Method, apparatus and system for model generation
The method and system improve digital twin model performance by integrating real-time data and distributed computing to adapt to changing physical environments, enhancing decision-making capabilities.
Patent Information
- Application Number
- PCT/CN2024/106122
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-07-18
- Publication Date
- 2026-01-22
AI Technical Summary
Current digital twin models struggle to adapt to rapidly changing physical environments, leading to suboptimal performance in decision-making processes.
A method and system for generating digital counterparts of physical worlds using real-time data and existing models, enabling dynamic model updates and distributed sub-model generation across multiple devices.
Enhances model performance by incorporating real-time data and leveraging distributed computing resources, resulting in improved adaptability and accuracy of digital twin models.
Smart Images

Figure CN2024106122_22012026_PF_FP_ABST
Abstract
Description
METHOD, APPARATUS AND SYSTEM FOR MODEL GENERATIONTECHNICAL FIELD
[0001] Embodiments of the present application relate to the field of communications, and more specifically, to a method, apparatus and a system for model generation.BACKGROUND
[0002] A digital twin (DT) model is used to generate a digital counterpart of a physical world, for example, a factory, a transport system, a cell and etc. A DT model may be used for decision making because it may simulate and predict a state of the physical world in a statistical sense.
[0003] However, the current DT model obtained by offline training is not performing well and cannot adapt to the rapidly changing physical world.
[0004] Therefore, an urgent technical problem to be solved is how to generate a model with better performance.SUMMARY
[0005] Embodiments of the present application provide a method, apparatus and a system for model generation, which may generate a model with better performance.
[0006] According to a first aspect, a communication method is described. The method may be applied at a first device side, for example, a first device or a component (for example, a circuit, a chip, or a chip system) in a first device. For example, the method is applied to a first device (e.g., a controller or a location server) . In the method, the first device receives first information, where the first information indicates a first model; and the first device generates a second model based on the first model and real-time data related to a physical world, where the second model is used to generate a digital counterpart of the physical world.
[0007] According to the foregoing method, the first device may obtain a first model from the second device, and may generate a second model based on the first model and real-time data. The second model generated in a (near) real-time way can have better performance.
[0008] According to a first aspect, in a possible design, the method further includes: transmitting second information, where the second information indicates the second model.
[0009] According to the foregoing method, the first device generates a second model based on the first model and real-time data, and the first device may transmit the new generated second model to the second device, to update the first model in the second device.
[0010] According to a first aspect, in a possible design, the real-time data includes one or more of: data that indicates the physical environment objects in the physical world; data that indicates radio signal propagation characteristics in the physical world; and data that indicates parameters associated with a wireless communication network deployed in the physical world.
[0011] According to the foregoing method, the real-time data can include various aspects of data, so that the digital counterpart generated by the second model can describe the physical world from various aspects.
[0012] According to a first aspect, in a possible design, the real-time data is obtained from one or more of: measuring the physical world, sensing the physical world, and a third model.
[0013] According to the foregoing method, the real-time data can be obtained from various implementations, and the second model generated based on these real-time data can have a better performance.
[0014] According to a first aspect, in a possible design, the method further includes: transmitting (740) third information, where the third information requests the first model.
[0015] According to the foregoing method, the first device may request a model from the second device and the second device can transmit the first model in response to the request. Multiple types of signaling interactions are supported between the first device and the second device.
[0016] According to a first aspect, in a possible design, the third information indicates one or more of: an identifier of a device that requests the first model, and requested parameter list associated with the first model.
[0017] According to the foregoing method, the first device may indicate various parameters related to the requested model, so that the second device could transmit the required first model reliably.
[0018] According to a first aspect, in a possible design, the method further includes: transmitting fourth information, the fourth information requests the real-time data; and receiving the real-time data.
[0019] According to the foregoing method, the first device may collect the real-time data from one or more other devices, and generate the second model based on the first model and collected real-time data reliably.
[0020] According to a first aspect, in a possible design, the fourth information indicates one or more of: a configuration for obtaining the real-time data; a configuration for reporting the real-time data; and at least one identifier of at least one device that obtains the real-time data.
[0021] According to the foregoing method, the first device may indicate various parameters related to the requested real-time data, so that it can obtain the real-time data reliably.
[0022] According to a first aspect, in a possible design, the method further includes: transmitting fifth information, where the fifth information indicates one or more first sub-models obtained based on the first model; and receive sixth information, where the sixth information indicates one or more second sub-models, the one or more second sub-models are generated based on the one or more first sub-models and the real-time data, and the second model is generated based on the one or more second sub-models.
[0023] According to the foregoing method, the first device may distribute one or more first sub-models to one or more other devices, and collect the generated second sub-models from the one or more other devices, to generate the second model based on the second sub-models. The model generation process can make full use of calculation power of multiple devices, which improves the efficiency of the model generation.
[0024] According to a first aspect, in a possible design, the fifth information further indicates one or more of: a configuration for obtaining the real-time data, a configuration for generating the one or more second sub-models, a configuration for reporting the one or more second sub-models, and at least one identifier of at least one device that generates the one or more second sub-models.
[0025] According to a first aspect, in a possible design, where the configuration for obtaining the real-time data indicates one or more of: a type of the real-time data, and at least one parameter that describes one or more tasks used for generating the real-time data.
[0026] According to a first aspect, in a possible design, the configuration for reporting the real-time data indicates one or more of: at least one parameter of the real-time data to be reported, and a physical resource used for reporting the real-time data.
[0027] According to the foregoing method, the first device may indicate various parameters related to the first sub-model and / or second sub-model, so that it can obtain the one or more second sub-models to generate the second model reliably.
[0028] According to a second aspect, a communication method is described. The method may be applied at a second device side, for example, a second device or a component (for example, a circuit, a chip, or a chip system) in a second device. For example, the method is applied to a second device (e.g., a could server) . In the method, the second device transmits first information, where the first information indicates a first model, the first model and real-time data related to the physical world are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.
[0029] The various implementations of the second aspect correspond to the various implementations of the first aspect, the technical effects can be referred to the description of first aspect, which are omitted here.
[0030] According to a second aspect, in a possible design, the method further includes: receiving second information, where the second information indicates the second model.
[0031] According to a second aspect, in a possible design, the real-time data includes one or more of: data that indicates the physical environment objects in the physical world, data that indicates radio signal propagation characteristics in the physical world, and data that indicates parameters associated with a wireless communication network deployed in the physical world.
[0032] According to a second aspect, in a possible design, the real-time data is obtained from one or more of: measuring the physical world, sensing the physical world, and a third model.
[0033] According to a second aspect, in a possible design, the method further includes: receiving third information, where the third information requests the first model.
[0034] According to a second aspect, in a possible design, the third information indicates one or more of: an identifier of a device that requests the first model, and requested parameter list associated with the first model.
[0035] According to a third aspect, a communication method is described. The method may be applied at a third device side, for example, a third device or a component (for example, a circuit, a chip, or a chip system) in a third device. For example, the method is applied to a third device. In the method, the third device obtains real-time data related to a physical world; and the third device transmits information related to the real-time data, where the real-time data and a first model are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.
[0036] The various implementations of the third aspect correspond to the various implementations of the first aspect, the technical effects can be referred to the description of first aspect, which are omitted here.
[0037] According to a third aspect, in a possible design, the method further includes: the third device receives fourth information, where the fourth information requests the real-time data, and the information related to real-time data includes the real-time data.
[0038] According to a third aspect, in a possible design, the fourth information indicates one or more of: a configuration for obtaining the real-time data, a configuration for reporting the real-time data, and an identifier of a device that obtains the real-time data.
[0039] According to a third aspect, in a possible design, the method further includes: the third device receives fifth information, where the fifth information indicates a first sub-model among one or more first sub-models obtained from the first model; and the third device generates a second sub-model based on the first sub-model and the real-time data, where the information related to the real-time data indicates the second sub-model.
[0040] According to a third aspect, in a possible design, the fifth information further indicates one or more of: a configuration for obtaining the real-time data, a configuration for generating the second sub-model, a configuration for reporting the second sub-model, and an identifier of a device that generates the second sub-model.
[0041] According to a first aspect, in a possible design, where the configuration for obtaining the real-time data indicates one or more of: a type of the real-time data, and at least one parameter that describes one or more tasks used for generating the real-time data.
[0042] According to a first aspect, in a possible design, the configuration for reporting the real-time data indicates one or more of: at least one parameter of the real-time data to be reported, and a physical resource used for reporting the real-time data.
[0043] According to a fourth aspect, a communication apparatus is described. The communication apparatus has a function of implementing the first aspect. For example, the communication apparatus includes a corresponding module, unit, or means for performing operations in the first aspect. The module, unit, or means may be specifically implemented by using software, may be implemented by using hardware, or may be implemented by using software in combination with hardware.
[0044] According to a fifth aspect, a communication apparatus is described. The communication apparatus has a function of implementing the second aspect. For example, the communication apparatus includes a corresponding module, unit, or means for performing operations in the second aspect. The module, unit, or means may be specifically implemented by using software, may be implemented by using hardware, or may be implemented by using software in combination with hardware.
[0045] According to a sixth aspect, a communication apparatus is described. The communication apparatus has a function of implementing the third aspect. For example, the communication apparatus includes a corresponding module, unit, or means for performing operations in the third aspect. The module, unit, or means may be specifically implemented by using software, may be implemented by using hardware, or may be implemented by using software in combination with hardware.
[0046] According to a seventh aspect, another communication apparatus is described. The communication apparatus includes a memory and one or more processors. The memory is configured to store a part or all of a necessary computer program or instructions for implementing a function in the first aspect. The one or more processors may execute the computer program or the instructions, and when the computer program or the instructions is / are executed, the communication apparatus is enabled to implement the method in any possible design or implementation of the first aspect.
[0047] In some implementations, the communication apparatus may further include an interface circuit, and the processor is configured to communicate with another apparatus or component through the interface circuit.
[0048] In some implementations, the communication apparatus may further include the memory.
[0049] The communication apparatus may be a first device, a module in a first device, or a chip responsible for a communication function in a first device, for example, a modem chip (also referred to as a baseband chip) or an SoC chip or an SIP chip that includes a modem module.
[0050] According to an eighth aspect, another communication apparatus is described. The communication apparatus includes a memory and one or more processors. The memory is configured to store a part or all of a necessary computer program or instructions for implementing a function in the second aspect. The one or more processors may execute the computer program or the instructions, and when the computer program or the instructions is / are executed, the communication apparatus is enabled to implement the method in any possible design or implementation of the second aspect.
[0051] In some implementations, the communication apparatus may further include an interface circuit, and the processor is configured to communicate with another apparatus or component through the interface circuit.
[0052] In some implementations, the communication apparatus may further include the memory.
[0053] The communication apparatus may be a second device, a module in a second device, or a chip responsible for a communication function in a second device, for example, a modem chip (also referred to as a baseband chip) or an SoC chip or an SIP chip that includes a modem module.
[0054] According to a ninth aspect, another communication apparatus is described. The communication apparatus includes a memory and one or more processors. The memory is configured to store a part or all of a necessary computer program or instructions for implementing a function in the third aspect. The one or more processors may execute the computer program or the instructions, and when the computer program or the instructions is / are executed, the communication apparatus is enabled to implement the method in any possible design or implementation of the third aspect.
[0055] In some implementations, the communication apparatus may further include an interface circuit, and the processor is configured to communicate with another apparatus or component through the interface circuit.
[0056] In some implementations, the communication apparatus may further include the memory.
[0057] The communication apparatus may be a third device, a module in a third device, or a chip responsible for a communication function in a third device, for example, a modem chip (also referred to as a baseband chip) or an SoC chip or an SIP chip that includes a modem module.
[0058] According to a tenth aspect, a communication system is described, where the communication system includes the communication apparatus according to the seventh aspect and the communication apparatus according to the eighth aspect.
[0059] In some implementations, the communication system further includes the communication apparatus according to the ninth aspect.
[0060] According to an eleventh aspect, a computer-readable storage medium is described. The computer-readable storage medium stores computer-readable instructions, and when a computer reads and executes the computer-readable instructions, the computer is enabled to perform the method in any one of the possible designs of the first aspect to the third aspect.
[0061] According to a twelfth aspect, this application provides a computer program product. When a computer reads and executes the computer program product, the computer is enabled to perform the method in any one of the possible designs of the first aspect to the third aspect.
[0062] According to a thirteenth aspect, this application provides a system comprising at least one of an apparatus in (or at) a first device of the present application, or an apparatus in (or at) a second device of the present application, or an apparatus in (or at) a third device of the present application.
[0063] According to a fourteenth aspect, this application provides a method performed by a system comprising at least one of an apparatus in (or at) a first device of the present application, and an apparatus in (or at) a second device of the present application.
[0064] In some implementations, this application provides a method performed by a system further comprising at least one of an apparatus in (or at) a third device of the present application.
[0065] This application encompasses various implementations, including not only method implementations, but also other implementations such as apparatus implementations and implementations related to non-transitory computer readable storage media. Implementations may incorporate, individually or in combinations, the features disclosed herein.DESCRIPTION OF DRAWINGS
[0066] FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present application;
[0067] FIG. 2 illustrates another example for communication system 100;
[0068] FIG. 3 illustrates an example of an apparatus 310 wirelessly communicating with another apparatus 320 in a communication system;
[0069] FIG. 4 illustrates an example of an apparatus 410;
[0070] FIG. 5 illustrates example of apparatus 510;
[0071] FIG. 6 illustrates a schematic diagram of devices (nodes) involved in the model generation;
[0072] FIG. 7 is a schematic flowchart of a communication method according to an embodiment of this application;
[0073] FIG. 8 illustrates a first implementation to generate the first model according to this application; and
[0074] FIG. 9 illustrates a second implementation to generate the first model according to this application.DESCRIPTION OF EMBODIMENTS
[0075] The following describes technical solutions of the present application with reference to the accompanying drawings.
[0076] FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present application.
[0077] Referring to FIG. 1, as an illustrative example, a simplified schematic illustration of a communication system is provided. The communication system 100 may comprise a radio access network 120. The radio access network (RAN) 120 may be a future generation radio access network, or a legacy (such as 5th generation (5G) , 4th generation (4G) , 3rd generation (3G) or 2nd generation (2G) ) radio access network, the RAN 120 may be a network using another radio access technology. In some implementations, radio access refers to a future generation air interface of standards which may comprise both terrestrial networks (TNs) and non-terrestrial networks (NTNs) , and more details will be described below. One or more communication electronic device (ED) 110a, 110b, 110c, 110d, 110e, 110f, 110g, 110h, 110i, 110j (generically referred to as 110) may be interconnected to one another or connected to one or more network nodes 170a, 170b (generically referred to as 170) in the RAN 120. A core network (CN) 130 may be a part of the communication system and may be dependent or independent of the radio access technology used in the communication system 100. The communication system 100 may also comprise a public switched telephone network (PSTN) 140, the internet 150, and other networks 160.
[0078] In general, the communication system 100 enables communication of multiple wireless or wired elements. The communication system 100 may provide content, such as voice, data, video, and / or text, via broadcast, multicast, groupcast, unicast, etc. The communication system 100 may operate by sharing resources, such as carrier spectrum bandwidth, among its constituent elements.
[0079] The communication system 100 may provide a wide range of communication services and applications including enhanced Mobile Broadband (eMBB) services, ultra-reliable low-latency communication (URLLC) services, massive machine type communication (mMTC) services, integrated sensing and communication (ISAC) , immersive communication, massive communication, Hyper reliable and low-latency communication, ubiquitous connectivity, integrated AI and communication, and other services that can be provided by a future generation communication system. The communication system 100 may provide other services and applications such as earth monitoring, remote sensing, passive sensing and positioning, navigation and tracking, autonomous delivery and mobility, etc.
[0080] The communication system 100 may include a terrestrial communication system (or network) and / or a non-terrestrial communication system (or network) . The communication system 100 may provide a high degree of availability and robustness through a joint operation of a terrestrial communication system and a non-terrestrial communication system. For example, integrating a non-terrestrial communication system (or components thereof) into a terrestrial communication system can result in a heterogeneous network comprising multiple layers. The heterogeneous network may achieve better overall performance through efficient multi-link joint operation, more flexible functionality sharing, and faster physical layer link switching between terrestrial networks and non-terrestrial networks. The terrestrial communication system and the non-terrestrial communication system could be considered sub-systems of the communication system 100.
[0081] FIG. 2 illustrates another example for communication system 100. As described earlier, the communication system 100 may include EDs 110a, 110b, 110c, 110d (generically referred to as ED 110) , RAN 120a, 120b, and one or more of a CN 130, a PSTN 140, the internet 150, and other networks 160. In addition, the communication system 100 may also include a non-terrestrial network (NTN) 120c. The RANs 120a, 120b may include respective network nodes 170a, 170b such as base stations 170a, 170b, which may be generically referred to as terrestrial network (TN) devices or terrestrial transmit and receive points (T-TRPs) 170a, 170b (generically referred to as 170) . As referred to herein, the terms “TRP” and “base station” may be used interchangeably unless explicitly noted otherwise in a given example or section. For brevity, this disclosure may primarily refer to base station; however, absent an explicit limitation, references to TRP are merely non-limiting instances of interchangeable use. The T-TRPs 170a, 170b may be base stations mounted on a building or tower. In one implementation, the NTN 120c includes a RAN node such as base station 172, which may be generically referred to as an NTN device, a non-terrestrial node, a non-terrestrial network device, a non-terrestrial base station, or a non-terrestrial transmit and receive point (NT-TRP) 172.
[0082] In some implementations, the NT-TRP 172 is not attached to the ground, for example, in the case of an airborne base station. An airborne base station may be implemented using communication equipment supported or carried by a flying device. For example, a flying device may include an airborne platform (such as a blimp or an airship) , balloon, drone (such as quadcopter) , and other types of aerial vehicles. In some implementations, an airborne base station may be supported or carried by an unmanned aerial system (UAS) or an unmanned aerial vehicle (UAV) , such as a drone. An airborne base station may be a moveable or mobile base station that can be flexibly deployed in different locations to meet network demand. A satellite base station is another example of a non-terrestrial base station. A satellite base station may be implemented using communication equipment supported or carried by a satellite. A satellite base station may also be referred to as an orbiting base station. High altitude platforms are yet another example of non-terrestrial base stations, including international mobile telecommunication base stations.
[0083] As referred to herein, and unless specified otherwise, a “TRP” may also refer to a T-TRP or an NT-TRP, a “T-TRP” may also refer to a “TN TRP” , and an “NT-TRP” may also refer to an “NTN TRP” . The NTN 120c may be considered to be a radio access network (RAN) , with operational aspects in common with the RANs 120a, 120b. The NTN 120c may include at least one NTN device and at least one corresponding terrestrial network device, the at least one NTN device may function as a transport layer device and the at least one corresponding terrestrial network device may function as a RAN node, which communicates with the ED 110 via the non-terrestrial network device. In addition, there may be an NTN gateway on the ground (i.e., referred to as a terrestrial network device) that also functions as a transport layer device to communicate with both the NTN device and the RAN node. The RAN node may communicate with the ED 110 via the NTN device and the NTN gateway. In some implementations, the NTN gateway and the RAN node may be located in the same device.
[0084] A base station (also referred to as a TRP as stated above) 170 may be a network element in radio access network responsible for radio transmission and reception in one or more cells to or from the user equipment. Base station 170 may be known by other names in some implementations, such as a base transceiver station (BTS) , a radio base station, a network node, a network device, a device on the network side, a transmit / receive node, a Node B, an evolved NodeB (eNodeB or eNB) , a Home eNodeB, a next Generation NodeB (gNB) , a transmission point (TP) , a site controller, an access point (AP) , a wireless router, a relay station, a terrestrial node, a terrestrial network device, a terrestrial base station, a positioning node, among other possibilities. The base station 170 may be a macro base station (BS) , a pico BS, a relay node, a donor node, or the like, or combinations thereof. When a base station 170 performs (or is configured to perform) a method described herein, it may be interpreted as the base station, one or more modules (or units) in the base station, a circuit or chip, or a combination thereof, may perform the method. For example, the circuit or chip may include a modem chip, also referred to as a baseband chip, a system on chip (SoC) including a modem core, system in package (SIP) ) , and the like, and may be responsible for one or more communication functions in the base station.
[0085] The EDs 110a-110d and TRPs 170a-170b, 172 are examples of communication equipment that can be configured to implement some or all of the operations and / or embodiments described herein. The T-TRP 170a forms part of the RAN 120a, which may include other TRPs, and / or other devices. Also, the TRP 170b forms part of the RAN 120b, which may include other TRPs, and / or devices. Each TRP 170a, 170b may transmit and / or receive wireless signals within a particular geographic region or area, sometimes referred to as a “cell” or “coverage area” . The TRPs 170a-170b may be responsible for allocating and / or configuring resources and transmission and / or reception in a set of cells. A cell may be a radio network object that can be uniquely identified from a (cell) identification that is broadcasted over a geographical region or area from base stations associated with the cell. A cell can work in either FDD or TDD mode. A cell may be further divided into cell sectors, and a base station 170a-170b may, for example, employ multiple transceivers to provide service to multiple sectors. In some implementations, there may be established pico or femto cells where the radio access technology supports such. In some implementations, multiple transceivers could be used for each cell, for example using multiple-input multiple-output (MIMO) technology. The number of RAN 120a-120b shown is an example only. Any number of RAN may be contemplated when devising the communication system 100.
[0086] Any base station may be a single element, as shown, or multiple elements, distributed in the corresponding RAN, or otherwise. In some implementations, a plurality of RAN nodes coordinate to assist the ED 110 in implementing radio access, and different RAN nodes separately implement different functions of the base station. For example, the RAN node may be a central unit (CU) , a distributed unit (DU) , a CU-control plane (CP) , a CU-user plane (UP) , or a radio unit (RU) etc. The CU and the DU may be separately deployed, or may be included in a same element (i.e., a baseband unit (BBU) ) . The RU may be included in a radio frequency device or a radio frequency unit (i.e., a remote radio unit (RRU) , an active antenna unit (AAU) , or a remote radio head (RRH) ) . In different systems, the CU (or the CU-CP and the CU-UP) , the DU, or the RU may also have different names, but a person skilled in the art may understand meanings thereof. For example, in an open radio access network (ORAN) system, a CU may also be referred to as an open CU (O-CU) , a DU may also be referred to as an open DU (O-DU) , and a CU-CP may also be referred to as an open CU-CP (O-CU-CP) . The CU-UP may also be referred to as an open CU-UP (O-CU-UP) , and the RU may also be referred to as an open RU (O-RU) . Any one of the CU (or the CU-CP, the CU-UP) , the DU, and the RU may be implemented by using a software module, a hardware module, or a combination of a software module and a hardware module.
[0087] Further, communication (s) between different devices / apparatuses in various embodiments of this application may refer to direct communication between different devices / apparatuses (that is, no forwarding is required by another device / apparatuses) , or may refer to communication (s) between different devices / apparatuses via another device / apparatus (that is, forwarding is required by another device / apparatus) . Alternatively, such communication (s) may refer to that a functional unit inside the device / apparatus uses another functional unit in the device / apparatus to communicate with another device / apparatus. In other words, "sending (or transmitting) information to... (an ED or a base station) " in this application may be understood as that a destination endpoint of the information is an ED or a base station. It may include sending / transmitting information directly or indirectly to an ED or a base station. Similarly, "receiving information from... (an ED or a base station) " may be understood as that a source endpoint of the information is an ED or a base station, and may include directly or indirectly receiving information from an ED or a base station. Necessary processing such as format conversion, digital-to-analog conversion, amplification, and filtering may be performed on the information between the source endpoint that sends the information and the destination endpoint. However, the destination endpoint may understand valid information from the source endpoint. Similar descriptions in this application may be understood similarly. Details are not described herein again. In the present disclosure, the terms "send" and "transmit" may be used interchangeably in embodiments of this application.
[0088] The ED 110 is used to connect persons, objects, machines, etc. The ED 110 may be widely used in various scenarios including, for example, cellular communications, device-to-device (D2D) , vehicle to everything (V2X) , peer-to-peer (P2P) , machine-to-machine (M2M) , MTC, internet of things (IoT) , virtual reality (VR) , augmented reality (AR) , mixed reality (MR) , metaverse, digital twin, industrial control, self-driving, remote medical, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city, drones, robots, remote sensing, passive sensing, positioning, navigation and tracking, autonomous delivery and mobility, etc.
[0089] Each ED 110 represents any suitable end user device for wireless operation and may include such devices (or may be referred to but not limited to) as a user equipment (UE) or a user device or a terminal device, a wireless transmit / receive unit (WTRU) , a mobile station, a fixed or mobile subscriber unit, a cellular telephone, a station (STA) , a MTC device, a personal digital assistant (PDA) , a smartphone, a laptop, a computer, a tablet, a wireless sensor, a consumer electronics device, a smart book, a vehicle, a car, a truck, a bus, a train, or an IoT device, wearable devices (such as a watch, a pair of glasses, head mounted equipment, etc. ) , an industrial device, or an apparatus (such as module, modem, or chip) in the forgoing devices, among other possibilities. Future generation EDs 110 may be referred to using other terms. When an ED 110 performs (or is configured to perform) a method described herein, it may be interpreted as the ED, one or more module (or units) in the ED, a circuit or chip, or a combination thereof, may perform the method. For example, the circuit or chip may include a modem chip, also referred to as a baseband chip, a system on chip (SoC) including a modem core, or system in package (SIP) ) , and the like, and may be responsible for one or more communication functions in the ED.
[0090] Each ED 110 connected to TRPs 170a-170b, and / or TRPs 172 can be dynamically or semi-statically turned-on (i.e., established, activated, or enabled) , turned-off (i.e., released, deactivated, or disabled) and / or configured in response to one of more of: connection availability and connection necessity.
[0091] Any ED 110 may be alternatively or additionally configured to interface, access, or communicate with any TRPs 170a, 170b and 172, the Internet 150, the CN 130, the PSTN 140, the other networks 160, or any combination of the preceding. In some examples, ED 110a may communicate an uplink (UL) and / or downlink (DL) transmission over a terrestrial air interface 190a with station-TRP 170a. In some examples, the EDs 110a, 110b, 110c, and 110d may also communicate directly with one another via one or more sidelink (SL) air interfaces 190b. In some examples, ED 110a, 110d may communicate an UL and / or DL transmission over a non-terrestrial air interface 190c with NT-TRP 172.
[0092] An air interface (such as 190a, 190b, 190c) generally includes a number of components and associated parameters that collectively specify how a transmission is to be sent and / or received over a wireless communications link between two or more communicating devices such as ED and base station. For example, an air interface may include one or more components defining the waveform (s) , frame structure (s) , multiple access scheme (s) , protocol (s) , coding scheme (s) and / or modulation scheme (s) for conveying information (such as, data) over a wireless communications link. The air interfaces 190a and 190b may use similar communication technology, such as any suitable radio access technology.
[0093] The non-terrestrial air interface 190c can enable communication between the EDs 110a, 110d and one or multiple NT-TRPs 172 via a wireless link or simply a link. For some examples, the link is a dedicated connection for unicast transmission, a connection for broadcast transmission, or a connection between a group of EDs 110 and one or multiple NT-TRPs 172 for multicast transmission.
[0094] The TRPs 170a-170b, 172 may communicate with one another over one or more air interfaces 190e, 190f using wireless communication links (such as radio frequency (RF) , microwave, infrared (IR) , etc. ) or wired communication links. The air interfaces 190e, 190f may utilize any suitable radio access technology, and may be substantially similar to the air interfaces 190a, 190c over which the EDs 110a-110d communicate with one or more of the TRP 170a-170b, 172 or they may be substantially different. For example, the communication system 100 may implement one or more channel access methods, such as code division multiple access (CDMA) , time division multiple access (TDMA) , frequency division multiple access (FDMA) , orthogonal FDMA (OFDMA) , or single-carrier FDMA (SC-FDMA) .
[0095] The RANs 120a and 120b are in communication with the CN 130 to provide the EDs 110a 110b, and 110c with various services such as voice, data, and other services. The RANs 120a and 120b and / or the CN 130 may be in direct or indirect communication with one or more other RANs (not shown) , which may or may not be directly served by CN 130, and may or may not employ the same radio access technology as RAN 120a, RAN 120b or both. The CN 130 may also serve as a gateway access between (i) the RANs 120a and 120b or EDs 110a 110b, and 110c or both, and (ii) other networks (such as the PSTN 140, the Internet 150, and the other networks 160) . In addition, some or all of the EDs 110a 110b, and 110c may include functionality for communicating with different wireless networks over different wireless links using different wireless technologies and / or protocols. Instead of wireless communication (or in addition thereto) , the EDs 110a 110b, and 110c may communicate via wired communication channels to a service provider or switch (not shown) , and to the Internet 150. PSTN 140 may include circuit switched telephone networks for providing plain old telephone service (POTS) . Internet 150 may include a network of computers and subnets (intranets) or both, and incorporate protocols, such as internet protocol (IP) , transmission control protocol (TCP) , user datagram protocol (UDP) . EDs 110a 110b, and 110c may be multimode devices capable of operation according to multiple radio access technologies, and incorporate multiple transceivers necessary to support such.
[0096] In addition, the communication system 100 may comprise a sensing agent (not shown) to manage the sensed data from ED 110 and / or any one of TRPs 170 a-170b, 172. In one implementation, the sensing agent may be part of any one of TRPs 170 a-b, 172. In another implementation, the sensing agent is a separate node that can communicate with the CN 130 and / or the RAN 120 (such as any one of TRPs 170 a-b, 172) .
[0097] FIG. 3 illustrates an example of an apparatus 310 wirelessly communicating with another apparatus 320 in a communication system (such as the communication system 100) . The apparatus 310 may be an electronic device (such as ED 110) . The apparatus 320 may be a network node (such as network node 170) such as T-TRP 170 or an NT-TRP 172. Although there is only one apparatus 310, and one apparatus 320 shown in the figure, the number of apparatus 310 and / or 320 could be one or more. For example, one ED 110 may be served by only one T-TRP 170 (or one NT-TRP 172) , by more than one T-TRP 170 (or more than one NT-TRP 172) . One ED 110 may be served by one or more T-TRP 170 and one or more NT-TRP172. Similarly, one T-TRP 170 (or one NT-TRP172) may serve one or more ED 110.
[0098] Apparatus 310 includes at least one processor 210. Only one processor 210 is illustrated to avoid congestion in the drawing. The apparatus 310 may further include a transmitter 201 and a receiver 203 coupled to one or more antennas 204. Only one antenna 204 is illustrated to avoid congestion in the drawing. One, some, or all of the antennas 204 may alternatively be panels. The transmitter 201 and the receiver 203 may be integrated, such as a transceiver. The transceiver is configured to modulate data or other content for transmission by at least one antenna 204 or network interface controller (NIC) . The transceiver is also configured to demodulate data or other content received by the at least one antenna 204. Each transceiver includes any suitable structure for generating signals for wireless or wired transmission and / or processing signals received wirelessly or by wire. Each antenna 204 includes any suitable structure for transmitting and / or receiving wireless or wired signals. The apparatus 310 may include at least one memory 208. Only the transmitter 201, receiver 203, processor 210, memory 208, and antenna 204 is illustrated for simplicity, but the apparatus 310 may include one or more other components. In present disclosure, the transceiver (or transmitter 201 and / or receiver 203) may be viewed as an interface circuit.
[0099] The memory 208 stores instructions used to perform operations described herein. The memory 208 may also store data used, generated, or collected by the apparatus 310. For example, the memory 208 could store software instructions or modules configured to implement some or all of the functionality and / or embodiments described herein and that are executed by one or more processor 210.
[0100] The apparatus 310 may further include one or more input / output devices (not shown) or interfaces. The input / output devices or interfaces permit interaction with a user or other devices in the network. Each input / output device or interface includes any suitable structure for providing information to or receiving information from a user, and / or for network interface communications. Suitable structures include, for example, a speaker, microphone, keypad, keyboard, display, touch screen, etc.
[0101] The processor 210 may perform (or control the apparatus 310 to perform) operations (or methods) described herein as being performed by the apparatus 310. For example, the processor 210 performs or controls the apparatus 310 to perform receiving transport blocks (TBs) , using a resource for decoding of one of the received TBs, releasing the resource for decoding of another of the received TBs, and / or receiving configuration information configuring a resource. In detail, the operation may include those operations related to preparing a transmission for UL transmission to the apparatus 320; those operations related to processing DL transmissions received from the apparatus 320; and those operations related to processing SL transmission to and from another apparatus 310. Processing operations related to preparing a transmission for UL transmission may include operations such as encoding, modulating, transmit beamforming, and generating symbols for transmission. Processing operations related to processing DL transmissions may include operations such as receive beamforming, demodulating and decoding received symbols. Processing operations related to processing SL transmissions may include operations such as transmit / receive beamforming, modulating / demodulating and encoding / decoding symbols. Depending upon the embodiment, a DL transmission may be received by the receiver 203, possibly using receive beamforming, and the processor 210 may extract signaling from the DL transmission (such as by detecting and / or decoding the signaling) . An example of signaling may be a reference signal transmitted by the apparatus 320. In some implementations, the processor 210 implements the transmit beamforming and / or the receive beamforming based on the indication of beam direction, such as beam angle information (BAI) , received from the apparatus 320. In some implementations, the processor 210 may perform operations relating to network access (such as initial access) and / or downlink synchronization, such as operations relating to detecting a synchronization sequence, decoding and obtaining the system information, etc. In some implementations, the processor 210 may perform channel estimation, such as using a reference signal received from the apparatus 320.
[0102] Although not illustrated, the processor 210 may form part of the transmitter 201 and / or part of the receiver 203. Although not illustrated, the memory 208 may form part of the processor 210.
[0103] The processor 210, the processing components of the transmitter 201, and the processing components of the receiver 203 may each be implemented by the same or different one or more processors that are configured to execute instructions stored in a memory (such as in the memory 208) .
[0104] The apparatus 320 includes one or more processors 260 (only one processor 260 is illustrated to in the figure) . The apparatus 320 may further include at least one transmitter 252 and at least one receiver 254 coupled to one or more antennas 256. Only one antenna 256 is illustrated to avoid congestion in the drawing. One, some, or all of the antennas 256 may alternatively be panels. The transmitter 252 and the receiver 254 may be integrated as a transceiver. The apparatus 320 may further include at least one memory 258. The apparatus 320 may further include scheduler 253. Only the transmitter 252, receiver 254, processor 260, memory 258, antenna 256 and scheduler 253 are illustrated for simplicity, but the apparatus 320 may include one or more other components. In present disclosure, the transceiver (or transmitter 252 and / or receiver254) may be viewed as an interface circuit.
[0105] In some implementations, the parts of the apparatus 320 may be distributed. For example, some of the modules of the apparatus 320 may be located remote from the equipment that houses the antennas 256 for the apparatus 320 (thereby also can be viewed as one or more nodes) , and may be coupled to the equipment that houses the antennas 256 over a communication link (not shown) sometimes known as front haul, such as common public radio interface (CPRI) . Therefore, in some implementations, the term apparatus 320 may also refer to nodes on the network side that perform processing operations, such as determining the location of the apparatus 310, resource allocation (scheduling) , message generation, and encoding / decoding, and that are not necessarily part of the equipment that houses the antennas 256 of the apparatus 320. The nodes may also be coupled to other apparatus 320s. In some implementations, the apparatus 320 may actually be a plurality of nodes that are operating together to serve the apparatus 310, such as through the use of coordinated multipoint transmissions, or the use of ORAN system as described above in the application.
[0106] The processor 260 performs operations including those related to: preparing a transmission for DL transmission to the apparatus 310, processing an UL transmission received from the apparatus 310, preparing a transmission for backhaul transmission to another apparatus 320, and processing a transmission received over backhaul from another apparatus 320. Processing operations related to preparing a transmission for DL or backhaul transmission may include operations such as encoding, modulating, precoding (such as multiple input multiple output (MIMO) precoding) , transmit beamforming, and generating symbols for transmission. Processing operations related to processing received transmissions in the UL or over backhaul may include operations such as receive beamforming, demodulating received symbols, and decoding received symbols. The processor 260 may also perform operations relating to network access (such as initial access) and / or DL synchronization, such as generating the content of synchronization signal blocks (SSBs) , generating the system information, etc. In some implementations, the processor 260 also generates an indication of beam direction, such as BAI, which may be scheduled for transmission by a scheduler 253 which will be described below. In some implementations, the processor 260 implements the transmit beamforming and / or receive beamforming based on beam direction information (such as BAI) received from another apparatus 320. The processor 260 performs other network side processing operations described herein, such as determining the location of the apparatus 310, determining where to deploy another apparatus 320, etc. In some implementations, the processor 260 may generate signaling, such as to configure one or more parameters of the apparatus 310 and / or one or more parameters of another apparatus 320. Any signaling generated by the processor 260 is sent by the transmitter 252. In some implementations, the apparatus 320 implements physical layer processing. In some implementations, the apparatus 320 may implement higher layer functions such as functions at the medium access control (MAC) or radio link control (RLC) layer in addition to physical layer processing. The apparatus 320 may further comprise scheduler 253 coupled to the processor 260 or integrated in the processor 260. The scheduler 253 may be included within or operated separately from the apparatus 320a. The scheduler 253 may schedule UL, DL, SL, and / or backhaul transmissions, including issuing scheduling grants and / or configuring scheduling-free (such as “configured grant” ) resources.
[0107] The apparatus 320 may further include a memory 258 storing instructions used to perform operations described herein. The memory 258 may also store data used, generated, or collected by the apparatus 320. For example, the memory 258 could store software instructions or modules configured to implement some or all of the functionality and / or embodiments described herein and that are executed by the processor 260.
[0108] Although not illustrated, the processor 260 may form part of the transmitter 252 and / or part of the receiver 254. Also, although not illustrated, the processor 260 may implement the scheduler 253. Although not illustrated, the memory 258 may form part of the processor 260.
[0109] The processor 260, the scheduler 253, the processing components of the transmitter 252, and the processing components of the receiver 254 may each be implemented by the same or different one or more processors that are configured to execute instructions stored in a memory, such as in the memory 258.
[0110] The apparatus 320 and / or the apparatus 310 may include other components, but these have been omitted for the sake of clarity.
[0111] Note that “signaling” , as used herein, may alternatively be called control signaling, control message, control information, or message for simplicity. Signaling between a base station (such as the TRP 170a-b, 172) and a UE or sensing device (such as ED 110) , or signaling between a different UE or sensing device (such as between ED 110a and ED 110b) may be carried in physical layer signaling (also called as dynamic signaling) , which is transmitted in a physical layer control channel. For DL, the physical layer signaling may be known as downlink control information (DCI) which is transmitted in a physical downlink control channel (PDCCH) . For UL, the physical layer signaling may be known as uplink control information (UCI) which is transmitted in a physical uplink control channel (PUCCH) . For SL, signaling between different UEs or sensing devices (such as between ED 110a and ED 110b) may be known as SL control information (SCI) which is transmitted in a physical sidelink control channel (PSCCH) . Signaling may be carried in a higher layer (such as higher than physical layer) signaling, which is transmitted in a physical layer data channel, such as in a physical downlink shared channel (PDSCH) for downlink signaling, in a physical uplink shared channel (PUSCH) for uplink signaling, and in a physical sidelink shared channel (PSSCH) for SL signaling. Higher layer signaling may also be called static signaling, or semi-static signaling. Higher layer signaling may be radio resource control (RRC) protocol signaling or media access control -control element (MAC-CE) signaling. Signaling may be included in a combination of physical layer signaling and higher layer signaling.
[0112] It should be noted that in present application, “information” , when different from “message” , may be carried in one single message, or be carried in more than one separate message.
[0113] FIG. 4 illustrates an example of an apparatus 410. The apparatus 410 may be a communication device or an apparatus implemented in a communication device such as ED 110 or TRPs 170a-170b, 172. For example, the apparatus implemented in a communication device may be an integrated circuit, which in some contexts may be known by other colloquial names, such as chip, modem, modem chip, baseband chip, or baseband processor. In some implementations, one or more integrated circuits can be packaged into a system-on-chip, a system-in-package, or a multi-chip module. The apparatus may comprise one or more integrated circuits or comprise one or more integrated circuits and other discrete components. In some implementations, the apparatus 410 may be a module in ED 110, or apparatus 310. In some implementations, the apparatus 410 may be a module in one of TRPs 170a-170b, 172, or apparatus 320.
[0114] In an example, the apparatus 410 may include one or more processors / processor cores 411, and an interface circuit 412. The apparatus 410 may further include a memory 413. The one or more processors / processor cores 411 are configured to process signals and execute one or more communication protocols. The memory 413 is configured to store at least a part of corresponding computer program instructions and / or data. In an example, the one or more processors (or processor cores) 411 execute the computer program instructions stored in the memory 413 to implement related operations (for example, inputting, outputting, receiving, and transmitting) in the method embodiments disclosed herein. In some implementations, the memory 413 being configured to store the corresponding computer program instructions and / or data may mean that the memory 413 is configured to store all of the corresponding computer program instructions and / or data for execution by the one or more processors / processor cores 411. In some implementations, the memory 413 being configured to store the corresponding computer program instructions and / or data may mean that the memory 413 is configured to store a part of the corresponding computer program instructions and / or data. For example, the part of the corresponding computer program instructions and / or data may include computer program instructions and / or data that need to be currently executed by the one or more processors / processor cores 411. Thus, the memory 413 may store different parts of computer program instructions and / or data for a plurality times for the one or more processors (or processor cores) 411 to perform related operations in the method embodiments disclosed herein. As a communication interface, the interface circuit 412 is configured to implement communication with another component. For example, the interface circuit 412 may communicate a signal with other apparatus / system such as a radio frequency processing apparatus, or processor system. Optionally, to reduce a load of the one or more processors (or processor cores) , a baseband signal processing circuit 414 may be also disposed to implement processing of at least a part of baseband signals, including signal demodulation, modulation, encoding, decoding, or the like.
[0115] Apparatus 410 may be processor 210 (or 260) in apparatus 310 (or 320) , in some scenarios, or included in processor 210 (or 260) in apparatus 310 (or 320) in some scenarios. Apparatus 410 may be or include a baseband chip. In some implementations, the apparatus 410 may be independently packaged into a chip. In some implementations, the apparatus 310 (or 320) includes different types of chips. The apparatus 410 may be packaged into a processor chip (for example, an SoC chip or an SIP chip) with the different types of chips. In some implementations, the apparatus 410 may be packaged into a chip with some or all of circuits of a radio frequency processing system that may further included in the apparatus 310 (or 320) .
[0116] FIG. 5 illustrates example of apparatus 510. Apparatus 510 may include corresponding modules or units configured to implement methods and / or embodiments described herein. In some implementations, the apparatus 510 includes a processing unit 512 and a communication unit 513. Optionally, the apparatus 510 may further include a storage unit 511 configured to store apparatus program code (or instructions) and / or data.
[0117] The apparatus 510 may be an ED side apparatus, for example, an ED or a module in an ED, or a circuit or a chip responsible for a communication function in an ED. In some implementations, apparatus 510 may be the apparatus 310. The processing unit 512 is the processor 210. The communication unit 513 may comprise a receiving unit and / or a transmitting unit. The receiving unit and / or the transmitting unit may be the transmitter 201 and / or receiver 203 respectively. The storage unit 511 may be the memory 208.
[0118] The apparatus 510 may be a base station side apparatus, for example, a base station or a module in a base station, or a circuit or a chip responsible for a communication function in a base station. In some implementations, apparatus 510 may be apparatus 320. The processing unit 512 may be processor 260 (the scheduler 253 may also be included) . The communication unit 513 may comprise a receiving unit and / or a transmitting unit. The receiving unit and / or the transmitting unit may be transmitter 252 and / or receiver 254 respectively. The storage unit 511 may be memory 258.
[0119] In some implementations, when the apparatus 510 is an ED 110 or a module in an ED 110, a function of the apparatus 510 may be implemented by one or more processors. Specifically, the processor may include a modem chip, or a system on chip SoC chip or an SIP chip that includes a modem core. A function of the communication unit 513 may be implemented by a transceiver circuit.
[0120] In some implementations, when the apparatus 510 is a circuit or a chip that is responsible for a communication function in an ED 110, for example, a modem chip, a system on chip SoC chip or an SIP chip that includes a modem core, a function of the processing unit 512 may be implemented by a circuit system that is in the chip and that includes one or more processors or processor cores. A function of the communication unit 513 may be implemented by an interface circuit or a data transceiver circuit on the foregoing chip.
[0121] It may be understood that the units in the apparatus 510 may be logical or functional. Each function may correspond to one functional unit, or two or more functions may be integrated into one functional unit. In actual implementation, all or some of the units may be integrated into one physical entity, or may be distributed in different physical entities. In addition, the foregoing functional units may be implemented in a form of hardware, may be implemented in a form of software, or may be implemented in a form of a combination of hardware and software. Whether a function is performed in a form of hardware or software depends on particular applications and design constraint conditions of the technical solutions. A person skilled in the art may use different methods to implement the described functions for each particular application, but it should not be considered that the implementation goes beyond the scope of this application.
[0122] In an example, a functional unit in any one of the foregoing apparatuses may be configured as one or more integrated circuits for implementing the methods disclosed herein, for example, one or more application-specific integrated circuits (application-specific integrated circuits, ASICs) , one or more central processing units (central processing units, CPUs) , one or more microprocessors (microcontroller units, MCUs) , one or more digital signal processors (digital signal processors, DSP) , one or more field programmable gate arrays (field programmable gate arrays, FPGAs) , or a combination of at least two of these integrated circuit forms.
[0123] In an example, the storage unit 511 may include a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, and / or a register.
[0124] A processor, a processor system, a application processor, a baseband processor, a processor circuit, or a processor core may be collectively referred to as a processor. The processor may include one or a combination of a central processing unit (CPU) , a digital signal processor (DSP) , a microprocessor (microprocessor unit, MPU) , a microcontroller (microcontroller unit, MCU) , a graphics processing unit (GPU) , a field programmable gate array (FPGA) , an artificial intelligence processor (AI processor) , or a neural network processing unit (NPU) .
[0125] Memory or a storage unit may include one or more of the following storage media: a random access memory (RAM) , a static random access memory (static RAM, SRAM) , a dynamic random access memory (dynamic RAM, DRAM) , a phase-change memory (PCM) , a resistive random access memory (resistive RAM, ReRAM) , a magnetoresistive random access memory (magnetoresistive RAM, MRAM) , a ferroelectric random access memory (ferroelectric RAM, FRAM) , a cache, a register, a read-only memory (ROM) , a flash memory (flash memory) , an erasable programmable read-only memory (erasable programmable ROM, EPROM) , a hard disk, and the like. In an example, computer program instructions used to execute embodiments may be stored in a non-volatile memory, for example, at least a part of a memory or storage unit (for example, one or more of a ROM, a flash memory, an EPROM, or a hard disk) . When a terminal runs, a part or all of corresponding computer program instructions may be loaded to a memory that has a higher transmission speed with the processor, for example, at least a part of a memory or a storage unit (for example, one or more of a RAM, an SRAM, a DRAM, a PCM, a RERAM, an MRAM, a FRAM, a cache, or a register) , so that the processor executes the computer program instructions to perform the steps in the method embodiments disclosed herein.
[0126] Before introducing the communications method provided by this application, additional concepts and terms are introduced for better understanding.
[0127] A digital twin (DT) is used to generate a digital counterpart (or replica) of real physical world, which simulates physical assets in the virtual world. A DT may be referred to as a digital model of an intended or actual real-world physical product, system, or process (aphysical twin) that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance. The digital twin can exist before the physical entity, as for example with virtual prototyping.
[0128] A digital model may be trained based on collected dataset, where the trained model can be later used. This training process can be referred to as an offline training. However, the digital model obtained from an offline training may not be applied to the dynamic changes of the real word.
[0129] Therefore, this application provides a model generation method that can be applied to the dynamic changes of the real world. The model generation method may involve multiple nodes. Before introducing the model generation method provided by this application, the possible involved nodes are illustrated in FIG. 6.
[0130] FIG. 6 illustrates a schematic diagram of devices (nodes) involved in the model generation.
[0131] Referring to FIG. 6, as an illustrative example, a model generation system may include cloud and a controller. The cloud may be referred to as a server (e.g., centralized servers) , along with the software and databases that run on the server. The controller may be referred to as a location server that located in the RAN (e.g., RAN 120 in FIG. 1) or CN (e.g., CN 130 in FIG. 1) . Optionally, the model generation system may further include one or more nodes, where the one or more nodes may have a capability of sending and / or measuring signals. The one or more nodes may be (or located in) one or more EDs (e.g., the ED 110 in FIG. 1) , one or more TRPs (e.g., network nodes 170 in FIG. 1) , or other devices, or a combination thereof. This is not limited to this application. Notably, in some instances, the controller itself may have a capability of sensing and / or measuring signals.
[0132] Notably, the above presents a simplified description of some related technologies to provide a basic understanding. The various concepts presented throughout this disclosure may be implemented across a broad variety of telecommunication systems, network architectures and communication standards. The actual telecommunication standard, network architecture, and / or communication standard used will depend on the specific application and the overall design constraints imposed on the system.
[0133] A communication system enables wired or wireless communications between devices. In some implementations, a device may be known by an apparatus, a node, an entity, a module, etc. The disclosure is described with devices as examples. The communication system may include at least a first device and a second device. In some implementations, the first device may correspond to the controller in FIG. 6. In some implementations, the second device may correspond to the cloud in FIG. 6. In some implementations, the communication system may further include at least one third device, where a third device may correspond to a node in FIG. 6.
[0134] This application provides a method that a first device can obtain a first model from a second device, and generate a second model based on the first model and real-time data. The second model is used to generate a digital counterpart of a physical world. The second model can have better performance due to the real-time data. This method is described in detail in conjunction with FIGs. 7-9.
[0135] FIG. 7 is a schematic flowchart of a communication method according to an embodiment of this application.
[0136] At step 710, a second device transmits first information to a first device. Correspondingly, the first device receives the first information from the second device.
[0137] The first information indicates a first model. The first model may be implemented in the second device (e.g., the cloud) . The first device receives the first information, so that the first device may download the first model.
[0138] In some implementations, the first model is a model trained by the second device in advance. That is, as described earlier, the first model may be an offline trained model. The first model may be known by a general model, or other names in some implementations, such as a large model, a world model, a reference model. In some implementations, the term “first model” and the term “general model” are used interchangeably herein.
[0139] In some implementations, the first model could represent general characteristics of a physical world (referred to as a general physical world hereinafter) . For example, the first model could learn complex patterns and relationships within a general physical world. There are at least three levels of describing the general physical world.
[0140] For example, the first level is to describe the physical environment objects in a general physical world. In some instances, the physical environment objects may include one or more of: buildings, terrains, vegetations, vehicles in the street, etc.
[0141] For example, the second level is to describe radio signal propagation characteristics in a general physical world. In some instances, the radio signal propagation characteristics may include one or more of: signal reflection, diffraction, diffusion, etc.
[0142] For example, the third level is to describe a wireless communication network deployed in a general physical world. In some instances, the wireless communication network may include one or more of: communication in a physical layer, communication in a higher layer (e.g., MAC layer, RRC layer) .
[0143] Notably, the general physical world may be a virtual world that captures general characteristics of a real physical world, or a historical state of a real physical world, where this depends on the data the first model was trained on.
[0144] The first model may be offline trained on amounts of data. For ease of description, these amounts of data are referred to as general data. The general data can be obtained in a variety of ways. In some implementations, the general data may include one or more of: data stored in a database, historical measurement data from one or more measurement nodes, historical sensing data from one or more sensing nodes, and historical data obtained from the integrated sensing and communication (ISAC) system, and data from other devices (e.g., light laser detection and ranging (LiDAR) , camera, a sensor, etc. ) . This is not limited to this application.
[0145] The first information may indicate the first model in a variety of ways. For example, the first information may indicate the first model explicitly or implicitly. The first information may include parameters related to the first model. In some instances, the first information may indicate part or all of parameters of the first model structure (model parameters) . Notably, the first information may indicate part of parameters of the model parameters where other parameters may be known by the first device. In some instances, the first information may indicate the address of the first model, so that the first device could obtain the first model based on the address. This is not limited to this application.
[0146] At step 720, the first device generates a second model based on the first model and real-time data.
[0147] The second model is used to generate a digital counterpart of a physical world (referred to as a local physical world hereinafter) . The second model may also be known by a local model or other names. In some implementations, the term “second model” and “local model” are used interchangeably herein.
[0148] Notably, the local physical world may refer to as a real physical world of an area in which the first device is located (managed, served) .
[0149] In some implementations, the second model is a model trained by the first device (e.g., local RAN or CN) in (near) real-time. For example, the second model, utilizing the general model and real-time data related to the local physical world, may make inference to generate various DTs of the local physical world in real-time. In other words, the second model may be referred to as an online model that being used for inference is typically continuously trained in real-time with the arrival of new training samples (the real-time data) .
[0150] The digital counterpart generated by the second model may represent local characteristics of the local physical world. In some implementations, the second model may generate three types (levels) of digital counterpart: the digital counterpart for physical environment objects, the digital counterpart for radio signal propagation characteristics and the deployed wireless communication network.
[0151] The type of the real-time data may be related to the type of the digital counterpart. In some implementations, the real-time data includes one or more of: data that indicates the physical environment objects in the physical world (referred to as data#1 hereinafter) , data that indicates radio signal propagation characteristics in the physical world (referred to as data#2 hereinafter) , and data that indicates parameters associated with a wireless communication network deployed in the physical world (referred to as data#3 hereinafter) .
[0152] For example, the data#1 may map (describe) position, shape or other geographical features of the physical environment objects. In some instances, the object data may further describe the material of the physical environment objects.
[0153] For example, the data#2 may describe the reflection, diffraction, diffusion, etc. experienced by a signal as it propagates through the real physical world. In some instances, the propagation data may describe channel information (e.g., path loss, time delay, etc. ) in the real physical world.
[0154] For example, the data#3 may include various of configuration parameters in wireless communication network. In some instances, for the physical layer, the data#3 may aim to optimize component design and / or improve the algorithm performance. For the MAC layer, the data#3 may aim to utilize learn, predict, and / or make a decision to solve a complicated optimization problem with possible better strategy and / or optimal solution, e.g. to optimize the functionality in the MAC layer, e.g. intelligent TRP management, intelligent beam management, intelligent channel resource allocation, intelligent power control, intelligent spectrum utilization, intelligent modulation and coding scheme (MCS) , intelligent hybrid automatic repeat request (HARQ) strategy, intelligent transmit / receive (Tx / Rx) mode adaption, etc.
[0155] The real-time data described above is exemplary only. This will depend on the specific application of the digital counterpart.
[0156] The real-time data can be obtained in a variety of ways. In some implementations, the real-time data is obtained from one or more of: measuring the physical world, sensing the physical world and a third model.
[0157] For example, the real-time data may be obtained from measuring the local physical world by one or more third devices (e.g., measuring nodes) . In this case, the real-time data may be referred to as measurement data, which may be the measurement result for the radio propagation characteristics and transmission parameters associated with the wireless communication network. In some instances, one or more measuring nodes (e.g., ED, TRP, etc. ) may receive (measure) signals (e.g., reference signals) to obtain the measurement result. The measurement result may include the real-time data as described earlier.
[0158] For example, the real-time data may be obtained from sensing the local physical world by one or more third devices (e.g., sensing nodes) . In this case, the real-time data may be referred to as sensing data, which may be the sensing result for physical environment objects in the local physical world. In some instances, one or more sensing nodes (e.g., ED, TRP, camera, sensor, LiDAR, etc. ) may perform sensing tasks to obtain the sensing result. The sensing result may include the real-time data as described earlier.
[0159] For example, the real-time data may be obtained from one or more third models deployed in one or more third devices (e.g., modeling nodes) . In this case, the real-time data may be referred to as modeling data, which may be a modeling result for the radio propagation characteristics and transmission parameters associated with the wireless communication network. In some instances, one or more nodes (e.g., ED, TRP, CN, etc. ) may train a small model to obtain the model result. For example, a third device may be deployed with a local general model (i.e., the third model) . The third device may obtain real-time local measuring result and / or sensing result. The real-time local measuring result and / or the sensing result may be as input of the third model, and the output of the third model may be as the real-time data to generate the second model. Notably, the third device may continuously infer the local third model to obtain real-time data.
[0160] Notably, the exemplary measuring node, sensing node and modeling node may be the same node or different nodes. For example, an ED may have the capabilities of both the measuring, sensing and modeling. For another example, an ED may be responsible for measuring and sensing, and a TRP may be responsible for modeling. This is not limited to this application.
[0161] The first device generates the second model in a variety of ways.
[0162] In a first implementation, the first device may collect the real-time data from other device (s) (e.g., one or more third devices) , then generate the second model based on the first model and the collected real-time data. A detailed example is illustrated in conjunction with FIG. 8.
[0163] For example, FIG. 8 illustrates a first implementation to generate the first model according to this application.
[0164] At step 721A, the first device transmits fourth information to one or more third devices. Correspondingly, the one or more third devices receive the fourth information from the first device.
[0165] The fourth information may request the real-time data. For example, the first device (e.g., a local controller) , located in a local RAN and / or CN, may configure its associated infrastructure third devices (e.g., BSs and / or EDs) to execute various sensing and / or measuring tasks on local real physical world, and report the real-time data (sending and / or measuring data) according to the requirement of the local controller.
[0166] In some implementations, the fourth information may indicate one or more of: a configuration for obtaining the real-time data, a configuration for reporting the real-time data, and at least one identifier of at least one third device that obtains the real-time data.
[0167] The fourth information may include various parameters related to the configuration for obtaining the real-time data. The configuration for obtaining the real-time data may indicate one or more of: a type of the real-time data (e.g., sensing result, measuring result and / or model result) , and at least one parameter that describes one or more tasks used for generating the real-time data. In some instances, the fourth information may include parameter (s) that describes one or more tasks, where the one or more third devices may execute the one or more tasks to obtain real-time data. For example, the fourth information may include one or more of: task description of environment object sensing task, task description of channel information measurement task, task description of wireless transmission parameter measurement task, and task description of model inference task.
[0168] In some instances, the fourth information may include frequency parameter (s) that used for obtaining the real-time data. For example, the fourth information may include parameters indicate operation frequency bands and / or bandwidth, so that the third devices could obtain the real-time data based on the indicated bands.
[0169] In some instances, the fourth information may include parameter (s) related to reference signal (RS) configuration. For example, the parameter (s) may include one or more of RS type, RS port, quasi-colocation (QCL) relation and etc. The one or more third devices may measure the RS to obtain the measurement result (real-time data) based on the BS configuration.
[0170] In some instances, the fourth information may include parameter (s) related to sensing waveform configuration. For example, the parameter (s) may include one or more of OFDM, DFT-s-OFDM, FWCW, and etc. The one or more third devices may sense the physical world to obtain sensing result based on the sensing waveform configuration.
[0171] In some instances, the fourth information may include parameter (s) related to model inference configuration. For example, the parameter (s) may include one or more of: a type of the third model, at least one parameter related to input of the third model, at least one parameter related to output settings of the third model, and etc.
[0172] In some instances, the fourth information may indicate the type of the real-time data. For example, the fourth information may indicate that the real-time data include one or more of sensing result, measurement result and model result, so that the one or more third devices could obtain indicates type of the real-time data.
[0173] The fourth information may include various parameters related to the configuration for reporting the real-time data. The configuration for reporting the real-time data may indicate one or more of: at least one parameter of the real-time data to be reported, and a physical resource used for reporting the real-time data. In some instances, the fourth information may include parameter (s) that indicates report quantity. For example, the report quantity for environment objects may include one or more of the original scatter points corresponding to the environment objects, the reconstructed environment object images, indication of whether to compress or not, and etc. For example, the report quantity for radio signal propagation characteristics may indicate one or more of: power, delay, angle of arrival (AoA) , angle of departure (AoD) , direction of arrival (DoA) , (direction of departure) DoD, wireless channel response in frequency domain, etc. For example, the report quantity for wireless transmission parameters may indicate one or more of power, MCS, rank, MIMO precoding vectors, beam, and etc.
[0174] In some instances, the fourth information may indicate the scheduling configuration for reporting the real-time data. For example, the fourth information may indicate the frequency resources used for reporting the real-time data; or indicate the real-time can be reported aperiodically, semi-persistently or periodically; or a combination thereof. The one or more third devices can transmit the real-time data based on the scheduling configuration.
[0175] The fourth information may include parameter (s) related to the one or more third devices. In some instances, the fourth information may indicate identifies (IDs) of the one or more third devices that obtain the real-time data.
[0176] Notably, the first device may transmit the fourth information in a variety of ways. For example, the first device may broadcast the fourth information or multi-cast the fourth information to a group of third devices. For another example, the first device may transmit multiple fourth information to multiple third devices respectively, and each fourth information may request corresponding real-time data. The parameter (s) carried in each fourth information may be the same, or different, or partially the same, this depends on the specific application scenario. For another example, when the first device transmits multiple fourth information to multiple third devices respectively, the fourth information in step 721A may indicate the combination of the multiple fourth information.
[0177] At step 722A, the one or more third devices obtain the real-time data based on the fourth information.
[0178] The one or more third devices may obtain the sensing result, measuring result, and / or model result based on the fourth information.
[0179] At step 723A, the one or more third devices transmit information related to the real-time data to the first device. Correspondingly, the first device receives the information related to the real-time data from the one or more third devices.
[0180] The one or more third devices may report their respectively obtained information related to real-time data to the first device. For example, third devices #1 obtains real-time data #1, and reports information #1 related to the real-time data #1, third devices #2 obtains and real-time data #2, and reports information #2 related to the real-time data #2. Then from the first device side, the information related to the real-time data may indicate a combination of the information #1 related to real-time data #1 and information #2 related to real-time data #2.
[0181] At step 724A, the first device generates the second model based on the first model and the real-time data.
[0182] The first device may generate the second model in a variety of ways. In some implementations, the first device may generate the second model by performing the one or more of: model fine-tuning, model alignment and model inference. The model fine-tuning process is to improve the accuracy of the model by initialing its model parameters with a pre-trained model (i.e., the first model) on big data (i.e., real-time data) . The model alignment process is to encode values and goals into the model to make it as helpful, safe and reliable as possible. The model inference process is to run the real-time data into the model to calculate an output. Notably, this application does not exclude other possible model processes.
[0183] With the collected online real-time data related to the local physical world and first model, the second model can be generated in a centralizes way.
[0184] In a second implementation, the first device may decompose the first model into one or more first sub-models, distribute the one or more first sub-models to multiple third devices respectively. Each third device may process the first sub-model based on its local real-time data. Then the first device may collect one or more processed first sub-models (referred to as second sub-models) and generate the second model based on the multiple second sub-models. A detailed example is illustrated in conjunction with FIG. 9.
[0185] For example, FIG. 9 illustrates a second implementation to generate the first model according to this application.
[0186] At step 721B, the first device transmits fifth information to one or more third devices. Correspondingly, the one or more third devices receive the fifth information from the first device.
[0187] The fifth information may indicate one or more first sub-models. The fifth information may indicate various parameters related to the one or more first sub-models. In some instances, the fifth information may include one or more sets of sub-model parameters, and each set of sub-model parameters may correspond a sub-model. In some instances, the fifth information may indicate functionality ID and / or model ID of the general model. In some instances, the fifth information may indicate functionality ID and / or model ID of the one or more first sub-modes. This is not limited to this application.
[0188] For example, when the first device (e.g., the local controller) downloads the general model from the second device (e.g., the cloud) , the first device may split the general model into one or more first sub-models. Then the one or more third devices may obtain the one or more first sub-models respectively.
[0189] Notably, the first device can split the general model in a variety of ways. In some implementations, the first model could determine the one or more third devices who participate in generating the second model first, and then split the general model based on the determined third devices. In some implementations, the first model could split the general model into one or more first sub-models first, and then determine the one or more third devices based on the split first sub-models. This is not limited to this application.
[0190] The fifth information may further indicate one or more of: a configuration for obtaining the real-time data, a configuration for generating the one or more second sub-models, a configuration for reporting the one or more second sub-models, and one or more identifiers of one or more devices that generate the one or more second sub-models.
[0191] The fifth information may include various parameters related to the configuration for obtaining the real-time data. The parameters related to the configuration for obtaining the real-time data can refer to the description for the fourth information. The details are omitted for brevity.
[0192] The fifth information may include various parameters related to the configuration for generating the one or more second sub-models. In some instances, the fifth information may indicate the level at which the one or more second sub-models represent the characteristics of a physical world, e.g., the physical environment objects, the radio signal propagation characteristics or the wireless communication network. Notably, a second sub-model is an intermediate quantity that generates the second model, but the sub-model may be used to generate a digital counterpart in some implementations.
[0193] In some instances, the fifth information may indicate the model process to generate the one or more second sub-models. For example, the fifth information may indicate model fine-tuning, model alignment and / or model inference.
[0194] In some instances, the fifth information may indicate the input data for generating the second sub-model; or the output data for generating the second sub-model; or the reward of reinforce learning for generating the second sub-model; or a combination thereof.
[0195] The fifth information may include various parameters related to the configuration for reporting the one or more second sub-models. In some instances, the fifth information may indicate the scheduling configuration for transmitting the one or more second sub-models respectively. In some instances, the fifth information may indicate required parameters corresponding to the one or more sub-models. In some instances, the parameters related to the configuration for reporting the one or more second sub-models can refer to the description of the configuration for reporting the real-time data indicated by the fourth information. The details are omitted for brevity.
[0196] The fifth information may include parameter (s) related to the one or more third devices. In some instances, the fifth information may indicate IDs of the one or more third devices that generate a second sub-model based on a first sub-model.
[0197] Notably, the first device may transmit the fifth information in a variety of ways. For example, the first device may broadcast the fifth information, or multi-cast the fifth information to a group of third devices. Each third device could obtain its first sub-model from the fifth information. For another example, the first device may transmit multiple fifth information to multiple third devices respectively, and each fifth information may indicate the corresponding first sub-model. This is not limited to this application. For another example, when the first device transmits multiple fifth information to multiple third devices respectively, the fifth information in step 721B may indicate the combination of the multiple fifth information.
[0198] At step 722B, the one or more third devices obtain real-time data based on the fifth information.
[0199] For example, the one or more third devices may obtain the sensing result, measuring result, and / or model result respectively.
[0200] At step 723B, the one or more third devices generate one or more second sub-models based on the one or more first sub-models and real-time data respectively.
[0201] For example, each third device may generate the corresponding second sub-model based on its corresponding first sub-model and real-time data. Exemplary, the third device may perform the one or more of: model fine-tuning, model alignment and model inference. Notably, this application does not exclude other possible model processes.
[0202] At step 724B, the one or more third devices transmit sixth information to the first device. Correspondingly, the first device may receive the sixth information from the one or more third devices.
[0203] The sixth information indicates the one or more second sub-models. For example, each sixth information that transmitted by a third device indicate its corresponding second sub-model. For another example, third devices #1 reports information #1 indicate its corresponding second sub-model #1, third devices #2 reports information #2 related to indicate its corresponding second sub-model #2. Then from the first device side, the sixth information indicating the one or more second sub-models may indicate a combination of the information #1 and information #2.
[0204] In some implementations, each sixth information may include various parameters related to the corresponding second sub-model. In some instances, the sixth information may include part or all of the sub-model parameters (e.g., updated sub-model parameters) of the corresponding second sub-model. In some instances, the sixth information may indicate ID of the corresponding third device. In some instances, the sixth information may indicate the functionality ID and / or model ID of the general model. In some instances, the sixth information may indicate the functionality ID and / or model ID of the corresponding second sub-model. This is not limited to this application.
[0205] At step 725B, the first device generates the second model based on the one or more second sub-models.
[0206] The first device may combine the second sub-models together to form a local model (i.e., the second model) . The local model is generated in a distributed way.
[0207] In a third implementation, the first device may obtain the real-time data by itself. For example, the first device may have the capability of sensing, measuring, or modeling (e.g., via a third model) , so that the first device may perform the sensing, measuring or modeling tasks to obtain the real-time data. Therefore, the first device generates the second model based on the first model and the real-time data.
[0208] Notably, the foregoing three implementations may be implemented individually or implemented in a combination. For example, the first device may obtain part of real-time data by itself, and collect part of real-time from one or more third devices. For another example, when the first device splits the first model into multiple first sub-models, the first model may distribute part of the multiple first sub-models to third devices, and remain part of the multiple first sub-models to generate a second sub-model by itself. This is not limited to this application.
[0209] Notably, in some instances, the first device may request real-time data from the one or more third devices directly (as illustrated in FIG. 7) . In some other instances, although not illustrated, the first device may request real-time data from the one or more third devices through another device (e.g., a fourth device responsible for data collection) . In these instances, the first device may transmit fifth information (request the real-time data) to the fourth device, the fourth device collect the real-data and transmit the real-data to the first device. This is not limited to this application.
[0210] Notably, in some instances, the first device may distribute the one or more first sub-models to the one or more third devices directly (as illustrated in FIG. 8) . In some other instances, although not illustrated, the first device may distribute the one or more first sub-models to the one or more third devices through another device (e.g., a fifth device for managing calculating) . In these instances, the first device may transmit sixth information (indicate the one or more first sub-models) to the fifth device, and the fifth device distribute the one or more first sub-models to the one or more third devices. This is not limited to this application.
[0211] Still referring to FIG. 7, the first device may upload the new second model to the first device. That is, the first device and the second device could further perform step 730.
[0212] Optionally, at step 730, the first device transmits second information to the second device. Correspondingly, the second device receives the second information from the first device.
[0213] The second information indicates the second model. In some implementations, the second information may indicate various parameters related to the second model. In some instances, the second information may include part or all of model parameters of the second model. For example, the second information may include all of model parameters of the second model, or the second information may include updated model parameters compared to the first model.
[0214] In some instances, the second information may indicate ID of the second model. For example, the second information may include the functionality ID and / or model ID of the second model. In some instances, the second information may indicate the ID of the first device (e.g., the ID of local controller) .
[0215] In some implementations, the second device may acknowledge the second information, so that the first device may know that the second model is uploaded successfully.
[0216] In some implementations, the first device may upload the second model to the second device periodically. Since the second model is generated in a real-time way, the first device could update a new second model in a period. Notably, the uploaded second model may be used as a general model later.
[0217] Still referring to FIG. 7, as aforementioned in step 710, the first device may obtain the first information in a variety of ways. In a first implementation, the second device may transmit the first information to the first device without first device’s request. For example, the second device may broadcast the first information. In a second implementation, the first device and the second device may perform the step 740 before step 710.
[0218] Optionally, at step 740, the first device transmits third information to the second device. Correspondingly, the second device receives the third information from the first device.
[0219] The third information requests the first model. The second device could respond to the third information, transmit the first information to the first device.
[0220] In some implementations, the third information indicates one or more of: an identifier of the first device, and requested parameter list associated with the first model.
[0221] The requested parameter list associated with the first model may include various parameters related to the first model. In some instances, the third information may indicate the ID (model ID and / or functionality ID) of the requested model (i.e., the first model) . In some instances, the third information may indicate a version (preferred version) of the requested model. In some instances, the third information may indicate a format (preferred format) of the requested model. Thus, the second device could transmit the requested first model to the first device based on the requested parameter list.
[0222] In some implementations, the third information may further indicate parameters related to the previously downloaded model, for example, functionality ID, model ID, version, format, and etc. Thus, the second device may determine whether the first device has already downloaded the latest general model. When the latest model is different from the indicated previously downloaded model, the second device may transmit the requested first model to the first device.
[0223] According to the foregoing method, a first device can obtain a first model from a second device, and generate a second model based on the first model and real-time data. The second model is used to generate a digital counterpart of a physical world. The second model can have better performance due to the real-time data.
[0224] The methods according to embodiments of this application are described above in detail with reference to FIGS. 7-9. The apparatuses provided in embodiments of this application are described below in detail with reference to FIGS. 7-9. The description of apparatus embodiments corresponds to the description of the method embodiments. Therefore, for content that is not described in detail, refer to the foregoing method embodiments. For brevity, details are not described herein again.
[0225] As aforementioned in FIG. 4, the apparatus 410 may be configured to perform actions performed by the first device in the foregoing method embodiments. In this case, the apparatus 410 may be the first device or a component that can be configured in the first device.
[0226] The apparatus 410 may implement steps or procedures performed by the first device in FIGs. 7-9 according to embodiments of this application. The apparatus 410 may include units configured to perform the method performed by the first device in FIGs. 7-9. In addition, the units in the communication apparatus 410 and the foregoing other operations and / or functions are separately used to implement corresponding procedures in FIGS. 7-9.
[0227] Alternatively, the apparatus 410 may be configured to perform actions performed by the second device in the foregoing method embodiments. In this case, the apparatus 410 may be the second device or a component that can be configured in the second device.
[0228] The apparatus 410 may implement steps or procedures performed by the second device in FIGs. 7-9 according to embodiments of this application. The apparatus 410 may include units configured to perform the method performed by the second device in FIGs. 7-9. In addition, the units in the communication apparatus 410 and the foregoing other operations and / or functions are separately used to implement corresponding procedures in FIGs. 7-9.
[0229] Alternatively, the apparatus 410 may be configured to perform actions performed by the third device in the foregoing method embodiments. In this case, the apparatus 410 may be the third device or a component that can be configured in the third device.
[0230] The apparatus 410 may implement steps or procedures performed by the third device in FIGs. 7-9 according to embodiments of this application. The apparatus 410 may include units configured to perform the method performed by the third device in FIGs. 7-9. In addition, the units in the communication apparatus 410 and the foregoing other operations and / or functions are separately used to implement corresponding procedures in FIGs. 7-9.
[0231] A specific process in which the units perform the foregoing corresponding steps is described in detail in the foregoing method embodiments. For brevity, details are not described herein again.
[0232] As aforementioned in FIG. 5, the methods in the foregoing method embodiments are executed by the apparatus 510.
[0233] In some embodiments, the apparatus 510 may be a first device or a component (e.g., a chip, a circuit, or a processing system) that can be configured in the first device; or the communication apparatus 510 may be a second device or a component (e.g., a chip, a circuit, or a processing system) that can be configured in the second device; or the communication apparatus 510 may be a third device or a component (e.g., a chip, a circuit, or a processing system) that can be configured in the third device.
[0234] In a solution, the apparatus 510 is configured to perform the operations performed by the first device in the foregoing method embodiments.
[0235] For example, the processor unit 511 may be configured to perform a processing-related operation performed by the first device in the foregoing method embodiments, and the communication unit 513 may be configured to perform a communicating-related (e.g., receiving / transmitting-related) operation performed by the first device in the foregoing method embodiments.
[0236] In another solution, the apparatus 510 is configured to perform the operations performed by the second device in the foregoing method embodiments.
[0237] For example, the processor unit 511 may be configured to perform a processing-related operation performed by the second device in the foregoing method embodiments, and the communication unit 513 may be configured to perform a communicating-related (e.g., receiving / transmitting-related) operation performed by the second device in the foregoing method embodiments.
[0238] In another solution, the apparatus 510 is configured to perform the operations performed by the third device in the foregoing method embodiments.
[0239] For example, the processor unit 511 may be configured to perform a processing-related operation performed by the third device in the foregoing method embodiments, and the communication unit 513 may be configured to perform a communicating-related (e.g., receiving / transmitting-related) operation performed by the third device in the foregoing method embodiments.
[0240] An embodiment of this application further provides a computer-readable storage medium. The computer-readable storage medium stores computer instructions used to implement the method performed by the first device, or the method performed by the second device or the method performed by the third device in the foregoing method embodiments.
[0241] For example, when the computer program is executed by a computer, the computer may be enabled to implement the method performed by the first device, or the method performed by the second device, or the method performed by the third device in the foregoing method embodiments.
[0242] An embodiment of this application further provides a computer program product including instructions. When the instructions are executed by a computer, the computer is enabled to implement the method performed by the first device, or the method performed by the second device, or the method performed by the third device in the foregoing method embodiments.
[0243] An embodiment of this application further provides a communication system. The communication system includes the first device and the second device in the foregoing embodiments. Optionally, the communication system further includes the third device in the foregoing embodiments.
[0244] For explanations and beneficial effects of related content of any communication apparatus provided above, refer to a corresponding method embodiment provided above. Details are not described herein again.
[0245] A person of ordinary skill in the art may be aware that, in combination with the examples described in embodiments disclosed in this specification, units and methods may be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed by hardware or software depends on particular applications and design constraints of the technical solutions. A person skilled in the art may use different methods to implement the described functions for each particular application, but it should not be considered that the implementation goes beyond the protection scope of this application.
[0246] It should be noted that the term “receive” or “receiving” used herein may refer to receiving or otherwise obtaining from an element / component in same apparatus or from another device separate from the apparatus. Similarly, the term “transmit” or “transmitting” may refer to outputting or sending to / for an element / component in same apparatus or to / for another device separate from the apparatus. For example, any of the methods / procedures described herein may be performed by a chipset, in which case any sending or receiving steps may occur between elements of the chipset.
[0247] It may be clearly understood by a person skilled in the art that, for the purpose of convenient and brief description, for a detailed working process of the foregoing apparatus and unit, refer to a corresponding process in the foregoing method embodiment. Details are not described herein again.
[0248] In the several embodiments provided in this application, the disclosed apparatuses and methods may be implemented in other manners. For example, the described apparatus embodiment is merely an example. For example, division into the units is merely logical function division and may be other division in an actual implementation. For example, a plurality of units or components may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections may be implemented through some interfaces. The indirect couplings or communication connections between the apparatuses or units may be implemented in electronic forms, mechanical forms, or other forms.
[0249] The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units may be selected based on an actual requirement to implement the solutions provided in this application.
[0250] In addition, function units in embodiments of this application may be integrated into one unit, or each of the units may exist alone physically, or two or more units may be integrated into one unit.
[0251] All or some of the foregoing embodiments may be implemented by using software, hardware, firmware, or any combination thereof. When the software is used to implement embodiments, all or a part of embodiments may be implemented in a form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the procedures or functions according to embodiments of this application are all or partially generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or another programmable apparatus. For example, the computer may be a personal computer, a server, a network device, or the like. The computer instructions may be stored in a computer-readable storage medium or may be transmitted from a computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website, computer, server, or data center to another website, computer, server, or data center in a wired (for example, a coaxial cable, an optical fiber, or a digital subscriber line (DSL) ) or wireless (for example, infrared, radio, and microwave, or the like) manner. The computer-readable storage medium may be any usable medium accessible by the computer, or a data storage device, for example, a server or a data center, integrating one or more usable media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, or a magnetic tape) , an optical medium (for example, a DVD) , a semiconductor medium (for example, an SSD) , or the like. For example, the usable medium may include but is not limited to any medium that can store program code, such as a USB flash drive, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disc.
[0252] The present disclosure encompasses various embodiments, including not only method embodiments, but also other embodiments such as apparatus embodiments and embodiments related to non-transitory computer readable storage media. Embodiments may incorporate, individually or in combinations, the features disclosed herein.
[0253] Although this disclosure refers to illustrative embodiments, this is not intended to be construed in a limiting sense. Various modifications and combinations of the illustrative embodiments, as well as other embodiments of the disclosure, will be apparent to persons skilled in the art upon reference to the description.
[0254] Features disclosed herein in the context of any particular embodiments may also or instead be implemented in other embodiments. Method embodiments, for example, may also or instead be implemented in apparatus, system, and / or computer program product embodiments. In addition, although embodiments are described primarily in the context of methods and apparatus, other implementations are also contemplated, as instructions stored on one or more non-transitory computer-readable media, for example. Such media could store programming or instructions to perform any of various methods consistent with the present disclosure.
Claims
1.A model generation method, comprising:receiving (710) first information, wherein the first information indicates a first model; andgenerating (720) a second model based on the first model and real-time data related to a physical world, wherein the second model is used to generate a digital counterpart of the physical world.2.The method according to claim 1, wherein the method further comprises:transmitting (730) second information, wherein the second information indicates the second model.3.The method according to claim 1 or 2, wherein the real-time data comprises one or more of:data that indicates the physical environment objects in the physical world;data that indicates radio signal propagation characteristics in the physical world; anddata that indicates parameters associated with a wireless communication network deployed in the physical world.4.The method according to any one of claims 1 to 3, wherein the real-time data is obtained from one or more of: measuring the physical world, sensing the physical world, and a third model.5.The method according to any one of claims 1 to 4, wherein the method further comprises:transmitting (740) third information, wherein the third information requests the first model.6.The method according to claim 5, wherein the third information indicates one or more of:an identifier of a device that requests the first model; andrequested parameter list associated with the first model.7.The method according to any one of claims 1 to 6, wherein the method further comprises:transmitting fourth information, the fourth information requests the real-time data; andreceiving the real-time data.8.The method according to claim 7, wherein the fourth information indicates one or more of:a configuration for obtaining the real-time data;a configuration for reporting the real-time data; andat least one identifier of at least one device that obtains the real-time data.9.The method according to any one of claims 1 to 6, wherein the method further comprises:transmitting fifth information, wherein the fifth information indicates one or more first sub-models obtained based on the first model; andreceiving sixth information, wherein the sixth information indicates one or more second sub-models, the one or more second sub-models are generated based on the one or more first sub-models and the real-time data, and the second model is generated based on the one or more second sub-models.10.The method according to claim 9, wherein the fifth information further indicates one or more of:a configuration for obtaining the real-time data;a configuration for generating the one or more second sub-models;a configuration for reporting the one or more second sub-models; andat least one identifier of at least one device that generates the one or more second sub-models.11.The method according to claim 8 or 10, wherein the configuration for obtaining the real-time data indicates one or more of: a type of the real-time data, and at least one parameter that describes one or more tasks used for generating the real-time data.12.The method according to claim 8, wherein the configuration for reporting the real-time data indicates one or more of:at least one parameter of the real-time data to be reported, and a physical resource used for reporting the real-time data.13.A model generation method, comprising:transmitting (710) first information, wherein the first information indicates a first model, and the first model and real-time data related to a physical world are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.14.The method according to claim 13, wherein the method further comprises:receiving (730) second information, wherein the second information indicates the second model.15.The method according to claim 13 or 14, wherein the real-time data comprises one or more of:data that indicates the physical environment objects in the physical world;data that indicates radio signal propagation characteristics in the physical world; anddata that indicates parameters associated with a wireless communication network deployed in the physical world.16.The method according to any one of claims 13 to 15, wherein the real-time data is obtained from one or more of: measuring the physical world, sensing the physical world, and a third model.17.The method according to any one of claims 13 to 16, wherein the method further comprises:receiving (740) third information, wherein the third information requests the first model.18.The method according to claim 17, wherein the third information indicates one or more of:an identifier of a device that requests the first model; andrequested parameter list associated with the first model.19.A model generation method, comprising:obtaining real-time data related to a physical world; andtransmitting information related to the real-time data, wherein the real-time data and a first model are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.20.The method according to claim 19, wherein the method further comprises:receiving fourth information, wherein the fourth information requests the real-time data, and the information related to real-time data comprises the real-time data.21.The method according to claim 20, wherein the fourth information indicates one or more of:a configuration for obtaining the real-time data;a configuration for reporting the real-time data; andan identifier of a device that obtains the real-time data.22.The method according to claim 19, wherein the method further comprises:receiving fifth information, wherein the fifth information indicates a first sub-model among one or more first sub-models obtained based on the first model; andgenerating a second sub-model based on the first sub-model and the real-time data, wherein the information related to the real-time data indicates the second sub-model.23.The method according to claim 22, wherein the fifth information further indicates one or more of:a configuration for obtaining the real-time data;a configuration for generating the second sub-model;a configuration for reporting the second sub-model; andan identifier of a device that generates the second sub-model.24.The method according to claim 21 or 23, wherein the configuration for obtaining the real-time data indicates one or more of: a type of the real-time data, and at least one parameter that describes one or more tasks used for generating the real-time data.25.The method according to claim 21, wherein the configuration for reporting the real-time data indicates one or more of: at least one parameter of the real-time data to be reported, and a physical resource used for reporting the real-time data.26.A communication apparatus, configured to perform the method according to any one of claims 1 to 12, or 13 to 18, or 19 to 25.27.The communication apparatus of claim 26, wherein comprising:receiving unit, configured to receive first information, wherein the first information indicates a first model;generating unit, configured to generate a second model based on the first model and real-time data related to a physical world, wherein the second model is used to generate a digital counterpart of the physical world.28.The communication apparatus of claim 26, comprising transmitting unit that is configured to first information, wherein the first information indicates a first model, and the first model and real-time data related to a physical world are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.29.The communication apparatus of claim 26, wherein comprising:obtaining unit, configured to obtain real-time data related to a physical world;transmitting unit, configured to transmit information related to the real-time data, wherein the real-time data and a first model are used to generate a second model, and the second model is used to generate a digital counterpart of the physical world.30.The communication apparatus of claim 26, comprising:one or more processors, configured to perform processing step according to any one of claims 1 to 12, or 13 to 18, or 19 to 25;an interface circuit, configure to perform transmitting or receiving step according to any one of claims 1 to 12, or 13 to 18, or 19 to 25.31.The communication apparatus of claim 30, the interface circuit comprises one or more transceivers.32.An apparatus comprising:one or more processors; anda memory storing instructions which, when executed by the one or more processors, cause the apparatus to: perform the method of any one of claims 1 to 12, or 13 to 18, or 19 to 25.33.A communication system, wherein the communication system comprises a first communication apparatus configured to perform the method of any one of claims 1 to 12 and a second communication apparatus configured to perform the method of any one of claims 13 to 18.34.The system according to claim 33, wherein the communication system further comprises a third communication apparatus configured to perform the method of any one of claims 19 to 25.35.A computer-readable storage medium having instructions stored thereon which, when executed by apparatus, cause the apparatus to perform the method of any one of 1 to 12, or 13 to 18, or 19 to 25.36.A computer program product having instructions which, when executed, cause an apparatus to perform the method of any one of claims 1 to 12, or 13 to 18, or 19 to 25.
Citation Information
Patent Citations
Smart factory management system based on digital twinning
CN118192453A
State prediction reliability modeling
US20230078208A1
Crane stability analysis method and apparatus, and crane Anti-overturn control method and apparatus
WO2023197417A1