diff options
Diffstat (limited to 'gr-digital/python/ofdm_sync_ml.py')
| -rw-r--r-- | gr-digital/python/ofdm_sync_ml.py | 25 |
1 files changed, 15 insertions, 10 deletions
diff --git a/gr-digital/python/ofdm_sync_ml.py b/gr-digital/python/ofdm_sync_ml.py index f732fdf29a..885531f66a 100644 --- a/gr-digital/python/ofdm_sync_ml.py +++ b/gr-digital/python/ofdm_sync_ml.py @@ -28,6 +28,11 @@ try: except ImportError: import filter_swig as filter +try: + from gnuradio import blocks +except ImportError: + import blocks_swig as blocks + class ofdm_sync_ml(gr.hier_block2): def __init__(self, fft_length, cp_length, snr, kstime, logging): ''' Maximum Likelihood OFDM synchronizer: @@ -40,7 +45,7 @@ class ofdm_sync_ml(gr.hier_block2): gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature - self.input = gr.add_const_cc(0) + self.input = blocks.add_const_cc(0) SNR = 10.0**(snr/10.0) rho = SNR / (SNR + 1.0) @@ -59,7 +64,7 @@ class ofdm_sync_ml(gr.hier_block2): # magnitude squared blocks self.magsqrd1 = gr.complex_to_mag_squared() self.magsqrd2 = gr.complex_to_mag_squared() - self.adder = gr.add_ff() + self.adder = blocks.add_ff() moving_sum_taps = [rho/2 for i in range(cp_length)] self.moving_sum_filter = filter.fir_filter_fff(1,moving_sum_taps) @@ -72,8 +77,8 @@ class ofdm_sync_ml(gr.hier_block2): # Correlation from ML Sync - self.conjg = gr.conjugate_cc(); - self.mixer = gr.multiply_cc(); + self.conjg = blocks.conjugate_cc(); + self.mixer = blocks.multiply_cc(); movingsum2_taps = [1.0 for i in range(cp_length)] self.movingsum2 = filter.fir_filter_ccf(1,movingsum2_taps) @@ -87,12 +92,12 @@ class ofdm_sync_ml(gr.hier_block2): self.connect(self.movingsum2,self.angle) # ML Sync output arg, need to find maximum point of this - self.diff = gr.sub_ff() + self.diff = blocks.sub_ff() self.connect(self.c2mag,(self.diff,0)) self.connect(self.moving_sum_filter,(self.diff,1)) #ML measurements input to sampler block and detect - self.f2c = gr.float_to_complex() + self.f2c = blocks.float_to_complex() self.pk_detect = gr.peak_detector_fb(0.2, 0.25, 30, 0.0005) self.sample_and_hold = gr.sample_and_hold_ff() @@ -122,7 +127,7 @@ class ofdm_sync_ml(gr.hier_block2): kstime.reverse() self.kscorr = filter.fir_filter_ccc(1, kstime) self.corrmag = gr.complex_to_mag_squared() - self.div = gr.divide_ff() + self.div = blocks.divide_ff() # The output signature of the correlation has a few spikes because the rest of the # system uses the repeated preamble symbol. It needs to work that generically if @@ -131,9 +136,9 @@ class ofdm_sync_ml(gr.hier_block2): # identify the proper peak and remove other products in this cross-correlation self.threshold_factor = 0.1 self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0) - self.f2b = gr.float_to_char() - self.b2f = gr.char_to_float() - self.mul = gr.multiply_ff() + self.f2b = blocks.float_to_char() + self.b2f = blocks.char_to_float() + self.mul = blocks.multiply_ff() # Normalize the power of the corr output by the energy. This is not really needed # and could be removed for performance, but it makes for a cleaner signal. |