Understanding and converting Matlab's coarse frequency compensation function

Question

I am trying to understand and convert to C Matlab's coarse frequency compensator the documentation for which can be found here: Documentation

Matlab's design itself is based on this IEEE paper: Carrier Frequency Recovery in All-Digital Modems for Burst-Mode Transmissions

I want to translate the correlation based algorithm for QPSK modulation; for example the invocation of such an object in Matlab would look like this:

cfc = comm.CoarseFrequencyCompensator('Modulation', 'QPSK', ...
                                      'Algorithm', 'Correlation-based', ...
                                      'MaximumFrequencyOffset', 12.5e3, ...
                                      'SampleRate',400000);

The documentation states that the estimate is given by:

$estimate=\frac{f_{samp}}{\pi(L+1)}arg\{\sum_{k=1}^{L}R(k)\}$

where

$L = round(\frac{f_{samp}}{f_{max}}) - 1$

$R(k) = \frac{1}{N-k}\sum_{i=k+1}^{N}r_{i}r^{*}_{i-k}$, autocorrelation function,

$r_k = e^{j(2\pi\Delta f k T_{s} + \theta)}$, model of received signal

$r^{*}_{k} = e^{-j(2\pi\Delta f k T_{s} + \theta)}$, is the complex conjugate of $r_{k}$

$N = \frac{L+1}{M} $, number of samples

$M = 4$, because for QPSK there are four possible symbols

My C code:

double complex autocorrelation_func(double complex* input, 
                                    double complex* conjinput, 
                                    int k, int input_size)
{
    double complex auto_corr_sum = 0+0*I;

    for(int i = 0 + k; i < input_size; i++ )
    {
        auto_corr_sum += input[i]*conjinput[i];
    }
    auto_corr_sum *= (1/(input_size-k));

    return auto_corr_sum;
}


double coarse_freq_comp(double complex* input, 
                        double complex* output, 
                        int input_size, int mod_order, 
                        double max_freq_offset, 
                        double sample_rate )
{
    int auto_corr_seq = round(sample_rate/max_freq_offset)-1;
    int num_samples = (auto_corr_seq+1)/mod_order;
    double mult_const = sample_rate/((auto_corr_seq+1)*M_PI);
    double complex input_conjugated[input_size];
    double complex auto_corr_sum = 0 + 0*I;
    double offset_est = 0;

    for(int ndx = 0; ndx < input_size; ndx++)
    {
        input_conjugated[ndx] = conj(input[ndx]);
    }

    for(int i = 0; i < num_samples; i++)
    {
        auto_corr_sum += autocorrelation_func(input, input_conjugated, i, input_size);
    }

    offset_est = mult_const*catan(auto_corr_sum);

    return offset_est;
}

Questions:

How do I apply the estimate to the input signal to get a compensated output signal?

What is wrong with my C code? I am not getting the same estimate value that I get for a given complex array in Matlab. I must be doing something wrong but this isn't obvious to me.

Understanding and converting Matlab's coarse frequency compensation function

0 Answers0