def test_004_pcfich(self):
print "\ntest_004_pcfich"
cell_id = 124
ns = 0
N_ant = 2
vlen = 16
style = "tx_diversity"
self.tb2 = gr.top_block()
self.src = blocks.vector_source_c([0] * vlen, False, vlen)
self.demapper = lte.layer_demapper_vcvc(0, vlen, style)
self.snk = blocks.vector_sink_c(vlen)
self.tb2.connect(self.src, self.demapper, self.snk)
self.demapper.set_N_ant(N_ant)
data = []
exp_res = []
for cfi in range(4):
cfi_seq = lte_test.get_cfi_sequence(cfi + 1)
scr_cfi_seq = lte_test.scramble_cfi_sequence(cfi_seq, cell_id, ns)
mod_cfi_seq = lte_test.qpsk_modulation(scr_cfi_seq)
exp_res.extend(mod_cfi_seq)
lay_cfi_seq = lte_test.layer_mapping(mod_cfi_seq, N_ant, style)
for i in range(len(lay_cfi_seq)):
data.extend(lay_cfi_seq[i])
self.src.set_data(data)
self.tb2.run()
res = self.snk.data()
self.assertComplexTuplesAlmostEqual(res, exp_res)
def test_004_pcfich(self):
print "\ntest_004_pcfich"
cell_id = 124
ns = 0
N_ant = 2
vlen = 16
style = "tx_diversity"
self.tb2 = gr.top_block()
self.src = blocks.vector_source_c([0]*vlen,False,vlen)
self.demapper = lte_swig.layer_demapper_vcvc(0, vlen, style)
self.snk = blocks.vector_sink_c(vlen)
self.tb2.connect(self.src, self.demapper, self.snk)
self.demapper.set_N_ant(N_ant)
data = []
exp_res = []
for cfi in range(4):
cfi_seq = lte_test.get_cfi_sequence(cfi+1)
scr_cfi_seq = lte_test.scramble_cfi_sequence(cfi_seq, cell_id, ns)
mod_cfi_seq = lte_test.qpsk_modulation(scr_cfi_seq)
exp_res.extend(mod_cfi_seq)
lay_cfi_seq = lte_test.layer_mapping(mod_cfi_seq, N_ant, style)
for i in range(len(lay_cfi_seq)):
data.extend(lay_cfi_seq[i])
self.src.set_data(data)
self.tb2.run()
res = self.snk.data()
self.assertComplexTuplesAlmostEqual(res, exp_res)
def test_001_generated(self):
print "\ntest_001_generated"
cell_id = 124
N_ant = 2
style = "tx_diversity"
mib = lte_test.pack_mib(50, 0, 1.0, 511)
bch = lte_test.encode_bch(mib, N_ant)
scrambled = lte_test.pbch_scrambling(bch, cell_id)
qpsk_modulated = lte_test.qpsk_modulation(scrambled)
#print np.shape(qpsk_modulated)
layer_mapped = lte_test.layer_mapping(qpsk_modulated, N_ant, style)
pre_coded = lte_test.pre_coding(layer_mapped, N_ant, style)
#print np.shape(pre_coded)
h0 = [complex(1, 0)] * len(pre_coded[0])
h1 = [complex(1, 0)] * len(pre_coded[1])
stream = [pre_coded[0][i] + pre_coded[1][i] for i in range(len(pre_coded[0]))]
self.src1.set_data(stream)
self.src2.set_data(h0)
self.src3.set_data(h1)
self.tb.run()
res = self.snk.data()
exp_res = []
for i in range(len(stream) / 240):
print i
lay0 = layer_mapped[0][i * 120:(i + 1) * 120]
lay1 = layer_mapped[1][i * 120:(i + 1) * 120]
comb = [lay0, lay1]
exp_res.extend(lte_test.prepare_for_demapper_block(comb, N_ant, style))
print "test 001 final ASSERT!"
print self.assertComplexTuplesAlmostEqual(res, exp_res)
def test_002_pcfich(self):
print "test_002_pcfich"
# some constants
cell_id = 124
N_ant = 2
style = "tx_diversity"
vlen = 16
ns = 0
# new top_block because even the interface changes
self.tb2 = gr.top_block()
# generate test data together with the expected output
data = []
exp_res = []
for cfi in range(4):
cfi_seq = lte_test.get_cfi_sequence(cfi + 1)
scr_cfi_seq = lte_test.scramble_cfi_sequence(cfi_seq, cell_id, ns)
mod_cfi_seq = lte_test.qpsk_modulation(scr_cfi_seq)
lay_cfi_seq = lte_test.layer_mapping(mod_cfi_seq, N_ant, style)
lay_cfi_prep = lte_test.prepare_for_demapper_block(
lay_cfi_seq, N_ant, style)
exp_res.extend(lay_cfi_prep)
pc_cfi_seq = lte_test.pre_coding(lay_cfi_seq, N_ant, style)
pc_cfi_seq = [
pc_cfi_seq[0][i] + pc_cfi_seq[1][i]
for i in range(len(pc_cfi_seq[0]))
]
data.extend(pc_cfi_seq)
# dummy channel estimates
intu2 = [complex(1, 0)] * len(data)
intu3 = [complex(1, 0)] * len(data)
# get blocks
self.src1 = blocks.vector_source_c(data, False, vlen)
self.src2 = blocks.vector_source_c(intu2, False, vlen)
self.src3 = blocks.vector_source_c(intu3, False, vlen)
self.pd = lte.pre_decoder_vcvc(1, 1, vlen, style)
self.snk = blocks.vector_sink_c(vlen)
# connect all blocks
self.tb2.connect(self.src1, (self.pd, 0))
self.tb2.connect(self.src2, (self.pd, 1))
self.tb2.connect(self.src3, (self.pd, 2))
self.tb2.connect(self.pd, self.snk)
self.pd.set_N_ant(N_ant)
# run flowgraph
self.tb2.run()
# compare result with expected result
res = self.snk.data()
self.assertComplexTuplesAlmostEqual(res, exp_res)
def test_003_demapping (self):
print "\ntest_003_demapping"
N_ant = [1,2,4]
cell_id = 124
mib = lte_test.pack_mib(50,0,1.0, 511)
bch = tuple(lte_test.encode_bch(mib, N_ant[0]))
data = lte_test.pbch_scrambling(bch, cell_id)
style = "tx_diversity"
self.demapper.set_decoding_style(style)
mapped = [[],[],[]]
mapped[0] = lte_test.layer_mapping(data, 1 , style)
m2 = lte_test.layer_mapping(data, 2 , style)
m2a = []
for i in range(len(m2[0])/120):
m2a.extend(m2[0][120*i:(i+1)*120])
m2a.extend(m2[1][120*i:(i+1)*120])
mapped[1] = m2a
m4 = lte_test.layer_mapping(data, 4, style)
m4a = []
for i in range(len(m4[0])/60):
m4a.extend(m4[0][i*60:(i+1)*60])
m4a.extend(m4[1][i*60:(i+1)*60])
m4a.extend(m4[2][i*60:(i+1)*60])
m4a.extend(m4[3][i*60:(i+1)*60])
mapped[2] = m4a
exp_res = [complex(data[i]) for i in range(len(data))]
for i in range(3):
self.demapper.set_N_ant(N_ant[i])
print "N_ant = " +str(self.demapper.get_N_ant())
self.src.set_data(mapped[i])
self.snk.reset()
self.tb.run()
res = self.snk.data()
try:
self.assertComplexTuplesAlmostEqual(res, tuple(exp_res) )
except:
print "FAILED N_ant = " +str(self.demapper.get_N_ant())
self.assertComplexTuplesAlmostEqual(res, tuple(exp_res) )
def test_003_demapping(self):
print "\ntest_003_demapping"
N_ant = [1, 2, 4]
cell_id = 124
mib = lte_test.pack_mib(50, 0, 1.0, 511)
bch = tuple(lte_test.encode_bch(mib, N_ant[0]))
data = lte_test.pbch_scrambling(bch, cell_id)
style = "tx_diversity"
self.demapper.set_decoding_style(style)
mapped = [[], [], []]
mapped[0] = lte_test.layer_mapping(data, 1, style)[0]
m2 = lte_test.layer_mapping(data, 2, style)
m2a = []
for i in range(len(m2[0]) / 120):
m2a.extend(m2[0][120 * i:(i + 1) * 120])
m2a.extend(m2[1][120 * i:(i + 1) * 120])
mapped[1] = m2a
m4 = lte_test.layer_mapping(data, 4, style)
m4a = []
for i in range(len(m4[0]) / 60):
m4a.extend(m4[0][i * 60:(i + 1) * 60])
m4a.extend(m4[1][i * 60:(i + 1) * 60])
m4a.extend(m4[2][i * 60:(i + 1) * 60])
m4a.extend(m4[3][i * 60:(i + 1) * 60])
mapped[2] = m4a
exp_res = [complex(data[i]) for i in range(len(data))]
for i in range(3):
self.demapper.set_N_ant(N_ant[i])
print "N_ant = " + str(self.demapper.get_N_ant()), np.shape(mapped[i])
self.src.set_data(mapped[i])
self.snk.reset()
self.tb.run()
res = self.snk.data()
try:
self.assertComplexTuplesAlmostEqual(res, tuple(exp_res))
except:
print "FAILED N_ant = " + str(self.demapper.get_N_ant())
self.assertComplexTuplesAlmostEqual(res, tuple(exp_res))
def test_002_pcfich(self):
print "test_002_pcfich"
# some constants
cell_id = 124
N_ant = 2
style = "tx_diversity"
vlen = 16
ns = 0
# new top_block because even the interface changes
self.tb2 = gr.top_block()
# generate test data together with the expected output
data = []
exp_res = []
for cfi in range(4):
cfi_seq = lte_test.get_cfi_sequence(cfi + 1)
scr_cfi_seq = lte_test.scramble_cfi_sequence(cfi_seq, cell_id, ns)
mod_cfi_seq = lte_test.qpsk_modulation(scr_cfi_seq)
lay_cfi_seq = lte_test.layer_mapping(mod_cfi_seq, N_ant, style)
lay_cfi_prep = lte_test.prepare_for_demapper_block(lay_cfi_seq, N_ant, style)
exp_res.extend(lay_cfi_prep)
pc_cfi_seq = lte_test.pre_coding(lay_cfi_seq, N_ant, style)
pc_cfi_seq = [pc_cfi_seq[0][i] + pc_cfi_seq[1][i] for i in range(len(pc_cfi_seq[0]))]
data.extend(pc_cfi_seq)
# dummy channel estimates
intu2 = [complex(1, 0)] * len(data)
intu3 = [complex(1, 0)] * len(data)
# get blocks
self.src1 = blocks.vector_source_c(data, False, vlen)
self.src2 = blocks.vector_source_c(intu2, False, vlen)
self.src3 = blocks.vector_source_c(intu3, False, vlen)
self.pd = lte.pre_decoder_vcvc(1, vlen, style)
self.snk = blocks.vector_sink_c(vlen)
# connect all blocks
self.tb2.connect(self.src1, (self.pd, 0))
self.tb2.connect(self.src2, (self.pd, 1))
self.tb2.connect(self.src3, (self.pd, 2))
self.tb2.connect(self.pd, self.snk)
self.pd.set_N_ant(N_ant)
# run flowgraph
self.tb2.run()
# compare result with expected result
res = self.snk.data()
self.assertComplexTuplesAlmostEqual(res, exp_res)
def test_001_generated(self):
print "\ntest_001_generated"
cell_id = 124
N_ant = 2
style = "tx_diversity"
mib = lte_test.pack_mib(50, 0, 1.0, 511)
bch = lte_test.encode_bch(mib, N_ant)
scrambled = lte_test.pbch_scrambling(bch, cell_id)
qpsk_modulated = lte_test.qpsk_modulation(scrambled)
#print np.shape(qpsk_modulated)
layer_mapped = lte_test.layer_mapping(qpsk_modulated, N_ant, style)
pre_coded = lte_test.pre_coding(layer_mapped, N_ant, style)
#print np.shape(pre_coded)
h0 = [complex(1, 0)] * len(pre_coded[0])
h1 = [complex(1, 0)] * len(pre_coded[1])
stream = [
pre_coded[0][i] + pre_coded[1][i] for i in range(len(pre_coded[0]))
]
self.src1.set_data(stream)
self.src2.set_data(h0)
self.src3.set_data(h1)
self.tb.run()
res = self.snk.data()
exp_res = []
for i in range(len(stream) / 240):
print i
lay0 = layer_mapped[0][i * 120:(i + 1) * 120]
lay1 = layer_mapped[1][i * 120:(i + 1) * 120]
comb = [lay0, lay1]
exp_res.extend(
lte_test.prepare_for_demapper_block(comb, N_ant, style))
print "test 001 final ASSERT!"
print self.assertComplexTuplesAlmostEqual(res, exp_res)
