def sync_symbol2(filtertype, alpha, K, L, n_mod):
pn_order = 14
pn_seed = '01001000111011'
pn_mask = '01001101001110'
seq_length = K * n_mod
pn_sequence = cp.pnsequence(pn_order, pn_seed, pn_mask, seq_length)
qam_mod = cp.modulation.QAMModem(2 ** n_mod)
qam_sequence = qam_mod.modulate(pn_sequence)
output = gfdm_tx_fft2(np.tile(qam_sequence, 2), filtertype, alpha, 2, K, 2, 1)
return output
def gr_conformity_validation():
M = 32
K = 8
alpha = .5
oversampling_factor = 1
overlap = 2
tests = 100
for t in range(tests):
# d = np.random.standard_normal(2 * M * K)
# d = np.reshape(d, (2, -1))
# d = d[0] + 1j * d[1]
d = get_random_samples(M * K)
xo = gfdm_tx_fft2(d, 'rrc', alpha, M, K, overlap, oversampling_factor)
xn = gfdm_gr_modulator(d, 'rrc', alpha, M, K, overlap)
assert np.all(np.abs(xo - xn) < 1e-4)
def gr_conformity_validation():
M = 32
K = 8
alpha = .5
oversampling_factor = 1
overlap = 2
tests = 100
for t in range(tests):
# d = np.random.standard_normal(2 * M * K)
# d = np.reshape(d, (2, -1))
# d = d[0] + 1j * d[1]
d = get_random_samples(M * K)
xo = gfdm_tx_fft2(d, 'rrc', alpha, M, K, overlap, oversampling_factor)
xn = gfdm_gr_modulator(d, 'rrc', alpha, M, K, overlap)
if not np.all(xo == xn):
raise RuntimeError('Function results deviate')
def gr_conformity_validation():
M = 32
K = 8
alpha = .5
oversampling_factor = 1
overlap = 2
tests = 100
for t in range(tests):
# d = np.random.standard_normal(2 * M * K)
# d = np.reshape(d, (2, -1))
# d = d[0] + 1j * d[1]
d = get_random_samples(M * K)
xo = gfdm_tx_fft2(d, 'rrc', alpha, M, K, overlap, oversampling_factor)
xn = gfdm_gr_modulator(d, 'rrc', alpha, M, K, overlap)
if not np.all(xo == xn):
raise RuntimeError('Function results deviate')