def test_bpsk_mapping():
expected_symbolstream = numpy.array([1 + 1j, -1 - 1j])/numpy.sqrt(2)
actual_bitstream = numpy.array([0, 1])
actual_symbolstream = iq_mapper.bpsk(actual_bitstream)
results = utils.isclose(
expected_symbolstream, actual_symbolstream, atol=0.01, rtol=0.01
)
assert (results).all()
def test_qam16_mapping():
expected_symbolstream = numpy.array(
[+1 + 1j, 1 + 3j, 3 + 1j, 3 + 3j,
+1 - 1j, 1 - 3j, 3 - 1j, 3 - 3j,
-1 + 1j, -1 + 3j, -3 + 1j, -3 + 3j,
-1 - 1j, -1 - 3j, -3 - 1j, -3 - 3j]
)/numpy.sqrt(10)
actual_bitstream = numpy.array(
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1,
0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1,
1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1,
1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1]
)
actual_symbolstream = iq_mapper.qam16(actual_bitstream)
results = utils.isclose(
expected_symbolstream, actual_symbolstream, atol=0.01, rtol=0.01
)
assert (results).all()
def test_qam():
time = numpy.linspace(0, 1, int(1e5))
symbol_duration = 0.25
carrier_freq = 400
angular_freq = 2 * numpy.pi * carrier_freq
expected_symbolstream = numpy.array([-1 - 2j, -3 + 4j, 5 - 6j, 7 + 8j])
actual_waveform_cos1 = -1 * numpy.cos(angular_freq * time[0:25000])
actual_waveform_sin1 = -2 * numpy.sin(angular_freq * time[0:25000])
actual_waveform_cos2 = -3 * numpy.cos(angular_freq * time[25000:50000])
actual_waveform_sin2 = +4 * numpy.sin(angular_freq * time[25000:50000])
actual_waveform_cos3 = +5 * numpy.cos(angular_freq * time[50000:75000])
actual_waveform_sin3 = -6 * numpy.sin(angular_freq * time[50000:75000])
actual_waveform_cos4 = +7 * numpy.cos(angular_freq * time[75000:100000])
actual_waveform_sin4 = +8 * numpy.sin(angular_freq * time[75000:100000])
actual_waveform = numpy.stack([
actual_waveform_cos1 + actual_waveform_sin1,
actual_waveform_cos2 + actual_waveform_sin2,
actual_waveform_cos3 + actual_waveform_sin3,
actual_waveform_cos4 + actual_waveform_sin4
]).flatten()
actual_symbolstream = wave_detector.qam(time, actual_waveform,
symbol_duration, carrier_freq)
assert (utils.isclose(expected_symbolstream, actual_symbolstream)).all()
def test_qam():
time = numpy.linspace(0, 1, int(1e5))
carrier_freq = 400
angular_freq = 2*numpy.pi*carrier_freq
symbol_duration = 0.25
expected_waveform_cos1 = +1*numpy.cos(angular_freq*time[0:25000])
expected_waveform_sin1 = +2*numpy.sin(angular_freq*time[0:25000])
expected_waveform_cos2 = +3*numpy.cos(angular_freq*time[25000:50000])
expected_waveform_sin2 = -4*numpy.sin(angular_freq*time[25000:50000])
expected_waveform_cos3 = -5*numpy.cos(angular_freq*time[50000:75000])
expected_waveform_sin3 = +6*numpy.sin(angular_freq*time[50000:75000])
expected_waveform_cos4 = -7*numpy.cos(angular_freq*time[75000:100000])
expected_waveform_sin4 = -8*numpy.sin(angular_freq*time[75000:100000])
expected_waveform = numpy.stack(
[expected_waveform_cos1 + expected_waveform_sin1,
expected_waveform_cos2 + expected_waveform_sin2,
expected_waveform_cos3 + expected_waveform_sin3,
expected_waveform_cos4 + expected_waveform_sin4]
).flatten()
actual_symbolstream = numpy.array([1 + 2j, 3 - 4j, -5 + 6j, -7 - 8j])
actual_waveform = wave_generator.qam(
time, actual_symbolstream, symbol_duration, carrier_freq
)
assert (utils.isclose(expected_waveform, actual_waveform)).all()
def test_isclose(expected, arg1, arg2, atol, rtol):
assert (expected == utils.isclose(arg1, arg2, atol=atol, rtol=rtol))