Abstract: A secure processor for a post-quantum cryptography (PQC) algorithm CRYSTALS-KYBER, includes a communication unit, a management unit, a processing unit, and a storage unit. The communication unit is configured to receive and transmit data for the secure processor; the management unit is configured to control the processing unit according to the data; the processing unit is configured to process the data to form encrypted data, decrypted data and key data; and the storage unit is configured to store all data. The secure processor can efficiently and rapidly realize key generation, encryption and decryption of a KYBER algorithm under KYBER1024, KYBER768 and KYBER512 security levels, makes data encryption more complicated, and ensures security of the data.

Abstract: Embodiments of the present disclosure provide a resource configuration method and a device. The method includes: sending configuration information to a terminal device, where the configuration information is used to configure a target SRS resource in M SRS resource sets, and M is a positive integer greater than or equal to 2.

Abstract: The present application discloses a channel estimation method and apparatus, a device, and a readable storage medium. The channel estimation method includes: receiving, by a communication device, a pilot signal and a data signal; determining, by the communication device, a linear feature according to the pilot signal; determining, by the communication device, a nonlinear feature according to the data signal; and performing, by the communication device, channel estimation according to the linear feature and the nonlinear feature.

Abstract: A training data set obtaining method includes determining, based on degrees of contribution of transmission conditions to an optimization objective of a neural network, data volumes of training data under the transmission conditions; and obtaining, based on the data volumes of the training data under the transmission conditions, the training data under the transmission conditions, to form a training data set for training the neural network. The degrees of contribution of the transmission conditions to the optimization objective of the neural network represent degrees of impact of the transmission conditions on a value of the optimization objective of the neural network.

Abstract: This application discloses an information reporting method and apparatus, a first device, and a second device. The method includes: reporting first information to a second device; where the first information includes predicted first channel state information or second information determined based on the predicted first channel state information, and the first channel state information includes channel state information of a first time period after a reference time point.

Abstract: This application provides a communications data processing method and apparatus, and a communications device. The method includes: pre-processing first communications data in a pre-specified processing manner; and inputting the pre-processed first communications data to a target Artificial Intelligence (AI) network to obtain second communications data. The pre-specified processing manner includes at least one of an amplitude processing manner, a phase processing manner, or a transform domain processing manner.

Abstract: This application discloses a communication method, a communications apparatus, and a communications device. The method includes: dividing, by a first communications device, first communication information into n pieces of first target subband information. The method further includes inputting the n pieces of first target subband information into a first Artificial Intelligence (AI) subnetwork of a first AI network model. A maximum input amount of the first AI subnetwork is N pieces of subband information. A maximum input amount of the first AI network is M pieces of subband information. n, M, and N are all integers greater than 0, and n?N?M. The method also includes sending second communication information output by the first AI subnetwork.

Abstract: A method for processing partial input missing of an AI network includes: in a case that there is a missing input in a plurality of inputs of an AI network, replacing, by a first communication device, the missing input with a target input or a default value to obtain an output of the AI network.

Abstract: This application discloses a beam processing method and apparatus, and a communication device, which belong to the field of communication technologies. The method includes: obtaining quality information of a first beam; and determining quality information of a second beam according to the quality information of the first beam.

Abstract: A communication information sending method includes dividing, by a first communication device, first communication information into one or more pieces of sub-band information; and inputting broadband information of the first communication information and/or the one or more pieces of sub-band information to a first artificial intelligence network model, and sending second communication information output by the first artificial intelligence network model.

Abstract: A beam reporting method, a beam information determining method, and a related device are provided. The method includes: performing beam measurement according to a beam measurement configuration to obtain a beam measurement result; inputting the beam measurement result into an artificial intelligence (AI) network to obtain N pieces of first information, where N is a positive integer; and sending a first beam measurement report to a second device, where the first beam measurement report includes the N pieces of first information, and the first information is used to determine beam information.

Abstract: A configuration method for an AI network parameter includes: obtaining, by a first communication device, an AI network parameter in at least one of following manners: predefinition, receiving from a second communication device, or real-time training; or processing, by the first communication device, a target service according to the AI network parameter.

Abstract: This application provides a neural network information transmission method and apparatus, a communication device, and a storage medium. The method includes: receiving first information sent by a first communication device, where the first information is output information of a first neural network of the first communication device; and sending second information to the first communication device, where the second information is information obtained by training the first information or third information as an input of a second neural network of a second communication device, and the third information is information obtained based on the first information.

Abstract: A CSS monitoring method, includes: monitoring, by a terminal, a PDCCH candidate on a CSS set, where the terminal uses same first information as an anchor node, or uses same first information as a cell/TRP associated with the CSS set.

Abstract: A cell handover method and a terminal are provided. The method includes: determining, by a terminal according to a Downlink Control Information (DCI) indicator, whether a cell handover trigger condition is met; and the terminal performs a cell handover in a case that the cell handover trigger condition is met.

Abstract: A method for measuring a reference signal, a terminal, and a network side device are provided. The method includes: performing, by a terminal, L1 measurement on a reference signal of a neighboring cell or a neighboring Transmission and Reception Point (TRP) based on a measurement restriction condition to obtain a measurement result; and sending, by the terminal, the measurement result.

Abstract: A Reference Signal (RS) measurement method and apparatus, and a communications device are provided. When being performed by a terminal, the RS measurement method includes: receiving RS measurement indication information sent by a network-side device. The RS measurement indication information is used to indicate that the terminal performs layer 1 beam measurement for an RS of a first cell. The RS measurement method further includes performing the layer 1 beam measurement for the RS of the first cell based on the RS measurement indication information. The terminal performs scheduling restriction or rate matching on a second cell when performing the layer 1 beam measurement for the RS of the first cell.

Abstract: A measurement reporting method includes: performing, by UE, measurement on a target reference signal of a target neighboring cell of a first cell at a layer 1 to obtain a first measurement result; and reporting, by the UE, a target measurement report to a network side device through the layer 1. The target measurement report includes the first measurement result.

Abstract: A beam report method and a device are provided. The method is performed by a terminal device, and includes: sending a beam report, where the beam report is obtained by performing measurement based on at least one of a reference signal (RS) of a first TRP and an RS of a second TRP, and for the beam report, referring to or prioritizing the first RS of the first TRP.

Abstract: Embodiments of the present disclosure disclose a beam report transmission method, a mobile terminal, and a network device, to guarantee transmission and reception performance and reduce overheads of beam reports. The method includes: sending corresponding first beam reports respectively to a plurality of first transmission and reception points, where the first beam reports are reports of reference signals corresponding to the first transmission and reception points.