WO2023088269A1 - Procédé et dispositif de transmission d'informations d'intelligence artificielle - Google Patents

Procédé et dispositif de transmission d'informations d'intelligence artificielle Download PDF

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Publication number
WO2023088269A1
WO2023088269A1 PCT/CN2022/132086 CN2022132086W WO2023088269A1 WO 2023088269 A1 WO2023088269 A1 WO 2023088269A1 CN 2022132086 W CN2022132086 W CN 2022132086W WO 2023088269 A1 WO2023088269 A1 WO 2023088269A1
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WIPO (PCT)
Prior art keywords
communication device
information
model representation
model
supported
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PCT/CN2022/132086
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English (en)
Chinese (zh)
Inventor
任千尧
崇卫微
纪子超
孙鹏
吴晓波
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维沃移动通信有限公司
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Publication of WO2023088269A1 publication Critical patent/WO2023088269A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence

Definitions

  • the present application belongs to the field of communication technology, and specifically relates to a method and equipment for transmitting artificial intelligence (AI) information.
  • the equipment may include communication equipment such as an AI information transmission device, a terminal or a network side device.
  • AI model representations such as AI frameworks
  • different AI model representations have different emphases and even support different development languages, and the descriptions and functions of AI models are also implemented in different ways, resulting in AI information cannot be transmitted between two or more communication devices using different AI model representations, which affects the performance of the communication system.
  • the embodiments of the present application provide a method and device for transmitting AI information, which can solve the problem that the performance of the communication system is affected due to the inability of communication devices to understand AI information in different AI model representation modes.
  • a method for transmitting AI information including: a first communication device and a second communication device transmit AI information; wherein, the first AI model representation used by the first communication device is the same as the The representation of the second AI model used by the second communication device matches.
  • an apparatus for transmitting AI information including: a transmission module, configured to transmit AI information with a second communication device; wherein, the first AI model representation used by the apparatus is the same as that of the second The second AI model representation used by the communication device matches.
  • a communication device which includes a processor, a memory, and a program or instruction stored in the memory and operable on the processor, and the program or instruction is executed by the processor During execution, the method described in the first aspect is realized.
  • a communication device including a processor and a communication interface, wherein the communication interface is used to transmit AI information with a second communication device; wherein, the first AI model used by the communication device represents The mode matches the second AI model representation mode used by the second communication device.
  • a readable storage medium where a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the method as described in the first aspect is implemented.
  • a sixth aspect provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the method as described in the first aspect .
  • a computer program/program product is provided, the computer program/program product is stored in a non-transitory storage medium, and the computer program/program product is executed by at least one processor to implement the first method described in the aspect.
  • the first AI model expression used by the first communication device matches the second AI model expression used by the second communication device, in this way, the first communication device and the second communication device have an AI model
  • the understanding of the AI information in the representation mode is consistent, and the AI information can be transmitted between the first communication device and the second communication device, which is beneficial to improve the performance of the communication system.
  • FIG. 1 is a schematic diagram of a wireless communication system according to an embodiment of the present application.
  • FIG. 2 is a schematic flowchart of a method for transmitting AI information according to an embodiment of the present application
  • FIG. 3 is a schematic structural diagram of an AI information transmission device according to an embodiment of the present application.
  • FIG. 4 is a schematic structural diagram of a communication device according to an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of a terminal according to an embodiment of the present application.
  • Fig. 6 is a schematic structural diagram of a network side device according to an embodiment of the present application.
  • first, second and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application are capable of operation in sequences other than those illustrated or described herein and that "first" and “second” distinguish objects. It is usually one category, and the number of objects is not limited. For example, there may be one or more first objects.
  • “and/or” in the description and claims means at least one of the connected objects, and the character “/” generally means that the related objects are an "or” relationship.
  • LTE Long Term Evolution
  • LTE-Advanced LTE-Advanced
  • LTE-A Long Term Evolution-Advanced
  • CDMA Code Division Multiple Access
  • TDMA Time Division Multiple Access
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal Frequency Division Multiple Access
  • SC-FDMA Single carrier-Frequency Division Multiple Access
  • system and “network” in the embodiments of the present application are often used interchangeably, and the described technology can be used for the above-mentioned system and radio technology, and can also be used for other systems and radio technologies.
  • the following description describes the New Radio (New Radio, NR) system for illustrative purposes, and uses NR terms in most of the following descriptions. These technologies can also be applied to applications other than NR system applications, such as the 6th generation ( 6th Generation , 6G) communication system.
  • 6th generation 6th Generation
  • Fig. 1 shows a schematic diagram of a wireless communication system to which this embodiment of the present application is applicable.
  • the wireless communication system includes a terminal 11 and a network side device 12 .
  • the terminal 11 can also be called a terminal device or a user terminal (User Equipment, UE), and the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer) or a notebook computer, a personal digital Assistant (Personal Digital Assistant, PDA), handheld computer, netbook, ultra-mobile personal computer (ultra-mobile personal computer, UMPC), mobile internet device (Mobile Internet Device, MID), augmented reality (augmented reality, AR)/virtual reality (virtual reality, VR) equipment, robots, wearable devices (Wearable Device), vehicle-mounted equipment (VUE), pedestrian terminal (PUE), smart home (home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture etc.) and other terminal-side devices, wearable devices include: smart watches, smart bracelets, smart
  • the network side device 12 may be a base station or a core network, where a base station may be called a node B, an evolved node B, an access point, a base transceiver station (Base Transceiver Station, BTS), a radio base station, a radio transceiver, a basic service Basic Service Set (BSS), Extended Service Set (ESS), Node B, Evolved Node B (eNB), Next Generation Node B (gNB), Home Node B, Home Evolved Node B, WLAN Access point, WiFi node, Transmitting Receiving Point (Transmitting Receiving Point, TRP) or some other suitable term in the field, as long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that, In the embodiment of the present application, only the base station in the NR system is taken as an example, but the specific type of the base station is not limited.
  • the embodiment of the present application provides a method 200 for transmitting AI information, which can be performed by the first communication device, in other words, the method can be performed by software or hardware installed on the first communication device, the
  • the first communication device may be a network side device or a terminal, and the method includes the following steps.
  • the first communication device transmits AI information with the second communication device; the first AI model expression used by the first communication device matches the second AI model expression used by the second communication device.
  • the AI information mentioned in various embodiments of the present application may include AI models (or called AI networks), parameters, structures, etc., such AI models include neural network models, decision tree models, support vector machine models, and Bayesian classifiers. model etc. Subsequent embodiments mostly use the AI model as an example to introduce this embodiment. It can be understood that the AI information is not limited to the AI model.
  • the AI model representation mentioned in each embodiment of the present application can specifically be an AI framework, and the AI framework includes, for example, TensorFlow, PyTorch, Keras, MXNet, Caffe2
  • the AI framework includes, for example, TensorFlow, PyTorch, Keras, MXNet, Caffe2
  • Each AI framework will use its own method to describe the AI model, and complete operations such as building, training, and inferring the AI model.
  • the transmission of AI information between the first communication device and the second communication device includes at least one of the following:
  • the first communication device receives AI information from the second communication device.
  • the terminal receives the AI model from the network-side device, that is, the network-side device can send the trained AI model to the terminal; another example, the first terminal receives the AI model from the second terminal, that is, the second terminal The terminal can send the trained AI model to the first terminal.
  • the first communication device sends AI information to the second communication device.
  • the network-side device sends the AI model to the terminal, that is, the network-side device can send the trained AI model to the terminal;
  • the second terminal sends the AI model to the first terminal, that is, the second terminal can send the trained AI model to the terminal.
  • a good AI model is sent to the first terminal.
  • matching the first AI model representation used by the first communication device with the second AI model representation used by the second communication device includes: the first AI model representation used by the first communication device The manner is the same as that of the second AI model representation used by the second communication device; or, the version supported by the first AI model representation and the version supported by the second AI model representation are mutually progressive.
  • the representation of the first AI model mentioned here is the same as the representation of the second AI model, which may be of the same type (for example, both are TensorFlow), the same version and other information, the same file storage format, and so on.
  • the ones mentioned here are progressive.
  • the version supported by the first AI model representation is TensorFlow
  • the version supported by the second AI model representation is Keras, which is a packaged version based on TensorFlow.
  • the first AI model expression used by the first communication device matches the second AI model expression used by the second communication device, in this way, the first communication device and the second The communication devices have the same understanding of the AI information represented by the AI model, and the AI information can be transmitted between the first communication device and the second communication device, which is conducive to improving the performance of the communication system.
  • the AI information transmission method provided by the embodiment of the present application can use some methods in advance, such as network-side device configuration or protocol pre-agreement, to ensure that several communication devices (or called AI nodes) use matching (such as the same) AI framework to transmit AI information, the AI information includes AI model, parameters, structure, etc.
  • the above-mentioned communication device can be a base station, a terminal, a computing node of the core network, a functional node, etc., as long as it is a node that uses AI functions for training or inference.
  • the communication devices mentioned above can be two AI nodes, multiple AI nodes, or more than three AI nodes, where one AI node uses multiple different AI A certain AI framework of a certain AI node interacts.
  • the method further includes the following steps: the first communication device receives first indication information, and the first communication device The indication information is used to indicate multiple AI model representations supported by the second communication device, where the multiple AI model representations include the second AI model representation; the first communication device sends first feedback information, The first feedback information is used to indicate an AI model representation selected by the first communication device from the plurality of AI model representations, and the selected AI model representation includes the first AI model representation Way.
  • the method further includes: the first communication device receiving third indication information, where the third indication information is used to instruct the first communication device to receive or send the AI information.
  • the first communication device is a terminal
  • the second communication device is a network side device
  • the network side and the terminal side use mutually matching AI frameworks to transmit AI information.
  • the network side may deliver the selection range of the AI framework (which may be realized through the first indication information), and the terminal makes the selection and reports the selection result (which may be realized through the first feedback information).
  • the network side can use different AI frameworks to train the same AI model, and the network side broadcasts the AI framework used to the service terminals, and each terminal receives the same content; the terminal selects the appropriate AI model according to its own situation. Its own AI framework, feeds back the selected AI framework and additional information; the additional information includes, for example: the version and variant of the AI framework selected by the terminal; if the terminal does not find a suitable AI framework for itself, the terminal feeds back unselected information.
  • the network side uses the matching AI framework to transmit the AI model to the terminal, for example, the network side sends the AI model to the terminal.
  • the subsequent network side may also instruct the terminal (which may be realized through the third indication information) whether to establish an AI model transfer relationship, and the time-frequency resource location of the AI model transfer, etc.
  • the method further includes: the first communication device sends second indication information, and the second indication information It is used to indicate the AI model expression supported by the first communication device, and the AI model expression supported by the first communication device includes the first AI model expression; the second indication information is also used for the first AI model expression.
  • the second communication device selects an AI model representation from the AI model representations supported by the first communication device, and the selected AI model representation includes the second AI model representation.
  • the method further includes: the first communication device receiving third indication information, where the third indication information is used to instruct the first communication device to receive or send the AI information.
  • the first communication device is a terminal
  • the second communication device is a network side device
  • the network side and the terminal side use mutually matching AI frameworks to transmit AI information.
  • the terminal can report the AI framework capability (which can be realized through the second indication information), and the network side selects the AI framework to be used and indicates it to the terminal.
  • the network side can instruct the terminal to report the supported AI framework capability; the terminal reports the supported AI framework capability, indicating the AI framework and additional information that it can support (which can be realized through the second instruction information); the network side selects according to the capability of the terminal. Whether to establish the transfer relationship of the AI model with the terminal.
  • the network side uses a matching AI framework for subsequent AI model training.
  • the network side notifies the terminal of the content of the AI framework used, which may be specifically implemented through third indication information. This embodiment may be completed when the terminal accesses the cell, or may be completed by the network side instructing the terminal through signaling.
  • Each of the above embodiments introduces that the first communication device and the second communication device use the matching AI model representation to transmit AI information.
  • the first communication device establishes a connection with the second communication device
  • the first communication device and the second communication device The two communication devices can determine the matching AI model representation.
  • the first communication device and the second communication device may re-calibrate the AI model representation; or, after the cell, environment, etc. change, the AI model representation may be re-calibrated.
  • the calibration or switching process of the AI model representation mode will be introduced in multiple embodiments.
  • the method further includes: the first communication device sending first request information, where the first request information is used to request switching of the first AI model representation mode.
  • the terminal sends the first request information to the network side, for requesting to switch the AI framework.
  • the first request information includes at least one of the following: 1) AI model representation supported by the first communication device; 2) multiple AI models supported by the first communication device from the second communication device The AI model representation mode selected from the AI model representation modes; 3) the moment when the first AI model representation mode is switched.
  • the method further includes: the first communication device receives fourth instruction information, and the first communication device performs one of the following according to the fourth instruction information: 1 ) AI information is no longer transmitted between the second communication device, for example, the fourth indication information indicates that AI information is no longer transmitted; 2) AI information is transmitted between the second communication device based on the switched AI model representation Information, for example, the fourth indication information indicates which AI model representation method to switch to; 3) The AI information is transmitted between the second communication device based on the original AI model representation mode, for example, the fourth indication information indicates AI representation method is not switched.
  • the first communication device is a terminal
  • the second communication device is a network-side device
  • the terminal may apply to switch the representation mode of the AI model.
  • the terminal applies for a new AI framework according to its own situation, such as using a high-precision framework (TensorFlow, etc.) when the battery is high, and switching to a low-precision framework (caffe, etc.) when the battery is low, to improve the flexibility of communication.
  • the network side selects one of the following according to the AI framework newly requested by the terminal: a) abandon the AI connection; b) use a new AI framework connection; c) maintain the original AI framework connection.
  • the terminal can directly send its updated AI framework capabilities to the network side, allowing the network side to decide on a new AI framework; or, the terminal selects one of the optional AI frameworks delivered by the network side, and notifies the network , the network indicates the result of the terminal's selection.
  • the method further includes: the first communication device receiving fifth indication information, where the fifth indication information is used to instruct the first communication device to switch the first AI model representation mode .
  • the fifth indication information includes at least one of the following: 1) the AI model representation mode selected by the second communication device from the AI model representation modes supported by the first communication device; 2) the Multiple AI model representation modes supported by the second communication device.
  • the method further includes: no longer transmitting AI information between the first communication device and the second communication device when at least one of the following conditions is met: 1) The first communication device only Support an AI model representation; 2) The AI model representation supported by the first communication device does not have the AI model representation that the second communication device expects to switch to; 3) The first communication device does not send the AI model representation Feedback information of the fifth indication information.
  • the first communication device is a terminal
  • the second communication device is a network-side device
  • the network side instructs the terminal to switch the AI model representation mode (which may be realized through fifth instruction information).
  • the network side decides to change the AI framework that matches the terminal according to the usage situation, including one of the following: a) the network side selects a new AI framework from the AI framework capabilities reported by the terminal and instructs the terminal; The optional AI framework is sent to the terminal for selection; c) If the terminal can only support one AI framework, or there is no AI framework that the network side wants to switch among the AI frameworks supported by the terminal, or the terminal feedbacks that it is not selected, the network side indicates whether the terminal Disconnect from AI.
  • the method further includes: the first communication device (such as the base station before the terminal handover) sends the AI model representation used or supported by the second communication device (such as the terminal) to the second communication device (such as the terminal) Three communication devices (such as the target base station after the terminal is handed over); wherein, the second communication device is also configured to transmit AI information with the third communication device.
  • the first communication device such as the base station before the terminal handover
  • sends the AI model representation used or supported by the second communication device such as the terminal
  • the second communication device such as the terminal
  • Three communication devices such as the target base station after the terminal is handed over
  • the second communication device is also configured to transmit AI information with the third communication device.
  • the first communication device is a network-side device
  • the second communication device is a terminal.
  • AI model representation information of the terminal is exchanged between the cells.
  • the old cell transmits information such as the situation of the AI network and the AI matching framework of the terminal to the new cell.
  • the method further includes: the first communication device (such as the target base station after the terminal handover) receives sixth indication information from the third communication device (such as the base station before the terminal handover); The first communication device determines at least one of the following according to the sixth indication information: whether to transmit AI information between the first communication device and the second communication device; The AI model representation method used to transmit AI information between communication devices.
  • the first communication device such as the target base station after the terminal handover
  • receives sixth indication information from the third communication device such as the base station before the terminal handover
  • the first communication device determines at least one of the following according to the sixth indication information: whether to transmit AI information between the first communication device and the second communication device;
  • the AI model representation method used to transmit AI information between communication devices.
  • the first communication device is a network-side device
  • the second communication device is a terminal.
  • AI model representation information of the terminal is exchanged between the cells.
  • the new cell decides whether to continue to establish AI model transfer with the terminal according to its own capabilities, and whether the user needs to adjust the AI framework; if adjustment is required, the new cell sends signaling to the terminal for adjustment.
  • the methods provided in the above two embodiments further include: the first communication device receiving seventh indication information from a fourth communication device (such as a core network device); 7.
  • the core network device can also adjust the cell information. For example, the core network device re-sends the required AI information to the new cell according to the cell switching situation; the new cell and the terminal re-establish the link for AI information transmission, and use the new AI framework; the terminal uses the new AI framework and parameters to retrain the AI model.
  • the method further includes one of the following: 1) the first communication The device does not establish a communication connection with the third communication device, but is still connected with the second communication device; 2) The first communication device establishes a communication connection with the third communication device, and the first communication device establishes a communication connection with the third communication device. 3) The first communication device establishes a communication connection with the third communication device, and the first communication device stops using the AI function.
  • the first communication device is a terminal
  • the second communication device is a network-side device
  • the new cell to be accessed by the terminal does not support the use of the AI function
  • the terminal may perform one of the following: 1) Do not switch cells. 2) When the cell is switched, the AI information is no longer transmitted.
  • the AI model used alone on the terminal side can continue to run, such as channel estimation based on the terminal AI, etc.; the function that requires the terminal and the network side to use the AI model at the same time stops and switches to the traditional method. For example, AI-based channel state information (Channel State Information, CSI) feedback, etc. 3) Switch the cell, cut off all AI connections, stop using the AI function, and the terminal completely restores the traditional method.
  • CSI Channel State Information
  • the first communication device is a terminal and the second communication device is a network-side device as an example.
  • the first communication device and the second communication device may both be terminals, and the specific implementation process will not be described with examples.
  • the method further includes: after the first communication device determines that the AI supported by the first communication device When the model representation matches the AI model representation supported by the second communication device, the first communication device sends second request information, where the second request information is used to request the first communication device and The second communication device transmits AI information using a matching AI model representation; the first communication device receives second feedback information, and the second feedback information is used to indicate that the first communication device and the second communication device The communication device transmits AI information using a matching AI model representation.
  • the method further includes at least one of the following: 1) The first communication device obtains the AI supported by the second communication device Model representation; 2) The first communication device sends the AI model representation supported by the first communication device to the second communication device.
  • the first communication device and the second communication device are two parallel nodes, if they are both terminals, the first communication device and the second communication device may use the same AI framework.
  • each AI node sends the AI framework it can support to all participating AI nodes. For example, when AI node A wants to establish a data connection with AI node B, it first distinguishes between itself and the AI node. Whether B has the same AI framework capability, if so, send a request to AI node B, after AI node B receives it, it will feedback whether it can use the same AI framework as AI node A.
  • the method further includes: the first communication device sends third request information to the fifth communication device, so The third request information is used to request the first communication device and the second communication device to use a matching AI model expression to transmit AI information; the first communication device receives the first communication from the fifth communication device eighth indication information, where the eighth indication information instructs the first communication device and the second communication device to transmit AI information using a matching AI model representation.
  • the fifth communication device stores the AI model expression supported by the first communication device and the AI model expression supported by the second communication device; or, the third request information includes the The AI model expression supported by the first communication device, the fifth communication device is further configured to acquire the AI model expression supported by the second communication device when receiving the third request information; or, the The third request information includes an AI model expression supported by the first communication device, and the fifth communication device is further configured to send the AI model expression supported by the first communication device to the second communication device, And based on the report result of the second communication device, it is determined that the second communication device supports the transmission of AI information in an AI model representation mode that matches that of the first communication device.
  • the first communication device and the second communication device are two parallel nodes, if both are terminals, the fifth communication device may be a third-party node, and the third-party node assists the first communication device and the second communication device in using the same Matching AI framework.
  • the third-party node may be a special terminal, a base station, a core network device, and the like.
  • a third-party node requires all participating AI nodes to send their supported AI frameworks.
  • AI node A sends a request to establish a connection with AI node B to a third-party node, and the content includes at least one of the following: the identification of the AI node that requests the connection, the AI framework that AI node A can support, and the AI framework that AI node A wants to use ;
  • the third-party node decides whether to establish an AI connection between AI node A and AI node B according to the AI framework capabilities of AI node A and AI node B and the actual situation; the third-party node sends instruction information to AI node A and AI node B.
  • the third-party nodes do not know the AI framework capabilities of other AI nodes.
  • AI node A sends a request to establish a connection with AI node B to a third-party node, and the content includes at least one of the following: the identification of the AI node that requests the connection, the AI framework that AI node A can support, and the AI framework that AI node A wants to use ;
  • the third-party node requires AI node B to report its capabilities and make a decision based on it; or the third-party node sends information to B, and B makes a decision and reports the result; the third-party node sends information to A.
  • This embodiment mainly introduces the CSI feedback process based on the AI model (or AI network).
  • the terminal and the network use a joint AI network to perform CSI feedback, that is, the terminal converts the channel information into several bits of CSI feedback information through the AI network, and reports it to the base station, and the base station receives the CSI feedback information of the terminal, The channel information is recovered through the AI network on the base station side.
  • the CSI feedback here focuses on the Pre-coding Matrix Indicator (PMI) information, which can be the calculated pre-coding matrix or the channel itself.
  • PMI Pre-coding Matrix Indicator
  • the cell When a user accesses a cell, the cell will send frame information that can be supported by the cell to each user. Specifically, it can be broadcast through a Physical Random Access Channel (PRACH), or it can be sent to the user through a data channel after access. User, for all users, the cell sends the same frame information. After receiving the framework information, the terminal selects whether there is a suitable framework according to its own capabilities.
  • PRACH Physical Random Access Channel
  • the terminal finds that all the frameworks supported by the cell cannot be supported by itself, or the terminal itself does not support the AI function, the terminal will feed back a message to the base station, indicating that no suitable framework has been selected.
  • the terminal finds and suits its own framework, the terminal will feed back the selected framework and whether there is additional framework information, such as the version of the framework, special operation sets, and so on.
  • the base station determines whether to establish AI information transmission with the terminal according to the content fed back by the user. If the AI information transmission cannot be established, a non-AI codebook is used for CSI feedback.
  • the base station uses the corresponding AI framework to send the trained network to a terminal, ensuring that it is a data structure that the terminal can load.
  • the specific AI model can only send the network part of the terminal, or can send the joint network of the base station and the terminal together.
  • a user accesses a cell
  • the user reports the frame information that it can support, and the network side selects the appropriate frame and sends the CSI under the corresponding frame according to the frame information supported by the user.
  • Feedback AI model or if the base station finds that a unified AI framework cannot be established, it chooses to use non-AI codebook feedback.
  • the specific signaling interaction process can be that when the user accesses the cell, he interacts with each cell, and when other conditions are the same, preferentially select the cell that can match the AI framework, or that the user access After entering the cell, determine the framework information with the cell you are accessing.
  • This embodiment mainly introduces the channel measurement process based on the AI network.
  • UE can use AI network to perform channel measurement, including channel state information reference signal (Channel State Information-Reference Signal, CSI-RS), demodulation reference signal (Demodulation Reference Signal, DMRS) and other channels Estimation and radio resource management (Radio Resource Management, RRM) measurement.
  • CSI-RS Channel State Information-Reference Signal
  • DMRS Demodulation Reference Signal
  • RRM Radio Resource Management
  • a data channel will be established between the new cell and the old cell, and the old cell will send the AI framework information of the current user to the new cell. If the new cell does not support the AI framework, it will notify the UE to restore AI method for channel measurement, this notification can be downlink control information (Downlink Control Information, DCI), Media Access Control Control Element (Media Access Control Control Element, MAC CE) directly allows the terminal to modify the method, or radio resource control ( Radio Resource Control, RRC) configuration takes effect after a delay.
  • DCI Downlink Control Information
  • Media Access Control Element Media Access Control Element
  • MAC CE Media Access Control Element
  • RRC Radio Resource Control
  • the new cell may also resend supported framework information to the user, or require the user to report other supported framework information for re-matching.
  • the specific method is similar to the first embodiment.
  • the new cell can support this framework, the new cell can directly use the corresponding framework to send the network structure and parameters of the new channel measurement without notifying the user. If there is a difference in version information between the framework supported by the new cell and the framework used by the user, the user may be notified whether the feedback is compatible with other versions.
  • the old cell when the new cell does not support the user's framework, it can notify the old cell to send the user's framework capability, or the old cell can directly send the user's capability to the new cell, so that no Users report their capabilities, and they can directly obtain user capabilities and select a new framework.
  • This embodiment mainly introduces the base station assisted positioning process based on the AI network.
  • the AI positioning on the terminal side is to process the positioning signal through the AI network to determine the user's location.
  • the training and inference of the network can be performed simultaneously, that is, continuous training can be performed.
  • the AI positioning on the network side can send the information on the network side to a user after training through the AI network, thereby assisting the user in positioning.
  • Positioning accuracy has a lot to do with motion speed.
  • low-speed motion users can use a simple network or even a simple framework for training, thereby reducing the amount of calculation and power consumption, while high-speed users need complex networks.
  • a more powerful framework for training to improve positioning accuracy Therefore, as the user's movement speed changes, both the AI network and the AI framework may change.
  • the Caffe2 framework is used for training and inference of the positioning network.
  • the user can apply for a more refined framework for training and inference, such as Use TensorFlow2 for inference and training to improve the speed of training and the accuracy of inference.
  • the user chooses to continue using the existing framework, or use a non-AI method for channel prediction. If the user can support other frameworks and needs to switch, the user sends a switching request to the base station, carrying the framework and information to be switched, and the base station judges whether it can support and switch according to the framework information switched by the user, and instructs the user whether to switch .
  • the user only sends a switching request, and the base station determines whether the frame can be switched according to the business situation, and indicates the result to the user. If possible, the frame information that can be switched is issued synchronously, and the user selects the desired frame for switching, or allows the user to report the switching frame. , Supported framework information, and then the base station selects the framework.
  • the terminal After the new framework is determined, the terminal continues to train under the new framework, and the network continues to generate auxiliary information under the new framework, which is passed to the terminal.
  • This embodiment mainly introduces AI network interaction between terminals.
  • AI networks are affected by the channel environment and require continuous training as the terminal moves. Update the network.
  • terminal B enters the area of terminal A
  • terminal A can pass the trained network to terminal B, and terminal B performs training based on the network of terminal A. Since A and B are in similar areas, the channel information is related to a certain extent. Therefore, using A's network to continue training can help B converge faster.
  • the training complexity can be reduced by passing the trained network, or even directly use the network trained by other nodes.
  • Two terminals using the AI network can exchange information. For example, terminal A sends an AI framework matching request to terminal B through the SideLink channel, including the framework information it can support, and terminal B judges whether it is based on the framework it is using. It can match with terminal B, and then send matching information to terminal B.
  • terminal A sends a request to the network side, and the network side judges whether the two terminals can perform framework matching according to the framework capability of terminal A and the previously matched framework capability of terminal B, and notifies terminal A to use the same framework as terminal B. After the framework is matched, terminal B can directly transmit network parameters to terminal A.
  • the AI information transmission method provided in the embodiment of the present application may be executed by the AI information transmission device, or a control module in the AI information transmission device for executing the AI information transmission method.
  • the method for transmitting the AI information performed by the AI information transmission device is taken as an example to describe the AI information transmission device provided in the embodiment of the present application.
  • Fig. 3 is a schematic structural diagram of an apparatus for transmitting AI information according to an embodiment of the present application, and the apparatus may correspond to the first communication device in other embodiments.
  • the device 300 includes the following modules.
  • the transmission module 302 may be configured to transmit AI information with the second communication device; wherein, the first AI model representation used by the apparatus matches the second AI model representation used by the second communication device.
  • the apparatus 300 further includes a processing module, such as a processor.
  • a processing module such as a processor.
  • the AI information transmission device since the first AI model representation used by the AI information transmission device matches the second AI model representation used by the second communication device, in this way, the AI information transmission device and The second communication device maintains the same understanding of the AI information in the AI model representation mode, and the AI information transmission device and the second communication device can transmit the AI information, which is conducive to improving the performance of the communication system.
  • the first AI model representation used by the apparatus is the same as the second AI model representation used by the second communication device; or, the version supported by the first AI model representation The versions supported by the second AI model representation manner are mutually progressive.
  • the transmission module 302 is configured to at least one of the following: receive AI information from the second communication device; send AI information to the second communication device.
  • the transmission module 302 is further configured to: receive first indication information, where the first indication information is used to indicate multiple AI model representation modes supported by the second communication device, so The multiple AI model representations include the second AI model representation; sending first feedback information, the first feedback information is used to indicate the AI model selected by the device from the multiple AI model representations A representation manner, the selected AI model representation manner includes the first AI model representation manner.
  • the transmission module 302 is further configured to: send second indication information, where the second indication information is used to indicate the AI model expression mode supported by the device, and the AI model supported by the device
  • the model representation mode includes the first AI model representation mode
  • the second indication information is also used for the second communication device to select an AI model representation mode from the AI model representation modes supported by the device, and the selected The AI model representation manner includes the second AI model representation manner.
  • the transmission module 302 is further configured to: receive third indication information, where the third indication information is used to instruct the apparatus to receive or send the AI information.
  • the transmission module 302 is further configured to: send first request information, where the first request information is used to request switching of the first AI model representation manner.
  • the first request information includes at least one of the following: an AI model representation supported by the device; the device selects from multiple AI model representations supported by the second communication device The selected AI model representation mode; the moment when the first AI model representation mode is switched.
  • the transmission module 302 is further configured to: receive fourth indication information, and perform one of the following according to the fourth indication information: no longer transmit AI with the second communication device Information; transmit AI information with the second communication device based on the switched AI model representation mode; transmit AI information with the second communication device based on the original AI model representation mode.
  • the transmission module 302 is further configured to: receive fifth indication information, where the fifth indication information is used to instruct the apparatus to switch the first AI model representation manner.
  • the fifth indication information includes at least one of the following: an AI model representation mode selected by the second communication device from AI model representation modes supported by the device; Multiple AI model representations supported by communication devices.
  • the transmission module 302 is further configured to: no longer transmit AI information with the second communication device when at least one of the following conditions is satisfied: the device only supports one an AI model expression manner; the AI model expression manner supported by the apparatus does not have the AI model expression manner that the second communication device expects to switch to; the apparatus does not send the feedback information of the fifth indication information.
  • the transmission module 302 is further configured to: send the AI model expression used or supported by the second communication device to a third communication device; wherein, the second communication device is also It is used to transmit AI information with the third communication device; or, receiving sixth indication information from the third communication device, and determining at least one of the following according to the sixth indication information: the device and the first communication device Whether to transmit AI information between the two communication devices; the AI model expression used for transmitting AI information between the device and the second communication device.
  • the transmission module 302 is further configured to: receive seventh indication information from the fourth communication device; and adjust the AI model representation mode used according to the seventh indication information.
  • the transmission module 302 is also used for one of the following: not communicating with the third communication device
  • the third communication device establishes a communication connection, still connected to the second communication device; establishes a communication connection with the third communication device, and does not transmit AI information with the third communication device; establishes a communication connection with the third communication device Communication connection, stop using AI function.
  • the transmission module 302 is further configured to: when it is determined that the AI model representation supported by the device matches the AI model representation supported by the second communication device, Sending second request information, where the second request information is used to request the apparatus and the second communication device to use a matching AI model representation to transmit AI information; receiving second feedback information, where the second feedback information uses Instructing the apparatus and the second communication device to transmit AI information using a matching AI model representation.
  • the transmission module 302 is further configured to at least one of the following: acquire the AI model representation supported by the second communication device; send the AI model supported by the device to the second communication device AI model representation.
  • the transmission module 302 is further configured to: send third request information to a fifth communication device, where the third request information is used to request that the device and the second communication device Transmitting AI information using a matching AI model representation; receiving eighth instruction information from the fifth communication device, the eighth instruction information instructing the apparatus and the second communication device to use a matching AI model Representation way to transmit AI information.
  • the fifth communication device stores the AI model representation supported by the apparatus and the AI model representation supported by the second communication device; or, the third request information includes The AI model expression supported by the device, the fifth communication device is further configured to obtain the AI model expression supported by the second communication device when receiving the third request information; or, the The third request information includes the representation of the AI model supported by the device, and the fifth communication device is further configured to send the representation of the AI model supported by the device to the second communication device, and based on the second communication The reporting result of the device determines that the second communication device supports the transmission of AI information in an AI model representation manner that matches that of the apparatus.
  • the device 300 can refer to the process of the method 200 corresponding to the embodiment of the present application, and each unit/module in the device 300 and the above-mentioned other operations and/or functions are respectively in order to realize the corresponding process in the method 200, And can achieve the same or equivalent technical effect, for the sake of brevity, no more details are given here.
  • the AI information transmission device in the embodiment of the present application may be a device, a device with an operating system or an electronic device, or a component, an integrated circuit, or a chip in a terminal.
  • the apparatus or electronic equipment may be a mobile terminal or a non-mobile terminal.
  • the mobile terminal may include but not limited to the types of terminals 11 listed above, and the non-mobile terminal may be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television ( television, TV), teller machines or self-service machines, etc., are not specifically limited in this embodiment of the present application.
  • the AI information transmission device provided by the embodiment of the present application can realize each process realized by the method embodiment in FIG. 2 and achieve the same technical effect. To avoid repetition, details are not repeated here.
  • this embodiment of the present application further provides a communication device 400, including a processor 401, a memory 402, and programs or instructions stored in the memory 402 and operable on the processor 401,
  • a communication device 400 including a processor 401, a memory 402, and programs or instructions stored in the memory 402 and operable on the processor 401
  • the communication device 400 is a terminal
  • the program or instruction is executed by the processor 401
  • each process of the above-mentioned AI information transmission method embodiment can be realized, and the same technical effect can be achieved.
  • the communication device 400 is a network-side device, when the program or instruction is executed by the processor 401, each process of the above-mentioned AI information transmission method embodiment can be achieved, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.
  • the embodiment of the present application also provides a terminal, including a processor and a communication interface, and the communication interface is used to transmit AI information with a second communication device; wherein, the first AI model representation used by the terminal is the same as the second The second AI model representation used by the communication device matches.
  • This terminal embodiment corresponds to the above-mentioned terminal-side method embodiment, and each implementation process and implementation mode of the above-mentioned method embodiment can be applied to this terminal embodiment, and can achieve the same technical effect.
  • FIG. 5 is a schematic diagram of a hardware structure of a terminal implementing an embodiment of the present application.
  • the terminal 500 includes but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, and a processor 510, etc. at least some of the components.
  • the terminal 500 can also include a power supply (such as a battery) for supplying power to various components, and the power supply can be logically connected to the processor 510 through the power management system, so as to manage charging, discharging, and power consumption through the power management system. Management and other functions.
  • a power supply such as a battery
  • the terminal structure shown in FIG. 5 does not constitute a limitation on the terminal, and the terminal may include more or fewer components than shown in the figure, or combine certain components, or arrange different components, which will not be repeated here.
  • the input unit 504 may include a graphics processing unit (Graphics Processing Unit, GPU) 5041 and a microphone 5042, and the graphics processing unit 5041 is used in a video capture mode or an image capture mode by an image capture device (such as the image data of the still picture or video obtained by the camera) for processing.
  • the display unit 506 may include a display panel 5061, and the display panel 5061 may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.
  • the user input unit 507 includes a touch panel 5071 and other input devices 5072 .
  • the touch panel 5071 is also called a touch screen.
  • the touch panel 5071 may include two parts, a touch detection device and a touch controller.
  • Other input devices 5072 may include, but are not limited to, physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be repeated here.
  • the radio frequency unit 501 receives the downlink data from the network side device, and processes it to the processor 510; in addition, sends the uplink data to the network side device.
  • the radio frequency unit 501 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like.
  • the memory 509 can be used to store software programs or instructions as well as various data.
  • the memory 509 may mainly include a program or instruction storage area and a data storage area, wherein the program or instruction storage area may store an operating system, an application program or instructions required by at least one function (such as a sound playback function, an image playback function, etc.) and the like.
  • the memory 509 may include a high-speed random access memory, and may also include a non-transitory memory, wherein the non-transitory memory may be a read-only memory (Read Only Memory, ROM), a programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically erasable programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
  • ROM Read Only Memory
  • PROM programmable read-only memory
  • Erasable PROM Erasable PROM
  • EPROM electrically erasable programmable read-only memory
  • flash memory for example at least one disk storage device, flash memory device, or other non-transitory solid state storage device.
  • the processor 510 may include one or more processing units; optionally, the processor 510 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, application programs or instructions, etc., Modem processors mainly handle wireless communications, such as baseband processors. It can be understood that the foregoing modem processor may not be integrated into the processor 510 .
  • the radio frequency unit 501 may be used to transmit AI information with the second communication device; wherein, the first AI model representation mode used by the terminal matches the second AI model representation mode used by the second communication device .
  • the terminal and the second communication device have an understanding of the AI model under the AI model representation mode.
  • the understanding of the information remains consistent, and the AI information can be transmitted between the terminal and the second communication device, which is beneficial to improving the performance of the communication system.
  • the terminal 500 provided in the embodiment of the present application can also implement the various processes in the above embodiment of the AI information transmission method, and can achieve the same technical effect. To avoid repetition, details are not repeated here.
  • the embodiment of the present application also provides a network-side device, including a processor and a communication interface, and the communication interface is used to transmit AI information with a second communication device; wherein, the first AI model representation used by the network-side device is the same as The representation manner of the second AI model used by the second communication device matches.
  • the network-side device embodiment corresponds to the above-mentioned network-side device method embodiment, and each implementation process and implementation mode of the above-mentioned method embodiment can be applied to this network-side device embodiment, and can achieve the same technical effect.
  • the embodiment of the present application also provides a network side device.
  • the network side device 600 includes: an antenna 61 , a radio frequency device 62 , and a baseband device 63 .
  • the antenna 61 is connected to the radio frequency device 62 .
  • the radio frequency device 62 receives information through the antenna 61, and sends the received information to the baseband device 63 for processing.
  • the baseband device 63 processes the information to be sent and sends it to the radio frequency device 62
  • the radio frequency device 62 processes the received information and sends it out through the antenna 61 .
  • the foregoing frequency band processing device may be located in the baseband device 63 , and the method performed by the network side device in the above embodiments may be implemented in the baseband device 63 , and the baseband device 63 includes a processor 64 and a memory 65 .
  • the baseband device 63 can include at least one baseband board, for example, a plurality of chips are arranged on the baseband board, as shown in FIG. The operation of the network side device shown in the above method embodiments.
  • the baseband device 63 may also include a network interface 66 for exchanging information with the radio frequency device 62, such as a Common Public Radio Interface (CPRI).
  • CPRI Common Public Radio Interface
  • the network-side device in the embodiment of the present application also includes: instructions or programs stored in the memory 65 and operable on the processor 64, and the processor 64 calls the instructions or programs in the memory 65 to execute the modules shown in FIG. 3 To avoid duplication, the method of implementation and to achieve the same technical effect will not be repeated here.
  • the embodiment of the present application also provides a readable storage medium.
  • the readable storage medium may be volatile or non-volatile.
  • the readable storage medium may be transient or non-volatile. Transient, the readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the various processes of the above-mentioned AI information transmission method embodiments can be achieved, and the same technical effect can be achieved. In order to avoid Repeat, no more details here.
  • the processor may be the processor in the terminal described in the foregoing embodiments.
  • the readable storage medium includes computer readable storage medium, such as computer read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.
  • the embodiment of the present application further provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, the processor is used to run programs or instructions, and realize the implementation of the above-mentioned AI information transmission method
  • the chip includes a processor and a communication interface
  • the communication interface is coupled to the processor
  • the processor is used to run programs or instructions, and realize the implementation of the above-mentioned AI information transmission method
  • the chip mentioned in the embodiment of the present application may also be called a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip.
  • An embodiment of the present application further provides a computer program product, the computer program product is stored in a non-transitory storage medium, and the computer program product is executed by at least one processor to implement the above-mentioned AI information transmission method embodiment.
  • Each process can achieve the same technical effect, so in order to avoid repetition, it will not be repeated here.
  • the embodiment of the present application further provides a communication device, which is configured to execute each process of the above-mentioned AI information transmission method embodiment, and can achieve the same technical effect. To avoid repetition, details are not repeated here.
  • the term “comprising”, “comprising” or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or device. Without further limitations, an element defined by the phrase “comprising a " does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising that element.
  • the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions are performed, for example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
  • the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation.
  • the technical solution of the present application can be embodied in the form of computer software products, which are stored in a storage medium (such as ROM/RAM, magnetic disk, etc.) , CD-ROM), including several instructions to enable a terminal (which may be a mobile phone, computer, server, air conditioner, or network-side device, etc.) to execute the methods described in various embodiments of the present application.

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Abstract

Des modes de réalisation de la présente demande relèvent du domaine technique des communications. La présente demande concerne un procédé et un dispositif de transmission d'informations d'intelligence artificielle (IA). Le procédé de transmission d'informations d'IA selon les modes de réalisation de la présente demande comprend l'étape suivante : des informations d'IA sont transmises entre un premier dispositif de communication et un second dispositif de communication ; et un premier mode de représentation de modèle d'IA utilisé par le premier dispositif de communication correspond à un second mode de représentation de modèle d'IA utilisé par le second dispositif de communication.
PCT/CN2022/132086 2021-11-16 2022-11-15 Procédé et dispositif de transmission d'informations d'intelligence artificielle WO2023088269A1 (fr)

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CN112965804A (zh) * 2021-03-25 2021-06-15 深圳市优必选科技股份有限公司 一种处理信息的方法、装置、终端、系统以及存储介质

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CN111837425A (zh) * 2020-06-10 2020-10-27 北京小米移动软件有限公司 一种接入方法、接入装置及存储介质
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