There is provided a decoding circuit including; a first decoding unit that decodes a first signal from a multiplexed signal in which the first signal and a second signal are multiplexed in an LDM (Layered Division Multiplexing) system; and a second decoding unit that decodes the second signal from the multiplexed signal using the decoding result of the decoded first signal, wherein the second signal is selectively decoded based on noise information related to a reception state of the multiplexed signal.

This application discloses example decoding methods, example decoder, and example decoding apparatuses. One example decodine method includes performing soft decision decoding on a first sub-codeword in a plurality of sub-codewords to obtain a hard decision result. It is determined whether to skip a decoding iteration. In response to determining not to skip the decoding iteration, a first turn-off identifier corresponding to the first sub-codeword is set to a first value based on the hard decision result. The first turn-off identifier indicates whether to perform soft decision decoding on the first sub-codeword in a next decoding iteration. The soft decision decoding is not performed on the first sub-codeword in the next decoding iteration when a value indicated by the first turn-off identifier is the first value. The hard decision result is stored.

Aspects of the disclosure provide methods, apparatuses, and a non-transitory computer-readable medium for point cloud compression and decompression. In a method, syntax information of a point cloud in a quantized space is decoded from a coded bitstream. The syntax information includes dividing information and adaptive geometry quantization information for a bounding box of the point cloud. The bounding box of the point cloud is divided into a plurality of parts based on the dividing information. Quantization parameters for the parts in the bounding box are determined based on the adaptive geometry quantization information. Points in each of the parts in the bounding box of the point cloud are reconstructed based on the quantization parameter for the respective part in the bounding box.

Iterative signal processing. At communication hardware, a signal is received from a transmission medium. The signal has characteristics that obscure data or a signal of interest in the signal. The signal is processed at a first signal processor, which is an iterative processor that performs signal processing in cycles whereby successive cycles: improve the performance of processing of the processor itself over previous cycles, or improve the output from the processor. The signal is processed at one or more second signal processors. Extrinsic data, with respect to the first signal processor is produced as a result. The extrinsic data is provided to the first signal processor and used to counter the effects of the data or signal of interest being obscured in the signal, while the first signal processor is intracycle of a first processing cycle.

A memory system of an embodiment includes a non-volatile memory and a memory controller. The memory controller executes a first decoding process of reading data encoded by an error correction code from the non-volatile memory and repeatedly executing bounded distance decoding on a symbol group protected by each of component codes included in N component code groups; executes a second decoding process of repeatedly executing decoding exceeding a bounded distance in units of component codes for an error symbol group determined to include an error due to a syndrome of a component code included in the N component code groups when the first decoding process fails; executes a rollback process when the first decoding process executed after the second decoding process fails; and changes a parameter used in the second decoding process and further executes the second decoding process when it is detected that the second decoding process is not progressed.

A memory device can include a memory array, a processor coupled to the memory array, and a decoding apparatus. The decoding apparatus is configured to perform parallel decoding of codewords. Each of the codewords has a plurality of data blocks, each data block having a number of data bits. The decoding apparatus is configured to decode in parallel two or more codewords, which share a common data block, to determine error information associated with each codeword. For each error, the error information identifies a data block having the and associated error bit patterns. The decoding apparatus is configured to update the two or more codewords based on the identified data blocks having errors and the associated error bit patterns.

Systems and methods are provided for concatenated error-correcting coding. An apparatus may include a Low-Density Parity-Check (LDPC) decoder configured to perform an iterative LDPC decoding process on bits of an LDPC codeword, a Bose-Chaudhuri-Hocquenghem (BCH) decoder coupled to the LDPC decoder and a BCH scheduler coupled to the LDPC decoder and the BCH decoder. The LDPC codeword may be generated by LDPC encoding a Bose-Chaudhuri-Hocquenghem (BCH) codeword and the BCH codeword may be generated by BCH encoding a data unit. The BCH scheduler may be configured to determine whether a triggering condition for the BCH decoder is met after each iteration of the iterative LDPC decoding process and activate the BCH decoder to operate on an intermediate decoding result of the LDPC decoder if the triggering condition for the BCH decoder is met.

Apparatuses and methods for performing an error correction code (ECC) operation are provided. One example method can include generating a codeword based on a number of low density parity check (LDPC) codewords failing a LDPC decoding operation and performing a BCH decoding operation on the codeword.

Example implementations include a method of optimizing irregular error correction code components in memory devices, a method including obtaining one or more code rate parameters including a payload size parameter, a group size parameter, and a redundancy parameter generating a first number of first code component blocks associated with a first error correction capability, and a second number of code component blocks associated with a second error correction capability aligning the first code component blocks and the second code component blocks to the group size parameter aligning the first code component blocks and the second code component blocks to a code component length constraint, and generating, in accordance with an optimization metric based on the first error correction capability and the second error correction capability, first optimized code components based on the first code component blocks and second optimized code components based on the second code component blocks.

A device for decoding a generalized concatenated code (GCC) codeword includes: a buffer; and at least one processor configured to: obtain the GCC codeword, calculate a plurality of inner syndromes based on a plurality of frames; calculate a plurality of sets of delta syndromes based on the frames; determine a plurality of outer syndromes based on the sets of delta syndromes; store the inner syndromes and the outer syndromes in a buffer; perform inner decoding on the frames based on the inner syndromes stored in the buffer; update at least one outer syndrome stored in the buffer based on a result of the inner decoding; perform outer decoding on the frames based on the updated at least one outer syndrome; and obtain decoded information bits corresponding to the GCC codeword based on a result of the inner decoding and the result of the outer decoding.