Channel

Module containing the functions that cover the channel characteristics.

Additive White Gaussian Noise

channel.AWGN(sig, SNR, K)

Adds noise to the signal based on the proposed SNR.

Parameters:

• sig (1D array of floats) – IF signal.

• SNR (float) – Signal to noise ratio in dB.

Returns:

sig_n – Signal with noise based on the SNR.

Return type:

1D array of floats

import numpy as np

def AWGN(sig, SNR, K):
   sig_abs2 = [abs(s)**2 for s in sig]
   P = (K * sum(sig_abs2)) / len(sig_abs2)
   gamma = 10**(SNR/10)
   N0 = P / gamma
   n = np.sqrt(N0 / 2) * np.random.standard_normal(len(sig))
   sig_n = sig + n
   return sig_n