GNU Radio 3.6.5 C++ API

gr_pfb_clock_sync_fff Class Reference

Timing synchronizer using polyphase filterbanks. More...

#include <gr_pfb_clock_sync_fff.h>

Inheritance diagram for gr_pfb_clock_sync_fff:
gr_block gr_basic_block gr_msg_accepter gruel::msg_accepter

List of all members.

Public Member Functions

 ~gr_pfb_clock_sync_fff ()
void set_taps (const std::vector< float > &taps, std::vector< std::vector< float > > &ourtaps, std::vector< gr_fir_fff * > &ourfilter)
std::vector< float > channel_taps (int channel)
std::vector< float > diff_channel_taps (int channel)
void print_taps ()
void print_diff_taps ()
void set_alpha (float alpha)
void set_beta (float beta)
void set_max_rate_deviation (float m)
bool check_topology (int ninputs, int noutputs)
 Confirm that ninputs and noutputs is an acceptable combination.
int general_work (int noutput_items, gr_vector_int &ninput_items, gr_vector_const_void_star &input_items, gr_vector_void_star &output_items)
 compute output items from input items

Friends

GR_CORE_API
gr_pfb_clock_sync_fff_sptr 
gr_make_pfb_clock_sync_fff (double sps, float gain, const std::vector< float > &taps, unsigned int filter_size, float init_phase, float max_rate_deviation)

Detailed Description

Timing synchronizer using polyphase filterbanks.

This block performs timing synchronization for PAM signals by minimizing the derivative of the filtered signal, which in turn maximizes the SNR and minimizes ISI.

This approach works by setting up two filterbanks; one filterbank contains the signal's pulse shaping matched filter (such as a root raised cosine filter), where each branch of the filterbank contains a different phase of the filter. The second filterbank contains the derivatives of the filters in the first filterbank. Thinking of this in the time domain, the first filterbank contains filters that have a sinc shape to them. We want to align the output signal to be sampled at exactly the peak of the sinc shape. The derivative of the sinc contains a zero at the maximum point of the sinc (sinc(0) = 1, sinc(0)' = 0). Furthermore, the region around the zero point is relatively linear. We make use of this fact to generate the error signal.

If the signal out of the derivative filters is d_i[n] for the ith filter, and the output of the matched filter is x_i[n], we calculate the error as: e[n] = (Re{x_i[n]} * Re{d_i[n]} + Im{x_i[n]} * Im{d_i[n]}) / 2.0 This equation averages the error in the real and imaginary parts. There are two reasons we multiply by the signal itself. First, if the symbol could be positive or negative going, but we want the error term to always tell us to go in the same direction depending on which side of the zero point we are on. The sign of x_i[n] adjusts the error term to do this. Second, the magnitude of x_i[n] scales the error term depending on the symbol's amplitude, so larger signals give us a stronger error term because we have more confidence in that symbol's value. Using the magnitude of x_i[n] instead of just the sign is especially good for signals with low SNR.

The error signal, e[n], gives us a value proportional to how far away from the zero point we are in the derivative signal. We want to drive this value to zero, so we set up a second order loop. We have two variables for this loop; d_k is the filter number in the filterbank we are on and d_rate is the rate which we travel through the filters in the steady state. That is, due to the natural clock differences between the transmitter and receiver, d_rate represents that difference and would traverse the filter phase paths to keep the receiver locked. Thinking of this as a second-order PLL, the d_rate is the frequency and d_k is the phase. So we update d_rate and d_k using the standard loop equations based on two error signals, d_alpha and d_beta. We have these two values set based on each other for a critically damped system, so in the block constructor, we just ask for "gain," which is d_alpha while d_beta is equal to (gain^2)/4.

The block's parameters are:

  • sps: The clock sync block needs to know the number of samples per symbol, because it defaults to return a single point representing the symbol. The sps can be any positive real number and does not need to be an integer.
  • taps: One of the most important parameters for this block is the taps of the filter. One of the benefits of this algorithm is that you can put the matched filter in here as the taps, so you get both the matched filter and sample timing correction in one go. So create your normal matched filter. For a typical digital modulation, this is a root raised cosine filter. The number of taps of this filter is based on how long you expect the channel to be; that is, how many symbols do you want to combine to get the current symbols energy back (there's probably a better way of stating that). It's usually 5 to 10 or so. That gives you your filter, but now we need to think about it as a filter with different phase profiles in each filter. So take this number of taps and multiply it by the number of filters. This is the number you would use to create your prototype filter. When you use this in the PFB filerbank, it segments these taps into the filterbanks in such a way that each bank now represents the filter at different phases, equally spaced at 2pi/N, where N is the number of filters.
  • filter_size (default=32): The number of filters can also be set and defaults to 32. With 32 filters, you get a good enough resolution in the phase to produce very small, almost unnoticeable, ISI. Going to 64 filters can reduce this more, but after that there is very little gained for the extra complexity.
  • init_phase (default=0): The initial phase is another settable parameter and refers to the filter path the algorithm initially looks at (i.e., d_k starts at init_phase). This value defaults to zero, but it might be useful to start at a different phase offset, such as the mid-point of the filters.
  • max_rate_deviation (default=1.5): The next parameter is the max_rate_devitation, which defaults to 1.5. This is how far we allow d_rate to swing, positive or negative, from 0. Constraining the rate can help keep the algorithm from walking too far away to lock during times when there is no signal.
  • osps: note that unlike the ccf version of this algorithm, this block does not have a setting for the number of output samples per symbol. This is mostly because it should not be necessary as the reason for having multiple output sps is to perform equalization and the equalizers will take in complex numbers in order to do magnitude and phase correction.

Constructor & Destructor Documentation

gr_pfb_clock_sync_fff::~gr_pfb_clock_sync_fff ( )

Member Function Documentation

std::vector<float> gr_pfb_clock_sync_fff::channel_taps ( int  channel)

Returns the taps of the matched filter

bool gr_pfb_clock_sync_fff::check_topology ( int  ninputs,
int  noutputs 
) [virtual]

Confirm that ninputs and noutputs is an acceptable combination.

Parameters:
ninputsnumber of input streams connected
noutputsnumber of output streams connected
Returns:
true if this is a valid configuration for this block.

This function is called by the runtime system whenever the topology changes. Most classes do not need to override this. This check is in addition to the constraints specified by the input and output gr_io_signatures.

Reimplemented from gr_basic_block.

std::vector<float> gr_pfb_clock_sync_fff::diff_channel_taps ( int  channel)

Returns the taps in the derivative filter

int gr_pfb_clock_sync_fff::general_work ( int  noutput_items,
gr_vector_int ninput_items,
gr_vector_const_void_star input_items,
gr_vector_void_star output_items 
) [virtual]

compute output items from input items

Parameters:
noutput_itemsnumber of output items to write on each output stream
ninput_itemsnumber of input items available on each input stream
input_itemsvector of pointers to the input items, one entry per input stream
output_itemsvector of pointers to the output items, one entry per output stream
Returns:
number of items actually written to each output stream, or -1 on EOF. It is OK to return a value less than noutput_items. -1 <= return value <= noutput_items

general_work must call consume or consume_each to indicate how many items were consumed on each input stream.

Reimplemented from gr_block.

void gr_pfb_clock_sync_fff::print_diff_taps ( )

Print all of the filterbank taps of the derivative filter to screen.

void gr_pfb_clock_sync_fff::print_taps ( )

Print all of the filterbank taps to screen.

void gr_pfb_clock_sync_fff::set_alpha ( float  alpha) [inline]

Set the gain value alpha for the control loop

void gr_pfb_clock_sync_fff::set_beta ( float  beta) [inline]

Set the gain value beta for the control loop

void gr_pfb_clock_sync_fff::set_max_rate_deviation ( float  m) [inline]

Set the maximum deviation from 0 d_rate can have

void gr_pfb_clock_sync_fff::set_taps ( const std::vector< float > &  taps,
std::vector< std::vector< float > > &  ourtaps,
std::vector< gr_fir_fff * > &  ourfilter 
)

Resets the filterbank's filter taps with the new prototype filter


Friends And Related Function Documentation

GR_CORE_API gr_pfb_clock_sync_fff_sptr gr_make_pfb_clock_sync_fff ( double  sps,
float  gain,
const std::vector< float > &  taps,
unsigned int  filter_size,
float  init_phase,
float  max_rate_deviation 
) [friend]

Build the polyphase filterbank timing synchronizer.

Parameters:
sps(double) The number of samples per second in the incoming signal
gain(float) The alpha gain of the control loop; beta = (gain^2)/4 by default.
taps(vector<int>) The filter taps.
filter_size(uint) The number of filters in the filterbank (default = 32).
init_phase(float) The initial phase to look at, or which filter to start with (default = 0).
max_rate_deviation(float) Distance from 0 d_rate can get (default = 1.5).

The documentation for this class was generated from the following file: