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#!/usr/bin/env python
#
# Copyright 2008 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.
#
# GNU Radio is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Radio; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
# Andreas Mueller, 2008
# andrmuel@ee.ethz.ch
class dab_parameters:
"""
@brief Represents the DAB parameters.
DAB parameters for mode I to IV
as specified in
ETSI EN 300 401 V1.4.1 (2006-06)
"Digital Audio Broadcasting (DAB) to mobile, portable and fixed receivers"
"""
# parameter values for all modes
# OFDM parameters (section 14)
# Table 38, page 145 of the DAB specification
__symbols_per_frame__ = [76, 76, 153, 76] # number of OFDM symbols per DAB frame (incl. pilot, excl. NS)
__num_carriers__ = [1536, 384, 192, 768] # number of carriers -> carrier width = 1536kHz/carriers
__frame_length__ = [196608, 49152, 49152, 98304] # samples per frame; in ms: 96,24,24,48 (incl. NS)
__ns_length__ = [2656, 664, 345, 1328] # length of null symbol in samples
__symbol_length__ = [2552, 638, 319, 1276] # length of an OFDM symbol in samples
__fft_length__ = [2048, 512, 256, 1024] # fft length
__cp_length__ = [504, 126, 63, 252] # length of cyclic prefix
default_sample_rate = 2048000
T = 1. / default_sample_rate
# prn calculation data
# tables 39-43 on pages 148 and 149
# format: [mode][index][k_min, k_max, k', i, n]
__prn_kin__ = [[
[-768, -737, -768, 0, 1],
[-736, -705, -736, 1, 2],
[-704, -673, -704, 2, 0],
[-672, -641, -672, 3, 1],
[-640, -609, -640, 0, 3],
[-608, -577, -608, 1, 2],
[-576, -545, -576, 2, 2],
[-544, -513, -544, 3, 3],
[-512, -481, -512, 0, 2],
[-480, -449, -480, 1, 1],
[-448, -417, -448, 2, 2],
[-416, -385, -416, 3, 3],
[-384, -353, -384, 0, 1],
[-352, -321, -352, 1, 2],
[-320, -289, -320, 2, 3],
[-288, -257, -288, 3, 3],
[-256, -225, -256, 0, 2],
[-224, -193, -224, 1, 2],
[-192, -161, -192, 2, 2],
[-160, -129, -160, 3, 1],
[-128, -97, -128, 0, 1],
[-96, -65, -96, 1, 3],
[-64, -33, -64, 2, 1],
[-32, -1, -32, 3, 2],
[1, 32, 1, 0, 3],
[33, 64, 33, 3, 1],
[65, 96, 65, 2, 1],
[97, 128, 97, 1, 1],
[129, 160, 129, 0, 2],
[161, 192, 161, 3, 2],
[193, 224, 193, 2, 1],
[225, 256, 225, 1, 0],
[257, 288, 257, 0, 2],
[289, 320, 289, 3, 2],
[321, 352, 321, 2, 3],
[353, 384, 353, 1, 3],
[385, 416, 385, 0, 0],
[417, 448, 417, 3, 2],
[449, 480, 449, 2, 1],
[481, 512, 481, 1, 3],
[513, 544, 513, 0, 3],
[545, 576, 545, 3, 3],
[577, 608, 577, 2, 3],
[609, 640, 609, 1, 0],
[641, 672, 641, 0, 3],
[673, 704, 673, 3, 0],
[705, 736, 705, 2, 1],
[737, 768, 737, 1, 1]
], [
[-192, -161, -192, 0, 2],
[-160, -129, -160, 1, 3],
[-128, -97, -128, 2, 2],
[-96, -65, -96, 3, 2],
[-64, -33, -64, 0, 1],
[-32, -1, -32, 1, 2],
[1, 32, 1, 2, 0],
[33, 64, 33, 1, 2],
[65, 96, 65, 0, 2],
[97, 128, 97, 3, 1],
[129, 160, 129, 2, 0],
[161, 192, 161, 1, 3]
], [
[-96, -65, -96, 0, 2],
[-64, -33, -64, 1, 3],
[-32, -1, -32, 2, 0],
[1, 32, 1, 3, 2],
[33, 64, 33, 2, 2],
[65, 96, 65, 1, 2]
], [
[-384, -353, -384, 0, 0],
[-352, -321, -352, 1, 1],
[-320, -289, -320, 2, 1],
[-288, -257, -288, 3, 2],
[-256, -225, -256, 0, 2],
[-224, -193, -224, 1, 2],
[-192, -161, -192, 2, 0],
[-160, -129, -160, 3, 3],
[-128, -97, -128, 0, 3],
[-96, -65, -96, 1, 1],
[-64, -33, -64, 2, 3],
[-32, -1, -32, 3, 2],
[1, 32, 1, 0, 0],
[33, 64, 33, 3, 1],
[65, 96, 65, 2, 0],
[97, 128, 97, 1, 2],
[129, 160, 129, 0, 0],
[161, 192, 161, 3, 1],
[193, 224, 193, 2, 2],
[225, 256, 225, 1, 2],
[257, 288, 257, 0, 2],
[289, 320, 289, 3, 1],
[321, 352, 321, 2, 3],
[353, 384, 353, 1, 0]
]]
# h_i,j
# note: values for h_i,j are the same as for h_i,j+16 ...
__prn_h__ = [
[0, 2, 0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 1, 1, 0, 2, 0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 1, 1],
[0, 3, 2, 3, 0, 1, 3, 0, 2, 1, 2, 3, 2, 3, 3, 0, 0, 3, 2, 3, 0, 1, 3, 0, 2, 1, 2, 3, 2, 3, 3, 0],
[0, 0, 0, 2, 0, 2, 1, 3, 2, 2, 0, 2, 2, 0, 1, 3, 0, 0, 0, 2, 0, 2, 1, 3, 2, 2, 0, 2, 2, 0, 1, 3],
[0, 1, 2, 1, 0, 3, 3, 2, 2, 3, 2, 1, 2, 1, 3, 2, 0, 1, 2, 1, 0, 3, 3, 2, 2, 3, 2, 1, 2, 1, 3, 2]
]
__expected_frequency_interleaving__ = [
# these few values are listed in the specs - they are used to verify the sequence
[-513, -14, 329, 692, -733, 13, 680, 273, -36, 43],
[-129, -14, -55, -76, 163, 141, -88, 7, -111, -85],
[-65, -14, 52, -29, -58, 77, 40, 71, -38, 81],
[-257, -14, 73, 180, 198, -243, 168, 218, 17, 299]
]
# transport mechanism parameters
__num_fic_syms__ = [3, 3, 8, 3] # number of OFDM symbols per frame belonging to the FIC
__num_msc_syms__ = [72, 72, 144, 72] # number of OFDM symbols per frame belonging to the MSC
# puncturing
puncturing_vectors = [ # table 29, page 131
[], # "Who are you? How did you get in my house?"
[1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
# PI=1: code rate: 8/9
[1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
# PI=2: code rate: 8/10
[1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
# PI=3: code rate: 8/11
[1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0],
# PI=4: code rate: 8/12
[1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0],
# PI=5: code rate: 8/13
[1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0],
# PI=6: code rate: 8/14
[1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0],
# PI=7: code rate: 8/15
[1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
# PI=8: code rate: 8/16
[1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
# PI=9: code rate: 8/17
[1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
# PI=10 code rate: 8/18
[1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
# PI=11 code rate: 8/19
[1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0],
# PI=12 code rate: 8/20
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0],
# PI=13 code rate: 8/21
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0],
# PI=14 code rate: 8/22
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0],
# PI=15 code rate: 8/23
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0],
# PI=16 code rate: 8/24
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0],
# PI=17 code rate: 8/25
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0],
# PI=18 code rate: 8/26
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0],
# PI=19 code rate: 8/27
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0],
# PI=20 code rate: 8/28
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0],
# PI=21 code rate: 8/29
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
# PI=22 code rate: 8/30
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
# PI=23 code rate: 8/31
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
# PI=24 code rate: 8/32
]
puncturing_tail_vector = [1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0] # V_T
puncturing_vectors_ones = [0, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]
# conv coding rate at a protection level, table 7
conv_code_rate = [1/4, 3/8, 1/2, 3/4]
subch_size_multiple_n = [12, 8, 6, 4]
# convolutional coding - 11.1, page 129/130
conv_code_generator_polynomials = [
0o133,
0o171,
0o145,
0o133
]
conv_code_initial_state = 0
conv_code_final_state = 0
conv_code_constraint_length = 7
conv_code_in_bits = 1
conv_code_add_bits_input = 6
conv_code_out_bits = 4
__fic_conv_codeword_length__ = [3096, 3096, 4120, 3096] # 4*I + 24
__fic_punctured_codeword_length__ = [2304, 2304, 3072, 2304]
# energy dispersal
__energy_dispersal_fic_fibs_per_vector__ = [3, 3, 4, 3]
__energy_dispersal_fic_vector_length__ = [768, 768, 1024, 768] # I
__prbs_bits__ = [0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1,
0] # first 16 PRBS bits are given in the standard - can be used for another assert
# time interleaving
scrambling_vector = [0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15]
# transport mechanism parameters
fib_bits = 256
cif_bits = 55296
__num_fibs__ = [12, 3, 4, 6] # FIC
__num_cifs__ = [4, 1, 1, 2] # MSC -> num cifs = num fib groups
num_cus = 864 # number of CUs in one cif
msc_cu_size = 64 # size of capacity unit in msc (smallest unit)
def __init__(self, mode, sample_rate=2048000, verbose=True):
"""
selects the correct parameters for the selected mode and calculates the prn sequence, etc.
@param mode DAB mode (I-IV)
@param sample_rate sampling frequency
"""
if verbose:
print("--> creating DAB parameter object") # should not be seen more than once
assert (mode >= 1 and mode <= 4)
self.mode = mode
self.sample_rate = sample_rate
self.verbose = verbose
# sanity checks:
for i in range(0, 4):
# OFDM parameters
assert (
self.__symbols_per_frame__[i] * self.__symbol_length__[i] + self.__ns_length__[i] == self.__frame_length__[
i])
assert (self.__symbol_length__[i] == self.__fft_length__[i] + self.__cp_length__[i])
# block partitioning
assert (self.__num_carriers__[i] * 2 * self.__num_fic_syms__[i] / self.__num_cifs__[i] ==
self.__fic_punctured_codeword_length__[i])
# energy dispersal parameters
assert (self.__energy_dispersal_fic_fibs_per_vector__[i] * self.fib_bits ==
self.__energy_dispersal_fic_vector_length__[i])
assert (3 * self.__energy_dispersal_fic_vector_length__[i] == self.__fic_punctured_codeword_length__[
i]) # not sure - according to specification, code rate is only approximately 1/3, but seems to be exact
# sanity checks for PRBS sequence (energy dispersal)
assert (self.prbs(16) == self.__prbs_bits__) # bits from DAB standard
assert (self.prbs(511) == self.prbs(1022)[511:]) # sequence must repeat itself
if verbose:
print("--> DAB parameters self check ok")
self.__update_parameters__()
def set_mode(self, mode):
if self.verbose:
print("--> setting DAB mode to " + str(mode))
self.mode = mode
self.__update_parameters__()
def set_sample_rate(self, sample_rate):
if self.verbose:
print("--> setting sample rate to " + str(sample_rate))
self.sample_rate = sample_rate
self.__update_parameters__()
def __update_parameters__(self):
if self.verbose:
print("--> updating DAB parameters")
mode = self.mode
# OFDM parameters (14)
self.symbols_per_frame = self.__symbols_per_frame__[mode - 1]
self.num_carriers = self.__num_carriers__[mode - 1]
self.frame_length = self.__frame_length__[mode - 1]
self.ns_length = self.__ns_length__[mode - 1]
self.symbol_length = self.__symbol_length__[mode - 1]
self.fft_length = self.__fft_length__[mode - 1]
self.cp_length = self.__cp_length__[mode - 1]
# bytes per frame and bytes per symbol
self.bytes_per_frame = (self.symbols_per_frame - 1) * self.num_carriers / 4
self.bytes_per_symbol = self.num_carriers / 4
# prn sequence
self.prn = []
for k in range(-self.num_carriers // 2, self.num_carriers // 2 + 1):
if k == 0:
# self.prn.append(0)
pass
else:
[kk, i, n] = self.__get_prn_kk_i_n__(k)
h = self.__prn_h__[i][k - kk]
phi_k = (h + n) % 4 # actually phi_k/(pi/2)
if phi_k == 0: # e^(j*pi/2*phi_k) is not exact if calculated by python
self.prn.append(1)
elif phi_k == 1:
self.prn.append(1j)
elif phi_k == 2:
self.prn.append(-1)
elif phi_k == 3:
self.prn.append(-1j)
# frequency (de)interleaving
a = self.fft_length / 4 - 1
b = self.fft_length
A = [0]
for i in range(1, self.fft_length):
A.append((13 * A[-1] + a) % b)
D = [d for d in A if d >= self.fft_length / 8 and d <= 7 * self.fft_length / 8 and d != self.fft_length / 2]
assert (len(D) == self.num_carriers)
self.frequency_interleaving_sequence = [d - self.fft_length / 2 for d in D]
assert (self.frequency_interleaving_sequence[0:len(self.__expected_frequency_interleaving__[mode - 1])] ==
self.__expected_frequency_interleaving__[mode - 1])
# sequence for arrays, with indices starting from 0 and central carrier already removed
self.frequency_interleaving_sequence_array = [k + self.num_carriers / 2 - (k > 0) for k in
self.frequency_interleaving_sequence]
assert (len(self.frequency_interleaving_sequence_array) == self.num_carriers)
assert (min(self.frequency_interleaving_sequence_array) == 0)
assert (max(self.frequency_interleaving_sequence_array) == self.num_carriers - 1)
assert (len(set(self.frequency_interleaving_sequence_array)) == len(
self.frequency_interleaving_sequence_array)) # uniqueness of elements
# frequency deinterleaving sequence
self.frequency_deinterleaving_sequence_array = [self.frequency_interleaving_sequence_array.index(i) for i in
range(0, self.num_carriers)]
# adapt for non-standard sample rate - do this at end, frequency interleaving calculation still needs default fft length
if self.sample_rate != self.default_sample_rate:
if self.verbose:
print("--> using non-standard sample rate: " + str(self.sample_rate))
self.T = 1. / self.sample_rate
self.ns_length = int(round(self.ns_length * float(self.sample_rate) / float(self.default_sample_rate)))
self.cp_length = int(round(self.cp_length * float(self.sample_rate) / float(self.default_sample_rate)))
self.fft_length = int(round(self.fft_length * float(self.sample_rate) / float(self.default_sample_rate)))
self.symbol_length = self.cp_length + self.fft_length
self.frame_length = self.symbols_per_frame * self.symbol_length + self.ns_length
# block partitioning parameters (14.4)
self.num_fic_syms = self.__num_fic_syms__[mode - 1]
self.num_msc_syms = self.__num_msc_syms__[mode - 1]
# convolutional coding (11)
self.fic_conv_codeword_length = self.__fic_conv_codeword_length__[mode - 1] # length after puncturing
# unpuncturing sequence (assembled, such that it can be applied on a complete fib group)
# see 11.2 page 132
self.fic_punctured_codeword_length = self.__fic_punctured_codeword_length__[mode - 1]
if mode in [1, 2, 4]:
self.assembled_fic_puncturing_sequence = 21 * 4 * self.puncturing_vectors[16] + 3 * 4 * \
self.puncturing_vectors[
15] + self.puncturing_tail_vector
else:
self.assembled_fic_puncturing_sequence = 29 * 4 * self.puncturing_vectors[16] + 3 * 4 * \
self.puncturing_vectors[
15] + self.puncturing_tail_vector
assert (len(self.assembled_fic_puncturing_sequence) == self.fic_conv_codeword_length)
#assert (
#len(filter(lambda x: x == 1, self.assembled_fic_puncturing_sequence)) == self.fic_punctured_codeword_length)
# energy dispersal (10)
self.energy_dispersal_fic_fibs_per_vector = self.__energy_dispersal_fic_fibs_per_vector__[mode - 1]
self.energy_dispersal_fic_vector_length = self.__energy_dispersal_fic_vector_length__[mode - 1]
# transport mechanism parameters (5)
self.num_fibs = self.__num_fibs__[mode - 1]
self.num_cifs = self.__num_cifs__[mode - 1]
def __get_prn_kk_i_n__(self, k):
assert (k != 0)
assert (abs(k) <= self.num_carriers // 2)
if k < 0:
index = (k + self.num_carriers // 2) // 32
kk = 32 * (int(k) // 32)
else:
index = (k + self.num_carriers // 2 - 1) // 32
kk = 32 * (int(k - 1) // 32) + 1
values = self.__prn_kin__[self.mode - 1][index]
assert (k >= values[0] and k <= values[1])
assert (kk == values[2])
i = values[3]
n = values[4]
return [kk, i, n]
def prbs(self, length):
"""
PRBS generated with the polynomial p(x) = x^9 + x^5 + 1
and initial state 111111111
@param length number of bits in the sequence
"""
bits = [1] * 9
sequence = []
for i in range(0, length):
newbit = bits[8] ^ bits[4]
bits = [newbit] + bits[0:-1]
sequence.append(newbit)
return sequence
class receiver_parameters:
"""
@brief Parameters for the receiver, independent of the DAB standard
"""
# filter at input
filt_bw = (768 + 100) * 1e3
filt_tb = 50e3
# OFDM stuff
__cp_gap__ = [252, 63, 31, 124] # gap for ofdm_sampler to leave before the start of the next symbol
__symbols_for_ffs_estimation__ = [8, 8, 16, 8] # number of symbols to evaluate for fine frequency error estimation
__symbols_for_magnitude_equalization__ = [6, 6, 12,
6] # how many symbols should be used to estimate magnitude equalizer?
ffs_alpha = 0.5
# phase variance estimation
phase_var_estimate_alpha = 0.01
phase_var_estimate_downsample = 100 # 50 -> uses about 1% of the CPU time
# for USRP
usrp_ffc_retune_frequency = 5 # how often should the USRP be retuned at most?
usrp_ffc_min_deviation = 5 # how far off does the FFE have to be to retune the USRP?
usrp_ffc_adapt_factor = 0.5 # how much to adapt the correction?
def __init__(self, mode, sample_rate=2048000, softbits=False, input_fft_filter=True, autocorrect_sample_rate=False,
sample_rate_correction_factor=1, correct_ffe=True, equalize_magnitude=True, verbose=True, always_include_resample=False):
"""
Create new instance.
@param mode DAB mode (I-IV)
@param sample_rate sampling frequency
@param input_fft_filter whether to use an FFT filter at the input
@param autocorrect_sample_rate whether to correct the sample rate dynamically
@param sample_rate_correction_factor static correction factor for sample rate
@parem correct_ffe if False, only estimate fine frequency error - don't correct it
@param verbose be talkative
"""
if verbose:
print("--> creating RX parameter object")
assert (mode >= 1 and mode <= 4)
self.set_mode(mode)
self.sample_rate = sample_rate
self.softbits = softbits
self.input_fft_filter = input_fft_filter
self.autocorrect_sample_rate = autocorrect_sample_rate
self.sample_rate_correction_factor = sample_rate_correction_factor
self.correct_ffe = correct_ffe
self.equalize_magnitude = equalize_magnitude
self.verbose = verbose
self.always_include_resample = always_include_resample
def set_mode(self, mode):
self.mode = mode
self.cp_gap = self.__cp_gap__[mode - 1]
self.symbols_for_ffs_estimation = self.__symbols_for_ffs_estimation__[mode - 1]
self.symbols_for_magnitude_equalization = self.__symbols_for_magnitude_equalization__[mode - 1]
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