Methods, systems, and devices for wireless communications are described. An encoding device (e.g., a user equipment (UE) or a base station) may divide one or more data units (e.g., packet data convergence protocol (PDCP) protocol data units (PDU)) into a set of data blocks. The encoding device may encode the set of data blocks using a fountain code and may generate a set of data units (e.g., radio link control (RLC) PDUs) based on encoding the set of data blocks using the fountain code. The UE may allocate a first subset of the set of data units to a first carrier and a second subset of the set of data units to a second carrier and may transmit the first subset over the first carrier and the second subset over the second carrier.

Example systems, read channels, and methods provide bit value detection from an encoded data signal using a neural network soft information detector. The neural network detector determines a set of probabilities for possible states of a data symbol from the encoded data signal. A soft output detector uses the set of probabilities for possible states of the data symbol to determine a set of bit probabilities that are iteratively exchanged as extrinsic information with an iterative decoder for making decoding decisions. The iterative decoder outputs decoded bit values for a data unit that includes the data symbol.

This disclosure provides methods, devices and systems for acknowledgement and retransmission, and more specifically, to methods, devices and systems that enable a secondary wireless channel to provide acknowledgements of data transmitted on a primary wireless channel concurrently with the reception of additional data on the primary wireless channel. In some implementations, a transmitting device may transmit wireless packets including multiple codewords to a receiving device via a first wireless channel. The receiving device may attempt to decode the received codewords based on primary information in the codewords. The receiving device may then transmit to the transmitting device, via a second wireless channel, a codeword acknowledgement that identifies codewords that the receiving device did not successfully decode. The transmitting device may then transmit parity information to the receiving device via the first wireless channel that aids the receiving device in decoding the identified codewords.

A method for managing processing power in a storage system is provided. The method includes providing a plurality of blades, each of a first subset having a storage node and storage memory, and each of a second, differing subset having a compute-only node. The method includes distributing authorities across the plurality of blades, to a plurality of nodes including at least one compute-only node, wherein each authority has ownership of a range of user data.

A memory system includes a non-volatile memory and a controller. The controller is configured to perform iterative correction on a plurality of frames of data read from the non-volatile memory. The iterative correction includes performing a first error correction on each of the frames including a first frame having errors not correctable by the first error correction, generating a syndrome on a set of second frames that include the first frame, performing a second error correction on the second frames using the syndrome, and performing a third error correction on the first frame. Each of the frames includes user data and first parity data used in the first error correction, the first parity data of the first frame also being used in the third error correction.

Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

A system for software error-correcting code (ECC) protection or compression of original data using ECC data in a first memory is provided. The system includes a processing core for executing computer instructions and accessing data from a main memory, and a non-volatile storage medium for storing the computer instructions. The software ECC protection or compression includes: a data matrix for holding the original data in the first memory; a check matrix for holding the ECC data in the first memory; an encoding matrix for holding first factors in the main memory, the first factors being for encoding the original data into the ECC data; and a thread for executing on the processing core. The thread includes a Galois Field multiplier for multiplying entries of the data matrix by an entry of the encoding matrix, and a sequencer for ordering operations using the Galois Field multiplier to generate the ECC data.

A method for managing processing power in a storage system is provided. The method includes providing a plurality of blades, each of a first subset having a storage node and storage memory, and each of a second, differing subset having a compute-only node. The method includes distributing authorities across the plurality of blades, to a plurality of nodes including at least one compute-only node, wherein each authority has ownership of a range of user data.

A method of data recovery for a distributed storage system is a method of recovering multiple failed nodes concurrently with the minimum feasible bandwidth when failed nodes exist in a distributed storage system. By means of selecting assistant nodes, obtaining helper data sub-blocks through computing the selected assistant nodes, then computing a repair matrix and finally multiple the repair matrix and the helper data sub-blocks, the missing data blocks are reconstructed; or the missing data blocks are reconstructed by decoding. The method is applicable to data recovery in the case of any number of failed nodes and any reasonable combinations of coding parameters. The data recovery herein can reach the theoretical lower limit of the minimum recovery bandwidth.