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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2021 Sara Cinzia Halter.
#
# This 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.
#
# This software 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 this software; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
import numpy as np
from numpy.fft import fft,ifft,fftshift
from gnuradio import gr
from fadingui.logger import get_logger
log = get_logger("multipath_fading")
class multipath_fading(gr.sync_block):
"""
docstring for block multipath_fading
"""
def __init__(self, amplitudes=[], delays=[], los=True): # only default arguments here
"""arguments to this function show up as parameters in GRC"""
gr.sync_block.__init__(
self,
name='Embedded Python Block', # will show up in GRC
in_sig=[np.complex64],
out_sig=[np.complex64]
)
# if an attribute with the same name as a parameter is found,
# a callback is registered (properties work, too).
self.amplitudes = amplitudes
self.delays = delays
self.temp = [0]
# if los:
# self.amplitudes.append(1)
# self.delays.append(0)
self.los= 1
#self.fir =
def work(self, input_items, output_items):
"""example: multiply with constant"""
inp = input_items[0]
oup = output_items[0]
if len(self.amplitudes) != len(self.delays):
raise Exception("Amplitudes and Delay length dont match")
# raise Exception("Delay length can't be one")
#if np.min(self.delays)<=1:
# raise Exception("Delay length can't be one")
max_len = np.max(self.delays)
sum_x = np.zeros(max_len)
for(a,d) in zip(self.amplitudes,self.delays):
# if d-1 <= 0:
# x = np.concatenate([[a], np.zeros(max_len-1)])
# else:
x = np.concatenate([np.zeros(d-1), [a], np.zeros(max_len-d)])
sum_x += x
sum_x[0] = self.los
log.debug(sum_x)
#H_int = fft(sum_x)
#h = ifft(H_int)
#h[0]=1
y = np.convolve(inp, sum_x)
y+=np.concatenate([self.temp,np.zeros(len(y)-len(self.temp))])
oup[:] = y[:len(inp)]
self.temp = y[len(inp):]
return len(oup)
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