Signal-to-noise ratio estimation for broadband satellite-to-ground communication based on time-domain channel impulse response reconstruction

Signal-to-noise ratio (SNR) estimation is crucial for spectrum management and data transmission. However, the existing classical methods in satellite-to-ground (SG) communication links, particularly for broadband transmission and under ultra-low SNR conditions, often encounter substantial estimation errors. In this paper, a novel SNR estimation method based on time-domain channel impulse response (CIR) reconstruction is proposed. Least square (LS) algorithm in frequency domain and inverse fast Fourier transform (IFFT) with a rectangular window are employed to reconstructed CIR. The noise energy is calculated by computing the average energy outside the window. The signal power is obtained by subtracting the noise energy from the total energy inside the window. In addition, a numerical simulation with a signal bandwidth of 400 MHz is performed to evaluate the effectiveness of the proposed algorithm in real SG communication scenarios. The simulation results show that compared with existing classical methods, even under ultra-low SNR conditions, the proposed algorithm exhibits more accurate estimation ability and stronger resistance to frequency offset interference in nonterrestrial network (NTN) channels.