def test_002_big_data(self):
print("big data test")
reps = 5
alpha = .5
M = 127
K = 16
L = 2
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
data = np.array([], dtype=complex)
ref = np.array([], dtype=complex)
for i in range(reps):
d = get_random_qpsk(M * K)
ref = np.append(ref, gfdm_demodulate_block(d, taps, K, M, L))
data = np.append(data, d)
src = blocks.vector_source_c(data)
mod = gfdm.simple_receiver_cc(M, K, L, taps)
dst = blocks.vector_sink_c()
self.tb.connect(src, mod, dst)
# set up fg
self.tb.run()
# check data
res = np.array(dst.data())
self.assertComplexTuplesAlmostEqual(ref, res, 4)
def test_001_simple_receiver(self):
# make sure advanced receiver works like simple receiver in case no IC iterations are applied!
reps = 5
alpha = .5
M = 127
K = 16
L = 2
taps = filters.get_frequency_domain_filter('rrc', alpha, M, K, L)
data = np.array([], dtype=np.complex)
ref = np.array([], dtype=np.complex)
for i in xrange(reps):
d = utils.get_random_qpsk(M * K)
ref = np.append(ref, gfdm_demodulate_block(d, taps, K, M, L))
data = np.append(data, d)
# print data
# print ref
# print "MAXIMUM ref value: ", np.max(abs(ref))
src = blocks.vector_source_c(data)
est_data = np.ones(len(data), dtype=np.complex)
est_src = blocks.vector_source_c(est_data)
gfdm_constellation = digital.constellation_qpsk().base()
mod = gfdm.advanced_receiver_sb_cc(M, K, L, 0,
taps, gfdm_constellation, np.arange(K))
dst = blocks.vector_sink_c()
self.tb.connect(src, (mod, 0), dst)
self.tb.connect(est_src, (mod, 1))
# set up fg
self.tb.run()
# check data
res = np.array(dst.data())
self.assertComplexTuplesAlmostEqual(ref, res, 4)
def test_001_simple_receiver(self):
# make sure advanced receiver works like simple receiver in case no IC iterations are applied!
reps = 5
alpha = .5
M = 127
K = 16
L = 2
taps = filters.get_frequency_domain_filter('rrc', alpha, M, K, L)
data = np.array([], dtype=np.complex)
ref = np.array([], dtype=np.complex)
for i in xrange(reps):
d = utils.get_random_qpsk(M * K)
ref = np.append(ref, gfdm_demodulate_block(d, taps, K, M, L))
data = np.append(data, d)
# print data
# print ref
# print "MAXIMUM ref value: ", np.max(abs(ref))
src = blocks.vector_source_c(data)
est_data = np.ones(len(data), dtype=np.complex)
est_src = blocks.vector_source_c(est_data)
gfdm_constellation = digital.constellation_qpsk().base()
mod = gfdm.advanced_receiver_sb_cc(M, K, L, 0, taps,
gfdm_constellation, np.arange(K), 0)
dst = blocks.vector_sink_c()
self.tb.connect(src, (mod, 0), dst)
self.tb.connect(est_src, (mod, 1))
# set up fg
self.tb.run()
# check data
res = np.array(dst.data())
self.assertComplexTuplesAlmostEqual(ref, res, 4)
def test_005_steps(self):
timeslots = 5
subcarriers = 32
overlap = 2
filter_alpha = 0.35
taps = get_frequency_domain_filter('rrc', filter_alpha,
timeslots, subcarriers,
overlap)
data = get_random_qpsk(timeslots * subcarriers)
D = get_data_matrix(data, subcarriers, group_by_subcarrier=False)
frame = gfdm_modulate_block(D, taps, timeslots, subcarriers,
overlap, False)
ref = gfdm_demodulate_block(
frame, taps, subcarriers, timeslots, overlap)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
fd_res = demod.fft_filter_downsample(frame)
res = demod.transform_subcarriers_to_td(fd_res)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
for _ in range(2):
ic_res = demod.cancel_sc_interference(data, fd_res)
res = demod.transform_subcarriers_to_td(ic_res)
self.assertComplexTuplesAlmostEqual(data, res, 1)
def test_002_big_data(self):
print("big data test")
reps = 5
alpha = .5
M = 127
K = 16
L = 2
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
data = np.array([], dtype=np.complex)
ref = np.array([], dtype=np.complex)
for i in xrange(reps):
d = get_random_qpsk(M * K)
ref = np.append(ref, gfdm_demodulate_block(d, taps, K, M, L))
data = np.append(data, d)
# print data
# print ref
# print "MAXIMUM ref value: ", np.max(abs(ref))
src = blocks.vector_source_c(data)
mod = gfdm.simple_receiver_cc(M, K, L, taps)
dst = blocks.vector_sink_c()
self.tb.connect(src, mod, dst)
# set up fg
self.tb.run()
# check data
res = np.array(dst.data())
self.assertComplexTuplesAlmostEqual(ref, res, 4)
def test_001_t(self):
alpha = .5
M = 8
K = 4
L = 2
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
taps /= np.sqrt(calculate_signal_energy(taps) / M)
data = get_random_qpsk(M * K)
src = blocks.vector_source_c(data)
mod = gfdm.simple_receiver_cc(M, K, L, taps)
dst = blocks.vector_sink_c()
self.tb.connect(src, mod, dst)
self.tb.run()
res = np.array(dst.data())
ref = gfdm_demodulate_block(data, taps, K, M, L)
res *= np.sqrt(
calculate_signal_energy(ref) / calculate_signal_energy(res))
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_001_t(self):
alpha = .5
M = 8
K = 4
L = 2
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
taps /= np.sqrt(calculate_signal_energy(taps) / M)
data = get_random_qpsk(M * K)
src = blocks.vector_source_c(data)
mod = gfdm.simple_receiver_cc(M, K, L, taps)
dst = blocks.vector_sink_c()
self.tb.connect(src, mod, dst)
self.tb.run()
res = np.array(dst.data())
ref = gfdm_demodulate_block(data, taps, K, M, L)
# print calculate_signal_energy(ref), calculate_signal_energy(res)
res *= np.sqrt(calculate_signal_energy(ref) / calculate_signal_energy(res))
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_003_big(self):
timeslots = 21
subcarriers = 128
overlap = 2
filter_alpha = 0.35
taps = get_frequency_domain_filter("rrc", filter_alpha, timeslots,
subcarriers, overlap)
data = get_random_qpsk(timeslots * subcarriers)
D = get_data_matrix(data, subcarriers, group_by_subcarrier=False)
frame = gfdm_modulate_block(D, taps, timeslots, subcarriers, overlap,
False)
ref = gfdm_demodulate_block(frame, taps, subcarriers, timeslots,
overlap)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
res = demod.demodulate(frame)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_004_big_equalize(self):
timeslots = 21
subcarriers = 128
overlap = 2
filter_alpha = 0.35
taps = get_frequency_domain_filter('rrc', filter_alpha,
timeslots, subcarriers,
overlap)
data = get_random_qpsk(timeslots * subcarriers)
D = get_data_matrix(data, subcarriers, group_by_subcarrier=False)
frame = gfdm_modulate_block(D, taps, timeslots, subcarriers,
overlap, False)
ref = gfdm_demodulate_block(
frame, taps, subcarriers, timeslots, overlap)
eq_vals = np.ones(ref.size, ref.dtype) * np.exp(1.j)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
res = demod.demodulate_equalize(frame * np.exp(1.j), eq_vals)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_006_steps_equalize(self):
timeslots = 5
subcarriers = 32
overlap = 2
filter_alpha = 0.35
taps = get_frequency_domain_filter("rrc", filter_alpha, timeslots,
subcarriers, overlap)
data = get_random_qpsk(timeslots * subcarriers)
D = get_data_matrix(data, subcarriers, group_by_subcarrier=False)
frame = gfdm_modulate_block(D, taps, timeslots, subcarriers, overlap,
False)
ref = gfdm_demodulate_block(frame, taps, subcarriers, timeslots,
overlap)
eq_vals = np.ones(ref.size, ref.dtype) * np.exp(1.0j)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
fd_res = demod.fft_equalize_filter_downsample(frame * np.exp(1.0j),
eq_vals)
res = demod.transform_subcarriers_to_td(fd_res)
self.assertComplexTuplesAlmostEqual(ref, res, 5)