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Andreas Tsouchlos 2022-11-07 11:07:24 +01:00
parent 78fd8bf95c
commit 2f1497b1b8
1 changed files with 11 additions and 6 deletions
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17
sw/decoders/proximal.py
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@ -2,13 +2,14 @@ import numpy as np
class ProximalDecoder: class ProximalDecoder:
"""Class implementing the Proximal Decoding algorithm. See "Proximal Decoding for LDPC Codes" by Tadashi """Class implementing the Proximal Decoding algorithm. See "Proximal Decoding for LDPC Codes"
Wadayama, and Satoshi Takabe. by Tadashi Wadayama, and Satoshi Takabe.
""" """
# TODO: How large should K be? # TODO: How large should K be?
# TODO: How large should eta be? # TODO: How large should eta be?
# TODO: How large should step_size be? # TODO: How large should step_size be?
def __init__(self, H: np.array, K: int = 100, step_size: float = 0.5, gamma: float = 0.05, eta: float = 1.1): def __init__(self, H: np.array, K: int = 100, step_size: float = 0.5, gamma: float = 0.05,
eta: float = 1.1):
"""Construct a new ProximalDecoder Object. """Construct a new ProximalDecoder Object.
:param H: Parity Check Matrix :param H: Parity Check Matrix
@ -25,7 +26,9 @@ class ProximalDecoder:
@staticmethod @staticmethod
def _L_awgn(s: np.array, y: np.array) -> np.array: def _L_awgn(s: np.array, y: np.array) -> np.array:
"""Variation of the negative log-likelihood for the special case of AWGN noise. See 4.1, p. 4.""" """Variation of the negative log-likelihood for the special case of AWGN noise.
See 4.1, p. 4.
"""
return s - y return s - y
# TODO: Is this correct? # TODO: Is this correct?
@ -84,9 +87,11 @@ class ProximalDecoder:
def decode(self, y: np.array) -> np.array: def decode(self, y: np.array) -> np.array:
"""Decode a received signal. The algorithm is detailed in 3.2, p.3. """Decode a received signal. The algorithm is detailed in 3.2, p.3.
This function assumes a BPSK-like modulated signal ([-1, 1]^n instead of [0, 1]^n) and an AWGN channel. This function assumes a BPSK-like modulated signal ([-1, 1]^n instead of [0, 1]^n)
and an AWGN channel.
:param y: Vector of received values. (y = x + n, where 'x' is element of [-1, 1]^m and 'n' is noise) :param y: Vector of received values. (y = x + w, where 'x' is element of [-1, 1]^n
and 'w' is noise)
:return: Most probably sent symbol :return: Most probably sent symbol
""" """
s = 0 s = 0