A decoder performs: computing (S501) a value (i,j) of a performance-improvement metric for each kernel K.sub.i,j; and sorting (S502) the kernels in a list in decreasing order of the values (i,j). The decoder then performs a beliefs propagation iterative process as follows: updating (S503) output beliefs for the W top kernels of the list , and propagating said output beliefs as input beliefs of the neighbour kernels of said W top kernels; updating (S504) output beliefs for each neighbour kernel of said W top kernels following update of their input beliefs, and re-computing (S505) the performance-improvement metric value (i,j) for each said neighbour kernel; setting (S505) the performance-improvement metric for said W top kernels to a null value; and re-ordering (S506) the kernels in the list . Then, the decoder repeats the beliefs propagation iterative process until a stop condition is met.

Systems and methods for improving the error floor performance in decoding generalized product codes (GPC) are described. The systems and methods can implement a two stage process to decode a GPC block code and break a stall error pattern for the decoding the block code. In the first stage, erroneuous bits in a codeword can be flagged. In the second stage, some of these bits and related bits in a codeword can be toggled to generate one or more test patterns. The test patterns can be decoded and one of them can be selected using a particular selection criteria to ultimately break the stall error pattern and improve the error floor performance.

A decoding system, a decoding controller, and a decoding control method are provided. In the decoding system, a decoding controller is disposed between two adjacent decoders. The decoding controller determines whether to perform turn-off based on a non-turn-off indication received by a previous-stage decoder, a turn-off indication output by the previous-stage decoder, and historical turn-off probability statistics. This is equivalent to adding a buffer zone between the two adjacent decoders.

Methods, systems, and apparatuses include receiving a codeword stored in a memory device. The codeword is error corrected for a first number of iterations. The error correction includes traversing the codeword according to a first order. The codeword is error corrected for a second number of the iterations. The error correction of the codeword during a second iteration from the second number of iterations includes traversing the codeword according to a second order that is different from the first order.

Embodiments herein provide a method for predicting iterations for decoding an encoded data at an electronic device. The method includes: receiving, by the electronic device, the encoded data; detecting, by the electronic device, signal parameters associated with the encoded data; predicting, by the electronic device, one of a cyclic redundancy check (CRC) failure, CRC success, and a CRC uncertainty in iterations for decoding the encoded data based on the signal parameters using a Neural Network (NN) model.

The present disclosure includes apparatuses and methods related to stopping criteria for layered iterative error correction. A number of methods can include receiving a codeword with an error correction circuit, iteratively error correcting the codeword with the error correction circuit including parity checking the codeword on a layer-by-layer basis and updating the codeword after each layer. Methods can include stopping the iterative error correction in response to a parity check being correct for a particular layer.

A polar code decoding apparatus according to an embodiment includes a divider configured to generate a decoding tree in which a plurality of nodes including one or more critical sets for a polar-encoded codeword are formed in a hierarchical structure, and divide the decoding tree into one or more partitions, each partition equally including lowest nodes of the decoding tree, a determiner configured to determine a memory size for storing a primary decoding result based on a specific partition, the specific partition being selected from among the one or more partitions based on the number of critical sets included in each partition, and a decoder configured to decode the codeword primarily by using a successive cancellation (SC) decoding technique.

Methods, systems, and apparatuses include receiving a codeword stored in a memory device. The codeword is error corrected for a first number of iterations. The error correction includes traversing the codeword according to a first order. The codeword is error corrected for a second number of the iterations. The error correction of the codeword during a second iteration from the second number of iterations includes traversing the codeword according to a second order that is different from the first order.

Methods, systems, and apparatuses include receiving a codeword stored in a memory device. The codeword is error corrected for a first number of iterations. The error correction includes traversing the codeword according to a first order. The codeword is error corrected for a second number of the iterations. The error correction of the codeword during a second iteration from the second number of iterations includes traversing the codeword according to a second order that is different from the first order.

Systems and methods for ACM trajectory include receiving data at a communications receiver; decoding the received data based on a selected MODCOD; monitoring a number of iterations used to decode the data using the selected MODCOD; comparing the number of iterations used to decode the data using the first selected MODCOD to a reference number of iterations; and adjusting a SNR threshold value for the selected MODCOD where the number of iterations used to decode the data using the first selected MODCOD is greater than the reference number of iterations.