def test_003_block_pinching(self):
n_reps = 1
n_subcarriers = 8
n_timeslots = 8
block_len = n_subcarriers * n_timeslots
cp_len = 8
ramp_len = 4
cs_len = ramp_len * 2
window_len = get_window_len(cp_len, n_timeslots, n_subcarriers, cs_len)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
data = np.arange(block_len, dtype=np.complex) + 1
ref = add_cyclic_starfix(data, cp_len, cs_len)
ref = pinch_block(ref, window_taps)
data = np.tile(data, n_reps)
ref = np.tile(ref, n_reps)
print "input is: ", len(data), " -> " , len(ref)
# short_window = np.concatenate((window_taps[0:ramp_len], window_taps[-ramp_len:]))
prefixer = gfdm.cyclic_prefixer_cc(block_len, cp_len, cs_len, ramp_len, window_taps)
src = blocks.vector_source_c(data)
dst = blocks.vector_sink_c()
self.tb.connect(src, prefixer, dst)
self.tb.run()
res = np.array(dst.data())
print ref[-10:]
print res[-10:]
self.assertComplexTuplesAlmostEqual(res, ref, 4)
def create_frame(config, tag_key):
symbols = get_random_qpsk(config.timeslots * config.active_subcarriers)
d_block = modulate_mapped_gfdm_block(
symbols,
config.timeslots,
config.subcarriers,
config.active_subcarriers,
2,
0.2,
dc_free=True,
)
preamble = config.full_preambles[0]
frame = add_cyclic_starfix(d_block, config.cp_len, config.cs_len)
frame = np.concatenate((preamble, frame))
tag = gr.tag_t()
tag.key = pmt.string_to_symbol(tag_key)
d = pmt.make_dict()
d = pmt.dict_add(d, pmt.mp("xcorr_idx"), pmt.from_uint64(42))
d = pmt.dict_add(d, pmt.mp("xcorr_offset"), pmt.from_uint64(4711))
d = pmt.dict_add(d, pmt.mp("sc_rot"), pmt.from_complex(1.0 + 0.0j))
# tag.offset = data.size + cp_len
tag.srcid = pmt.string_to_symbol("qa")
tag.value = d
return frame, symbols, tag
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=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 generate_reference_frame(symbols, timeslots, subcarriers, active_subcarriers, subcarrier_map,
taps, overlap, cp_len, cs_len, window_taps, cyclic_shifts, preambles):
dd = map_to_waveform_resources(symbols, active_subcarriers,
subcarriers, subcarrier_map)
D = get_data_matrix(dd, subcarriers, group_by_subcarrier=False)
b = gfdm_modulate_block(D, taps, timeslots, subcarriers,
overlap, False)
frame = []
for cs, p in zip(cyclic_shifts, preambles):
data = np.roll(b, cs)
data = add_cyclic_starfix(data, cp_len, cs_len)
data = pinch_block(data, window_taps)
frame.append(np.concatenate((p, data)))
return frame
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_001_prefix(self):
timeslots = 19
subcarriers = 32
block_len = timeslots * subcarriers
cp_len = 16
ramp_len = 4
cs_len = ramp_len * 2
window_len = get_window_len(cp_len, timeslots, subcarriers, cs_len)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
data = np.arange(block_len, dtype=complex) + 1
ref = add_cyclic_starfix(data, cp_len, cs_len)
ref = pinch_block(ref, window_taps)
ref = ref.astype(np.complex64)
prefixer = Cyclic_prefixer(block_len, cp_len, cs_len, ramp_len,
window_taps)
res = prefixer.add_cyclic_prefix(data)
self.assertComplexTuplesAlmostEqual(res, ref, 6)
def test_002_prefix_shifted(self):
timeslots = 3
subcarriers = 32
cyclic_shift = 4
block_len = timeslots * subcarriers
cp_len = 16
cs_len = cp_len // 2
ramp_len = 4
window_len = get_window_len(cp_len, timeslots, subcarriers, cs_len)
window_taps = get_raised_cosine_ramp(ramp_len, window_len)
data = np.arange(block_len, dtype=complex) + 1
ref = add_cyclic_starfix(data, cp_len, cs_len)
ref = np.concatenate((data[-(cp_len + cyclic_shift):], data,
data[0:cs_len - cyclic_shift]))
ref = pinch_block(ref, window_taps)
ref = ref.astype(np.complex64)
prefixer = Cyclic_prefixer(block_len, cp_len, cs_len, ramp_len,
window_taps, cyclic_shift)
res = prefixer.add_cyclic_prefix(data)
self.assertEqual(res.size, cp_len + block_len + cs_len)
self.assertComplexTuplesAlmostEqual(res, ref, 5)
