def qam64_map_demap_chain():
constellation_order = 6
snr_db = 20
constellation, bits_rep = cstl.generate_gray_constellation(
constellation_order)
print(constellation)
print(bits_rep)
app_llrs = np.zeros(constellation_order)
for i in range(2):
for j in range(2):
for k in range(2):
for l in range(2):
for m in range(2):
for n in range(2):
bits = np.array((i, j, k, l, m, n))
print(bits)
s = map_to_constellation(bits, constellation)
print(s)
l_prob = calculate_log_probability_vector(
s, constellation, snr_db)
print(l_prob)
llrs = calculate_64qam_llrs_messages(
app_llrs, l_prob)
llrs = np.array(llrs)
print(llrs)
hat_bits = decide_bits(llrs)
print(hat_bits)
print(np.all(bits == hat_bits))
if not np.all(bits == hat_bits):
raise RuntimeError(
'64QAM Mapping --> Demapping fails!')
def qam16_map_demap_chain():
constellation_order = 4
snr_db = 20
constellation, bits_rep = cstl.generate_gray_constellation(
constellation_order)
print(constellation)
print(bits_rep)
app_llrs = np.zeros(constellation_order)
for i in range(2):
for j in range(2):
for k in range(2):
for l in range(2):
bits = np.array((i, j, k, l))
# print(utils.pack_bits(bits, 4), bits)
app_llrs = 100. * (2. * bits - 1)
print(app_llrs)
s = map_to_constellation(bits, constellation)
print(s)
l_prob = calculate_log_probability_vector(
s, constellation, snr_db)
print(l_prob)
llrs = calculate_16qam_llrs_messages(app_llrs, l_prob)
# llrs = np.array(llrs)
print(llrs)
hat_bits = decide_bits(llrs)
print(hat_bits)
print(np.all(bits == hat_bits))
if not np.all(bits == hat_bits):
raise RuntimeError(
'16QAM Mapping --> Demapping fails!')
def verify_vector_snr(self, constellation_order, nbits):
constellation, bits_rep = generate_gray_constellation(
constellation_order)
data = np.random.randint(0, 2,
constellation_order * nbits).astype(np.uint8)
symbols = map_to_constellation(data, constellation)
snr = np.arange(35, dtype=np.float) + 1.
snr_step = 2.5
tags = []
offsets = (0, 50, 400, 450, 800)
last_offset = 0
ref = np.array([], dtype=np.float32)
for offset in offsets:
valuevector = pmt.init_f32vector(snr.size, snr.tolist())
t = gr.tag_utils.python_to_tag(
(offset, pmt.string_to_symbol("snr"), valuevector))
tags.append(t)
syms = symbols[last_offset:offset]
# print(syms.size)
ref_ln_probs = calculate_symbol_log_probabilities(
syms, constellation, snr - snr_step)
refs = calculate_llrs(ref_ln_probs)
ref = np.concatenate((ref, refs))
last_offset = offset
snr += snr_step
syms = symbols[last_offset:]
ref_ln_probs = calculate_symbol_log_probabilities(
syms, constellation, snr - snr_step)
refs = calculate_llrs(ref_ln_probs)
ref = np.concatenate((ref, refs))
ref *= .5
# print(f'test: Order={constellation_order}, bits={nbits}/{data.size}, packed={is_packed}')
mapper = symbolmapping.symbol_demapper_cf(constellation_order, "GRAY",
"snr")
src = blocks.vector_source_c(symbols, False, 1, tags)
snk = blocks.vector_sink_f()
self.tb.connect(src, mapper, snk)
self.tb.run()
res = np.array(snk.data())
if constellation_order > 3:
self.assertFloatTuplesAlmostEqual(tuple(np.sign(res)),
tuple(np.sign(ref)))
else:
# for i in range(ref.size - 10):
# if not np.abs(ref[i + 10] - res[i + 10]) < 1e-5:
# print(i, ref[i], res[i], np.abs(ref[i] - res[i]) < 1e-5)
self.assertFloatTuplesAlmostEqual(tuple(res), tuple(ref), 5)
def qpsk_map_demap_chain():
constellation_order = 2
snr_db = 20
constellation, bits_rep = cstl.generate_gray_constellation(
constellation_order)
print(constellation)
print(bits_rep)
app_llrs = np.zeros(constellation_order)
for i in range(2):
for j in range(2):
bits = np.array((i, j))
print(bits)
s = map_to_constellation(bits, constellation)
print(s)
l_prob = calculate_log_probability_vector(s, constellation, snr_db)
print(l_prob)
llr0, llr1 = calculate_qpsk_llrs_messages(app_llrs, l_prob)
print(llr0, llr1)
hat_bits = decide_bits((llr0, llr1))
print(hat_bits)
print(np.all(bits == hat_bits))
if not np.all(bits == hat_bits):
raise RuntimeError('QPSK Mapping --> Demapping fails!')
def main():
np.set_printoptions(precision=2)
qpsk_map_demap_chain()
qam16_map_demap_chain()
qam64_map_demap_chain()
try:
calculate_llrs(np.array([
[1, 4, 5, 6, 7, 8, 4, 3],
]))
except NotImplementedError:
pass
# return
rx = .6 + .7j
constellation_order = 4
snr_db = 20
constellation, bits_rep = cstl.generate_gray_constellation(
constellation_order)
l_prob = calculate_log_probability_vector(rx, constellation, snr_db)
# print(constellation)
# print(bits_rep)
# print(l_prob)
llr0, llr1 = calculate_qpsk_log_probs_to_llrs(l_prob)
calculate_qpsk_probs_to_llrs(np.exp(l_prob))
# print(llr0)
# print(llr1)
bits = np.random.randint(0, 2, constellation_order * 300)
symbols = map_to_constellation(bits, constellation)
# print(symbols)
# symbols += utils.generate_complex_noise_symbols(len(symbols), snr_db)
log_probs = calculate_symbol_log_probabilities(symbols, constellation,
snr_db)
calculate_16qam_llrs(log_probs)
def verify_constellation_unpacked(self, constellation_order, nbits,
is_packed):
constellation, bits_rep = generate_gray_constellation(
constellation_order)
data = np.random.randint(0, 2,
constellation_order * nbits).astype(np.uint8)
ref = map_to_constellation(data, constellation)
if is_packed:
data = np.packbits(data)
# print(f'test: Order={constellation_order}, bits={nbits}/{data.size}, packed={is_packed}')
mapper = symbolmapping.symbol_mapper_bc(constellation_order, "GRAY",
is_packed)
src = blocks.vector_source_b(data)
snk = blocks.vector_sink_c()
self.tb.connect(src, mapper, snk)
self.tb.run()
res = np.array(snk.data())
self.assertComplexTuplesAlmostEqual(tuple(res), tuple(ref), 6)