Methods and systems for managing decoding of control channel on a multi-SIM UE. A method includes receiving, by the UE, the plurality of control channels from at least one Base Station (BS), the plurality of control channels corresponding to a plurality of Subscriber Identity Modules (SIMs), selecting, by the UE, a respective decoder for each of the plurality of SIMs, and decoding, by the UE, each respective control channel among the plurality of control channels using the respective decoder for a respective SIM among the plurality of SIMs, the respective SIM corresponding to the respective control channel.

Hard errors are determined for an unsuccessful decoding of codeword bits read from NAND memory cells via a read channel and input to a low-density parity check (LDPC) decoder. A bit error rate (BER) for the hard errors is estimated and BER for the read channel is estimated. Hard error regions are found using a single level cell (SLC) reading of the NAND memory cells. A log likelihood ratio (LLR) mapping of the codeword bits input to the LDPC decoder is changed based on the hard error regions, the hard error BER, and/or the read channel BER.

A mobile electronic device may include a memory device and a memory controller including an error correction code (ECC) encoder to encode data, a constrained channel encoder configured to encode an output of the ECC encoder based on one or more constraints, a reinforcement learning pulse programming (RLPP) component configured to identify a programming algorithm for programming the data to the memory device, an expectation maximization (EM) signal processing component configured to receive a noisy multi-wordline voltage vector from the memory device and classify each bit of the vector with a log likelihood ration (LLR) value, a constrained channel decoder configured to receive a constrained vector from the EM signal processing component and produce an unconstrained vector, and an ECC decoder configured to decode the unconstrained vector. A machine learning interference cancellation component may operate based on or independent of input from the EM signal processing component.

The present invention is directed to communication systems and methods. According to a specific embodiment, FEC data streams from multiple FEC data lanes are received. First stage interleaving and inner encoding are performed on the FEC data streams to generate inner encoded data streams. A second stage interleaving process is performed to interleave the inner encoded data streams. There are other embodiments as well.

The present disclosure relates to a 5.sup.th generation (5G) or pre-5G communication system for supporting a data transmission rate higher than that of a post-4.sup.th generation (4G) communication system such as Long Term Evolution (LTE). The present disclosure is for decoding a polar code in a communication system. An operation method of a reception device comprises the steps of: receiving data encoded by means of a polar code and comprising a plurality of bits; confirming one or more bits which do not require a decoding operation among the plurality of bits; and decoding at least some of the bits remaining after excluding the one or more bits.

Systems and methods are provided for performing error recovery using LLRs generated from multi-read operations. A method may comprise selecting a set of decoding factors for a multi-read operation to read a non-volatile storage device multiple times. The set of decoding factors may include an aggregation mode for aggregating read results of multiple reads. The method may further comprise issuing a command to the non-volatile storage device to read user data according to the set of decoding factors, generating a plurality of Log-Likelihood Ratio (LLR) values using a mapping engine from a pre-selected set of LLR value magnitudes based on the set of decoding factors, obtaining an aggregated read result in accordance with the aggregation mode and obtaining an LLR value from the plurality of LLR values using the aggregated read result as an index.

A decoding method of low-density parity-check (LDPC) codes based on partial average residual belief propagation includes the following steps: S1: calculating a size of a cluster π in a protograph based on a code length m and a code rate of a target codeword; S2: pre-computing an edge residual r.sub.c.sub.i.sub..fwdarw.v.sub.j corresponding to each edge from a variable node to a check node in a check matrix H; S3: calculating, based on π, a partial average residual (PAR) value corresponding to each cluster in the check matrix H; S4: sorting m/π clusters in descending order of corresponding PAR values, and updating an edge with a largest edge residual in each cluster; S5: updating edge information m.sub.c.sub.i.sub..fwdarw.v.sub.i from a check node c.sub.i to a variable node v.sub.j, and then updating a log-likelihood ratio (LLR) value L(v.sub.j) of the variable node v.sub.j; and S6: after the updating, making a decoding decision.

The method includes: reading a memory cell having a encoded information bit, so as to obtain an LLR value of a current memory cell with reference to a pre-established LLR table according to a storage time, a threshold voltage partition and a comprehensive distribution corresponding to the current memory cell during reading; and performing a soft decoding operation on a codeword in the memory cell having the encoded information bit according to the read LLR value of the current memory cell, wherein the comprehensive distribution of the current memory cell is determined according to an influence of a memory cell adjacent to the current memory cell on a distribution of the current memory cell; an input of the pre-established LLR table comprises a storage time, a threshold voltage partition and a comprehensive distribution, and an output of the pre-established LLR table comprises an LLR value.

A decoding method of low-density parity-check (LDPC) codes based on partial average residual belief propagation includes the following steps: S1: calculating a size of a cluster π in a protograph based on a code length m and a code rate of a target codeword; S2: pre-computing an edge residual r.sub.c.sub.i.sub..fwdarw.v.sub.j corresponding to each edge from a variable node to a check node in a check matrix H; S3: calculating, based on π, a partial average residual (PAR) value corresponding to each cluster in the check matrix H; S4: sorting m/π clusters in descending order of corresponding PAR values, and updating an edge with a largest edge residual in each cluster; S5: updating edge information m.sub.c.sub..fwdarw.v.sub.i from a check node c.sub.i to a variable node v.sub.j, and then updating a log-likelihood ratio (LLR) value L(v.sub.j) of the variable node v.sub.j; and S6: after the updating, making a decoding decision.

Methods, systems and devices for forward error correction in orthogonal time frequency space (OTFS) communication systems using non-binary low-density parity-check (NB-LDPC) codes are described. One exemplary method for forward error correction includes receiving data, encoding the data via a non-binary low density parity check (NB-LDPC) code, wherein the NB-LDPC code is characterized by a matrix with binary and non-binary entries, modulating the encoded data to generate a signal, and transmitting the signal. Another exemplary method for forward error correction includes receiving a signal, demodulating the received signal to produce data, decoding the data via a NB-LDPC code, wherein the NB-LDPC code is characterized by a matrix with binary and non-binary entries, and providing the decoded data to a data sink.