Systems and methods for decoding block and concatenated codes are provided. These include advanced iterative decoding techniques based on belief propagation algorithms, with particular advantages when applied to codes having higher density parity check matrices such as iterative soft-input soft-output and list decoding of convolutional codes, Reed-Solomon codes and BCH codes. Improvements are also provided for performing channel state information estimation including the use of optimum filter lengths based on channel selectivity and adaptive decision-directed channel estimation. These improvements enhance the performance of various communication systems and consumer electronics. Particular improvements are also provided for decoding HD radio signals, satellite radio signals, digital audio broadcasting (DAB) signals, digital audio broadcasting plus (DAB+) signals, digital video broadcasting-handheld (DVB-H) signals, digital video broadcasting-terrestrial (DVB-T) signals, world space system signals, terrestrial-digital multimedia broadcasting (T-DMB) signals, and China mobile multimedia broadcasting (CMMB) signals. These and other improvements enhance the decoding of different digital signals.

Wireless communications systems and methods are introduced. A wireless communication device may arrange a first encoded information block including a first sub-block having a first bit location and a second sub-block having a second bit location. The second bit location is after the first bit location. The wireless communication device may also position the first location earlier in a decoding order of a receiving second wireless communication than the second bit location. The wireless communication device may transmit the first and second sub-blocks as an encoded information block to the second wireless communication device.

An embodiment method includes receiving, by a first user equipment (UE), a message, for a second UE, transmitted over a plurality of resource blocks (RBs) on behalf of a communications controller and determining a plurality of log-likelihood ratios (LLRs) in accordance with the received plurality of RBs. The method also includes transmitting, a subset of the determined LLRs to the second UE.

A memory sub-system configured to: measure a plurality of sets of signal and noise characteristics of a group of memory cells in a memory device; determine a plurality of optimized read voltages of the group of memory cells from the plurality of sets of signal and noise characteristics respectively; generate features from the plurality of sets of signal and noise characteristics, including at least one compound feature generated from the plurality of sets of signal and noise characteristics; generate, using the features, a classification of a bit error rate of data retrievable from the group of memory cells; and control an operation to read the group of memory cells based on the classification.

Devices, systems and methods for list decoding of polarization-adjusted convolutional (PAC) codes are described. One example method for improving error correction in a decoder for data in a communication channel includes receiving a noisy codeword, the codeword having been generated using a polarization-adjusted convolutional (PAC) code and provided to the communication channel prior to reception by the decoder, and performing PAC list decoding on the noisy codeword, wherein an encoding operation of the PAC code comprises a convolutional precoding operation that generates one or more dynamically frozen bits, and wherein the PAC list decoding comprises extending, based on the one or more dynamically frozen bits, at least two paths of a plurality of paths in the PAC list decoding differently and independently.

Reconstructing compressed data to reduce compression loss. Data at a device is compressed using lossy compression and metadata values are added to the compressed data. A gateway receives a package including the compressed data and the metadata values. The data is decompressed and input to a machine learning model along with the metadata values. The machine learning model is trained to reduce the compression loss. The output of the model is an improved decompressed data. Actions may be performed based on the improved decompressed data.

A device receives signals over a communication medium and uses a low density parity check decoder to decode data in the signals. A number of unsatisfied parity checks are counted prior to a first decoding iteration of the low density parity check decoder on a basis of log likelihood ratios computed from the signals. An operational characteristic of the low density parity check decoder is computed based on an accumulated number of unsatisfied parity checks.

In an illustrative example, a method includes sensing at least a portion of a representation of a convolutional low-density parity-check (CLDPC) codeword stored at a memory of a data storage device. The method further includes receiving the portion of the representation of the CLDPC codeword at a controller of the data storage device. The method further includes performing one or more management operations associated with the memory based on an estimated number of errors of the portion of the representation of the CLDPC codeword.

The present disclosure includes apparatuses and methods for estimating an error rate associated with memory. A number of embodiments include sensing data stored in a memory, performing an error detection operation on the sensed data, determining a quantity of parity violations associated with the error detection operation, and estimating an error rate associated with the memory based on the determined quantity of parity violations.

Aspects of the disclosure provide an apparatus that includes transmitting circuit and processing circuit. The transmitting circuitry is configured to transmit wireless signals. The processing circuitry is configured to encode a set of information bits with a code that is configured for incremental redundancy to generate a code word that includes the information bits and parity bits, buffer the code word in a circular buffer, determine a start position in the circular buffer based on a redundancy version that is selected from a plurality of redundancy versions based on a scenario evaluation of a previous transmission associated with the set of information bits, and transmit, via the transmitting circuitry, a selected portion of the code word from the start position.