The FFT-based cross-correlation is done as follows:
TX = np.fft.fft(tx)
RX = np.fft.fft(rx)
CORR = np.multiply(TX, np.conjugate(RX))
corr = np.real(np.fft.ifft(corr))
Here is a NumPy script that tries a solution.
It does the following:
create a TX and delayed RX signal that similar to your waveform (a sine wave modulated by an envelope cosine with zeros at ...
I wanted to ask what are the techniques which can be used to extract this sub-band data?
That's a description of a filter bank.
Yes, the FFT can be used for such applications. You'll find that OFDM, which powers DVB-T, 4G/5G, WiFi, … (basically all high-speed wireless terrestrial links) does exactly that.
You'll also find that if you find the inherent sinc-...
This will should work fine.
For each realization $k$, we can write
$$y_k[n] = x[n] + w_k[n] + q_k[n] = x[n] + v_k[n]$$
So basically define the "effective" noise $v[n]$ as the sum of the analog noise and the quantization noise $q[n]$. Averaging will converge towards the desired signal $x[n]$ as long as two conditions are met:
$v[n]$ is uncorrelated ...
IF a 1 is always represented by the waveform in the figure, you can use that waveform as the matched filter response.
However, it sounds like the waveform could be anything as long as there are some pulses in it. In that case, the matched filter should be a single pulse, and you'll have to count how many pulses were detected afterwards.
The non-Gaussian ...
The answer generally is yes- if the SNR is large enough then we can accurately estimate EVM just based on the raw decisions in the known constellation after all typical offsets have been properly corrected for (DC offset, IQ offset, phase offset, frequency offset, timing offset). In fact often the EVM is a measure of how good our corrections are for each of ...
Does it calculate the EVM of each equalized received symbol with a closest ideal symbol on the constellation and then average it out to give final EVM value?
You very rarely test EVM on a low-SNR signal that's not according to any standard, especially because if that signal doesn't adhere to any standard, there would be very little for your signal analyzer ...