A method of soft decoding received signals. The method comprising defining quantisation intervals for a signal value range, determining a number of bits in each quantisation interval that are connected to unsatisfied constraints, providing, the number of bits in each quantisation interval that are connected to unsatisfied constraints, as an input to a trained model, wherein the trained model has been trained to cover an operational range of a device for soft decoding of signals, determining, using the trained model, a log likelihood ratio for each quantisation interval, and performing soft decoding using the log likelihood ratios.

A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

A method of correcting data stored in a memory device includes: applying an iterative decoder to the data; determining a total number of rows in first data the decoder attempted to correct; estimating first visible error rows among the total number that continue to have an error after the attempt; estimating residual error rows among the total number that no longer have an error after the attempt; determining second visible error rows in second data of the decoder that continue to have an error by permuting indices of the residual error rows according to a permutation; and correcting the first data using the first visible error rows.

Embodiments of the present disclosure provide an encoding/decoding method, apparatus, and system. The method includes: encoding information bits to obtain a first-level encoded code word; obtaining a sorting value of each check bit of the first-level encoded code word, and adjusting each check bit to a corresponding position according to the sorting value of each check bit, where the sorting value refers to a value of S when the check bit is related to first S information bits of the information bits in the first-level encoded code word, and S is a non-zero integer; and performing second-level encoding on the first-level encoded code word after positions of the check bits are adjusted, thereby obtaining a second-level encoded code word. The present disclosure is applicable to various communication systems.

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.

A method of decoding a polar coded signal includes determining channel reliabilities for a plurality of polar coded bit channels in a data communication system including a plurality of frozen bit channels and non-frozen bit channels, selecting a frozen bit channel, calculating a likelihood value for a bit estimate associated with the frozen bit channel, generating a hard decision value for the bit estimate in response to the likelihood value, comparing the hard decision value for the bit estimate to a known value of a frozen bit transmitted on the frozen bit channel, in response to determining that the hard decision value for the bit estimate differs from the known value of the frozen bit transmitted on the frozen bit channel, updating an accumulated uncertainty, comparing the accumulated uncertainty to a threshold, and determining that a decoding error has occurred in response to the comparison.

A method of correcting one or more bit errors in a memory device includes retrieving a codeword from a memory device. The codeword includes a data and an error correcting code. The method further includes determining whether the one or more bit errors are present in the retrieved codeword and correcting the retrieved codeword for the one bit error in response to determining one bit error is present in the retrieved codeword. The method also includes flipping a bit of the retrieved codeword in response to determining a plurality of bit errors is present in the retrieved codeword and correcting the retrieved codeword for the plurality of bit errors based on the bit-flipped codeword.

The disclosure provides a method and a polar code decoder for determining a to-be-flipped bit position when performing a successive cancellation list flip operation. The method includes: obtaining a polar code decoding tree generated by performing a successive cancellation list (SCL) operation on a polar code segment, and the polar code segment includes multiple bit positions, and each bit position in the polar code decoding tree includes multiple surviving paths and multiple pruned paths; in a post-processing stage for the SCL operation, estimating a correct path probability of each of the surviving paths and the pruned paths of the i-th bit position and accordingly estimating a reliability for the i-th bit position; selecting a specific bit position among the bit positions based on the reliability of each bit position; and performing an SCL flip operation on the polar code decoding tree based on the specific bit position.

A method, system, and ASIC chip for comparing a bit error rate (BER) to a forward error correction (FEC) threshold to determine a Q margin for a codeblock; wherein the BER corresponds to the number of errors in a given amount of data; where a codeblock of a FEC corresponds to the given amount of data; wherein the FEC threshold corresponds to the maximum amount of errors per codeblock that the FEC is able to remove per given amount of data; wherein the Q margin corresponds to a difference between the BER and the FEC threshold.