Provided by the present application are a data transmission method and device, which are used to solve the problem of being unable to accurately transmit an RRC message which is too large. The method comprises: when determining that the length of an original RRC message exceeds a preset threshold, compressing the original RRC message; packaging the compressed RRC message into a PDCP PDU; and sending the packaged PDCP PDU to a receiving end.

A point cloud decoding method includes: receiving a point cloud file transmitted by a data source, the point cloud file including at least one point cloud media track; parsing file encapsulation information of the at least one point cloud media track, to obtain quality indication information carried in the file encapsulation information, the quality indication information being used for representing point cloud quality of the at least one point cloud media track; and selecting and decoding a point cloud media track with designated point cloud quality from the point cloud file according to the quality indication information carried in the file encapsulation information.

An on-board device includes a processor. The processor is configured to operate as an acquisition unit configured to acquire data from a sensor mounted on a vehicle, a human-machine-interface (HMI) unit configured to perform a process for exerting a human-machine-interface (HMI) function, and a data management unit configured to make determination on a category of the data delivered from the acquisition unit and deliver, to the HMI unit, data in a first category that does not contain data that is not desired to be delivered to the HMI unit. The HMI unit is configured to perform the process for exerting the HMI function based on the data delivered from the data management unit.

Disclosed are example embodiments of systems and methods for hybrid automatic repeat request (HARQ). An example method includes performing a first HARQ compression to reduce a number of HARQ bits, the HARQ compression comprising one of a unified HARQ compression and a block-wise HARQ compression. Optionally, the example method further includes performing a second HARQ compression to further reduce the number of HARQ bits to a compressed number of HARQ bits. One of the first HARQ compression and the second HARQ compression include the unified HARQ compression and another of the first HARQ compression and the second HARQ compression comprising the block-wise HARQ compression. The example method also includes saving the compressed HARQ data to a DDR storage.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may perform a measurement operation to attain multiple measurements to report to a base station. The measurements may correspond to a first number of bits if reported. The UE may compress the measurements using an encoder neural network (NN) to obtain an encoder output indicating the measurements. This encoder output may include a second number of bits that is less than the first number of bits. The UE may report the encoder output to the base station in this compressed form. At the base station, the encoder output may be decompressed according to a decoder NN. Once the base station decompresses the encoder output, the UE and base station may communicate according to the measurements determined from the decompression. In some cases, the base station may perform load redistribution based on the measurements.

Redundancy synchronization of remote terminal unit (RTU) central processing units (CPUs) associated with an industrial operation includes queuing time-stamped events on a main RTU CPU for transfer to a standby RTU CPU as the time-stamped events are generated on the main RTU CPU (i.e., in real-time). The synchronized RTU CPUs further permit synchronization of logic states and synchronization of firmware upgrades. Synchronization activities occur on the same synchronization communications channel between redundant RTU CPUs.

A data transmission method and a related device are provided. In various embodiments a first device generates a two-dimensional index table based on a preset multi-thread sequence traversal algorithm and a size of target data that needs to be transmitted, where the two-dimensional index table is used to indicate a storage location of each piece of data in the target data. In those embodiments, the first device performs data reconstruction on the target data based on the two-dimensional index table to obtain a two-dimensional data block pool, where the two-dimensional data block pool includes a plurality of data blocks, and each data block corresponds to one pair of coordinates in the two-dimensional index table. Still in those embodiments, the first device obtains the plurality of data blocks through indexing by using the two-dimensional index table, and sending the plurality of data blocks to a second device.

A data transmission method and a related device are provided. In various embodiments a first device generates a two-dimensional index table based on a preset multi-thread sequence traversal algorithm and a size of target data that needs to be transmitted, where the two-dimensional index table is used to indicate a storage location of each piece of data in the target data. In those embodiments, the first device performs data reconstruction on the target data based on the two-dimensional index table to obtain a two-dimensional data block pool, where the two-dimensional data block pool includes a plurality of data blocks, and each data block corresponds to one pair of coordinates in the two-dimensional index table. Still in those embodiments, the first device obtains the plurality of data blocks through indexing by using the two-dimensional index table, and sending the plurality of data blocks to a second device.

A disclosed information handling system includes an edge device communicatively coupled to a cloud computing resource. The edge device is configured to respond to receiving, from an internet of things (IoT) unit, a numeric value for a parameter of interest by determining a compressed encoding for the numeric value in accordance with a non-lossless compression algorithm. The edge device transmits the compressed encoding of the numeric value to the cloud computing resource. The cloud computing resource includes a decoder communicatively coupled to the encoder and configured to respond to receiving the compressed encoding by generating a surrogate for the numeric value. The surrogate may be generated in accordance with a probability distribution applicable to the parameter of interest. The compression algorithm may be a clustering algorithm such as a k-means clustering algorithm.

A data concentration system for an inner detector of an oil-gas pipeline, and a timing control method, the system includes: a multi-channel data receiving module, a data concentration module and a data transmission module. The multi-channel data receiving module is electrically connected to a plurality of probes of an inner detector and is configured to receive detection data acquired by the plurality of probes. The data concentration module is electrically connected to the multi-channel data receiving module, and is configured to receive the detection data outputted by the multi-channel data receiving module and compress the detection data. The data transmission module is electrically connected to a data storage module of the inner detector and the data concentration module respectively, and the data transmission module is configured to receive compressed detection data.