def __init__(self, N=12, M=256, indices=[], mapping=0, modulation=16, cp_ratio=0.25):
gr.hier_block2.__init__(self,
"scfdma_receiver_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signature(len(indices), len(indices), gr.sizeof_char*1),
)
##################################################
# Parameters
##################################################
self.indices = indices
self.modulation = modulation
self.cp_ratio = cp_ratio
self.M = M
self.N = N
self.mapping = mapping
##################################################
# Variables
##################################################
self.demappers = demappers = list()
self.idft_blocks = idft_blocks = list()
self.estimation_blocks = estimation_blocks = list()
##################################################
# Blocks
##################################################
# self.ofdm_scfdma_subcarrier_demapper_vcvc_0 = ofdm.scfdma_subcarrier_demapper_vcvc(N, M, start_index, mapping)
# self.ofdm_fbmc_symbol_estimation_vcb_0 = ofdm.fbmc_symbol_estimation_vcb(N, modulation)
# self.fft_vxx_0_0 = fft.fft_vcc(N, False, (), True, 1)
self.fft_vxx_0 = fft.fft_vcc(M, True, (), True, 1)
self.blocks_stream_to_vector_0 = blocks.stream_to_vector(gr.sizeof_gr_complex*1, M)
self.blocks_keep_m_in_n_0 = blocks.keep_m_in_n(gr.sizeof_gr_complex, M, int(M*(1+cp_ratio)), int(cp_ratio*M))
# create demappers, idft and estimation blocks
for i in range(len(indices)):
self.demappers.append(ofdm.scfdma_subcarrier_demapper_vcvc(N, M, indices[i], mapping))
self.idft_blocks.append(fft.fft_vcc(N, False, (), True, 1))
self.estimation_blocks.append(ofdm.fbmc_symbol_estimation_vcb(N, modulation))
##################################################
# Connections
##################################################
self.connect((self, 0), (self.blocks_keep_m_in_n_0, 0))
self.connect((self.blocks_keep_m_in_n_0, 0), (self.blocks_stream_to_vector_0, 0))
self.connect((self.blocks_stream_to_vector_0, 0), (self.fft_vxx_0, 0))
# connect the rest
for i in range(len(indices)):
self.connect((self.fft_vxx_0, 0), (self.demappers[i],0))
self.connect((self.demappers[i],0), (self.idft_blocks[i],0))
self.connect((self.idft_blocks[i],0), (self.estimation_blocks[i],0))
self.connect((self.estimation_blocks[i],0), (self, i))
def __init__(self,
M=1024,
K=4,
qam_size=16,
syms_per_frame=10,
carriers=924,
theta_sel=0,
sel_eq=0,
exclude_preamble=0,
sel_preamble=0,
zero_pads=1,
extra_pad=False):
gr.hier_block2.__init__(
self,
"fbmc_receiver_hier_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(1, 1, gr.sizeof_char * 1),
)
##################################################
# Parameters
##################################################
self.theta_sel = theta_sel
self.exclude_preamble = exclude_preamble
self.sel_eq = sel_eq
self.M = M
self.K = K
self.qam_size = qam_size
self.syms_per_frame = syms_per_frame
##################################################
# Variables
##################################################
if self.exclude_preamble == 1 and self.sel_eq != 3:
self.sel_eq = sel_eq = 3
warnings.warn(
"Since exclude_preamble is set as 1, sel_eq is forced to be 3 (no equalizer)"
)
self.skip = skip = 0
if exclude_preamble == 1 or sel_eq == 3 or sel_eq == 0:
self.skip = skip = 0
else:
self.skip = skip = 1
# Assertions
assert (M > 0 and K > 0
and qam_size > 0), "M, K and qam_size should be bigger than 0"
assert ((math.log(M) / math.log(2)) == int(
math.log(M) / math.log(2))), "M should be a power of 2"
assert (K == 4), "for now only K=4 s supported."
assert (qam_size == 4 or qam_size == 16 or qam_size == 64
or qam_size == 128 or qam_size == 256
), "Only 4-,16-,64-,128-,256-qam constellations are supported."
assert (theta_sel == 0 or theta_sel == 1)
assert (exclude_preamble == 0 or exclude_preamble == 1)
##################################################
# Blocks
##################################################
self.ofdm_vector_mask_0 = ofdm.vector_mask(M, (M - carriers) / 2,
carriers, [])
self.ofdm_fbmc_symbol_estimation_vcb_0 = ofdm.fbmc_symbol_estimation_vcb(
carriers, qam_size)
# unsigned int M, unsigned int syms_per_frame, int sel_preamble, int zero_pads, bool extra_pad, int sel_eq
self.ofdm_fbmc_subchannel_processing_vcvc_0 = ofdm.fbmc_subchannel_processing_vcvc(
M, syms_per_frame, sel_preamble, zero_pads, extra_pad, sel_eq)
self.ofdm_fbmc_separate_vcvc_0 = ofdm.fbmc_separate_vcvc(M, 2)
self.ofdm_fbmc_remove_preamble_vcvc_0 = ofdm.fbmc_remove_preamble_vcvc(
M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
self.ofdm_fbmc_polyphase_network_vcvc_3 = ofdm.fbmc_polyphase_network_vcvc(
M, K, K * M - 1, True)
self.ofdm_fbmc_polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(
M, K, K * M - 1, True)
self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0 = ofdm.fbmc_overlapping_serial_to_parallel_cvc(
M)
self.ofdm_fbmc_oqam_postprocessing_vcvc_0 = ofdm.fbmc_oqam_postprocessing_vcvc(
M, 0, theta_sel)
self.ofdm_fbmc_junction_vcvc_0 = ofdm.fbmc_junction_vcvc(M, 2)
self.ofdm_fbmc_beta_multiplier_vcvc_1 = ofdm.fbmc_beta_multiplier_vcvc(
M, K, K * M - 1, 0)
self.fft_vxx_1 = fft.fft_vcc(M, True, ([]), True, 1)
self.blocks_skiphead_0_0 = blocks.skiphead(gr.sizeof_gr_complex * M,
skip)
self.blocks_skiphead_0 = blocks.skiphead(gr.sizeof_gr_complex * M,
2 * K - 1 - 1)
self.blocks_null_sink_0 = blocks.null_sink(gr.sizeof_gr_complex * M)
self.blks2_selector_0_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex * M,
num_inputs=2,
num_outputs=1,
input_index=exclude_preamble,
output_index=0,
)
##################################################
# Connections
##################################################
self.connect((self.blks2_selector_0_0, 0),
(self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0))
self.connect((self.ofdm_fbmc_remove_preamble_vcvc_0, 0),
(self.blks2_selector_0_0, 0))
self.connect((self.blocks_skiphead_0_0, 0),
(self.blks2_selector_0_0, 1))
self.connect((self.blocks_skiphead_0_0, 0),
(self.ofdm_fbmc_remove_preamble_vcvc_0, 0))
self.connect((self.ofdm_fbmc_beta_multiplier_vcvc_1, 0),
(self.blocks_skiphead_0, 0))
self.connect((self.fft_vxx_1, 0),
(self.ofdm_fbmc_beta_multiplier_vcvc_1, 0))
self.connect((self.blocks_skiphead_0, 0),
(self.ofdm_fbmc_subchannel_processing_vcvc_0, 0))
self.connect((self.ofdm_fbmc_junction_vcvc_0, 0), (self.fft_vxx_1, 0))
self.connect((self.ofdm_fbmc_symbol_estimation_vcb_0, 0), (self, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_vcvc_0, 1),
(self.blocks_null_sink_0, 0))
self.connect((self.ofdm_vector_mask_0, 0),
(self.ofdm_fbmc_symbol_estimation_vcb_0, 0))
self.connect((self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0),
(self.ofdm_vector_mask_0, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_vcvc_0, 0),
(self.blocks_skiphead_0_0, 0))
self.connect((self, 0),
(self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 0),
(self.ofdm_fbmc_polyphase_network_vcvc_2, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 1),
(self.ofdm_fbmc_polyphase_network_vcvc_3, 0))
self.connect((self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0),
(self.ofdm_fbmc_separate_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_2, 0),
(self.ofdm_fbmc_junction_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_3, 0),
(self.ofdm_fbmc_junction_vcvc_0, 1))
def __init__(self,
N=12,
M=256,
indices=[],
mapping=0,
modulation=16,
cp_ratio=0.25):
gr.hier_block2.__init__(
self,
"scfdma_receiver_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(len(indices), len(indices), gr.sizeof_char * 1),
)
##################################################
# Parameters
##################################################
self.indices = indices
self.modulation = modulation
self.cp_ratio = cp_ratio
self.M = M
self.N = N
self.mapping = mapping
##################################################
# Variables
##################################################
self.demappers = demappers = list()
self.idft_blocks = idft_blocks = list()
self.estimation_blocks = estimation_blocks = list()
##################################################
# Blocks
##################################################
# self.ofdm_scfdma_subcarrier_demapper_vcvc_0 = ofdm.scfdma_subcarrier_demapper_vcvc(N, M, start_index, mapping)
# self.ofdm_fbmc_symbol_estimation_vcb_0 = ofdm.fbmc_symbol_estimation_vcb(N, modulation)
# self.fft_vxx_0_0 = fft.fft_vcc(N, False, (), True, 1)
self.fft_vxx_0 = fft.fft_vcc(M, True, (), True, 1)
self.blocks_stream_to_vector_0 = blocks.stream_to_vector(
gr.sizeof_gr_complex * 1, M)
self.blocks_keep_m_in_n_0 = blocks.keep_m_in_n(gr.sizeof_gr_complex, M,
int(M * (1 + cp_ratio)),
int(cp_ratio * M))
# create demappers, idft and estimation blocks
for i in range(len(indices)):
self.demappers.append(
ofdm.scfdma_subcarrier_demapper_vcvc(N, M, indices[i],
mapping))
self.idft_blocks.append(fft.fft_vcc(N, False, (), True, 1))
self.estimation_blocks.append(
ofdm.fbmc_symbol_estimation_vcb(N, modulation))
##################################################
# Connections
##################################################
self.connect((self, 0), (self.blocks_keep_m_in_n_0, 0))
self.connect((self.blocks_keep_m_in_n_0, 0),
(self.blocks_stream_to_vector_0, 0))
self.connect((self.blocks_stream_to_vector_0, 0), (self.fft_vxx_0, 0))
# connect the rest
for i in range(len(indices)):
self.connect((self.fft_vxx_0, 0), (self.demappers[i], 0))
self.connect((self.demappers[i], 0), (self.idft_blocks[i], 0))
self.connect((self.idft_blocks[i], 0),
(self.estimation_blocks[i], 0))
self.connect((self.estimation_blocks[i], 0), (self, i))
def __init__(self, M=1024, K=4, qam_size=16, syms_per_frame=10, carriers=924, theta_sel=0, sel_eq=0, exclude_preamble=0, sel_preamble=0, zero_pads=1, extra_pad=False):
gr.hier_block2.__init__(self,
"fbmc_receiver_hier_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signature(1, 1, gr.sizeof_char*1),
)
##################################################
# Parameters
##################################################
self.theta_sel = theta_sel
self.exclude_preamble = exclude_preamble
self.sel_eq = sel_eq
self.M = M
self.K = K
self.qam_size = qam_size
self.syms_per_frame = syms_per_frame
##################################################
# Variables
##################################################
if self.exclude_preamble == 1 and self.sel_eq != 3:
self.sel_eq = sel_eq = 3
warnings.warn("Since exclude_preamble is set as 1, sel_eq is forced to be 3 (no equalizer)")
self.skip = skip = 0
if exclude_preamble == 1 or sel_eq == 3 or sel_eq== 0:
self.skip = skip = 0
else:
self.skip = skip = 1
# Assertions
assert(M>0 and K>0 and qam_size>0), "M, K and qam_size should be bigger than 0"
assert((math.log(M)/math.log(2))==int(math.log(M)/math.log(2))), "M should be a power of 2"
assert(K==4), "for now only K=4 s supported."
assert(qam_size==4 or qam_size==16 or qam_size==64 or qam_size==128 or qam_size==256 ), "Only 4-,16-,64-,128-,256-qam constellations are supported."
assert(theta_sel==0 or theta_sel==1)
assert(exclude_preamble==0 or exclude_preamble==1)
##################################################
# Blocks
##################################################
self.ofdm_vector_mask_0 = ofdm.vector_mask(M, (M-carriers)/2, carriers, [])
self.ofdm_fbmc_symbol_estimation_vcb_0 = ofdm.fbmc_symbol_estimation_vcb(carriers, qam_size)
# unsigned int M, unsigned int syms_per_frame, int sel_preamble, int zero_pads, bool extra_pad, int sel_eq
self.ofdm_fbmc_subchannel_processing_vcvc_0 = ofdm.fbmc_subchannel_processing_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad, sel_eq)
self.ofdm_fbmc_separate_vcvc_0 = ofdm.fbmc_separate_vcvc(M, 2)
self.ofdm_fbmc_remove_preamble_vcvc_0 = ofdm.fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
self.ofdm_fbmc_polyphase_network_vcvc_3 = ofdm.fbmc_polyphase_network_vcvc(M, K, K*M-1, True)
self.ofdm_fbmc_polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(M, K, K*M-1, True)
self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0 = ofdm.fbmc_overlapping_serial_to_parallel_cvc(M)
self.ofdm_fbmc_oqam_postprocessing_vcvc_0 = ofdm.fbmc_oqam_postprocessing_vcvc(M, 0, theta_sel)
self.ofdm_fbmc_junction_vcvc_0 = ofdm.fbmc_junction_vcvc(M, 2)
self.ofdm_fbmc_beta_multiplier_vcvc_1 = ofdm.fbmc_beta_multiplier_vcvc(M, K, K*M-1, 0)
self.fft_vxx_1 = fft.fft_vcc(M, True, ([]), True, 1)
self.blocks_skiphead_0_0 = blocks.skiphead(gr.sizeof_gr_complex*M, skip)
self.blocks_skiphead_0 = blocks.skiphead(gr.sizeof_gr_complex*M, 2*K-1-1)
self.blocks_null_sink_0 = blocks.null_sink(gr.sizeof_gr_complex*M)
self.blks2_selector_0_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex*M,
num_inputs=2,
num_outputs=1,
input_index=exclude_preamble,
output_index=0,
)
##################################################
# Connections
##################################################
self.connect((self.blks2_selector_0_0, 0), (self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0))
self.connect((self.ofdm_fbmc_remove_preamble_vcvc_0, 0), (self.blks2_selector_0_0, 0))
self.connect((self.blocks_skiphead_0_0, 0), (self.blks2_selector_0_0, 1))
self.connect((self.blocks_skiphead_0_0, 0), (self.ofdm_fbmc_remove_preamble_vcvc_0, 0))
self.connect((self.ofdm_fbmc_beta_multiplier_vcvc_1, 0), (self.blocks_skiphead_0, 0))
self.connect((self.fft_vxx_1, 0), (self.ofdm_fbmc_beta_multiplier_vcvc_1, 0))
self.connect((self.blocks_skiphead_0, 0), (self.ofdm_fbmc_subchannel_processing_vcvc_0, 0))
self.connect((self.ofdm_fbmc_junction_vcvc_0, 0), (self.fft_vxx_1, 0))
self.connect((self.ofdm_fbmc_symbol_estimation_vcb_0, 0), (self, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_vcvc_0, 1), (self.blocks_null_sink_0, 0))
self.connect((self.ofdm_vector_mask_0, 0), (self.ofdm_fbmc_symbol_estimation_vcb_0, 0))
self.connect((self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0), (self.ofdm_vector_mask_0, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_vcvc_0, 0), (self.blocks_skiphead_0_0, 0))
self.connect((self, 0), (self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 0), (self.ofdm_fbmc_polyphase_network_vcvc_2, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 1), (self.ofdm_fbmc_polyphase_network_vcvc_3, 0))
self.connect((self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0), (self.ofdm_fbmc_separate_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_2, 0), (self.ofdm_fbmc_junction_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_3, 0), (self.ofdm_fbmc_junction_vcvc_0, 1))
def __init__(self, M=1024, K=4, qam_size=16, syms_per_frame=10, boundaries=[], theta_sel=0, sel_eq=0, exclude_preamble=0, sel_preamble=0, zero_pads=1, extra_pad=False):
# for now, following assumption should be made:
# each user should be allocated with same number of subchannels.
lb = len(boundaries)
assert(lb>0), "The array that defines user boundaries cannot be passed as empty."
assert(lb%2 == 0), "Unbalanced boundary definition."
allocated = list()
for i in range(1,(lb/2)+1):
allocated.append(boundaries[2*i-1]-boundaries[2*i-2]+1)
if i>=2:
assert(allocated[i-2] == allocated[i-1]), "Each user should be allocated with same number of subchannels."
output_signature = list()
for i in range(lb/2):
output_signature.append(gr.sizeof_gr_complex*(boundaries[2*i+1]-boundaries[2*i]+1))
# print(output_signature)
gr.hier_block2.__init__(self,
"fbmc_receiver_multiuser_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1), # Input signature
gr.io_signature(lb/2, lb/2, gr.sizeof_char*1)) # Output signature
##################################################
# Parameters
##################################################
self.theta_sel = theta_sel
self.exclude_preamble = exclude_preamble
self.sel_eq = sel_eq
self.M = M
self.K = K
self.qam_size = qam_size
self.syms_per_frame = syms_per_frame
##################################################
# Variables
##################################################
if self.exclude_preamble == 1 and self.sel_eq != 3:
self.sel_eq = sel_eq = 3
warnings.warn("Since exclude_preamble is set as 1, sel_eq is forced to be 3 (no equalizer)")
self.skip = skip = 0
if exclude_preamble == 1 or sel_eq == 3 or sel_eq== 0:
self.skip = skip = 0
else:
self.skip = skip = 1
# Assertions
assert(M>0 and K>0 and qam_size>0), "M, K and qam_size should be bigger than 0"
assert((math.log(M)/math.log(2))==int(math.log(M)/math.log(2))), "M should be a power of 2"
assert(K==4), "for now only K=4 s supported."
assert(qam_size==4 or qam_size==16 or qam_size==64 or qam_size==128 or qam_size==256 ), "Only 4-,16-,64-,128-,256-qam constellations are supported."
assert(theta_sel==0 or theta_sel==1)
assert(exclude_preamble==0 or exclude_preamble==1)
##################################################
# Blocks
##################################################
self.ofdm_fbmc_subchannel_processing_mu_vcvc_0 = ofdm.fbmc_subchannel_processing_mu_vcvc(M=M,syms_per_frame=syms_per_frame,indices=boundaries,sel_preamble=sel_preamble,zero_pads=zero_pads,extra_pad=extra_pad,sel_eq=sel_eq)
self.ofdm_fbmc_separate_vcvc_0 = ofdm.fbmc_separate_vcvc(M, 2)
self.ofdm_fbmc_remove_preamble_vcvc_0 = ofdm.fbmc_remove_preamble_vcvc(M, syms_per_frame, sel_preamble, zero_pads, extra_pad)
self.ofdm_fbmc_polyphase_network_vcvc_3 = ofdm.fbmc_polyphase_network_vcvc(M, K, K*M-1, True)
self.ofdm_fbmc_polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(M, K, K*M-1, True)
self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0 = ofdm.fbmc_overlapping_serial_to_parallel_cvc(M)
self.ofdm_fbmc_oqam_postprocessing_vcvc_0 = ofdm.fbmc_oqam_postprocessing_vcvc(M, 0, theta_sel)
self.ofdm_fbmc_junction_vcvc_0 = ofdm.fbmc_junction_vcvc(M, 2)
self.ofdm_fbmc_beta_multiplier_vcvc_1 = ofdm.fbmc_beta_multiplier_vcvc(M, K, K*M-1, 0)
self.fft_vxx_1 = fft.fft_vcc(M, True, ([]), True, 1)
self.blocks_skiphead_0_0 = blocks.skiphead(gr.sizeof_gr_complex*M, skip)
self.blocks_skiphead_0 = blocks.skiphead(gr.sizeof_gr_complex*M, 2*K-1-1)
self.blocks_null_sink_0 = blocks.null_sink(gr.sizeof_gr_complex*M)
self.blks2_selector_0_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex*M,
num_inputs=2,
num_outputs=1,
input_index=exclude_preamble,
output_index=0,
)
##################################################
# Connections
##################################################
self.connect((self.blks2_selector_0_0, 0), (self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0))
self.connect((self.ofdm_fbmc_remove_preamble_vcvc_0, 0), (self.blks2_selector_0_0, 0))
self.connect((self.blocks_skiphead_0_0, 0), (self.blks2_selector_0_0, 1))
self.connect((self.blocks_skiphead_0_0, 0), (self.ofdm_fbmc_remove_preamble_vcvc_0, 0))
self.connect((self.ofdm_fbmc_beta_multiplier_vcvc_1, 0), (self.blocks_skiphead_0, 0))
self.connect((self.fft_vxx_1, 0), (self.ofdm_fbmc_beta_multiplier_vcvc_1, 0))
self.connect((self.blocks_skiphead_0, 0), (self.ofdm_fbmc_subchannel_processing_mu_vcvc_0, 0))
self.connect((self.ofdm_fbmc_junction_vcvc_0, 0), (self.fft_vxx_1, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_mu_vcvc_0, 1), (self.blocks_null_sink_0, 0))
self.connect((self.ofdm_fbmc_subchannel_processing_mu_vcvc_0, 0), (self.blocks_skiphead_0_0, 0))
self.connect((self, 0), (self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 0), (self.ofdm_fbmc_polyphase_network_vcvc_2, 0))
self.connect((self.ofdm_fbmc_separate_vcvc_0, 1), (self.ofdm_fbmc_polyphase_network_vcvc_3, 0))
self.connect((self.ofdm_fbmc_overlapping_serial_to_parallel_cvc_0, 0), (self.ofdm_fbmc_separate_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_2, 0), (self.ofdm_fbmc_junction_vcvc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_3, 0), (self.ofdm_fbmc_junction_vcvc_0, 1))
# blocks
# self.ofdm_fbmc_receiver_demo_0 = ofdm.fbmc_receiver_demo(M, K, qam_size, syms_per_frame, M, theta_sel, sel_eq, exclude_preamble, sel_preamble, zero_pads, extra_pad)
# instead of calling receiver_demo block we copy the content of that block and change subchannel processing part. 10.03.2015
# this way receiver_demo file will stay as original, multiuser case not implemented.
asymms = list()
for i in range(lb/2):
asymms.append(ofdm.fbmc_asymmetrical_vector_mask_vcvc(M,boundaries[2*i],boundaries[2*i+1]))
# print(str(i))
sym_est = list()
for i in range(lb/2):
sym_est.append(ofdm.fbmc_symbol_estimation_vcb(allocated[i], qam_size))
# connections
for i in range(lb/2):
self.connect((self.ofdm_fbmc_oqam_postprocessing_vcvc_0, 0), (asymms[i], 0))
self.connect((asymms[i], 0),(sym_est[i], 0))
self.connect((sym_est[i], 0),(self,i))