The current MAP decoder implementation is for coding rate 1/2 but assumes that the code is systematic (based on the input parameters).
Is it possible to decode non-systematic codes like the one from the example conv_encode_decode.py with this algorithm?
# =============================================================================
# Convolutional Code 1: G(D) = [1+D^2, 1+D+D^2]
# Standard code with rate 1/2
# =============================================================================
# Number of delay elements in the convolutional encoder
memory = np.array(2, ndmin=1)
# Generator matrix
g_matrix = np.array((0o5, 0o7), ndmin=2)
# Create trellis data structure
trellis1 = cc.Trellis(memory, g_matrix)
The output of map_decode() only provides LLRs for the systematic symbols, which is just half of the whole message.
The current MAP decoder implementation is for coding rate 1/2 but assumes that the code is systematic (based on the input parameters). Is it possible to decode non-systematic codes like the one from the example conv_encode_decode.py with this algorithm?
The output of map_decode() only provides LLRs for the systematic symbols, which is just half of the whole message.