def test_005_t (self):
# just to see if when syms_per_frame=0, it is still working.
M = 256
syms_per_frame = 10
num_frame = int(math.pow(2,10))
start = 5
end = 9
zero_pads = 1
extra_pad = False
sel_preamble = 0
sel_eq = 2
# preamble = [0]*M*zero_pads+[0]*4+[1, -1j, -1, 1j]*3+[0]*(M-end-1)+[0]*M*zero_pads
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
preamble = [0]*M*zero_pads+[0]*4+[1, -1j, -1, 1j]+[1, -1j, -1]+[0]*(M-end-1-1)+[0]*M*zero_pads
elif sel_preamble == 1: # standard preamble with triple repetition
preamble = [0]*M*zero_pads+([0]*4+[1, -1j, -1, 1j]+[1, -1j, -1]+[0]*(M-end-1-1))*3+[0]*M*zero_pads
elif sel_preamble ==2: # IAM-R preamble [1, -1,-1, 1]
preamble = [0]*M*zero_pads+[0]*4+[1, -1, -1, 1]+4+[1, -1, -1]+[0]*(M-end-1-1)+[0]*M*zero_pads
else: # standard one vector center preamble [1,-j,-1,j]
preamble = [0]*M*zero_pads+[0]*4+[1, -1j, -1, 1j]+[1, -1j, -1]+[0]*(M-end-1-1)+[0]*M*zero_pads
if extra_pad:
preamble.extend(M*[0])
# for i in range(len(preamble)):
# print("i= "+str(i%M)+" "+str(preamble[i]))
# print("end")
src_data=list()
expected_result = list()
# e = 0 # exp. res index
for i in range(num_frame):
# expected_result.extend(preamble)
for k in range(M*2*syms_per_frame):
temp = int(random.random()*10)
src_data.append(temp)
# expected_result.append(temp)
expected_result.extend(src_data)
src = blocks.vector_source_c(src_data,vlen=M)
ipr = fbmc_insert_preamble_mu_vcvc(M=M, syms_per_frame=syms_per_frame, start=start, end=end, sel_eq=sel_eq, sel_preamble=sel_preamble, zero_pads=zero_pads, extra_pad=extra_pad)
rpr = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
dst = blocks.vector_sink_c(vlen=M)
self.tb.connect(src,ipr,rpr,dst)
self.tb.run ()
# check data
result_data = dst.data()
# print result_data
self.assertComplexTuplesAlmostEqual(tuple(expected_result),tuple(result_data))
def test_001_t (self):
# set up fg
src_data=(9,9j,-9,-9j,2,2j,-2,-2j,4,4j,-4,-4j,6,6j,-6,-6j)
preamble = (0,0,0,0,1,-1j,-1,1j,0,0,0,0)
# expected_result=(0,0,0,0,1,-1j,-1,1j,0,0,0,0,
# 1,1j,-1,-1j,2,2j,-2,-2j,
# 0,0,0,0,1,-1j,-1,1j,0,0,0,0,
# 4,4j,-4,-4j,6,6j,-6,-6j)
src = blocks.vector_source_c(src_data,vlen=4)
ipr = fbmc_insert_preamble_vcvc(4,1,preamble)
rpr = fbmc_remove_preamble_vcvc(4,1,len(preamble))
dst = blocks.vector_sink_c(vlen=4)
self.tb.connect(src,ipr,rpr,dst)
self.tb.run ()
# check data
result_data=dst.data()
# print len(preamble)
self.assertEqual(src_data,result_data)
def test_001_t(self):
# set up fg
src_data = (9, 9j, -9, -9j, 2, 2j, -2, -2j, 4, 4j, -4, -4j, 6, 6j, -6,
-6j)
preamble = (0, 0, 0, 0, 1, -1j, -1, 1j, 0, 0, 0, 0)
# expected_result=(0,0,0,0,1,-1j,-1,1j,0,0,0,0,
# 1,1j,-1,-1j,2,2j,-2,-2j,
# 0,0,0,0,1,-1j,-1,1j,0,0,0,0,
# 4,4j,-4,-4j,6,6j,-6,-6j)
src = blocks.vector_source_c(src_data, vlen=4)
ipr = fbmc_insert_preamble_vcvc(4, 1, preamble)
rpr = fbmc_remove_preamble_vcvc(4, 1, len(preamble))
dst = blocks.vector_sink_c(vlen=4)
self.tb.connect(src, ipr, rpr, dst)
self.tb.run()
# check data
result_data = dst.data()
# print len(preamble)
self.assertEqual(src_data, result_data)
def test_002_t(self):
M=int(math.pow(2,7))
len_frame = 10
num_frame = int(math.pow(2,12))
preamble = [0]*M+[1, -1j, -1, 1j]*int(M/4)+[0]*M
src_data=list()
for i in range(len_frame*2*num_frame*M):
src_data.append(int(random.random()*10))
src = blocks.vector_source_c(src_data,vlen=M)
ipr = fbmc_insert_preamble_vcvc(M,len_frame,preamble)
rpr = fbmc_remove_preamble_vcvc(M,len_frame,len(preamble))
dst = blocks.vector_sink_c(vlen=M)
self.tb.connect(src,ipr,rpr,dst)
self.tb.run ()
# check data
result_data = dst.data()
# print result_data
self.assertComplexTuplesAlmostEqual(tuple(src_data),tuple(result_data))
def test_002_t(self):
M = int(math.pow(2, 7))
len_frame = 10
num_frame = int(math.pow(2, 12))
preamble = [0] * M + [1, -1j, -1, 1j] * int(M / 4) + [0] * M
src_data = list()
for i in range(len_frame * 2 * num_frame * M):
src_data.append(int(random.random() * 10))
src = blocks.vector_source_c(src_data, vlen=M)
ipr = fbmc_insert_preamble_vcvc(M, len_frame, preamble)
rpr = fbmc_remove_preamble_vcvc(M, len_frame, len(preamble))
dst = blocks.vector_sink_c(vlen=M)
self.tb.connect(src, ipr, rpr, dst)
self.tb.run()
# check data
result_data = dst.data()
# print result_data
self.assertComplexTuplesAlmostEqual(tuple(src_data),
tuple(result_data))
def test_005_t(self):
# just to see if when syms_per_frame=0, it is still working.
M = 256
syms_per_frame = 10
num_frame = int(math.pow(2, 10))
start = 5
end = 9
zero_pads = 1
extra_pad = False
sel_preamble = 0
sel_eq = 2
# preamble = [0]*M*zero_pads+[0]*4+[1, -1j, -1, 1j]*3+[0]*(M-end-1)+[0]*M*zero_pads
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
preamble = [0] * M * zero_pads + [0] * 4 + [1, -1j, -1, 1j] + [
1, -1j, -1
] + [0] * (M - end - 1 - 1) + [0] * M * zero_pads
elif sel_preamble == 1: # standard preamble with triple repetition
preamble = [0] * M * zero_pads + (
[0] * 4 + [1, -1j, -1, 1j] + [1, -1j, -1] + [0] *
(M - end - 1 - 1)) * 3 + [0] * M * zero_pads
elif sel_preamble == 2: # IAM-R preamble [1, -1,-1, 1]
preamble = [0] * M * zero_pads + [0] * 4 + [1, -1, -1, 1] + 4 + [
1, -1, -1
] + [0] * (M - end - 1 - 1) + [0] * M * zero_pads
else: # standard one vector center preamble [1,-j,-1,j]
preamble = [0] * M * zero_pads + [0] * 4 + [1, -1j, -1, 1j] + [
1, -1j, -1
] + [0] * (M - end - 1 - 1) + [0] * M * zero_pads
if extra_pad:
preamble.extend(M * [0])
# for i in range(len(preamble)):
# print("i= "+str(i%M)+" "+str(preamble[i]))
# print("end")
src_data = list()
expected_result = list()
# e = 0 # exp. res index
for i in range(num_frame):
# expected_result.extend(preamble)
for k in range(M * 2 * syms_per_frame):
temp = int(random.random() * 10)
src_data.append(temp)
# expected_result.append(temp)
expected_result.extend(src_data)
src = blocks.vector_source_c(src_data, vlen=M)
ipr = fbmc_insert_preamble_mu_vcvc(M=M,
syms_per_frame=syms_per_frame,
start=start,
end=end,
sel_eq=sel_eq,
sel_preamble=sel_preamble,
zero_pads=zero_pads,
extra_pad=extra_pad)
rpr = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble,
zero_pads, extra_pad)
dst = blocks.vector_sink_c(vlen=M)
self.tb.connect(src, ipr, rpr, dst)
self.tb.run()
# check data
result_data = dst.data()
# print result_data
self.assertComplexTuplesAlmostEqual(tuple(expected_result),
tuple(result_data))
def test_001_t(self):
# set up fg
M = 16
syms_per_frame = 20
num_frame = int(math.pow(2, 10))
indices = [3, 6, 10, 14] # num_users = 2
sel_preamble = 1 # triple repetition preamble
zero_pads = 4
extra_pad = 1
sel_eq = 0 # one tap equalizer
# prepare test data containers
src_data = list()
expected_result1 = list() # expected res for user 1
expected_result2 = list() # expected res for user 2
preamble = list()
# prepare preamble
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [
0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0
]
elif sel_preamble == 1: # standard preamble with triple repetition
tmp = [0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0]
center_preamble = tmp * 3 #[1/math.sqrt(3), -1j/math.sqrt(3), -1/math.sqrt(3), 1j/math.sqrt(3)]*((int)(M/4))*3
elif sel_preamble == 2: # IAM-R preamble [1, -1,-1, 1]
center_preamble = [
0, 0, 0, 1, 1, -1, -1, 0, 0, 0, -1, 1, 1, -1, -1, 0
]
else: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [
0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0
]
preamble.extend([0] * zero_pads * M)
preamble.extend(center_preamble)
preamble.extend([0] * zero_pads * M)
if extra_pad:
preamble.extend([0] * M)
# print len(preamble)
# prepare test data
for k in range(num_frame):
# each frame will be multiplied by a random factor.
factor = int(random.random() * 10) + 1
tmp = [x * factor for x in preamble]
src_data.extend(tmp) # preamble is prepended.
for l in range(2 * syms_per_frame * M):
if (l % M < 3) or (l % M > 14) or (l % M > 6 and l % M < 10):
src_data.extend([0])
elif ((l % M >= 3) and (l % M <= 6)):
#belong to user1
data = int((random.random() * 10 + 1) *
abs(center_preamble[l % M]))
expected_result1.append(data)
src_data.append(data * factor)
else:
# belong to user2
data = int((random.random() * 10 + 1) *
abs(center_preamble[l % M]))
expected_result2.append(data)
src_data.append(data * factor)
# print "src:"
# for k in range((syms_per_frame*2+len(preamble)/M)*num_frame):
# print src_data[k*M:(k+1)*M]
# print str(len(src_data)-len(preamble)*num_frame)
src = blocks.vector_source_c(src_data, vlen=M)
scp = ofdm.fbmc_subchannel_processing_mu_vcvc(
M=M,
syms_per_frame=syms_per_frame,
indices=indices,
sel_preamble=sel_preamble,
zero_pads=zero_pads,
extra_pad=extra_pad,
sel_eq=sel_eq)
rem = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble,
zero_pads, extra_pad)
avm1 = ofdm.fbmc_asymmetrical_vector_mask_vcvc(M, 3, 6)
avm2 = ofdm.fbmc_asymmetrical_vector_mask_vcvc(M, 10, 14)
dst1 = blocks.vector_sink_c(vlen=4)
dst2 = blocks.vector_sink_c(vlen=5)
dst99 = blocks.vector_sink_c(vlen=M)
self.tb.connect((src, 0), (scp, 0))
self.tb.connect((scp, 0), (rem, 0))
self.tb.connect((rem, 0), avm1)
self.tb.connect((rem, 0), avm2)
self.tb.connect((avm1, 0), dst1)
self.tb.connect((avm2, 0), dst2)
# estimation probe is connected to dst99
self.tb.connect((scp, 1), dst99)
self.tb.run()
# check data
result_data1 = dst1.data()
result_data2 = dst2.data()
result_data99 = dst99.data()
# print "res:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data1[k*4:(k+1)*4]
# print "res99:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data99[k*M:(k+1)*M]
# for i in range(len(result_data2)):
# print str(i)+"\t"+str(result_data2[i])
# print result_data
self.assertComplexTuplesAlmostEqual(expected_result1, result_data1, 6)
self.assertComplexTuplesAlmostEqual(expected_result2, result_data2, 6)
def test_003_t(self):
# set up fg
M = 16
syms_per_frame = 20
num_frame = int(math.pow(2, 10))
indices = [3, 6, 10, 14] # num_users = 2
sel_preamble = 1
zero_pads = 2
extra_pad = 0
sel_eq = 4 #no eq
# prepare test data containers
src_data = list()
expected_result = list()
preamble = list()
# prepare preamble
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [
0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0
]
elif sel_preamble == 1: # standard preamble with triple repetition
tmp = [0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0]
center_preamble = tmp * 3 #[1/math.sqrt(3), -1j/math.sqrt(3), -1/math.sqrt(3), 1j/math.sqrt(3)]*((int)(M/4))*3
elif sel_preamble == 2: # IAM-R preamble [1, -1,-1, 1]
center_preamble = [
0, 0, 0, 1, 1, -1, -1, 0, 0, 0, -1, 1, 1, -1, -1, 0
]
else: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [
0, 0, 0, 1j, 1, -1j, -1, 0, 0, 0, -1, 1j, 1, -1j, -1, 0
]
preamble.extend([0] * zero_pads * M)
preamble.extend(center_preamble)
preamble.extend([0] * zero_pads * M)
if extra_pad:
preamble.extend([0] * M)
# print len(preamble)
# prepare test data
for k in range(num_frame):
# each frame will be multiplied by a random factor.
factor = int(random.random() * 10) + 1
tmp = [x * factor for x in preamble]
src_data.extend(tmp)
for l in range(2 * syms_per_frame * M):
if (l % M < 3) or (l % M > 14) or (l % M > 6 and l % M < 10):
data = 0
else:
data = int((random.random() * 10 + 1) *
abs(center_preamble[l % M]))
expected_result.append(data * factor)
src_data.append(data * factor)
# print "exp:"
# for k in range(syms_per_frame*2*num_frame):
# print expected_result[k*M:(k+1)*M]
# print "src:"
# for k in range((syms_per_frame*2+len(preamble)/M)*num_frame):
# print src_data[k*M:(k+1)*M]
# # print str(len(src_data)-len(preamble)*num_frame)
src = blocks.vector_source_c(src_data, vlen=M)
scp = ofdm.fbmc_subchannel_processing_mu_vcvc(
M=M,
syms_per_frame=syms_per_frame,
indices=indices,
sel_preamble=sel_preamble,
zero_pads=zero_pads,
extra_pad=extra_pad,
sel_eq=sel_eq)
rem = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble,
zero_pads, extra_pad)
dst = blocks.vector_sink_c(vlen=M)
dst2 = blocks.vector_sink_c(vlen=M)
self.tb.connect((src, 0), (scp, 0))
self.tb.connect((scp, 0), (rem, 0))
self.tb.connect((rem, 0), dst)
self.tb.connect((scp, 1), dst2)
self.tb.run()
# check data
result_data = dst.data()
result_data2 = dst2.data()
# print "res:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data[k*M:(k+1)*M]
# for i in range(len(result_data2)):
# print str(i)+"\t"+str(result_data2[i])
# print result_data
self.assertComplexTuplesAlmostEqual(expected_result, result_data, 6)
def test_001_t (self):
# set up fg
M = 16
syms_per_frame = 20
num_frame = int(math.pow(2,10))
indices = [3,6,10,14] # num_users = 2
sel_preamble = 1 # triple repetition preamble
zero_pads = 4
extra_pad = 1
sel_eq = 0 # one tap equalizer
# prepare test data containers
src_data = list()
expected_result1 = list() # expected res for user 1
expected_result2 = list() # expected res for user 2
preamble = list()
# prepare preamble
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
elif sel_preamble == 1: # standard preamble with triple repetition
tmp = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
center_preamble = tmp*3 #[1/math.sqrt(3), -1j/math.sqrt(3), -1/math.sqrt(3), 1j/math.sqrt(3)]*((int)(M/4))*3
elif sel_preamble ==2: # IAM-R preamble [1, -1,-1, 1]
center_preamble = [0, 0, 0, 1, 1, -1, -1, 0, 0, 0, -1, 1,1, -1, -1, 0]
else: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
preamble.extend([0]*zero_pads*M)
preamble.extend(center_preamble)
preamble.extend([0]*zero_pads*M)
if extra_pad:
preamble.extend([0]*M)
# print len(preamble)
# prepare test data
for k in range(num_frame):
# each frame will be multiplied by a random factor.
factor = int(random.random()*10)+1
tmp = [x*factor for x in preamble]
src_data.extend(tmp) # preamble is prepended.
for l in range(2*syms_per_frame*M):
if (l%M<3) or (l%M>14) or (l%M>6 and l%M<10):
src_data.extend([0])
elif ((l%M>=3) and (l%M<=6)):
#belong to user1
data = int((random.random()*10+1)*abs(center_preamble[l%M]))
expected_result1.append(data)
src_data.append(data*factor)
else:
# belong to user2
data = int((random.random()*10+1)*abs(center_preamble[l%M]))
expected_result2.append(data)
src_data.append(data*factor)
# print "src:"
# for k in range((syms_per_frame*2+len(preamble)/M)*num_frame):
# print src_data[k*M:(k+1)*M]
# print str(len(src_data)-len(preamble)*num_frame)
src = blocks.vector_source_c(src_data,vlen=M)
scp = ofdm.fbmc_subchannel_processing_mu_vcvc(M=M,syms_per_frame=syms_per_frame,indices=indices,sel_preamble=sel_preamble,zero_pads=zero_pads,extra_pad=extra_pad,sel_eq=sel_eq)
rem = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
avm1 = ofdm.fbmc_asymmetrical_vector_mask_vcvc(M,3,6)
avm2 = ofdm.fbmc_asymmetrical_vector_mask_vcvc(M,10,14)
dst1 = blocks.vector_sink_c(vlen=4)
dst2 = blocks.vector_sink_c(vlen=5)
dst99 = blocks.vector_sink_c(vlen=M)
self.tb.connect((src,0),(scp,0))
self.tb.connect((scp,0),(rem,0))
self.tb.connect((rem,0),avm1)
self.tb.connect((rem,0),avm2)
self.tb.connect((avm1,0),dst1)
self.tb.connect((avm2,0),dst2)
# estimation probe is connected to dst99
self.tb.connect((scp,1),dst99)
self.tb.run ()
# check data
result_data1 = dst1.data()
result_data2 = dst2.data()
result_data99 = dst99.data()
# print "res:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data1[k*4:(k+1)*4]
# print "res99:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data99[k*M:(k+1)*M]
# for i in range(len(result_data2)):
# print str(i)+"\t"+str(result_data2[i])
# print result_data
self.assertComplexTuplesAlmostEqual(expected_result1,result_data1,6)
self.assertComplexTuplesAlmostEqual(expected_result2,result_data2,6)
def test_003_t(self):
# set up fg
M = 16
syms_per_frame = 20
num_frame = int(math.pow(2,10))
indices = [3,6,10,14] # num_users = 2
sel_preamble = 1
zero_pads = 2
extra_pad = 0
sel_eq = 4 #no eq
# prepare test data containers
src_data = list()
expected_result = list()
preamble = list()
# prepare preamble
if sel_preamble == 0: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
elif sel_preamble == 1: # standard preamble with triple repetition
tmp = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
center_preamble = tmp*3 #[1/math.sqrt(3), -1j/math.sqrt(3), -1/math.sqrt(3), 1j/math.sqrt(3)]*((int)(M/4))*3
elif sel_preamble ==2: # IAM-R preamble [1, -1,-1, 1]
center_preamble = [0, 0, 0, 1, 1, -1, -1, 0, 0, 0, -1, 1,1, -1, -1, 0]
else: # standard one vector center preamble [1,-j,-1,j]
center_preamble = [0, 0, 0, 1j,1, -1j, -1, 0,0, 0, -1, 1j,1, -1j, -1, 0]
preamble.extend([0]*zero_pads*M)
preamble.extend(center_preamble)
preamble.extend([0]*zero_pads*M)
if extra_pad:
preamble.extend([0]*M)
# print len(preamble)
# prepare test data
for k in range(num_frame):
# each frame will be multiplied by a random factor.
factor = int(random.random()*10)+1
tmp = [x*factor for x in preamble]
src_data.extend(tmp)
for l in range(2*syms_per_frame*M):
if (l%M<3) or (l%M>14) or (l%M>6 and l%M<10):
data = 0
else:
data = int((random.random()*10+1)*abs(center_preamble[l%M]))
expected_result.append(data*factor)
src_data.append(data*factor)
# print "exp:"
# for k in range(syms_per_frame*2*num_frame):
# print expected_result[k*M:(k+1)*M]
# print "src:"
# for k in range((syms_per_frame*2+len(preamble)/M)*num_frame):
# print src_data[k*M:(k+1)*M]
# # print str(len(src_data)-len(preamble)*num_frame)
src = blocks.vector_source_c(src_data,vlen=M)
scp = ofdm.fbmc_subchannel_processing_mu_vcvc(M=M,syms_per_frame=syms_per_frame,indices=indices,sel_preamble=sel_preamble,zero_pads=zero_pads,extra_pad=extra_pad,sel_eq=sel_eq)
rem = fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
dst = blocks.vector_sink_c(vlen=M)
dst2 = blocks.vector_sink_c(vlen=M)
self.tb.connect((src,0),(scp,0))
self.tb.connect((scp,0),(rem,0))
self.tb.connect((rem,0),dst)
self.tb.connect((scp,1),dst2)
self.tb.run ()
# check data
result_data = dst.data()
result_data2 = dst2.data()
# print "res:"
# for k in range(syms_per_frame*2*num_frame):
# print result_data[k*M:(k+1)*M]
# for i in range(len(result_data2)):
# print str(i)+"\t"+str(result_data2[i])
# print result_data
self.assertComplexTuplesAlmostEqual(expected_result,result_data,6)
