diff options
Diffstat (limited to 'gnuradio-core')
| -rw-r--r-- | gnuradio-core/src/python/gnuradio/blks2impl/ofdm_sync_pnac.py | 74 |
1 files changed, 43 insertions, 31 deletions
diff --git a/gnuradio-core/src/python/gnuradio/blks2impl/ofdm_sync_pnac.py b/gnuradio-core/src/python/gnuradio/blks2impl/ofdm_sync_pnac.py index 89f70ed2b..10a125964 100644 --- a/gnuradio-core/src/python/gnuradio/blks2impl/ofdm_sync_pnac.py +++ b/gnuradio-core/src/python/gnuradio/blks2impl/ofdm_sync_pnac.py @@ -26,7 +26,25 @@ from gnuradio import gr class ofdm_sync_pnac(gr.hier_block2): def __init__(self, fft_length, cp_length, kstime, logging=False): - + """ + OFDM synchronization using PN Correlation and initial cross-correlation: + F. Tufvesson, O. Edfors, and M. Faulkner, "Time and Frequency Synchronization for OFDM using + PN-Sequency Preambles," IEEE Proc. VTC, 1999, pp. 2203-2207. + + This implementation is meant to be a more robust version of the Schmidl and Cox receiver design. + By correlating against the preamble and using that as the input to the time-delayed correlation, + this circuit produces a very clean timing signal at the end of the preamble. The timing is + more accurate and does not have the problem associated with determining the timing from the + plateau structure in the Schmidl and Cox. + + This implementation appears to require that the signal is received with a normalized power or signal + scalling factor to reduce ambiguities intorduced from partial correlation of the cyclic prefix and + the peak detection. A better peak detection block might fix this. + + Also, the cross-correlation falls apart as the frequency offset gets larger and completely fails + when an integer offset is introduced. Another thing to look at. + """ + gr.hier_block2.__init__(self, "ofdm_sync_pnac", gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature @@ -42,7 +60,6 @@ class ofdm_sync_pnac(gr.hier_block2): kstime = [k.conjugate() for k in kstime[0:fft_length//2]] kstime.reverse() self.crosscorr_filter = gr.fir_filter_ccc(1, kstime) - self.connect(self.crosscorr_filter, gr.file_sink(gr.sizeof_gr_complex, "crosscorr.dat")) # Create a delay line self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2) @@ -51,63 +68,58 @@ class ofdm_sync_pnac(gr.hier_block2): self.conjg = gr.conjugate_cc(); self.corr = gr.multiply_cc(); - # Create a moving sum filter for the corr output - moving_sum_taps = [1.0 for i in range(fft_length//2)] - self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps) - # Create a moving sum filter for the input - self.inputmag2 = gr.complex_to_mag_squared() - movingsum2_taps = [1.0 for i in range(fft_length//2)] - self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps) - self.square = gr.multiply_ff() - self.normalize = gr.divide_ff() + self.mag = gr.complex_to_mag_squared() + movingsum_taps = (fft_length//1)*[1.0,] + self.power = gr.fir_filter_fff(1,movingsum_taps) # Get magnitude (peaks) and angle (phase/freq error) self.c2mag = gr.complex_to_mag_squared() self.angle = gr.complex_to_arg() - + self.compare = gr.sub_ff() + self.sample_and_hold = gr.sample_and_hold_ff() #ML measurements input to sampler block and detect - self.sub1 = gr.add_const_ff(-1) - self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001) + self.threshold = gr.threshold_ff(0,0,0) # threshold detection might need to be tweaked + self.peaks = gr.float_to_char() self.connect(self, self.input) # Cross-correlate input signal with known preamble self.connect(self.input, self.crosscorr_filter) - # use the output of the cross-correlation as input to Schmidl&Cox + # use the output of the cross-correlation as input time-shifted correlation self.connect(self.crosscorr_filter, self.delay) self.connect(self.crosscorr_filter, (self.corr,0)) self.connect(self.delay, self.conjg) self.connect(self.conjg, (self.corr,1)) - self.connect(self.corr, self.moving_sum_filter) - self.connect(self.moving_sum_filter, self.c2mag) - self.connect(self.moving_sum_filter, self.angle) + self.connect(self.corr, self.c2mag) + self.connect(self.corr, self.angle) self.connect(self.angle, (self.sample_and_hold,0)) + + # Get the power of the input signal to compare against the correlation + self.connect(self.crosscorr_filter, self.mag, self.power) - # Get the power of the input signal to normalize the output of the correlation - self.connect(self.crosscorr_filter, self.inputmag2, self.inputmovingsum) - self.connect(self.inputmovingsum, (self.square,0)) - self.connect(self.inputmovingsum, (self.square,1)) - self.connect(self.square, (self.normalize,1)) - self.connect(self.c2mag, (self.normalize,0)) - - self.connect(self.normalize, self.sub1, self.pk_detect) - self.connect(self.pk_detect, (self.sample_and_hold,1)) + # Compare the power to the correlator output to determine timing peak + # When the peak occurs, it peaks above zero, so the thresholder detects this + self.connect(self.c2mag, (self.compare,0)) + self.connect(self.power, (self.compare,1)) + self.connect(self.compare, self.threshold) + self.connect(self.threshold, self.peaks, (self.sample_and_hold,1)) # Set output signals # Output 0: fine frequency correction value # Output 1: timing signal self.connect(self.sample_and_hold, (self,0)) - self.connect(self.pk_detect, (self,1)) + self.connect(self.peaks, (self,1)) if logging: + self.connect(self.compare, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-compare_f.dat")) self.connect(self.c2mag, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-theta_f.dat")) - self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-normalized_f.dat")) - self.connect(self.sub1, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-sub1_f.dat")) + self.connect(self.power, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-inputpower_f.dat")) self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-epsilon_f.dat")) - self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat")) + self.connect(self.threshold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-threshold_f.dat")) + self.connect(self.peaks, gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat")) self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-sample_and_hold_f.dat")) self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pnac-input_c.dat")) |