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Diffstat (limited to 'python/receiver/fcch_burst_tagger.py')
| -rw-r--r-- | python/receiver/fcch_burst_tagger.py | 130 |
1 files changed, 130 insertions, 0 deletions
diff --git a/python/receiver/fcch_burst_tagger.py b/python/receiver/fcch_burst_tagger.py new file mode 100644 index 0000000..56fead9 --- /dev/null +++ b/python/receiver/fcch_burst_tagger.py @@ -0,0 +1,130 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# +# Copyright 2014 Piotr Krysik pkrysik@elka.pw.edu.pl +# +# 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. +# + +from numpy import * +from pylab import * +from gnuradio import gr +import pmt +from gsm.chirpz import ZoomFFT + +class fcch_burst_tagger(gr.sync_block): + """ + docstring for block fcch_burst_tagger + """ + def __init__(self, OSR): + gr.sync_block.__init__(self, + name="fcch_burst_tagger", + in_sig=[complex64, float32], + out_sig=[complex64]) + + self.state=False + self.symbol_rate = 1625000/6 + self.OSR=OSR + self.samp_rate = self.symbol_rate*OSR + self.burst_size = int(156.25*self.OSR) + self.guard_period = int(round(8.25*self.OSR)) + self.block_size = self.burst_size+self.guard_period + self.processed_block_size = int(142*self.OSR) + self.set_history(self.block_size) + self.set_output_multiple(self.guard_period) + self.prev_offset=0 + + #parameters of zoomfft frequency estimator + f1 = self.symbol_rate/4*0.9 + f2 = self.symbol_rate/4*1.1 + m=5000*self.OSR + self.zoomfft = ZoomFFT(self.processed_block_size, f1, f2, m, Fs=self.samp_rate) + self.f_axis = linspace(f1,f2,m) + + def work(self, input_items, output_items): + in0=input_items[0] + output_items[0][:] = in0[self.history()-1:] + + threshold = input_items[1][self.history()-1:] + threshold_diff = diff(concatenate([[0],threshold])) + up_to_high_indexes = nonzero(threshold_diff>0)[0] + + up_to_high_idx=[] + + for up_to_high_idx in up_to_high_indexes: #look for "high" value at the trigger + if up_to_high_idx==0 and self.state==True: #if it's not transition from "low" to "high" + continue #then continue + self.state=True #if found - change state + + if self.state==True and up_to_high_idx and any(threshold_diff<0): #and look for transition from high to low + last_up_to_high_idx = up_to_high_idx + last_high_to_low_idx = nonzero(threshold_diff<0)[0][-1] + + if last_high_to_low_idx-last_up_to_high_idx>0: + coarse_idx = int(last_high_to_low_idx+self.history()-self.block_size) + inst_freq = angle(in0[coarse_idx:coarse_idx+self.block_size]*in0[coarse_idx-self.OSR:coarse_idx+self.block_size-self.OSR].conj())/(2*pi)*self.symbol_rate #instantaneus frequency estimate + precise_idx = self.find_best_position(inst_freq) +# measured_freq = mean(inst_freq[precise_idx:precise_idx+self.processed_block_size]) + expected_freq = self.symbol_rate/4 + + print "input_items:",len(in0) + print "coarse_idx",coarse_idx + print "coarse_idx+precise_idx",coarse_idx+precise_idx + + zoomed_spectrum = abs(self.zoomfft(in0[coarse_idx+precise_idx:coarse_idx+precise_idx+self.processed_block_size])) + measured_freq = self.f_axis[argmax(zoomed_spectrum)] + freq_offset = measured_freq - expected_freq + offset = self.nitems_written(0) + coarse_idx + precise_idx - self.guard_period + key = pmt.string_to_symbol("fcch") + value = pmt.from_double(freq_offset) + self.add_item_tag(0,offset, key, value) + self.state=False + +# Some additional plots and prints for debugging +# print "coarse_idx+precise_idx",coarse_idx+precise_idx +# print "offset-self.nitems_written(0):",offset-self.nitems_written(0) + print offset-self.prev_offset + self.prev_offset=offset + print "freq offset", freq_offset +# freq_offset = measured_freq - expected_freq +# plot(self.f_axis, zoomed_spectrum) +# show() +# plot(inst_freq[precise_idx:precise_idx+self.burst_size]) +# show() +# plot(unwrap(angle(in0[coarse_idx+precise_idx:coarse_idx+precise_idx+self.burst_size]))) +# show() +# + return len(output_items[0]) + + def find_best_position(self, inst_freq): + lowest_max_min_diff = 1e6 #1e6 - just some large value + start_pos = 0 + + for ii in xrange(0,int(2*self.guard_period)): + min_inst_freq = min(inst_freq[ii:self.processed_block_size+ii-1]); + max_inst_freq = max(inst_freq[ii:self.processed_block_size+ii-1]); + + if (lowest_max_min_diff > max_inst_freq - min_inst_freq): + lowest_max_min_diff = max_inst_freq - min_inst_freq; + start_pos = ii +# print 'start_pos',start_pos + +# plot(xrange(start_pos,start_pos+self.processed_block_size),inst_freq[start_pos:start_pos+self.processed_block_size],'r.') +# hold(True) +# plot(inst_freq) +# show() + + return start_pos |