Ejemplo n.º 1
0
  def __init__(self, vlen):
    gr.hier_block2.__init__(self, "coarse_frequency_offset_estimation",
        gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
        gr.io_signature (1,1,gr.sizeof_float))

    ## Preamble Extraction
    sampler = vector_sampler(gr.sizeof_gr_complex,vlen)
    self.connect(self,sampler)
    self.connect((self,1),(sampler,1))

    ## Split block into two parts
    splitter = gr.vector_to_streams(gr.sizeof_gr_complex*vlen/2,2)
    self.connect(sampler,splitter)

    ## Multiply 2nd sub-part with conjugate of 1st sub-part
    conj_mult = gr.multiply_conjugate_cc(vlen/2)
    self.connect((splitter,1),(conj_mult,0))
    self.connect((splitter,0),(conj_mult,1))

    ## Sum of Products
    psum = vector_sum_vcc(vlen/2)
    self.connect((conj_mult,0),psum)

    ## Complex to Angle
    angle = complex_to_arg()
    self.connect(psum,angle)

    ## Normalize
    norm = gr.multiply_const_ff(1.0/math.pi)
    self.connect(angle,norm)

    ## Setup Output Connections
    self.connect(norm,self)
Ejemplo n.º 2
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    def __init__(self, vlen):
        gr.hier_block2.__init__(
            self, "coarse_frequency_offset_estimation",
            gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
            gr.io_signature(1, 1, gr.sizeof_float))

        ## Preamble Extraction
        sampler = vector_sampler(gr.sizeof_gr_complex, vlen)
        self.connect(self, sampler)
        self.connect((self, 1), (sampler, 1))

        ## Split block into two parts
        splitter = gr.vector_to_streams(gr.sizeof_gr_complex * vlen / 2, 2)
        self.connect(sampler, splitter)

        ## Multiply 2nd sub-part with conjugate of 1st sub-part
        conj_mult = gr.multiply_conjugate_cc(vlen / 2)
        self.connect((splitter, 1), (conj_mult, 0))
        self.connect((splitter, 0), (conj_mult, 1))

        ## Sum of Products
        psum = vector_sum_vcc(vlen / 2)
        self.connect((conj_mult, 0), psum)

        ## Complex to Angle
        angle = complex_to_arg()
        self.connect(psum, angle)

        ## Normalize
        norm = gr.multiply_const_ff(1.0 / math.pi)
        self.connect(angle, norm)

        ## Setup Output Connections
        self.connect(norm, self)
Ejemplo n.º 3
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    def test_vff_001(self):
        N = 10

        data = [2.0] * N

        src = gr.vector_source_c(data)
        s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
        dst = gr.vector_sink_c()

        uut = ofdm.vector_sum_vcc(N)

        self.fg.connect(src, s2v, uut, dst)

        self.fg.run()

        self.assertEqual([sum(data)], list(dst.data()))
Ejemplo n.º 4
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    def test_vcc_002(self):
        N = 10

        data = [1.0 + 2.0j] * (N * 2)

        src = gr.vector_source_c(data)
        s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
        dst = gr.vector_sink_c()

        uut = ofdm.vector_sum_vcc(N)

        self.fg.connect(src, s2v, uut, dst)

        self.fg.run()

        self.assertEqual([sum(data[0:N]), sum(data[N:2 * N])],
                         list(dst.data()))
Ejemplo n.º 5
0
  def __init__( self, options, log = False ):
    
    ## Read configuration
    config = station_configuration()
    
    fft_length    = config.fft_length
    cp_length     = config.cp_length
    block_header  = config.training_data
    data_subc     = config.data_subcarriers
    virtual_subc  = config.virtual_subcarriers
    total_subc    = config.subcarriers
    block_length  = config.block_length
    frame_length  = config.frame_length
    dc_null       = config.dc_null
    
    L             = block_header.mm_periodic_parts
    
    
    ## Set Input/Output signature
    gr.hier_block2.__init__( self, 
        "ofdm_inner_receiver",
        gr.io_signature(
            1, 1,
            gr.sizeof_gr_complex ),
        gr.io_signaturev(
            4, 4,
            [gr.sizeof_gr_complex * total_subc,    # OFDM blocks
            gr.sizeof_char,                       # Frame start
            gr.sizeof_float * total_subc,
            gr.sizeof_float] ) )      # Normalized |CTF|^2 
    
    
    ## Input and output ports
    self.input = rx_input = self
    
    out_ofdm_blocks = ( self, 0 )
    out_frame_start = ( self, 1 )
    out_disp_ctf    = ( self, 2 )
    out_disp_cfo    = ( self, 3 )
    
    
    ## pre-FFT processing
    if options.ideal is False and options.ideal2 is False:
        if options.old_receiver is False:
            ## Compute autocorrelations for S&C preamble
            ## and cyclic prefix
            
            self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
            self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
            
            self.connect( rx_input, sc_metric )
            self.connect( rx_input, gi_metric )    
            
            ## Sync. Output contains OFDM blocks
            sync = ofdm.time_sync( fft_length, cp_length )
            self.connect( rx_input, ( sync, 0 ) )
            self.connect( sc_metric, ( sync, 1 ) )
            self.connect( gi_metric, ( sync, 2 ) )
            ofdm_blocks = ( sync, 0 )
            frame_start = ( sync, 1 )
            #log_to_file( self, ( sync, 1 ), "data/peak_detector.char" )
        else:
    
            #Testing old/new metric
            self.tm = schmidl.recursive_timing_metric(fft_length)
            self.connect( self.input, self.tm)
            #log_to_file( self, self.tm, "data/rec_sc_metric_ofdm.float" )
            
            timingmetric_shift = -2#int(-cp_length/4)# 0#-2 #int(-cp_length * 0.8)
            tmfilter = filter.fft_filter_fff(1, [1./cp_length]*cp_length)
            self.connect( self.tm, tmfilter )
            self.tm = tmfilter
        
            
            
            self._pd_thres = 0.3
            self._pd_lookahead = fft_length / 2 # empirically chosen
            peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
            self.connect(self.tm, peak_detector)
            #log_to_file( self, peak_detector, "data/rec_peak_detector.char" )
            
            
            frame_start = [0]*frame_length
            frame_start[0] = 1
            frame_start = self.frame_trigger_old = blocks.vector_source_b(frame_start,True)
            
            
            delayed_timesync = blocks.delay(gr.sizeof_char,
                                        (frame_length-1)*block_length + timingmetric_shift)
            self.connect( peak_detector, delayed_timesync )
            
            self.block_sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,block_length*frame_length)
            self.discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
            
            self.connect(self.input,self.block_sampler)
            self.connect(delayed_timesync,(self.block_sampler,1))
        
            # TODO: dynamic solution
            vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length,
                                                    frame_length)
            self.connect(self.block_sampler,vt2s,self.discard_cp)
            #terminate_stream(self,ofdm_blocks)
            ofdm_blocks = self.discard_cp
#     else:
#       serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
#       discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#       ofdm_blocks = discard_cp
#       self.connect( rx_input, serial_to_parallel, discard_cp )
#       frame_start = [0]*frame_length
#       frame_start[0] = 1
#       frame_start = blocks.vector_source_b(frame_start,True)
#       
#       print "Disabled time synchronization stage"
    
    ## Compute autocorrelations for S&C preamble
    ## and cyclic prefix
    
    #log_to_file( self, sc_metric, "data/sc_metric_ofdm.float" )
    #log_to_file(self, frame_start, "data/frame_start.compl")
    
#    log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
    
    if options.disable_time_sync or options.ideal or options.ideal2:
      if options.ideal is False and options.ideal2 is False:
          terminate_stream(self, ofdm_blocks)
          terminate_stream(self, frame_start)
      
      serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
      discard_cp = ofdm.vector_mask_dc_null(block_length,cp_length,fft_length,dc_null, [])
      ofdm_blocks = discard_cp
      self.connect( rx_input, serial_to_parallel, discard_cp )
      
      frame_start = [0]*frame_length
      frame_start[0] = 1
      frame_start = blocks.vector_source_b(frame_start,True)
      
      print "Disabled time synchronization stage"
    
    print"\t\t\t\t\tframe_length = ",frame_length
    
    
    
    
    if options.ideal is False and options.ideal2 is False:
        ## Extract preamble, feed to Morelli & Mengali frequency offset estimator
        assert( block_header.mm_preamble_pos == 0 )
        morelli_foe = ofdm.mm_frequency_estimator( fft_length, L,1,0 )
        sampler_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length,
                                            1 )
        self.connect( ofdm_blocks, ( sampler_preamble, 0 ) )
        self.connect( frame_start, ( sampler_preamble, 1 ) )
        self.connect( sampler_preamble, morelli_foe )
        freq_offset = morelli_foe
    
    
        ## Adaptive LMS FIR filtering of frequency offset
        lms_fir = ofdm.lms_fir_ff( 20, 1e-3 ) # TODO: verify parameter choice
        self.connect( freq_offset, lms_fir )
        freq_offset = lms_fir
    
        #self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
        self.connect(lms_fir, blocks.keep_one_in_n(gr.sizeof_float,20) ,out_disp_cfo)
    else:
        self.connect(blocks.vector_source_f ([1]) ,out_disp_cfo)
    
        #log_to_file(self, lms_fir, "data/lms_fir.float")
    
    if options.disable_freq_sync or options.ideal or options.ideal2:
      if options.ideal is False and options.ideal2 is False:
          terminate_stream(self, freq_offset)
          freq_offset = blocks.vector_source_f([0.0],True)
      print "Disabled frequency synchronization stage"
    
    if options.ideal is False and options.ideal2 is False:
        ## Correct frequency shift, feed-forward structure
        frequency_shift = ofdm.frequency_shift_vcc( fft_length, -1.0/fft_length,
                                                    cp_length )
        self.connect( ofdm_blocks, ( frequency_shift, 0 ) )
        self.connect( freq_offset, ( frequency_shift, 1 ) )
        self.connect( frame_start, ( frequency_shift, 2 ) )
        ofdm_blocks = frequency_shift
    
    
    
    
    ## FFT
    fft = fft_blocks.fft_vcc( fft_length, True, [], True )
    self.connect( ofdm_blocks, fft )
    ofdm_blocks = fft
    #log_to_file( self, fft, "data/compen.float" )
    
    
    
    ## Remove virtual subcarriers
    if fft_length > data_subc:
      subcarrier_mask = ofdm.vector_mask_dc_null( fft_length, virtual_subc/2,
                                           total_subc, dc_null, [] )
      self.connect( ofdm_blocks, subcarrier_mask )
      ofdm_blocks = subcarrier_mask
      #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
       ## Least Squares estimator for channel transfer function (CTF)
    
    
      if options.logcir:
          log_to_file( self, ofdm_blocks, "data/OFDM_Blocks.compl" )
          
          inv_preamble_fd = numpy.array( block_header.pilotsym_fd[ 
            block_header.channel_estimation_pilot[0] ] )
          inv_preamble_fd = numpy.concatenate([inv_preamble_fd[:total_subc/2],inv_preamble_fd[total_subc/2+dc_null:]])
          #print "Channel estimation pilot: ", inv_preamble_fd
          inv_preamble_fd = 1. / inv_preamble_fd
          LS_channel_estimator0 = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
          self.connect( ofdm_blocks, LS_channel_estimator0, gr.null_sink(gr.sizeof_gr_complex*total_subc))
          log_to_file( self, LS_channel_estimator0, "data/OFDM_Blocks_eq.compl" )
          
    ## post-FFT processing
      
    
    
    ## extract channel estimation preamble from frame
    if options.ideal is False and options.ideal2 is False:
        chest_pre_trigger = blocks.delay( gr.sizeof_char, 1)
        sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1)
        self.connect( frame_start,       chest_pre_trigger )
        self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
        self.connect( ofdm_blocks,       ( sampled_chest_preamble, 0 ) )
    

    
        ## Least Squares estimator for channel transfer function (CTF)
        inv_preamble_fd = numpy.array( block_header.pilotsym_fd[ 
                                                            block_header.channel_estimation_pilot[0] ] )
        inv_preamble_fd = numpy.concatenate([inv_preamble_fd[:total_subc/2],inv_preamble_fd[total_subc/2+dc_null:]])    
        #print "Channel estimation pilot: ", inv_preamble_fd
        inv_preamble_fd = 1. / inv_preamble_fd
    
        LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
        self.connect( sampled_chest_preamble, LS_channel_estimator )
        estimated_CTF = LS_channel_estimator
    
        if options.logcir:
             log_to_file( self, sampled_chest_preamble, "data/PREAM.compl" )
     
    
        if not options.disable_ctf_enhancer:
      
      
            if options.logcir:
                ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
                self.connect( estimated_CTF, ifft1,gr.null_sink(gr.sizeof_gr_complex*total_subc))
                summ1 = ofdm.vector_sum_vcc(total_subc)
                c2m =gr.complex_to_mag(total_subc)
                self.connect( estimated_CTF,summ1 ,gr.null_sink(gr.sizeof_gr_complex))
                self.connect( estimated_CTF, c2m,gr.null_sink(gr.sizeof_float*total_subc))
                log_to_file( self, ifft1, "data/CIR1.compl" )
                log_to_file( self, summ1, "data/CTFsumm1.compl" )
                log_to_file( self, estimated_CTF, "data/CTF1.compl" )
                log_to_file( self, c2m, "data/CTFmag1.float" )
        
            ## MSE enhancer
            ctf_mse_enhancer = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
            self.connect( estimated_CTF, ctf_mse_enhancer )
#      log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
      #ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
      #null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
      #ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
      #ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
                                          # total_subc, [] )
      #self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
        
            estimated_CTF = ctf_mse_enhancer 
            print "Disabled CTF MSE enhancer"

        if options.logcir:
             ifft2 = fft_blocks.fft_vcc(total_subc,False,[],True)
             self.connect( estimated_CTF, ifft2,gr.null_sink(gr.sizeof_gr_complex*total_subc))
             summ2 = ofdm.vector_sum_vcc(total_subc)
             c2m2 =gr.complex_to_mag(total_subc)
             self.connect( estimated_CTF,summ2 ,gr.null_sink(gr.sizeof_gr_complex))
             self.connect( estimated_CTF, c2m2,gr.null_sink(gr.sizeof_float*total_subc))
             log_to_file( self, ifft2, "data/CIR2.compl" )
             log_to_file( self, summ2, "data/CTFsumm2.compl" )
             log_to_file( self, estimated_CTF, "data/CTF2.compl" )
             log_to_file( self, c2m2, "data/CTFmag2.float" )
         
    ## Postprocess the CTF estimate
    ## CTF -> inverse CTF (for equalizer)
    ## CTF -> norm |.|^2 (for CTF display)
        ctf_postprocess = ofdm.postprocess_CTF_estimate( total_subc )
        self.connect( estimated_CTF, ctf_postprocess )
        inv_estimated_CTF = ( ctf_postprocess, 0 )
        disp_CTF = ( ctf_postprocess, 1 )
    
#     if options.disable_equalization or options.ideal:
#       terminate_stream(self, inv_estimated_CTF)
#       inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
#       inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
#       self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
#       #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
#       inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
#       self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
#       print "Disabled equalization stage"
    '''
    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset

    nondata_blocks = []
    for i in range(config.frame_length):
      if i in config.training_data.pilotsym_pos:
        nondata_blocks.append(i)
        
    print"\t\t\t\t\tnondata_blocks=",nondata_blocks
    pilot_subc = block_header.pilot_tones
    pilot_subcarriers = block_header.pilot_subc_sym
    print "PILOT SUBCARRIERS: ", pilot_subcarriers
        
    phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
                                               nondata_blocks, pilot_subcarriers,0 )
    self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
    self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
    self.connect( frame_start, ( phase_tracking, 2 ) ) ##
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer
      
    
    if options.disable_phase_tracking or options.ideal:
      terminate_stream(self, phase_tracking)
      print "Disabled phase tracking stage"
    else:
      ofdm_blocks = phase_tracking
    '''
    ## Channel Equalizer
    if options.disable_equalization or options.ideal or options.ideal2:
        print "Disabled equalization stage"
        if options.ideal is False and options.ideal2 is False:
            terminate_stream(self, inv_estimated_CTF)
    else:
        equalizer = ofdm.channel_equalizer( total_subc )
        self.connect( ofdm_blocks,       ( equalizer, 0 ) )
        self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
        self.connect( frame_start,       ( equalizer, 2 ) )
        ofdm_blocks = equalizer
    #log_to_file(self, equalizer,"data/equalizer_siso.compl")
    
    
    #log_to_file(self, ofdm_blocks, "data/equalizer.compl")

    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset
    if options.ideal is False and options.ideal2 is False:
        nondata_blocks = []
        for i in range(config.frame_length):
          if i in config.training_data.pilotsym_pos:
            nondata_blocks.append(i)
            
        print"\t\t\t\t\tnondata_blocks=",nondata_blocks
        pilot_subc = block_header.pilot_tones
        pilot_subcarriers = block_header.pilot_subc_sym
        print "PILOT SUBCARRIERS: ", pilot_subcarriers
         
        phase_tracking2 = ofdm.lms_phase_tracking_dc_null( total_subc, pilot_subc,
                                                   nondata_blocks, pilot_subcarriers, dc_null  )
        self.connect( ofdm_blocks, ( phase_tracking2, 0 ) )
        self.connect( frame_start, ( phase_tracking2, 1 ) ) ##
        
    if options.disable_phase_tracking or options.ideal or options.ideal2:
        if options.ideal is False and options.ideal2 is False:
            terminate_stream(self, phase_tracking2)
        print "Disabled phase tracking stage"
    else:
        ofdm_blocks = phase_tracking2
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer


    ## Output connections

    self.connect( ofdm_blocks, out_ofdm_blocks )
    self.connect( frame_start, out_frame_start )
    if options.ideal is False and options.ideal2 is False:
        self.connect( disp_CTF, out_disp_ctf )
    else:
        self.connect( blocks.vector_source_f([1.0]*total_subc),blocks.stream_to_vector(gr.sizeof_float,total_subc), out_disp_ctf )

    if log:
      log_to_file( self, sc_metric, "data/sc_metric.float" )
      log_to_file( self, gi_metric, "data/gi_metric.float" )
      log_to_file( self, morelli_foe, "data/morelli_foe.float" )
      log_to_file( self, lms_fir, "data/lms_fir.float" )
      log_to_file( self, sampler_preamble, "data/preamble.compl" )
      log_to_file( self, sync, "data/sync.compl" )
      log_to_file( self, frequency_shift, "data/frequency_shift.compl" )
      log_to_file( self, fft, "data/fft.compl")
      log_to_file( self, fft, "data/fft.float", mag=True )
      
      if vars().has_key( 'subcarrier_mask' ):
        log_to_file( self, subcarrier_mask, "data/subcarrier_mask.compl" )
      
      log_to_file( self, ofdm_blocks, "data/ofdm_blocks_out.compl" )
      log_to_file( self, frame_start, "data/frame_start.float", 
                   char_to_float=True )
      
      log_to_file( self, sampled_chest_preamble, 
                   "data/sampled_chest_preamble.compl" )
      log_to_file( self, LS_channel_estimator, 
                   "data/ls_channel_estimator.compl" )
      log_to_file( self, LS_channel_estimator, 
                   "data/ls_channel_estimator.float", mag=True )
      
      if "ctf_mse_enhancer" in locals(): 
        log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.compl" )
        log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.float", 
                     mag=True )
      
      log_to_file( self, (ctf_postprocess,0), "data/inc_estimated_ctf.compl" )
      log_to_file( self, (ctf_postprocess,1), "data/disp_ctf.float" )
      
      log_to_file( self, equalizer, "data/equalizer.compl" )
      log_to_file( self, equalizer, "data/equalizer.float", mag=True )
      
      log_to_file( self, phase_tracking, "data/phase_tracking.compl" )
Ejemplo n.º 6
0
  def __init__(self, vlen):
    gr.hier_block2.__init__(self, "snr_estimator",
        gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
        gr.io_signature (1,1,gr.sizeof_float))
    
    data_in = (self,0)
    trig_in = (self,1)
    snr_out = (self,0)

    ## Preamble Extraction
    sampler = vector_sampler(gr.sizeof_gr_complex,vlen)
    self.connect(data_in,sampler)
    self.connect(trig_in,(sampler,1))
    
    ## Algorithm implementation
    estim = sc_snr_estimator(vlen)
    self.connect(sampler,estim)
    self.connect(estim,snr_out)
    
    return 
  
  
  

    ## Split block into two parts
    splitter = gr.vector_to_streams(gr.sizeof_gr_complex*vlen/2,2)
    self.connect(sampler,splitter)

    ## Conjugate first half block
    conj = gr.conjugate_cc(vlen/2)
    self.connect(splitter,conj)

    ## Vector multiplication of both half blocks
    vmult = gr.multiply_vcc(vlen/2)
    self.connect(conj,vmult)
    self.connect((splitter,1),(vmult,1))

    ## Sum of Products
    psum = vector_sum_vcc(vlen/2)
    self.connect(vmult,psum)

    ## Magnitude of P(d)
    p_mag = gr.complex_to_mag()
    self.connect(psum,p_mag)

    ## Squared Magnitude of block
    r_magsqrd = gr.complex_to_mag_squared(vlen)
    self.connect(sampler,r_magsqrd)

    ## Sum of squared second half block
    r_sum = vector_sum_vff(vlen)
    self.connect(r_magsqrd,r_sum)

    ## Square Root of Metric
    m_sqrt = gr.divide_ff()
    self.connect(p_mag,(m_sqrt,0))
    self.connect(r_sum,gr.multiply_const_ff(0.5),(m_sqrt,1))

    ## Denominator of SNR estimate
    denom = gr.add_const_ff(1)
    neg_m_sqrt = gr.multiply_const_ff(-1.0)
    self.connect(m_sqrt,limit_vff(1,1-2e-5,-1000),neg_m_sqrt,denom)

    ## SNR estimate
    snr_est = gr.divide_ff()
    self.connect(m_sqrt,(snr_est,0))
    self.connect(denom,(snr_est,1))

    ## Setup Output Connections
    self.connect(snr_est,self)
Ejemplo n.º 7
0
    def __init__(self, options, log=False):

        ## Read configuration
        config = station_configuration()

        fft_length = config.fft_length
        cp_length = config.cp_length
        block_header = config.training_data
        data_subc = config.data_subcarriers
        virtual_subc = config.virtual_subcarriers
        total_subc = config.subcarriers
        block_length = config.block_length
        frame_length = config.frame_length
        dc_null = config.dc_null

        L = block_header.mm_periodic_parts

        ## Set Input/Output signature
        gr.hier_block2.__init__(
            self,
            "ofdm_inner_receiver",
            gr.io_signature(1, 1, gr.sizeof_gr_complex),
            gr.io_signaturev(
                4,
                4,
                [
                    gr.sizeof_gr_complex * total_subc,  # OFDM blocks
                    gr.sizeof_char,  # Frame start
                    gr.sizeof_float * total_subc,
                    gr.sizeof_float
                ]))  # Normalized |CTF|^2

        ## Input and output ports
        self.input = rx_input = self

        out_ofdm_blocks = (self, 0)
        out_frame_start = (self, 1)
        out_disp_ctf = (self, 2)
        out_disp_cfo = (self, 3)

        ## pre-FFT processing
        if options.ideal is False and options.ideal2 is False:
            if options.old_receiver is False:
                ## Compute autocorrelations for S&C preamble
                ## and cyclic prefix

                self._sc_metric = sc_metric = autocorrelator(
                    fft_length / 2, fft_length / 2)
                self._gi_metric = gi_metric = autocorrelator(
                    fft_length, cp_length)

                self.connect(rx_input, sc_metric)
                self.connect(rx_input, gi_metric)

                ## Sync. Output contains OFDM blocks
                sync = ofdm.time_sync(fft_length, cp_length)
                self.connect(rx_input, (sync, 0))
                self.connect(sc_metric, (sync, 1))
                self.connect(gi_metric, (sync, 2))
                ofdm_blocks = (sync, 0)
                frame_start = (sync, 1)
                #log_to_file( self, ( sync, 1 ), "data/peak_detector.char" )
            else:

                #Testing old/new metric
                self.tm = schmidl.recursive_timing_metric(fft_length)
                self.connect(self.input, self.tm)
                #log_to_file( self, self.tm, "data/rec_sc_metric_ofdm.float" )

                timingmetric_shift = -2  #int(-cp_length/4)# 0#-2 #int(-cp_length * 0.8)
                tmfilter = filter.fft_filter_fff(1,
                                                 [1. / cp_length] * cp_length)
                self.connect(self.tm, tmfilter)
                self.tm = tmfilter

                self._pd_thres = 0.3
                self._pd_lookahead = fft_length / 2  # empirically chosen
                peak_detector = ofdm.peak_detector_02_fb(
                    self._pd_lookahead, self._pd_thres)
                self.connect(self.tm, peak_detector)
                #log_to_file( self, peak_detector, "data/rec_peak_detector.char" )

                frame_start = [0] * frame_length
                frame_start[0] = 1
                frame_start = self.frame_trigger_old = blocks.vector_source_b(
                    frame_start, True)

                delayed_timesync = blocks.delay(
                    gr.sizeof_char,
                    (frame_length - 1) * block_length + timingmetric_shift)
                self.connect(peak_detector, delayed_timesync)

                self.block_sampler = ofdm.vector_sampler(
                    gr.sizeof_gr_complex, block_length * frame_length)
                self.discard_cp = ofdm.vector_mask(block_length, cp_length,
                                                   fft_length, [])

                self.connect(self.input, self.block_sampler)
                self.connect(delayed_timesync, (self.block_sampler, 1))

                # TODO: dynamic solution
                vt2s = blocks.vector_to_stream(
                    gr.sizeof_gr_complex * block_length, frame_length)
                self.connect(self.block_sampler, vt2s, self.discard_cp)
                #terminate_stream(self,ofdm_blocks)
                ofdm_blocks = self.discard_cp
#     else:
#       serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
#       discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#       ofdm_blocks = discard_cp
#       self.connect( rx_input, serial_to_parallel, discard_cp )
#       frame_start = [0]*frame_length
#       frame_start[0] = 1
#       frame_start = blocks.vector_source_b(frame_start,True)
#
#       print "Disabled time synchronization stage"

## Compute autocorrelations for S&C preamble
## and cyclic prefix

#log_to_file( self, sc_metric, "data/sc_metric_ofdm.float" )
#log_to_file(self, frame_start, "data/frame_start.compl")

#    log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")

        if options.disable_time_sync or options.ideal or options.ideal2:
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, ofdm_blocks)
                terminate_stream(self, frame_start)

            serial_to_parallel = blocks.stream_to_vector(
                gr.sizeof_gr_complex, block_length)
            discard_cp = ofdm.vector_mask_dc_null(block_length, cp_length,
                                                  fft_length, dc_null, [])
            ofdm_blocks = discard_cp
            self.connect(rx_input, serial_to_parallel, discard_cp)

            frame_start = [0] * frame_length
            frame_start[0] = 1
            frame_start = blocks.vector_source_b(frame_start, True)

            print "Disabled time synchronization stage"

        print "\t\t\t\t\tframe_length = ", frame_length

        if options.ideal is False and options.ideal2 is False:
            ## Extract preamble, feed to Morelli & Mengali frequency offset estimator
            assert (block_header.mm_preamble_pos == 0)
            morelli_foe = ofdm.mm_frequency_estimator(fft_length, L, 1, 0)
            sampler_preamble = ofdm.vector_sampler(
                gr.sizeof_gr_complex * fft_length, 1)
            self.connect(ofdm_blocks, (sampler_preamble, 0))
            self.connect(frame_start, (sampler_preamble, 1))
            self.connect(sampler_preamble, morelli_foe)
            freq_offset = morelli_foe

            ## Adaptive LMS FIR filtering of frequency offset
            lms_fir = ofdm.lms_fir_ff(20,
                                      1e-3)  # TODO: verify parameter choice
            self.connect(freq_offset, lms_fir)
            freq_offset = lms_fir

            #self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
            self.connect(lms_fir, blocks.keep_one_in_n(gr.sizeof_float, 20),
                         out_disp_cfo)
        else:
            self.connect(blocks.vector_source_f([1]), out_disp_cfo)

            #log_to_file(self, lms_fir, "data/lms_fir.float")

        if options.disable_freq_sync or options.ideal or options.ideal2:
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, freq_offset)
                freq_offset = blocks.vector_source_f([0.0], True)
            print "Disabled frequency synchronization stage"

        if options.ideal is False and options.ideal2 is False:
            ## Correct frequency shift, feed-forward structure
            frequency_shift = ofdm.frequency_shift_vcc(fft_length,
                                                       -1.0 / fft_length,
                                                       cp_length)
            self.connect(ofdm_blocks, (frequency_shift, 0))
            self.connect(freq_offset, (frequency_shift, 1))
            self.connect(frame_start, (frequency_shift, 2))
            ofdm_blocks = frequency_shift

        ## FFT
        fft = fft_blocks.fft_vcc(fft_length, True, [], True)
        self.connect(ofdm_blocks, fft)
        ofdm_blocks = fft
        #log_to_file( self, fft, "data/compen.float" )

        ## Remove virtual subcarriers
        if fft_length > data_subc:
            subcarrier_mask = ofdm.vector_mask_dc_null(fft_length,
                                                       virtual_subc / 2,
                                                       total_subc, dc_null, [])
            self.connect(ofdm_blocks, subcarrier_mask)
            ofdm_blocks = subcarrier_mask
            #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
            ## Least Squares estimator for channel transfer function (CTF)

            if options.logcir:
                log_to_file(self, ofdm_blocks, "data/OFDM_Blocks.compl")

                inv_preamble_fd = numpy.array(block_header.pilotsym_fd[
                    block_header.channel_estimation_pilot[0]])
                inv_preamble_fd = numpy.concatenate([
                    inv_preamble_fd[:total_subc / 2],
                    inv_preamble_fd[total_subc / 2 + dc_null:]
                ])
                #print "Channel estimation pilot: ", inv_preamble_fd
                inv_preamble_fd = 1. / inv_preamble_fd
                LS_channel_estimator0 = ofdm.multiply_const_vcc(
                    list(inv_preamble_fd))
                self.connect(ofdm_blocks, LS_channel_estimator0,
                             gr.null_sink(gr.sizeof_gr_complex * total_subc))
                log_to_file(self, LS_channel_estimator0,
                            "data/OFDM_Blocks_eq.compl")

        ## post-FFT processing

        ## extract channel estimation preamble from frame
        if options.ideal is False and options.ideal2 is False:
            chest_pre_trigger = blocks.delay(gr.sizeof_char, 1)
            sampled_chest_preamble = ofdm.vector_sampler(
                gr.sizeof_gr_complex * total_subc, 1)
            self.connect(frame_start, chest_pre_trigger)
            self.connect(chest_pre_trigger, (sampled_chest_preamble, 1))
            self.connect(ofdm_blocks, (sampled_chest_preamble, 0))

            ## Least Squares estimator for channel transfer function (CTF)
            inv_preamble_fd = numpy.array(block_header.pilotsym_fd[
                block_header.channel_estimation_pilot[0]])
            inv_preamble_fd = numpy.concatenate([
                inv_preamble_fd[:total_subc / 2],
                inv_preamble_fd[total_subc / 2 + dc_null:]
            ])
            #print "Channel estimation pilot: ", inv_preamble_fd
            inv_preamble_fd = 1. / inv_preamble_fd

            LS_channel_estimator = ofdm.multiply_const_vcc(
                list(inv_preamble_fd))
            self.connect(sampled_chest_preamble, LS_channel_estimator)
            estimated_CTF = LS_channel_estimator

            if options.logcir:
                log_to_file(self, sampled_chest_preamble, "data/PREAM.compl")

            if not options.disable_ctf_enhancer:

                if options.logcir:
                    ifft1 = fft_blocks.fft_vcc(total_subc, False, [], True)
                    self.connect(
                        estimated_CTF, ifft1,
                        gr.null_sink(gr.sizeof_gr_complex * total_subc))
                    summ1 = ofdm.vector_sum_vcc(total_subc)
                    c2m = gr.complex_to_mag(total_subc)
                    self.connect(estimated_CTF, summ1,
                                 gr.null_sink(gr.sizeof_gr_complex))
                    self.connect(estimated_CTF, c2m,
                                 gr.null_sink(gr.sizeof_float * total_subc))
                    log_to_file(self, ifft1, "data/CIR1.compl")
                    log_to_file(self, summ1, "data/CTFsumm1.compl")
                    log_to_file(self, estimated_CTF, "data/CTF1.compl")
                    log_to_file(self, c2m, "data/CTFmag1.float")

                ## MSE enhancer
                ctf_mse_enhancer = ofdm.CTF_MSE_enhancer(
                    total_subc, cp_length + cp_length)
                self.connect(estimated_CTF, ctf_mse_enhancer)
                #      log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
                #ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
                #null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
                #ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
                #ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
                # total_subc, [] )
                #self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )

                estimated_CTF = ctf_mse_enhancer
                print "Disabled CTF MSE enhancer"

            if options.logcir:
                ifft2 = fft_blocks.fft_vcc(total_subc, False, [], True)
                self.connect(estimated_CTF, ifft2,
                             gr.null_sink(gr.sizeof_gr_complex * total_subc))
                summ2 = ofdm.vector_sum_vcc(total_subc)
                c2m2 = gr.complex_to_mag(total_subc)
                self.connect(estimated_CTF, summ2,
                             gr.null_sink(gr.sizeof_gr_complex))
                self.connect(estimated_CTF, c2m2,
                             gr.null_sink(gr.sizeof_float * total_subc))
                log_to_file(self, ifft2, "data/CIR2.compl")
                log_to_file(self, summ2, "data/CTFsumm2.compl")
                log_to_file(self, estimated_CTF, "data/CTF2.compl")
                log_to_file(self, c2m2, "data/CTFmag2.float")

        ## Postprocess the CTF estimate
        ## CTF -> inverse CTF (for equalizer)
        ## CTF -> norm |.|^2 (for CTF display)
            ctf_postprocess = ofdm.postprocess_CTF_estimate(total_subc)
            self.connect(estimated_CTF, ctf_postprocess)
            inv_estimated_CTF = (ctf_postprocess, 0)
            disp_CTF = (ctf_postprocess, 1)


#     if options.disable_equalization or options.ideal:
#       terminate_stream(self, inv_estimated_CTF)
#       inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
#       inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
#       self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
#       #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
#       inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
#       self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
#       print "Disabled equalization stage"
        '''
    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset

    nondata_blocks = []
    for i in range(config.frame_length):
      if i in config.training_data.pilotsym_pos:
        nondata_blocks.append(i)
        
    print"\t\t\t\t\tnondata_blocks=",nondata_blocks
    pilot_subc = block_header.pilot_tones
    pilot_subcarriers = block_header.pilot_subc_sym
    print "PILOT SUBCARRIERS: ", pilot_subcarriers
        
    phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
                                               nondata_blocks, pilot_subcarriers,0 )
    self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
    self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
    self.connect( frame_start, ( phase_tracking, 2 ) ) ##
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer
      
    
    if options.disable_phase_tracking or options.ideal:
      terminate_stream(self, phase_tracking)
      print "Disabled phase tracking stage"
    else:
      ofdm_blocks = phase_tracking
    '''
        ## Channel Equalizer
        if options.disable_equalization or options.ideal or options.ideal2:
            print "Disabled equalization stage"
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, inv_estimated_CTF)
        else:
            equalizer = ofdm.channel_equalizer(total_subc)
            self.connect(ofdm_blocks, (equalizer, 0))
            self.connect(inv_estimated_CTF, (equalizer, 1))
            self.connect(frame_start, (equalizer, 2))
            ofdm_blocks = equalizer
        #log_to_file(self, equalizer,"data/equalizer_siso.compl")

        #log_to_file(self, ofdm_blocks, "data/equalizer.compl")

        ## LMS Phase tracking
        ## Track residual frequency offset and sampling clock frequency offset
        if options.ideal is False and options.ideal2 is False:
            nondata_blocks = []
            for i in range(config.frame_length):
                if i in config.training_data.pilotsym_pos:
                    nondata_blocks.append(i)

            print "\t\t\t\t\tnondata_blocks=", nondata_blocks
            pilot_subc = block_header.pilot_tones
            pilot_subcarriers = block_header.pilot_subc_sym
            print "PILOT SUBCARRIERS: ", pilot_subcarriers

            phase_tracking2 = ofdm.lms_phase_tracking_dc_null(
                total_subc, pilot_subc, nondata_blocks, pilot_subcarriers,
                dc_null)
            self.connect(ofdm_blocks, (phase_tracking2, 0))
            self.connect(frame_start, (phase_tracking2, 1))  ##

        if options.disable_phase_tracking or options.ideal or options.ideal2:
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, phase_tracking2)
            print "Disabled phase tracking stage"
        else:
            ofdm_blocks = phase_tracking2

        if options.scatter_plot_before_phase_tracking:
            self.before_phase_tracking = equalizer

        ## Output connections

        self.connect(ofdm_blocks, out_ofdm_blocks)
        self.connect(frame_start, out_frame_start)
        if options.ideal is False and options.ideal2 is False:
            self.connect(disp_CTF, out_disp_ctf)
        else:
            self.connect(blocks.vector_source_f([1.0] * total_subc),
                         blocks.stream_to_vector(gr.sizeof_float, total_subc),
                         out_disp_ctf)

        if log:
            log_to_file(self, sc_metric, "data/sc_metric.float")
            log_to_file(self, gi_metric, "data/gi_metric.float")
            log_to_file(self, morelli_foe, "data/morelli_foe.float")
            log_to_file(self, lms_fir, "data/lms_fir.float")
            log_to_file(self, sampler_preamble, "data/preamble.compl")
            log_to_file(self, sync, "data/sync.compl")
            log_to_file(self, frequency_shift, "data/frequency_shift.compl")
            log_to_file(self, fft, "data/fft.compl")
            log_to_file(self, fft, "data/fft.float", mag=True)

            if vars().has_key('subcarrier_mask'):
                log_to_file(self, subcarrier_mask,
                            "data/subcarrier_mask.compl")

            log_to_file(self, ofdm_blocks, "data/ofdm_blocks_out.compl")
            log_to_file(self,
                        frame_start,
                        "data/frame_start.float",
                        char_to_float=True)

            log_to_file(self, sampled_chest_preamble,
                        "data/sampled_chest_preamble.compl")
            log_to_file(self, LS_channel_estimator,
                        "data/ls_channel_estimator.compl")
            log_to_file(self,
                        LS_channel_estimator,
                        "data/ls_channel_estimator.float",
                        mag=True)

            if "ctf_mse_enhancer" in locals():
                log_to_file(self, ctf_mse_enhancer,
                            "data/ctf_mse_enhancer.compl")
                log_to_file(self,
                            ctf_mse_enhancer,
                            "data/ctf_mse_enhancer.float",
                            mag=True)

            log_to_file(self, (ctf_postprocess, 0),
                        "data/inc_estimated_ctf.compl")
            log_to_file(self, (ctf_postprocess, 1), "data/disp_ctf.float")

            log_to_file(self, equalizer, "data/equalizer.compl")
            log_to_file(self, equalizer, "data/equalizer.float", mag=True)

            log_to_file(self, phase_tracking, "data/phase_tracking.compl")
Ejemplo n.º 8
0
    def __init__(self, options, log=False):

        ## Read configuration
        config = station_configuration()

        fft_length = config.fft_length
        #cp_length     = config.cp_length
        block_header = config.training_data
        data_subc = config.data_subcarriers
        virtual_subc = config.virtual_subcarriers
        total_subc = config.subcarriers
        block_length = config.block_length
        frame_length = config.frame_length

        L = block_header.mm_periodic_parts

        cp_length = config.cp_length

        print "data_subc: ", config.data_subcarriers
        print "total_subc: ", config.subcarriers
        print "frame_lengthframe_length: ", frame_length

        ## Set Input/Output signature
        gr.hier_block2.__init__(
            self,
            "fbmc_inner_receiver",
            gr.io_signature(1, 1, gr.sizeof_gr_complex),
            gr.io_signaturev(
                4,
                4,
                [
                    gr.sizeof_float * total_subc,  # Normalized |CTF|^2 
                    gr.sizeof_char,  # Frame start
                    gr.sizeof_gr_complex * total_subc,  # OFDM blocks, SNR est
                    gr.sizeof_float
                ]))  # CFO

        ## Input and output ports
        self.input = rx_input = self

        out_ofdm_blocks = (self, 2)
        out_frame_start = (self, 1)
        out_disp_ctf = (self, 0)
        out_disp_cfo = (self, 3)
        #out_snr_pream    = ( self, 3 )

        ## pre-FFT processing
        '''
    ## Compute autocorrelations for S&C preamble
    ## and cyclic prefix
    
    self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
    self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
    
    self.connect( rx_input, sc_metric )
    self.connect( rx_input, gi_metric )
    terminate_stream(self, gi_metric)
    
    ## Sync. Output contains OFDM blocks
    sync = ofdm.time_sync( fft_length/2, 1)
    self.connect( rx_input, ( sync, 0 ) )
    self.connect( sc_metric, ( sync, 1 ) )
    self.connect( sc_metric, ( sync, 2 ) )
    
    ofdm_blocks = ( sync, 0 )
    frame_start = ( sync, 1 )
    log_to_file( self, ( sync, 1 ), "data/fbmc_peak_detector.char" )
    '''
        if options.ideal is False and options.ideal2 is False:
            #Testing old/new metric
            self.tm = schmidl.recursive_timing_metric(2 * fft_length)
            self.connect(self.input, self.tm)
            #log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm.float" )

            timingmetric_shift = 0  #-2 #int(-cp_length * 0.8)
            tmfilter = filter.fft_filter_fff(
                1, [2. / fft_length] * (fft_length / 2)
            )  # ofdm.lms_fir_ff( fft_length, 1e-3 ) #; filter.fir_filter_fff(1, [1./fft_length]*fft_length)
            self.connect(self.tm, tmfilter)
            self.tm = tmfilter
            #log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm2.float" )

            self._pd_thres = 0.6
            self._pd_lookahead = fft_length  # empirically chosen
            peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead,
                                                     self._pd_thres)
            self.connect(self.tm, peak_detector)
            #log_to_file( self, peak_detector, "data/fbmc_rec_peak_detector.char" )

            #frame_start = [0]*frame_length
            #frame_start[0] = 1
            #frame_start = blocks.vector_source_b(frame_start,True)

            #OLD
            #delayed_timesync = blocks.delay(gr.sizeof_char,
            #                           (frame_length-10)*fft_length/2 - fft_length/4 -1 + timingmetric_shift)
            delayed_timesync = blocks.delay(
                gr.sizeof_char,
                (frame_length - 10) * fft_length / 2 - fft_length / 4 +
                int(2.5 * fft_length) + timingmetric_shift - 1)
            #delayed_timesync = blocks.delay(gr.sizeof_char,
            #(frame_length-10)*fft_length/2 - fft_length/4 + int(3.5*fft_length)  + timingmetric_shift-1)
            self.connect(peak_detector, delayed_timesync)

            self.block_sampler = ofdm.vector_sampler(
                gr.sizeof_gr_complex, fft_length / 2 * frame_length)

            self.connect(self.input, self.block_sampler)
            self.connect(delayed_timesync, (self.block_sampler, 1))
            #log_to_file( self, self.block_sampler, "data/fbmc_block_sampler.compl" )

            vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex * fft_length,
                                           frame_length / 2)
            self.connect(self.block_sampler, vt2s)
            #terminate_stream(self,ofdm_blocks)

            ofdm_blocks = vt2s
            '''
        # TODO: dynamic solution
        vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length/2,
                                                frame_length)
        self.connect(self.block_sampler,vt2s)
        terminate_stream(self,( sync, 0 ))
        ofdm_blocks = vt2s
        '''

            ##stv_help = blocks.stream_to_vector(gr.sizeof_gr_complex*config.fft_length/2, 1)
            #stv_help = blocks.vector_to_stream(gr.sizeof_gr_complex*config.fft_length/2, 2)
            ##self.connect(ofdm_blocks, stv_help)
            ##ofdm_blocks = stv_help
            #ofdm_blocks = ( sync, 0 )
            #frame_start = ( sync, 1 )
            #log_to_file(self, frame_start, "data/frame_start.compl")

            #log_to_file( self, sc_metric, "data/sc_metric.float" )
            #log_to_file( self, gi_metric, "data/gi_metric.float" )
            #log_to_file( self, (sync,1), "data/sync.float" )

            #    log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
            frame_start = [0] * int(frame_length / 2)
            frame_start[0] = 1
            frame_start = blocks.vector_source_b(frame_start, True)

            #frame_start2 = [0]*int(frame_length/2)
            #frame_start2[0] = 1
            #frame_start2 = blocks.vector_source_b(frame_start2,True)

        if options.disable_time_sync or options.ideal or options.ideal2:
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, ofdm_blocks)
                terminate_stream(self, frame_start)

            serial_to_parallel = blocks.stream_to_vector(
                gr.sizeof_gr_complex, fft_length)
            #discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
            #serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
            #discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
            #self.connect( rx_input,serial_to_parallel)

            #self.connect( rx_input, blocks.delay(gr.sizeof_gr_complex,0),serial_to_parallel)
            initial_skip = blocks.skiphead(gr.sizeof_gr_complex,
                                           2 * fft_length)
            self.connect(rx_input, initial_skip)
            if options.ideal is False and options.ideal2 is False:
                self.connect(initial_skip, serial_to_parallel)
                ofdm_blocks = serial_to_parallel
            else:
                ofdm_blocks = initial_skip
            #self.connect( rx_input, serial_to_parallel, discard_cp )

            frame_start = [0] * int(frame_length / 2)
            frame_start[0] = 1
            frame_start = blocks.vector_source_b(frame_start, True)

            #frame_start2 = [0]*int(frame_length/2)
            #frame_start2[0] = 1
            #frame_start2 = blocks.vector_source_b(frame_start2,True)

            print "Disabled time synchronization stage"

        print "\t\t\t\t\tframe_length = ", frame_length

        if options.ideal is False and options.ideal2 is False:
            ## Extract preamble, feed to Morelli & Mengali frequency offset estimator
            assert (block_header.mm_preamble_pos == 0)
            morelli_foe = ofdm.mm_frequency_estimator(fft_length, 2, 1,
                                                      config.fbmc)
            sampler_preamble = ofdm.vector_sampler(
                gr.sizeof_gr_complex * fft_length, 1)
            self.connect(ofdm_blocks, (sampler_preamble, 0))
            self.connect(frame_start, blocks.delay(gr.sizeof_char, 1),
                         (sampler_preamble, 1))
            self.connect(sampler_preamble, morelli_foe)
            freq_offset = morelli_foe
            print "FRAME_LENGTH: ", frame_length
            #log_to_file( self, sampler_preamble, "data/sampler_preamble.compl" )
            #log_to_file( self, rx_input, "data/rx_input.compl" )
            #log_to_file( self, ofdm_blocks, "data/rx_input.compl" )

            #Extracting preamble for SNR estimation
            #fft_snr_est = fft_blocks.fft_vcc( fft_length, True, [], True )
            #self.connect( sampler_preamble, blocks.stream_to_vector(gr.sizeof_gr_complex*fft_length/2, 2),  fft_snr_est )

            ## Remove virtual subcarriers
            #if fft_length > data_subc:
            #subcarrier_mask_snr_est = ofdm.vector_mask( fft_length, virtual_subc/2,
            #                       total_subc, [] )
            #self.connect( fft_snr_est, subcarrier_mask_snr_est )
            #fft_snr_est = subcarrier_mask_snr_est
            #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
            ## Least Squares estimator for channel transfer function (CTF)

            #self.connect( fft_snr_est, out_snr_pream ) # Connecting to output

            ## Adaptive LMS FIR filtering of frequency offset
            lms_fir = ofdm.lms_fir_ff(20,
                                      1e-3)  # TODO: verify parameter choice
            self.connect(freq_offset, lms_fir)
            freq_offset = lms_fir

            self.connect(freq_offset,
                         blocks.keep_one_in_n(gr.sizeof_float,
                                              20), out_disp_cfo)
        else:
            self.connect(blocks.vector_source_f([1]), out_disp_cfo)

        #log_to_file(self, lms_fir, "data/lms_fir.float")

        if options.disable_freq_sync or options.ideal or options.ideal2:
            if options.ideal is False and options.ideal2 is False:
                terminate_stream(self, freq_offset)
                freq_offset = blocks.vector_source_f([0.0], True)
            print "Disabled frequency synchronization stage"

        if options.ideal is False and options.ideal2 is False:
            ## Correct frequency shift, feed-forward structure
            frequency_shift = ofdm.frequency_shift_vcc(fft_length,
                                                       -1.0 / fft_length, 0)

            #freq_shift = blocks.multiply_cc()
            #norm_freq = -0.1 / config.fft_length
            #freq_off = self.freq_off_src = analog.sig_source_c(1.0, analog.GR_SIN_WAVE, norm_freq, 1.0, 0.0 )

            self.connect(ofdm_blocks, (frequency_shift, 0))
            self.connect(freq_offset, (frequency_shift, 1))
            self.connect(frame_start, blocks.delay(gr.sizeof_char, 0),
                         (frequency_shift, 2))

            #self.connect(frequency_shift,s2help)
            #ofdm_blocks = s2help
            ofdm_blocks = frequency_shift
        #terminate_stream(self, frequency_shift)

        #inner_pb_filt = self._inner_pilot_block_filter = fbmc_inner_pilot_block_filter()
        #self.connect(ofdm_blocks,inner_pb_filt)
        #self.connect(frame_start,(inner_pb_filt,1))
        #self.connect((inner_pb_filt,1),blocks.null_sink(gr.sizeof_char))

        #ofdm_blocks = (inner_pb_filt,0)

        overlap_ser_to_par = ofdm.fbmc_overlapping_serial_to_parallel_cvc(
            fft_length)
        self.separate_vcvc = ofdm.fbmc_separate_vcvc(fft_length, 2)
        self.polyphase_network_vcvc_1 = ofdm.fbmc_polyphase_network_vcvc(
            fft_length, 4, 4 * fft_length - 1, True)
        self.polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(
            fft_length, 4, 4 * fft_length - 1, True)
        self.junction_vcvc = ofdm.fbmc_junction_vcvc(fft_length, 2)
        self.fft_fbmc = fft_blocks.fft_vcc(fft_length, True, [], True)

        print "config.training_data.fbmc_no_preambles: ", config.training_data.fbmc_no_preambles
        #center_preamble = [1, -1j, -1, 1j]

        #self.preamble = preamble = [0]*total_subc + center_preamble*((int)(total_subc/len(center_preamble)))+[0]*total_subc

        self.preamble = preamble = config.training_data.fbmc_pilotsym_fd_list
        #inv_preamble = 1. / numpy.array(self.preamble)
        #print "self.preamble: ", len(self.preamble
        #print "inv_preamble: ", list(inv_preamble)

        #print "self.preamble", self.preamble
        #print "self.preamble2", self.preamble2

        self.multiply_const = ofdm.multiply_const_vcc(
            ([1.0 / (math.sqrt(fft_length * 0.6863))] * total_subc))
        self.beta_multiplier_vcvc = ofdm.fbmc_beta_multiplier_vcvc(
            total_subc, 4, 4 * fft_length - 1, 0)
        #self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 2*4-1-1)
        self.skiphead = blocks.skiphead(gr.sizeof_gr_complex * total_subc, 2)
        self.skiphead_1 = blocks.skiphead(gr.sizeof_gr_complex * total_subc, 0)
        #self.remove_preamble_vcvc = ofdm.fbmc_remove_preamble_vcvc(total_subc, config.frame_data_part/2, config.training_data.fbmc_no_preambles*total_subc/2)
        #self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 1, 2, 1, 0)
        self.oqam_postprocessing_vcvc = ofdm.fbmc_oqam_postprocessing_vcvc(
            total_subc, 0, 0)

        #log_to_file( self, ofdm_blocks, "data/PRE_FBMC.compl" )
        #log_to_file( self, self.fft_fbmc, "data/FFT_FBMC.compl" )

        if options.ideal is False and options.ideal2 is False:
            self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(
                total_subc, config.frame_data_part, 3, 2, 1, 0)
            help2 = blocks.keep_one_in_n(gr.sizeof_gr_complex * total_subc,
                                         frame_length)
            self.connect((self.subchannel_processing_vcvc, 1), help2)
            #log_to_file( self, self.subchannel_processing_vcvc, "data/fbmc_subc.compl" )

        #terminate_stream(self, help2)

        if options.ideal is False and options.ideal2 is False:
            self.connect(
                ofdm_blocks,
                blocks.vector_to_stream(gr.sizeof_gr_complex, fft_length),
                overlap_ser_to_par)
        else:
            self.connect(ofdm_blocks, overlap_ser_to_par)

        self.connect(overlap_ser_to_par, self.separate_vcvc)
        self.connect((self.separate_vcvc, 1),
                     (self.polyphase_network_vcvc_2, 0))
        self.connect((self.separate_vcvc, 0),
                     (self.polyphase_network_vcvc_1, 0))
        self.connect((self.polyphase_network_vcvc_1, 0),
                     (self.junction_vcvc, 0))
        self.connect((self.polyphase_network_vcvc_2, 0),
                     (self.junction_vcvc, 1))
        self.connect(self.junction_vcvc, self.fft_fbmc)

        ofdm_blocks = self.fft_fbmc
        print "config.dc_null: ", config.dc_null
        if fft_length > data_subc:
            subcarrier_mask_fbmc = ofdm.vector_mask_dc_null(
                fft_length, virtual_subc / 2, total_subc, config.dc_null, [])
            self.connect(ofdm_blocks, subcarrier_mask_fbmc)
            ofdm_blocks = subcarrier_mask_fbmc
            #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
            ## Least Squares estimator for channel transfer function (CTF)
            #log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )

        self.connect(ofdm_blocks, self.beta_multiplier_vcvc)

        ofdm_blocks = self.beta_multiplier_vcvc
        #self.connect(ofdm_blocks,self.multiply_const)
        #self.connect(self.multiply_const, (self.skiphead, 0))

        self.connect(ofdm_blocks, (self.skiphead, 0))
        #log_to_file( self, self.skiphead, "data/fbmc_skiphead_4.compl" )

        #self.connect(ofdm_blocks, self.multiply_const)
        #self.connect(self.multiply_const, self.beta_multiplier_vcvc)
        #self.connect((self.beta_multiplier_vcvc, 0), (self.skiphead, 0))
        if options.ideal or options.ideal2:
            self.connect((self.skiphead, 0), (self.skiphead_1, 0))
        else:
            self.connect((self.skiphead, 0),
                         (self.subchannel_processing_vcvc, 0))
            self.connect((self.subchannel_processing_vcvc, 0),
                         (self.skiphead_1, 0))

        #log_to_file( self, self.skiphead, "data/fbmc_subc.compl" )
        #self.connect((self.skiphead_1, 0),(self.remove_preamble_vcvc, 0))
        #self.connect((self.remove_preamble_vcvc, 0),  (self.oqam_postprocessing_vcvc, 0))

        #ofdm_blocks = self.oqam_postprocessing_vcvc
        #log_to_file( self, self.subchannel_processing_vcvc, "data/subc_0.compl" )
        #log_to_file( self, (self.subchannel_processing_vcvc,1), "data/subc_1.compl" )

        self.connect((self.skiphead_1, 0), (self.oqam_postprocessing_vcvc, 0))
        #self.connect((self.oqam_postprocessing_vcvc, 0), (self.remove_preamble_vcvc, 0) )

        ofdm_blocks = (self.oqam_postprocessing_vcvc, 0
                       )  #(self.remove_preamble_vcvc, 0)
        #log_to_file( self, (self.oqam_postprocessing_vcvc, 0), "data/fbmc_before_remove.compl" )

        #log_to_file( self, self.skiphead, "data/SKIP_HEAD_FBMC.compl" )
        #log_to_file( self, self.beta_multiplier_vcvc, "data/BETA_REC_FBMC.compl" )
        #log_to_file( self, self.oqam_postprocessing_vcvc, "data/REC_OUT_FBMC.compl" )
        """ DISABLED OFDM CHANNEL ESTIMATION PREMBLE -> CORRECT LATER to compare FBMC and OFDM channel estimation
    #TAKING THE CHANNEL ESTIMATION PREAMBLE
    chest_pre_trigger = blocks.delay( gr.sizeof_char, 3 )
    sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length/2, 2 )
      
    self.connect( frame_start,       chest_pre_trigger )
    self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
    self.connect( frequency_shift,       ( sampled_chest_preamble, 0 ) )
    #ofdm_blocks = sampled_chest_preamble
    
        
    ## FFT
    fft = fft_blocks.fft_vcc( fft_length, True, [], True )
    self.connect( sampled_chest_preamble, fft )
    ofdm_blocks_est = fft
    log_to_file( self, sampled_chest_preamble, "data/SAMPLED_EST_PREAMBLE.compl" )
    log_to_file( self, ofdm_blocks_est, "data/FFT.compl" )
    
    
    ## Remove virtual subcarriers
    if fft_length > data_subc:
      subcarrier_mask = ofdm.vector_mask( fft_length, virtual_subc/2,
                                           total_subc, [] )
      self.connect( ofdm_blocks_est, subcarrier_mask )
      ofdm_blocks_est = subcarrier_mask
      #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
       ## Least Squares estimator for channel transfer function (CTF)
      log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
    
          
    ## post-FFT processing
      
    
    
    ## extract channel estimation preamble from frame
    ##chest_pre_trigger = blocks.delay( gr.sizeof_char, 
                                  ##1 )
    ##sampled_chest_preamble = \
     ## ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
    ##self.connect( frame_start,       chest_pre_trigger )
    ##self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
    ##self.connect( ofdm_blocks,       ( sampled_chest_preamble, 0 ) )
    

    
    ## Least Squares estimator for channel transfer function (CTF)
    inv_preamble_fd = numpy.array( block_header.pilotsym_fd[ 
        block_header.channel_estimation_pilot[0] ] )
    #print "Channel estimation pilot: ", inv_preamble_fd
    inv_preamble_fd = 1. / inv_preamble_fd
    
    LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
    self.connect( ofdm_blocks_est, LS_channel_estimator )
    estimated_CTF = LS_channel_estimator
    terminate_stream(self,estimated_CTF)
    """
        if options.ideal is False and options.ideal2 is False:
            if options.logcir:
                log_to_file(self, sampled_chest_preamble, "data/PREAM.compl")

            if not options.disable_ctf_enhancer:

                if options.logcir:
                    ifft1 = fft_blocks.fft_vcc(total_subc, False, [], True)
                    self.connect(
                        estimated_CTF, ifft1,
                        gr.null_sink(gr.sizeof_gr_complex * total_subc))
                    summ1 = ofdm.vector_sum_vcc(total_subc)
                    c2m = gr.complex_to_mag(total_subc)
                    self.connect(estimated_CTF, summ1,
                                 gr.null_sink(gr.sizeof_gr_complex))
                    self.connect(estimated_CTF, c2m,
                                 gr.null_sink(gr.sizeof_float * total_subc))
                    log_to_file(self, ifft1, "data/CIR1.compl")
                    log_to_file(self, summ1, "data/CTFsumm1.compl")
                    log_to_file(self, estimated_CTF, "data/CTF1.compl")
                    log_to_file(self, c2m, "data/CTFmag1.float")

                ## MSE enhancer
                ctf_mse_enhancer = ofdm.CTF_MSE_enhancer(
                    total_subc, cp_length + cp_length)
                self.connect(estimated_CTF, ctf_mse_enhancer)
                #      log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
                #ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
                #null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
                #ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
                #ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
                # total_subc, [] )
                #self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )

                estimated_CTF = ctf_mse_enhancer
                print "Disabled CTF MSE enhancer"

            if options.logcir:
                ifft2 = fft_blocks.fft_vcc(total_subc, False, [], True)
                self.connect(estimated_CTF, ifft2,
                             gr.null_sink(gr.sizeof_gr_complex * total_subc))
                summ2 = ofdm.vector_sum_vcc(total_subc)
                c2m2 = gr.complex_to_mag(total_subc)
                self.connect(estimated_CTF, summ2,
                             gr.null_sink(gr.sizeof_gr_complex))
                self.connect(estimated_CTF, c2m2,
                             gr.null_sink(gr.sizeof_float * total_subc))
                log_to_file(self, ifft2, "data/CIR2.compl")
                log_to_file(self, summ2, "data/CTFsumm2.compl")
                log_to_file(self, estimated_CTF, "data/CTF2.compl")
                log_to_file(self, c2m2, "data/CTFmag2.float")

            ## Postprocess the CTF estimate
            ## CTF -> inverse CTF (for equalizer)
            ## CTF -> norm |.|^2 (for CTF display)
            ctf_postprocess = ofdm.fbmc_postprocess_CTF_estimate(total_subc)

            self.connect(help2, ctf_postprocess)
            #estimated_SNR = ( ctf_postprocess, 0 )
            disp_CTF = (ctf_postprocess, 0)
            #self.connect(estimated_SNR,out_snr_pream)
            #log_to_file( self, estimated_SNR, "data/fbmc_SNR.float" )

            #Disable measured SNR output
            #terminate_stream(self, estimated_SNR)
            #self.connect(blocks.vector_source_f([10.0],True) ,out_snr_pream)


#     if options.disable_equalization or options.ideal:
#       terminate_stream(self, inv_estimated_CTF)
#       inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
#       inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
#       self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
#       #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
#       inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
#       self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
#       print "Disabled equalization stage"
        '''
    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset

    nondata_blocks = []
    for i in range(config.frame_length):
      if i in config.training_data.pilotsym_pos:
        nondata_blocks.append(i)
        
    print"\t\t\t\t\tnondata_blocks=",nondata_blocks
    pilot_subc = block_header.pilot_tones
    pilot_subcarriers = block_header.pilot_subc_sym
    print "PILOT SUBCARRIERS: ", pilot_subcarriers
        
    phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
                                               nondata_blocks, pilot_subcarriers,0 )
    self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
    self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
    self.connect( frame_start, ( phase_tracking, 2 ) ) ##
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer
      
    
    if options.disable_phase_tracking or options.ideal:
      terminate_stream(self, phase_tracking)
      print "Disabled phase tracking stage"
    else:
      ofdm_blocks = phase_tracking
    '''
        ## Channel Equalizer
        ##equalizer = ofdm.channel_equalizer( total_subc )
        ##self.connect( ofdm_blocks,       ( equalizer, 0 ) )
        ##self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
        ##self.connect( frame_start,       ( equalizer, 2 ) )
        ##ofdm_blocks = equalizer
        #log_to_file(self, equalizer,"data/equalizer_siso.compl")

        #log_to_file(self, ofdm_blocks, "data/equalizer.compl")

        ## LMS Phase tracking
        ## Track residual frequency offset and sampling clock frequency offset

        nondata_blocks = []
        for i in range(config.frame_length):
            if i in config.training_data.pilotsym_pos:
                nondata_blocks.append(i)

        print "\t\t\t\t\tnondata_blocks=", nondata_blocks
        pilot_subc = block_header.pilot_tones
        pilot_subcarriers = block_header.pilot_subc_sym
        print "PILOT SUBCARRIERS: ", pilot_subcarriers

        if options.scatter_plot_before_phase_tracking:
            self.before_phase_tracking = equalizer

        ## Output connections

        self.connect(ofdm_blocks, out_ofdm_blocks)
        self.connect(frame_start, out_frame_start)
        if options.ideal is False and options.ideal2 is False:
            self.connect(disp_CTF, out_disp_ctf)
        else:
            self.connect(blocks.vector_source_f([1.0] * total_subc),
                         blocks.stream_to_vector(gr.sizeof_float, total_subc),
                         out_disp_ctf)

        if log:
            log_to_file(self, sc_metric, "data/sc_metric.float")
            log_to_file(self, gi_metric, "data/gi_metric.float")
            log_to_file(self, morelli_foe, "data/morelli_foe.float")
            log_to_file(self, lms_fir, "data/lms_fir.float")
            log_to_file(self, sampler_preamble, "data/preamble.compl")
            log_to_file(self, sync, "data/sync.compl")
            log_to_file(self, frequency_shift, "data/frequency_shift.compl")
            log_to_file(self, fft, "data/fft.compl")
            log_to_file(self, fft, "data/fft.float", mag=True)

            if vars().has_key('subcarrier_mask'):
                log_to_file(self, subcarrier_mask,
                            "data/subcarrier_mask.compl")

            log_to_file(self, ofdm_blocks, "data/ofdm_blocks_out.compl")
            log_to_file(self,
                        frame_start,
                        "data/frame_start.float",
                        char_to_float=True)

            log_to_file(self, sampled_chest_preamble,
                        "data/sampled_chest_preamble.compl")
            log_to_file(self, LS_channel_estimator,
                        "data/ls_channel_estimator.compl")
            log_to_file(self,
                        LS_channel_estimator,
                        "data/ls_channel_estimator.float",
                        mag=True)

            if "ctf_mse_enhancer" in locals():
                log_to_file(self, ctf_mse_enhancer,
                            "data/ctf_mse_enhancer.compl")
                log_to_file(self,
                            ctf_mse_enhancer,
                            "data/ctf_mse_enhancer.float",
                            mag=True)

            log_to_file(self, (ctf_postprocess, 0),
                        "data/inc_estimated_ctf.compl")
            log_to_file(self, (ctf_postprocess, 1), "data/disp_ctf.float")

            log_to_file(self, equalizer, "data/equalizer.compl")
            log_to_file(self, equalizer, "data/equalizer.float", mag=True)

            log_to_file(self, phase_tracking, "data/phase_tracking.compl")
Ejemplo n.º 9
0
    def __init__(self, vlen):
        gr.hier_block2.__init__(
            self, "snr_estimator",
            gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
            gr.io_signature(1, 1, gr.sizeof_float))

        data_in = (self, 0)
        trig_in = (self, 1)
        snr_out = (self, 0)

        ## Preamble Extraction
        sampler = vector_sampler(gr.sizeof_gr_complex, vlen)
        self.connect(data_in, sampler)
        self.connect(trig_in, (sampler, 1))

        ## Algorithm implementation
        estim = sc_snr_estimator(vlen)
        self.connect(sampler, estim)
        self.connect(estim, snr_out)

        return

        ## Split block into two parts
        splitter = gr.vector_to_streams(gr.sizeof_gr_complex * vlen / 2, 2)
        self.connect(sampler, splitter)

        ## Conjugate first half block
        conj = gr.conjugate_cc(vlen / 2)
        self.connect(splitter, conj)

        ## Vector multiplication of both half blocks
        vmult = gr.multiply_vcc(vlen / 2)
        self.connect(conj, vmult)
        self.connect((splitter, 1), (vmult, 1))

        ## Sum of Products
        psum = vector_sum_vcc(vlen / 2)
        self.connect(vmult, psum)

        ## Magnitude of P(d)
        p_mag = gr.complex_to_mag()
        self.connect(psum, p_mag)

        ## Squared Magnitude of block
        r_magsqrd = gr.complex_to_mag_squared(vlen)
        self.connect(sampler, r_magsqrd)

        ## Sum of squared second half block
        r_sum = vector_sum_vff(vlen)
        self.connect(r_magsqrd, r_sum)

        ## Square Root of Metric
        m_sqrt = gr.divide_ff()
        self.connect(p_mag, (m_sqrt, 0))
        self.connect(r_sum, gr.multiply_const_ff(0.5), (m_sqrt, 1))

        ## Denominator of SNR estimate
        denom = gr.add_const_ff(1)
        neg_m_sqrt = gr.multiply_const_ff(-1.0)
        self.connect(m_sqrt, limit_vff(1, 1 - 2e-5, -1000), neg_m_sqrt, denom)

        ## SNR estimate
        snr_est = gr.divide_ff()
        self.connect(m_sqrt, (snr_est, 0))
        self.connect(denom, (snr_est, 1))

        ## Setup Output Connections
        self.connect(snr_est, self)
Ejemplo n.º 10
0
  def __init__( self, options, log = False ):
    
    ## Read configuration
    config = station_configuration()
    
    fft_length    = config.fft_length
    #cp_length     = config.cp_length
    block_header  = config.training_data
    data_subc     = config.data_subcarriers
    virtual_subc  = config.virtual_subcarriers
    total_subc    = config.subcarriers
    block_length  = config.block_length
    frame_length  = config.frame_length
    
    L             = block_header.mm_periodic_parts
    
        
    cp_length     = config.cp_length


    
    print "data_subc: ", config.data_subcarriers
    print "total_subc: ", config.subcarriers
    print "frame_lengthframe_length: ", frame_length
    
    
    ## Set Input/Output signature
    gr.hier_block2.__init__( self, 
        "fbmc_inner_receiver",
        gr.io_signature(
            1, 1,
            gr.sizeof_gr_complex ),
        gr.io_signaturev(
            4, 4,
            [gr.sizeof_float * total_subc,    # Normalized |CTF|^2 
            gr.sizeof_char,                       # Frame start
            gr.sizeof_gr_complex * total_subc, # OFDM blocks, SNR est
            gr.sizeof_float] ) )      # CFO
    
    
    ## Input and output ports
    self.input = rx_input = self
    
    out_ofdm_blocks = ( self, 2 )
    out_frame_start = ( self, 1 )
    out_disp_ctf    = ( self, 0 )
    out_disp_cfo    = ( self, 3 )
    #out_snr_pream    = ( self, 3 )
    
    
    
    
    ## pre-FFT processing
    
    '''
    ## Compute autocorrelations for S&C preamble
    ## and cyclic prefix
    
    self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
    self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
    
    self.connect( rx_input, sc_metric )
    self.connect( rx_input, gi_metric )
    terminate_stream(self, gi_metric)
    
    ## Sync. Output contains OFDM blocks
    sync = ofdm.time_sync( fft_length/2, 1)
    self.connect( rx_input, ( sync, 0 ) )
    self.connect( sc_metric, ( sync, 1 ) )
    self.connect( sc_metric, ( sync, 2 ) )
    
    ofdm_blocks = ( sync, 0 )
    frame_start = ( sync, 1 )
    log_to_file( self, ( sync, 1 ), "data/fbmc_peak_detector.char" )
    '''
    if options.ideal is False and options.ideal2 is False:
        #Testing old/new metric
        self.tm = schmidl.recursive_timing_metric(2*fft_length)
        self.connect( self.input, self.tm)
        #log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm.float" )
        
        timingmetric_shift = 0 #-2 #int(-cp_length * 0.8)
        tmfilter = filter.fft_filter_fff(1, [2./fft_length]*(fft_length/2))# ofdm.lms_fir_ff( fft_length, 1e-3 ) #; filter.fir_filter_fff(1, [1./fft_length]*fft_length)
        self.connect( self.tm, tmfilter )
        self.tm = tmfilter
        #log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm2.float" )
        
        self._pd_thres = 0.6
        self._pd_lookahead = fft_length # empirically chosen
        peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
        self.connect(self.tm, peak_detector)
        #log_to_file( self, peak_detector, "data/fbmc_rec_peak_detector.char" )
        
        
        #frame_start = [0]*frame_length
        #frame_start[0] = 1
        #frame_start = blocks.vector_source_b(frame_start,True)
        
        #OLD
        #delayed_timesync = blocks.delay(gr.sizeof_char,
         #                           (frame_length-10)*fft_length/2 - fft_length/4 -1 + timingmetric_shift)
        delayed_timesync = blocks.delay(gr.sizeof_char,
                                    (frame_length-10)*fft_length/2 - fft_length/4  + int(2.5*fft_length)  + timingmetric_shift-1)
        #delayed_timesync = blocks.delay(gr.sizeof_char,
                                    #(frame_length-10)*fft_length/2 - fft_length/4 + int(3.5*fft_length)  + timingmetric_shift-1)
        self.connect( peak_detector, delayed_timesync )
        
        self.block_sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,fft_length/2*frame_length)
        
        self.connect(self.input,self.block_sampler)
        self.connect(delayed_timesync,(self.block_sampler,1))
        #log_to_file( self, self.block_sampler, "data/fbmc_block_sampler.compl" )
        
        vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*fft_length,
                                                frame_length/2)
        self.connect(self.block_sampler,vt2s)
        #terminate_stream(self,ofdm_blocks)
        
        ofdm_blocks = vt2s
        
        '''
        # TODO: dynamic solution
        vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length/2,
                                                frame_length)
        self.connect(self.block_sampler,vt2s)
        terminate_stream(self,( sync, 0 ))
        ofdm_blocks = vt2s
        '''
        
        
        
        
        
        ##stv_help = blocks.stream_to_vector(gr.sizeof_gr_complex*config.fft_length/2, 1)
        #stv_help = blocks.vector_to_stream(gr.sizeof_gr_complex*config.fft_length/2, 2)
       ##self.connect(ofdm_blocks, stv_help)
        ##ofdm_blocks = stv_help
        #ofdm_blocks = ( sync, 0 )
        #frame_start = ( sync, 1 )
        #log_to_file(self, frame_start, "data/frame_start.compl")
        
        #log_to_file( self, sc_metric, "data/sc_metric.float" )
        #log_to_file( self, gi_metric, "data/gi_metric.float" )
        #log_to_file( self, (sync,1), "data/sync.float" )
        
    #    log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
        frame_start = [0]*int(frame_length/2)
        frame_start[0] = 1
        frame_start = blocks.vector_source_b(frame_start,True)          
        
        #frame_start2 = [0]*int(frame_length/2)
        #frame_start2[0] = 1
        #frame_start2 = blocks.vector_source_b(frame_start2,True)
    
    if options.disable_time_sync or options.ideal or options.ideal2:
      if options.ideal is False and options.ideal2 is False:
        terminate_stream(self, ofdm_blocks)
        terminate_stream(self, frame_start)
      
      serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,fft_length)
      #discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
      #serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
      #discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
      #self.connect( rx_input,serial_to_parallel)
      
      #self.connect( rx_input, blocks.delay(gr.sizeof_gr_complex,0),serial_to_parallel)
      initial_skip = blocks.skiphead(gr.sizeof_gr_complex,2*fft_length)
      self.connect( rx_input, initial_skip)
      if options.ideal is False and options.ideal2 is False:          
          self.connect(  initial_skip, serial_to_parallel)
          ofdm_blocks = serial_to_parallel
      else:
          ofdm_blocks = initial_skip
      #self.connect( rx_input, serial_to_parallel, discard_cp )
      
      frame_start = [0]*int(frame_length/2)
      frame_start[0] = 1
      frame_start = blocks.vector_source_b(frame_start,True)
      
      #frame_start2 = [0]*int(frame_length/2)
      #frame_start2[0] = 1
      #frame_start2 = blocks.vector_source_b(frame_start2,True)
      
      print "Disabled time synchronization stage"
    
    print"\t\t\t\t\tframe_length = ",frame_length
    
    if options.ideal is False and options.ideal2 is False:
        ## Extract preamble, feed to Morelli & Mengali frequency offset estimator
        assert( block_header.mm_preamble_pos == 0 )
        morelli_foe = ofdm.mm_frequency_estimator( fft_length, 2, 1, config.fbmc )
        sampler_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length,
                                                1 )
        self.connect( ofdm_blocks, ( sampler_preamble, 0 ) )
        self.connect( frame_start, blocks.delay( gr.sizeof_char, 1 ), ( sampler_preamble, 1 ) )
        self.connect( sampler_preamble, morelli_foe )
        freq_offset = morelli_foe
        print "FRAME_LENGTH: ", frame_length
        #log_to_file( self, sampler_preamble, "data/sampler_preamble.compl" )
        #log_to_file( self, rx_input, "data/rx_input.compl" )
        #log_to_file( self, ofdm_blocks, "data/rx_input.compl" )

        
        #Extracting preamble for SNR estimation
        #fft_snr_est = fft_blocks.fft_vcc( fft_length, True, [], True )
        #self.connect( sampler_preamble, blocks.stream_to_vector(gr.sizeof_gr_complex*fft_length/2, 2),  fft_snr_est )
        
        
        ## Remove virtual subcarriers
        #if fft_length > data_subc:
          #subcarrier_mask_snr_est = ofdm.vector_mask( fft_length, virtual_subc/2,
                        #                       total_subc, [] )
          #self.connect( fft_snr_est, subcarrier_mask_snr_est )
          #fft_snr_est = subcarrier_mask_snr_est
          #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
           ## Least Squares estimator for channel transfer function (CTF)
        
        #self.connect( fft_snr_est, out_snr_pream ) # Connecting to output
        
        ## Adaptive LMS FIR filtering of frequency offset
        lms_fir = ofdm.lms_fir_ff( 20, 1e-3 ) # TODO: verify parameter choice
        self.connect( freq_offset, lms_fir )
        freq_offset = lms_fir
        
        self.connect(freq_offset, blocks.keep_one_in_n(gr.sizeof_float,20) ,out_disp_cfo)
    else:
        self.connect(blocks.vector_source_f ([1]) ,out_disp_cfo)

    
    #log_to_file(self, lms_fir, "data/lms_fir.float")
    
    if options.disable_freq_sync or options.ideal or options.ideal2:
      if options.ideal is False and options.ideal2 is False:  
          terminate_stream(self, freq_offset)
          freq_offset = blocks.vector_source_f([0.0],True)
      print "Disabled frequency synchronization stage"
    
    if options.ideal is False and options.ideal2 is False:
        ## Correct frequency shift, feed-forward structure
        frequency_shift = ofdm.frequency_shift_vcc( fft_length, -1.0/fft_length,
                                                    0)
        
        #freq_shift = blocks.multiply_cc()
        #norm_freq = -0.1 / config.fft_length
        #freq_off = self.freq_off_src = analog.sig_source_c(1.0, analog.GR_SIN_WAVE, norm_freq, 1.0, 0.0 )
        
        self.connect( ofdm_blocks, ( frequency_shift, 0 ) )
        self.connect( freq_offset, ( frequency_shift, 1 ) )
        self.connect( frame_start,blocks.delay( gr.sizeof_char, 0), ( frequency_shift, 2 ) )
        
        

        
        #self.connect(frequency_shift,s2help)
        #ofdm_blocks = s2help
        ofdm_blocks = frequency_shift
    #terminate_stream(self, frequency_shift)
    
    
    
    #inner_pb_filt = self._inner_pilot_block_filter = fbmc_inner_pilot_block_filter()
    #self.connect(ofdm_blocks,inner_pb_filt)
    #self.connect(frame_start,(inner_pb_filt,1))
    #self.connect((inner_pb_filt,1),blocks.null_sink(gr.sizeof_char))
    
    #ofdm_blocks = (inner_pb_filt,0)
    
    
    overlap_ser_to_par = ofdm.fbmc_overlapping_serial_to_parallel_cvc(fft_length)
    self.separate_vcvc = ofdm.fbmc_separate_vcvc(fft_length, 2)
    self.polyphase_network_vcvc_1 = ofdm.fbmc_polyphase_network_vcvc(fft_length, 4, 4*fft_length-1, True)
    self.polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(fft_length, 4, 4*fft_length-1, True)
    self.junction_vcvc = ofdm.fbmc_junction_vcvc(fft_length, 2)
    self.fft_fbmc = fft_blocks.fft_vcc(fft_length, True, [], True)
    
    print "config.training_data.fbmc_no_preambles: ", config.training_data.fbmc_no_preambles
    #center_preamble = [1, -1j, -1, 1j]
    
    #self.preamble = preamble = [0]*total_subc + center_preamble*((int)(total_subc/len(center_preamble)))+[0]*total_subc
    
    self.preamble = preamble = config.training_data.fbmc_pilotsym_fd_list
    #inv_preamble = 1. / numpy.array(self.preamble)
    #print "self.preamble: ", len(self.preamble
    #print "inv_preamble: ", list(inv_preamble)
    
    #print "self.preamble", self.preamble
    #print "self.preamble2", self.preamble2
    
    
    self.multiply_const= ofdm.multiply_const_vcc(([1.0/(math.sqrt(fft_length*0.6863))]*total_subc))    
    self.beta_multiplier_vcvc = ofdm.fbmc_beta_multiplier_vcvc(total_subc, 4, 4*fft_length-1, 0)
    #self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 2*4-1-1)
    self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc,2)
    self.skiphead_1 = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 0)
    #self.remove_preamble_vcvc = ofdm.fbmc_remove_preamble_vcvc(total_subc, config.frame_data_part/2, config.training_data.fbmc_no_preambles*total_subc/2)
    #self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 1, 2, 1, 0)
    self.oqam_postprocessing_vcvc = ofdm.fbmc_oqam_postprocessing_vcvc(total_subc, 0, 0)
    
    #log_to_file( self, ofdm_blocks, "data/PRE_FBMC.compl" )
    #log_to_file( self, self.fft_fbmc, "data/FFT_FBMC.compl" )

    if options.ideal is False and options.ideal2 is False:
        self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 3, 2, 1, 0)
        help2 = blocks.keep_one_in_n(gr.sizeof_gr_complex*total_subc,frame_length)
        self.connect ((self.subchannel_processing_vcvc,1),help2)
        #log_to_file( self, self.subchannel_processing_vcvc, "data/fbmc_subc.compl" )

    
    #terminate_stream(self, help2)
    
    if options.ideal is False and options.ideal2 is False:
        self.connect(ofdm_blocks, blocks.vector_to_stream(gr.sizeof_gr_complex, fft_length),overlap_ser_to_par)
    else:
        self.connect(ofdm_blocks,overlap_ser_to_par)
        
    self.connect(overlap_ser_to_par, self.separate_vcvc)
    self.connect((self.separate_vcvc, 1), (self.polyphase_network_vcvc_2, 0))
    self.connect((self.separate_vcvc, 0), (self.polyphase_network_vcvc_1, 0))
    self.connect((self.polyphase_network_vcvc_1, 0), (self.junction_vcvc, 0))
    self.connect((self.polyphase_network_vcvc_2, 0), (self.junction_vcvc, 1))
    self.connect(self.junction_vcvc, self.fft_fbmc)
    
    ofdm_blocks = self.fft_fbmc
    print "config.dc_null: ", config.dc_null
    if fft_length > data_subc:
      subcarrier_mask_fbmc = ofdm.vector_mask_dc_null( fft_length, virtual_subc/2,
                                           total_subc, config.dc_null, [] )
      self.connect( ofdm_blocks, subcarrier_mask_fbmc )
      ofdm_blocks = subcarrier_mask_fbmc
      #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
       ## Least Squares estimator for channel transfer function (CTF)
      #log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
      
    
    self.connect(ofdm_blocks, self.beta_multiplier_vcvc)
    
    ofdm_blocks = self.beta_multiplier_vcvc
    #self.connect(ofdm_blocks,self.multiply_const)
    #self.connect(self.multiply_const, (self.skiphead, 0))
    
    self.connect(ofdm_blocks, (self.skiphead, 0))
    #log_to_file( self, self.skiphead, "data/fbmc_skiphead_4.compl" )
    
    
    #self.connect(ofdm_blocks, self.multiply_const)
    #self.connect(self.multiply_const, self.beta_multiplier_vcvc)
    #self.connect((self.beta_multiplier_vcvc, 0), (self.skiphead, 0))
    if options.ideal or options.ideal2:
        self.connect((self.skiphead, 0),(self.skiphead_1, 0))
    else:
        self.connect((self.skiphead, 0), (self.subchannel_processing_vcvc, 0))
        self.connect((self.subchannel_processing_vcvc, 0), (self.skiphead_1, 0))
        
    #log_to_file( self, self.skiphead, "data/fbmc_subc.compl" )    
    #self.connect((self.skiphead_1, 0),(self.remove_preamble_vcvc, 0))
    #self.connect((self.remove_preamble_vcvc, 0),  (self.oqam_postprocessing_vcvc, 0))
    
    #ofdm_blocks = self.oqam_postprocessing_vcvc
    #log_to_file( self, self.subchannel_processing_vcvc, "data/subc_0.compl" )
    #log_to_file( self, (self.subchannel_processing_vcvc,1), "data/subc_1.compl" )
    
    
    
    self.connect((self.skiphead_1, 0),(self.oqam_postprocessing_vcvc, 0))
    #self.connect((self.oqam_postprocessing_vcvc, 0), (self.remove_preamble_vcvc, 0) )
    
    ofdm_blocks = (self.oqam_postprocessing_vcvc, 0)#(self.remove_preamble_vcvc, 0)
    #log_to_file( self, (self.oqam_postprocessing_vcvc, 0), "data/fbmc_before_remove.compl" )
    
    #log_to_file( self, self.skiphead, "data/SKIP_HEAD_FBMC.compl" )
    #log_to_file( self, self.beta_multiplier_vcvc, "data/BETA_REC_FBMC.compl" )
    #log_to_file( self, self.oqam_postprocessing_vcvc, "data/REC_OUT_FBMC.compl" )
        
    

    
    
    
    
    
    """ DISABLED OFDM CHANNEL ESTIMATION PREMBLE -> CORRECT LATER to compare FBMC and OFDM channel estimation
    #TAKING THE CHANNEL ESTIMATION PREAMBLE
    chest_pre_trigger = blocks.delay( gr.sizeof_char, 3 )
    sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length/2, 2 )
      
    self.connect( frame_start,       chest_pre_trigger )
    self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
    self.connect( frequency_shift,       ( sampled_chest_preamble, 0 ) )
    #ofdm_blocks = sampled_chest_preamble
    
        
    ## FFT
    fft = fft_blocks.fft_vcc( fft_length, True, [], True )
    self.connect( sampled_chest_preamble, fft )
    ofdm_blocks_est = fft
    log_to_file( self, sampled_chest_preamble, "data/SAMPLED_EST_PREAMBLE.compl" )
    log_to_file( self, ofdm_blocks_est, "data/FFT.compl" )
    
    
    ## Remove virtual subcarriers
    if fft_length > data_subc:
      subcarrier_mask = ofdm.vector_mask( fft_length, virtual_subc/2,
                                           total_subc, [] )
      self.connect( ofdm_blocks_est, subcarrier_mask )
      ofdm_blocks_est = subcarrier_mask
      #log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
       ## Least Squares estimator for channel transfer function (CTF)
      log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
    
          
    ## post-FFT processing
      
    
    
    ## extract channel estimation preamble from frame
    ##chest_pre_trigger = blocks.delay( gr.sizeof_char, 
                                  ##1 )
    ##sampled_chest_preamble = \
     ## ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
    ##self.connect( frame_start,       chest_pre_trigger )
    ##self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
    ##self.connect( ofdm_blocks,       ( sampled_chest_preamble, 0 ) )
    

    
    ## Least Squares estimator for channel transfer function (CTF)
    inv_preamble_fd = numpy.array( block_header.pilotsym_fd[ 
        block_header.channel_estimation_pilot[0] ] )
    #print "Channel estimation pilot: ", inv_preamble_fd
    inv_preamble_fd = 1. / inv_preamble_fd
    
    LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
    self.connect( ofdm_blocks_est, LS_channel_estimator )
    estimated_CTF = LS_channel_estimator
    terminate_stream(self,estimated_CTF)
    """
    if options.ideal is False and options.ideal2 is False:
        if options.logcir:
         log_to_file( self, sampled_chest_preamble, "data/PREAM.compl" )
     
    
        if not options.disable_ctf_enhancer:
      
      
            if options.logcir:
                ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
                self.connect( estimated_CTF, ifft1,gr.null_sink(gr.sizeof_gr_complex*total_subc))
                summ1 = ofdm.vector_sum_vcc(total_subc)
                c2m =gr.complex_to_mag(total_subc)
                self.connect( estimated_CTF,summ1 ,gr.null_sink(gr.sizeof_gr_complex))
                self.connect( estimated_CTF, c2m,gr.null_sink(gr.sizeof_float*total_subc))
                log_to_file( self, ifft1, "data/CIR1.compl" )
                log_to_file( self, summ1, "data/CTFsumm1.compl" )
                log_to_file( self, estimated_CTF, "data/CTF1.compl" )
                log_to_file( self, c2m, "data/CTFmag1.float" )
        
            ## MSE enhancer
            ctf_mse_enhancer = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
            self.connect( estimated_CTF, ctf_mse_enhancer )
#      log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
      #ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
      #null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
      #ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
      #ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
                                          # total_subc, [] )
      #self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
        
            estimated_CTF = ctf_mse_enhancer 
            print "Disabled CTF MSE enhancer"

        if options.logcir:
         ifft2 = fft_blocks.fft_vcc(total_subc,False,[],True)
         self.connect( estimated_CTF, ifft2,gr.null_sink(gr.sizeof_gr_complex*total_subc))
         summ2 = ofdm.vector_sum_vcc(total_subc)
         c2m2 =gr.complex_to_mag(total_subc)
         self.connect( estimated_CTF,summ2 ,gr.null_sink(gr.sizeof_gr_complex))
         self.connect( estimated_CTF, c2m2,gr.null_sink(gr.sizeof_float*total_subc))
         log_to_file( self, ifft2, "data/CIR2.compl" )
         log_to_file( self, summ2, "data/CTFsumm2.compl" )
         log_to_file( self, estimated_CTF, "data/CTF2.compl" )
         log_to_file( self, c2m2, "data/CTFmag2.float" )
         
        ## Postprocess the CTF estimate
        ## CTF -> inverse CTF (for equalizer)
        ## CTF -> norm |.|^2 (for CTF display)
        ctf_postprocess = ofdm.fbmc_postprocess_CTF_estimate( total_subc )
        
        self.connect( help2, ctf_postprocess )
        #estimated_SNR = ( ctf_postprocess, 0 )
        disp_CTF = ( ctf_postprocess, 0 )
        #self.connect(estimated_SNR,out_snr_pream)
        #log_to_file( self, estimated_SNR, "data/fbmc_SNR.float" )
        
        #Disable measured SNR output
        #terminate_stream(self, estimated_SNR)
        #self.connect(blocks.vector_source_f([10.0],True) ,out_snr_pream)
    
#     if options.disable_equalization or options.ideal:
#       terminate_stream(self, inv_estimated_CTF)
#       inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
#       inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
#       self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
#       #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
#       inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
#       self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
#       print "Disabled equalization stage"
    '''
    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset

    nondata_blocks = []
    for i in range(config.frame_length):
      if i in config.training_data.pilotsym_pos:
        nondata_blocks.append(i)
        
    print"\t\t\t\t\tnondata_blocks=",nondata_blocks
    pilot_subc = block_header.pilot_tones
    pilot_subcarriers = block_header.pilot_subc_sym
    print "PILOT SUBCARRIERS: ", pilot_subcarriers
        
    phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
                                               nondata_blocks, pilot_subcarriers,0 )
    self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
    self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
    self.connect( frame_start, ( phase_tracking, 2 ) ) ##
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer
      
    
    if options.disable_phase_tracking or options.ideal:
      terminate_stream(self, phase_tracking)
      print "Disabled phase tracking stage"
    else:
      ofdm_blocks = phase_tracking
    '''
    ## Channel Equalizer
    ##equalizer = ofdm.channel_equalizer( total_subc )
    ##self.connect( ofdm_blocks,       ( equalizer, 0 ) )
    ##self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
    ##self.connect( frame_start,       ( equalizer, 2 ) )
    ##ofdm_blocks = equalizer
    #log_to_file(self, equalizer,"data/equalizer_siso.compl")
    
    
    #log_to_file(self, ofdm_blocks, "data/equalizer.compl")

    ## LMS Phase tracking
    ## Track residual frequency offset and sampling clock frequency offset

    nondata_blocks = []
    for i in range(config.frame_length):
      if i in config.training_data.pilotsym_pos:
        nondata_blocks.append(i)
        
    print"\t\t\t\t\tnondata_blocks=",nondata_blocks
    pilot_subc = block_header.pilot_tones
    pilot_subcarriers = block_header.pilot_subc_sym
    print "PILOT SUBCARRIERS: ", pilot_subcarriers
    
    if options.scatter_plot_before_phase_tracking:
      self.before_phase_tracking = equalizer
        

    ## Output connections

    self.connect( ofdm_blocks, out_ofdm_blocks )
    self.connect( frame_start, out_frame_start )
    if options.ideal is False and options.ideal2 is False:
        self.connect( disp_CTF, out_disp_ctf )
    else:
        self.connect( blocks.vector_source_f([1.0]*total_subc),blocks.stream_to_vector(gr.sizeof_float,total_subc), out_disp_ctf )
    
    

    if log:
      log_to_file( self, sc_metric, "data/sc_metric.float" )
      log_to_file( self, gi_metric, "data/gi_metric.float" )
      log_to_file( self, morelli_foe, "data/morelli_foe.float" )
      log_to_file( self, lms_fir, "data/lms_fir.float" )
      log_to_file( self, sampler_preamble, "data/preamble.compl" )
      log_to_file( self, sync, "data/sync.compl" )
      log_to_file( self, frequency_shift, "data/frequency_shift.compl" )
      log_to_file( self, fft, "data/fft.compl")
      log_to_file( self, fft, "data/fft.float", mag=True )
      
      if vars().has_key( 'subcarrier_mask' ):
        log_to_file( self, subcarrier_mask, "data/subcarrier_mask.compl" )
      
      log_to_file( self, ofdm_blocks, "data/ofdm_blocks_out.compl" )
      log_to_file( self, frame_start, "data/frame_start.float", 
                   char_to_float=True )
      
      log_to_file( self, sampled_chest_preamble, 
                   "data/sampled_chest_preamble.compl" )
      log_to_file( self, LS_channel_estimator, 
                   "data/ls_channel_estimator.compl" )
      log_to_file( self, LS_channel_estimator, 
                   "data/ls_channel_estimator.float", mag=True )
      
      if "ctf_mse_enhancer" in locals(): 
        log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.compl" )
        log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.float", 
                     mag=True )
      
      log_to_file( self, (ctf_postprocess,0), "data/inc_estimated_ctf.compl" )
      log_to_file( self, (ctf_postprocess,1), "data/disp_ctf.float" )
      
      log_to_file( self, equalizer, "data/equalizer.compl" )
      log_to_file( self, equalizer, "data/equalizer.float", mag=True )
      
      log_to_file( self, phase_tracking, "data/phase_tracking.compl" )