat"))
def __init__(self, fft_length, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(self, "ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
SNR = 10.0**(snr/10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = gr.complex_to_mag_squared()
self.magsqrd2 = gr.complex_to_mag_squared()
self.adder = gr.add_ff()
moving_sum_taps = [rho/2 for i in range(cp_length)]
self.moving_sum_filter = gr.fir_filter_fff(1,moving_sum_taps)
self.connect(self.input,self.magsqrd1)
self.connect(self.delay,self.magsqrd2)
self.connect(self.magsqrd1,(self.adder,0))
self.connect(self.magsqrd2,(self.adder,1))
self.connect(self.adder,self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.mixer = gr.multiply_cc();
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = gr.fir_filter_ccf(1,movingsum2_taps)
# Correlator data handler
self.c2mag = gr.complex_to_mag()
self.angle = gr.complex_to_arg()
self.connect(self.input,(self.mixer,1))
self.connect(self.delay,self.conjg,(self.mixer,0))
self.connect(self.mixer,self.movingsum2,self.c2mag)
self.connect(self.movingsum2,self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = gr.sub_ff()
self.connect(self.c2mag,(self.diff,0))
self.connect(self.moving_sum_filter,(self.diff,1))
#ML measurements input to sampler block and detect
self.f2c = gr.float_to_complex()
self.pk_detect = gr.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = gr.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length),0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold,1))
else:
self.connect(self.pk_detect, (self.sample_and_hold,1))
self.connect(self.angle, (self.sample_and_hold,0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = gr.fir_filter_ccc(1, kstime)
self.corrmag = gr.complex_to_mag_squared()
self.div = gr.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0)
self.f2b = gr.float_to_char()
self.b2f = gr.char_to_float()
self.mul = gr.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div,0))
self.connect(self.moving_sum_filter, (self.div,1))
self.connect(self.div, (self.mul,0))
self.connect(self.pk_detect, self.b2f, (self.mul,1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.slice, self.f2b, (self,1))
if logging:
self.connect(self.moving_sum_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(self.diff, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-epsilon_f.dat"))
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-corrmag_f.dat"))
self.connect(self.kscorr, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-kscorr_c.dat"))
self.connect(self.div, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(self.mul, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(self.slice, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(self.dpll, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-dpll_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-input_c.dat"))
def __init__(self,
agc_max=100,
agc_decay=0.1,
freq_offset=1000000,
outfile="datafifo",
bandpass_bandwidth=20,
threshold_buffer=0.25,
threshold_center=0.5,
agc_attack=0.1,
bandpass_transition_width=1000000):
gr.top_block.__init__(self, "Collect")
##################################################
# Parameters
##################################################
self.agc_max = agc_max
self.agc_decay = agc_decay
self.freq_offset = freq_offset
self.outfile = outfile
self.bandpass_bandwidth = bandpass_bandwidth
self.threshold_buffer = threshold_buffer
self.threshold_center = threshold_center
self.agc_attack = agc_attack
self.bandpass_transition_width = bandpass_transition_width
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 64000000
##################################################
# Blocks
##################################################
self.uhd_usrp_source_0 = uhd.usrp_source(
device_addr="",
io_type=uhd.io_type.COMPLEX_FLOAT32,
num_channels=1,
)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(915000000 - freq_offset, 0)
self.uhd_usrp_source_0.set_gain(0, 0)
self.uhd_usrp_source_0.set_antenna("TX/RX", 0)
self.gr_threshold_ff_0 = gr.threshold_ff(
threshold_center - threshold_buffer,
threshold_center + threshold_buffer, 0)
self.gr_map_bb_0 = gr.map_bb(([48, 49]))
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char * 1, outfile)
self.gr_file_sink_0.set_unbuffered(False)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.gr_agc2_xx_0_0 = gr.agc2_cc(agc_attack, agc_decay, 1.0, 1.0,
agc_max)
self.band_pass_filter_0 = gr.fir_filter_ccf(
1,
firdes.band_pass(1, samp_rate,
freq_offset - bandpass_bandwidth / 2,
freq_offset + bandpass_bandwidth / 2,
bandpass_transition_width, firdes.WIN_HAMMING,
6.76))
##################################################
# Connections
##################################################
self.connect((self.gr_float_to_char_0, 0), (self.gr_map_bb_0, 0))
self.connect((self.gr_map_bb_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.gr_agc2_xx_0_0, 0))
self.connect((self.gr_agc2_xx_0_0, 0), (self.band_pass_filter_0, 0))
self.connect((self.gr_threshold_ff_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_complex_to_mag_0, 0),
(self.gr_threshold_ff_0, 0))
self.connect((self.band_pass_filter_0, 0),
(self.gr_complex_to_mag_0, 0))
def __init__(self, fft_length, cp_length, kstime, threshold, threshold_type, threshold_gap, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
else:
moving_sum_taps = [complex(1.0,0.0) for i in range(fft_length//2)]
self.moving_sum_filter = gr.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length//2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate==1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0, fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0, fft_length, threshold_type, threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag, self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__(self, frame, panel, vbox, argv)
self.frame = frame
self.panel = panel
parser = OptionParser(option_class=eng_option)
parser.add_option("-R",
"--rx-subdev-spec",
type="subdev",
default=(0, 0),
help="select USRP Rx side A or B (default=A)")
parser.add_option(
"-d",
"--decim",
type="int",
default=16,
help="set fgpa decimation rate to DECIM [default=%default]")
parser.add_option("-f",
"--freq",
type="eng_float",
default=None,
help="set frequency to FREQ",
metavar="FREQ")
parser.add_option("-Q",
"--observing",
type="eng_float",
default=0.0,
help="set observing frequency to FREQ")
parser.add_option("-a",
"--avg",
type="eng_float",
default=1.0,
help="set spectral averaging alpha")
parser.add_option("-V",
"--favg",
type="eng_float",
default=2.0,
help="set folder averaging alpha")
parser.add_option("-g",
"--gain",
type="eng_float",
default=None,
help="set gain in dB (default is midpoint)")
parser.add_option("-l",
"--reflevel",
type="eng_float",
default=30.0,
help="Set pulse display reference level")
parser.add_option("-L",
"--lowest",
type="eng_float",
default=1.5,
help="Lowest valid frequency bin")
parser.add_option("-e",
"--longitude",
type="eng_float",
default=-76.02,
help="Set Observer Longitude")
parser.add_option("-c",
"--latitude",
type="eng_float",
default=44.85,
help="Set Observer Latitude")
parser.add_option("-F",
"--fft_size",
type="eng_float",
default=1024,
help="Size of FFT")
parser.add_option("-t",
"--threshold",
type="eng_float",
default=2.5,
help="pulsar threshold")
parser.add_option("-p",
"--lowpass",
type="eng_float",
default=100,
help="Pulse spectra cutoff freq")
parser.add_option("-P", "--prefix", default="./", help="File prefix")
parser.add_option("-u",
"--pulsefreq",
type="eng_float",
default=0.748,
help="Observation pulse rate")
parser.add_option("-D",
"--dm",
type="eng_float",
default=1.0e-5,
help="Dispersion Measure")
parser.add_option("-O",
"--doppler",
type="eng_float",
default=1.0,
help="Doppler ratio")
parser.add_option("-B",
"--divbase",
type="eng_float",
default=20,
help="Y/Div menu base")
parser.add_option("-I",
"--division",
type="eng_float",
default=100,
help="Y/Div")
parser.add_option("-A",
"--audio_source",
default="plughw:0,0",
help="Audio input device spec")
parser.add_option("-N",
"--num_pulses",
default=1,
type="eng_float",
help="Number of display pulses")
(options, args) = parser.parse_args()
if len(args) != 0:
parser.print_help()
sys.exit(1)
self.show_debug_info = True
self.reflevel = options.reflevel
self.divbase = options.divbase
self.division = options.division
self.audiodev = options.audio_source
self.mult = int(options.num_pulses)
# Low-pass cutoff for post-detector filter
# Set to 100Hz usually, since lots of pulsars fit in this
# range
self.lowpass = options.lowpass
# What is lowest valid frequency bin in post-detector FFT?
# There's some pollution very close to DC
self.lowest_freq = options.lowest
# What (dB) threshold to use in determining spectral candidates
self.threshold = options.threshold
# Filename prefix for recording file
self.prefix = options.prefix
# Dispersion Measure (DM)
self.dm = options.dm
# Doppler shift, as a ratio
# 1.0 == no doppler shift
# 1.005 == a little negative shift
# 0.995 == a little positive shift
self.doppler = options.doppler
#
# Input frequency and observing frequency--not necessarily the
# same thing, if we're looking at the IF of some downconverter
# that's ahead of the USRP and daughtercard. This distinction
# is important in computing the correct de-dispersion filter.
#
self.frequency = options.freq
if options.observing <= 0:
self.observing_freq = options.freq
else:
self.observing_freq = options.observing
# build the graph
self.u = usrp.source_c(decim_rate=options.decim)
self.u.set_mux(
usrp.determine_rx_mux_value(self.u, options.rx_subdev_spec))
#
# Recording file, in case we ever need to record baseband data
#
self.recording = gr.file_sink(gr.sizeof_char, "/dev/null")
self.recording_state = False
self.pulse_recording = gr.file_sink(gr.sizeof_short, "/dev/null")
self.pulse_recording_state = False
#
# We come up with recording turned off, but the user may
# request recording later on
self.recording.close()
self.pulse_recording.close()
#
# Need these two for converting 12-bit baseband signals to 8-bit
#
self.tofloat = gr.complex_to_float()
self.tochar = gr.float_to_char()
# Need this for recording pulses (post-detector)
self.toshort = gr.float_to_short()
#
# The spectral measurer sets this when it has a valid
# average spectral peak-to-peak distance
# We can then use this to program the parameters for the epoch folder
#
# We set a sentimental value here
self.pulse_freq = options.pulsefreq
# Folder runs at this raw sample rate
self.folder_input_rate = 20000
# Each pulse in the epoch folder is sampled at 128 times the nominal
# pulse rate
self.folding = 128
#
# Try to find candidate parameters for rational resampler
#
save_i = 0
candidates = []
for i in range(20, 300):
input_rate = self.folder_input_rate
output_rate = int(self.pulse_freq * i)
interp = gru.lcm(input_rate, output_rate) / input_rate
decim = gru.lcm(input_rate, output_rate) / output_rate
if (interp < 500 and decim < 250000):
candidates.append(i)
# We didn't find anything, bail!
if (len(candidates) < 1):
print "Couldn't converge on resampler parameters"
sys.exit(1)
#
# Now try to find candidate with the least sampling error
#
mindiff = 999.999
for i in candidates:
diff = self.pulse_freq * i
diff = diff - int(diff)
if (diff < mindiff):
mindiff = diff
save_i = i
# Recompute rates
input_rate = self.folder_input_rate
output_rate = int(self.pulse_freq * save_i)
# Compute new interp and decim, based on best candidate
interp = gru.lcm(input_rate, output_rate) / input_rate
decim = gru.lcm(input_rate, output_rate) / output_rate
# Save optimized folding parameters, used later
self.folding = save_i
self.interp = int(interp)
self.decim = int(decim)
# So that we can view N pulses in the pulse viewer window
FOLD_MULT = self.mult
# determine the daughterboard subdevice we're using
self.subdev = usrp.selected_subdev(self.u, options.rx_subdev_spec)
self.cardtype = self.u.daughterboard_id(0)
# Compute raw input rate
input_rate = self.u.adc_freq() / self.u.decim_rate()
# BW==input_rate for complex data
self.bw = input_rate
#
# Set baseband filter bandwidth if DBS_RX:
#
if self.cardtype == usrp_dbid.DBS_RX:
lbw = input_rate / 2
if lbw < 1.0e6:
lbw = 1.0e6
self.subdev.set_bw(lbw)
#
# We use this as a crude volume control for the audio output
#
#self.volume = gr.multiply_const_ff(10**(-1))
#
# Create location data for ephem package
#
self.locality = ephem.Observer()
self.locality.long = str(options.longitude)
self.locality.lat = str(options.latitude)
#
# What is the post-detector LPF cutoff for the FFT?
#
PULSAR_MAX_FREQ = int(options.lowpass)
# First low-pass filters down to input_rate/FIRST_FACTOR
# and decimates appropriately
FIRST_FACTOR = int(input_rate / (self.folder_input_rate / 2))
first_filter = gr.firdes.low_pass(1.0, input_rate,
input_rate / FIRST_FACTOR,
input_rate / (FIRST_FACTOR * 20),
gr.firdes.WIN_HAMMING)
# Second filter runs at the output rate of the first filter,
# And low-pass filters down to PULSAR_MAX_FREQ*10
#
second_input_rate = int(input_rate / (FIRST_FACTOR / 2))
second_filter = gr.firdes.band_pass(1.0, second_input_rate, 0.10,
PULSAR_MAX_FREQ * 10,
PULSAR_MAX_FREQ * 1.5,
gr.firdes.WIN_HAMMING)
# Third filter runs at PULSAR_MAX_FREQ*20
# and filters down to PULSAR_MAX_FREQ
#
third_input_rate = PULSAR_MAX_FREQ * 20
third_filter = gr.firdes_band_pass(1.0, third_input_rate, 0.10,
PULSAR_MAX_FREQ,
PULSAR_MAX_FREQ / 10.0,
gr.firdes.WIN_HAMMING)
#
# Create the appropriate FFT scope
#
self.scope = ra_fftsink.ra_fft_sink_f(panel,
fft_size=int(options.fft_size),
sample_rate=PULSAR_MAX_FREQ * 2,
title="Post-detector spectrum",
ofunc=self.pulsarfunc,
xydfunc=self.xydfunc,
fft_rate=200)
#
# Tell scope we're looking from DC to PULSAR_MAX_FREQ
#
self.scope.set_baseband_freq(0.0)
#
# Setup stripchart for showing pulse profiles
#
hz = "%5.3fHz " % self.pulse_freq
per = "(%5.3f sec)" % (1.0 / self.pulse_freq)
sr = "%d sps" % (int(self.pulse_freq * self.folding))
times = " %d Pulse Intervals" % self.mult
self.chart = ra_stripchartsink.stripchart_sink_f(
panel,
sample_rate=1,
stripsize=self.folding * FOLD_MULT,
parallel=True,
title="Pulse Profiles: " + hz + per + times,
xlabel="Seconds @ " + sr,
ylabel="Level",
autoscale=True,
divbase=self.divbase,
scaling=1.0 / (self.folding * self.pulse_freq))
self.chart.set_ref_level(self.reflevel)
self.chart.set_y_per_div(self.division)
# De-dispersion filter setup
#
# Do this here, just before creating the filter
# that will use the taps.
#
ntaps = self.compute_disp_ntaps(self.dm, self.bw, self.observing_freq)
# Taps for the de-dispersion filter
self.disp_taps = Numeric.zeros(ntaps, Numeric.Complex64)
# Compute the de-dispersion filter now
self.compute_dispfilter(self.dm, self.doppler, self.bw,
self.observing_freq)
#
# Call constructors for receive chains
#
#
# Now create the FFT filter using the computed taps
self.dispfilt = gr.fft_filter_ccc(1, self.disp_taps)
#
# Audio sink
#
#print "input_rate ", second_input_rate, "audiodev ", self.audiodev
#self.audio = audio.sink(second_input_rate, self.audiodev)
#
# The three post-detector filters
# Done this way to allow an audio path (up to 10Khz)
# ...and also because going from xMhz down to ~100Hz
# In a single filter doesn't seem to work.
#
self.first = gr.fir_filter_fff(FIRST_FACTOR / 2, first_filter)
p = second_input_rate / (PULSAR_MAX_FREQ * 20)
self.second = gr.fir_filter_fff(int(p), second_filter)
self.third = gr.fir_filter_fff(10, third_filter)
# Detector
self.detector = gr.complex_to_mag_squared()
self.enable_comb_filter = False
# Epoch folder comb filter
if self.enable_comb_filter == True:
bogtaps = Numeric.zeros(512, Numeric.Float64)
self.folder_comb = gr.fft_filter_ccc(1, bogtaps)
# Rational resampler
self.folder_rr = blks2.rational_resampler_fff(self.interp, self.decim)
# Epoch folder bandpass
bogtaps = Numeric.zeros(1, Numeric.Float64)
self.folder_bandpass = gr.fir_filter_fff(1, bogtaps)
# Epoch folder F2C/C2F
self.folder_f2c = gr.float_to_complex()
self.folder_c2f = gr.complex_to_float()
# Epoch folder S2P
self.folder_s2p = gr.serial_to_parallel(gr.sizeof_float,
self.folding * FOLD_MULT)
# Epoch folder IIR Filter (produces average pulse profiles)
self.folder_iir = gr.single_pole_iir_filter_ff(
1.0 / options.favg, self.folding * FOLD_MULT)
#
# Set all the epoch-folder goop up
#
self.set_folding_params()
#
# Start connecting configured modules in the receive chain
#
# Connect raw USRP to de-dispersion filter, detector
self.connect(self.u, self.dispfilt, self.detector)
# Connect detector output to FIR LPF
# in two stages, followed by the FFT scope
self.connect(self.detector, self.first, self.second, self.third,
self.scope)
# Connect audio output
#self.connect(self.first, self.volume)
#self.connect(self.volume, (self.audio, 0))
#self.connect(self.volume, (self.audio, 1))
# Connect epoch folder
if self.enable_comb_filter == True:
self.connect(self.first, self.folder_bandpass, self.folder_rr,
self.folder_f2c, self.folder_comb, self.folder_c2f,
self.folder_s2p, self.folder_iir, self.chart)
else:
self.connect(self.first, self.folder_bandpass, self.folder_rr,
self.folder_s2p, self.folder_iir, self.chart)
# Connect baseband recording file (initially /dev/null)
self.connect(self.u, self.tofloat, self.tochar, self.recording)
# Connect pulse recording file (initially /dev/null)
self.connect(self.first, self.toshort, self.pulse_recording)
#
# Build the GUI elements
#
self._build_gui(vbox)
# Make GUI agree with command-line
self.myform['average'].set_value(int(options.avg))
self.myform['foldavg'].set_value(int(options.favg))
# Make spectral averager agree with command line
if options.avg != 1.0:
self.scope.set_avg_alpha(float(1.0 / options.avg))
self.scope.set_average(True)
# set initial values
if options.gain is None:
# if no gain was specified, use the mid-point in dB
g = self.subdev.gain_range()
options.gain = float(g[0] + g[1]) / 2
if options.freq is None:
# if no freq was specified, use the mid-point
r = self.subdev.freq_range()
options.freq = float(r[0] + r[1]) / 2
self.set_gain(options.gain)
#self.set_volume(-10.0)
if not (self.set_freq(options.freq)):
self._set_status_msg("Failed to set initial frequency")
self.myform['decim'].set_value(self.u.decim_rate())
self.myform['fs@usb'].set_value(self.u.adc_freq() /
self.u.decim_rate())
self.myform['dbname'].set_value(self.subdev.name())
self.myform['DM'].set_value(self.dm)
self.myform['Doppler'].set_value(self.doppler)
#
# Start the timer that shows current LMST on the GUI
#
self.lmst_timer.Start(1000)
def __init__(self, options):
gr.top_block.__init__(self)
if options.rx_freq is not None:
u = uhd_receiver(options.args,
options.bandwidth,
options.rx_freq, options.rx_gain,
options.spec, options.antenna,
options.verbose)
elif options.infile is not None:
u = gr.file_source(gr.sizeof_gr_complex, options.infile)
else:
import sys
sys.stderr.write("--freq or --infile must be specified\n")
raise SystemExit
self.scope = None
if options.outfile is not None:
rx = gr.file_sink(gr.sizeof_gr_complex, options.outfile)
else:
rx = ofdm_rxtx.RX(options)
data_tones = rx.params.data_tones
if options.rxdata is not None:
if options.rxdata == '.':
import scope
# scope it out
rxs = gr.vector_to_stream(gr.sizeof_gr_complex, data_tones)
self.connect(rx, rxs)
self.scope = scope.scope(self, rxs, 'Frame SNR', isComplex=True)
else:
if options.char > 0:
# rail and scale
self.connect(rx,
gr.vector_to_stream(gr.sizeof_float, data_tones * 2),
gr.multiply_const_ff(128.0 * (2**0.5)/ options.char),
gr.rail_ff(-128.0, 127.0),
gr.float_to_char(),
gr.file_sink(gr.sizeof_char, options.rxdata))
else:
self.connect(rx, gr.file_sink(data_tones * gr.sizeof_gr_complex, options.rxdata))
if options.snrdata is not None:
# select one of the snr modes
snr = ofdm_rxtx.SNR(rx.params.data_tones, options.size, mode=options.snrmode)
if options.char > 0:
# NOTE: we use repeat, assuming the file is long enough or properly aligned
data = gr.stream_to_vector(gr.sizeof_float, data_tones * 2)
self.connect(gr.file_source(gr.sizeof_char, options.txdata, repeat=True),
gr.char_to_float(),
gr.multiply_const_ff(options.char * (2**-0.5) / 128.0),
data)
else:
data = ofdm_rxtx.make_data(rx.params.data_tones, options.size, options.txdata)
self.connect(rx, (snr,0))
self.connect(data, (snr,1))
if options.snrdata == '-':
# print it out
msgq = gr.msg_queue(16)
self.connect(snr, gr.message_sink(gr.sizeof_float, msgq, True))
self.watcher = ofdm_rxtx.queue_watcher(msgq)
elif options.snrdata == '.':
import scope
# scope it out
self.scope = scope.scope(self, snr, 'Frame SNR')
else:
self.connect(snr, gr.file_sink(gr.sizeof_float, options.snrdata))
else:
pass
#self.connect(rx, gr.null_sink(symbol_size)) # XXX do we still need this?
self.connect(u, rx)
def setUp (self):
self.tb = gr.top_block ()
# Read in successfully decoded live data from Matlab
linf=open('/home/demel/exchange/matlab_d.txt')
lintu=range(120)
for i in lintu:
lintu[i]=float(linf.readline())
#print lintu
# source for live data
self.srcl = gr.vector_source_f(lintu,False,120)
# Read in .txt file with example MIB encoded + CRC checksum
inf=open('/home/demel/exchange/crc.txt')
self.intu=range(40)
for i in self.intu:
self.intu[i]=float(inf.readline())
#inf=open('/home/demel/exchange/matlab_d.txt')
#intu=range(120)
#for i in range(120):
# intu[i]=float(inf.readline())
# Source and conversions
self.src = gr.vector_source_f(self.intu,False,40)
self.conv = gr.float_to_char(40,1)
# Resize vector with repetition of last part
# Vector to stream for encoder
my_map1=range(46)
for i in range(40):
my_map1[i+6]=i
for i in range(6):
my_map1[i]=i+40
self.map1 = lte.vector_resize_vbvb(my_map1,40,46)
self.vtos = gr.vector_to_stream(1*gr.sizeof_char,46)
# Encoding of input data
self.fsm = trellis.fsm(1,3,[91,121,117])
self.enc = trellis.encoder_bb(self.fsm,0)
# unpack packed bits from encoder
self.unp = gr.unpack_k_bits_bb(3)
# stream to vector
self.stov = gr.stream_to_vector(1*gr.sizeof_char,138)
# Remove first part which contains tail-biting init stuff
map2 = range(120)
for i in map2:
map2[i]= i+18
self.map2 = lte.vector_resize_vbvb(map2,138,120)
# conversion from char to float to match input of decoder
self.conv2= gr.char_to_float(120,1)
###############################################
# From here on only "receiver side" processing
###############################################
# like QPSK demodulation: NRZ coding.
vec2=range(120)
for i in vec2:
vec2[i]=float(-2.0)
self.mult = gr.multiply_const_vff(vec2)
vec=range(120)
for i in vec:
vec[i]=1
self.add = gr.add_const_vff(vec)
# this is the actual unit under test
self.vit = lte.viterbi_vfvb()
# Sinks
self.snk = gr.vector_sink_b(40)
self.snk2 = gr.vector_sink_f(120)
# connecting blocks
self.tb.connect(self.src,self.conv,self.map1,self.vtos,self.enc,self.unp)
self.tb.connect(self.unp,self.stov,self.map2,self.conv2)
self.tb.connect(self.conv2,self.mult,self.add)
self.tb.connect(self.srcl,self.vit,self.snk)
self.tb.connect(self.add,self.snk2)
def __init__(self, fft_length, cp_length, kstime, logging=False):
"""
OFDM synchronization using PN Correlation and initial cross-correlation:
F. Tufvesson, O. Edfors, and M. Faulkner, "Time and Frequency Synchronization for OFDM using
PN-Sequency Preambles," IEEE Proc. VTC, 1999, pp. 2203-2207.
This implementation is meant to be a more robust version of the Schmidl and Cox receiver design.
By correlating against the preamble and using that as the input to the time-delayed correlation,
this circuit produces a very clean timing signal at the end of the preamble. The timing is
more accurate and does not have the problem associated with determining the timing from the
plateau structure in the Schmidl and Cox.
This implementation appears to require that the signal is received with a normalized power or signal
scalling factor to reduce ambiguities intorduced from partial correlation of the cyclic prefix and
the peak detection. A better peak detection block might fix this.
Also, the cross-correlation falls apart as the frequency offset gets larger and completely fails
when an integer offset is introduced. Another thing to look at.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pnac",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
symbol_length = fft_length + cp_length
# PN Sync with cross-correlation input
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime[0:fft_length // 2]]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc()
self.corr = gr.multiply_cc()
# Create a moving sum filter for the input
self.mag = gr.complex_to_mag_squared()
movingsum_taps = (fft_length // 1) * [
1.0,
]
self.power = gr.fir_filter_fff(1, movingsum_taps)
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.compare = gr.sub_ff()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.threshold = gr.threshold_ff(
0, 0, 0) # threshold detection might need to be tweaked
self.peaks = gr.float_to_char()
self.connect(self, self.input)
# Cross-correlate input signal with known preamble
self.connect(self.input, self.crosscorr_filter)
# use the output of the cross-correlation as input time-shifted correlation
self.connect(self.crosscorr_filter, self.delay)
self.connect(self.crosscorr_filter, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.c2mag)
self.connect(self.corr, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0))
# Get the power of the input signal to compare against the correlation
self.connect(self.crosscorr_filter, self.mag, self.power)
# Compare the power to the correlator output to determine timing peak
# When the peak occurs, it peaks above zero, so the thresholder detects this
self.connect(self.c2mag, (self.compare, 0))
self.connect(self.power, (self.compare, 1))
self.connect(self.compare, self.threshold)
self.connect(self.threshold, self.peaks, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
self.connect(self.peaks, (self, 1))
if logging:
self.connect(
self.compare,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-compare_f.dat"))
self.connect(
self.c2mag,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-theta_f.dat"))
self.connect(
self.power,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-inputpower_f.dat"))
self.connect(
self.angle,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-epsilon_f.dat"))
self.connect(
self.threshold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-threshold_f.dat"))
self.connect(
self.peaks,
gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat"))
self.connect(
self.sample_and_hold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-sample_and_hold_f.dat"))
self.connect(
self.input,
gr.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_pnac-input_c.dat"))
def float_to_char(N):
op = gr.float_to_char()
tb = helper(N, op, gr.sizeof_float, gr.sizeof_char, 1, 1)
return tb
def __init__(self, options):
gr.hier_block2.__init__(self, "fbmc_receive_path",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(0,0,0))
print "This is FBMC receive path 1x1"
common_options.defaults(options)
config = self.config = station_configuration()
config.data_subcarriers = dsubc = options.subcarriers
config.cp_length = 0
config.frame_data_blocks = options.data_blocks
config._verbose = options.verbose #TODO: update
config.fft_length = options.fft_length
config.dc_null = options.dc_null
config.training_data = default_block_header(dsubc,
config.fft_length,config.dc_null,options)
config.coding = options.coding
config.ber_window = options.ber_window
config.periodic_parts = 8
config.frame_id_blocks = 1 # FIXME
self._options = copy.copy(options) #FIXME: do we need this?
config.fbmc = options.fbmc
config.block_length = config.fft_length + config.cp_length
config.frame_data_part = config.frame_data_blocks + config.frame_id_blocks
config.frame_length = config.training_data.fbmc_no_preambles + 2*config.frame_data_part
config.postpro_frame_length = config.frame_data_part + \
config.training_data.no_pilotsyms
config.subcarriers = dsubc + \
config.training_data.pilot_subcarriers
config.virtual_subcarriers = config.fft_length - config.subcarriers - config.dc_null
total_subc = config.subcarriers
# check some bounds
if config.fft_length < config.subcarriers:
raise SystemError, "Subcarrier number must be less than FFT length"
if config.fft_length < config.cp_length:
raise SystemError, "Cyclic prefix length must be less than FFT length"
#self.input = gr.kludge_copy(gr.sizeof_gr_complex)
#self.connect( self, self.input )
self.input = self
self.ideal = options.ideal
self.ideal2 = options.ideal2
## Inner receiver
## Timing & Frequency Synchronization
## Channel estimation + Equalization
## Phase Tracking for sampling clock frequency offset correction
inner_receiver = self.inner_receiver = fbmc_inner_receiver( options, options.log )
self.connect( self.input, inner_receiver )
ofdm_blocks = ( inner_receiver, 2 )
frame_start = ( inner_receiver, 1 )
disp_ctf = ( inner_receiver, 0 )
#self.snr_est_preamble = ( inner_receiver, 3 )
#terminate_stream(self,snr_est_preamble)
disp_cfo = ( inner_receiver, 3 )
if self.ideal is False and self.ideal2 is False:
self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
self.connect(disp_cfo, self.zmq_probe_freqoff)
else:
self.connect(disp_cfo, blocks.null_sink(gr.sizeof_float))
# for ID decoder
used_id_bits = config.used_id_bits = 8 #TODO: constant in source code!
rep_id_bits = config.rep_id_bits = dsubc/used_id_bits #BPSK
if options.log:
print "rep_id_bits %d" % (rep_id_bits)
if dsubc % used_id_bits <> 0:
raise SystemError,"Data subcarriers need to be multiple of 10"
## Workaround to avoid periodic structure
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
## NOTE!!! BIG HACK!!!
## first preamble ain't equalized ....
## for Milan's SNR estimator
## Outer Receiver
## Make new inner receiver compatible with old outer receiver
## FIXME: renew outer receiver
self.ctf = disp_ctf
#frame_sampler = ofdm_frame_sampler(options)
frame_sampler = fbmc_frame_sampler(options)
self.connect( ofdm_blocks, frame_sampler)
self.connect( frame_start, (frame_sampler,1) )
#
# ft = [0] * config.frame_length
# ft[0] = 1
#
# # The next block ensures that only complete frames find their way into
# # the old outer receiver. The dynamic frame start trigger is hence
# # replaced with a static one, fixed to the frame length.
#
# frame_sampler = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc,
# config.frame_length )
# self.symbol_output = blocks.vector_to_stream( gr.sizeof_gr_complex * total_subc,
# config.frame_length )
# delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length - 1 )
# damn_static_frame_trigger = blocks.vector_source_b( ft, True )
#
# if options.enable_erasure_decision:
# frame_gate = vector_sampler(
# gr.sizeof_gr_complex * total_subc * config.frame_length, 1 )
# self.connect( ofdm_blocks, frame_sampler, frame_gate,
# self.symbol_output )
# else:
# self.connect( ofdm_blocks, frame_sampler, self.symbol_output )
#
# self.connect( frame_start, delayed_frame_start, ( frame_sampler, 1 ) )
if options.enable_erasure_decision:
frame_gate = frame_sampler.frame_gate
self.symbol_output = frame_sampler
orig_frame_start = frame_start
frame_start = (frame_sampler,1)
self.frame_trigger = frame_start
#terminate_stream(self, self.frame_trigger)
## Pilot block filter
pb_filt = self._pilot_block_filter = fbmc_pilot_block_filter()
self.connect(self.symbol_output,pb_filt)
self.connect(self.frame_trigger,(pb_filt,1))
self.frame_data_trigger = (pb_filt,1)
#self.symbol_output = pb_filt
#if options.log:
#log_to_file(self, pb_filt, "data/pb_filt_out.compl")
if config.fbmc:
pda_in = pb_filt
else:
## Pilot subcarrier filter
ps_filt = self._pilot_subcarrier_filter = pilot_subcarrier_filter()
self.connect(self.symbol_output,ps_filt)
if options.log:
log_to_file(self, ps_filt, "data/ps_filt_out.compl")
pda_in = ps_filt
## Workaround to avoid periodic structure
# for ID decoder
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
if not options.enable_erasure_decision:
## ID Block Filter
# Filter ID block, skip data blocks
id_bfilt = self._id_block_filter = vector_sampler(
gr.sizeof_gr_complex * dsubc, 1 )
if not config.frame_id_blocks == 1:
raise SystemExit, "# ID Blocks > 1 not supported"
self.connect( pda_in , id_bfilt )
self.connect( self.frame_data_trigger, ( id_bfilt, 1 ) ) # trigger
#log_to_file( self, id_bfilt, "data/id_bfilt.compl" )
## ID Demapper and Decoder, soft decision
self.id_dec = self._id_decoder = ofdm.coded_bpsk_soft_decoder( dsubc,
used_id_bits, whitener_pn )
self.connect( id_bfilt, self.id_dec )
print "Using coded BPSK soft decoder for ID detection"
else: # options.enable_erasure_decision:
id_bfilt = self._id_block_filter = vector_sampler(
gr.sizeof_gr_complex * total_subc, config.frame_id_blocks )
id_bfilt_trig_delay = 0
for x in range( config.frame_length ):
if x in config.training_data.pilotsym_pos:
id_bfilt_trig_delay += 1
else:
break
print "Position of ID block within complete frame: %d" %(id_bfilt_trig_delay)
assert( id_bfilt_trig_delay > 0 ) # else not supported
id_bfilt_trig = blocks.delay( gr.sizeof_char, id_bfilt_trig_delay )
self.connect( ofdm_blocks, id_bfilt )
self.connect( orig_frame_start, id_bfilt_trig, ( id_bfilt, 1 ) )
self.id_dec = self._id_decoder = ofdm.coded_bpsk_soft_decoder( total_subc,
used_id_bits, whitener_pn, config.training_data.shifted_pilot_tones )
self.connect( id_bfilt, self.id_dec )
print "Using coded BPSK soft decoder for ID detection"
# The threshold block either returns 1.0 if the llr-value from the
# id decoder is below the threshold, else 0.0. Hence we convert this
# into chars, 0 and 1, and use it as trigger for the sampler.
min_llr = ( self.id_dec, 1 )
erasure_threshold = gr.threshold_ff( 10.0, 10.0, 0 ) # FIXME is it the optimal threshold?
erasure_dec = gr.float_to_char()
id_gate = vector_sampler( gr.sizeof_short, 1 )
ctf_gate = vector_sampler( gr.sizeof_float * total_subc, 1 )
self.connect( self.id_dec , id_gate )
self.connect( self.ctf, ctf_gate )
self.connect( min_llr, erasure_threshold, erasure_dec )
self.connect( erasure_dec, ( frame_gate, 1 ) )
self.connect( erasure_dec, ( id_gate, 1 ) )
self.connect( erasure_dec, ( ctf_gate, 1 ) )
self.id_dec = self._id_decoder = id_gate
self.ctf = ctf_gate
print "Erasure decision for IDs is enabled"
if options.log:
id_dec_f = gr.short_to_float()
self.connect(self.id_dec,id_dec_f)
log_to_file(self, id_dec_f, "data/id_dec_out.float")
if options.log:
log_to_file(self, id_bfilt, "data/id_blockfilter_out.compl")
# TODO: refactor names
if options.log:
map_src_f = gr.char_to_float(dsubc)
self.connect(map_src,map_src_f)
log_to_file(self, map_src_f, "data/map_src_out.float")
## Allocation Control
if options.static_allocation: #DEBUG
if options.coding:
mode = 1 # Coding mode 1-9
bitspermode = [0.5,1,1.5,2,3,4,4.5,5,6] # Information bits per mode
bitcount_vec = [(int)(config.data_subcarriers*config.frame_data_blocks*bitspermode[mode-1])]
bitloading = mode
else:
bitloading = 1
bitcount_vec = [config.data_subcarriers*config.frame_data_blocks*bitloading]
#bitcount_vec = [config.data_subcarriers*config.frame_data_blocks]
self.bitcount_src = blocks.vector_source_i(bitcount_vec,True,1)
# 0s for ID block, then data
#bitloading_vec = [0]*dsubc+[0]*(dsubc/2)+[2]*(dsubc/2)
bitloading_vec = [0]*dsubc+[bitloading]*dsubc
bitloading_src = blocks.vector_source_b(bitloading_vec,True,dsubc)
power_vec = [1]*config.data_subcarriers
power_src = blocks.vector_source_f(power_vec,True,dsubc)
else:
self.allocation_buffer = ofdm.allocation_buffer(config.data_subcarriers, config.frame_data_blocks, "tcp://"+options.tx_hostname+":3333",config.coding)
self.bitcount_src = (self.allocation_buffer,0)
bitloading_src = (self.allocation_buffer,1)
power_src = (self.allocation_buffer,2)
self.connect(self.id_dec, self.allocation_buffer)
if options.benchmarking:
self.allocation_buffer.set_allocation([4]*config.data_subcarriers,[1]*config.data_subcarriers)
if options.log:
log_to_file(self, self.bitcount_src, "data/bitcount_src_rx.int")
log_to_file(self, bitloading_src, "data/bitloading_src_rx.char")
log_to_file(self, power_src, "data/power_src_rx.cmplx")
log_to_file(self, self.id_dec, "data/id_dec_rx.short")
## Power Deallocator
pda = self._power_deallocator = multiply_frame_fc(config.frame_data_part, dsubc)
self.connect(pda_in,(pda,0))
self.connect(power_src,(pda,1))
## Demodulator
# if 0:
# ac_vector = [0.0+0.0j]*208
# ac_vector[0] = (2*10**(-0.452))
# ac_vector[3] = (10**(-0.651))
# ac_vector[7] = (10**(-1.151))
# csi_vector_inv=abs(numpy.fft.fft(numpy.sqrt(ac_vector)))**2
# dm_csi = numpy.fft.fftshift(csi_vector_inv) # TODO
dm_csi = [1]*dsubc # TODO
dm_csi = blocks.vector_source_f(dm_csi,True)
## Depuncturer
dp_trig = [0]*(config.frame_data_blocks/2)
dp_trig[0] = 1
dp_trig = blocks.vector_source_b(dp_trig,True) # TODO
if(options.coding):
fo=ofdm.fsm(1,2,[91,121])
if options.interleave:
int_object=trellis.interleaver(2000,666)
deinterlv = trellis.permutation(int_object.K(),int_object.DEINTER(),1,gr.sizeof_float)
demod = self._data_demodulator = generic_softdemapper_vcf(dsubc, config.frame_data_part, config.coding)
#self.connect(dm_csi,blocks.stream_to_vector(gr.sizeof_float,dsubc),(demod,2))
if(options.ideal):
self.connect(dm_csi,blocks.stream_to_vector(gr.sizeof_float,dsubc),(demod,2))
else:
dm_csi_filter = self.dm_csi_filter = filter.single_pole_iir_filter_ff(0.01,dsubc)
self.connect(self.ctf, self.dm_csi_filter,(demod,2))
#log_to_file(self, dm_csi_filter, "data/softs_csi.float")
#self.connect(dm_trig,(demod,3))
else:
demod = self._data_demodulator = generic_demapper_vcb(dsubc, config.frame_data_part)
if options.benchmarking:
# Do receiver benchmarking until the number of frames x symbols are collected
self.connect(pda,blocks.head(gr.sizeof_gr_complex*dsubc, options.N*config.frame_data_blocks),demod)
else:
self.connect(pda,demod)
self.connect(bitloading_src,(demod,1))
if(options.coding):
## Depuncturing
if not options.nopunct:
depuncturing = depuncture_ff(dsubc,0)
frametrigger_bitmap_filter = blocks.vector_source_b([1,0],True)
self.connect(bitloading_src,(depuncturing,1))
self.connect(dp_trig,(depuncturing,2))
## Decoding
chunkdivisor = int(numpy.ceil(config.frame_data_blocks/5.0))
print "Number of chunks at Viterbi decoder: ", chunkdivisor
decoding = self._data_decoder = ofdm.viterbi_combined_fb(fo,dsubc,-1,-1,2,chunkdivisor,[-1,-1,-1,1,1,-1,1,1],ofdm.TRELLIS_EUCLIDEAN)
if options.log and options.coding:
log_to_file(self, decoding, "data/decoded.char")
if not options.nopunct:
log_to_file(self, depuncturing, "data/vit_in.float")
if not options.nopunct:
if options.interleave:
self.connect(demod,deinterlv,depuncturing,decoding)
else:
self.connect(demod,depuncturing,decoding)
else:
self.connect(demod,decoding)
self.connect(self.bitcount_src, multiply_const_ii(1./chunkdivisor), (decoding,1))
if options.scatterplot or options.scatter_plot_before_phase_tracking:
if self.ideal2 is False:
scatter_vec_elem = self._scatter_vec_elem = ofdm.vector_element(dsubc,40)
scatter_s2v = self._scatter_s2v = blocks.stream_to_vector(gr.sizeof_gr_complex,config.frame_data_blocks)
scatter_id_filt = skip(gr.sizeof_gr_complex*dsubc,config.frame_data_blocks)
scatter_id_filt.skip_call(0)
scatter_trig = [0]*config.frame_data_part
scatter_trig[0] = 1
scatter_trig = blocks.vector_source_b(scatter_trig,True)
self.connect(scatter_trig,(scatter_id_filt,1))
self.connect(scatter_vec_elem,scatter_s2v)
if not options.scatter_plot_before_phase_tracking:
print "Enabling Scatterplot for data subcarriers"
self.connect(pda,scatter_id_filt,scatter_vec_elem)
# Work on this
#scatter_sink = ofdm.scatterplot_sink(dsubc)
#self.connect(pda,scatter_sink)
#self.connect(map_src,(scatter_sink,1))
#self.connect(dm_trig,(scatter_sink,2))
#print "Enabled scatterplot gui interface"
self.zmq_probe_scatter = zeromq.pub_sink(gr.sizeof_gr_complex,config.frame_data_blocks, "tcp://*:5560")
self.connect(scatter_s2v, blocks.keep_one_in_n(gr.sizeof_gr_complex*config.frame_data_blocks,20), self.zmq_probe_scatter)
else:
print "Enabling Scatterplot for data before phase tracking"
inner_rx = inner_receiver.before_phase_tracking
#scatter_sink2 = ofdm.scatterplot_sink(dsubc,"phase_tracking")
op = copy.copy(options)
op.enable_erasure_decision = False
new_framesampler = ofdm_frame_sampler(op)
self.connect( inner_rx, new_framesampler )
self.connect( orig_frame_start, (new_framesampler,1) )
new_ps_filter = pilot_subcarrier_filter()
new_pb_filter = fbmc_pilot_block_filter()
self.connect( (new_framesampler,1), (new_pb_filter,1) )
self.connect( new_framesampler, new_pb_filter,
new_ps_filter, scatter_id_filt, scatter_vec_elem )
#self.connect( new_ps_filter, scatter_sink2 )
#self.connect( map_src, (scatter_sink2,1))
#self.connect( dm_trig, (scatter_sink2,2))
if options.log:
if(options.coding):
log_to_file(self, demod, "data/data_stream_out.float")
else:
data_f = gr.char_to_float()
self.connect(demod,data_f)
log_to_file(self, data_f, "data/data_stream_out.float")
if options.sfo_feedback:
used_id_bits = 8
rep_id_bits = config.data_subcarriers/used_id_bits
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
id_enc = ofdm.repetition_encoder_sb(used_id_bits,rep_id_bits,whitener_pn)
self.connect( self.id_dec, id_enc )
id_mod = ofdm_bpsk_modulator(dsubc)
self.connect( id_enc, id_mod )
id_mod_conj = gr.conjugate_cc(dsubc)
self.connect( id_mod, id_mod_conj )
id_mult = blocks.multiply_vcc(dsubc)
self.connect( id_bfilt, ( id_mult,0) )
self.connect( id_mod_conj, ( id_mult,1) )
# id_mult_avg = filter.single_pole_iir_filter_cc(0.01,dsubc)
# self.connect( id_mult, id_mult_avg )
id_phase = gr.complex_to_arg(dsubc)
self.connect( id_mult, id_phase )
log_to_file( self, id_phase, "data/id_phase.float" )
est=ofdm.LS_estimator_straight_slope(dsubc)
self.connect(id_phase,est)
slope=blocks.multiply_const_ff(1e6/2/3.14159265)
self.connect( (est,0), slope )
log_to_file( self, slope, "data/slope.float" )
log_to_file( self, (est,1), "data/offset.float" )
# ------------------------------------------------------------------------ #
# Display some information about the setup
if config._verbose:
self._print_verbage()
## debug logging ##
if options.log:
# log_to_file(self,self.ofdm_symbols,"data/unequalized_rx_ofdm_symbols.compl")
# log_to_file(self,self.ofdm_symbols,"data/unequalized_rx_ofdm_symbols.float",mag=True)
fftlen = 256
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex,fftlen)
rxs_sampler_vect = concatenate([[1],[0]*49])
rxs_trigger = blocks.vector_source_b(rxs_sampler_vect.tolist(),True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen,True,[],True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = filter.single_pole_iir_filter_ff(0.01,fftlen)
#rxs_logdb = blocks.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
rxs_logdb = gr.kludge_copy( gr.sizeof_float * fftlen )
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float*fftlen,1)
self.connect(rxs_trigger,(rxs_sampler,1))
self.connect(self.input,rxs_sampler,rxs_window,
rxs_spectrum,rxs_mag,rxs_avg,rxs_logdb, rxs_decimate_rate)
log_to_file( self, rxs_decimate_rate, "data/psd_input.float" )
#output branches
self.publish_rx_performance_measure()
def float_to_char(N):
op = gr.float_to_char()
tb = helper(N, op, gr.sizeof_float, gr.sizeof_char, 1, 1)
return tb
def setUp (self):
self.tb = gr.top_block ()
# Read in successfully decoded live data from Matlab
linf=open('/home/demel/exchange/matlab_d.txt')
lintu=range(120)
for i in lintu:
lintu[i]=float(linf.readline())
#print lintu
# source for live data
self.srcl = gr.vector_source_f(lintu,False,120)
# Read in .txt file with example MIB encoded + CRC checksum
inf=open('/home/demel/exchange/crc.txt')
self.intu=range(40)
for i in self.intu:
self.intu[i]=float(inf.readline())
#inf=open('/home/demel/exchange/matlab_d.txt')
#intu=range(120)
#for i in range(120):
# intu[i]=float(inf.readline())
# Source and conversions
self.src = gr.vector_source_f(self.intu,False,40)
self.conv = gr.float_to_char(40,1)
# Resize vector with repetition of last part
# Vector to stream for encoder
my_map1=range(46)
for i in range(40):
my_map1[i+6]=i
for i in range(6):
my_map1[i]=i+40
self.map1 = lte.vector_resize_vbvb(my_map1,40,46)
self.vtos = gr.vector_to_stream(1*gr.sizeof_char,46)
# Encoding of input data
self.fsm = trellis.fsm(1,3,[91,121,117])
self.enc = trellis.encoder_bb(self.fsm,0)
# unpack packed bits from encoder
self.unp = gr.unpack_k_bits_bb(3)
# stream to vector
self.stov = gr.stream_to_vector(1*gr.sizeof_char,138)
# Remove first part which contains tail-biting init stuff
map2 = range(120)
for i in map2:
map2[i]= i+18
self.map2 = lte.vector_resize_vbvb(map2,138,120)
# conversion from char to float to match input of decoder
self.conv2= gr.char_to_float(120,1)
###############################################
# From here on only "receiver side" processing
###############################################
# like QPSK demodulation: NRZ coding.
vec2=range(120)
for i in vec2:
vec2[i]=float(-2.0)
self.mult = gr.multiply_const_vff(vec2)
vec=range(120)
for i in vec:
vec[i]=1
self.add = gr.add_const_vff(vec)
# this is the actual unit under test
self.vit = lte.viterbi_vfvb()
# Sinks
self.snk = gr.vector_sink_b(40)
self.snk2 = gr.vector_sink_f(120)
# connecting blocks
self.tb.connect(self.src,self.conv,self.map1,self.vtos,self.enc,self.unp)
self.tb.connect(self.unp,self.stov,self.map2,self.conv2)
self.tb.connect(self.conv2,self.mult,self.add)
self.tb.connect(self.srcl,self.vit,self.snk)
self.tb.connect(self.add,self.snk2)
def __init__(self, options):
gr.top_block.__init__(self)
if options.rx_freq is not None:
u = uhd_receiver(options.args, options.bandwidth, options.rx_freq,
options.rx_gain, options.spec, options.antenna,
options.verbose)
elif options.infile is not None:
u = gr.file_source(gr.sizeof_gr_complex, options.infile)
else:
import sys
sys.stderr.write("--freq or --infile must be specified\n")
raise SystemExit
self.scope = None
if options.outfile is not None:
rx = gr.file_sink(gr.sizeof_gr_complex, options.outfile)
else:
rx = ofdm_rxtx.RX(options)
data_tones = rx.params.data_tones
if options.rxdata is not None:
if options.rxdata == '.':
import scope
# scope it out
rxs = gr.vector_to_stream(gr.sizeof_gr_complex, data_tones)
self.connect(rx, rxs)
self.scope = scope.scope(self,
rxs,
'Frame SNR',
isComplex=True)
else:
if options.char > 0:
# rail and scale
self.connect(
rx,
gr.vector_to_stream(gr.sizeof_float,
data_tones * 2),
gr.multiply_const_ff(128.0 * (2**0.5) /
options.char),
gr.rail_ff(-128.0, 127.0), gr.float_to_char(),
gr.file_sink(gr.sizeof_char, options.rxdata))
else:
self.connect(
rx,
gr.file_sink(data_tones * gr.sizeof_gr_complex,
options.rxdata))
if options.snrdata is not None:
# select one of the snr modes
snr = ofdm_rxtx.SNR(rx.params.data_tones,
options.size,
mode=options.snrmode)
if options.char > 0:
# NOTE: we use repeat, assuming the file is long enough or properly aligned
data = gr.stream_to_vector(gr.sizeof_float, data_tones * 2)
self.connect(
gr.file_source(gr.sizeof_char,
options.txdata,
repeat=True), gr.char_to_float(),
gr.multiply_const_ff(options.char * (2**-0.5) / 128.0),
data)
else:
data = ofdm_rxtx.make_data(rx.params.data_tones,
options.size, options.txdata)
self.connect(rx, (snr, 0))
self.connect(data, (snr, 1))
if options.snrdata == '-':
# print it out
msgq = gr.msg_queue(16)
self.connect(snr,
gr.message_sink(gr.sizeof_float, msgq, True))
self.watcher = ofdm_rxtx.queue_watcher(msgq)
elif options.snrdata == '.':
import scope
# scope it out
self.scope = scope.scope(self, snr, 'Frame SNR')
else:
self.connect(
snr, gr.file_sink(gr.sizeof_float, options.snrdata))
else:
pass
#self.connect(rx, gr.null_sink(symbol_size)) # XXX do we still need this?
self.connect(u, rx)
def __init__(self, fft_length, block_length, block_header, range, options):
gr.hier_block2.__init__(
self, "integer_fo_estimator",
gr.io_signature3(3, 3, gr.sizeof_gr_complex, gr.sizeof_float,
gr.sizeof_char),
gr.io_signature2(3, 3, gr.sizeof_float, gr.sizeof_char))
raise NotImplementedError, "Obsolete class"
self._range = range
# threshold after integer part frequency offset estimation
# if peak value below threshold, assume false triggering
self._thr_lo = 0.4 #0.19 # empirically found threshold. see ioe_metric.float
self._thr_hi = 0.4 #0.2
# stuff to be removed after bugfix for hierblock2s
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.time_sync = gr.kludge_copy(gr.sizeof_char)
self.epsilon = (self, 1)
self.connect((self, 0), self.input)
self.connect((self, 2), self.time_sync)
delay(gr.sizeof_char, block_header.schmidl_fine_sync[0] * block_length)
# sample ofdm symbol (preamble 1 and 2)
sampler_symbol1 = vector_sampler(gr.sizeof_gr_complex, fft_length)
sampler_symbol2 = vector_sampler(gr.sizeof_gr_complex, fft_length)
time_delay1 = delay(gr.sizeof_char,
block_length * block_header.schmidl_fine_sync[1])
self.connect(self.input, (sampler_symbol1, 0))
self.connect(self.input, (sampler_symbol2, 0))
if block_header.schmidl_fine_sync[0] > 0:
time_delay0 = delay(
gr.sizeof_char,
block_length * block_header.schmidl_fine_sync[0])
self.connect(self.time_sync, time_delay0, (sampler_symbol1, 1))
else:
self.connect(self.time_sync, (sampler_symbol1, 1))
self.connect(self.time_sync, time_delay1, (sampler_symbol2, 1))
# negative fractional frequency offset estimate
epsilon = gr.multiply_const_ff(-1.0)
self.connect(self.epsilon, epsilon)
# compensate for fractional frequency offset on per symbol base
# freq_shift: vector length, modulator sensitivity
# freq_shift third input: reset phase accumulator
# symbol/preamble 1
freq_shift_sym1 = frequency_shift_vcc(fft_length, 1.0 / fft_length)
self.connect(sampler_symbol1, (freq_shift_sym1, 0))
self.connect(epsilon, (freq_shift_sym1, 1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym1, 2))
# symbol/preamble 2
freq_shift_sym2 = frequency_shift_vcc(fft_length, 1.0 / fft_length)
self.connect(sampler_symbol2, (freq_shift_sym2, 0))
self.connect(epsilon, (freq_shift_sym2, 1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym2, 2))
# fourier transfrom on both preambles
fft_sym1 = gr.fft_vcc(fft_length, True, [],
True) # Forward + Blockshift
fft_sym2 = gr.fft_vcc(fft_length, True, [],
True) # Forward + Blockshift
# calculate schmidl's metric for estimation of freq. offset's integer part
assert (hasattr(block_header, "schmidl_fine_sync"))
pre1 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[0]]
pre2 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[1]]
diff_pn = concatenate(
[[conjugate(math.sqrt(2) * pre2[2 * i] / pre1[2 * i]), 0.0j]
for i in arange(len(pre1) / 2)])
cfo_estimator = schmidl_cfo_estimator(fft_length, len(pre1),
self._range, diff_pn)
self.connect(freq_shift_sym1, fft_sym1,
(cfo_estimator, 0)) # preamble 1
self.connect(freq_shift_sym2, fft_sym2,
(cfo_estimator, 1)) # preamble 2
# search for maximum and its argument in interval [-range .. +range]
#arg_max = arg_max_vff(2*self._range + 1)
arg_max_s = gr.argmax_fs(2 * self._range + 1)
arg_max = gr.short_to_float()
ifo_max = gr.max_ff(2 * self._range + 1) # vlen
ifo_estimate = gr.add_const_ff(-self._range)
self.connect(cfo_estimator, arg_max_s, arg_max, ifo_estimate)
self.connect(cfo_estimator, ifo_max)
self.connect((arg_max_s, 1), gr.null_sink(gr.sizeof_short))
# threshold maximal value
ifo_threshold = gr.threshold_ff(self._thr_lo, self._thr_hi, 0.0)
ifo_thr_f2b = gr.float_to_char()
self.connect(ifo_max, ifo_threshold, ifo_thr_f2b)
# gating the streams ifo_estimate (integer part) and epsilon (frac. part)
# if the metric's peak value was above the chosen threshold, assume to have
# found a new burst. peak value below threshold results in blocking the
# streams
self.gate = gate_ff()
self.connect(ifo_thr_f2b, (self.gate, 0)) # threshold stream
self.connect(ifo_estimate, (self.gate, 1))
self.connect(epsilon, (self.gate, 2))
# peak filtering
# resynchronize and suppress peaks that didn't match a preamble
filtered_time_sync = peak_resync_bb(True) # replace
self.connect(self.time_sync, (filtered_time_sync, 0))
self.connect(ifo_thr_f2b, (filtered_time_sync, 1))
# find complete estimation for frequency offset
# add together fractional and integer part
freq_offset = gr.add_ff()
self.connect((self.gate, 1), gr.multiply_const_ff(-1.0),
(freq_offset, 0)) # integer offset
self.connect((self.gate, 2), (freq_offset, 1)) # frac offset
# output connections
self.connect(freq_offset, (self, 0))
self.connect(filtered_time_sync, (self, 1))
self.connect((self.gate, 0), (self, 2)) # used for frame trigger
#########################################
# debugging
if options.log:
self.epsilon2_sink = gr.vector_sink_f()
self.connect(epsilon, self.epsilon2_sink)
self.connect(
cfo_estimator,
gr.file_sink(gr.sizeof_float * (self._range * 2 + 1),
"data/ioe_metric.float"))
# output joint stream
preamble_stream = gr.streams_to_vector(
fft_length * gr.sizeof_gr_complex, 2)
self.connect(fft_sym1, (preamble_stream, 0))
self.connect(fft_sym2, (preamble_stream, 1))
self.connect(
preamble_stream,
gr.file_sink(gr.sizeof_gr_complex * 2 * fft_length,
"data/preambles.compl"))
# output, preambles before and after correction, magnitude and complex spectrum
self.connect(
sampler_symbol1, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre1_bef.compl"))
self.connect(
sampler_symbol1, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length,
"data/pre1_bef.float"))
self.connect(
sampler_symbol2, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre2_bef.compl"))
self.connect(
sampler_symbol2, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length,
"data/pre2_bef.float"))
self.connect(
freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre1.compl"))
self.connect(
freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length, "data/pre1.float"))
self.connect(
freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre2.compl"))
self.connect(
freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length, "data/pre2.float"))
# calculate epsilon from corrected source to check function
test_cp = cyclic_prefixer(fft_length, block_length)
test_eps = foe(fft_length)
self.connect(freq_shift_sym1, test_cp, test_eps,
gr.file_sink(gr.sizeof_float, "data/eps_after.float"))
try:
gr.hier_block.update_var_names(self, "ifo_estimator", vars())
gr.hier_block.update_var_names(self, "ifo_estimator", vars(self))
except:
pass
def __init__(self, fft_length, block_length, block_header, range, options):
gr.hier_block2.__init__(self, "integer_fo_estimator",
gr.io_signature3(3,3,gr.sizeof_gr_complex,gr.sizeof_float,gr.sizeof_char),
gr.io_signature2(3,3,gr.sizeof_float,gr.sizeof_char))
raise NotImplementedError,"Obsolete class"
self._range = range
# threshold after integer part frequency offset estimation
# if peak value below threshold, assume false triggering
self._thr_lo = 0.4 #0.19 # empirically found threshold. see ioe_metric.float
self._thr_hi = 0.4 #0.2
# stuff to be removed after bugfix for hierblock2s
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.time_sync = gr.kludge_copy(gr.sizeof_char)
self.epsilon = (self,1)
self.connect((self,0),self.input)
self.connect((self,2),self.time_sync)
delay(gr.sizeof_char,
block_header.schmidl_fine_sync[0]*block_length)
# sample ofdm symbol (preamble 1 and 2)
sampler_symbol1 = vector_sampler(gr.sizeof_gr_complex,fft_length)
sampler_symbol2 = vector_sampler(gr.sizeof_gr_complex,fft_length)
time_delay1 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[1])
self.connect(self.input, (sampler_symbol1,0))
self.connect(self.input, (sampler_symbol2,0))
if block_header.schmidl_fine_sync[0] > 0:
time_delay0 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[0])
self.connect(self.time_sync, time_delay0, (sampler_symbol1,1))
else:
self.connect(self.time_sync, (sampler_symbol1,1))
self.connect(self.time_sync, time_delay1, (sampler_symbol2,1))
# negative fractional frequency offset estimate
epsilon = gr.multiply_const_ff(-1.0)
self.connect(self.epsilon, epsilon)
# compensate for fractional frequency offset on per symbol base
# freq_shift: vector length, modulator sensitivity
# freq_shift third input: reset phase accumulator
# symbol/preamble 1
freq_shift_sym1 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol1, (freq_shift_sym1,0))
self.connect(epsilon, (freq_shift_sym1,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym1,2))
# symbol/preamble 2
freq_shift_sym2 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol2, (freq_shift_sym2,0))
self.connect(epsilon, (freq_shift_sym2,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym2,2))
# fourier transfrom on both preambles
fft_sym1 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
fft_sym2 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
# calculate schmidl's metric for estimation of freq. offset's integer part
assert(hasattr(block_header, "schmidl_fine_sync"))
pre1 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[0]]
pre2 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[1]]
diff_pn = concatenate([[conjugate(math.sqrt(2)*pre2[2*i]/pre1[2*i]),0.0j] for i in arange(len(pre1)/2)])
cfo_estimator = schmidl_cfo_estimator(fft_length, len(pre1),
self._range, diff_pn)
self.connect(freq_shift_sym1, fft_sym1, (cfo_estimator,0)) # preamble 1
self.connect(freq_shift_sym2, fft_sym2, (cfo_estimator,1)) # preamble 2
# search for maximum and its argument in interval [-range .. +range]
#arg_max = arg_max_vff(2*self._range + 1)
arg_max_s = gr.argmax_fs(2*self._range+1)
arg_max = gr.short_to_float()
ifo_max = gr.max_ff(2*self._range + 1) # vlen
ifo_estimate = gr.add_const_ff(-self._range)
self.connect(cfo_estimator, arg_max_s, arg_max, ifo_estimate)
self.connect(cfo_estimator, ifo_max)
self.connect((arg_max_s,1),gr.null_sink(gr.sizeof_short))
# threshold maximal value
ifo_threshold = gr.threshold_ff(self._thr_lo, self._thr_hi, 0.0)
ifo_thr_f2b = gr.float_to_char()
self.connect(ifo_max, ifo_threshold, ifo_thr_f2b)
# gating the streams ifo_estimate (integer part) and epsilon (frac. part)
# if the metric's peak value was above the chosen threshold, assume to have
# found a new burst. peak value below threshold results in blocking the
# streams
self.gate = gate_ff()
self.connect(ifo_thr_f2b, (self.gate,0)) # threshold stream
self.connect(ifo_estimate, (self.gate,1))
self.connect(epsilon, (self.gate,2))
# peak filtering
# resynchronize and suppress peaks that didn't match a preamble
filtered_time_sync = peak_resync_bb(True) # replace
self.connect(self.time_sync, (filtered_time_sync,0))
self.connect(ifo_thr_f2b, (filtered_time_sync,1))
# find complete estimation for frequency offset
# add together fractional and integer part
freq_offset = gr.add_ff()
self.connect((self.gate,1), gr.multiply_const_ff(-1.0), (freq_offset,0)) # integer offset
self.connect((self.gate,2), (freq_offset,1)) # frac offset
# output connections
self.connect(freq_offset, (self,0))
self.connect(filtered_time_sync, (self,1))
self.connect((self.gate,0), (self,2)) # used for frame trigger
#########################################
# debugging
if options.log:
self.epsilon2_sink = gr.vector_sink_f()
self.connect(epsilon, self.epsilon2_sink)
self.connect(cfo_estimator, gr.file_sink(gr.sizeof_float*(self._range*2+1), "data/ioe_metric.float"))
# output joint stream
preamble_stream = gr.streams_to_vector(fft_length * gr.sizeof_gr_complex, 2)
self.connect(fft_sym1, (preamble_stream,0))
self.connect(fft_sym2, (preamble_stream,1))
self.connect(preamble_stream, gr.file_sink(gr.sizeof_gr_complex * 2 * fft_length, "data/preambles.compl"))
# output, preambles before and after correction, magnitude and complex spectrum
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre1_bef.compl"))
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre1_bef.float"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre2_bef.compl"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre2_bef.float"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre1.compl"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre1.float"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre2.compl"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre2.float"))
# calculate epsilon from corrected source to check function
test_cp = cyclic_prefixer(fft_length, block_length)
test_eps = foe(fft_length)
self.connect(freq_shift_sym1, test_cp, test_eps, gr.file_sink(gr.sizeof_float, "data/eps_after.float"))
try:
gr.hier_block.update_var_names(self, "ifo_estimator", vars())
gr.hier_block.update_var_names(self, "ifo_estimator", vars(self))
except:
pass
def __init__(self,
fft_length,
cp_length,
kstime,
threshold,
threshold_type,
threshold_gap,
logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc()
self.corr = gr.multiply_cc()
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length // 2)]
self.moving_sum_filter = gr.fir_filter_ccf(1, moving_sum_taps)
else:
moving_sum_taps = [
complex(1.0, 0.0) for i in range(fft_length // 2)
]
self.moving_sum_filter = gr.fft_filter_ccc(1, moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length // 2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1, movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1, movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(
0.20, 0.20, 30, 0.001
) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate == 1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor,
self.threshold_factor, 0,
fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0,
fft_length, threshold_type,
threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag,
self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag,
gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(
self.matched_filter,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(
self.normalize,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(
self.angle,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(
self.pk_detect,
gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(
self.sample_and_hold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(
self.input,
gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(
self,
agc_max=100,
agc_decay=0.1,
freq_offset=1000000,
outfile="datafifo",
bandpass_bandwidth=20,
threshold_buffer=0.25,
threshold_center=0.5,
agc_attack=0.1,
bandpass_transition_width=1000000,
):
gr.top_block.__init__(self, "Collect")
##################################################
# Parameters
##################################################
self.agc_max = agc_max
self.agc_decay = agc_decay
self.freq_offset = freq_offset
self.outfile = outfile
self.bandpass_bandwidth = bandpass_bandwidth
self.threshold_buffer = threshold_buffer
self.threshold_center = threshold_center
self.agc_attack = agc_attack
self.bandpass_transition_width = bandpass_transition_width
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 64000000
##################################################
# Blocks
##################################################
self.uhd_usrp_source_0 = uhd.usrp_source(device_addr="", io_type=uhd.io_type.COMPLEX_FLOAT32, num_channels=1)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(915000000 - freq_offset, 0)
self.uhd_usrp_source_0.set_gain(0, 0)
self.uhd_usrp_source_0.set_antenna("TX/RX", 0)
self.gr_threshold_ff_0 = gr.threshold_ff(
threshold_center - threshold_buffer, threshold_center + threshold_buffer, 0
)
self.gr_map_bb_0 = gr.map_bb(([48, 49]))
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char * 1, outfile)
self.gr_file_sink_0.set_unbuffered(False)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.gr_agc2_xx_0_0 = gr.agc2_cc(agc_attack, agc_decay, 1.0, 1.0, agc_max)
self.band_pass_filter_0 = gr.fir_filter_ccf(
1,
firdes.band_pass(
1,
samp_rate,
freq_offset - bandpass_bandwidth / 2,
freq_offset + bandpass_bandwidth / 2,
bandpass_transition_width,
firdes.WIN_HAMMING,
6.76,
),
)
##################################################
# Connections
##################################################
self.connect((self.gr_float_to_char_0, 0), (self.gr_map_bb_0, 0))
self.connect((self.gr_map_bb_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.gr_agc2_xx_0_0, 0))
self.connect((self.gr_agc2_xx_0_0, 0), (self.band_pass_filter_0, 0))
self.connect((self.gr_threshold_ff_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_complex_to_mag_0, 0), (self.gr_threshold_ff_0, 0))
self.connect((self.band_pass_filter_0, 0), (self.gr_complex_to_mag_0, 0))
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="USRP LRIT Receiver")
##################################################
# Variables
##################################################
self.config_filename = config_filename = "usrp_rx_lrit.cfg"
self._saved_decim_config = ConfigParser.ConfigParser()
self._saved_decim_config.read(config_filename)
try: saved_decim = self._saved_decim_config.getint("main", "decim")
except: saved_decim = 160
self.saved_decim = saved_decim
self.decim = decim = saved_decim
self.symbol_rate = symbol_rate = 293e3
self._saved_gain_mu_config = ConfigParser.ConfigParser()
self._saved_gain_mu_config.read(config_filename)
try: saved_gain_mu = self._saved_gain_mu_config.getfloat("main", "gain_mu")
except: saved_gain_mu = 0.005
self.saved_gain_mu = saved_gain_mu
self._saved_gain_config = ConfigParser.ConfigParser()
self._saved_gain_config.read(config_filename)
try: saved_gain = self._saved_gain_config.getfloat("main", "gain")
except: saved_gain = 33
self.saved_gain = saved_gain
self._saved_freq_config = ConfigParser.ConfigParser()
self._saved_freq_config.read(config_filename)
try: saved_freq = self._saved_freq_config.getfloat("main", "freq")
except: saved_freq = 137e6
self.saved_freq = saved_freq
self._saved_costas_alpha_config = ConfigParser.ConfigParser()
self._saved_costas_alpha_config.read(config_filename)
try: saved_costas_alpha = self._saved_costas_alpha_config.getfloat("main", "costas_alpha")
except: saved_costas_alpha = 0.005
self.saved_costas_alpha = saved_costas_alpha
self.samp_rate = samp_rate = 64e6/decim
self.sps = sps = samp_rate/symbol_rate
self.gain_mu = gain_mu = saved_gain_mu
self.gain = gain = saved_gain
self.freq = freq = saved_freq
self.costas_alpha = costas_alpha = saved_costas_alpha
##################################################
# Notebooks
##################################################
self.displays = wx.Notebook(self.GetWin(), style=wx.NB_TOP)
self.displays.AddPage(grc_wxgui.Panel(self.displays), "USRP RX")
self.displays.AddPage(grc_wxgui.Panel(self.displays), "Costas Output")
self.GridAdd(self.displays, 2, 0, 1, 3)
##################################################
# Controls
##################################################
self._decim_text_box = forms.text_box(
parent=self.GetWin(),
value=self.decim,
callback=self.set_decim,
label="Decim",
converter=forms.int_converter(),
)
self.GridAdd(self._decim_text_box, 0, 0, 1, 1)
_gain_mu_sizer = wx.BoxSizer(wx.VERTICAL)
self._gain_mu_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_gain_mu_sizer,
value=self.gain_mu,
callback=self.set_gain_mu,
label="Gain Mu",
converter=forms.float_converter(),
proportion=0,
)
self._gain_mu_slider = forms.slider(
parent=self.GetWin(),
sizer=_gain_mu_sizer,
value=self.gain_mu,
callback=self.set_gain_mu,
minimum=0,
maximum=0.5,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_gain_mu_sizer, 1, 1, 1, 1)
_gain_sizer = wx.BoxSizer(wx.VERTICAL)
self._gain_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
label="Gain",
converter=forms.float_converter(),
proportion=0,
)
self._gain_slider = forms.slider(
parent=self.GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
minimum=0,
maximum=115,
num_steps=115,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_gain_sizer, 0, 1, 1, 1)
_freq_sizer = wx.BoxSizer(wx.VERTICAL)
self._freq_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_freq_sizer,
value=self.freq,
callback=self.set_freq,
label="Frequency",
converter=forms.float_converter(),
proportion=0,
)
self._freq_slider = forms.slider(
parent=self.GetWin(),
sizer=_freq_sizer,
value=self.freq,
callback=self.set_freq,
minimum=135e6,
maximum=139e6,
num_steps=400,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_freq_sizer, 0, 2, 1, 1)
_costas_alpha_sizer = wx.BoxSizer(wx.VERTICAL)
self._costas_alpha_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_costas_alpha_sizer,
value=self.costas_alpha,
callback=self.set_costas_alpha,
label="Costas Alpha",
converter=forms.float_converter(),
proportion=0,
)
self._costas_alpha_slider = forms.slider(
parent=self.GetWin(),
sizer=_costas_alpha_sizer,
value=self.costas_alpha,
callback=self.set_costas_alpha,
minimum=0,
maximum=0.5,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_costas_alpha_sizer, 1, 0, 1, 1)
##################################################
# Blocks
##################################################
self.gr_add_const_vxx_0 = gr.add_const_vff((48.0, ))
self.gr_agc_xx_0 = gr.agc_cc(1e-6, 1.0, 1.0/32767.0, 1.0)
self.gr_binary_slicer_fb_0 = gr.binary_slicer_fb()
self.gr_char_to_float_0 = gr.char_to_float()
self.gr_complex_to_real_0 = gr.complex_to_real(1)
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char*1, "bits.dat")
self.gr_file_source_0 = gr.file_source(gr.sizeof_gr_complex*1, "lrit.dat", False)
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_mpsk_receiver_cc_0 = gr.mpsk_receiver_cc(2, 0, costas_alpha, costas_alpha*costas_alpha/4.0, -0.05, 0.05, 0.5, gain_mu, sps, gain_mu*gain_mu/4.0, 0.05)
self.gr_probe_mpsk_snr_c_0 = grc_blks2.probe_mpsk_snr_c(
type='snr',
alpha=0.0001,
probe_rate=10,
)
self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate)
self.wxgui_fftsink2_0 = fftsink2.fft_sink_c(
self.displays.GetPage(0).GetWin(),
baseband_freq=freq,
y_per_div=10,
y_divs=10,
ref_level=50,
sample_rate=samp_rate,
fft_size=1024,
fft_rate=30,
average=False,
avg_alpha=None,
title="Spectrum",
peak_hold=False,
)
self.displays.GetPage(0).GridAdd(self.wxgui_fftsink2_0.win, 0, 0, 1, 1)
self.wxgui_numbersink2_0 = numbersink2.number_sink_f(
self.displays.GetPage(1).GetWin(),
unit="dB",
minval=0,
maxval=30,
factor=1.0,
decimal_places=1,
ref_level=0,
sample_rate=10,
number_rate=10,
average=False,
avg_alpha=None,
label="SNR",
peak_hold=False,
show_gauge=True,
)
self.displays.GetPage(1).GridAdd(self.wxgui_numbersink2_0.win, 2, 0, 1, 1)
self.wxgui_scopesink2_0 = scopesink2.scope_sink_c(
self.displays.GetPage(0).GetWin(),
title="Waveform",
sample_rate=samp_rate,
v_scale=0.5,
t_scale=20.0/samp_rate,
ac_couple=False,
xy_mode=True,
num_inputs=1,
)
self.displays.GetPage(0).GridAdd(self.wxgui_scopesink2_0.win, 1, 0, 1, 1)
self.wxgui_scopesink2_1 = scopesink2.scope_sink_c(
self.displays.GetPage(1).GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0.4,
t_scale=20.0/samp_rate,
ac_couple=False,
xy_mode=True,
num_inputs=1,
)
self.displays.GetPage(1).GridAdd(self.wxgui_scopesink2_1.win, 0, 0, 1, 1)
##################################################
# Connections
##################################################
self.connect((self.gr_agc_xx_0, 0), (self.wxgui_scopesink2_0, 0))
self.connect((self.gr_file_source_0, 0), (self.gr_throttle_0, 0))
self.connect((self.gr_throttle_0, 0), (self.gr_agc_xx_0, 0))
self.connect((self.gr_probe_mpsk_snr_c_0, 0), (self.wxgui_numbersink2_0, 0))
self.connect((self.gr_mpsk_receiver_cc_0, 0), (self.gr_probe_mpsk_snr_c_0, 0))
self.connect((self.gr_agc_xx_0, 0), (self.gr_mpsk_receiver_cc_0, 0))
self.connect((self.gr_mpsk_receiver_cc_0, 0), (self.wxgui_scopesink2_1, 0))
self.connect((self.gr_agc_xx_0, 0), (self.wxgui_fftsink2_0, 0))
self.connect((self.gr_mpsk_receiver_cc_0, 0), (self.gr_complex_to_real_0, 0))
self.connect((self.gr_complex_to_real_0, 0), (self.gr_binary_slicer_fb_0, 0))
self.connect((self.gr_binary_slicer_fb_0, 0), (self.gr_char_to_float_0, 0))
self.connect((self.gr_char_to_float_0, 0), (self.gr_add_const_vxx_0, 0))
self.connect((self.gr_add_const_vxx_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_float_to_char_0, 0), (self.gr_file_sink_0, 0))