A multi-channel decoder circuit associated with a multi-channel decoder system is disclosed. The multi-channel decoder circuit comprises a distributed decoder circuit comprising a set of unit decoder circuits, each unit decoder circuit configured to receive one or more codewords of a plurality of codewords associated with a plurality of input channels, and decode the one or more codewords. The multi-channel decoder circuit further comprises a distribution controller circuit configured to distribute each incoming codeword of the one or more codewords to the respective unit decoder circuit of the set of unit decoder circuits within the distributed decoder circuit, based on determining a currently available unit decoder circuit within the set of unit decoder circuits.

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.

Read data associated with Flash storage that is in a Flash storage state is received. One of a plurality of log-likelihood ratio (LLR) mapping tables is selected based at least in part on: (1) the Flash storage state and (2) a decoding attempt count associated with a finite-precision low-density parity-check (LDPC) decoder. A set of one or more LLR values is generated using the read data and the selected LLR mapping table, where each LLR value in the set of LLR values has a same finite precision as the finite-precision LDPC decoder. The finite-precision LDPC decoder generates the error-corrected read data using the set of LLR values and outputs it.

Various embodiments of the present disclosure provide methods and apparatuses for improved belief propagation (BP) decoding. A method performed by a receiver comprises: performing BP decoding on received information; obtaining, in response to the BP decoding being unsuccessful and based on a first table comprising left-to-right messages associated with nodes of a plurality of processing elements (PEs) for the BP decoding and the received information, a second table comprising right-to-left messages associated with the nodes; searching, based on the first table and the second table, a conflict verification processing element (VPE); updating, for the conflict VPE, both signs of the right-to-left messages associated with its right-upper node and right-lower node to be the same and the sign of the right-to-left messages associated with its left-upper node to be positive; updating the second table; and performing the BP decoding based on the updated second table.

This invention presents a method and apparatus for vertical layered finite alphabet iterative decoding of low-density parity-check codes (LDPC) which operate on parity check matrices that consist of blocks of sub-matrices. The iterative decoding involves passing messages between variable nodes and check nodes of the Tanner graph that associated with one or more sub-matrices constitute decoding blocks, and the messages belong to a finite alphabet. Various embodiments for the method and apparatus of the invention are presented that can achieve very high throughputs with low hardware resource usage and power.

Techniques related to improving the decoding performance of codewords, such as LDPC codewords, are described. In an example, the error-correction capability of a decoding layer is improved, where the improvements may include lowering the error floor. To do so, higher order information is used in the decoding. Higher order information refers to, during the decoding of a variable node that is in error, using information that is not limited to the variable node and check nodes connected thereto, but includes information related to variable nodes that are also in error and connected to the variable node via satisfied check nodes and related to unsatisfied check nodes connected to such variable nodes.

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.

Embodiments of the invention provide a decoder comprising at least one check node processing unit configured to receive at least three variable node messages from one or more variable node processing units and to determine one or more check node messages, wherein the at least one check node processing unit comprises at least two blocks of sub-check nodes, each block of sub-check node being configured to: determine a set of sub-check node syndromes from at least one variable node message among the at least three variable node messages; and determine at least one check node message from at least one syndrome.

A method for constructing parity-check concatenated polar codes and an apparatus therefor are disclosed. According to an embodiment of the inventive concept, a method for constructing a polar code includes receiving a code length, a message length, and channel information, generating an information set and a parity set of polar codes based on the received code length, the received message length, and the received channel information, and generating a parity node including the information set of elements based on the generated information set and the generated parity set.

A device is disclosed. The device may include an input buffer to receive a first low bit width message. A reconstruction circuit may implement a reconstruction function on the first low bit width message, producing a first high bit width message. A computation circuit may implementing a computation function on the first high bit width message, producing a second high bit width message. A quantization circuit may implementing a quantization function on the second high bit width message, producing a second low bit width message. A decision buffer may then store the second low bit width message. The reconstruction function and the quantization function may vary depending on an iteration and a layer of the device.