Neural-network-optimized degree-specific weights for LDPC minsum decoding

A decoder for a low-density parity-check (LDPC) code, comprising:

• variable nodes connected to check nodes, where the variable nodes and check nodes are implemented in at least one of a programmable device and an integrated circuit;
• wherein the connections between variable nodes and check nodes are structured according to a protograph having a protomatrix;
• passing of messages between the variable nodes and the check nodes;
• message weighting in which at least a portion of the messages are weighted using weights determined by a neural network, where the neural network is implemented in at least one of a programmable device and an integrated circuit;
• and
• wherein weighted edges that correspond to the same row of a protomatrix of the protograph are constrained to have the same weight.

A decoder for a low-density parity-check (LDPC) code, comprising:

• variable nodes connected to check nodes, where the variable nodes and check nodes are implemented in at least one of a programmable device and an integrated circuit;
• wherein connections between variable nodes and check nodes are structured according to a protograph having a protomatrix;
• passing of messages between the variable nodes and the check nodes;
• wherein at least a portion of the messages are weighted using weights determined by a neural network, where the neural network is implemented in at least one of a programmable device and an integrated circuit;
• and
• wherein said weighted edges that correspond to the same column of the protomatrix of the protograph are constrained to have the same weight.