36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
"""Utility functions relating to noise and SNR calculations."""
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import numpy as np
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def get_noise_variance_from_SNR(SNR: float, n: int, k: int) -> float:
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"""Calculate the variance of the noise from an SNR and the signal amplitude.
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:param SNR: Signal-to-Noise-Ratio in dB (E_b/N_0)
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:param n: Length of a codeword of the used code
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:param k: Length of a dataword of the used code
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:return: Variance of the noise
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"""
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# noise_amp = (1 / np.sqrt(SNR_linear)) * signal_amp
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SNR_linear = 10 ** (SNR / 10)
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variance = 1 / (2 * (k/n) * SNR_linear)
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return variance
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def add_awgn(c: np.array, SNR: float, n: int, k: int) -> np.array:
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"""Add Additive White Gaussian Noise to a data vector. As this function adds random noise to
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the input, the output changes, even if it is called multiple times with the same input.
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:param c: Binary vector representing the data to be transmitted
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:param SNR: Signal-to-Noise-Ratio in dB
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:param n: Length of a codeword of the used code
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:param k: Length of a dataword of the used code
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:return: Data vector with added noise
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"""
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noise_var = get_noise_variance_from_SNR(SNR, n, k)
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y = c + np.sqrt(noise_var) * np.random.normal(size=c.size)
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return y
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