WO2022000216A1 - Procédé et dispositif de communication, dispositif électronique et support d'enregistrement lisible par ordinateur - Google Patents

Procédé et dispositif de communication, dispositif électronique et support d'enregistrement lisible par ordinateur Download PDF

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Publication number
WO2022000216A1
WO2022000216A1 PCT/CN2020/099051 CN2020099051W WO2022000216A1 WO 2022000216 A1 WO2022000216 A1 WO 2022000216A1 CN 2020099051 W CN2020099051 W CN 2020099051W WO 2022000216 A1 WO2022000216 A1 WO 2022000216A1
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Prior art keywords
information
terminal
communication method
network node
initiate
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PCT/CN2020/099051
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English (en)
Chinese (zh)
Inventor
李艳华
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北京小米移动软件有限公司
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Application filed by 北京小米移动软件有限公司 filed Critical 北京小米移动软件有限公司
Priority to CN202080001172.4A priority Critical patent/CN114208255A/zh
Priority to PCT/CN2020/099051 priority patent/WO2022000216A1/fr
Publication of WO2022000216A1 publication Critical patent/WO2022000216A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/002—Transmission of channel access control information
    • H04W74/006—Transmission of channel access control information in the downlink, i.e. towards the terminal
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning

Definitions

  • the present disclosure relates to the field of communication technologies, and in particular, the present disclosure relates to a communication method, a communication device, an electronic device, and a computer-readable storage medium.
  • AI/ML-based mobile applications are increasingly computationally intensive, memory-intensive, and power-hungry.
  • terminals often have strict energy consumption, computing and memory cost constraints. Therefore, it is usually necessary to separate the AI/ML operation type services on the terminal and the network.
  • AI/ML operation type services for example, AI/ML model training operations
  • service eg, call service
  • the present disclosure provides a communication method and device, an electronic device, and a computer-readable storage medium.
  • the present disclosure provides a communication method, the communication method comprising: sending first information, wherein the first information is used to enable a terminal to determine to initiate a service of an artificial intelligence or machine learning operation type.
  • the first information is used to enable the access layer of the terminal to determine to initiate a service of an artificial intelligence or machine learning operation type.
  • the first information includes at least one of the following: information related to network node capabilities; network comprehensive capability indication information; information related to terminal capabilities; direct indication of the business.
  • the information related to the network node capability includes: at least one item of network node capability indication information.
  • the network comprehensive capability indication information is information obtained by comprehensively considering the at least one item of network node capability indication information.
  • the information related to the network node capability further includes: a threshold corresponding to each item of network node capability indication information in the at least one item of network node capability indication information.
  • the network comprehensive capability indication information further includes: a threshold corresponding to the network comprehensive capability.
  • the information related to the terminal capability includes: a threshold corresponding to each item of terminal capability information of the at least one item of terminal capability information.
  • the sending the first information includes: sending the first message through at least one of main information, a remaining minimum system message, or other system messages.
  • the communication method may further include: when the first message is sent through other system messages, in response to at least one item of information included in the first information being changed, not changing the system message The system message value label in .
  • the present disclosure provides a communication method, the communication method includes: acquiring first information; and determining to initiate a service of an artificial intelligence or machine learning operation type based on the first information.
  • the acquiring and the determining are performed through an access stratum of a terminal, wherein the communication method further includes: notifying a non-access stratum of the terminal of a result of the determination.
  • determining to initiate a business of an artificial intelligence or machine learning operation type based on the first information includes at least one of the following:
  • the communication method may further include: estimating resources required for a business of an artificial intelligence or machine learning operation type to be initiated. Determining to initiate a business of an artificial intelligence or machine learning operation type based on the first information includes: determining to initiate a business of an artificial intelligence or machine learning operation type based on the estimated resources and/or the first information.
  • the present disclosure provides a communication device, the communication device comprising: a communication module configured to: send first information, wherein the first information is used to make a terminal determine to initiate an artificial intelligence or machine learning operation type of business.
  • the present disclosure provides a communication device, the communication device comprising: a communication module configured to: acquire first information; and a processing module configured to: determine to initiate an artificial intelligence or a machine based on the first information Learn to operate types of business.
  • the present disclosure also provides an electronic device, the electronic device includes a memory and a processor; a computer program is stored in the memory; the processor is configured to execute the above-mentioned method when the computer program is executed.
  • the present disclosure also provides a computer-readable storage medium, in which a computer program is stored, the computer program being used to execute the method as described above when executed by a processor.
  • 1 is a schematic diagram of an architecture of a communication system
  • FIG. 2 is a schematic flowchart of a communication method provided in an embodiment of the present disclosure
  • FIG. 3 is a schematic diagram of a communication device provided in an embodiment of the present disclosure.
  • FIG. 4 is a schematic diagram of another communication device provided in an embodiment of the present disclosure.
  • FIG. 5 is a schematic structural diagram of an electronic device provided by the present disclosure.
  • FIG. 1 is a schematic diagram of the architecture of a communication system 100 to which an embodiment of the disclosure is applied.
  • a communication system 100 may include a base station 110 and a terminal 120 .
  • Terminal 120 is located in a cell covered by base station 110 and can communicate with base station 110 .
  • FIG. 1 shows only one base station 110, one terminal 120, and three cells that the base station 110 can cover, these are only exemplary, and exemplary embodiments of the present disclosure are not limited thereto.
  • the communication system 100 may further include multiple base stations, multiple terminals located in various cells, and/or access points, and the like.
  • terminals may include, but are not limited to, cellular phones, smart phones, wearable devices, computers, personal digital assistants (PDAs), personal communication system (PCS) devices, personal information managers (PIMs), personal navigation devices (PNDs) ), global positioning systems, multimedia devices, Internet of Things (IoT) devices, etc.
  • PDAs personal digital assistants
  • PCS personal communication system
  • PIMs personal information managers
  • PNDs personal navigation devices
  • global positioning systems multimedia devices
  • IoT Internet of Things
  • the computationally intensive, energy-intensive part of AI/ML can be offloaded to the network node, while the Privacy-sensitive and latency-sensitive parts are left on the terminal.
  • Terminals can perform operations/specific parts/layers in the model and send intermediate data to network nodes.
  • the network nodes execute the remaining parts/layers and feed back the inference results to the terminal.
  • the key to splitting the business of AI/ML operation types is to choose the best splitting mode and splitting point to ensure that the required resources are lower than the upper limit of the resources available on the terminal, and to optimize computing, storage/memory, power consumption, terminal side and network side communication resources, etc.
  • the resource requirements for uplink and downlink are very different.
  • a large amount of downlink bandwidth is required because the AI/ML model download is involved; while for the AI/ML operation in the network cloud training mode, because it involves For the upload of training data, a large amount of uplink bandwidth is required, while for downlink only the result of inference after training is not required. large bandwidth. Therefore, when a user (eg, the user's terminal 120 ) initiates an application for model training, the required bandwidth may be as high as 20 Gbps (gigabits per second) and a large amount of computing resources are required.
  • an embodiment of the present disclosure proposes a mechanism for notifying a terminal of related information in a system message to restrict the terminal from initiating a service of an AI/ML operation type.
  • FIG. 2 shows a schematic flowchart of a communication method according to an embodiment of the present disclosure.
  • first information may be sent.
  • the base station may send (or notify) the first information to the terminal.
  • the first information is used to enable the terminal to determine whether to initiate an AI/ML operation type service.
  • the first message is used to make an access (AS, Access Stratum) layer or a non-access (NAS, Non Access Stratum) layer of the terminal determine whether to initiate an AI/ML operation type service.
  • the first message is used to make the AS layer of the terminal determine whether to initiate an AI/ML operation type service.
  • the specific manner in which the base station sends the first message to the terminal is not limited in the embodiment of the present disclosure.
  • the first message may be sent to the terminal through a system message or other agreed manner.
  • the first information may include at least one of the following: information related to network node capabilities; network comprehensive capability indication information; information related to terminal capabilities; Direct instruction information.
  • direct indication information for indicating whether to initiate an artificial intelligence or machine learning operation type service may be referred to as "direct indication information”
  • auxiliary information information other than “direct indication information”
  • the information related to the network node capability in the first information may include: at least one item of network node capability indication information.
  • the at least one item of network node capability indication information may include at least one of the following: computing capability indication information, radio resource capability indication information, and backward link bandwidth indication information.
  • the at least one item of network node capability indication information may be a resource that a network node (eg, a base station) can provide for AI/ML operation type services (eg, a resource provided for AI/ML model training), or It can be a resource already occupied by a network node.
  • the computing capability indication information may include the occupancy of at least one of the memory, CPU, storage space of the network node (this may be indicated in the form of a percentage or high, high, low) or the current load of the network situation;
  • the wireless resource capability indication information may include the bandwidth provided by the network node, the current spectrum utilization rate, etc., which may also be indicated in the form of percentage or high, medium and low;
  • the backward link bandwidth indication information may include the relationship between the base station and the core network element. The bandwidth of the interface link between them, or the bandwidth of the interface link between the base station and the dedicated server that provides AI/ML services.
  • the example of the at least one item of network node capability indication information is not limited to the above embodiments.
  • the at least one item of network node capability indication information may also include the number of operations broadcasted by the network node that it can support, such as addition and multiplication operations. number of times.
  • the information related to the network node capability in the first information may further include: a threshold corresponding to each item of network node capability indication information in the at least one item of network node capability indication information.
  • a threshold corresponding to each item of network node capability indication information in the at least one item of network node capability indication information.
  • the threshold may be the same as the one used for AI/ML model training.
  • the threshold may be a threshold corresponding to the already occupied resource.
  • the inventive concept is not limited thereto, for example, when at least one item of network node capability indication information is a resource that has been occupied by the network node, the threshold may be a threshold corresponding to the available resources, in this case, the terminal (for example, AS layer) can first infer the threshold corresponding to the occupied resources based on the threshold corresponding to the available resources, and then determine whether AI/ML can be initiated according to at least one item of network node capability indication information and the inferred threshold Operation type business.
  • the information related to the network node capability may further include: computation capability decision Threshold, radio resource capability decision threshold and/or backward link bandwidth decision threshold.
  • the threshold information is used to make the terminal (eg, the AS layer of the terminal) compare each item of network node capability indication information in the first information with the corresponding threshold to determine whether to initiate an AI/ML operation type service. This will be described in detail later in the decision step performed by the terminal (eg, the AS layer of the terminal).
  • the network comprehensive capability indication information in the first information is information obtained by comprehensively considering at least one item of network node capability indication information described above.
  • the base station can obtain the network comprehensive capability indication information by comprehensively evaluating the computing capability, radio resource capability and backward link bandwidth of the network node, for example, the network comprehensive capability indication information can be represented by the signal load.
  • the traffic capacity may refer to the traffic capacity currently carried by the network node or the remaining traffic capacity of the network node.
  • the network comprehensive capability indication information in the first information may further include: a threshold corresponding to the network comprehensive capability.
  • the network comprehensive capability indication information when the network comprehensive capability indication information is represented by the signal load, the network comprehensive capability indication information may further include a threshold corresponding to the signal load.
  • the threshold is used to make the terminal (eg, the AS layer of the terminal) compare each item of network node capability indication information in the first information with the corresponding threshold to determine whether to initiate an AI/ML operation type service.
  • the above-mentioned threshold information (ie, the threshold corresponding to each item of network node capability indication information in the at least one item of network node capability indication information, the threshold corresponding to the network comprehensive capability) may be included in the first information, so as to be sent to the terminal through the network node; as another example, these threshold information may not be included in the first information, that is, not sent to the terminal through the network node, but may be pre-stored in the terminal or connected to the terminal.
  • the pre-stored or solidified threshold information can be directly used when the terminal needs to make a decision; as another example, the terminal can obtain the threshold information in advance before receiving the first information; in addition, the network node can also periodically or at When necessary, the threshold information is sent, and the pre-stored threshold information is updated.
  • the information related to the terminal capability in the first information may include: a threshold corresponding to each item of terminal capability information of the at least one item of terminal capability information.
  • the at least one item of terminal capability information may include at least one of the following: terminal computing capability information, terminal power information.
  • the network node eg, base station
  • the network node needs to allow the terminal to initiate an AI/ML operation type service only when the terminal capability reaches a certain threshold.
  • the threshold that the terminal's current computing capacity margin needs to reach for example, the occupancy of at least one of the terminal's memory, CPU, and storage space indicated in the form of a percentage
  • the threshold that the terminal's current power margin needs to reach can be In the form of a percentage
  • the terminal power is lower than the required threshold, the terminal needs to be in a charging state, etc.
  • the first message may be sent through at least one of main information, Remaining Minimum System Information (RMSI, Remaining Minimum System Information), or other system information (SI, System Information).
  • RMSI Remaining Minimum System Information
  • SI System Information
  • the base station may notify the terminal in RMSI or other SI of the auxiliary information in the first message (ie, information related to network node capabilities, network integrated capability indication information, information related to terminal capabilities); and , the base station can notify the terminal of the direct indication information in the first message through master information (for example, master information block MIB (Master Information Block)), RMSI or other system messages (for example, system message block SIB (System Information Block)).
  • master information for example, master information block MIB (Master Information Block)
  • RMSI or other system messages for example, system message block SIB (System Information Block)
  • the base station may use an indication bit (one or more bits) in the system message to send direct indication information to directly inform the terminal whether the AI/ML operation type service can be initiated.
  • the indication bit may be carried in the MIB; for another example, the indication bit may be carried in the RMSI or other SIBs.
  • the communication method shown in FIG. 2 may further include: when the first message is sent through other system messages (ie, other system messages except MIB and RMSI), in response to at least one of the first messages included in the first message
  • the system message value tag (SI value tag) in the system message is not changed.
  • the base station needs to page the terminal by sending a paging message (paging), and accordingly, the terminal needs to monitor paging to obtain the change of the system message.
  • the SI value tag is not changed, so that the base station does not need to notify the terminal by paging, but the terminal needs to initiate an AI/ML operation type when the Before the service (ie, initiating AI/ML access), it monitors system messages by itself to obtain and/or update the first message, thereby saving resources. That is, the base station does not need to occupy resources to send paging messages, and the terminal does not need to frequently receive or parse the SI value tag, thereby saving power, transmission and/or computing resources.
  • a network node eg, a base station
  • the network node may send a plurality of pieces of information in the first information and/or an indication rule specifying valid information in the first information to the terminal according to the service of the AI/ML operation type that it can support, and the terminal may, according to the indication rule to determine the valid information among the multiple pieces of information, and to decide whether to initiate an AI/ML operation type service according to the valid information.
  • multiple pieces of information may indicate information related to network node capabilities (eg, at least one item of network node capability indication information and/or corresponding thresholds), network comprehensive capability indication information, and information related to terminal capability information (eg, a threshold corresponding to each item of at least one item of terminal capability information) and/or direct indication information.
  • the instruction rules may not be sent by the network node, but may be pre-written or stored in the terminal or a device connected to the terminal, or may be agreed through a protocol.
  • the network node may only send multiple pieces of information (eg, computing capability indication information, radio resource capability indication information, backward link bandwidth indication information and their corresponding thresholds) to the terminal, as well as designated computing capability indication information and radio resource capability indication
  • the information is an indication rule for valid information.
  • the terminal has received multiple pieces of information, it only uses the computing capability indication information, the wireless resource capability indication information and the corresponding threshold according to the indication rule obtained from the local area. Determines whether to initiate an AI/ML operation type service.
  • the network node may predetermine which information is valid according to the services of the AI/ML operation type that it can support, so as to send only valid information to the terminal. For example, the network node may predetermine that the threshold of the radio resource capability indication information and/or the terminal power information is valid information, so as to only send the radio resource capability indication information and/or the threshold of the terminal power information to the terminal, so that the terminal can use them to decide whether to Initiate business of AI/ML operation type.
  • the network node may comprehensively consider its capability information (eg, network node capability indication information) to determine the direct indication information, and send the direct indication information to the terminal, so that the terminal can directly determine whether to initiate or not according to the direct indication information AI/ML operation type business.
  • its capability information eg, network node capability indication information
  • the information sent by the network node to the terminal is valid by default, so the terminal can use the received information to decide whether to initiate an AI/ML operation type service.
  • the terminal may acquire the first information, and determine whether to initiate an AI/ML operation type service based on the acquired first information.
  • the base station may send the first message to the terminal through the system message, that is, carry the first message in the system message, and the terminal may obtain the system message before initiating the AI/ML service, so as to obtain the first information from the system message .
  • the above operations may be performed through the AS layer or the NAS layer of the terminal.
  • the above-mentioned acquisition and determination operations may be performed through the AS layer of the terminal.
  • the AS layer of the terminal is more controllable for the behavior of the terminal, because the policies are provided by the base station, and the terminal can make a decision according to the provided policy.
  • some decision conditions are related to users (eg, user preferences and privacy protection), and the decision is relatively complicated.
  • the AS layer of the terminal may notify the NAS layer of the terminal of the determination result, so that the NAS layer performs corresponding operations according to the determined result. For example, when the AS layer of the terminal determines based on the acquired first information that the service of the AI/ML operation type can be initiated, in step S120, the NAS layer can execute the service of initiating the AI/ML operation type.
  • the terminal determines whether to initiate an AI/ML operation type service based on the acquired first information, which may include at least one of the following:
  • the network node may send different first information for services of different AI/ML operation types, and the terminal may make a decision based on the information sent by the network node to determine whether to initiate the AI/ML operation type service.
  • the terminal receives different first information from the base station, it can judge which information is valid from the first information (similar to that described in step S110 ), or judge the priority of each piece of information.
  • the direct indication information may be determined as having the highest priority, so as to decide whether to initiate an AI/ML operation type based on the direct indication information preferentially or only based on the direct indication information. business.
  • the terminal may determine whether the computing capability indication information provided by the base station in the first message satisfies the requirements for initiating a service of an AI/ML operation type (eg, access for AI/ML model training). required resource requirements. If it is not satisfied, it is considered that the AI/ML service part of this type is allowed to access the cell (or base station).
  • the terminal eg, AS layer
  • the terminal can compare the resources (eg, the size of memory, CPU, and/or storage space that can be provided) that can be provided by the network node with the corresponding threshold, so as to determine whether the resources provided by the network node reach the threshold.
  • the corresponding threshold is used to determine whether AI/ML operation type services can be initiated.
  • the terminal for example, the AS layer
  • the terminal may decide whether the radio resource capability indication information provided by the base station in the first message satisfies the service of initiating AI/ML operation type (for example, the access of AI/ML model training) required resource requirements. If it is not satisfied, it is considered that the AI/ML service part of this type is allowed to access the cell (or base station).
  • the terminal for example, the AS layer
  • the terminal can determine whether it can initiate the operation by judging whether the resources provided by the network node (for example, the bandwidth provided by the network node) reach the corresponding threshold, or by judging whether the current frequency utilization rate of the network is lower than the corresponding threshold.
  • AI/ML operation type business.
  • the terminal may decide whether the backward link bandwidth indication information provided by the base station in the first message satisfies the service of initiating AI/ML operation type (for example, the connection for AI/ML model training). input) required resource requirements. If it is not satisfied, it is considered that the AI/ML service part of this type is allowed to access the cell (or base station). For example, whether the AI/ML operation type service can be initiated is determined by judging whether the resources provided by the network node (eg, the size of the backward link bandwidth provided by the network node) reach a corresponding threshold.
  • the service of initiating AI/ML operation type for example, the connection for AI/ML model training. input
  • the terminal may compare the network comprehensive capability indication information (eg, the signal load) in the first message with a corresponding threshold to determine whether to initiate an AI/ML operation type service.
  • the network comprehensive capability indication information eg, the signal load
  • the terminal may compare its own computing capability with the corresponding threshold indicated by the terminal computing capability information of the first message, or compare the remaining power of the terminal itself with the terminal computing capability information indicated by the terminal computing capability information.
  • the corresponding thresholds are compared to determine whether the AI/ML operation type service can be initiated.
  • a terminal may combine one or more of the above-described embodiments to determine whether an AI/ML operation type service can be initiated. For example, the terminal may determine whether the computing capability information of the base station and the computing capability of the terminal are both sufficient to initiate an AI/ML operation type service.
  • the communication method shown in FIG. 2 may further comprise: estimating the resources required for the service of the AI/ML operation type to be initiated.
  • the terminal eg, AS layer
  • the terminal may determine whether to initiate AI/ML operation type services based on the estimated resources and/or the first information.
  • the AS layer of the terminal can use historical records or other high-level instructions, or the AS layer of the terminal can pre-estimate the AI/ML to be initiated based on historical statistical information and/or user behavior (eg, the user's current communication behavior).
  • the resources required by the operation type of business so as to obtain the resource requirements of the initiated AI/ML model training access.
  • the history record may be record information of resources used when the terminal previously initiated the AI/ML operation type service.
  • the historical statistical information may be information obtained by performing statistical calculation on the record information of resources used when a service of the AI/ML operation type was previously initiated. Accordingly, the AS layer of the terminal can judge whether the resources provided by the network node meet the resource requirements (ie, compare the resources provided by the network nodes with the resource requirements) to determine whether to initiate an AI/ML operation type service.
  • the terminal may estimate in advance at least one of memory, CPU, and storage space required for the AI/ML operation type service to be initiated, and compare the estimated value with the value provided by the network node in the computing capability indication information Compare to determine whether to initiate an AI/ML operation type business.
  • the terminal may pre-estimate the number of addition and multiplication operations required for the AI/ML operation type service to be initiated, and compare the estimated number of times with the number of addition and multiplication operations supported by the network broadcast to determine whether to initiate the AI/ML operation type Business.
  • the terminal may pre-estimate the bandwidth (for example, the estimated bandwidth) required by the AI/ML operation type service to be initiated, and compare the estimated bandwidth with the bandwidth provided by the network node in the radio resource indication information to obtain Determines whether to initiate an AI/ML operation type business.
  • the bandwidth for example, the estimated bandwidth
  • the terminal can pre-estimate the required backward bandwidth of the AI/ML operation type to be initiated, and compare the required backward bandwidth with the bandwidth of the backward link provided by the network to determine whether to initiate AI /ML operation type business.
  • the communication method shown in FIG. 2 may further include: in response to determining that the AI/ML operation type service is not allowed to be initiated and only the AI/ML operation type service is initiated, identifying the cell state as "cell prohibited (cell prohibited)" bar)".
  • the terminal may receive system messages in the further cell and attempt to initiate AI/ML operation type traffic.
  • the NAS layer is notified that the current cell has access to the AI/ML model. Access is prohibited, but other services (for example, call services) can be initiated; if the AS layer of the terminal judges that access is allowed, otherwise the NAS layer is notified that the current cell is allowed to access the AI/ML model.
  • the above communication method can notify the terminal of network-related information as early as possible, so as to reasonably restrict or allow the terminal to initiate AI/ML operation type services.
  • FIG. 3 is a schematic diagram illustrating a communication device 300 according to an embodiment of the present disclosure.
  • the communication device 300 may include a communication module 310 .
  • the communication module 310 is configured to: send the first information.
  • the first information is used to enable the terminal to determine whether to initiate an artificial intelligence or machine learning operation type service.
  • the description about the first information is similar to step S110 in FIG. 2 , and repeated descriptions are omitted here for brevity.
  • the communication module may be a node on the base station side, an access point in a wireless local area network, or other control devices.
  • the communication module 310 may be configured to transmit the first message through at least one of a master message, a remaining minimum system message, or other system messages.
  • the structure of the communication device 300 shown in FIG. 3 is only exemplary, and embodiments of the present disclosure are not limited thereto, for example, the communication device 300 may further include a processing device for processing AI/ML operation type services, or A device that communicates with a dedicated server that provides AI/ML operation type services through the core network, etc.
  • the processing module in the communication device 300 may be configured to not change the system message in response to at least one item of information included in the first information being changed when the first message is sent through other system messages The system message value label in .
  • the communication device 300 may perform the operations in step S110 described above with reference to FIG. 2 , and repeated descriptions are omitted here for brevity.
  • FIG. 4 is a schematic diagram illustrating another communication device 400 according to an embodiment of the present disclosure.
  • the communication device 400 may include a communication module 410 and a processing module 420 .
  • the communication module 410 may be configured to acquire the first information.
  • the processing module 420 may be configured to: determine whether to initiate an AI/ML operation type service based on the first information.
  • the communication module 410 and the processing module 420 may be included in the AS layer or the NAS layer of the terminal. Preferably, both the communication module 410 and the processing module 420 may be included in the AS layer of the terminal.
  • the operation performed by the processing module 420 to determine whether to initiate an artificial intelligence or machine learning operation type service based on the first information may include at least one of the following:
  • the processing module 420 may perform operations similar to the decision operation of the terminal (eg, the AS layer) described with reference to FIG. 2 , and repeated descriptions are omitted here for brevity.
  • the processing module 420 may be further configured to: estimate the resources required for a business of the type of artificial intelligence or machine learning operation to be initiated, and determine whether to Launch an AI or machine learning operation type business.
  • the processing module 420 may be further configured to: in response to determining that initiation of services of the artificial intelligence or machine learning operation type is not allowed and that there are only services of the initiation artificial intelligence or machine learning operation type, identify the cell status as "Cell Prohibition".
  • the communication device 400 may further include a NAS layer for receiving the determined result from the AS layer, And when the AS layer determines to allow access, the NAS layer can initiate artificial intelligence or machine learning operations.
  • the communication device 400 may further include a memory for storing various data and information, and/or a sending module for transmitting data required for AI/ML operation type services to network nodes, and the like.
  • the devices provided in the embodiments of the present disclosure are devices that can execute the corresponding methods provided in the embodiments of the present disclosure, those skilled in the art can understand the The specific implementation of the device in the disclosed embodiment and its various modifications are not described in detail here for how the device implements the method in the embodiment of the present disclosure. As long as the devices used by those skilled in the art to implement the methods in the embodiments of the present disclosure fall within the scope of the intended protection of the present disclosure. Wherein, each module included in the above device may be specifically implemented by software and/or hardware.
  • the present disclosure also provides an electronic device, which may include at least one processor, and the processor may be configured to perform the method provided in any optional embodiment of the present disclosure.
  • the electronic device may include at least one memory in which a computer program (or may also be referred to as computer instructions or codes) is stored, and the at least one processor may execute any one of the present disclosure when running the computer program.
  • a computer program or may also be referred to as computer instructions or codes
  • the at least one processor may execute any one of the present disclosure when running the computer program.
  • the present disclosure also provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program can execute the communication method shown in any optional embodiment of the present disclosure.
  • FIG. 5 shows a schematic structural diagram of an electronic device that can be applied to the solution provided by the present disclosure.
  • the electronic device 5000 includes: a processor 5001 and a memory 5003 .
  • the processor 5001 is connected to the memory 5003, for example, through a bus 5002.
  • the electronic device 5000 may also include a transceiver 5004 .
  • the transceiver 5004 is not limited to one, and the structure of the electronic device 5000 does not constitute a limitation to the embodiments of the present disclosure.
  • the processor 5001 can be CPU (Central Processing Unit, central processing unit), general-purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), FPGA (Field Programmable Gate Array) , field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logical blocks, modules and circuits described in connection with this disclosure.
  • the processor 5001 may also be a combination that realizes computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.
  • the bus 5002 may include a path to transfer information between the components described above.
  • the bus 5002 may be a PCI (Peripheral Component Interconnect, Peripheral Component Interconnect Standard) bus or an EISA (Extended Industry Standard Architecture, Extended Industry Standard Architecture) bus or the like.
  • the bus 5002 can be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, only one thick line is used in FIG. 5, but it does not mean that there is only one bus or one type of bus.
  • the memory 5003 can be a ROM (Read Only Memory, read only memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory, random access memory) or other types of storage devices that can store information and instructions.
  • Dynamic storage device can also be EEPROM (Electrically Erasable Programmable Read Only Memory, electrically erasable programmable read only memory), CD-ROM (Compact Disc Read Only Memory, CD-ROM) or other optical disk storage, optical disk storage (including compressed compact disc, laser disc, compact disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer any other medium, but not limited to this.
  • the memory 5003 is used for storing application program codes (computer programs) for executing the solutions of the present disclosure, and the execution is controlled by the processor 5001 .
  • the processor 5001 is configured to execute the application program code stored in the memory 5003, so as to realize the content shown in any of the foregoing method embodiments.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

La présente invention concerne un procédé et un dispositif de communication, un dispositif électronique et un support d'enregistrement lisible par ordinateur. Le procédé de communication consiste à : transmettre de premières informations, les premières informations étant utilisées pour amener un terminal à déterminer s'il faut lancer un service d'un type d'opération d'intelligence artificielle (IA) ou d'apprentissage automatique (ML). La solution technique de la présente invention peut informer, le plus tôt possible, un terminal d'informations relatives à un réseau, afin de limiter raisonnablement ou de permettre au terminal de lancer un service d'un type d'opération d'IA/ML.
PCT/CN2020/099051 2020-06-29 2020-06-29 Procédé et dispositif de communication, dispositif électronique et support d'enregistrement lisible par ordinateur WO2022000216A1 (fr)

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CN202080001172.4A CN114208255A (zh) 2020-06-29 2020-06-29 通信方法及设备、电子设备以及计算机可读存储介质
PCT/CN2020/099051 WO2022000216A1 (fr) 2020-06-29 2020-06-29 Procédé et dispositif de communication, dispositif électronique et support d'enregistrement lisible par ordinateur

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WO2024092788A1 (fr) * 2022-11-04 2024-05-10 Shenzhen Tcl New Technology Co., Ltd. Système de communication sans fil et procédé de détermination d'un modèle ia/ml pendant une mobilité d'ue

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* Cited by examiner, † Cited by third party
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WO2024092788A1 (fr) * 2022-11-04 2024-05-10 Shenzhen Tcl New Technology Co., Ltd. Système de communication sans fil et procédé de détermination d'un modèle ia/ml pendant une mobilité d'ue

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