def test_shape(self):
# Without cover code
self.assertEqual(self.dmrs_seq1.shape, (12, ))
self.assertEqual(self.dmrs_seq2.shape, (12, ))
self.assertEqual(self.dmrs_seq3.shape, (24, ))
self.assertEqual(self.dmrs_seq4.shape, (24, ))
self.assertEqual(self.dmrs_seq5.shape, (48, ))
self.assertEqual(self.dmrs_seq6.shape, (48, ))
# With cover code
root_seq1 = RootSequence(root_index=15, size=12)
cover_code1 = np.array([1, 1])
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
cover_code=cover_code1)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
root_seq5 = RootSequence(root_index=15, size=48)
cover_code5 = np.array([1, -1, 1, -1])
dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5,
n_cs=3,
cover_code=cover_code5)
self.assertEqual(dmrs_seq1.shape, (2, 12))
self.assertEqual(dmrs_seq2.shape, (2, 12))
self.assertEqual(dmrs_seq5.shape, (4, 48))
def test_repr(self):
root_seq1 = RootSequence(root_index=15, size=12)
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1, n_cs=3)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
self.assertEqual(
"<DmrsUeSequence(root_index=15, n_cs=3, cover_code=None)>",
repr(dmrs_seq1))
self.assertEqual(
"<DmrsUeSequence(root_index=23, n_cs=4, cover_code=[ 1 -1])>",
repr(dmrs_seq2))
def test_getitem(self):
seqs = [self.dmrs_seq1, self.dmrs_seq2, self.dmrs_seq3, self.dmrs_seq4]
for seq in seqs:
np.testing.assert_almost_equal(seq[4], seq.seq_array()[4])
np.testing.assert_almost_equal(seq[3:15], seq.seq_array()[3:15])
np.testing.assert_almost_equal(seq[3:40:2],
seq.seq_array()[3:40:2])
# Now let's test with a DMRS sequence with cover codes. The first
# dimension of the underlying numpy array is the cover code index
root_seq = RootSequence(root_index=23, size=12)
cover_code = np.array([1, -1])
dmrs_seq = DmrsUeSequence(root_seq=root_seq,
n_cs=4,
cover_code=cover_code)
np.testing.assert_almost_equal(dmrs_seq[0, 4],
dmrs_seq.seq_array()[0, 4])
np.testing.assert_almost_equal(dmrs_seq[1, 0:8:2],
dmrs_seq.seq_array()[1, 0:8:2])
class DmrsUeSequenceTestCase(unittest.TestCase):
def setUp(self):
"""Called before each test."""
root_seq1 = RootSequence(root_index=15, size=12)
self.dmrs_seq1 = DmrsUeSequence(
root_seq=root_seq1, n_cs=3)
root_seq2 = RootSequence(root_index=23, size=12)
self.dmrs_seq2 = DmrsUeSequence(
root_seq=root_seq2, n_cs=4)
root_seq3 = RootSequence(root_index=15, size=24)
self.dmrs_seq3 = DmrsUeSequence(
root_seq=root_seq3, n_cs=3)
root_seq4 = RootSequence(root_index=23, size=24)
self.dmrs_seq4 = DmrsUeSequence(
root_seq=root_seq4, n_cs=4)
root_seq5 = RootSequence(root_index=15, size=48)
self.dmrs_seq5 = DmrsUeSequence(
root_seq=root_seq5, n_cs=3)
root_seq6 = RootSequence(root_index=23, size=48)
self.dmrs_seq6 = DmrsUeSequence(
root_seq=root_seq6, n_cs=4)
def test_size(self):
self.assertEqual(self.dmrs_seq1.size, 12)
self.assertEqual(self.dmrs_seq2.size, 12)
self.assertEqual(self.dmrs_seq3.size, 24)
self.assertEqual(self.dmrs_seq4.size, 24)
self.assertEqual(self.dmrs_seq5.size, 48)
self.assertEqual(self.dmrs_seq6.size, 48)
def test_seq_array(self):
expected_dmrs1 = get_dmrs_seq(RootSequence(15, 12).seq_array(), 3)
expected_dmrs2 = get_dmrs_seq(RootSequence(23, 12).seq_array(), 4)
expected_dmrs3 = get_dmrs_seq(RootSequence(15, 24).seq_array(), 3)
expected_dmrs4 = get_dmrs_seq(RootSequence(23, 24).seq_array(), 4)
expected_dmrs5 = get_dmrs_seq(RootSequence(15, 48).seq_array(), 3)
expected_dmrs6 = get_dmrs_seq(RootSequence(23, 48).seq_array(), 4)
np.testing.assert_array_almost_equal(
expected_dmrs1, self.dmrs_seq1.seq_array())
np.testing.assert_array_almost_equal(
expected_dmrs2, self.dmrs_seq2.seq_array())
np.testing.assert_array_almost_equal(
expected_dmrs3, self.dmrs_seq3.seq_array())
np.testing.assert_array_almost_equal(
expected_dmrs4, self.dmrs_seq4.seq_array())
np.testing.assert_array_almost_equal(
expected_dmrs5, self.dmrs_seq5.seq_array())
np.testing.assert_array_almost_equal(
expected_dmrs6, self.dmrs_seq6.seq_array())
def setUp(self):
"""Called before each test."""
root_seq1 = RootSequence(root_index=15, size=12)
self.dmrs_seq1 = DmrsUeSequence(
root_seq=root_seq1, n_cs=3)
root_seq2 = RootSequence(root_index=23, size=12)
self.dmrs_seq2 = DmrsUeSequence(
root_seq=root_seq2, n_cs=4)
root_seq3 = RootSequence(root_index=15, size=24)
self.dmrs_seq3 = DmrsUeSequence(
root_seq=root_seq3, n_cs=3)
root_seq4 = RootSequence(root_index=23, size=24)
self.dmrs_seq4 = DmrsUeSequence(
root_seq=root_seq4, n_cs=4)
root_seq5 = RootSequence(root_index=15, size=48)
self.dmrs_seq5 = DmrsUeSequence(
root_seq=root_seq5, n_cs=3)
root_seq6 = RootSequence(root_index=23, size=48)
self.dmrs_seq6 = DmrsUeSequence(
root_seq=root_seq6, n_cs=4)
def setUp(self):
"""Called before each test."""
root_seq1 = RootSequence(root_index=15, size=12)
self.dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
normalize=True)
root_seq2 = RootSequence(root_index=23, size=12)
self.dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2, n_cs=4)
root_seq3 = RootSequence(root_index=15, size=24)
self.dmrs_seq3 = DmrsUeSequence(root_seq=root_seq3, n_cs=3)
root_seq4 = RootSequence(root_index=23, size=24)
self.dmrs_seq4 = DmrsUeSequence(root_seq=root_seq4,
n_cs=4,
normalize=True)
root_seq5 = RootSequence(root_index=15, size=48)
self.dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5, n_cs=3)
root_seq6 = RootSequence(root_index=23, size=48)
self.dmrs_seq6 = DmrsUeSequence(root_seq=root_seq6, n_cs=4)
class DmrsUeSequenceTestCase(unittest.TestCase):
def setUp(self):
"""Called before each test."""
root_seq1 = RootSequence(root_index=15, size=12)
self.dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
normalize=True)
root_seq2 = RootSequence(root_index=23, size=12)
self.dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2, n_cs=4)
root_seq3 = RootSequence(root_index=15, size=24)
self.dmrs_seq3 = DmrsUeSequence(root_seq=root_seq3, n_cs=3)
root_seq4 = RootSequence(root_index=23, size=24)
self.dmrs_seq4 = DmrsUeSequence(root_seq=root_seq4,
n_cs=4,
normalize=True)
root_seq5 = RootSequence(root_index=15, size=48)
self.dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5, n_cs=3)
root_seq6 = RootSequence(root_index=23, size=48)
self.dmrs_seq6 = DmrsUeSequence(root_seq=root_seq6, n_cs=4)
def test_size(self):
# Without cover code
self.assertEqual(self.dmrs_seq1.size, 12)
self.assertEqual(self.dmrs_seq2.size, 12)
self.assertEqual(self.dmrs_seq3.size, 24)
self.assertEqual(self.dmrs_seq4.size, 24)
self.assertEqual(self.dmrs_seq5.size, 48)
self.assertEqual(self.dmrs_seq6.size, 48)
# With cover code
root_seq1 = RootSequence(root_index=15, size=12)
cover_code1 = np.array([1, 1])
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
cover_code=cover_code1)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
root_seq5 = RootSequence(root_index=15, size=48)
cover_code5 = np.array([1, -1, 1, -1])
dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5,
n_cs=3,
cover_code=cover_code5)
self.assertEqual(dmrs_seq1.size, 12)
self.assertEqual(dmrs_seq2.size, 12)
self.assertEqual(dmrs_seq5.size, 48)
def test_shape(self):
# Without cover code
self.assertEqual(self.dmrs_seq1.shape, (12, ))
self.assertEqual(self.dmrs_seq2.shape, (12, ))
self.assertEqual(self.dmrs_seq3.shape, (24, ))
self.assertEqual(self.dmrs_seq4.shape, (24, ))
self.assertEqual(self.dmrs_seq5.shape, (48, ))
self.assertEqual(self.dmrs_seq6.shape, (48, ))
# With cover code
root_seq1 = RootSequence(root_index=15, size=12)
cover_code1 = np.array([1, 1])
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
cover_code=cover_code1)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
root_seq5 = RootSequence(root_index=15, size=48)
cover_code5 = np.array([1, -1, 1, -1])
dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5,
n_cs=3,
cover_code=cover_code5)
self.assertEqual(dmrs_seq1.shape, (2, 12))
self.assertEqual(dmrs_seq2.shape, (2, 12))
self.assertEqual(dmrs_seq5.shape, (4, 48))
def test_seq_array(self):
# xxxxxxxxxx Test withoyut cover code xxxxxxxxxxxxxxxxxxxxxxxxxxxxx
expected_dmrs1 = get_dmrs_seq(RootSequence(15, 12).seq_array(), 3)
expected_dmrs1 /= math.sqrt(expected_dmrs1.size)
expected_dmrs2 = get_dmrs_seq(RootSequence(23, 12).seq_array(), 4)
expected_dmrs3 = get_dmrs_seq(RootSequence(15, 24).seq_array(), 3)
expected_dmrs4 = get_dmrs_seq(RootSequence(23, 24).seq_array(), 4)
expected_dmrs4 /= math.sqrt(expected_dmrs4.size)
expected_dmrs5 = get_dmrs_seq(RootSequence(15, 48).seq_array(), 3)
expected_dmrs6 = get_dmrs_seq(RootSequence(23, 48).seq_array(), 4)
np.testing.assert_array_almost_equal(expected_dmrs1,
self.dmrs_seq1.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs2,
self.dmrs_seq2.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs3,
self.dmrs_seq3.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs4,
self.dmrs_seq4.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs5,
self.dmrs_seq5.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs6,
self.dmrs_seq6.seq_array())
self.assertIsNone(self.dmrs_seq1.cover_code)
self.assertIsNone(self.dmrs_seq2.cover_code)
self.assertIsNone(self.dmrs_seq3.cover_code)
self.assertIsNone(self.dmrs_seq4.cover_code)
self.assertIsNone(self.dmrs_seq5.cover_code)
self.assertIsNone(self.dmrs_seq6.cover_code)
# xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# xxxxxxxxxx Test with cover code xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
root_seq1 = RootSequence(root_index=15, size=12)
cover_code1 = np.array([1, 1])
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
cover_code=cover_code1,
normalize=True)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
root_seq3 = RootSequence(root_index=15, size=24)
cover_code3 = np.array([-1, 1])
dmrs_seq3 = DmrsUeSequence(root_seq=root_seq3,
n_cs=3,
cover_code=cover_code3)
root_seq4 = RootSequence(root_index=23, size=24)
cover_code4 = np.array([-1, -1])
dmrs_seq4 = DmrsUeSequence(root_seq=root_seq4,
n_cs=4,
cover_code=cover_code4,
normalize=True)
root_seq5 = RootSequence(root_index=15, size=48)
cover_code5 = np.array([1, -1, 1, -1])
dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5,
n_cs=3,
cover_code=cover_code5)
# Test that OCC was set
np.testing.assert_array_equal(np.array([1, 1]), dmrs_seq1.cover_code)
np.testing.assert_array_equal(np.array([1, -1]), dmrs_seq2.cover_code)
np.testing.assert_array_equal(np.array([-1, 1]), dmrs_seq3.cover_code)
np.testing.assert_array_equal(np.array([-1, -1]), dmrs_seq4.cover_code)
np.testing.assert_array_equal(np.array([1, -1, 1, -1]),
dmrs_seq5.cover_code)
# Test getting the full sequence with cover code using
# `seq_array()` method
expected_dmrs1_occ = np.vstack([expected_dmrs1, expected_dmrs1])
expected_dmrs2_occ = np.vstack([expected_dmrs2, -expected_dmrs2])
expected_dmrs3_occ = np.vstack([-expected_dmrs3, expected_dmrs3])
expected_dmrs4_occ = np.vstack([-expected_dmrs4, -expected_dmrs4])
expected_dmrs5_occ = np.vstack(
[expected_dmrs5, -expected_dmrs5, expected_dmrs5, -expected_dmrs5])
np.testing.assert_array_almost_equal(expected_dmrs1_occ,
dmrs_seq1.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs2_occ,
dmrs_seq2.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs3_occ,
dmrs_seq3.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs4_occ,
dmrs_seq4.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs5_occ,
dmrs_seq5.seq_array())
# xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
def test_getitem(self):
seqs = [self.dmrs_seq1, self.dmrs_seq2, self.dmrs_seq3, self.dmrs_seq4]
for seq in seqs:
np.testing.assert_almost_equal(seq[4], seq.seq_array()[4])
np.testing.assert_almost_equal(seq[3:15], seq.seq_array()[3:15])
np.testing.assert_almost_equal(seq[3:40:2],
seq.seq_array()[3:40:2])
# Now let's test with a DMRS sequence with cover codes. The first
# dimension of the underlying numpy array is the cover code index
root_seq = RootSequence(root_index=23, size=12)
cover_code = np.array([1, -1])
dmrs_seq = DmrsUeSequence(root_seq=root_seq,
n_cs=4,
cover_code=cover_code)
np.testing.assert_almost_equal(dmrs_seq[0, 4],
dmrs_seq.seq_array()[0, 4])
np.testing.assert_almost_equal(dmrs_seq[1, 0:8:2],
dmrs_seq.seq_array()[1, 0:8:2])
def test_repr(self):
root_seq1 = RootSequence(root_index=15, size=12)
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1, n_cs=3)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
self.assertEqual(
"<DmrsUeSequence(root_index=15, n_cs=3, cover_code=None)>",
repr(dmrs_seq1))
self.assertEqual(
"<DmrsUeSequence(root_index=23, n_cs=4, cover_code=[ 1 -1])>",
repr(dmrs_seq2))
def test_estimate_channel_multiple_rx(self):
Nsc = 24
size = Nsc
Nr = 3 # Number of receive antennas
num_taps_to_keep = 15
cover_codes = [np.array([-1, 1]), np.array([1, 1])]
user1_seq = DmrsUeSequence(RootSequence(root_index=25, size=size),
1,
cover_code=cover_codes[0])
user2_seq = DmrsUeSequence(RootSequence(root_index=25, size=size),
4,
cover_code=cover_codes[0])
ue1_channel_estimator = CazacBasedWithOCCChannelEstimator(user1_seq)
speed_terminal = 3 / 3.6 # Speed in m/s
fcDbl = 2.6e9 # Central carrier frequency (in Hz)
subcarrier_bandwidth = 15e3 # Subcarrier bandwidth (in Hz)
wave_length = 3e8 / fcDbl # Carrier wave length
Fd = speed_terminal / wave_length # Doppler Frequency
Ts = 1. / (Nsc * subcarrier_bandwidth) # Sampling interval
L = 16 # Number of jakes taps
# Create the fading generators and set multiple receive antennas
jakes1 = JakesSampleGenerator(Fd, Ts, L, shape=(Nr, 1))
jakes2 = JakesSampleGenerator(Fd, Ts, L, shape=(Nr, 1))
# Create a TDL channel object for each user
tdlchannel1 = TdlChannel(jakes1, channel_profile=COST259_TUx)
tdlchannel2 = TdlChannel(jakes2, channel_profile=COST259_TUx)
# Generate channel that would corrupt the transmit signal.
tdlchannel1.generate_impulse_response(1)
tdlchannel2.generate_impulse_response(1)
# Get the generated impulse response
impulse_response1 = tdlchannel1.get_last_impulse_response()
impulse_response2 = tdlchannel2.get_last_impulse_response()
# Get the corresponding frequency response
freq_resp_1 = impulse_response1.get_freq_response(Nsc)
H1 = freq_resp_1[:, :, 0, 0].T
freq_resp_2 = impulse_response2.get_freq_response(Nsc)
H2 = freq_resp_2[:, :, 0, 0].T
# Sequence of the users
r1 = user1_seq.seq_array()
r2 = user2_seq.seq_array()
# Received signal (in frequency domain) of user 1
Y1 = H1[:, np.newaxis, :] * r1[np.newaxis, :, :]
Y2 = H2[:, np.newaxis, :] * r2[np.newaxis, :, :]
Y = Y1 + Y2 # Dimension: `Nr x cover_code_size x num_elements`
# Calculate expected estimated channel for user 1
cover_code1 = cover_codes[0]
Y_with_cover_code = \
(cover_code1[0] * Y[:,0,:] + cover_code1[1] * Y[:,1,:]) / 2.0
":type: np.ndarray"
r1_no_cover_code = r1[0] * cover_code1[0]
y1 = np.fft.ifft(np.conj(r1_no_cover_code[np.newaxis]) *
Y_with_cover_code,
size,
axis=1)
tilde_h1_espected = y1[:, 0:(num_taps_to_keep + 1)]
tilde_H1_espected = np.fft.fft(tilde_h1_espected, Nsc, axis=1)
# Test the CazacBasedWithOCCChannelEstimator estimation
H1_estimated = ue1_channel_estimator.estimate_channel_freq_domain(
Y, num_taps_to_keep, extra_dimension=True)
np.testing.assert_array_almost_equal(H1_estimated, tilde_H1_espected)
# Test if true channel and estimated channel are similar. Since the
# channel estimation error is higher at the first and last
# subcarriers we will test only the inner 200 subcarriers
error = np.abs(H1 - tilde_H1_espected)
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.shape),
decimal=2)
def test_estimate_channel_with_dmrs(self):
Nsc = 24
size = Nsc
cover_codes = [np.array([-1, 1]), np.array([1, 1])]
user1_seq = DmrsUeSequence(root_seq=RootSequence(root_index=17,
size=size),
n_cs=1,
cover_code=cover_codes[0])
user2_seq = DmrsUeSequence(root_seq=RootSequence(root_index=17,
size=size),
n_cs=4,
cover_code=cover_codes[1])
ue1_channel_estimator = CazacBasedWithOCCChannelEstimator(user1_seq)
speed_terminal = 3 / 3.6 # Speed in m/s
fcDbl = 2.6e9 # Central carrier frequency (in Hz)
subcarrier_bandwidth = 15e3 # Subcarrier bandwidth (in Hz)
wave_length = 3e8 / fcDbl # Carrier wave length
Fd = speed_terminal / wave_length # Doppler Frequency
Ts = 1. / (Nsc * subcarrier_bandwidth) # Sampling interval
L = 16 # Number of jakes taps
jakes1 = JakesSampleGenerator(Fd, Ts, L)
jakes2 = JakesSampleGenerator(Fd, Ts, L)
# Create a TDL channel object for each user
tdlchannel1 = TdlChannel(jakes1, channel_profile=COST259_TUx)
tdlchannel2 = TdlChannel(jakes2, channel_profile=COST259_TUx)
# Generate channel that would corrupt the transmit signal.
tdlchannel1.generate_impulse_response(1)
tdlchannel2.generate_impulse_response(1)
# Get the generated impulse response
impulse_response1 = tdlchannel1.get_last_impulse_response()
impulse_response2 = tdlchannel2.get_last_impulse_response()
# Get the corresponding frequency response
freq_resp_1 = impulse_response1.get_freq_response(Nsc)
H1 = freq_resp_1[:, 0]
freq_resp_2 = impulse_response2.get_freq_response(Nsc)
H2 = freq_resp_2[:, 0]
# Sequence of the users
r1 = user1_seq.seq_array()
r2 = user2_seq.seq_array()
# Received signal (in frequency domain) of user 1
Y1 = H1 * r1
Y2 = H2 * r2
Y = Y1 + Y2
# Calculate expected estimated channel for user 1
cover_code1 = cover_codes[0]
Y_with_cover_code = \
(cover_code1[0] * Y[0] + cover_code1[1] * Y[1]) / 2.0
":type: np.ndarray"
r1_no_cover_code = r1[0] * cover_code1[0]
y1 = np.fft.ifft(np.conj(r1_no_cover_code) * Y_with_cover_code, size)
tilde_h1 = y1[0:4]
tilde_H1 = np.fft.fft(tilde_h1, Nsc)
# Test the CazacBasedWithOCCChannelEstimator estimation
np.testing.assert_array_almost_equal(
ue1_channel_estimator.estimate_channel_freq_domain(
Y, 3, extra_dimension=True), tilde_H1)
# Test if true channel and estimated channel are similar. Since the
# channel estimation error is higher at the first and last
# subcarriers we will test only the inner 200 subcarriers
error = np.abs(H1 - tilde_H1)
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.size),
decimal=2)
def test_seq_array(self):
# xxxxxxxxxx Test withoyut cover code xxxxxxxxxxxxxxxxxxxxxxxxxxxxx
expected_dmrs1 = get_dmrs_seq(RootSequence(15, 12).seq_array(), 3)
expected_dmrs1 /= math.sqrt(expected_dmrs1.size)
expected_dmrs2 = get_dmrs_seq(RootSequence(23, 12).seq_array(), 4)
expected_dmrs3 = get_dmrs_seq(RootSequence(15, 24).seq_array(), 3)
expected_dmrs4 = get_dmrs_seq(RootSequence(23, 24).seq_array(), 4)
expected_dmrs4 /= math.sqrt(expected_dmrs4.size)
expected_dmrs5 = get_dmrs_seq(RootSequence(15, 48).seq_array(), 3)
expected_dmrs6 = get_dmrs_seq(RootSequence(23, 48).seq_array(), 4)
np.testing.assert_array_almost_equal(expected_dmrs1,
self.dmrs_seq1.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs2,
self.dmrs_seq2.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs3,
self.dmrs_seq3.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs4,
self.dmrs_seq4.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs5,
self.dmrs_seq5.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs6,
self.dmrs_seq6.seq_array())
self.assertIsNone(self.dmrs_seq1.cover_code)
self.assertIsNone(self.dmrs_seq2.cover_code)
self.assertIsNone(self.dmrs_seq3.cover_code)
self.assertIsNone(self.dmrs_seq4.cover_code)
self.assertIsNone(self.dmrs_seq5.cover_code)
self.assertIsNone(self.dmrs_seq6.cover_code)
# xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# xxxxxxxxxx Test with cover code xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
root_seq1 = RootSequence(root_index=15, size=12)
cover_code1 = np.array([1, 1])
dmrs_seq1 = DmrsUeSequence(root_seq=root_seq1,
n_cs=3,
cover_code=cover_code1,
normalize=True)
root_seq2 = RootSequence(root_index=23, size=12)
cover_code2 = np.array([1, -1])
dmrs_seq2 = DmrsUeSequence(root_seq=root_seq2,
n_cs=4,
cover_code=cover_code2)
root_seq3 = RootSequence(root_index=15, size=24)
cover_code3 = np.array([-1, 1])
dmrs_seq3 = DmrsUeSequence(root_seq=root_seq3,
n_cs=3,
cover_code=cover_code3)
root_seq4 = RootSequence(root_index=23, size=24)
cover_code4 = np.array([-1, -1])
dmrs_seq4 = DmrsUeSequence(root_seq=root_seq4,
n_cs=4,
cover_code=cover_code4,
normalize=True)
root_seq5 = RootSequence(root_index=15, size=48)
cover_code5 = np.array([1, -1, 1, -1])
dmrs_seq5 = DmrsUeSequence(root_seq=root_seq5,
n_cs=3,
cover_code=cover_code5)
# Test that OCC was set
np.testing.assert_array_equal(np.array([1, 1]), dmrs_seq1.cover_code)
np.testing.assert_array_equal(np.array([1, -1]), dmrs_seq2.cover_code)
np.testing.assert_array_equal(np.array([-1, 1]), dmrs_seq3.cover_code)
np.testing.assert_array_equal(np.array([-1, -1]), dmrs_seq4.cover_code)
np.testing.assert_array_equal(np.array([1, -1, 1, -1]),
dmrs_seq5.cover_code)
# Test getting the full sequence with cover code using
# `seq_array()` method
expected_dmrs1_occ = np.vstack([expected_dmrs1, expected_dmrs1])
expected_dmrs2_occ = np.vstack([expected_dmrs2, -expected_dmrs2])
expected_dmrs3_occ = np.vstack([-expected_dmrs3, expected_dmrs3])
expected_dmrs4_occ = np.vstack([-expected_dmrs4, -expected_dmrs4])
expected_dmrs5_occ = np.vstack(
[expected_dmrs5, -expected_dmrs5, expected_dmrs5, -expected_dmrs5])
np.testing.assert_array_almost_equal(expected_dmrs1_occ,
dmrs_seq1.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs2_occ,
dmrs_seq2.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs3_occ,
dmrs_seq3.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs4_occ,
dmrs_seq4.seq_array())
np.testing.assert_array_almost_equal(expected_dmrs5_occ,
dmrs_seq5.seq_array())
def test_estimate_channel_with_dmrs(self):
Nsc = 24
size = Nsc
user1_seq = DmrsUeSequence(
RootSequence(root_index=17, size=size), 1)
user2_seq = DmrsUeSequence(
RootSequence(root_index=13, size=size), 4)
ue1_channel_estimator = CazacBasedChannelEstimator(user1_seq,
size_multiplier=1)
speed_terminal = 3/3.6 # Speed in m/s
fcDbl = 2.6e9 # Central carrier frequency (in Hz)
subcarrier_bandwidth = 15e3 # Subcarrier bandwidth (in Hz)
wave_length = 3e8/fcDbl # Carrier wave length
Fd = speed_terminal / wave_length # Doppler Frequency
Ts = 1./(Nsc * subcarrier_bandwidth) # Sampling interval
L = 16 # Number of jakes taps
jakes1 = JakesSampleGenerator(Fd, Ts, L)
jakes2 = JakesSampleGenerator(Fd, Ts, L)
# Create a TDL channel object for each user
tdlchannel1 = TdlChannel(jakes1, channel_profile=COST259_TUx)
tdlchannel2 = TdlChannel(jakes2, channel_profile=COST259_TUx)
# Generate channel that would corrupt the transmit signal.
tdlchannel1._generate_impulse_response(1)
tdlchannel2._generate_impulse_response(1)
# Get the generated impulse response
impulse_response1 = tdlchannel1.get_last_impulse_response()
impulse_response2 = tdlchannel2.get_last_impulse_response()
# Get the corresponding frequency response
freq_resp_1 = impulse_response1.get_freq_response(Nsc)
H1 = freq_resp_1[:, 0]
freq_resp_2 = impulse_response2.get_freq_response(Nsc)
H2 = freq_resp_2[:, 0]
# Sequence of the users
r1 = user1_seq.seq_array()
r2 = user2_seq.seq_array()
# Received signal (in frequency domain) of user 1
Y1 = H1 * r1
Y2 = H2 * r2
Y = Y1 + Y2
# Calculate expected estimated channel for user 1
y1 = np.fft.ifft(np.conj(r1) * Y, size)
tilde_h1 = y1[0:4]
tilde_H1 = np.fft.fft(tilde_h1, Nsc)
# xxxxxx DEBUG xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
a = y1[0:4]
A = np.fft.fft(a, Nsc)
import matplotlib.pyplot as plt
# xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Test the CazacBasedChannelEstimator estimation
np.testing.assert_array_almost_equal(
ue1_channel_estimator.estimate_channel_freq_domain(Y, 3),
tilde_H1)
# Test if true channel and estimated channel are similar. Since the
# channel estimation error is higher at the first and last
# subcarriers we will test only the inner 200 subcarriers
error = np.abs(H1[5:-5] - tilde_H1[5:-5])
np.testing.assert_almost_equal(
error/2., np.zeros(error.size), decimal=2)
