Examples include techniques to improve error correction using an exclusive OR (XOR) rebuild scheme that includes two uncorrectable codewords. Examples include generation of soft XOR codewords using bits of correctable codewords to rebuild a codeword read from a memory that has uncorrectable errors and adjust bit reliability information to generate a new codeword having correctable errors. Examples also include techniques to prevent mis-correction due to read reference voltage shifts using non-linear transformations.

A memory system including a memory device and a memory controller including a processor. The memory controller is configured to read outputs from the memory cells in response to a read command from a host and to convert the read outputs to a first codeword. The processor performs a first error correcting code (ECC) operation on the first codeword. The processor is further configured to apply, for each selected memory cell among the memory cells, a corresponding one of the read outputs and at least one related feature as input features to a machine learning algorithm to generate a second codeword, and the memory controller is configured to perform a second ECC operation on the second codeword, when the first ECC operation fails.

A method of operating a storage system is provided. The storage system includes memory cells and a memory controller, wherein each memory cell is an m-bit multi-level cell (MLC), where m is an integer, and the memory cells are arranged in m pages. The method includes determining initial LLR (log likelihood ratio) values for each of the m pages, comparing bit error rates in the m pages, identifying a programmed state in one of the m pages that has a high bit error rate (BER), and selecting an assist-read threshold voltage of the identified page. The method also includes performing an assist-read operation on the identified page using the assist-read threshold voltage, determining revised LLR values for the identified page based on results from the assist-read operation, and performing soft decoding using the revised LLR values for the identified page and the initial LLR values for other pages.

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.

It provides a method (300) for polar decoding a received signal into a number, N, of bits with Successive Cancellation List, SCL. The method (300) includes: at the i-th level of a binary tree for decoding the i-th bit of the N bits, where 1≤i≤N: when the i-th bit is an information bit, calculating (310) a path metric for each of 2*L.sub.i-1 candidate paths at the i-th level, where L.sub.i-1 is an SCL size at the (i−1)-th level and L.sub.0=1; setting (320) an SCL size at the i-th level, L.sub.i, based on L.sub.i-1 and a statistical distribution of the path metrics calculated for the 2*L.sub.i-1 candidate paths; and selecting (330) L.sub.i surviving paths from the 2*L.sub.i-1 candidate paths based on their respective path metrics.

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.

A method of operating a storage system is provided. The storage system includes memory cells and a memory controller, wherein each memory cell is an m-bit multi-level cell (MLC), where m is an integer, and the memory cells are arranged in m pages. The method includes determining initial LLR (log likelihood ratio) values for each of the m pages, comparing bit error rates in the m pages, identifying a programmed state in one of the m pages that has a high bit error rate (BER), and selecting an assist-read threshold voltage of the identified page. The method also includes performing an assist-read operation on the identified page using the assist-read threshold voltage, determining revised LLR values for the identified page based on results from the assist-read operation, and performing soft decoding using the revised LLR values for the identified page and the initial LLR values for other pages.

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 a total number of reads, an aggregation mode for aggregating read results of multiple reads, and whether the read results include soft data. 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.

In some aspects, a user equipment (UE) may receive a configuration that indicates an association between a pre-emption indication field and at least one of: a set of transmission configuration indicator (TCI) states, a set of demodulation reference signal (DMRS) ports, or a set of layers; receive downlink control information (DCI) that includes a pre-emption indication that is indicated as a set of bits in the pre-emption indication field; determine whether the UE is scheduled to receive a communication in one or more pre-empted resources indicated by the set of bits, via a component carrier associated with the pre-emption indication, and using at least one of: a TCI state included in the set of TCI states, a DMRS port included in the set of DMRS ports, or a layer included in the set of layers; and decode the communication based at least in part on the determination.

Estimation of read parameters for a read channel of a solid-state storage device using a machine learning apparatus. The machine learning apparatus may be provided with signal count metrics from multiple regions of the memory cell signal space and syndrome weights from an error correction code. Other inputs may also be provided comprising metrics of the memory or read operations. In an example, the read parameters may include one or more reference threshold voltage values for read voltages applied to a memory cell and/or log-likelihood ratio (LLR) values for the memory cell.