CN115225495A - Communication system, method, first functional body and storage medium - Google Patents
Communication system, method, first functional body and storage medium Download PDFInfo
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- H—ELECTRICITY
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The application discloses a communication system, a method, a first functional body and a storage medium. Wherein, communication system includes: a first functional body comprising a first AI functional body and/or a first digital twin functional body; at least one second AI functional body and/or at least one second digital twin functional body, one second AI functional body corresponding to at least one service object, one second digital twin functional body corresponding to at least one service object; the first AI functional body is used for controlling at least one second AI functional body; the second AI function body is used for providing service for the service object; a first digital twin function for controlling at least one second digital twin function; the second digital twin functional body is used for providing services for the service object; the service object contains at least one of: a core network; an access network; a transmission network; and (4) a terminal.
Description
Technical Field
The present application relates to the field of wireless communications, and in particular, to a communication system, a method, a first functional unit, and a storage medium.
Background
In the related art, in the fourth generation mobile communication technology (4G) or the fifth generation mobile communication technology (5G) network, an application manner of an Artificial Intelligence (AI) technology is an add-on AI. The cost and interoperability of AI usage approaches has resulted in an inability to apply AI technology usage to commercial networks; meanwhile, the use mode of the AI cannot reflect the gain of the AI technology to the network.
Disclosure of Invention
In order to solve the related technical problem, embodiments of the present application provide a communication system, a method, a first functional body, and a storage medium.
The technical scheme of the embodiment of the application is realized as follows:
an embodiment of the present application provides a communication system, including:
a first functional body comprising a first AI functional body and/or a first digital twin functional body;
at least one second AI function and/or at least one second digital twin function, one second AI function corresponding to at least one service object and one second digital twin function corresponding to at least one service object; wherein the content of the first and second substances,
the first AI function is used for controlling at least one second AI function;
the second AI function body is used for providing service for the service object;
the first digital twin function body is used for controlling at least one second digital twin function body;
the second digital twin function body is used for providing services for the service object;
the service object includes at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
In the foregoing solution, the controlling at least one second AI function includes at least one of:
arranging a second AI function body;
managing a second AI function;
a second AI function is deployed.
In the foregoing solution, the first AI function is further configured to perform at least one of the following operations:
performing an AI function for a first time period;
and receiving the information reported by the second AI functional body.
In the above scheme, the controlling at least one second digital twin function includes at least one of:
arranging a second digital twin functional body;
managing a second digital twin function;
a second digital twin function is deployed.
In the above solution, the first digital twin functional unit is further configured to perform at least one of the following operations:
performing a digital twinning function for a second time period;
and receiving information reported by the second digital twin.
In the foregoing solution, the second AI function is further configured to perform at least one of the following operations:
executing an AI function for a service object requirement during a third time period;
and reporting information to the first AI functional body.
In the above scheme, the second digital twin functional body is further configured to perform at least one of the following operations:
performing a digital twin function for service object requirements during a fourth time period;
and reporting information to the first digital twin functional body.
In the foregoing solution, the first AI function is further configured to configure to a second AI function of the terminal.
In the foregoing solution, the first AI function is further configured to perform configuration update to a second AI function of the terminal.
In the above solution, the first AI function configures the second AI function of the terminal based on the capability of the terminal.
In the above solution, the first digital twin function is further configured to configure to a second digital twin function of the terminal.
In the above solution, the first digital twin function is further configured to perform configuration update to the second digital twin function of the terminal.
In the above scheme, the first digital twin function configures to the second digital twin function of the terminal based on the capability of the terminal.
In the above solution, the first AI functional body is located on the AI layer of the first functional body, and the first digital twin functional body is located on the digital twin layer of the first functional body;
the second AI function is located at the AI layer of the service object, and the second digital twin function is located at the digital twin layer of the service object; wherein, the first and the second end of the pipe are connected with each other,
the digital twin layer is positioned at the lower layer of the AI layer.
In the scheme, the digital twin layer is positioned at the lower layer adjacent to the AI layer.
The embodiment of the present application further provides a communication method, applied to a first functional body, where the first functional body includes a first AI functional body and/or a first digital twin functional body, and the method includes:
the first AI functional body controls at least one second AI functional body to provide service for the service object; and/or the first digital twin function body controls at least one second digital twin function body to provide service for the service object; wherein the content of the first and second substances,
a second AI function corresponds to at least one service object and a second digital twin function corresponds to at least one service object;
the service object contains at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
In the foregoing solution, when the first AI function controls at least one second AI function to provide service for a service object, the method includes at least one of:
arranging a second AI function body;
managing a second AI function;
a second AI functionality is deployed.
In the above scheme, the method further comprises:
the first AI function performs at least one of:
performing an AI function for a first time period;
and receiving the information reported by the second AI functional body.
In the above solution, when the first digital twin function controls at least one second digital twin function to provide a service for a service object, the method includes at least one of:
arranging a second digital twin functional body;
managing a second digital twin function;
deploying a second digital twin function.
In the foregoing solution, the method further includes at least one of:
performing a digital twinning function for a second time period;
and receiving information reported by the second digital twin.
In the foregoing solution, the method further includes:
the first AI function configures a second AI function of the terminal.
In the above scheme, the method further comprises:
the first digital twin function is configured to a second digital twin function of the terminal.
The embodiment of the present application further provides a first functional body, including: a processor and a first memory for storing a computer program capable of running on the processor,
wherein the first processor is configured to perform the steps of any of the above methods when running the computer program.
Embodiments of the present application further provide a storage medium, on which a computer program is stored, where the computer program implements the steps of any one of the above methods when executed by a processor.
In the communication system, the method, the first functional unit and the storage medium provided by the embodiment of the present application, the first functional unit includes a first AI functional unit and/or a first digital twin functional unit; wherein a second AI function corresponds to at least one service object and a second digital twin function corresponds to at least one service object; the second AI function provides service for the service object under the control of the first AI function; the second digital twin function body provides service for the service object under the control of the first digital twin function body; the service object contains at least one of: a core network; an access network; a transmission network; and (4) a terminal. According to the scheme provided by the embodiment of the application, a distributed AI system and/or a distributed digital twin system are introduced, AI and digital twin functions are integrated with a core network, a transmission network, an access network and a terminal, so that an endogenous intelligent and digital twin network is realized, and gains brought to the network by an AI technology are improved.
Drawings
Fig. 1 is a schematic structural diagram of a communication system according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a distributed intelligent endogenous and digital twin network architecture according to an embodiment of the present application;
FIG. 3 is a diagram illustrating distributed intelligent endogenous and digital twin network functions and controls according to an exemplary embodiment of the present application;
FIG. 4 is a schematic configuration flow diagram of a terminal-side digital twin layer function according to an embodiment of the present application;
fig. 5 is a schematic configuration flow diagram of AI layer functions at the terminal side according to an embodiment of the application;
fig. 6 is a schematic structural diagram of a first functional body according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples.
In the related art, in the fourth generation mobile communication technology (4G) or the fifth generation mobile communication technology (5G) network, the AI technology is used in an external AI mode, that is, various information required for AI processing is reported to an AI function node through a network side (base station, core network) and a terminal side, so as to implement the processing related to the AI operation outside the network element, that is, the AI function node outside the network element performs data collection, processing and AI model training, and sends the result of the AI operation or the generated policy (english can be expressed as policy) to the network again, so that the following challenges that cannot be overcome exist:
1. in order to make the AI operation result more accurate or more effective, a large amount of real-time and fine-grained measurement information needs to be reported to an external AI center, that is, an AI function node, and this method needs to report a large amount of data to the AI center, resulting in a large cost overhead of a transmission network, causing a core network, a base station and a terminal to need to provide additional computing resources and storage resources for reporting measurement messages, and also causing an increase in power consumption of network equipment and terminal equipment, and the like, so that the cost (english can be expressed as cost) and interoperability (interconnection and interworking of different manufacturers) brought by this method cannot be commercialized in a commercial network;
2. in this way, the effectiveness of AI on the network depends on the accuracy of the measurement data, so that the result of AI operation or the generated strategy cannot match the needs of the network, and therefore, the gain of AI on the network cannot be reflected, and the vision of the intelligent network cannot be realized.
That is, in the related art, the cost and interoperability brought by the use of AI results in failure to apply the use of AI technology to commercial networks; meanwhile, the use mode of the AI cannot reflect the gain of the AI technology to the network.
Therefore, the sixth generation mobile communication technology (6G) network is a network with internal intelligence (which may be expressed as Native AI). In the 6G network of the endogenous intelligence, the AI is no longer merely a radio resource optimization for the wireless network, but an intelligence System (english can be expressed as AI System) integrated with the core network, the transmission network, and the radio access network. The 6G network needs to support services in multiple application scenarios, and the intelligent 6G network can achieve the above requirements.
Wherein, the Digital Twin (English can be expressed as Digital Twin, abbreviated as DT) system provides the operation basic environment for the internal intelligence of 6G, which provides the basic support for the AI-related processing and calculation and simplifies the physical network operation load and complexity. That is to say, the 6G digital twin system and the endogenous intelligence system together form a series of online operations such as operation, maintenance, application-oriented control calculation, etc. for the physical network, become the brain of the physical network, and command each part of the physical network to complete the service capability required by the agreement or the operator.
In summary, in a 6G network, endogenous intelligence and digital twin generation are the core features of the 6G network.
Based on this, in various embodiments of the present application, a distributed AI system and/or a distributed digital twin system are introduced, so that AI and digital twin functions are integrated with a core network, a transmission network, an access network, and a terminal.
An embodiment of the present application provides a communication system, as shown in fig. 1, the system includes:
a first functional body 101, the first functional body 101 comprising a first AI functional body 1011 and/or a first digital twin functional body 1012;
at least one second AI function 102 and/or at least one second digital twin function 103, one second AI function 102 corresponding to at least one service object, one second digital twin function 103 corresponding to at least one service object; wherein the content of the first and second substances,
the first AI function 1011 for controlling at least one second AI function 102;
the second AI function 102 is configured to provide a service for a service object;
said first digital twin function 1012 for controlling at least one second digital twin function 103;
the second digital twin function body 103 is used for providing services for service objects;
the service object contains at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
In actual application, the service object may also be referred to as an object. The service object refers to a functional body in the network.
The second AI function body 102 may specifically provide a service for a service object under the control of the first AI function body 1011 or the second AI function body 102 may provide a service for a service object independently.
Accordingly, the second digital twin function 103 may specifically provide services for service objects under the control of the first digital twin function 1012 or the second digital twin function 103 may provide services for service objects independently.
The transport network may be used to connect the access network to the core network or to connect an internal network element of the core network or to a function in the transport network.
As can be seen from the above description, the endogenous intelligence system and the endogenous digital twin system provided by the embodiments of the present application are both distributed; specifically, the endogenous intelligence embodiment includes a centralized AI function processing center (also referred to as AI processing center, i.e. the first AI function 1101) and AI functions distributed to various service objects (i.e. the second AI function 102), so that the network of the embodiment of the present application is a distributed endogenous intelligence network; accordingly, the endogenous digital twinning hierarchy comprises a centralized digital twinning function processing center (which may also be referred to as a digital twinning processing center, i.e. the first digital twinning function 1102), and distributed digital twinning functions distributed to the individual service objects, i.e. the second digital twinning function 103, and thus the network of the embodiment of the present application is a distributed endogenous digital twinning network.
Wherein the AI processing center is organically integrated with the distributed AI functions. In one embodiment, the first AI function 1011 is specifically configured to perform at least one of the following operations on the second AI function 102:
orchestrating a second AI function 102;
manage the second AI function 102;
the second AI function 102 is deployed.
That is, the controlling the at least one second AI function 102 includes at least one of:
orchestrating a second AI function 102;
manage the second AI function 102;
the second AI function 102 is deployed.
When actually applied, the scheduling of the second AI function 102 may include at least one of the following:
control the functional combination or selection or customization of the second AI function 102;
control or coordinate functional coordination, collaboration, parameter or information interaction between different second AI functionalities 102;
control the upgrading, modification or replacement of the running AI algorithm of the second AI function 102 (shutdown or start or restart of the AI algorithm);
parameter modification or tuning of the AI algorithm controlling the second AI function 102;
control the processing cycle of the different second AI functions 102, the division or definition of AI algorithm functions, etc.
The manage second AI function 102 may include at least one of:
activating or deactivating the second AI function 102;
initializing a second AI function 102, including initial selection or customization of an AI algorithm, etc.;
the second AI function 102 reports measurement management, including: the method comprises the steps of measurement reporting of the running state, starting or closing of the measurement reporting or modification of a reporting mode, subscription of measurement reporting content and the like.
The deploying the second AI function 102 may include: the overall planning of the AI functions between different or the same second AI functions 102 is performed, for example, the planning includes the requirement of cooperation between different second AI functions 102, the definition of the AI function of the same second AI function 102, and the like, and then the subsequent operations are performed through management and/or orchestration.
The first AI function 1011 is further configured to perform at least one of the following operations:
performing an AI function for a first time period;
the information reported by the second AI function 102 is received.
Here, the first AI function 1011 may control the second AI function 102 based on information (i.e., measurement information) reported by the second AI function 102.
Accordingly, the second AI function 102 is further configured to perform at least one of the following operations:
executing an AI function for the service object requirements during a third time period;
the information is reported to the first AI function 1011.
As can be seen from the above description, the centralized AI function processing center is primarily responsible for:
1. arranging, managing and deploying all distributed AI functional bodies;
2. the processing functions of the AI function processing center are performed (i.e., executed), including generating a control or processing cycle at a time granularity of a certain time scale (e.g., 10ms,100ms,1m, etc.) (i.e., according to a first time period), performing model training and data processing, control operations, strategy generation and configuration, or other processing at the corresponding time scale, that is, executing the AI function during the first time period or executing the AI function every other first time period.
In addition, the AI function processing center needs to support other function requirements on the centralized platform (i.e., the first functional body 101).
The distributed AI functionality is mainly responsible for:
1. receiving and executing an instruction of an AI function processing center;
2. for the requirement of the service object, completing (i.e., executing) a processing function of the corresponding AI, including generating a control or processing cycle (i.e., according to a third time period) according to a certain time scale (e.g., 1ms,0.5ms,0.1ms, less than 0.1ms, etc.), that is, generating a control or policy, that is, executing the AI function for the requirement of the service object in the third time period or executing the AI function for the requirement of the service object every third time period;
3. and generating an information Report meeting the requirement of an AI function processing center or a Response (Response) corresponding to a Request (Request) according to the information or data processed by the service object in real time, and completing (namely executing) a task of Zero Measurement Report (which can be expressed as Zero Measurement Report in English). Wherein the zero measurement reporting means: the measurement information of communication related functions such as a Packet Data Convergence Protocol (PDCP) function, a Radio Resource Control (RRC) function, or a Radio Link Control (RLC) function, etc. running on the service object does not need to be reported, but the information processed by the AI function is sent to the AI function processing center.
The centralized digital twin function processing center and the distributed digital twin function body are an organic whole. In an embodiment, the first digital twin function 1012 is specifically configured to perform at least one of the following operations on the second digital twin function 103:
arranging a second digital twin function 103;
managing a second digital twin function 103;
a second digital twin function 103 is deployed.
That is, the controlling at least one second digital twin function 103 includes at least one of:
arranging a second digital twin function 103;
managing a second digital twin function 103;
a second digital twin function 103 is deployed.
When actually applied, the arranging of the second digital twin function 103 may include at least one of the following:
controlling the functional combination or selection or customization of the second digital twin function 103;
controlling or coordinating functional coordination, collaboration, parameter or information interaction between different second digital twin functions 103;
control the upgrading, modification or replacement of the running digital twin algorithm of the second digital twin function 103 (shutdown or start or restart of the digital twin algorithm);
parameter modification or tuning of the digital twinning algorithm controlling the second digital twinning function 103;
control the processing cycle of the different second digital twin function 103, division or definition of the digital twin algorithm functions, etc.
The managing second digital twin function 103 may include at least one of:
activating or deactivating the second digital twin function 103;
initializing a second digital twin function 103, including initial selection or customization of a digital twin, etc.;
the second digital twin function 103 reports measurement management, including: the method comprises the steps of measurement reporting of the running state, starting or closing of the measurement reporting or modification of a reporting mode, subscription of measurement reporting content and the like.
The deploying the second digital twin function 103 may include: the overall planning of the digital twin function between different or identical second digital twin functions 103 is performed, for example including the requirement of cooperation between different second digital twin functions 103, the definition of the digital twin function of the same second digital twin function 103, etc., and then the subsequent operations are performed by management and/or orchestration.
The first digital twin function 1012 is further configured to perform at least one of:
performing a digital twinning function for a second time period;
and receiving the information reported by the second digital twin function body 103.
Here, the first digital twin function 1012 may control the second digital twin function 103 based on information (i.e., measurement information) reported by the second digital twin function 103.
As can be seen from the above description, the centralized digital twin function processing center is primarily responsible for:
1. arranging, managing and deploying all distributed digital twin functional bodies;
2. completing (i.e. executing) the on-line simulation support function required by the centralized AI function processing center, including receiving the reported information and processing, generating a control or processing cycle (i.e. according to a second time period) according to a certain time scale (e.g. 10ms,100ms,1m, etc.) or a mirror function of the AI service object generated according to a certain scale (i.e. a scale with a certain operation scale or a certain number of service objects, etc.), and allowing the AI function of the centralized AI function processing center to perform on-line simulation operation or processing on the service object so as to verify the availability, accuracy, etc. of the control, strategy or other information generated by the AI function, that is, executing the digital twin function in the second time period or executing the digital twin function in the second time period;
3. generating, managing and operating a mirror function corresponding to the AI service;
4. and generating information report meeting the requirement of the digital twin function processing center or Response (Response) corresponding to the Request (Request) according to the information or data processed by the service object in real time, and completing (namely executing) the task of zero measurement report. Wherein, the zero measurement reporting means: the information processed by the digital twin function is sent to the digital twin function processing center without reporting the measurement information of the communication related function running on the service object.
The distributed digital twin functionality is mainly responsible for:
1. under the control of a centralized digital twin function processing center, the support of distributed AI functional bodies is completed, wherein the distributed AI functional bodies comprise data collection processing, mirror image functional bodies of AI service objects and the like;
2. and the system is deeply fused with the service object of the AI, and provides online simulation data support for the distributed AI function body.
In practical application, the digital twin system and the AI system can run synchronously, and the digital twin system and the AI system are deployed synchronously, so that zero measurement reporting of a core network, a transmission network, an access network or internal functions thereof is realized, that is, zero measurement in the network and/or outside the network is realized through the AI and the digital twin system.
In practical applications, in the embodiments of the present application, a core network, a transport network, an access network, a terminal, and the like are referred to as functional entities, and some functions inside these functional entities may also be referred to as functional entities. From this point of view, the first functional body 101 may be located on the network side, the second AI functional body 102 and the second digital twin functional body 103 are distributed on each functional body, the first AI functional body 1011 controls the distributed second AI functional body 102, and the first digital twin functional body 1012 controls the distributed second digital twin functional body 103.
When the service object includes a core network, a service object may be a certain network element or certain network elements of the core network, or may be some functions inside a certain network element. When the service object includes an access network, the service object may specifically be a base station, such as an eNB, a gNB, or some function inside the base station. When the service object includes a transport network, the service object may specifically be a certain transport node (such as a router) or certain transport nodes of the transport network, or may be some functions inside a certain transport node, and the like.
The distributed intelligent endogenous and digital twin network provided by the embodiment of the application is an end-to-end network and comprises a network side and a terminal side.
An interface, such as an Application Programming Interface (API) or the like, exists between the first function 101 and the second AI function 102 and the second digital twin function 103. The first function 101 interacts with the second AI function 102 and the second digital twin function 103 via an interface.
In practical application, the network side may configure the AI and the digital twin at the terminal side through a wireless air interface, that is, bear configuration information through the established wireless connection. For example, the configuration information is sent on a Physical Downlink Shared Channel (PDSCH) channel, and the format may be a MAC Protocol Data Unit (PDU) format.
Based on this, in an embodiment, the first AI function 1011 is also configured to configure the second AI function 102 of the terminal.
In actual application, the first AI function 1011 may be configured to the second AI function 102 of the terminal based on the capability of the terminal.
Of course, the first AI function 1011 may also perform configuration update to the second AI function 102 of the terminal.
Specifically, the configuration and the configuration update may be performed to the second AI function 102 of the terminal through the air interface.
In an embodiment, the first digital twin function 1012 is further configured to configure the second digital twin function 103 of the terminal.
In practical applications, the first digital twin function body 1012 may be configured to the second digital twin function body of the terminal based on the capability of the terminal.
Of course, the first digital twin function 1012 may also perform a configuration update to the terminating second digital twin function 103.
Specifically, the first digital twin function 1012 may be configured and updated over the air to the second digital twin function 103 of the terminal.
The first functional unit 101 may be referred to as a processing center, a control center, or a management center, and in practical application, the first functional unit 101 may be disposed on an operation, maintenance and management (OAM) device (also referred to as an OAM system).
In one embodiment, the first AI function 1011 is located at an AI layer of the first function 101, and the first digital twin function 1012 is located at a digital twin layer of the first function 101;
the digital twin layer is positioned at the lower layer of the AI layer.
In practical application, the digital twin layer is located at a lower layer of the AI layer, that is, the AI layer is located at an upper layer of the digital twin layer, and the two functional layers may be adjacent to each other, that is, the digital twin layer may be located at an adjacent lower layer of the AI layer, and the two functional layers may not be adjacent to each other.
The communication system provided by the embodiment of the present application includes a first functional body 101 and at least one second AI functional body 102 and/or at least one second digital twin functional body 103; the first functional body 101 includes a first AI functional body 1011 and/or a first digital twin functional body 1012; wherein, a second AI function 102 corresponds to at least one service object, and a second digital twin function 103 corresponds to at least one service object; the second AI function 102 provides a service to a service object under the control of the first AI function 1011; the second digital twin function 103 provides services for service objects under the control of the first digital twin function 1012; the service object contains at least one of: a core network; an access network; a transmission network; and (4) a terminal. According to the scheme provided by the embodiment of the application, a distributed AI system and/or a distributed digital twin system are introduced, AI and digital twin functions are integrated with a core network, a transmission network, an access network and a terminal, so that a network of endogenetic intelligence and digital twin is realized, and gains brought to the network by AI technology are improved.
Based on the above system, an embodiment of the present application further provides a communication method, applied to a first functional body, where the first functional body includes a first AI functional body and/or a first digital twin functional body, and the method includes:
the first AI function body controls at least one second AI function body to provide service for the service object; and/or the first digital twin function controls at least one second digital twin function to provide service for the service object; wherein the content of the first and second substances,
a second AI function corresponds to at least one service object and a second digital twin function corresponds to at least one service object;
the service object contains at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
In an embodiment, when the first AI function controls at least one second AI function to provide service for the service object, the method includes at least one of:
arranging a second AI functional body;
managing a second AI function;
a second AI functionality is deployed.
In an embodiment, the method may further comprise:
the first AI function performs at least one of:
performing an AI function for a first time period;
and receiving the information reported by the second AI functional body.
In an embodiment, when the first digital twin function controls at least one second digital twin function to provide a service for a service object, the method comprises at least one of:
arranging a second digital twin functional body;
managing a second digital twin function;
deploying a second digital twin function.
In an embodiment, the method may further comprise at least one of:
performing a digital twinning function for a second time period;
and receiving information reported by the second digital twin.
In an embodiment, the method may further comprise:
the first AI function configures a second AI function of the terminal.
In an embodiment, the method may further comprise:
the first digital twin function is configured to a second digital twin function of the terminal.
The present application will be described in further detail with reference to the following application examples.
In the embodiment of the application, an AI function body and a digital twin function body are respectively introduced into protocol stack function bodies introduced into an OAM system, a core network, a transmission network, an access network, a terminal and other systems, and a centralized AI center interacts with a distributed AI function body, so that the distributed AI function body selects a targeted AI algorithm according to different driven objects (such as the function bodies of the core network, the transmission network, the access network, the terminal and other functions and a specific network function (such as a protocol function of an access and mobility management function (AMF), a Media Access Control (MAC)) of the function bodies, thereby realizing an AI-driven intelligent network.
The distributed intelligent endogenous and digital twin network scheme provided by the application embodiment is an end-to-end scheme and comprises a network side and a terminal side.
Fig. 2 illustrates a distributed intelligent endogenous and digital twin network architecture. As shown in fig. 2, the network architecture includes: a center (english center), a core network, a transport network, a Base Station (BS), and a User Equipment (UE); wherein, the first and the second end of the pipe are connected with each other,
in the center, a centralized AI function processing center and a digital twin function processing center are included, and the centralized AI function processing center and the digital twin function processing center run on a Cloud Platform (English can be expressed as Cloud Platform);
for a core network, an AI function body (which can be called CN-AI) and a digital twin function body (which can be called CN-DT) run on a cloud platform;
for the transmission network, an AI function body (which can be called TN-AI) and a digital twin function body (which can be called TN-DT) are operated on a cloud platform;
for the BS, an AI function body (may be referred to as BS-AI) and a digital twin function body (may be referred to as BS-DT) operate on a cloud platform, and support different functions such as a physical layer is realized through an Accelerator (Accelerator).
For the UE, an AI function (may be referred to as UE-AI) and a digital twin function operate on a terminal device with soft and hard separation (minimized cloud platform), the AI function and the digital twin function (may be referred to as UE-DT) operate on the cloud platform, and configuration, operation, deployment, and the like of the AI function and the digital twin function are realized under configuration on a network side.
That is to say, the system runs on the cloud platform, so that the integration of computing and storage is realized through the cloud platform.
The network side configures the configuration of the UE side through a wireless air interface, and carries through the established wireless connection. Such as on the PDSCH channel, in the format of MAC PDUs.
As shown in fig. 3, the centralized AI function processing center and the digital twin function processing center may be disposed on the OAM system, the AI and the digital twin control is end-to-end control, the processing center on the network side not only controls the AI and the digital twin function of the network side, but also controls the AI and the digital twin function on the terminal side through an air interface, including configuration of algorithm parameters, AI models, and the like; and the terminal reports the algorithm operation parameters or the measurement parameters and the like to the network side.
As shown in fig. 3, there are an AI Layer (english may be expressed as AI Layer) and a digital twin Layer (english may be expressed as DT Layer) that are equivalent on the network side and the terminal side.
Specifically, a digital twin layer and an AI layer are respectively introduced into a UE, an OAM system, a core network, a transport network, and a BS (Cloud-end (Cloud) wireless Cloud platform (RCP) and simple (Lite) AI wireless access point (RAP)), where the digital twin layer is at a lower layer of the AI layer, the AI layer is at an upper layer of the digital twin layer, and the two functional layers may be an adjacent upper layer and a lower layer (as shown in fig. 3) or may not be adjacent.
In this case, various Application Functions (Application or Functions) are run on the AI layer.
Specifically, for the UE, an Access Stratum (AS) and a Non-Access Stratum (NAS) are run, and various Applications (All kins of Applications). For the OAM system, functions of network management and maintenance, AI application open to the outside, maintenance and management functions of UE side AI and digital twin functions, etc. are operated. For the core network, defined core network functions are run, such as AMF, session Management Function (SMF), user Plane Function (UPF), etc. For the Transport network, functions such as Transport Bandwidth Allocation (Bandwidth Allocation), data Flow control (Data Flow control), and Transport Link quality guarantee (QoS of Transport Link) are executed. For the BS, the protocol functions of layer 1 (L1), layer 2 (L2), layer 3 (L3) are run.
The digital twin layer provides data processing service, model training service of on-line simulation, AI function service of on-line simulation and the like for the AI layer. Correspondingly, the AI layer puts forward an operation data requirement, an AI model training requirement, AI model operation result feedback information and the like to the digital twin layer.
The AI layer provides services for the upper layer; the AI layer provides various services driven by the AI to the upper layer, including AI analysis and flow control on the data plane, AI prediction on the control plane, dynamic modification of mapping relation driven by the AI, resource allocation driven by the AI, and the like.
The network side (i.e. the processing center) needs to configure the AI layer and the digital twin layer functions of the terminal side.
As shown in fig. 4, the configuration flow of the terminal-side digital twin layer function includes the following steps:
step 400: after the UE has Connected with the network, i.e. the UE is in a radio resource control Connected (RRC _ Connected) state, step 401 is executed;
step 401: a digital twin function body at a UE side initiates a Registration Request (namely DT Registration Request) to a function body at a network side (namely an OAM side);
here, the registering request may specifically include: the type of the UE (e.g., a common terminal, an internet of things terminal, a vertical industry terminal, an automobile terminal, or an aircraft terminal, etc.), a model (digital abstract feature) of a data service that the UE needs to be provided by a network, a UE computing capability model and a storage capability model, a UE wireless communication capability model (including a protocol-defined UE capability, a UE radio frequency capability, L1, L2, L3 protocol version numbers), a power model and an air interface transmit-receive power model of the UE (e.g., a constant power supply, a battery capacity, an air interface maximum receive and transmit power, etc.), and the like.
Step 402: the network side performs Registration Response (namely DT Registration Response) aiming at Registration;
here, after receiving the capability information (may also be referred to as DT information), the network side registers and activates the digital twin software body of the UE, and sends a registration response.
Wherein, the registration response carries an indication of success or failure of the UE registration, an update of an online simulation data processing algorithm available for the UE, and the like.
Step 403: UE or a network side initiates digital twin updating;
here, when the location of the user changes, for example, the network channel changes greatly, or the service requirement of the user changes, etc., the UE or the network initiates the digital twin update.
Step 404: and the network or the terminal performs reconfiguration response.
In steps 403 to 404, the model of the operation process of the digital twin functional body is updated, the interaction or information synchronization is performed on the online simulation result of one or more functions, or a relevant algorithm or algorithm parameter is configured, or various operation measurement information is reported, etc.
As shown in fig. 5, the configuration flow of the AI layer function at the terminal side includes the following steps:
step 500: the UE has Connected with the network, i.e. the UE is in RRC _ Connected state;
step 501: an AI function body at a UE side initiates a Registration Request (namely an AI Registration Request) to a network side OAM system (namely a centralized AI function processing center);
here, the registration request carries the capability of the UE, including the supportable AI model type or set of the UE, the algorithm type identifier, the computation capability (such as data size) of the AI, the requirement of burdening the computation load of the AI that needs to be provided by the network side (for example, 100 iterations of the algorithm, the UE needs the network to provide the result after 80 iterations of the computation, or the UE provides the result of 20 iterations of the computation to the network side), and so on.
Step 502: the network side establishes an AI function body of the UE in an OAM system, a core network, RCP, RAP and the like;
step 503: the network side performs Registration Response (namely AI Registration Response) aiming at Registration;
here, after receiving the capability information (may also be referred to as AI information), the network side registers and activates the AI function of the UE on the digital twin software of the UE, configures an available AI model or an algorithm set for the UE according to the request of the UE and by combining with an AI algorithm or a model supported by the network side, and transfers interface type configurations of different algorithm separation (sharing calculation load) parameters, and the like.
Step 504: UE or each functional unit of network initiates AI function update;
here, when the service model changes, the corresponding AI model needs to be changed, for example, when the physical channel changes, the model needs to be changed; for another example, the total number of users of the network is increased, AI calculation undertaken by each UE is reduced, and an AI model needs to be changed.
Step 505: and the network or the UE responds to the reconfiguration.
In steps 504 to 505, parameters, algorithms or models of the AI function operating process are updated, etc. The network side establishes the AI function body of the UE in an OAM system, a core network, RCP, RAP and the like so as to realize the updating of the AI function.
The AI layer of the OAM system interacts with the AI layers of other functional bodies through an interface (API); the digital twin layer of the OAM system interacts with the digital twin layer of other functionality through an interface (such as an API). Wherein, the digital twin layer of the OAM system interacts with the digital twin layer at the terminal side through an air interface (shown by a dotted line in FIG. 3, which indicates through the air interface); and the AI layer of the OAM system interacts with the AI layer at the terminal side through an air interface.
As can be seen from the above description, the solution provided by the embodiment of the present application has the following technical advantages:
1. network architecture with endogenic AI and digital twins facing;
2. fusion of endogenous AI and digital twins is realized;
3. the definition and control of endogenous AI and digital twin from end to end are realized;
4. the terminal can apply differentiated AI and digital twinning functions to the network side as required.
In order to implement the solution provided by the embodiment of the present application, an embodiment of the present application further provides a first functional body, as shown in fig. 6, where the first functional body 600 includes:
a communication interface 601 capable of information interaction with the second AI function and/or the second digital twin function;
the processor 602 is connected with the communication interface 601 to realize information interaction with the second AI function body and/or the second digital twin function body, and is used for executing the method provided by one or more technical schemes of the first function body side when running a computer program;
a memory 603, said computer program being stored on said memory 603.
It should be noted that: the specific processing of the processor 602 and the communication interface 601 may be understood with reference to the above-described methods.
Of course, in practice, the various components in the first functional body 600 are coupled together by a bus system 604. It is understood that the bus system 604 is used to enable communications among the components. The bus system 604 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are identified in fig. 6 as the bus system 604.
The memory 603 in the embodiment of the present application is used to store various types of data to support the operation of the first functional body 600. Examples of such data include: any computer program for operating on the first functionality 600.
The method disclosed in the embodiments of the present application may be applied to the processor 602, or implemented by the processor 602. The processor 602 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 602. The Processor 602 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. The processor 602 may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 603, and the processor 602 reads the information in the memory 603 and performs the steps of the aforementioned method in conjunction with its hardware.
In an exemplary embodiment, the first functional body 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, programmable Logic Devices (PLDs), complex Programmable Logic Devices (CPLDs), field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro Controllers (MCUs), microprocessors (microprocessors), or other electronic components for performing the aforementioned methods.
It is to be appreciated that the memory 603 in the embodiments of the subject application can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), synchronous Static Random Access Memory (SSRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), synchronous Dynamic Random Access Memory (SLDRAM), direct Memory (DRmb Access), and Random Access Memory (DRAM). The memories described in the embodiments of the present application are intended to comprise, without being limited to, these and any other suitable types of memory.
In an exemplary embodiment, the present application further provides a storage medium, i.e. a computer storage medium, specifically a computer readable storage medium, for example, including a memory 603 for storing a computer program, which can be executed by the processor 602 of the first functional body 600 to complete the steps of the foregoing first functional body side method. The computer readable storage medium may be Memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash Memory, magnetic surface Memory, optical disk, or CD-ROM.
It should be noted that: "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The technical means described in the embodiments of the present application may be arbitrarily combined without conflict.
The above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application.
Claims (24)
1. A communication system, comprising:
a first functional body comprising a first Artificial Intelligence (AI) functional body and/or a first digital twin functional body;
at least one second AI functional body and/or at least one second digital twin functional body, one second AI functional body corresponding to at least one service object, one second digital twin functional body corresponding to at least one service object; wherein, the first and the second end of the pipe are connected with each other,
the first AI function is used for controlling at least one second AI function;
the second AI function body is used for providing service for the service object;
the first digital twin function for controlling at least one second digital twin function;
the second digital twin functional body is used for providing service for the service object;
the service object includes at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
2. The system of claim 1, wherein the controlling at least one second AI function comprises at least one of:
arranging a second AI functional body;
managing a second AI function;
a second AI function is deployed.
3. The system of claim 1, wherein the first AI function is further configured to perform at least one of:
performing an AI function for a first time period;
and receiving the information reported by the second AI functional body.
4. The system of claim 1, wherein the controlling at least one second digital twin function comprises at least one of:
arranging a second digital twin functional body;
managing the second digital twin function;
a second digital twin function is deployed.
5. The system of claim 1, wherein the first digital twin function is further configured to perform at least one of:
performing a digital twinning function for a second time period;
and receiving information reported by the second digital twin.
6. The system of claim 1, wherein the second AI function is further configured to perform at least one of:
executing an AI function for the service object requirements during a third time period;
and reporting information to the first AI functional body.
7. The system of claim 1, wherein the second digital twin function is further configured to perform at least one of:
performing a digital twin function for service object requirements during a fourth time period;
and reporting information to the first digital twin functional body.
8. The system according to any one of claims 1 to 7, wherein the first AI function is further configured to configure a second AI function of the terminal.
9. The system of claim 8, wherein the first AI function is further configured to perform a configuration update to a second AI function of the terminal.
10. The system of claim 8, wherein the first AI function configures the second AI function of the terminal based on capabilities of the terminal.
11. The system of any of claims 1-7, wherein the first digital twin function is further configured to configure a second digital twin function of a terminal.
12. The system of claim 11, wherein the first digital twin function is further configured to perform a configuration update to a second digital twin function of a terminal.
13. The system of claim 8, wherein the first digital twin function is configured to the second digital twin function of the terminal based on capabilities of the terminal.
14. The system of any one of claims 1 to 7,
the first AI functional body is located on an AI layer of the first functional body, and the first digital twin functional body is located on a digital twin layer of the first functional body;
the second AI function is located at the AI layer of the service object, and the second digital twin function is located at the digital twin layer of the service object; wherein, the first and the second end of the pipe are connected with each other,
the digital twin layer is positioned at the lower layer of the AI layer.
15. The system of claim 14,
the digital twin layer is located at the lower layer next to the AI layer.
16. A communication method applied to a first functional body including a first AI functional body and/or a first digital twin functional body, the method comprising:
the first AI function body controls at least one second AI function body to provide service for the service object; and/or the first digital twin function body controls at least one second digital twin function body to provide service for the service object; wherein, the first and the second end of the pipe are connected with each other,
a second AI function corresponds to at least one service object and a second digital twin function corresponds to at least one service object;
the service object includes at least one of:
a core network;
an access network;
a transmission network;
and (4) a terminal.
17. The method of claim 16, wherein the first AI function controls at least one second AI function to service a service object, the method comprising at least one of:
arranging a second AI function body;
managing a second AI function;
a second AI functionality is deployed.
18. The method of claim 17, further comprising:
the first AI function performs at least one of:
performing an AI function for a first time period;
and receiving the information reported by the second AI functional body.
19. The method as claimed in claim 16 wherein the first digital twin function controls at least one second digital twin function to provide service to a service object, the method including at least one of:
arranging a second digital twin functional body;
managing a second digital twin function;
a second digital twin function is deployed.
20. The method of claim 19, further comprising at least one of:
performing a digital twinning function for a second time period;
and receiving information reported by the second digital twin.
21. The method of any one of claims 16 to 20, further comprising:
the first AI function configures a second AI function of the terminal.
22. The method of any one of claims 16 to 20, further comprising:
the first digital twin function is configured to a second digital twin function of the terminal.
23. A first functional body, characterized by comprising: a processor and a first memory for storing a computer program capable of running on the processor,
wherein the first processor is adapted to perform the steps of the method of any one of claims 16 to 22 when running the computer program.
24. A storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, is adapted to carry out the steps of the method according to any one of claims 16 to 22.
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| PCT/CN2022/086635 WO2022218347A1 (en) | 2021-04-15 | 2022-04-13 | Communication system and method, first functional entity, and storage medium |
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