def test_001_t(self):
np.set_printoptions(precision=2)
n_frames = 3
alpha = .5
active = 8
M = 8
K = 16
L = 2
cp_len = 8
cs_len = 4
ramp_len = 4
block_len = M * K
window_len = get_window_len(cp_len, M, K, cs_len)
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
taps /= np.sqrt(calculate_signal_energy(taps) / M)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
pn_symbols = get_random_qpsk(K)
H_preamble = get_frequency_domain_filter('rrc', alpha, 2, K, L)
preamble = get_sync_symbol(pn_symbols, H_preamble, K, L, cp_len,
ramp_len)[0]
smap = get_subcarrier_map(K, active, dc_free=True)
ref = np.array([], dtype=complex)
data = np.array([], dtype=complex)
frame_len = window_len + len(preamble)
frame_gap = np.zeros(frame_len)
for i in range(n_frames):
d = get_random_qpsk(active * M)
dd = map_to_waveform_resources(d, active, K, smap)
D = get_data_matrix(dd, K, group_by_subcarrier=False)
b = gfdm_modulate_block(D, taps, M, K, L, False)
b = add_cyclic_starfix(b, cp_len, cs_len)
b = pinch_block(b, window_taps)
ref = np.concatenate((ref, frame_gap, preamble, b))
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
mapper = gfdm.resource_mapper_cc(active, K, M, smap, True)
mod = gfdm.simple_modulator_cc(M, K, L, taps)
prefixer = gfdm.cyclic_prefixer_cc(block_len, cp_len, cs_len, ramp_len,
window_taps)
preambler = blocks.vector_insert_c(preamble,
window_len + len(preamble), 0)
gapper = blocks.vector_insert_c(frame_gap, frame_len + len(frame_gap),
0)
dst = blocks.vector_sink_c()
self.tb.connect(src, mapper, mod, prefixer, preambler, gapper, dst)
# self.tb.connect(src, mapper, dst)
self.tb.run()
res = np.array(dst.data())[0:len(ref)]
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_001_t(self):
np.set_printoptions(precision=2)
n_frames = 7
alpha = .5
active_subcarriers = 52
timeslots = 9
subcarriers = 64
overlap = 2
cp_len = 8
cs_len = 4
ramp_len = 4
window_len = get_window_len(cp_len, timeslots, subcarriers, cs_len)
taps = get_frequency_domain_filter('rrc', alpha, timeslots,
subcarriers, overlap)
# taps /= np.sqrt(calculate_signal_energy(taps) / time)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
pn_symbols = get_random_qpsk(subcarriers)
H_preamble = get_frequency_domain_filter('rrc', alpha, 2,
subcarriers, overlap)
preamble = get_sync_symbol(pn_symbols, H_preamble, subcarriers,
overlap, cp_len, ramp_len)[0]
smap = get_subcarrier_map(subcarriers, active_subcarriers, True)
ref = np.array([], dtype=np.complex)
data = np.array([], dtype=np.complex)
for i in range(n_frames):
d = get_random_qpsk(active_subcarriers * timeslots)
dd = map_to_waveform_resources(d, active_subcarriers,
subcarriers, smap)
D = get_data_matrix(dd, subcarriers, group_by_subcarrier=False)
b = gfdm_modulate_block(D, taps, timeslots, subcarriers,
overlap, False)
b = add_cyclic_starfix(b, cp_len, cs_len)
b = pinch_block(b, window_taps)
ref = np.concatenate((ref, preamble, b))
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
dut = gfdm.transmitter_cc(timeslots, subcarriers, active_subcarriers,
cp_len, cs_len, ramp_len, smap, True,
overlap, taps, window_taps, preamble, "packet_len")
dst = blocks.vector_sink_c()
self.tb.connect(src, dut, dst)
self.tb.run()
res = np.array(dst.data())[0:len(ref)]
self.assertComplexTuplesAlmostEqual(ref, res, 5)
tags = dst.tags()
for t in tags:
print(t.offset, t.value)
def test_001_t(self):
np.set_printoptions(precision=2)
n_frames = 3
alpha = .5
active = 8
M = 8
K = 16
L = 2
cp_len = 8
cs_len = 4
ramp_len = 4
block_len = M * K
window_len = get_window_len(cp_len, M, K, cs_len)
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
taps /= np.sqrt(calculate_signal_energy(taps) / M)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
pn_symbols = get_random_qpsk(K)
H_preamble = get_frequency_domain_filter('rrc', alpha, 2, K, L)
preamble = get_sync_symbol(pn_symbols, H_preamble, K, L, cp_len, ramp_len)[0]
smap = get_subcarrier_map(K, active, dc_free=True)
ref = np.array([], dtype=np.complex)
data = np.array([], dtype=np.complex)
frame_len = window_len + len(preamble)
frame_gap = np.zeros(frame_len)
for i in range(n_frames):
d = get_random_qpsk(active * M)
dd = map_to_waveform_resources(d, active, K, smap)
D = get_data_matrix(dd, K, group_by_subcarrier=False)
b = gfdm_modulate_block(D, taps, M, K, L, False)
b = add_cyclic_starfix(b, cp_len, cs_len)
b = pinch_block(b, window_taps)
ref = np.concatenate((ref, frame_gap, preamble, b))
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
mapper = gfdm.resource_mapper_cc(active, K, M, smap, True)
mod = gfdm.simple_modulator_cc(M, K, L, taps)
prefixer = gfdm.cyclic_prefixer_cc(block_len, cp_len, cs_len, ramp_len, window_taps)
preambler = blocks.vector_insert_c(preamble, window_len + len(preamble), 0)
gapper = blocks.vector_insert_c(frame_gap, frame_len + len(frame_gap), 0)
dst = blocks.vector_sink_c()
self.tb.connect(src, mapper, mod, prefixer, preambler, gapper, dst)
# self.tb.connect(src, mapper, dst)
self.tb.run()
res = np.array(dst.data())[0:len(ref)]
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_003_active_subcarriers(self):
n_frames = 1
timeslots = 9
subcarriers = 32
active_subcarriers = 20
overlap = 2
f_taps = filters.get_frequency_domain_filter('rrc', .5, timeslots,
subcarriers, overlap)
gfdm_constellation = digital.constellation_qpsk().base()
subcarrier_map = get_subcarrier_map(subcarriers, active_subcarriers)
data = get_random_qpsk(n_frames * timeslots * active_subcarriers)
src = blocks.vector_source_c(data)
mapper = gfdm.resource_mapper_cc(timeslots, subcarriers,
active_subcarriers, subcarrier_map,
True)
mod = gfdm.simple_modulator_cc(timeslots, subcarriers, overlap, f_taps)
demod = gfdm.advanced_receiver_sb_cc(timeslots, subcarriers, overlap,
64, f_taps, gfdm_constellation,
subcarrier_map, 0)
demapper = gfdm.resource_demapper_cc(timeslots, subcarriers,
active_subcarriers,
subcarrier_map, True)
snk = blocks.vector_sink_c()
self.tb.connect(src, mapper, mod, demod, demapper, snk)
self.tb.run()
res = np.array(snk.data())
self.assertComplexTuplesAlmostEqual(data, res, 2)
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_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 = np.repeat(np.arange(1, K + 1), M)
data = get_random_qpsk(M * K)
D = get_data_matrix(data, K, group_by_subcarrier=False)
src = blocks.vector_source_c(data)
mod = gfdm.simple_modulator_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())
# res /= M * K
# F = gfdm_transform_subcarriers_to_fd(D, M)
# F = gfdm_upsample_subcarriers_in_fd(F, K, L)
# F = gfdm_filter_subcarriers_in_fd(F, taps, M, K, L)
ref = gfdm_modulate_block(D, taps, M, K, L, False)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_002_big_data(self):
print "big data test"
reps = 5
alpha = .5
M = 127
K = 16
L = 4
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 range(reps):
d = get_random_qpsk(M * K)
D = get_data_matrix(d, K, group_by_subcarrier=False)
ref = np.append(ref, gfdm_modulate_block(D, taps, M, K, L, False))
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_modulator_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())
# res /= M * K
# print "MAXIMUM result value: ", np.max(abs(res))
self.assertComplexTuplesAlmostEqual(ref, res, 2)
def test_001_t(self):
alpha = .5
M = 8
K = 4
L = 2
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
# data = np.repeat(np.arange(1, K + 1), M)
data = get_random_qpsk(M * K)
D = get_data_matrix(data, K, group_by_subcarrier=False)
# print data
# print D
src = blocks.vector_source_c(data)
mod = gfdm.simple_modulator_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())
# res /= M * K
# F = gfdm_transform_subcarriers_to_fd(D, M)
# F = gfdm_upsample_subcarriers_in_fd(F, K, L)
# F = gfdm_filter_subcarriers_in_fd(F, taps, M, K, L)
ref = gfdm_modulate_block(D, taps, M, K, L, False)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
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_002_big_data(self):
print("big data test")
reps = 5
alpha = .5
M = 127
K = 16
L = 4
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
taps /= np.sqrt(calculate_signal_energy(taps) / M)
data = np.array([], dtype=complex)
ref = np.array([], dtype=complex)
for i in range(reps):
d = get_random_qpsk(M * K)
D = get_data_matrix(d, K, group_by_subcarrier=False)
ref = np.append(ref, gfdm_modulate_block(D, taps, M, K, L, False))
data = np.append(data, d)
src = blocks.vector_source_c(data)
mod = gfdm.simple_modulator_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())
# res /= M * K
self.assertComplexTuplesAlmostEqual(ref, res, 2)
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_002_t(self):
n_frames = 1
self.gfdm_var = gfdm_var = struct({'subcarriers': 64, 'timeslots': 9, 'alpha': 0.5, 'overlap': 2,})
self.gfdm_constellation = gfdm_constellation = digital.constellation_qpsk().base()
self.f_taps = f_taps = filters.get_frequency_domain_filter('rrc', 1.0, gfdm_var.timeslots, gfdm_var.subcarriers,
gfdm_var.overlap)
self.random_bits = blocks.vector_source_b(map(int, np.random.randint(0, len(gfdm_constellation.points()),
n_frames * gfdm_var.timeslots * gfdm_var.subcarriers)),
False)
self.bits_to_symbols = digital.chunks_to_symbols_bc((gfdm_constellation.points()), 1)
self.mod = gfdm.simple_modulator_cc(gfdm_var.timeslots, gfdm_var.subcarriers, gfdm_var.overlap, f_taps)
self.demod = gfdm.advanced_receiver_sb_cc(gfdm_var.timeslots, gfdm_var.subcarriers, gfdm_var.overlap, 64,
f_taps, gfdm_constellation, np.arange(gfdm_var.subcarriers))
self.tx_symbols = blocks.vector_sink_c()
self.rx_symbols = blocks.vector_sink_c()
self.tb.connect((self.random_bits, 0), (self.bits_to_symbols, 0))
self.tb.connect((self.bits_to_symbols, 0), (self.tx_symbols, 0))
self.tb.connect((self.bits_to_symbols, 0), (self.mod, 0))
self.tb.connect((self.mod, 0), (self.demod, 0))
self.tb.connect((self.demod, 0), (self.rx_symbols, 0))
self.tb.run()
ref = np.array(self.tx_symbols.data())
res = np.array(self.rx_symbols.data())
# more or less make sure all symbols have their correct sign.
self.assertComplexTuplesAlmostEqual(ref, res, 2)
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_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_t(self):
nsubcarrier = 4
ntimeslots = 16
filter_alpha = 0.35
tag_key = "frame_len"
fft_length = nsubcarrier * ntimeslots
taps = get_frequency_domain_filter('rrc', filter_alpha, ntimeslots,
nsubcarrier, 2)
data = get_random_qpsk(nsubcarrier * ntimeslots)
D = get_data_matrix(data, nsubcarrier, group_by_subcarrier=False)
print D
md = gfdms.modulator_cc(nsubcarrier, ntimeslots, filter_alpha,
fft_length, 1, tag_key)
tagger = blocks.stream_to_tagged_stream(gr.sizeof_gr_complex, 1,
fft_length, tag_key)
src = blocks.vector_source_c(data)
dst = blocks.vector_sink_c()
self.tb.connect(src, tagger, md, dst)
self.tb.run()
res = np.array(dst.data())
print res
ref = gfdm_modulate_block(D, taps, ntimeslots, nsubcarrier, 2, True)
print ref
self.assertComplexTuplesAlmostEqual(ref, res, 2)
def test_001_t(self):
nsubcarrier = 4
ntimeslots = 16
filter_alpha = 0.35
tag_key = "frame_len"
fft_length = nsubcarrier * ntimeslots
taps = get_frequency_domain_filter('rrc', filter_alpha, ntimeslots, nsubcarrier, 2)
data = get_random_qpsk(nsubcarrier * ntimeslots)
# data = np.zeros(nsubcarrier)
# data[0] = 1
# data = np.repeat(data, ntimeslots)
D = get_data_matrix(data, nsubcarrier, group_by_subcarrier=False)
print D
md = gfdms.modulator_cc(nsubcarrier, ntimeslots, filter_alpha, fft_length, 1, tag_key)
tagger = blocks.stream_to_tagged_stream(gr.sizeof_gr_complex, 1, fft_length, tag_key)
src = blocks.vector_source_c(data)
dst = blocks.vector_sink_c()
self.tb.connect(src, tagger, md, dst)
self.tb.run()
res = np.array(dst.data())
print res
ref = gfdm_modulate_block(D, taps, ntimeslots, nsubcarrier, 2, True)
print ref
self.assertComplexTuplesAlmostEqual(ref, res, 2)
def test_001_t(self):
np.set_printoptions(precision=2)
n_frames = 7
active_subcarriers = 52
timeslots = 9
subcarriers = 64
cp_len = subcarriers // 4
cs_len = cp_len // 2
taps = get_frequency_domain_filter(self.filter_type, self.alpha,
timeslots, subcarriers,
self.overlap)
window_taps = get_raised_cosine_ramp(
cs_len, get_window_len(cp_len, timeslots, subcarriers, cs_len))
smap = get_subcarrier_map(subcarriers, active_subcarriers, True)
preambles = get_full_preambles(self.filter_type, self.alpha,
active_subcarriers, subcarriers, smap,
self.overlap, cp_len, cs_len, [
0,
])
frame_size = preambles[
0].size + cp_len + timeslots * subcarriers + cs_len
ref = np.array([], dtype=np.complex)
data = np.array([], dtype=np.complex)
for i in range(n_frames):
d = get_random_qpsk(active_subcarriers * timeslots)
frame = generate_reference_frame(d, timeslots, subcarriers,
active_subcarriers, smap, taps,
self.overlap, cp_len, cs_len,
window_taps, [
0,
], preambles)
ref = np.concatenate((ref, frame[0]))
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
dut = gfdm.transmitter_cc(timeslots, subcarriers, active_subcarriers,
cp_len, cs_len, cs_len, smap, True,
self.overlap, taps, window_taps, [
0,
], preambles, "packet_len")
dst = blocks.vector_sink_c()
self.tb.connect(src, dut, dst)
self.tb.run()
res = np.array(dst.data())[0:len(ref)]
self.assertComplexTuplesAlmostEqual(ref, res, 5)
tags = dst.tags()
for i, t in enumerate(tags):
print(f't={i}, offset={t.offset}, value={pmt.to_python(t.value)}')
self.assertEqual(t.offset, i * frame_size)
self.assertEqual(pmt.to_python(t.value), frame_size)
def test_002_cyclic_delay_diversity(self):
np.set_printoptions(precision=2)
n_frames = 7
active_subcarriers = 52
timeslots = 9
subcarriers = 64
cp_len = subcarriers // 4
cs_len = cp_len // 2
cyclic_shifts = [0, 3, 7, 8]
taps = get_frequency_domain_filter(self.filter_type, self.alpha, timeslots,
subcarriers, self.overlap)
window_taps = get_raised_cosine_ramp(
cs_len, get_window_len(cp_len, timeslots, subcarriers, cs_len))
smap = get_subcarrier_map(subcarriers, active_subcarriers, True)
preambles = get_full_preambles(self.filter_type, self.alpha, active_subcarriers,
subcarriers, smap, self.overlap, cp_len, cs_len, cyclic_shifts)
frame_size = preambles[0].size + cp_len + timeslots * subcarriers + cs_len
ref = [np.array([], dtype=complex) for _ in cyclic_shifts]
data = np.array([], dtype=complex)
for i in range(n_frames):
d = get_random_qpsk(active_subcarriers * timeslots)
frame = generate_reference_frame(d, timeslots, subcarriers, active_subcarriers, smap,
taps, self.overlap, cp_len, cs_len, window_taps,
cyclic_shifts, preambles)
ref = [np.concatenate((r, f)) for r, f in zip(ref, frame)]
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
dut = gfdm.transmitter_cc(timeslots, subcarriers, active_subcarriers,
cp_len, cs_len, cs_len, smap, True,
self.overlap, taps, window_taps, cyclic_shifts, preambles, "packet_len")
snks = [blocks.vector_sink_c() for _ in cyclic_shifts]
self.tb.connect(src, dut)
for i, s in enumerate(snks):
self.tb.connect((dut, i), s)
self.tb.run()
for snk, refport in zip(snks, ref):
res = np.array(snk.data())[0:refport.size]
self.assertComplexTuplesAlmostEqual(refport, res, 5)
for j, snk in enumerate(snks):
tags = snk.tags()
for i, t in enumerate(tags):
print(f'p={j}, t={i}, offset={t.offset}, value={pmt.to_python(t.value)}')
self.assertEqual(t.offset, i * frame_size)
self.assertEqual(pmt.to_python(t.value), frame_size)
def test_004_setIC(self):
ic = 2
timeslots = 9
subcarriers = 32
active_subcarriers = 20
overlap = 2
f_taps = filters.get_frequency_domain_filter('rrc', .5, timeslots, subcarriers, overlap)
gfdm_constellation = digital.constellation_qpsk().base()
subcarrier_map = get_subcarrier_map(subcarriers, active_subcarriers)
demod = gfdm.advanced_receiver_sb_cc(timeslots, subcarriers, overlap, 64, f_taps, gfdm_constellation, subcarrier_map)
demod.set_ic(ic)
self.assertEqual(ic, demod.get_ic())
def modulator_test():
fft_len = 128
timeslots = 205
overlap = 2
taps = get_frequency_domain_filter('rrc', .5, timeslots, fft_len, overlap)
kernel = cgfdm.py_modulator_kernel_cc(timeslots, fft_len, overlap, taps)
N = 10
for i in range(N):
data = np.random.randn(2, fft_len * timeslots)
data = data[0] + 1j * data[1]
data = data.astype(dtype=np.complex64)
kernel.modulate(data)
def modulator_test():
fft_len = 128
timeslots = 205
overlap = 2
taps = get_frequency_domain_filter('rrc', .5, timeslots, fft_len, overlap)
kernel = cgfdm.py_modulator_kernel_cc(timeslots, fft_len, overlap, taps)
N = 10
for i in range(N):
data = np.random.randn(2, fft_len * timeslots)
data = data[0] + 1j * data[1]
data = data.astype(dtype=np.complex64)
kernel.modulate(data)
def test_001_t(self):
np.set_printoptions(precision=2)
n_frames = 3
alpha = .5
M = 8
K = 4
L = 2
cp_len = 8
ramp_len = 4
block_len = M * K
window_len = get_window_len(cp_len, M, K)
taps = get_frequency_domain_filter('rrc', alpha, M, K, L)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
pn_symbols = get_random_qpsk(K)
H_preamble = get_frequency_domain_filter('rrc', alpha, 2, K, L)
preamble = get_sync_symbol(pn_symbols, H_preamble, K, L, cp_len, ramp_len)
ref = np.array([], dtype=np.complex)
data = np.array([], dtype=np.complex)
for i in range(n_frames):
d = get_random_qpsk(block_len)
D = get_data_matrix(d, K, group_by_subcarrier=False)
b = gfdm_modulate_block(D, taps, M, K, L, False)
b = add_cyclic_prefix(b, cp_len)
b = pinch_block(b, window_taps)
ref = np.concatenate((ref, preamble, b))
data = np.concatenate((data, d))
src = blocks.vector_source_c(data)
mod = gfdm.simple_modulator_cc(M, K, L, taps)
prefixer = gfdm.cyclic_prefixer_cc(cp_len, ramp_len, block_len, window_taps)
preambler = blocks.vector_insert_c(preamble, window_len + len(preamble), 0)
dst = blocks.vector_sink_c()
self.tb.connect(src, mod, prefixer, preambler, dst)
self.tb.run()
res = np.array(dst.data())[0:len(ref)]
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def modulate_gfdm_frame(tx_symbols, params):
mapper = cgfdm.py_resource_mapper_kernel_cc(params['timeslots'], params['fft_len'], params['active_subcarriers'],
params['subcarrier_map'])
taps = get_frequency_domain_filter(params['prototype_type'], params['prototype_alpha'], params['timeslots'],
params['fft_len'], params['overlap'])
kernel = cgfdm.py_modulator_kernel_cc(params['timeslots'], params['fft_len'], params['overlap'], taps)
win_filt = get_raised_cosine_ramp(params['filter_len'], params['timeslots'] * params['fft_len'] + params['cp_len'])
cpler = cgfdm.py_add_cyclic_prefix_cc(params['timeslots'] * params['fft_len'], params['cp_len'], params['filter_len'],
win_filt)
syms = mapper.map_to_resources(tx_symbols)
frame = kernel.modulate(syms.flatten())
frame = cpler.add_cyclic_prefix(frame)
return frame
def modulate_gfdm_frame(tx_symbols, params):
mapper = cgfdm.py_resource_mapper_kernel_cc(params['timeslots'], params['fft_len'], params['active_subcarriers'],
params['subcarrier_map'])
taps = get_frequency_domain_filter(params['prototype_type'], params['prototype_alpha'], params['timeslots'],
params['fft_len'], params['overlap'])
kernel = cgfdm.py_modulator_kernel_cc(params['timeslots'], params['fft_len'], params['overlap'], taps)
win_filt = get_raised_cosine_ramp(params['filter_len'], params['timeslots'] * params['fft_len'] + params['cp_len'])
cpler = cgfdm.py_add_cyclic_prefix_cc(params['timeslots'] * params['fft_len'], params['cp_len'], params['filter_len'],
win_filt)
syms = mapper.map_to_resources(tx_symbols)
frame = kernel.modulate(syms.flatten())
frame = cpler.add_cyclic_prefix(frame)
return frame
def test_004_setIC(self):
ic = 2
timeslots = 9
subcarriers = 32
active_subcarriers = 20
overlap = 2
f_taps = filters.get_frequency_domain_filter('rrc', .5, timeslots,
subcarriers, overlap)
gfdm_constellation = digital.constellation_qpsk().base()
subcarrier_map = get_subcarrier_map(subcarriers, active_subcarriers)
demod = gfdm.advanced_receiver_sb_cc(timeslots, subcarriers, overlap,
64, f_taps, gfdm_constellation,
subcarrier_map, 0)
demod.set_ic(ic)
self.assertEqual(ic, demod.get_ic())
def test_001_init(self):
timeslots = 25
subcarriers = 96
overlap = 2
filter_alpha = 0.35
taps = get_frequency_domain_filter("rrc", filter_alpha, timeslots,
subcarriers, overlap)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
self.assertEqual(timeslots, demod.timeslots())
self.assertEqual(subcarriers, demod.subcarriers())
self.assertEqual(overlap, demod.overlap())
self.assertEqual(timeslots * subcarriers, demod.block_size())
self.assertComplexTuplesAlmostEqual(taps, demod.filter_taps())
def test_002_fd_filter(self):
self.params.K = 64
self.params.Kon = 52
self.params.Non = self.params.Kon * self.params.Mon
self.params.N = self.params.K * self.params.M
self.params.pulse = 'rrc'
taps = vc.gfdmutil.get_transmitter_pulse(self.params)
g2 = taps[::self.params.K // self.params.L]
G2 = np.fft.fft(g2)
freq_taps = get_frequency_domain_filter('rrc', self.params.a,
self.params.M, self.params.K,
self.params.L)
freq_taps *= np.abs(G2[0]) / np.abs(freq_taps[0])
self.assertTrue(np.all(np.abs(freq_taps - G2) < 1e-3))
def test_002_fd_filter(self):
self.params.K = 64
self.params.Kon = 52
self.params.Non = self.params.Kon * self.params.Mon
self.params.N = self.params.K * self.params.M
self.params.pulse = 'rrc'
taps = vc.gfdmutil.get_transmitter_pulse(self.params)
g2 = taps[::self.params.K // self.params.L]
G2 = np.fft.fft(g2)
freq_taps = get_frequency_domain_filter('rrc',
self.params.a, self.params.M,
self.params.K, self.params.L)
freq_taps *= np.abs(G2[0]) / np.abs(freq_taps[0])
self.assertTrue(np.all(np.abs(freq_taps - G2) < 1e-3))
def test_002_t(self):
n_frames = 1
gfdm_var = struct({
"subcarriers": 64,
"timeslots": 9,
"alpha": 0.5,
"overlap": 2,
})
gfdm_constellation = digital.constellation_qpsk().base()
self.f_taps = f_taps = filters.get_frequency_domain_filter(
"rrc", 1.0, gfdm_var.timeslots, gfdm_var.subcarriers,
gfdm_var.overlap)
source_bits = np.random.randint(
0,
len(gfdm_constellation.points()),
n_frames * gfdm_var.timeslots * gfdm_var.subcarriers,
).astype(np.uint8)
self.random_bits = blocks.vector_source_b(source_bits, False)
self.bits_to_symbols = digital.chunks_to_symbols_bc(
(gfdm_constellation.points()), 1)
self.mod = gfdm.simple_modulator_cc(gfdm_var.timeslots,
gfdm_var.subcarriers,
gfdm_var.overlap, f_taps)
self.demod = gfdm.advanced_receiver_sb_cc(
gfdm_var.timeslots,
gfdm_var.subcarriers,
gfdm_var.overlap,
64,
f_taps,
gfdm_constellation,
np.arange(gfdm_var.subcarriers),
0,
)
self.tx_symbols = blocks.vector_sink_c()
self.rx_symbols = blocks.vector_sink_c()
self.tb.connect((self.random_bits, 0), (self.bits_to_symbols, 0))
self.tb.connect((self.bits_to_symbols, 0), (self.tx_symbols, 0))
self.tb.connect((self.bits_to_symbols, 0), (self.mod, 0))
self.tb.connect((self.mod, 0), (self.demod, 0))
self.tb.connect((self.demod, 0), (self.rx_symbols, 0))
self.tb.run()
ref = np.array(self.tx_symbols.data())
res = np.array(self.rx_symbols.data())
# more or less make sure all symbols have their correct sign.
self.assertComplexTuplesAlmostEqual(ref, res, 2)
def test_002_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)
ref = gfdm_modulate_block(D, taps, timeslots, subcarriers, overlap,
False)
mod = Modulator(timeslots, subcarriers, overlap, taps)
res = mod.modulate(data)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_004_active_subcarriers(self):
n_frames = 1
timeslots = 9
subcarriers = 32
active_subcarriers = 20
overlap = 2
ic_iterations = 64
f_taps = filters.get_frequency_domain_filter("rrc", 0.5, timeslots,
subcarriers, overlap)
gfdm_constellation = digital.constellation_qpsk().base()
print(gfdm_constellation.points())
subcarrier_map = get_subcarrier_map(subcarriers, active_subcarriers)
data = get_random_qpsk(n_frames * timeslots * active_subcarriers)
data *= 2.0
src = blocks.vector_source_c(data)
mapper = gfdm.resource_mapper_cc(timeslots, subcarriers,
active_subcarriers, subcarrier_map,
True)
mod = gfdm.simple_modulator_cc(timeslots, subcarriers, overlap, f_taps)
demod = gfdm.advanced_receiver_sb_cc(
timeslots,
subcarriers,
overlap,
ic_iterations,
f_taps,
gfdm_constellation,
subcarrier_map,
0,
)
demod.set_ic(64)
demapper = gfdm.resource_demapper_cc(timeslots, subcarriers,
active_subcarriers,
subcarrier_map, True)
snk = blocks.vector_sink_c()
self.tb.connect(src, mapper, mod, demod, demapper, snk)
self.tb.run()
res = np.array(snk.data())
print(data[0:10])
print(res[0:10])
self.assertComplexTuplesAlmostEqual(data, res, 1)
def test_002_small(self):
timeslots = 16
subcarriers = 4
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, 6)
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_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(1.0j)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
res = demod.demodulate_equalize(frame * np.exp(1.0j), eq_vals)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
def test_003_active_subcarriers(self):
n_frames = 1
timeslots = 9
subcarriers = 32
active_subcarriers = 20
overlap = 2
f_taps = filters.get_frequency_domain_filter('rrc', .5, timeslots, subcarriers, overlap)
gfdm_constellation = digital.constellation_qpsk().base()
subcarrier_map = get_subcarrier_map(subcarriers, active_subcarriers)
data = get_random_qpsk(n_frames * timeslots * active_subcarriers)
src = blocks.vector_source_c(data)
mapper = gfdm.resource_mapper_cc(timeslots, subcarriers, active_subcarriers, subcarrier_map, True)
mod = gfdm.simple_modulator_cc(timeslots, subcarriers, overlap, f_taps)
demod = gfdm.advanced_receiver_sb_cc(timeslots, subcarriers, overlap, 64, f_taps, gfdm_constellation, subcarrier_map)
demapper = gfdm.resource_demapper_cc(timeslots, subcarriers, active_subcarriers, subcarrier_map, True)
snk = blocks.vector_sink_c()
self.tb.connect(src, mapper, mod, demod, demapper, snk)
self.tb.run()
res = np.array(snk.data())
self.assertComplexTuplesAlmostEqual(data, res, 2)
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.j)
demod = Demodulator(timeslots, subcarriers, overlap, taps)
fd_res = demod.fft_equalize_filter_downsample(
frame * np.exp(1.j), eq_vals)
res = demod.transform_subcarriers_to_td(fd_res)
self.assertComplexTuplesAlmostEqual(ref, res, 5)
