Abstract: This application provides a random access method and an apparatus. The random access method includes: User equipment sends a random access message of a first-type random access procedure to a network device. The random access message of the first-type random access procedure includes a random access preamble and uplink data. The user equipment starts a first time window after the end of the transmission of the random access preamble, and detects first downlink control information (DCI) and second DCI within the first time window. The first DCI is used to schedule a first physical downlink shared channel PDSCH for carrying a first response message to the random access preamble, and the second DCI is used to schedule a second PDSCH for carrying a second response message to the random access message.

Abstract: A terminal device obtains M pieces of first downlink channel sub-data, where each piece of first downlink channel sub-data corresponds to one data space in M data spaces. For an ith piece of first downlink channel sub-data in the M pieces of first downlink channel sub-data, the terminal device determines, based on a first dictionary corresponding to an ith data space, first information corresponding to the ith piece of first downlink channel sub-data, where M pieces of first information are determined in total. The terminal device sends first indication information, to indicate the M pieces of first information. Different data spaces can represent different channel environment information. The terminal device feeds back first information corresponding to different data spaces, so that an access network device can determine a correspondence between first information and environment information. Accuracy of the first information fed back by the terminal device is improved.

Abstract: A reference signal indication method includes receiving a plurality of reference signals, and sending at least one codeword on a first time-frequency resource. The at least one codeword includes a first codeword. The first codeword corresponds to a first reference signal in N reference signals of the plurality of reference signals. The first reference signal is a selected reference signal. The N reference signals are a subset of the plurality of reference signals, and N is a positive integer.

Abstract: A method includes: When user equipment is in an RRC idle mode or inactive mode, the user equipment sends a first random access preamble to an access network device on a PRACH resource, and sends first uplink data to the access network device on a PUSCH resource. The user equipment sends, by using at least two beams respectively, SRSs to the access network device on at least two SRS resources associated with the PUSCH resource. The user equipment receives a random access response from the access network device, where the random access response includes beam indication information, and the beam indication information is used to indicate an optimal beam in the at least two beams.

Abstract: The present disclosure provides a communication method. The method includes: determining first channel information, where the first channel information includes information in M1 dimensions, information in an ith dimension in the M1 dimensions includes Ni pieces of information, M1 is a positive integer greater than 1, i is a positive integer ranging from 1 to M1, and Ni is a positive integer greater than 1; determining channel state indication information based on second channel information, where the second channel information indicates partial information of Nm pieces of information in an mth dimension in the M1 dimensions, and m is a positive integer from 1 to M1; and sending first indication information and the channel state indication information, where the first indication information indicates a location of the second channel information in the first channel information.

Abstract: This disclosure provides a communication method and a communication apparatus. The method includes: receiving first information from a first node, where the first information is for configuring a first model structure of an intelligent model, the first model structure includes N operations, N is a positive integer, an operation in the N operations is a calculation for obtaining an output parameter by using an operation parameter and an operator, and the operator is an operation rule or a function; and determining the intelligent model based on the first information. This enables communication nodes to reach a consensus on the model structure, makes the intelligent model applicable to a communication network, and implements communication network intelligence.

Abstract: This disclosure provides an information transmission method and an apparatus. A first device receives N pieces of first node information from a second device, so that a first artificial intelligence model can be determined based on the N pieces of first node information and first link information, in other words, a structure of the first artificial intelligence model can be reconstructed. According to the method, when the second device indicates an artificial intelligence model to the first device, node information of a node and a connection relationship between nodes may be separately indicated. In addition, if the connection relationship between the nodes in the artificial intelligence model is a serial structure, the first link information may not be indicated, and only the node information is indicated, so that representation and transmission overheads of the artificial intelligence model can be reduced.

Abstract: This disclosure provides a communication method and apparatus, to improve positioning performance. The method includes: obtaining M pieces of first channel estimation information, where an mth piece of first channel estimation information in the M pieces of first channel estimation information is estimation information of a channel between an mth cell node in M cell nodes and a terminal device, M is a positive integer greater than 1, and m is a positive integer from 1 to M; and determining M pieces of second channel estimation information based on at least one of the M pieces of first channel estimation information, where an mth piece of second channel estimation information in the M pieces of second channel estimation information corresponds to the channel between the mth cell node and the terminal device.

Abstract: This disclosure provides a communication method, which includes: obtaining M pieces of channel estimation information, where an mth piece of channel estimation information in the M pieces of channel estimation information is estimation information of a channel between an mth cell node in M cell nodes and a terminal device; determining a type of a target positioning manner based on the M pieces of channel estimation information; and obtaining N pieces of channel estimation information based on the type of the target positioning manner, where the N pieces of channel estimation information are used to position the terminal device, an nth piece of channel estimation information in the N pieces of channel estimation information is estimation information of a channel between an nth cell node in N cell nodes and the terminal device, the N cell nodes are included in the M cell nodes.

Abstract: An uplink precoding method and an apparatus are provided. The method includes: A terminal device receives first information from an access network device; the terminal device determines a first precoding matrix based on the first information and a first model, where the first precoding matrix is determined based on an output of the first model, and an input of the first model is determined based on the first information; the terminal device precodes an uplink signal based on the first precoding matrix; and the terminal device sends a precoded uplink signal to the access network device. In the method, the terminal device determines the first precoding matrix based on the first information and the first model. The precoding matrix is no longer selected from an offline codebook, but is a floating-point matrix generated by the terminal device based on the first information.

Abstract: A data processing method for a model and an apparatus are provided. The method includes: A first node determines the data processing method for the model; and the first node implements, according to the data processing method for the model, at least one of the following: performing model training or performing model inference. Based on the method and the apparatus, inference tasks for different radio resource configurations can be completed by using one model, so that overheads for model training and storage are reduced.

Abstract: This disclosure provides a communication method and apparatus. An apparatus obtains an ith piece of first information that indicates an ith local model of each of K subnodes and i is a positive integer, and determines an ith federated learning model of a kth subnode based on the ith piece of first information and a type of the ith federated learning model of the kth subnode, where k is any positive integer from 1 to K. When i is greater than 1, the type of the ith federated learning model of the kth subnode is determined based on a type or performance of an (i?1)th federated learning model of the kth subnode. The apparatus sends an ith piece of second information, where the ith piece of second information indicates an ith federated learning model of each of the K subnodes.

Abstract: This disclosure relates to a communication method and apparatus. A terminal device obtains M channel estimation results corresponding to M time units, where M is greater than 1. The terminal device performs joint compression on the M channel estimation results by using an encoder network, to obtain N pieces of compression information. The terminal device sends the N pieces of compression information to an access network device. Because the terminal device performs joint compression, correlation between downlink channels at different time points is fully utilized. The access network device recovers the N pieces of compression information obtained through joint compression, so that more accurate and effective downlink channel information can be obtained.

Abstract: This disclosure provides a communication method and apparatus, to reduce transmission overheads of training data and improve performance of an artificial intelligence model. The method includes: obtaining first data and first information from a first node, where the first information indicates a data augmentation manner of the first data; and determining a first training dataset of a model based on the first data and the first information.

Abstract: This application provides example uplink transmit power determining methods and example terminal devices. One example method includes: determining a total transmit power of a first plurality of uplink signals located in a first time domain resource, wherein the first plurality of uplink signals include MsgA PRACH; and when the total transmit power of the first plurality of uplink signals exceeds a maximum transmit power of a terminal device, determining a transmit power of the MsgA PRACH based on a power priority of the MsgA PRACH, wherein the power priority of the MsgA PRACH is same as a power priority of Msg 1 PRACH in a primary cell.

Abstract: A communication method and a communication apparatus. The method includes: the communication apparatus receives first information, where the first information indicates a training policy of a first intelligent model. The communication apparatus performs model training on the first intelligent model according to the training policy. In this way, an intelligent model that meets a communication performance requirement can be obtained while air interface resource overheads are reduced.

Abstract: This application provides a communication method and apparatus. The method includes: determining a first downlink signal and a second downlink signal, where the first downlink signal is a downlink signal determined based on an output of a first prediction model, an input of the first prediction model is determined based on Y pieces of downlink measurement information in X pieces of downlink measurement information, and the second downlink signal is determined based on the X pieces of downlink measurement information; and indicating the second downlink signal and the Y pieces of downlink measurement information to an access network device if the first downlink signal and the second downlink signal meet a first condition. According to the method, the first prediction model can be updated based on the foregoing information, and performance of the prediction model can be continuously improved.

Abstract: This application provides a calibration method and apparatus. The method includes: determining first channel state information and second channel state information, where the first channel state information is obtained through prediction via a first channel prediction model, and the second channel state information is determined based on channel estimation on a downlink signal from an access network device; and sending first information to the access network device if a difference metric value between the first channel state information and the second channel state information is greater than or equal to a first threshold, where the first information indicates the second channel state information.

Abstract: This application provides a data processing method and a communication apparatus. The method includes: receiving or sending a plurality of reference signals; obtaining a first channel data set, where the first channel data set is a set of a plurality of pieces of channel data obtained based on the plurality of reference signals; obtaining a data quality screening policy, where the data quality screening policy is used to obtain, through screening, model training data that meets a data quality requirement; and screening the channel data in the first channel data set according to the data quality screening policy, to obtain a training data set. In this way, quality of the training data for model training is improved, so that a trained intelligent model meets a performance requirement.

Abstract: A communication method and an apparatus. A terminal device (or an access network device) obtains a channel feature through inference by using a channel feature extraction model, where the channel feature corresponds to a channel between the terminal device and the access network device. The terminal device (or the access network device) sends the channel feature to a location management function LMF. The LMF obtains, based on the channel feature, positioning information of the terminal device through inference by using a positioning information obtaining model. The LMF may determine location information of the terminal device based on the positioning information. An artificial intelligence model may be used to implement positioning or assist in implementing positioning of the terminal device.