def test_003_abs_integrate(self):
print 'abs_integrate test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
window_size = 1024
kic = np.array([], dtype=np.complex)
for i in range(0, len(signal), window_size):
w = ac[i:i + window_size]
kic = np.concatenate((kic, kernel.abs_integrate_preamble(w)))
# kic = np.array(kernel.abs_integrate_preamble(ac))
self.assertFloatTuplesAlmostEqual(ic[cp_len:], kic[cp_len:], 6)
def test_004_find_auto_correlation_peak(self):
print 'find auto correlation peak test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
nm = np.argmax(ic)
knm = kernel.find_peak_preamble(ic)
self.assertEqual(nm, knm)
cfo = np.angle(ac[nm]) / np.pi
kcfo = kernel.calculate_normalized_cfo_preamble(ac[knm])
self.assertAlmostEqual(cfo, kcfo)
def test_005_remove_cfo(self):
print 'remove CFO test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
nm = np.argmax(ic)
cfo = np.angle(ac[nm]) / np.pi
s = correct_frequency_offset(signal, cfo / (2. * K))
ks = kernel.remove_cfo_preamble(signal, cfo)
self.assertComplexTuplesAlmostEqual(
s, ks, 3) # VOLK rotator is inaccurate. Thus, accuracy == 3
def test_003_abs_integrate(self):
print 'abs_integrate test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
window_size = 1024
kic = np.array([], dtype=np.complex)
for i in range(0, len(signal), window_size):
w = ac[i:i + window_size]
kic = np.concatenate((kic, kernel.abs_integrate_preamble(w)))
# kic = np.array(kernel.abs_integrate_preamble(ac))
self.assertFloatTuplesAlmostEqual(ic[cp_len:], kic[cp_len:], 6)
def test_004_find_auto_correlation_peak(self):
print 'find auto correlation peak test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
nm = np.argmax(ic)
knm = kernel.find_peak_preamble(ic)
self.assertEqual(nm, knm)
cfo = np.angle(ac[nm]) / np.pi
kcfo = kernel.calculate_normalized_cfo_preamble(ac[knm])
self.assertAlmostEqual(cfo, kcfo)
def test_001_norm_preamble(self):
alpha = .5
K = 32
cp_len = K
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
kernel_preamble = np.array(kernel.preamble())
# normalize preamble
preamble /= np.sqrt(np.abs(calculate_signal_energy(preamble)))
print 'norm_preamble energy:', calculate_signal_energy(preamble)
self.assertComplexTuplesAlmostEqual(kernel_preamble, preamble)
def test_001_norm_preamble(self):
alpha = .5
K = 32
cp_len = K
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
kernel_preamble = np.array(kernel.preamble())
# normalize preamble
preamble /= np.sqrt(np.abs(calculate_signal_energy(preamble)))
print 'norm_preamble energy:', calculate_signal_energy(preamble)
self.assertComplexTuplesAlmostEqual(kernel_preamble, preamble)
def test_002_auto_correlate(self):
print 'auto correlation test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
ac = auto_correlate_signal(signal, K)
kac = np.array(kernel.auto_correlate_preamble(signal))
self.assertComplexTuplesAlmostEqual(ac, kac, 6)
def test_002_auto_correlate(self):
print 'auto correlation test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(
K, cp_len, preamble, 4000)
signal, preamble = generate_test_sync_samples(M, K, L, alpha, cp_len,
ramp_len, snr_dB,
test_cfo)
ac = auto_correlate_signal(signal, K)
kac = np.array(kernel.auto_correlate_preamble(signal))
self.assertComplexTuplesAlmostEqual(ac, kac, 6)
def test_005_remove_cfo(self):
print 'remove CFO test'
alpha = .5
M = 33
K = 32
L = 2
cp_len = K
ramp_len = cp_len / 2
test_cfo = -.1
snr_dB = 15.0
pre_gen = gfdm.preamble_generator(K, alpha, K * 2)
preamble = np.array(pre_gen.get_preamble())
kernel = gfdm.improved_sync_algorithm_kernel_cc(K, cp_len, preamble, 4000)
signal, preamble, pn_symbols = generate_test_sync_samples(M, K, L, alpha, cp_len, ramp_len, snr_dB, test_cfo)
ac = auto_correlate_signal(signal, K)
ic = abs_integrate(np.abs(ac), cp_len)
nm = np.argmax(ic)
cfo = np.angle(ac[nm]) / np.pi
s = correct_frequency_offset(signal, cfo, 2 * K)
ks = kernel.remove_cfo_preamble(signal, cfo)