def __init__(self, tx_id, rx_id, sample_rate, filename):
"""
Parameters:
sample_rate: int or float
sample_rate of the flowgraph
filename: string
file containing the channel model
Notes:
The modelfile was created with the pickle module and contains a list
of sum of cisoids, each sum of cisoids models the Doppler spectrum
with a specific delay. If one list element is empty this means that
there exist no scatterers with the specified delay. Each sum of
cisoids, i.e. list element, contains again a list of amplitudes and
frequencies.
"""
gr.hier_block2.__init__(self, "Channel Sounder Measurement",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.sample_rate = sample_rate
fp = open(filename, 'r')
model = pickle.load(fp)
self.taps_delays = []
# check for non-empty list elements to find multipath components with a
# certain delay
for idx, mpc in enumerate(model):
if mpc:
self.taps_delays.append(idx)
# print 'taps_delays', self.taps_delays
# create a tapped delay line structure, since the amplitudes of the sum
# of cisoids already contain all the information about the power of a
# Doppler spectrum, the power delay profile is set to 1 for all delays.
self.mpc_channel = mpc_channel_cc(self.taps_delays,
[1] * len(self.taps_delays))
# loop through all delays
for idx, delay in enumerate(self.taps_delays):
adder = gr.add_cc()
# loop through all cisoids of a delay
for iidx, (freq, ampl) in enumerate(model[delay]):
src = gr.sig_source_c(sample_rate, gr.GR_COS_WAVE, freq, ampl)
self.connect(src, (adder, iidx))
# print iidx
self.connect(adder, (self.mpc_channel, idx + 1))
self.connect(self, (self.mpc_channel, 0))
self.connect(self.mpc_channel, self)
def __init__(self, tx_id, rx_id, sample_rate, fmax):
gr.hier_block2.__init__(self, "COST207 Bad Urban 6 paths",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.sample_rate = sample_rate
print sample_rate
# Statistics of this channel, taken from
# "Mobile Radio Channels", Paetzold, 2011, p 357
# Delays of the multipath components in seconds
delays = [0, 0.4e-6, 1.0e-6, 1.6e-6, 5.0e-6, 6.6e-6]
print 'delays', delays
# Delays expressed in samples
self.taps_delays = [int(sample_rate * delay) for delay in delays]
print 'delays in samples', self.taps_delays
# power delay profile
self.pdp = [0.5, 1, 0.5, 0.32, 0.63, 0.4]
# channel options
self.channel_opts = {'N': 2001,
'fmax': fmax}
self.mpc_channel = mpc_channel_cc(self.taps_delays, self.pdp)
# The different multipath components have to be uncorrelated. This is
# the reason for choosing changing values for N
self.mpc1 = gauss_rand_proc_c(sample_rate, "cost207:jakes", "mea",
12, self.channel_opts)
self.mpc2 = gauss_rand_proc_c(sample_rate, "cost207:jakes", "mea",
14, self.channel_opts)
self.mpc3 = gauss_rand_proc_c(sample_rate, "cost207:gauss1", "gmea",
9, self.channel_opts)
self.mpc4 = gauss_rand_proc_c(sample_rate, "cost207:gauss1", "gmea",
10, self.channel_opts)
self.mpc5 = gauss_rand_proc_c(sample_rate, "cost207:gauss2", "gmea",
11, self.channel_opts)
self.mpc6 = gauss_rand_proc_c(sample_rate, "cost207:gauss2", "gmea",
8, self.channel_opts)
self.connect(self, (self.mpc_channel, 0))
self.connect(self.mpc1, (self.mpc_channel, 1))
self.connect(self.mpc2, (self.mpc_channel, 2))
self.connect(self.mpc3, (self.mpc_channel, 3))
self.connect(self.mpc4, (self.mpc_channel, 4))
self.connect(self.mpc5, (self.mpc_channel, 5))
self.connect(self.mpc6, (self.mpc_channel, 6))
self.connect(self.mpc_channel, self)