def test_010_sync_block(self):
np.set_printoptions(precision=4)
print 'GR block sync!'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
frame_len = 2 * K + cp_len + M * K
test_cfo = -.2
snr_dB = 10.0
n_reps = 4
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(signal, np.array(kernel.preamble()), K, cp_len)
print 'Python frame start: ', nc
signal = np.tile(signal, n_reps)
src = blocks.vector_source_c(signal)
sync = gfdm.sync_cc(K, cp_len, frame_len, preamble, 'gfdm_block')
snk = blocks.vector_sink_c()
self.tb.connect(src, sync, snk)
self.tb.run()
ref = signal[nc:nc + frame_len]
ref = np.tile(ref, n_reps)
res = np.array(snk.data())
print 'res length:', len(res) / n_reps
print 'frame size:', frame_len
self.assertComplexTuplesAlmostEqual(ref, res)
def test_009_step_window(self):
print 'long windowed test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 10.0
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(
signal, preamble, K, cp_len)
slen = len(signal)
n_rep = 10
signal = np.tile(signal, n_rep)
nc_vec = (np.arange(0, n_rep) * slen) + nc
step_size = nc + 4
window_nc = np.array([], dtype=int)
dumped = np.array([], dtype=int)
for i in range(0, len(signal), step_size):
w = signal[i:i + step_size + 3 * K]
if len(w) > 4 * K:
# it = i // step_size
# print 'PROCESS WINDOW ', it
snc = int(kernel.find_preamble(w))
if not snc == -2 * len(w):
abs_nc = i + snc
n_frame = len(window_nc)
prev_pos = nc_vec[n_frame - 1]
if abs_nc == prev_pos:
print 'found:', abs_nc, 'previous:', prev_pos
elif not abs_nc == nc_vec[n_frame]:
print 'FAIL STATUS: reps', n_rep, 'detected frames:', n_frame, 'avail_frames:', len(
nc_vec)
print '#frame', n_frame, 'expected:', nc_vec[
n_frame], 'found:', abs_nc, 'diff:', abs_nc - nc_vec[
n_frame]
print 'step_size:', step_size, 'step_start:', i, 'snc:', snc
print nc_vec[n_frame - 3:n_frame + 3]
print window_nc[-3:]
self.assertEqual(abs_nc, nc_vec[n_frame])
else:
# print 'SUCCESSFULLY detected frame @', abs_nc
window_nc = np.append(window_nc, abs_nc)
else:
dumped = np.append(dumped, snc)
self.assertTupleEqual(tuple(nc_vec), tuple(window_nc))
def test_007_frame(self):
print 'find frame test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 20.0
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
# print 'preamble size:', len(preamble), len(preamble) == 2 * K
# print 'init kernel'
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, auto_corr_vals, corr_vals, napcc, apcc = find_frame_start(
signal, preamble, K, cp_len)
# print 'kernel.find_preamble'
knc = np.array(kernel.find_preamble(signal))
print knc, nc
self.assertEqual(nc, knc)
def test_009_step_window(self):
print 'long windowed test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 10.0
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(signal, preamble, K, cp_len)
slen = len(signal)
n_rep = 10
signal = np.tile(signal, n_rep)
nc_vec = (np.arange(0, n_rep) * slen) + nc
step_size = nc + 4
window_nc = np.array([], dtype=int)
dumped = np.array([], dtype=int)
for i in range(0, len(signal), step_size):
w = signal[i:i + step_size + 3 * K]
if len(w) > 4 * K:
# it = i // step_size
# print 'PROCESS WINDOW ', it
snc = int(kernel.find_preamble(w))
if not snc == -2 * len(w):
abs_nc = i + snc
n_frame = len(window_nc)
prev_pos = nc_vec[n_frame - 1]
if abs_nc == prev_pos:
print 'found:', abs_nc, 'previous:', prev_pos
elif not abs_nc == nc_vec[n_frame]:
print 'FAIL STATUS: reps', n_rep, 'detected frames:', n_frame, 'avail_frames:', len(nc_vec)
print '#frame', n_frame, 'expected:', nc_vec[n_frame], 'found:', abs_nc, 'diff:', abs_nc - nc_vec[n_frame]
print 'step_size:', step_size, 'step_start:', i, 'snc:', snc
print nc_vec[n_frame-3:n_frame+3]
print window_nc[-3:]
self.assertEqual(abs_nc, nc_vec[n_frame])
else:
# print 'SUCCESSFULLY detected frame @', abs_nc
window_nc = np.append(window_nc, abs_nc)
else:
dumped = np.append(dumped, snc)
self.assertTupleEqual(tuple(nc_vec), tuple(window_nc))
def preamble_sync_test():
seed = 4711
timeslots = 9
subcarriers = 32
active_subcarriers = 20
cp_len = 16
filter_len = 8
overlap = 2
subcarrier_map = np.concatenate(
(np.arange(0, active_subcarriers // 2),
np.arange(subcarriers - active_subcarriers // 2, subcarriers)))
print subcarrier_map
snr_db = 5.
offset = 1000
preamble, x_preamble = mapped_preamble(seed, 'rrc', .5, active_subcarriers,
subcarriers, subcarrier_map,
overlap, cp_len, filter_len)
noise_variance = calculate_awgn_noise_variance(preamble, snr_db)
rx = get_complex_noise_vector(len(preamble) + 2 * offset, noise_variance)
rx[offset:offset + len(preamble)] += preamble
print('frame offset', offset, 'with cp_len', cp_len)
xc = np.correlate(rx, x_preamble, 'valid')
# xc *= np.max(np.abs(rx)) / np.max(np.abs(xc))
# xc /= calculate_average_signal_energy(tx)
peak = np.argmax(np.abs(xc))
print('frame located @{}'.format(peak))
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(
rx, x_preamble, subcarriers, cp_len)
print('find frame start res @{} and cfo: {}'.format(nc, cfo))
s_nm, s_cfo, simple_ac = simplified_sync_algo(rx, x_preamble, subcarriers,
cp_len)
print('simple algo res @{} and cfo: {}'.format(s_nm, s_cfo))
sync_kernel = cgfdm.py_auto_cross_corr_multicarrier_sync_cc(
subcarriers, cp_len, x_preamble)
kpos, kcfo = sync_kernel.detect_frame(rx.astype(dtype=np.complex64))
print('kernel: nc={}, cfo={}'.format(kpos, kcfo))
assert (kpos == s_nm)
assert (np.abs(s_cfo - kcfo) < 1e-7)
def test_008_auto_correlation_stepped(self):
print 'test window buffering for auto correlation'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 10.0
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(
signal, preamble, K, cp_len)
step_size = 1088
for i in range(0, len(signal), step_size):
w = signal[i:i + step_size + 3 * K]
a = abs_corr_vals[i:i + step_size]
ref_buf = abs_corr_vals[i + step_size - 2 * K:i + step_size]
cref_buf = corr_vals[i + step_size - 2 * K:i + step_size]
inref_buf = signal[i + step_size - 2 * K:i + step_size]
if len(w) > 4 * K and len(ref_buf) == 2 * K:
bi_buf = np.array(kernel.integration_buffer())
kbuf = np.concatenate((bi_buf, a))
print 'KBEF argmax', np.argmax(kbuf)
snc = int(kernel.find_preamble(
w)) # necessary to update kernel state!
ai_buf = np.array(kernel.integration_buffer())
self.assertFloatTuplesAlmostEqual(ref_buf, ai_buf, 5)
c_buf = np.array(kernel.auto_corr_buffer())
self.assertComplexTuplesAlmostEqual(cref_buf, c_buf, 5)
in_buf = np.array(kernel.input_buffer())
self.assertComplexTuplesAlmostEqual(inref_buf, in_buf)
def test_010_sync_block(self):
np.set_printoptions(precision=4)
print 'GR block sync!'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
frame_len = 2 * K + cp_len + M * K
test_cfo = -.2
snr_dB = 10.0
n_reps = 4
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(
signal, np.array(kernel.preamble()), K, cp_len)
print 'Python frame start: ', nc
signal = np.tile(signal, n_reps)
src = blocks.vector_source_c(signal)
sync = gfdm.sync_cc(K, cp_len, frame_len, preamble, 'gfdm_block')
snk = blocks.vector_sink_c()
self.tb.connect(src, sync, snk)
self.tb.run()
ref = signal[nc:nc + frame_len]
ref = np.tile(ref, n_reps)
res = np.array(snk.data())
print 'res length:', len(res) / n_reps
print 'frame size:', frame_len
self.assertComplexTuplesAlmostEqual(ref, res)
def preamble_sync_test():
seed = 4711
timeslots = 9
subcarriers = 32
active_subcarriers = 20
cp_len = 16
filter_len = 8
overlap = 2
subcarrier_map = np.concatenate((np.arange(0, active_subcarriers // 2), np.arange(subcarriers - active_subcarriers // 2, subcarriers)))
print subcarrier_map
snr_db = 5.
offset = 1000
preamble, x_preamble = mapped_preamble(seed, 'rrc', .5, active_subcarriers, subcarriers, subcarrier_map, overlap,
cp_len, filter_len)
noise_variance = calculate_awgn_noise_variance(preamble, snr_db)
rx = get_complex_noise_vector(len(preamble) + 2 * offset, noise_variance)
rx[offset:offset + len(preamble)] += preamble
print('frame offset', offset, 'with cp_len', cp_len)
xc = np.correlate(rx, x_preamble, 'valid')
# xc *= np.max(np.abs(rx)) / np.max(np.abs(xc))
# xc /= calculate_average_signal_energy(tx)
peak = np.argmax(np.abs(xc))
print('frame located @{}'.format(peak))
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(rx, x_preamble, subcarriers,
cp_len)
print('find frame start res @{} and cfo: {}'.format(nc, cfo))
s_nm, s_cfo, simple_ac = simplified_sync_algo(rx, x_preamble, subcarriers, cp_len)
print('simple algo res @{} and cfo: {}'.format(s_nm, s_cfo))
sync_kernel = cgfdm.py_auto_cross_corr_multicarrier_sync_cc(subcarriers, cp_len, x_preamble)
kpos, kcfo = sync_kernel.detect_frame(rx.astype(dtype=np.complex64))
print('kernel: nc={}, cfo={}'.format(kpos, kcfo))
assert(kpos == s_nm)
assert(np.abs(s_cfo - kcfo) < 1e-7)
def test_007_frame(self):
print 'find frame test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 20.0
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
# print 'preamble size:', len(preamble), len(preamble) == 2 * K
# print 'init kernel'
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, auto_corr_vals, corr_vals, napcc, apcc = find_frame_start(signal, preamble, K, cp_len)
# print 'kernel.find_preamble'
knc = np.array(kernel.find_preamble(signal))
print knc, nc
self.assertEqual(nc, knc)
def test_008_auto_correlation_stepped(self):
print 'test window buffering for auto correlation'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.2
snr_dB = 10.0
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
signal *= .001
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
preamble = np.array(kernel.preamble())
nc, cfo, abs_corr_vals, corr_vals, napcc, apcc = find_frame_start(signal, preamble, K, cp_len)
step_size = 1088
for i in range(0, len(signal), step_size):
w = signal[i:i + step_size + 3 * K]
a = abs_corr_vals[i:i + step_size]
ref_buf = abs_corr_vals[i + step_size - 2 * K:i + step_size]
cref_buf = corr_vals[i + step_size - 2 * K:i + step_size]
inref_buf = signal[i + step_size - 2 * K:i + step_size]
if len(w) > 4 * K and len(ref_buf) == 2 * K:
bi_buf = np.array(kernel.integration_buffer())
kbuf = np.concatenate((bi_buf, a))
print 'KBEF argmax', np.argmax(kbuf)
snc = int(kernel.find_preamble(w)) # necessary to update kernel state!
ai_buf = np.array(kernel.integration_buffer())
self.assertFloatTuplesAlmostEqual(ref_buf, ai_buf, 5)
c_buf = np.array(kernel.auto_corr_buffer())
self.assertComplexTuplesAlmostEqual(cref_buf, c_buf, 5)
in_buf = np.array(kernel.input_buffer())
self.assertComplexTuplesAlmostEqual(inref_buf, in_buf)