A service classification method, terminal and process under base station network slicing

Abstract

The present invention relates to a service classification method, terminal and process under base station network slicing, including: the base station collects the service QoS requirements of each terminal device within its coverage; classifies the terminal devices according to the network slice category to be divided according to the service QoS requirements; updates the network slice type and the wireless resource configuration information within the slice according to the terminal device fuzzy C-means clustering method; broadcasts the configured network slice type and wireless resource configuration information to the terminal device; notifies the terminal device of the probability of the terminal device accessing the network slice through a random access process. The beneficial effects of the present invention are: the base station of the present invention can classify user terminals according to the number of network slices, and the user terminal can probabilistically access multiple different network slices according to the actual service type to ensure QoS requirements and improve wireless resource utilization.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and more specifically, to a service classification method, terminal and process under base station network slicing. Background Art

[0002] Traditional wireless communication technologies can no longer meet the development needs of diversified smart grid services. At the same time, these isolated wireless access methods also reduce the flexibility of the network to support different services. Traditional single networks carry all services, and it is difficult to meet the requirements of ultra-large bandwidth, ultra-low latency, and ultra-high reliability at the same time, resulting in poor service experience, low management efficiency, high network construction costs, and high operating costs, which seriously restricts the development of services.

[0003] 5G network has the advantages of ultra-high bandwidth, ultra-low latency and ultra-large-scale connection, which can meet the diversified business needs of the power industry. 56+ smart grid applications involve power grid security, so they are different from public network applications and have relatively strict requirements for security isolation and SLA guarantees. Smart grid business scenarios are rich, involving various types such as state perception, control protection, data collection, AI assistance, robot inspection, etc.; the transmission data is diversified, including state quantity, control instructions, pictures, videos, etc., and there are different requirements for network bandwidth, latency, jitter, bit error rate, reliability, etc. 5G network slicing can be divided into multiple end-to-end logical networks based on a unified physical network to meet the application scenarios of high bandwidth, high security, low latency and ultra-high reliability of the power grid, and provide the best solution for smart grid communication. The application of 5G network slicing technology can create customized "industry-specific network" services for power companies, which can better meet the security, reliability and flexibility requirements of power business, realize differentiated service guarantee, and greatly enhance the autonomous and controllable ability of power companies to their own business.

[0004] At present, the division method used for network slicing is mainly based on the user's service quality (Quality of Service, QoS) requirements to perform "hard slicing". The base station divides the wireless resources into several different network slices according to a certain service category template criterion, and each network slice allows access to users with similar service attributes.

[0005] In fact, the service requirements of user terminals are complex and diverse, and the total number of network slices that can be divided by base stations is limited. It is impossible to find a matching network slice for each user terminal. In other words, the service of a certain terminal must meet both low latency requirements and large bandwidth requirements. In this case, it is impossible to strictly match the terminal with the network slice on the base station side. The existing network slicing "hard slicing" method requires strict classification of user terminals into a certain network slice. Therefore, due to the uniqueness of certain services, strictly classifying such services into a network slice will not meet the quality of service (QoS) requirements of the service. Summary of the invention

[0006] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a service classification method, terminal and process under base station network slicing. The technical solution is as follows:

[0007] In a first aspect, a service classification method under a base station network slice is provided, including:

[0008] Step 1: The base station collects the service QoS requirements of each terminal device within its coverage area;

[0009] Step 2: The base station classifies the terminal devices according to the service QoS requirements and the network slice categories to be divided;

[0010] Step 3: The base station updates the network slice type and the wireless resource configuration information within the slice according to the fuzzy C means (FCM) method of the terminal device;

[0011] Step 4: The base station broadcasts the type of configured network slice and wireless resource configuration information to the terminal device;

[0012] Step 5: The base station notifies the terminal device of the probability of the terminal device accessing the network slice through a random access process.

[0013] Preferably, in step 3, the base station determines whether there is an update to the service QoS requirement of the terminal device in each transmission time interval; if the service QoS requirement is not updated, step 4 is executed; if the service QoS requirement is updated, it is determined whether the update cycle of the network slice is reached; if the update cycle of the network slice is reached, the network slice type and the wireless resource configuration information within the slice are updated according to the FCM method; if the update cycle of the network slice is not reached, step 4 is executed.

[0014] Preferably, in step 3, the FCM method comprises:

[0015] Step 3.1, input the service QoS requirements of the terminal device;

[0016] Step 3.2, initialize the basic parameters of terminal allocation, cluster center and slice membership matrix; the basic parameters of terminal allocation include: objective function J(U, c 1 , ..., c c ), the accuracy e of the objective function, the fuzzy index m, the maximum number of iterations LOOP and the number of iterations T;

[0017] Step 3.3, update the slice membership matrix and cluster center;

[0018] Step 3.4: Calculate the objective function J(U, c 1 , ..., c c ); If the objective function J(U, c 1 , ..., c c )satisfy:

[0019] |J(U,c 1 , ..., c c )-J(U+1,c 1 , ..., c c )|≤e

[0020] If the iteration is completed, execute step 3.5; otherwise, increase the number of iterations T by 1, and determine whether the number of iterations T is greater than the maximum number of iterations LOOP. If T>LOOP, the iteration is completed and execute step 3.5; otherwise, jump to step 3.3;

[0021] Step 3.5: Output the cluster center and slice membership matrix.

[0022] Preferably, in step 3.2, the objective function J(U, c 1 , ..., c c ) is expressed as:

[0023]

[0024] in, c i is the cluster center of network slice i; d ij =||c i -x j || is the Euclidean distance between the i-th cluster center and the j-th data point; m is the weighted index, and m∈1,∞).

[0025] Preferably, in step 3.3, the updating formula of the slice membership matrix is:

[0026]

[0027] Among them, p ijis the probability of the terminal device accessing each network slice; the update formula of the cluster center is:

[0028]

[0029] As a preference, in step 3.4, the objective function J(U, c 1 , ..., c c ) is expressed as: And with constraints:

[0030] In a second aspect, a base station as described in any one of the first aspects is provided, wherein the base station comprises: a first processor, a first memory, a sending interface and a slice classifier.

[0031] Preferably, the first processor performs flexible access grouping of terminal devices according to the slice classifier in accordance with the FCM method, and determines the wireless resources allocated in each network slice through a probabilistic flexible access method.

[0032] According to a third aspect, a terminal device as described in any one of the first aspects is provided, wherein the terminal device comprises: a second processor, a second memory and a communication interface.

[0033] In a fourth aspect, a computer-readable storage medium is provided, in which a computer program is stored; when the computer program runs on a computer, the computer executes the service classification method under the base station network slice described in any one of claims 1 to 6.

[0034] The beneficial effect of the present invention is that the base station of the present invention can classify user terminals according to the number of network slices, and the user terminals can probabilistically access multiple different network slices according to the actual service type to ensure QoS requirements and improve wireless resource utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the power network slicing application scenario provided for this application;

[0036] Figure 2 Schematic diagram of the type definition of network slices provided for this application;

[0037] Figure 3 A flowchart of a service classification method under a base station network slice provided in this application;

[0038] Figure 4 A flowchart of a fuzzy C-means clustering method provided in this application;

[0039] Figure 5 A schematic diagram of the structure of a base station provided in this application;

[0040] Figure 6 A schematic diagram of the structure of a terminal device provided for this application;

[0041] Explanation of the reference numerals: first processor 501 , first memory 502 , sending interface 503 , slice classifier 504 , second processor 601 , second memory 602 , communication interface 603 . DETAILED DESCRIPTION

[0042] The present invention is further described below in conjunction with embodiments. The description of the following embodiments is only used to help understand the present invention. It should be noted that for ordinary persons in the art, without departing from the principle of the present invention, the present invention can also be modified in some ways, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0043] Embodiment 1:

[0044] Smart grid covers five key links: power generation, transmission, transformation, distribution, and consumption. Dozens of smart grid communication services need to be deployed in each link, and the SLA requirements of each service, such as latency, bandwidth, and security isolation, vary greatly. According to the role of power grid services and the requirements of security isolation, power grid services are divided into two major categories: production control area and management information area. In the production control area, it is divided into security area I and security area II. The security area I service directly realizes real-time monitoring of the power system, and the security area II service only detects but does not control; in the management information area, it is divided into management area III and management area IV / V, which mainly manages power production and internal power grid enterprises, such as video monitoring and information office.

[0045] Figure 1 The schematic diagram of the power network slicing application scenario provided for this application is as follows: Figure 1 As shown in the figure, in the smart grid, the power business can be divided into three types of slices according to the power intelligent service: the first is the power control slice, which can achieve millisecond-level low latency and ensure the reliable transmission of distribution control data and commands; the second is the power monitoring slice, which can realize the collection of massive meter data and the upload of inspection data of smart devices such as drones; the third is the power communication slice, which can meet the security call requirements of the power industry private network. The corresponding business requirements under each network slice are differentiated.

[0046] Embodiment 2:

[0047] Under the division of a given network slice, when a user terminal accesses different network slices, it needs to identify the network slice, so the base station needs to define different types of network slice types. Figure 2The definition of slice types is given. The base station identifies the network slice through the single network slice selection assistance information (Single Network Slice Selection Assistance Information, S-NSSAI) parameter. Figure 2 As shown, an S-NSSAI consists of SST (Slice / Service Type) and SD (Slice Differentiation). In a 5G network, a collection of one or more S-NSSAI is called Network Slice Selection Assistance Information (NSSAI). When a power terminal attaches to the network, the terminal needs to provide S-NSSAI information, and the base station selects the core network based on the S-NSSAI information; if the terminal does not provide relevant S-NSSAI information, the base station routes the terminal's non-access layer information to a default core network link.

[0048] Embodiment 3:

[0049] A service classification method under base station network slicing, the base station divides the wireless resources into network slices, and configures the wireless resources in each network slice according to the service QoS requirements of the terminal device, which can realize the isolation of terminal devices with different QoS services and improve the utilization rate of wireless resources. Figure 3 As shown, including:

[0050] Step 1: The base station collects the service QoS requirements of each terminal device within its coverage area.

[0051] Step 1 is the initialization phase, where the base station collects the service QoS requirements of each terminal device within its coverage area and summarizes the data transmission requirements of the terminal devices.

[0052] Step 2: The base station classifies the terminal devices according to the network slice category to be divided based on the service QoS requirements.

[0053] In step 2, the base station groups the terminal devices according to the service QoS requirements of the terminal devices within the coverage area according to the network slice category to be divided, and makes a one-to-one correspondence between the terminal devices and the network slices, and calculates the probability p of each terminal device accessing each network slice. In order to ensure fairness among users, the sum of the probabilities of each device accessing all network slices of the base station is 1. That is, for any terminal device user m, the probability p of accessing the network slice k on the base station side is m，k Satisfy k p m，k =1.

[0054] Step 3: The base station updates the network slice type and the wireless resource configuration information within the slice according to the fuzzy C means (FCM) method of the terminal device;

[0055] Step 4: The base station broadcasts the type of configured network slice and wireless resource configuration information to the terminal device;

[0056] Step 5: The base station notifies the terminal device of the probability of the terminal device accessing the network slice through a random access process.

[0057] After executing step 5, based on the notification information received by the terminal device, the user can choose which network slices the terminal device should access to receive services.

[0058] In addition, in step 3, the base station determines whether the service QoS requirements of the terminal device are updated in each transmission time interval (Transmission Time Interval, TTI). If the service QoS requirements are not updated, step 4 is executed; if the service QoS requirements are updated, it is determined whether the update cycle of the network slice is reached; if the update cycle of the network slice is reached, the network slice type and the wireless resource configuration information within the slice are updated according to the FCM method; if the update cycle of the network slice is not reached, step 4 is executed.

[0059] like Figure 4 As shown, the FCM method includes:

[0060] Step 3.1, input the service QoS requirements of the terminal device;

[0061] Step 3.2, initialize the basic parameters of terminal allocation, cluster center and slice membership matrix; the basic parameters of terminal allocation include: objective function J(U, c 1 , ..., c c ), the accuracy e of the objective function, the fuzzy index m, the maximum number of iterations LOOP and the number of iterations T;

[0062] Step 3.3, update the slice membership matrix and cluster center;

[0063] Step 3.4: Calculate the objective function J(U, c 1 , ..., c c ); If the objective function J(U, c 1 , ..., c c )satisfy:

[0064] |J(U,c 1 , ..., c c )-J(U+1,c 1 , ..., c c )|≤e

[0065] If the iteration is completed, execute step 3.5; otherwise, increase the number of iterations T by 1, and determine whether the number of iterations T is greater than the maximum number of iterations LOOP. If T>LOOP, the iteration is completed and execute step 3.5; otherwise, jump to step 3.3;

[0066] Step 3.5: Output the cluster center and slice membership matrix. Specifically, according to the obtained probability p of the terminal device accessing each network slice, ij The slice membership matrix is ​​composed of the sample membership matrix, and the class corresponding to the maximum sample membership is taken as the result of sample clustering, and the clustering ends. Furthermore, the base station notifies each terminal device of the probability p of the terminal device accessing all network slices in a point-to-point manner during random access, and the terminal device can access the slice according to the probability of accessing the slice for data transmission.

[0067] In step 3.2, the objective function J(U, c 1 , ..., c c ) is expressed as:

[0068]

[0069] in, c i is the cluster center of network slice i; d ij =||c i -x j || is the Euclidean distance between the i-th cluster center and the j-th data point; m is a weighted index, and m∈1,∞), m is generally taken as 2. In addition, the slice membership matrix consists of the probability p of each network slice ij =0, the number of initial cluster centers is determined by the number of network slices divided by the base station, and any terminal device can be selected as the initial cluster center.

[0070] In step 3.3, the update formula of the slice membership matrix is:

[0071]

[0072] Among them, p ij is the probability of the terminal device accessing each network slice; the update formula of the cluster center is:

[0073]

[0074] In step 3.4, calculate the objective function J(U, c 1 , ..., c c ) is expressed as: And with constraints: The constraint is to ensure fairness among users, that is, the sum of the probabilities of each terminal device accessing all network slices is ∑ k p m，k =1.

[0075] In addition, the technical solution of the present application can be specifically applied to NR communication system, LTE communication system, WCDMA communication system and CDMA2000 communication system, among which NR communication system is a 5G communication system, LTE communication system is a 4G communication system, WCDMA communication system and CDMA2000 communication system are 3G communication systems, and all three communication systems have their corresponding authorized licensed frequency bands.

[0076] In summary, in the service classification method under base station network slicing provided by the present application, first, the base station divides the wireless resources into a limited number of network slices according to the service template of the user terminal, and the service template in each network slice is unified and determined; secondly, the base station flexibly divides the user terminal into different categories according to the user's service needs; finally, the user terminal determines which network slice the terminal belongs to according to the actual service needs. When the actual service needs of the user terminal completely match the network slice needs divided by the base station, the terminal accesses the corresponding network slice to receive the service with probability 1; when the actual service needs of the user terminal cannot completely match the network slice needs divided by the base station, the terminal accesses the corresponding network slice to receive the service with probability p.

[0077] Embodiment 4:

[0078] A base station, such as Figure 5 As shown, the base station includes: a first processor 501 (such as a CPU), a first memory 502, a sending interface 503 and a slice classifier 504, wherein the number of the first processor 501 and the number of the sending interface 503 are both at least one.

[0079] The sending interface 503 may include a display screen (Display), a keyboard (Keyboard), and in addition, the sending interface 503 may also include a standard wired interface and a wireless interface. The memory may include a volatile memory (Volatile Memory), such as a random access memory (Random Access Memory, RAM); the memory may also include a non-volatile memory (Non-Volatile Memory), such as a read-only memory (Read-Only Memory, ROM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, HDD) or a solid-state drive (Solid-State Drive, SSD); the first memory 502 may also include a combination of the above-mentioned types of memory. The first memory 502 may also be at least one storage device located away from the aforementioned first processor 501. A set of program codes are stored in the first memory 502, and the first processor 501 calls the program code stored in the first memory 502 to perform the following operations:

[0080] Obtain the classification of network slices, where the slice classification is determined by the base station. The base station selects and assembles the corresponding slice instance through NSSAI, and broadcasts it to the target user terminal device through S-NSSAI.

[0081] Furthermore, the S-NSSAI includes a slice service type SST and a slice distinguishing symbol SD. Since SST has a maximum of 8 bits, the standard value of the slice service type SST is 0-127. However, in fact, considering the management of network slicing and the classification of actual services, the current 5G network generally divides services into three categories with large bandwidth: enhanced mobile broadband services (eMBB), ultra-high reliability and low-latency communications.

[0082] Further, the first processor 501 is further configured to perform the following operations:

[0083] According to the slice classifier, user terminals are flexibly grouped for access according to a user clustering algorithm, and the wireless resources allocated within each network slice are determined through a probabilistic flexible access method.

[0084] In an embodiment of the present invention, the base station obtains the average network resources in each network slice group through a slice classifier, and can evaluate the required quantity of wireless resources in the network slice resources, thereby accurately dividing the wireless network resources for each network slice.

[0085] Embodiment 5:

[0086] A terminal device, such as Figure 6As shown, the terminal device includes: a second processor 601, a second memory 602 and a communication interface 603. The number of the second processor 601 and the communication interface 603 is at least one. The second processor 601 can be a CPU, and the communication interface 603 can include a display screen (Display), a keyboard (Keyboard), and the communication interface 603 can also include a standard wired interface and a wireless interface. The second memory 602 can include a volatile memory (Volatile Memory), such as a random access memory (Random Access Memory, RAM); the memory can also include a non-volatile memory (Non-Volatile Memory), such as a read-only memory (Read-Only Memory, ROM), a flash memory (FlashMemory), a hard disk (Hard Disk Drive, HDD) or a solid-state drive (Solid-State Drive, SSD); the second memory 602 can also include a combination of the above-mentioned types of memory. The second memory 602 can also be at least one storage device located away from the aforementioned second processor 601. A group of program codes are stored in the second memory 602, and the second processor 601 calls the program codes stored in the memory 602 to receive broadcast messages from the base station and obtain the access probability corresponding to each network slice.

[0087] The second processor 601 is further configured to perform the following operations:

[0088] According to the service changes of the user terminal, the changes in service types are reported to the base station through the communication interface 603 so that the base station can adjust the network slice and the wireless resource configuration within the slice in time.

[0089] The second processor 601 is further configured to perform the following operations:

[0090] Obtain the wireless resource configuration information of each network slice to determine whether the wireless resources corresponding to the wireless network slice can support the QoS requirements of the user terminal device.

[0091] In an embodiment of the present application, the user diagnostic device obtains the probability of accessing each network slice by receiving the broadcast message of the base station, and determines the network slice to be accessed on the base station side.

[0092] Embodiment 6:

[0093] A computer-readable storage medium, in which a computer program is stored; when the computer program runs on a computer, the computer executes the service classification method under the base station network slice provided in the present application.

[0094] The computer program realizes the present invention when executed by a processor Figure 3 to Figure 4 The implementation described in any of the embodiments can also implement the present invention. Figure 5 The described base station implementation or Figure 6 The implementation method of the user equipment described in the embodiment will not be repeated here.

[0095] The computer-readable storage medium may be an internal storage unit of the terminal described in any of the foregoing embodiments, such as a hard disk or memory of the terminal. The computer-readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit of the terminal and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0096] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0097] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

Claims

1. A service classification method under base station network slicing, characterized in that: include: Step 1: The base station collects the service QoS requirements of each terminal device within its coverage area; Step 2: The base station classifies the terminal devices according to the service QoS requirements and the network slice categories to be divided; Step 3, the base station updates the network slice type and the wireless resource configuration information in the slice according to the fuzzy C-means clustering method of the terminal device; in step 3, the base station determines whether the service QoS demand of the terminal device is updated in each transmission time interval, if the service QoS demand is not updated, step 4 is executed, if the service QoS demand is updated, it is determined whether the update cycle of the network slice is reached; if the update cycle of the network slice is reached, the network slice type and the wireless resource configuration information in the slice are updated according to the fuzzy C-means clustering method, if the update cycle of the network slice is not reached, step 4 is executed; In step 3, the fuzzy C-means clustering method includes: Step 3.1, input the service QoS requirements of the terminal device; Step 3.2, initialize the basic parameters of terminal allocation, cluster center and slice membership matrix; the basic parameters of terminal allocation include: objective function J(U,c1,...,c c ), the accuracy e of the objective function, the fuzzy index m, the maximum number of iterations LOOP and the number of iterations T; Step 3.3, update the slice membership matrix and cluster center; Step 3.4, calculate the objective function J(U,c1,...,c c ); if the objective function J(U,c1,...,c c )satisfy: |J(U,c1,...,c c )-J(U+1,c1,...,c c )|≤e If so, the iteration ends and step 3.5 is executed; otherwise, the number of iterations T is increased by 1, and it is determined whether the number of iterations T is greater than the maximum number of iterations LOOP. If T>LOOP, the iteration ends and step 3.5 is executed; otherwise, the execution jumps to step 3.3; Step 3.5, output the cluster center and slice membership matrix; Step 4: The base station broadcasts the type of configured network slice and wireless resource configuration information to the terminal device; Step 5: The base station notifies the terminal device of the probability of the terminal device accessing the network slice through a random access process.

2. The service classification method under base station network slicing according to claim 1 is characterized in that: In step 3.2, the objective function J(U,c1,...,c c ) is expressed as: in, c i is the cluster center of network slice i; d ij =‖c i -x j ‖ is the Euclidean distance between the i-th cluster center and the j-th data point; m is the weighted exponent, and m∈1,∞).

3. The service classification method under base station network slicing according to claim 1 is characterized in that: In step 3.3, the update formula of the slice membership matrix is: Among them, p ij is the probability of the terminal device accessing each network slice; the update formula of the cluster center is:

4. The service classification method under base station network slicing according to claim 1 is characterized in that: In step 3.4, calculate the objective function J(U,c1,...,c c ) is expressed as: And with constraints:

5. A base station for executing the method according to any one of claims 1 to 4, characterized in that: The base station comprises: a first processor (501), a first memory (502), a sending interface (503) and a slice classifier (504).

6. The base station according to claim 5, characterized in that The first processor (501) performs flexible access grouping on the terminal devices according to the slice classifier (504) in accordance with the fuzzy C-means clustering method, and determines the wireless resources allocated within each network slice through a probabilistic flexible access method.

7. A terminal device for executing the method according to any one of claims 1 to 4, characterized in that: The terminal device comprises: a second processor (601), a second memory (602) and a communication interface (603).

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program; when the computer program runs on a computer, the computer executes the service classification method under the base station network slice described in any one of claims 1 to 4.

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