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_estimate_channel_without_comb_pattern(self):
Nsc = 300 # 300 subcarriers
size = Nsc # The size is also 300, since there is no comb pattern
Nzc = 139
user1_seq = SrsUeSequence(
RootSequence(root_index=25, size=size, Nzc=Nzc), 1)
user2_seq = SrsUeSequence(
RootSequence(root_index=25, size=size, Nzc=Nzc), 4)
# Set size_multiplier to 1, since we won't use the comb pattern
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[0:16]
tilde_H1 = np.fft.fft(tilde_h1, Nsc)
# Test the CazacBasedChannelEstimator estimation
np.testing.assert_array_almost_equal(
ue1_channel_estimator.estimate_channel_freq_domain(Y, 15),
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[50:-50] - tilde_H1[50:-50])
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.size),
decimal=2)
def test_estimate_channel_multiple_rx(self):
Nsc = 300 # 300 subcarriers
size = Nsc // 2
Nzc = 139
user1_seq = SrsUeSequence(RootSequence(root_index=25,
size=size,
Nzc=Nzc),
1,
normalize=True)
user2_seq = SrsUeSequence(RootSequence(root_index=25,
size=size,
Nzc=Nzc),
4,
normalize=True)
ue1_channel_estimator = CazacBasedChannelEstimator(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=(3, 1))
jakes2 = JakesSampleGenerator(Fd, Ts, L, shape=(3, 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]
freq_resp_2 = impulse_response2.get_freq_response(Nsc)
H2 = freq_resp_2[:, :, 0, 0]
# Sequence of the users
r1 = user1_seq.seq_array()
r2 = user2_seq.seq_array()
# Received signal (in frequency domain) of user 1
comb_indexes = np.arange(0, Nsc, 2)
Y1 = H1[comb_indexes, :] * r1[:, np.newaxis]
Y2 = H2[comb_indexes, :] * r2[:, np.newaxis]
Y = Y1 + Y2
# Calculate expected estimated channel for user 1
y1 = np.fft.ifft(r1.size * np.conj(r1[:, np.newaxis]) * Y,
size,
axis=0)
tilde_h1_espected = y1[0:16]
tilde_H1_espected = np.fft.fft(tilde_h1_espected, Nsc, axis=0)
# Test the CazacBasedChannelEstimator estimation
H1_estimated = ue1_channel_estimator.estimate_channel_freq_domain(
Y.T, 15)
np.testing.assert_array_almost_equal(H1_estimated, tilde_H1_espected.T)
# 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[50:-50, :] - tilde_H1_espected[50:-50, :])
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.shape),
decimal=2)
def test_estimate_channel_with_srs(self):
Nsc = 300 # 300 subcarriers
size = Nsc // 2
Nzc = 139
user1_seq = SrsUeSequence(RootSequence(root_index=25,
size=size,
Nzc=Nzc),
1,
normalize=True)
user2_seq = SrsUeSequence(RootSequence(root_index=25,
size=size,
Nzc=Nzc),
4,
normalize=True)
ue1_channel_estimator = CazacBasedChannelEstimator(user1_seq)
ue2_channel_estimator = CazacBasedChannelEstimator(user2_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
comb_indexes = np.arange(0, Nsc, 2)
Y1 = H1[comb_indexes] * r1
Y2 = H2[comb_indexes] * r2
Y = Y1 + Y2
# xxxxxxxxxx USER 1 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Calculate expected estimated channel for user 1
y1 = np.fft.ifft(r1.size * np.conj(r1) * Y, size)
tilde_h1 = y1[0:16]
tilde_H1 = np.fft.fft(tilde_h1, Nsc)
# Test the CazacBasedChannelEstimator estimation
np.testing.assert_array_almost_equal(
ue1_channel_estimator.estimate_channel_freq_domain(Y, 15),
tilde_H1)
# Check that the estimated channel and the True channel have similar
# norms
self.assertAlmostEqual(np.linalg.norm(
ue1_channel_estimator.estimate_channel_freq_domain(Y, 15)),
np.linalg.norm(H1),
delta=0.5)
# 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[50:-50] - tilde_H1[50:-50])
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.size),
decimal=2)
# xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# xxxxxxxxxx USER 2 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Calculate expected estimated channel for user 2
y2 = np.fft.ifft(r2.size * np.conj(r2) * Y, size)
tilde_h2 = y2[0:16]
tilde_H2 = np.fft.fft(tilde_h2, Nsc)
# Test the CazacBasedChannelEstimator estimation
np.testing.assert_array_almost_equal(
ue2_channel_estimator.estimate_channel_freq_domain(Y, 15),
tilde_H2)
# Check that the estimated channel and the True channel have similar
# norms
self.assertAlmostEqual(np.linalg.norm(
ue2_channel_estimator.estimate_channel_freq_domain(Y, 15)),
np.linalg.norm(H2),
delta=0.5)
# 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(H2[50:-50] - tilde_H2[50:-50])
":type: np.ndarray"
np.testing.assert_almost_equal(error / 2.,
np.zeros(error.size),
decimal=2)