Communication method and device

Abstract

The invention provides a communication method and device, and the method comprises the steps: obtaining multi-domain data information, the multi-domain data information comprises first data information and second data information, the first data information is data information related to user service experience, and the second data information is data information related to a wireless key performance index of a user service; determining a digital twin based on the multi-domain data information, the digital twin including entity objects and attribute information corresponding to the entity objects, the entity objects including a user entity object, a network function entity, a grid entity object and a service entity object, the attribute information corresponding to the entity object comprises the attribute information of the user entity object, the attribute information of the network function entity, the attribute information of the grid entity object and the attribute information of the service entity object, and the digital twin is used for network optimization. And the service experience is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a communication method and device. Background Art

[0002] During the network optimization process, when the user's service experience is poor, the purpose of improving the user's service experience is achieved by optimizing all key performance indicators that may be related to the service problem. For example, within a certain period of time, the number of game freezes in a certain cell / network element increases. After the service problem is assigned to the network optimization department, the network optimization department improves the service experience by optimizing all wireless key performance indicators related to the service problem, such as coverage, interference, capacity, etc. Summary of the invention

[0003] The present application proposes a communication method and device that can build a digital twin and use the digital twin for network optimization, thereby improving the service experience.

[0004] In a first aspect, an embodiment of the present application provides a communication method, the method comprising acquiring multi-domain data information, the multi-domain data information comprising first data information and second data information, the first data information being data information related to a user service experience, and the second data information being data information related to wireless key performance indicators of a user service; determining a digital twin based on the multi-domain data information, the digital twin comprising an entity object and attribute information corresponding to the entity object, the entity object comprising a user entity object, a network function entity, a grid entity object, and a business entity object, the attribute information corresponding to the entity object comprising attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object, and attribute information of the business entity object, and the digital twin is used for network optimization.

[0005] The method can be applied to a server, including being executed by the server, or by a component in the server (e.g., a processor, a chip, or a chip system, etc.), or by a logic module or software that can implement all or part of the server functions.

[0006] In the above method, the digital twin is determined by multi-domain data information, and the multi-domain data information is integrated, so that the data for constructing the digital twin is more diversified. Moreover, the digital twin can be used for network optimization, thereby improving the business experience.

[0007] In one possible implementation, the first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

[0008] In another possible implementation, the attribute information of the user entity object includes the user identifier; the attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; the attributes of the grid entity object include the grid identifier and grid portrait information, and the grid portrait information includes grid location information and grid point of interest information; the attributes of the business entity object include business type information and the business identifier.

[0009] In another possible implementation, the digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs, and the relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

[0010] In yet another possible implementation manner, the method further includes: mapping the multi-domain data information to determine the grid entity object.

[0011] In another possible implementation, mapping the multi-domain data information to determine the grid entity object includes: mapping the multi-domain data information to determine the grid entity object based on longitude and latitude; or mapping the multi-domain data information to determine the grid entity object based on cell entry.

[0012] In the above method, the multi-domain data information is mapped to determine the grid entity object in the above two ways, so that the grid entity object can be analyzed more conveniently.

[0013] In another possible implementation, a main factor affecting the service experience information is determined from the at least two wireless key performance indicators based on the digital twin, and the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

[0014] Optionally, efficient relationship query and complex relationship insight analysis capabilities can be achieved through graph-based multi-hop query and relationship computing capabilities, and the main factors can be determined based on digital twins through frequent subgraph mining algorithms.

[0015] In the above method, through the above manner, the strongly correlated wireless key performance indicators that cause business problems can be determined through the digital twin, and the accuracy rate is very high, for example, it can be as high as 85%, so as to perform precise optimization. For example, the strongly correlated wireless key performance indicators can be optimized to solve business problems and improve business experience. The problem of insufficient correlation between business problems and wireless key performance indicators is solved. Compared with optimizing all wireless key performance indicators, network optimization resources can be used efficiently, thereby avoiding resource waste.

[0016] In another possible implementation, determining the main factors affecting the user service experience information from the at least two wireless key performance indicators based on the digital twin includes: determining at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to a score; comparing the at least two scores to determine the main factors affecting the service experience information, the main factor being the wireless key performance indicator with the highest score.

[0017] In another possible implementation, the method further includes: determining value indicators of different types of grids based on the digital twin; and determining value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0018] In the above method, the value scores of different types of grids are determined, and the value scores of different types of grids can be sorted. For example, different types of grids include schools, business districts, hospitals, and governments. Determining the value scores of different types of grids can be understood as determining the value scores of schools, business districts, hospitals, and governments, and sorting them according to the value scores to determine the value areas. For example, areas with high value scores are high-value areas, so network optimization can be performed to make efficient use of network optimization resources.

[0019] In another possible implementation, the multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

[0020] In the above method, through the above manner, multi-domain data information can be made not single, and the data can be more comprehensive, thereby making the constructed digital twin more accurate.

[0021] In a second aspect, an embodiment of the present application provides a communication device, which may be a server, or a component in a server (for example, a processor, a chip, or a chip system, etc.), or a logic module or software that can implement all or part of the server functions, including: an acquisition unit and a first determination unit, the acquisition unit being used to acquire multi-domain data information, the multi-domain data information including first data information and second data information, the first data information being data information related to a user service experience, and the second data information being data information related to wireless key performance indicators of a user service; the first determination unit being used to determine a digital twin based on the multi-domain data information, the digital twin including an entity object and attribute information corresponding to the entity object, the entity object including a user entity object, a network function entity, a grid entity object, and a business entity object, the attribute information corresponding to the entity object including attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object, and attribute information of the business entity object, and the digital twin is used for network optimization.

[0022] In one possible implementation, the first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

[0023] In another possible implementation, the attribute information of the user entity object includes the user identifier; the attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; the attributes of the grid entity object include the grid identifier and grid portrait information, and the grid portrait information includes grid location information and grid point of interest information; the attributes of the business entity object include business type information and the business identifier.

[0024] In another possible implementation, the digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs, and the relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

[0025] In yet another possible implementation, the device further includes a mapping unit, and the mapping unit is configured to map the multi-domain data information to determine the grid entity object.

[0026] In another possible implementation, the mapping unit is used to map the multi-domain data information based on longitude and latitude to determine the grid entity object; or to map the multi-domain data information based on cell entry to determine the grid entity object.

[0027] In another possible implementation, the device also includes a second determination unit, which is used to determine a main factor affecting the service experience information from the at least two wireless key performance indicators based on the digital twin, and the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

[0028] In another possible implementation, the second determination unit is used to determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to a score; the second determination unit is used to compare the at least two scores to determine the main factor affecting the service experience information, wherein the main factor is the wireless key performance indicator with the highest score.

[0029] In another possible implementation, the device also includes a third determination unit, which is used to determine value indicators of different types of grids based on the digital twin; the third determination unit is used to determine the value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0030] In another possible implementation, the multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

[0031] Regarding the technical effects brought about by the second aspect or possible implementation methods, reference may be made to the introduction to the technical effects of the first aspect or corresponding implementation methods.

[0032] In a third aspect, an embodiment of the present application provides a communication device, which may be a server, or a component in a server (for example, a processor, a chip, or a chip system, etc.), or a logic module or software that can implement all or part of the server functions. The communication device includes at least one processor and a communication interface, and the at least one processor calls a computer program or instruction stored in a memory to perform the following operations: obtaining multi-domain data information, the multi-domain data information including first data information and second data information, the first data information being data information related to a user service experience, and the second data information being data information related to wireless key performance indicators of the user service; determining a digital twin based on the multi-domain data information, the digital twin including an entity object and attribute information corresponding to the entity object, the entity object including a user entity object, a network function entity, a grid entity object, and a business entity object, the attribute information corresponding to the entity object including attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object, and attribute information of the business entity object, and the digital twin is used for network optimization.

[0033] In one possible implementation, the first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

[0034] In another possible implementation, the attribute information of the user entity object includes the user identifier; the attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; the attributes of the grid entity object include the grid identifier and grid portrait information, and the grid portrait information includes grid location information and grid point of interest information; the attributes of the business entity object include business type information and the business identifier.

[0035] In another possible implementation, the digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs, and the relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

[0036] In yet another possible implementation, the processor is further configured to map the multi-domain data information to determine the grid entity object.

[0037] In another possible implementation, the processor is configured to map the multi-domain data information based on longitude and latitude to determine the grid entity object; or map the multi-domain data information based on cell entry to determine the grid entity object.

[0038] In another possible implementation, the processor is further used to determine a main factor affecting the service experience information from the at least two wireless key performance indicators based on the digital twin, and the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

[0039] In another possible implementation, the processor is also used to determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to a score; and compare the at least two scores to determine the main factor affecting the service experience information, wherein the main factor is the wireless key performance indicator with the highest score.

[0040] In another possible implementation, the processor is further used to determine value indicators of different types of grids based on the digital twin; and determine value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0041] In another possible implementation, the multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

[0042] Regarding the technical effects brought about by the third aspect or possible implementation methods, reference may be made to the introduction to the technical effects of the first aspect or corresponding implementation methods.

[0043] In a fourth aspect, an embodiment of the present application provides a chip device, wherein the chip device includes at least one processor, and the at least one processor is used to execute computer programs or instructions to implement the method described in any one of the above aspects.

[0044] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program or instruction is stored. When the computer program or instruction runs on a processor, the method described in any one of the above aspects is implemented.

[0045] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed on a computer, the method described in any one of the above aspects is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the architecture of a communication system provided by an embodiment of the present application;

[0047] Figure 2 It is a schematic diagram of a network problem optimization collaborative processing provided by an embodiment of the present application;

[0048] Figure 3 is a schematic diagram of a communication method provided in an embodiment of the present application;

[0049] Figure 4 is a schematic diagram of a user entity object provided in an embodiment of the present application;

[0050] Figure 5 is a schematic diagram of a network function entity provided in an embodiment of the present application;

[0051] Figure 6 is a schematic diagram of a grid entity object provided in an embodiment of the present application;

[0052] Figure 7 is a schematic diagram of a business entity object provided in an embodiment of the present application;

[0053] Figure 8 is a schematic diagram of a model of a digital twin provided in an embodiment of the present application;

[0054] Fig. 9 is a schematic diagram of a digital twin provided in an embodiment of the present application;

[0055] Fig.10 It is a schematic diagram of a grid entity object and TAZ-level indicators provided in an embodiment of the present application;

[0056] Fig.11 It is a schematic diagram of determining main factors provided in an embodiment of the present application;

[0057] Fig.12 is a schematic diagram of determining a value score provided in an embodiment of the present application;

[0058] Fig.13 is a structural diagram of a communication device provided in an embodiment of the present application;

[0059] Fig.14 It is a structural diagram of another communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application are described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0061] References to "one embodiment" or "some embodiments" etc. described in this application mean that a particular feature, structure or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present application. Thus, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear at different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0062] In the description of this application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c; a and b; a and c; b and c; or a, b, and c. Among them, a, b, and c can be single or multiple.

[0063] It can be understood that in this application, "indication" can include direct indication, indirect indication, explicit indication, implicit indication. When describing that a certain indication information is used to indicate A, it can be understood that the indication information carries A, directly indicates A, or indirectly indicates A.

[0064] In this application, the information indicated by the indication information is referred to as the information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated, etc., or the information to be indicated can be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved with the help of the arrangement order of each information agreed in advance (such as specified by the protocol), thereby reducing the indication overhead to a certain extent.

[0065] The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in this application. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the transmitting end device by sending configuration information to the receiving end device.

[0066] It can be understood that "sending" and "receiving" in this application indicate the direction of signal transmission. For example, "sending information to XX" can be understood as the destination of the information is XX, which can include direct sending through the air interface, and also includes indirect sending through the air interface by other units or modules. "Receiving information from YY" can be understood as the source of the information is YY, which can include directly receiving from YY through the air interface, and also includes indirectly receiving from YY through the air interface from other units or modules. "Sending" can also be understood as the "output" of the chip interface, and "receiving" can also be understood as the "input" of the chip interface.

[0067] In other words, sending and receiving can be performed between devices, for example, between a network device and a terminal device, or can be performed within a device, for example, sending or receiving between components, modules, chips, software modules, or hardware modules within the device through a bus, wiring, or interface.

[0068] It is understandable that information may be processed between the source and destination of information transmission, such as coding, modulation, etc., but the destination can understand the valid information from the source. Similar expressions in this application can be understood similarly and will not be repeated.

[0069] The communication method provided in the embodiment of the present application can be applied to cellular communication systems related to the third generation partnership project (3GPP), for example, fourth generation (4G) communication systems, such as long term evolution (LTE) communication systems, and can also be applied to fifth generation (5G) communication systems, such as 5G new radio (NR) communication systems, or to various future communication systems, such as sixth generation (6G) communication systems. The method provided in the embodiment of the present application can also be applied to Bluetooth systems, wireless fidelity (WiFi) systems, LoRa systems or Internet of Vehicles systems, communication systems that support the integration of multiple wireless technologies, and device-to-device (D2D) systems. The method provided in the embodiment of the present application can also be applied to satellite communication systems, wherein the satellite communication system can be integrated with the above-mentioned communication system. The wireless communication systems involved in this application also include but are not limited to: narrowband Internet of Things system (NB-IoT), global system for mobile communications (GSM), enhanced data rate for GSM evolution (EDGE), wideband code division multiple access system (WCDMA), code division multiple access 2000 system (CDMA2000), or time division-synchronization code division multiple access system (TD-SCDMA).

[0070] See also Figure 1 , Figure 1 is a schematic diagram of the architecture of a communication system provided in an embodiment of the present application. Figure 1The communication system shown is taken as an example to illustrate the application scenario used in this application. The communication system can be deployed on a single server or in a server cluster consisting of multiple servers. Among them, the communication system may include a customer experience management (CEM) system 101. Optionally, the communication system may also include a data acquisition system 102 and a network optimization system 103. Optionally, the data acquisition system 102 can be used to collect multi-domain data information, and the multi-domain data information includes first data information and second data information, wherein the first data information is data information related to the user's service experience, and the second data information is data information related to the wireless key performance indicators of the user's service. The CEM system 101 obtains the multi-domain data information. Optionally, the CEM system 101 can obtain the multi-domain data information from the data acquisition system 102, and then determine the digital twin based on the multi-domain data information. The digital twin includes a physical object and a corresponding physical object. The attribute information of the entity object includes a user entity object, a network function entity, a grid entity object and a business entity object. The attribute information corresponding to the entity object includes the attribute information of the user entity object, the attribute information of the network function entity, the attribute information of the grid entity object and the attribute information of the business entity object. The digital twin is used for network optimization. The CEM system 101 can also determine the main factors affecting the business experience information from the at least two wireless key performance indicators based on the digital twin. The CEM system 101 can also determine the value index of different types of grids based on the digital twin, and determine the value scores of different types of grids based on the value index and the weights corresponding to the value index. Among them, the network optimization system 103 can obtain the main factors affecting the business experience information from the CEM system 101, so as to optimize the network corresponding to the main factors. It can also obtain the value scores of different types of grids from the CEM system 101, and optimize the network based on the value scores of different types of grids.

[0071] Combine the following Figure 1 The communication system shown provides a detailed description of the communication method provided in the embodiment of the present application.

[0072] In order to better understand the solutions provided by the embodiments of the present application, some terms, concepts or processes involved in the embodiments of the present application are first introduced below.

[0073] During network optimization, see Figure 2 , Figure 2 It is a schematic diagram of a network problem optimization collaborative processing provided by an embodiment of the present application.

[0074] Step 1: Determine the business model based on business experience.

[0075] For example, the number of times a game detects freezes.

[0076] Step 2: Identify business problems based on the business model.

[0077] For example, the service problem may be that at a certain moment, the number of game freezes increases in a certain cell / network element.

[0078] Step 3: Define the business problem.

[0079] It can be understood that the service problem is a problem with the wireless cell, a transmission problem, or a core network problem.

[0080] Step 4: If the business issue is not a wireless issue, send the ticket to the corresponding department for processing.

[0081] For example, if the service problem is a core network problem, the order will be sent to the operator's core network department for processing.

[0082] Step 5: If the service issue is a wireless problem, send the ticket to the network optimization department for processing.

[0083] The dispatch information includes the community and business problem corresponding to the business problem.

[0084] Step 6: The network optimization department determines whether there is any abnormality in the wireless key performance indicator (KPI) of the cell corresponding to the service problem.

[0085] If there are any anomalies, all wireless KPIs of the cell are optimized. Wireless KPIs may include one or more of the following: signal to interference plus noise ratio (SINR), reference signal receiving power (RSRP), and physical resource block (PRB) utilization. Then the optimized service quality can be compared to determine whether the optimization is successful. If there are no anomalies, an order can be sent to the district / county for on-site optimization.

[0086] When the user's service experience is poor, the purpose of improving the user's service experience is achieved by optimizing all wireless key performance indicators that may cause the service problem. In this way, the optimization effect cannot be applied to the corresponding service, that is, it is impossible to determine the main factor causing the service problem, that is, the most relevant wireless key performance indicator among all wireless key performance indicators, and perform accurate optimization, resulting in a waste of resources.

[0087] See also Figure 3 , Figure 3Schematic diagram of a communication method provided in an embodiment of the present application, the method includes but is not limited to the following steps:

[0088] Step S301: Acquire multi-domain data information.

[0089] Among them, the multi-domain data information includes first data information and second data information, the first data information is data information related to the user's service experience, and the first data information may include one or more of the following: user identification, service identification, service type information, service experience information, network quality data information, wherein the user identification and service identification are mandatory items, and the service type information, service experience information and network quality data information are optional items. The service type information may be the category information of the service initiated by the user, for example, it may be video, game, instant messaging (IM), live broadcast, etc., which is not limited in the embodiment of the present application. The service experience information may be the data information obtained by measuring the key quality indicator (KQI) of the service experience after the user initiates the service, for example, it may be the effective download rate, freeze, etc., which is not limited in the embodiment of the present application. The network quality data information may be the data information obtained by measuring the key performance indicator (KPI) of the network after the user initiates the service, for example, it may be the network delay, uplink and downlink packet loss rate, etc., which is not limited in the embodiment of the present application.

[0090] Among them, the second data information is data information related to the wireless key performance indicators of the user service. For example, the second data information may include a measurement report (MR), which is the original network data measured by the user terminal. The measurement report carries the relevant information of the uplink and downlink wireless links, and may include the received signal channel power (RSCP), interference signal code power (ISCP), bit error rate (BLER), transmission power, etc.; for example, the second data information may include a call history record (CHR), which refers to a log file used by a network device to record problems encountered by a user during a call. The second data information may include one or more of the following: a network function entity identifier, a grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators. Among them, the network function entity identifier, the grid identifier, and the user identifier are mandatory items, and the type information of the network function entity and at least two wireless key performance indicators are optional items. The type information of the network function entity may be a cell, a base station, a core network element, etc. The wireless key performance indicators may include RSRP, SINR, and PRB utilization. Optionally, the first data information and the second data information are referred to as data information in the operation support system (OSS) domain, which may be referred to as OSS domain data information. Optionally, the first data information and the second data information in the multi-domain data information may be obtained from a data collection system or a network management system. Optionally, the data collection system may be a probe, which is deployed between core network elements and is used to collect network data in real time.

[0091] Optionally, the multi-domain data information may also include one or more of the following: data information related to customer management and services, and third-party data information. Optionally, the data information related to customer management and services includes one or more of the following: call package, whether it is a very, very important person VVIP, average revenue per user (ARPU), complaint information, roaming information, traffic package information, whether it is off-network, whether it is a derogatory user, whether it is in arrears, and whether it is limited. Among them, ARPU refers to the average communication service revenue contributed by each user in a period of time (usually one month or one year). Optionally, the data information related to customer management and services can be obtained from the operator. Optionally, the data information related to customer management and services can be referred to as data information in the business support system (BSS) domain, which can be referred to as B domain data information. The third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads. For example, POI information can be colleges, factories, residential areas, etc., which is not limited in the embodiments of this application. Optionally, the third-party data information can be purchased from a third party, for example, POI information can be purchased from a map company. Optionally, the third-party data information can be referred to as S-domain data information. In the above manner, the multi-domain data information can be made non-single, the data can be more comprehensive, and the constructed digital twin can be made more accurate.

[0092] Step S302: Determine the digital twin based on multi-domain data information.

[0093] Among them, the digital twin includes entity objects and attribute information corresponding to the entity objects. The entity objects include user entity objects, network function entities, grid entity objects and business entity objects. The attribute information corresponding to the entity objects includes attribute information of user entity objects, attribute information of network function entities, attribute information of grid entity objects and attribute information of business entity objects. The digital twin is used for network optimization. Determining the digital twin based on multi-domain data information can specifically include: generating entity objects based on the identification information in the first data information and the second data information in the multi-domain data information, for example, generating a user entity object based on the user identifier in the first data information, generating a business entity object based on the business identifier and business type information in the first data information, generating a network function entity based on the network function entity identifier and the type information of the network function entity in the second data information, and determining the grid entity object based on the multi-domain data information. The specific determination method is described below accordingly. Optionally, the digital twin can be represented by a graphical model.

[0094] The attribute information of the user entity object includes the user ID and, optionally, the user information. Optionally, the user ID may be the user's mobile phone number, and the user information may be the user's age, phone package, business preferences, etc. The user information may be obtained from the BSS, or may be obtained from the user data of the OSS using a machine learning method. In one example, see Figure 4 , Figure 4 This is a schematic diagram of a user entity object provided in an embodiment of the present application, wherein the attribute information of the user entity object includes: the user ID is 13XXX, the age is 28 years old, the business hobby is short videos, and the call package is a 168 package.

[0095] The attribute information of the network function entity includes the type information of the network function entity and the network function entity identifier. The type information of the network function entity may be a cell, a base station, a core network element, etc. Different types of network function entities may use different identifiers as network function entity identifiers. For example, a cell may use a cell identifier as a network function entity identifier. Optionally, the attribute information of the network function entity may also include parameter information of the network function entity, such as a network vendor, a service Internet protocol address (IP), etc. In one example, see Figure 5 , Figure 5 It is a schematic diagram of a network function entity provided in an embodiment of the present application, wherein the attribute information of the network function entity includes: the type information of the network function entity is a cell, the network function entity identifier is uid, and the network manufacturer is operator 1.

[0096] The attribute information of the grid entity object includes the grid identifier and the grid portrait information, wherein the grid portrait information includes the grid location information and the grid POI information, wherein the grid location information can be understood as the size and location of the grid coverage. The grid POI information can be understood as a classification, such as colleges, factories, residential areas, business districts, etc. In one example, see Figure 6 , Figure 6 It is a schematic diagram of a grid entity object provided in an embodiment of the present application, wherein the attribute information of the grid entity object includes: the grid identifier is network identifier 1, the grid POI information is XX school, the location information of the grid includes XX Road No. XX, the coverage size of the grid is 20 acres, the business type is mainly game business, delay sensitivity, and the commercial attribute is the number of VVIP users.

[0097] The attribute information of the business entity object includes business type information and business identification, and may also include business attributes, wherein the business type information may be the category information of the business initiated by the user, for example, it may be video, game, IM, live broadcast, etc., which is not limited in the present embodiment of the application. The business attributes may be the operating manufacturer of the business, the IP address of the business, etc. In one example, see Figure 7 , Figure 7 It is a schematic diagram of a business entity object provided in an embodiment of the present application, wherein the business entity object attribute information includes: the business identifier is business identifier 1, the operating manufacturer is manufacturer 1, the IP is 10.XX.XX.XX, and the business type information is live broadcast.

[0098] Among them, the digital twin also includes the relationship between entity objects and the time when the relationship between entity objects occurs. The relationship between entity objects includes one or more of the following: the relationship between user entity objects and network function entities, the relationship between user entity objects and grid entity objects, the relationship between user entity objects and business entity objects, the relationship between network function entities and grid entity objects, the relationship between network function entities and business entity objects, and the relationship between grid entity objects and business entity objects. Optionally, the relationship between user objects and network function entities may include network performance or load. For example, if the network function entity is a cell, network performance may refer to the user's delay, bandwidth, jitter, packet loss, etc. in the cell, and the load may be understood as the cell load, for example, the maximum number of users in the cell. The relationship between user entity objects and grid entity objects may include user location or user distribution, for example, whether the user is in the grid and the user distribution in the grid. The relationship between user entity objects and business entity objects may include user experience, for example, it may include business experience information, and the business experience information includes freeze, effective download rate, etc. The relationship between the network function entity and the grid entity object includes location information or the number of network function entities serving in the grid. For example, if the network function entity is a cell, the location information can be understood as whether the cell location is in the grid. The number of network function entities serving in the grid can refer to the number of cells served in the grid. The relationship between the network function entity and the service entity object includes the service network model or the service distribution in the grid. The service network model can be understood as service and network. For example, the service can be video service or game service. For example, the network can refer to the network's pipeline transmission indicators, delay rate, etc. In an example, see Figure 8 , Figure 8 The digital twin model is a schematic diagram of a digital twin, which includes four entity objects and the relationship between the four entity objects.

[0099] Optionally, when the digital twin is represented by a graph model, the relationship between entity objects can be described by the edges between nodes, that is, the edges are used to periodically describe the associations between entity objects, for example, XX business occurred at XX, what is the network quality data information, and what is the wireless key performance indicator. Optionally, each edge can have multiple attributes. Optionally, the attribute information of the edge may include the time when the relationship between entity objects occurs. Optionally, the attribute information of the edge may also include the service experience information, network quality data information in the first data information, and may also include at least two wireless key performance indicators in the second data information. Among them, the time when the relationship between entity objects occurs may refer to the moment or time period when the relationship between entity objects occurs. Optionally, the relationship between each entity object can be constructed based on the data information of the OSS domain (at XX moment, what business occurred, what is the service experience information, what is the network quality data information, and what is the wireless key performance indicator). Each time a business is initiated, the first data information and the second data information will be generated, but the value of the data collected each time is different. The first data information and the second data information can be associated by user identification and time. For example, a user with a user ID of 13XX initiates a gaming service at time T1, where the gaming service's service ID is service ID 2, lasts for x hours, service experience information is freeze, network quality data information includes an effective downlink rate of XX, a packet loss rate of XX, and at least two wireless key performance indicators include SRSP of XX, SINR of XX, and PRB utilization of XX. When the collected data includes the ID of entity object A and the ID of entity object B, A and B have a relationship, which in this example includes a user ID of 13XX and a service ID of service ID 2, that is, a user entity object and a service entity object have a relationship.

[0100] In one example, see Fig. 9 , Fig. 9This is a schematic diagram of a digital twin provided in an embodiment of the present application. The digital twin includes a user entity object, a network function entity, a grid entity object, and a business entity object. The attribute information of the user entity object includes: the user's identifier is 13XXX, the age is 28 years old, the business hobby is short video, and the call package is 168 package; the attribute information of the network function entity includes: the type information of the network function entity is a cell, the network function entity identifier is uid, and the network manufacturer is operator 1. The attribute information of the grid entity object includes: the grid identifier is network mark 1, the grid POI information is XX school, the location information of the grid includes XX Road XX, the coverage size of the grid is 20 acres, the business type is mainly game business, delay sensitivity, and the commercial attribute is the number of VVIP users. The attribute information of the business entity object includes: the business identifier is industry mark 1, the operating manufacturer is manufacturer 1, the IP is 10.XX.XXXX, and the type information of the business is live broadcast. The digital twin also includes the relationship between entity objects, which can be specifically referred to. Fig. 9 It should be noted that Fig. 9 The description of the relationship between entity objects in is only used as an example, and the relationship between entity objects, that is, the attributes of the edges, may change depending on the analysis scenario.

[0101] In a possible implementation, before determining the twin based on the multi-domain data information, the multi-domain data information can also be mapped to determine the mesh entity object. Specifically, there are two mapping methods:

[0102] The first mapping method: multi-domain data information can be mapped in the form of longitude and latitude to determine the grid entity object.

[0103] Specifically, the first data information can be associated with the second data information through the five-tuple information (AMF Region ID, AMF Set ID, AMFPointer, AMF_UE_NGAP_ID) to fill in the longitude and latitude information.<AMF RegionID> Identify the area,<AMF Set ID> Uniquely identifies the AMF set within the authentication management function (AMF) area.<AMF Pointer> Identify one or more AMFs in the AMF set, and the AMF UENGAP ID is used to identify the UE in the AMF on the N2 reference point. For example, the first data information may include a user identifier, a service identifier, service type information, service experience information, network quality data information, the area where the user is located, and the user's location information. The second data information may include a network function entity identifier, a grid identifier, the user identifier, the type information of the network function entity, and at least two wireless key performance indicators. The number of users in the grid entity object can be determined through the first data information and the second data information. For example, if the grid entity object is a university, the number of users, high-frequency video traffic, high-frequency video downloads, and download rates of the university at a certain time node can be determined. Among them, the longitude and latitude information can be used to achieve a more accurate mapping of multi-domain data information to determine the grid entity object.

[0104] The second mapping method: mapping multi-domain data information based on the cell-to-grid method to determine the grid entity object.

[0105] Specifically, the multi-domain data information can be mapped to determine the grid entity object based on the number of wireless MRs in the cell and the quality of the MRs. For example, base station 1 covers two grid entity objects, namely grid 1 and grid 2. The network function entity identifier of grid 1 is network label 1, the POI information of the network is XX school, the location information of the grid includes No. 01 of XX Road, and the coverage size of the grid is 20 mu; the network function entity identifier of grid 2 is network label 2, the POI information of the network is XX shopping mall, the location information of the grid includes No. 02 of XX Road, and the coverage size of the grid is 3000 square meters. For example, the total flow of user 1 under base station 1 is XX, and the number of MRs under grid 1 and the number of MRs under grid 2 can be determined through the configuration information of the base station, so that the flow proportion of user 1 under grid 1 and grid 2 can be determined according to the number of MRs under grid 1 and the number of MRs under grid 2, and finally the flow of user 1 under grid 1 and the flow of user 1 under grid 2 are determined.

[0106] In general, through the above two mapping methods, after the multi-domain data information is mapped to determine the grid entity object, the traffic autonomous zone (TAZ) level indicator can be determined from the grid entity object. Optionally, the TAZ level indicator can be the attribute information of the grid entity object. For example, see Fig.10 , Fig.10 This is a schematic diagram of a grid entity object and TAZ-level indicators proposed in an embodiment of the present application. For example, the grid entity object is a central business district (CBD), and the TAZ-level indicators are the number of users who have opened a certain package under the CBD, the number of speed-limited users, and the number of users in arrears; for example, the grid entity object is a business district, and the TAZ-level indicators can be the number of high-ARPU users, high-definition video traffic of high-ARPU users, real-time mobile game duration of high-ARPU users, the number of speed-limited users, the number of users in arrears, the number of users with poor voice quality, and the number of users with poor WeChat voice / video quality; for example, the grid entity object is a university, and the TAZ-level indicators can be the number of users who are off-grid, high-definition video traffic, high-definition video downloads, the number of users with poor game experience, and the real-time mobile game duration of users under the university; for example, the grid entity object is a government, and the TAZ-level indicators can be the number of complaining users; for example, the grid entity object is a hospital, and the TAZ-level indicators can be the number of derogatory users; for example, the grid entity object is an airport, and the TAZ-level indicators can be the number of roaming users. Optionally, high-value services, such as high-definition video traffic and real-time mobile game duration, can be determined based on TAZ-level indicators. Optionally, the grid including TAZ-level indicators can be referred to as TAZ grid. TAZ grid is the optimized block unit for business basic network planning, the source of user business demand, the basis for network basic resource demand measurement, and the basis for space-based differentiated strategy. Multi-scale grids can be provided for different business needs (planning, construction, operation and maintenance, optimization, etc.). Differentiated strategy of one grid and one policy execution. The grid seamlessly covers the planning area, carries multiple information, and contains multiple business forms.

[0107] In one example, the grid identifier of the grid entity object can be determined as network mark 1 through the POI information in the third-party data information and the grid information with commercial attributes divided by roads, the POI information of the grid is XX school, the location information of the grid includes No. XX, XX Road, and the coverage size of the grid is 20 acres. Then, through the population information in the third-party data and the statistics of the first data information and the second data information, it is determined that the business type of the XX school is mainly gaming business, the number of users with poor gaming experience, HD video traffic, HD video downloads, and users' real-time mobile game time.

[0108] In the above method, the multi-domain data information is mapped to determine the grid entity object in the above two ways, so that the grid entity object can be analyzed more conveniently.

[0109] In yet another possible implementation, after determining the digital twin, the method further includes: determining, based on the digital twin, a main factor affecting the service experience information from at least two wireless key performance indicators.

[0110] Optionally, the main factor is one wireless key performance indicator among at least two wireless key performance indicators.

[0111] Optionally, at least two scores corresponding to at least two wireless key performance indicators can be determined based on the digital twin, and at least two scores can be compared to determine the main factors affecting the service experience information. Among them, each key performance indicator corresponds to a score, and the main factor affecting the service experience information is the wireless key performance indicator with the highest score. Optionally, determining the main factors affecting the service experience information from at least two wireless key performance indicators based on the digital twin can be understood as determining the root cause relationship between the service experience information in the first data information and at least two wireless key performance indicators in the second data information based on the digital twin, or, in other words, determining the service experience information in the first data information and a wireless key performance indicator that is strongly correlated with the service experience information based on the digital twin, or determining the service experience information in the first data information and the main factors, non-main factors, etc. that affect the service experience information based on the digital twin. Optionally, after determining the main factors, the service experience can be improved by optimizing the main factors.

[0112] Optionally, based on the relational computing capability of the digital twin, that is, the multi-hop query and relational computing capability of the graph, the main factors affecting the service experience information can be determined from at least two wireless key performance indicators through frequent item mining of the subgraph, that is, the Frequent Subgraph Mining algorithm. This can be understood as determining the correlation between the service experience information and the wireless key performance indicators. For example, the service experience information is game lag, and the main factor is RSRP, that is, the main factor causing the game lag is RSRP.

[0113] In one example, see Fig.11 , Fig.11This is a schematic diagram for determining the main factors proposed in an embodiment of the present application. It is assumed that the first data information includes a user with a user identifier of 13XX initiating a gaming service at time T1, wherein the gaming service's service identifier is service identifier 2, lasting for x hours, and the service experience information is the video download rate difference, and the network quality data information includes an effective downlink rate of XX and a packet loss rate of XX. The second data information includes a user identifier of 13XX, and at least two wireless key performance indicators including SRSP of XX, SINR of XX, and PRB utilization of XX. Optionally, the wireless key performance indicator SRSP corresponding to the video download rate difference, the score 1, the SINR corresponding to the score 2, and the PRB utilization of the score 3 that affect the video download rate difference can be determined based on the digital twin through a frequent item mining algorithm of a subgraph, wherein the score 1 is greater than the score 2, and the score 1 is greater than the score 3. Therefore, SRSP is the main factor affecting the video download rate difference. Optionally, SINR and PRB utilization are non-main factors affecting the video download rate difference.

[0114] In the above method, through the above manner, the strongly correlated wireless key performance indicators that cause business problems can be determined through the digital twin, and the accuracy rate is very high, for example, it can be as high as 85%, so as to perform precise optimization. For example, the strongly correlated wireless key performance indicators can be optimized to solve business problems and improve business experience. The problem of insufficient correlation between business problems and wireless key performance indicators is solved. Compared with optimizing all wireless key performance indicators, network optimization resources can be used efficiently, thereby avoiding resource waste.

[0115] In another possible implementation, after determining the digital twin, the method further includes: determining value indicators of different types of grids based on the digital twin, and determining value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0116] Optionally, the value indicator can be the above-mentioned TAZ-level indicator. Optionally, different types of grids can be understood as different POI information of the grid. In one example, based on the digital twin, the grid identifier is determined to be network mark 1, the grid POI information is XX school, and the location information of the grid includes No. 01, XX Road. The value indicators can include the number of users with poor gaming experience, high-definition video traffic, high-definition video downloads, and the user's real-time mobile game duration, that is, the value indicator corresponding to XX school can be determined based on the digital twin; in another example, based on the digital twin, the grid identifier is determined to be network mark 2, the grid POI information is XX business district, and the location information of the grid includes No. 02, XX Road. The value indicators can include the number of high ARPU users in the business district, the high-definition video traffic of high ARPU users, the real-time mobile game duration of high ARPU users, the number of users with poor voice quality, and the number of users with poor WeChat voice / video quality, that is, the value indicators corresponding to XX business district can be determined based on the digital twin. Alternatively, when the grid is of other types, the corresponding value indicators may include the number of VVIP users, the number of complaining users, and so on.

[0117] Optionally, the weights corresponding to the value indicators can be determined by the entropy weight method. For specific steps, see Fig.12 , Fig.12 It is a schematic diagram of determining a value score provided by an embodiment of the present application. First, the value index is data standardized, then the information entropy of the value index is determined, and then the weight corresponding to the value index is determined, and finally the value score of different types of grids is determined. In one example, the value index corresponding to XX school determined based on the digital twin may include the number of users with poor gaming experience, high-definition video traffic, high-definition video downloads, and the user's real-time mobile game duration. The value index is data standardized. For example, the number of users with poor gaming experience, high-definition video traffic, high-definition video downloads, and the user's real-time mobile game duration are data standardized, respectively X1, X2, X3, and X4, and then the weight corresponding to the value index is determined based on the entropy weight method. For example, the number of users with poor gaming experience, high-definition video traffic, high-definition video downloads, and the weights corresponding to the user's real-time mobile game duration are w1, w2, w3, and w4, respectively, and the value score of the XX school is finally determined to be (w1*X1+w2*X2+w3*X3+w4*X4). The above is only an example of determining the value score of one type of grid, that is, an example of determining the value score of XX school. Of course, the value scores of other types of grids can be determined by reference to the above. For example, the value score of XX business district and the value score of the hospital can also be determined. Accordingly, after determining the value scores of different types of grids, they can be sorted according to the value scores to determine the value areas. For example, areas with high value scores are high-value areas, so as to perform network optimization, such as generating optimization plans and selecting optimization areas.

[0118] In the above method, the value scores of different types of grids are determined, and the value scores of different types of grids can be sorted. For example, different types of grids include schools, business districts, hospitals, and governments. Determining the value scores of different types of grids can be understood as determining the value scores of schools, business districts, hospitals, and governments, and sorting them according to the value scores to determine the value areas. For example, areas with high value scores are high-value areas, so network optimization can be performed to make efficient use of network optimization resources.

[0119] exist Figure 3 In the described method, the digital twin is determined by multi-domain data information, and the multi-domain data information is integrated, so that the data for constructing the digital twin is more diversified. Moreover, the digital twin can be used for network optimization, thereby improving the business experience.

[0120] The method of the embodiment of the present application is described in detail above, and the device of the embodiment of the present application is provided below.

[0121] See also Fig.13 , Fig.13 It is a structural diagram of a communication device 1300 provided in an embodiment of the present application. The communication device 1300 can be a server, or a component in a server (for example, a processor, a chip, or a chip system, etc.), or a logic module or software that can realize all or part of the server functions. The communication device 1300 may include an acquisition unit 1301 and a first determination unit 1302, and each unit is specifically as follows: the acquisition unit 1301 is used to acquire multi-domain data information, and the multi-domain data information includes first data information and second data information. The first data information is data information related to the user service experience, and the second data information is data information related to the wireless key performance indicators of the user service; the first determination unit 1302 is used to determine a digital twin based on the multi-domain data information, and the digital twin includes an entity object and attribute information corresponding to the entity object. The entity object includes a user entity object, a network function entity, a grid entity object, and a business entity object. The attribute information corresponding to the entity object includes attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object, and attribute information of the business entity object, and the digital twin is used for network optimization.

[0122] In one possible implementation, the first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

[0123] In another possible implementation, the attribute information of the user entity object includes the user identifier; the attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; the attributes of the grid entity object include the grid identifier and grid portrait information, and the grid portrait information includes grid location information and grid point of interest information; the attributes of the business entity object include business type information and the business identifier.

[0124] In another possible implementation, the digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs, and the relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

[0125] In yet another possible implementation, the device further includes a mapping unit, and the mapping unit is configured to map the multi-domain data information to determine the grid entity object.

[0126] In another possible implementation, the mapping unit is used to map the multi-domain data information based on longitude and latitude to determine the grid entity object; or to map the multi-domain data information based on cell entry to determine the grid entity object.

[0127] In another possible implementation, the device also includes a second determination unit, which is used to determine a main factor affecting the service experience information from the at least two wireless key performance indicators based on the digital twin, and the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

[0128] In another possible implementation, the second determination unit is used to determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to a score; the second determination unit is used to compare the at least two scores to determine the main factor affecting the service experience information, wherein the main factor is the wireless key performance indicator with the highest score.

[0129] In another possible implementation, the device also includes a third determination unit, which is used to determine value indicators of different types of grids based on the digital twin; the third determination unit is used to determine the value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0130] In another possible implementation, the multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

[0131] It should be noted that the implementation and beneficial effects of each module can also refer to Figure 3 The corresponding description of the method embodiment shown.

[0132] See also Fig.14 , Fig.14 It is a communication device 1400 provided in an embodiment of the present application. The communication device 1300 can be a server, or a component in a server (for example, a processor, a chip, or a chip system, etc.), or a logic module or software that can realize all or part of the server functions. The communication device 1400 includes at least one processor 1401 and a communication interface 1403, and optionally, also includes a memory 1402, wherein the processor 1401, the memory 1402 and the communication interface 1403 are interconnected via a bus 1404. The memory 1402 includes, but is not limited to, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a portable read-only memory (CD-ROM), and the memory 1402 is used for related computer programs and data. The communication interface 1403 is used to receive and send data.

[0133] The processor 1401 may be one or more central processing units (CPUs). When the processor 1401 is a CPU, the CPU may be a single-core CPU or a multi-core CPU.

[0134] The processor 1401 in the communication device 1400 is used to read the computer program stored in the memory 1402 to perform the following operations: obtain multi-domain data information, the multi-domain data information includes first data information and second data information, the first data information is data information related to the user service experience, and the second data information is data information related to the wireless key performance indicators of the user service; determine a digital twin based on the multi-domain data information, the digital twin includes an entity object and attribute information corresponding to the entity object, the entity object includes a user entity object, a network function entity, a grid entity object and a business entity object, the attribute information corresponding to the entity object includes attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object and attribute information of the business entity object, and the digital twin is used for network optimization.

[0135] In one possible implementation, the first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

[0136] In another possible implementation, the attribute information of the user entity object includes the user identifier; the attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; the attributes of the grid entity object include the grid identifier and grid portrait information, and the grid portrait information includes grid location information and grid point of interest information; the attributes of the business entity object include business type information and the business identifier.

[0137] In another possible implementation, the digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs, and the relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

[0138] In yet another possible implementation, the processor 1401 is further configured to map the multi-domain data information to determine the grid entity object.

[0139] In another possible implementation, the processor 1401 is configured to map the multi-domain data information based on longitude and latitude to determine the grid entity object; or map the multi-domain data information based on cell entry to determine the grid entity object.

[0140] In another possible implementation, the processor 1401 is further used to determine a main factor affecting the service experience information from the at least two wireless key performance indicators based on the digital twin, and the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

[0141] In another possible implementation, the processor 1401 is also used to determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to a score; and compare the at least two scores to determine the main factor affecting the service experience information, wherein the main factor is the wireless key performance indicator with the highest score.

[0142] In another possible implementation, the processor 1401 is further used to determine value indicators of different types of grids based on the digital twin; and determine value scores of different types of grids based on the value indicators and weights corresponding to the value indicators.

[0143] In another possible implementation, the multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

[0144] It should be noted that the implementation and beneficial effects of each operation can also refer to Figure 3 The corresponding description of the method embodiment shown.

[0145] The embodiment of the present application also provides a chip device, the chip device includes at least one processor, the at least one processor is used to call a computer program or instruction stored in a memory, so that the processor executes the above Figure 3 The illustrated embodiments provide methods.

[0146] The embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program or instruction, and when the computer program or instruction is executed on a processor, the above Figure 3 The illustrated embodiments provide for the method to be performed.

[0147] The embodiment of the present application also provides a computer program product, which includes a computer program or an instruction. When the computer program or the instruction is executed on a processor, the above Figure 3 The illustrated embodiments provide for the method to be performed.

[0148] It is understandable that the processor in the embodiments of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0149] The method steps in the embodiments of the present application can be implemented by hardware, or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, a register, a hard disk, a mobile hard disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a base station or a terminal. Of course, the processor and the storage medium can also be present in a base station or a terminal as discrete components.

[0150] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present application is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, a tape; it may also be an optical medium, for example, a digital video disc; it may also be a semiconductor medium, for example, a solid-state hard disk. The computer-readable storage medium may be a volatile or nonvolatile storage medium, or may include both volatile and nonvolatile types of storage media.

[0151] In the various embodiments of the present application, unless otherwise specified or provided for in any logical conflict, the terms and / or descriptions between the different embodiments are consistent and may be referenced to each other, and the technical features in the different embodiments may be combined to form new embodiments according to their inherent logical relationships.

[0152] In the description of this application, words such as "first", "second", "S301", or "S302" are only used to distinguish the description and facilitate the context. Different sequence numbers themselves do not have specific technical meanings and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying the order of execution of operations. The execution order of each process should be determined by its function and internal logic.

[0153] The term "and / or" in this application is only a description of the association relationship of the associated objects, indicating that there can be three kinds of relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article indicates that the associated objects before and after are in an "or" relationship.

[0154] In this application, "transmission" may include the following three situations: sending of data, receiving of data, or sending of data and receiving of data. In this application, "data" may include service data and / or signaling data.

[0155] In this application, the terms "comprises" or "has" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process / method comprising a series of steps, or a system / product / apparatus comprising a series of units, is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes / methods / products / apparatus.

[0156] In the description of this application, the number of nouns, unless otherwise specified, means "singular noun or plural noun", that is, "one or more". "At least one" means one or more. "Including at least one of the following: A, B, C." means that it may include A, or include B, or include C, or include A and B, or include A and C, or include B and C, or include A, B and C. A, B, and C can be single or plural.

Claims

1. A communication method, characterized in that: include: Acquire multi-domain data information, where the multi-domain data information includes first data information and second data information, where the first data information is data information related to user service experience, and the second data information is data information related to wireless key performance indicators of user services; A digital twin is determined based on the multi-domain data information, the digital twin including entity objects and attribute information corresponding to the entity objects, the entity objects including user entity objects, network function entities, grid entity objects and business entity objects, the attribute information corresponding to the entity objects includes attribute information of the user entity objects, attribute information of the network function entities, attribute information of the grid entity objects and attribute information of the business entity objects, and the digital twin is used for network optimization.

2. The method according to claim 1, characterized in that: The first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

3. The method according to claim 1 or 2, characterized in that: The attribute information of the user entity object includes the user identifier; The attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; The attributes of the grid entity object include the grid identifier and grid image information, and the grid image information includes grid location information and grid point of interest information; The attributes of the business entity object include business type information and the business identifier.

4. The method according to any one of claims 1 to 3, characterized in that: The digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs. The relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

5. The method according to any one of claims 2 to 4, characterized in that: The method further comprises: Based on the digital twin, a main factor affecting the service experience information is determined from the at least two wireless key performance indicators, where the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

6. The method according to claim 5, characterized in that The determining, based on the digital twin, the main factors affecting the user service experience information from the at least two wireless key performance indicators includes: Determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to one score; The at least two scores are compared to determine the main factor affecting the service experience information, where the main factor is the wireless key performance indicator with the highest score.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: determining value indicators of different types of grids based on the digital twin; The value scores of different types of grids are determined based on the value indicators and weights corresponding to the value indicators.

8. The method according to any one of claims 1 to 7, characterized in that: The multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

9. A communication device, characterized in that: comprising an acquisition unit and a first determination unit, The acquisition unit is used to acquire multi-domain data information, where the multi-domain data information includes first data information and second data information, where the first data information is data information related to user service experience, and the second data information is data information related to wireless key performance indicators of user services; The first determination unit is used to determine a digital twin based on the multi-domain data information, the digital twin including an entity object and attribute information corresponding to the entity object, the entity object including a user entity object, a network function entity, a grid entity object and a business entity object, the attribute information corresponding to the entity object includes attribute information of the user entity object, attribute information of the network function entity, attribute information of the grid entity object and attribute information of the business entity object, and the digital twin is used for network optimization.

10. The device according to claim 9, characterized in that The first data information includes one or more of the following: user identifier, service identifier, service type information, service experience information, and network quality data information; the second data information includes one or more of the following: network function entity identifier, grid identifier, the user identifier, type information of the network function entity, and at least two wireless key performance indicators, wherein the wireless key performance indicators include reference signal received power RSRP, signal to interference plus noise ratio SINR, and physical resource block PRB utilization.

11. The device according to claim 9 or 10, characterized in that The attribute information of the user entity object includes the user identifier; The attribute information of the network function entity includes type information of the network function entity and the network function entity identifier; The attributes of the grid entity object include the grid identifier and grid image information, and the grid image information includes grid location information and grid point of interest information; The attributes of the business entity object include business type information and the business identifier.

12. The device according to any one of claims 9 to 11, characterized in that: The digital twin also includes the relationship between the entity objects and the time when the relationship between the entity objects occurs. The relationship between the entity objects includes one or more of the following: the relationship between the user entity object and the network function entity, the relationship between the user entity object and the grid entity object, the relationship between the user entity object and the business entity object, the relationship between the network function entity and the grid entity object, the relationship between the network function entity and the business entity object, and the relationship between the grid entity object and the business entity object.

13. The device according to any one of claims 10 to 12, characterized in that: The device further comprises a second determining unit, The second determination unit is used to determine a main factor affecting the service experience information from the at least two wireless key performance indicators based on the digital twin, where the main factor is one wireless key performance indicator among the at least two wireless key performance indicators.

14. The method according to claim 13, characterized in that The second determination unit is used to determine at least two scores corresponding to the at least two wireless key performance indicators based on the digital twin, wherein each wireless key performance indicator corresponds to one score; The second determining unit is used to compare the at least two scores to determine the main factor affecting the service experience information, where the main factor is the wireless key performance indicator with the highest score.

15. The device according to any one of claims 9 to 14, characterized in that: The device further comprises a third determining unit, The third determination unit is used to determine value indicators of different types of grids based on the digital twin; The third determining unit is used to determine the value scores of different types of grids based on the value indicators and the weights corresponding to the value indicators.

16. The device according to any one of claims 9 to 15, characterized in that: The multi-domain data information also includes one or more of the following: data information related to customer management and services, and third-party data information; the data information related to customer management and services includes one or more of the following: user packages, whether the user is a very, very important person (VVIP), and the third-party data information includes one or more of the following: population information, point of interest (POI) information, and grid information with commercial attributes divided by roads.

17. A communication device, characterized in that: The apparatus comprises at least one processor and a communication interface, wherein the at least one processor calls a computer program or instruction stored in a memory to execute the method according to claims 1-8.

18. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program or instruction, which, when executed on a processor, implements the method according to any one of claims 1 to 8.

19. A computer program product, characterized in that The computer program product includes a computer program or instructions, and when the computer program or instructions are executed on a computer, the method according to any one of claims 1 to 8 is implemented.

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