def main(options):
"""
Main function.
@param options
"""
options.my_ip = all_radios_ip[options.my_id]
radio = build_radio(options)
radio.id = options.my_id
radio.set_gain(radios_gain[radio.id])
tb = OpERAFlow('OperaFlow')
tb.add_radio(radio, 'radio')
tb.start()
channel_list = [Channel(ch=0, freq=1.11e9, bw=200e3),
Channel(ch=1, freq=1.51e9, bw=400e3),
Channel(ch=2, freq=1.7e9, bw=500e3),
Channel(ch=3, freq=1.9e9, bw=400e3),
]
cognitive_radio_loop(options, radio, channel_list)
tb.stop()
tb.wait()
def main(options):
"""
Main function
@param options
"""
options.my_ip = all_radios_ip[options.my_id]
radio = build_radio(options)
radio.id = options.my_id
tb = OpERAFlow('OperaFlow')
tb.add_radio(radio, 'radio')
tb.start()
channel_list = [Channel(ch=0, freq=2.2e9, bw=200e3), ]
cognitive_radio_loop(options, radio, channel_list)
tb.stop()
tb.wait()
class QaEnergyDetector(gr_unittest.TestCase):
"""
QA related to EnergyDetector class.
"""
def setUp(self):
"""
Set globals for all tests. Called before a test is started.
"""
self.tb = OpERAFlow(name='top')
def tear_down(self):
"""
Destroy globals for all tests. Called right after a test if finished.
"""
self.tb = None
def test_001(self):
"""
Test the energy of a simple sequence (1, 2, -1, -2).
"""
# input and expected results
src_data = (1, 1, 1, 1)
expected_result = 1
# blocks
fft_size = len(src_data)
mavg_size = 1
src = blocks.vector_source_c(data=src_data)
dst = blocks.probe_signal_f()
ed = EnergySSArch(fft_size, mavg_size, EnergyDecision(1))
#radio_device = RadioDevice(the_source = src, the_sink = dst)
radio_device = RadioDevice()
radio_device.add_arch(source=src, arch=ed, sink=dst, uhd_device=None, name='ed')
################ FIM NOVO RADIO DEVICE
## flowgraph
##self.tb.add_arch(ed, radio_device, 'ed')
self.tb.add_radio(radio_device)
self.tb.run()
result_data = dst.level()
self.assertEqual(expected_result, result_data)
def test_002(self):
"""
Test a sequence with float number (0.1, 0.1, 0.1, 0.1).
"""
# input and expected results
src_data = (0.1, 0.1, 0.1, 0.1)
expected_result = 0
# blocks
fft_size = len(src_data)
mavg_size = 1
src = blocks.vector_source_c(data=src_data)
ed = EnergyDetectorC(fft_size, mavg_size, EnergyDecision(1))
dst = blocks.probe_signal_f()
# flowgraph
self.tb.connect(src, ed, dst)
self.tb.run()
result_data = dst.level()
self.assertEqual(expected_result, result_data)
def test_003(self):
"""
Test EDTopBlock with the input (1, 1, 1, 1, 1, 1, 1, 1).
"""
arr = (1, 1, 1, 1, 1, 1, 1, 1)
expected_out = 8
ed = EnergySSArch(fft_size=len(arr),
mavg_size=8,
algorithm=EnergyDecision(expected_out - 1)
)
src = blocks.vector_source_c(data=arr, vlen=1)
sink = blocks.probe_signal_f()
device = RadioDevice()
device.add_arch(source=src, arch=ed, sink=sink, uhd_device=None, name='ed')
self.tb.add_radio(device, 'ed')
self.tb.run()
##self.assertEqual(1 , device.sink.level()) # didn't work
self.assertEqual(1, device.output()[0])
def test_004(self):
"""
Test EDTopBlock with a simple input (1, 2, 3, 4).
"""
arr = (1.0, 2.0, 3.0, 4.0)
expected_result = 30 # before expected result was 2536
ed = EnergySSArch(fft_size=len(arr),
mavg_size=1,
algorithm=EnergyDecision(expected_result + 1) # (expected_out + 1)
)
src = blocks.vector_source_c(data=arr, vlen=1)
sink = blocks.probe_signal_f()
device = RadioDevice()
device.add_arch(source=src, arch=ed, sink=sink, uhd_device=None, name='ed')
self.tb.add_radio(device, 'ed')
self.tb.start()
self.tb.wait()
###self.assertEqual(expected_result , device.sink.output()[1])
self.assertEqual(expected_result, device.ed.output()[1]) # uses 'name' parameter of the add_arch method
