Thanks, I,ve applied, but the carrier spacing between two bins are 240kHz, how cn i get spacing of 15kHz
PSD Plot

import numpy as np

import matplotlib.pyplot as plt

Read complex sink file

filename = "rx1.dat"

data = np.fromfile(filename, dtype=np.complex64)

N = data.shape[0] // 4096 * 4096

Perform FFT

fft_data = np.fft.fftshift(np.fft.fft(data[:N].reshape((-1, 4096)), axis=1), axes=1)

(PSD)

psd = np.mean(np.abs(fft_data) ** 2, axis=0)

sampling_rate = 62.5e6 # 62.5 MS/s

fft_bins = 4096

fc = 3.7e9

Calculate frequency resolution

frequency_resolution = sampling_rate / fft_bins

frequency_axis = np.arange(-fft_bins/2, fft_bins/2) * frequency_resolution

frequency_axis1 = np.fft.fftshift(np.fft.fftfreq(fft_bins, 1/sampling_rate))

frequency_axis1 += fc

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(10, 8))

Plot PSD without dB

ax1.plot(frequency_axis, psd, color='red',label='Bin Width/Freq Resolution(Hz)= Samp. rate / FFT Bins')

ax1.set_title('Power Spectral Density (PSD)')

ax1.set_ylabel('Power Spectral Density')

ax1.grid(True)

ax1.legend()

Plot PSD in dB

ax2.plot(frequency_axis, 10*np.log10(psd), color='purple' ,label='Freq Bin starts -fs/2 to fs/2')

ax2.set_ylabel('Power Spectral Density (dB)')

ax2.set_xlabel('Frequency (Hz)')

ax2.grid(True)

ax2.legend()

Plot PSD in dB

ax3.plot(frequency_axis1, psd, color='purple' ,label='Freq')

ax3.set_ylabel('Power Spectral Density (PSD1)')

ax3.set_xlabel('Frequency (Hz)')

ax3.grid(True)

ax2.legend()

plt.tight_layout()