Method and apparatus for determining handover target

Abstract

To provide a handover target determination method and device that improve shortcomings and performance.SOLUTION: A handover target determination method includes the steps of: receiving a measurement report sent by user equipment; obtaining a handover priority list according to the measurement report; instructing the user equipment to perform a handover procedure according to the handover priority list and obtaining a handover result; obtaining handover parameters according to the handover result; and training a handover model according to the measurement report, the handover parameters, and neighbor information, and updating the handover priority list.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a method and apparatus for determining a handover target, and more particularly to a method and apparatus for determining a handover target using machine learning and artificial intelligence (AI). [Background technology]

[0002] Network densification through the deployment of base stations has become a viable solution for mobile operators to address the growing demand for higher capacity. It is also expected that mobile operators will meet a large part of the ambitious fifth generation (5G) demand through network densification. Network densification can be achieved by deploying different types of base stations (e.g. macro, micro, pico, and femto base stations) depending on the trade-off between performance, time, and cost. Deploying more base stations reduces the coverage area of ​​each base station, thereby improving spatial spectrum utilization and network capacity.

[0003] Handover refers to the process by which a mobile device moves from the coverage area of ​​one base station to the coverage area of ​​another base station during a call, or hands over to another transmission channel due to external interference. The handover process is described in detail in 3GPP TS 38.300 (version 17.0.0), chapter 9.2.3.2 "Handover".

[0004] However, network densification and the integration of various wireless communication products and frequency bands significantly increase the complexity of handover. In dense 5G cellular networks, handover delays may eliminate or even negate the advantages provided by network densification. Therefore, there is a need for a method and apparatus for determining a handover target that improves the above-mentioned shortcomings and improves performance. Summary of the Invention [Problem to be solved by the invention]

[0005] A method and apparatus for determining a handover target that overcomes the drawbacks and improves performance. [Means for solving the problem]

[0006] The following summary is illustrative only and is not intended to be in any way limiting. That is, the following summary is provided to introduce concepts, highlights, benefits, and advantages of the novel and non-obvious technology described herein. Selected embodiments, but not all, are described in the Detailed Description below. Thus, the following summary is not intended to identify essential features of the claimed invention, nor is it intended for use in determining the scope of the claimed invention.

[0007] Therefore, the main objective of the present disclosure is to provide a method and apparatus for determining a handover target that overcomes and improves the shortcomings and improves performance.

[0008] The present disclosure proposes a method for determining a handover target, the method including the steps of receiving a measurement report sent by a user equipment, obtaining a handover priority list according to the said measurement report, instructing the said user equipment to perform a handover procedure according to the said handover priority list and obtaining a handover result, obtaining handover parameters according to the said handover result, and training a handover model according to the said measurement report, the said handover parameters and neighborhood information, and updating the said handover priority list.

[0009] In some embodiments, the measurement report includes signal criteria, wherein the measurement report includes signal criteria, wherein the signal criteria includes at least a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), a reference signal received power (RSRP), a sidelink channel occupancy rate, and a sidelink channel busy rate.

[0010] In some embodiments, the handover parameters mentioned above include at least handover attempted, handover successful, handover cancelled, and network cause.

[0011] In some embodiments, the above-mentioned neighborhood information is transmitted by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, a time, and a cell capacity.

[0012] In some embodiments, the handover model described above is based on a Recurrent Neural Network (RNN) model or a Deep Recurrent Neural Network (DRNN) model.

[0013] The present disclosure proposes a method for determining a handover target, used in an apparatus, the method including: training a handover model according to handover data; when receiving a measurement report sent by a user equipment, generating a handover priority list using the above-mentioned handover model according to the above-mentioned measurement report and neighborhood information; instructing the above-mentioned user equipment to perform a handover procedure according to the above-mentioned handover priority list, and obtaining a handover result; obtaining handover parameters according to the above-mentioned handover result; and updating the above-mentioned handover priority list using the above-mentioned handover model according to the above-mentioned measurement report, the above-mentioned neighborhood information, and the above-mentioned handover parameters.

[0014] The present disclosure proposes an apparatus for determining a handover target, including one or more processors and one or more computer storage media storing computer-readable instructions, where the said processor uses the said computer storage medium to perform the steps of receiving a measurement report sent by a user equipment, obtaining a handover priority list according to the said measurement report, instructing the said user equipment to perform a handover procedure according to the said handover priority list and obtaining a handover result, obtaining handover parameters according to the said handover result, and training a handover model according to the said measurement report, the said handover parameters, and neighborhood information, and updating the said handover priority list.

[0015] The present disclosure proposes an apparatus for determining a handover target, comprising: one or more processors; and one or more computer storage media storing computer-readable instructions, wherein the above-mentioned processor performs, using the above-mentioned computer storage media, the steps of: training a handover model according to handover data; when receiving a measurement report sent by a user equipment, generating a handover priority list using the above-mentioned handover model according to the above-mentioned measurement report and neighborhood information; instructing the above-mentioned user equipment to perform a handover procedure according to the above-mentioned handover priority list, and obtaining a handover result; obtaining handover parameters according to the above-mentioned handover result; and updating the above-mentioned handover priority list using the above-mentioned handover model according to the above-mentioned measurement report, the above-mentioned neighborhood information, and the above-mentioned handover parameters. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic diagram illustrating a wireless network according to one embodiment of the present disclosure. [Diagram 2] FIG. 2 shows a schematic diagram of training a handover model according to a first embodiment of the present disclosure. [Figure 3A] FIG. 13 shows a schematic diagram of training a handover model according to a second embodiment of the present disclosure; [Figure 3B] FIG. 13 shows a schematic diagram of training a handover model according to a second embodiment of the present disclosure; [Figure 4] 1 is a flowchart illustrating a method for determining a handover target according to an embodiment of the present disclosure. [Diagram 5] 1 is a flowchart illustrating a method for determining a handover target according to an embodiment of the present disclosure. [Figure 6] 1 illustrates an exemplary operating environment for implementing embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] The embodiments of the present disclosure provide a method and apparatus for determining a handover target, and can introduce artificial intelligence and machine learning to achieve the goal of quickly processing handover operations.

[0018] FIG. 1 is a schematic diagram illustrating a wireless network 100 (e.g., a New Radio (NR) or 5G network) according to one embodiment of the present disclosure.

[0019] As shown in FIG. 1, the wireless network 100 may include several Base Stations (BS) 110a-110e and a core network 120. The BSs 110a-110e may be stations that communicate with User Equipment (UE). Each BS 110a-110e may provide communication coverage to a particular geographic area. In 3GPP, the term "cell" may refer to serving a coverage area of ​​a Node B and / or a coverage area of ​​a subsystem of a Node B depending on the context in which the term is used. In an NR system, the terms "cell" and eNB, Node B, 5G NB, AP, NR BS, NR BS, gNB, Radio Access Network (RAN), or Transmission and Reception Point (TRP) may be interchangeable. In some examples, a cell is not necessarily stationary and the geographic area of ​​a cell may move depending on the location of a mobile base station. In some examples, the base stations may be interconnected within wireless network 100 and / or to one or more other base stations or network nodes (not shown) via various types of backhaul interfaces (e.g., using direct physical connections, virtual networks, or any applicable transmission network).

[0020] In general, any number of wireless networks may be deployed in a given geographic area. Each wireless network may support a particular radio access technology (RAT) and may operate at one or more frequencies. The RAT may also be referred to as a radio technology, an air interface, etc. The frequencies may also be referred to as a carrier, a frequency channel, etc. Each frequency may support a single RAT within a given geographic area and may avoid interference between wireless networks of different RATs. In some cases, NR or 5G RAT networks may be deployed employing a multi-slice network architecture.

[0021] The BSs 110a-110e may provide communication coverage for macro cells, pico cells, and / or other types of cells. The macro cells may cover a relatively large geographic area (e.g., a radius of several kilometers) and may allow unrestricted access for UEs with service subscriptions. The pico cells may cover a relatively small geographic area and may allow unrestricted access for UEs with service subscriptions. In the example shown in FIG. 1, the BS 110a may be a macro BS for the macro cell 112a. The BSs 110b, 110c may be pico BSs for the pico cells 112b, 112c. Also, the BS 110d may be an access point (AP) using a Wi-Fi protocol, and the BS 110e may be a device supporting an unlicensed band defined in 3GPP TR 38.889.

[0022] The core network 120 may be a public data network, such as the Internet, a private data network, or a combination thereof.

[0023] The UEs 130 may be distributed throughout the wireless network 100, and each UE may be stationary or mobile. The UEs 130 may be feature phones, smartphones, tablet personal computers (PCs), notebook computers, machine type communications (MTCs), or any wireless communication device that supports the radio access technology used in the core network 120 and the wireless network 100.

[0024] The handover device 150 is for determining a handover target for the UE 130 and can be realized as a network element on dedicated hardware, or as a software instance running on dedicated hardware, or as a virtual function instantiated on a suitable platform (e.g., a base station, a RAN device, cloud infrastructure).

[0025] It should be understood that when the handover device 150 is used as dedicated hardware, it can be realized via any type of electronic device, such as the electronic device 700 described with reference to FIG. 7, as shown in FIG.

[0026] FIG. 2 is a schematic diagram showing a process of training a handover model according to the first embodiment of the present disclosure, where the handover model can be realized by a processor of a handover device.

[0027] It should be noted that the measurement reports, measurement report implementations, and message parameters compiled from the measurement results used in the following examples are defined in 3GPP TS 38.331, and the message parameters may include SINR, RSRP, RSRQ, RSSI, averageDelay, and other parameters.

[0028] When the handover device receives a measurement report sent by the UE (S201), the handover device can store the measurement report and generate a handover priority list 200 according to the measurement report (S202). As shown in the figure, the handover priority list 200 at least includes a cell identifier (ID) and a cell type, a reference signal received power (RSRP), a reference signal received quality (RSRQ), a signal-to-interference-and-noise ratio (SINR), and a priority.

[0029] Then, the handover device can determine a handover target according to the handover priority list 200 and instruct the UE to perform a handover procedure (S203). As shown in the figure, the first priority handover target in the handover priority list 200 is cell 10. The UE performs a handover procedure to hand over to cell 10.

[0030] After the handover procedure is completed, the handover device obtains the handover result, obtains handover parameters according to the handover result, and inputs the handover parameters into a handover model (S204), where the above-mentioned handover parameters include at least parameters of handover attempt, handover success, handover cancellation, network cause, etc. In one embodiment, the above-mentioned handover model is based on a recurrent neural network (RNN) model or a deep recurrent neural network (DRNN) model.

[0031] The handover device can obtain signal criteria according to the measurement report (S205), where the above-mentioned signal criteria at least include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), a reference signal received power (RSRP), a sidelink channel occupancy rate, and a sidelink channel busy rate.

[0032] In this schematic diagram, the handover device can continuously receive neighborhood information transmitted by a base station or a core network (S206), where the neighborhood information includes at least General Packet Radio Service (GPRS), cell type, time, and cell capacity.

[0033] The handover device trains a handover model according to the signal criteria of the above-mentioned measurement report, the above-mentioned handover parameters and neighbor information, and updates the handover priority list 200 (S207). The handover device determines whether the user equipment needs to perform a handover procedure according to the updated handover priority list 200.

[0034] More specifically, before the handover model is updated and the handover priority list 200 is output, the handover device first generates the handover priority list 200 according to the measurement report of S202. After the handover model is updated and the handover priority list 200 is output, the handover device repeatedly executes steps S203-S207. In other words, the handover device can achieve the purpose of training and calibrating the handover model in real time and updating the handover priority list 200 in real time.

[0035] 3A-3B show a schematic diagram of training a handover model according to a second embodiment of the present disclosure, where the above-mentioned handover model can be realized by a processor of a handover device.

[0036] In Fig. 3A, the handover device first trains a handover model according to handover data, and the above-mentioned handover data is relevant historical data after the user equipment executes a handover procedure. In one embodiment, the above-mentioned handover model is based on a recurrent neural network (RNN) model or a deep recurrent neural network (DRNN) model.

[0037] In FIG. 3B, when the handover device receives a measurement report sent by the UE (S301), the handover device can store the measurement report and obtain signal criteria according to the measurement report (S302), where the above-mentioned signal criteria at least include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), a reference signal received power (RSRP), a sidelink channel occupancy rate, and a sidelink channel busy rate.

[0038] In this schematic diagram, the handover device can continuously receive neighborhood information transmitted by a base station or a core network (S303), where the neighborhood information includes at least General Packet Radio Service (GPRS), cell type, time, and cell capacity.

[0039] Then, the handover device populates a handover model according to the signal criteria and the neighborhood information in the above-mentioned measurement report. The handover model generates a handover priority list according to the signal criteria and the neighborhood information (S304). In one embodiment, the handover priority list includes at least a cell identifier (ID) and a cell type, a reference signal received power (RSRP), a reference signal received quality (RSRQ), a signal-to-interference-and-noise ratio (SINR), and a priority.

[0040] The handover device can determine a handover target according to the handover priority list, and instruct the UE to perform a handover procedure (S305).

[0041] After the handover procedure is completed, the handover device obtains the handover result, obtains handover parameters according to the handover result, and inputs the handover parameters into the handover model (S306), where the above-mentioned handover parameters include at least parameters such as handover attempt, handover success, handover cancellation, network cause, etc.

[0042] After the handover parameters are input into the handover model, the handover model updates the above-mentioned handover priority list according to the signal criteria, neighbor information and handover parameters in the measurement report.

[0043] More specifically, before the handover model has not output the handover priority list 200, the handover device first generates the handover priority list according to the signal criterion obtained in step S302 and the neighbor information obtained in step S303. After the handover model outputs the handover priority list, the handover device repeatedly executes steps S302-S306. In other words, except for the first handover model that generates the handover priority list based on the signal criterion and the neighbor information, the handover model then updates the handover priority list based on the signal criterion, the neighbor information, and the handover parameters. In the second embodiment, the handover model may not be calibrated in real time, but the purpose of updating the handover priority list in real time can still be achieved.

[0044] 4 is a flowchart 400 illustrating a method for determining a handover target according to an embodiment of the present disclosure. The flowchart 400 corresponds to the first embodiment of FIG. 2 and can be executed by the handover device 150 of FIG.

[0045] In step S405, the handover device receives a measurement report transmitted by a user equipment, wherein the said measurement report includes a signal criterion, wherein the said signal criterion includes at least a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), a reference signal received power (RSRP), a sidelink channel occupancy rate, and a sidelink channel busy rate.

[0046] In step S410, the handover device obtains a handover priority list according to the above-mentioned measurement report, where the above-mentioned handover priority list at least includes a cell identifier (ID) and a cell type, a reference signal received power (RSRP), a reference signal received quality (RSRQ), a signal-to-interference-and-noise ratio (SINR), and a priority.

[0047] In step S415, the handover device instructs the abovementioned user equipment to perform a handover procedure according to the abovementioned handover priority list, and obtains a handover result.

[0048] In step S420, the handover device obtains handover parameters according to the abovementioned handover results, where the abovementioned handover parameters include at least handover attempt, handover success, handover cancellation and network cause.

[0049] In step S425, the handover device trains the above-mentioned handover model according to the above-mentioned measurement report, the above-mentioned handover parameters, and the neighborhood information, and updates the above-mentioned handover priority list, where the above-mentioned neighborhood information is sent by the base station or the core network and includes at least General Packet Radio Service (GPRS), cell type, time, and cell capacity.

[0050] The handover device then repeats steps S415, S420, and S425 to continuously train the handover model and update the handover priority list.

[0051] 5 is a flowchart 500 illustrating a method for determining a handover target according to an embodiment of the present disclosure. The flowchart 500 corresponds to the second embodiment of FIGS. 3A-3B and can be executed by the handover device 150 of FIG. 1.

[0052] In step 505, the handover device trains a handover model according to the handover data, where the above-mentioned handover data is relevant historical data after the user equipment performs a handover procedure.

[0053] In step S510, when the handover device receives the measurement report sent by the user equipment, the handover device generates a handover priority list using the above-mentioned handover model according to the above-mentioned measurement report and neighborhood information, where the above-mentioned handover priority list at least includes a cell identifier (ID) and a cell type, a Reference Signal Received Power (RSRP), a Reference Signal Received Quality (RSRQ), a Signal-to-Interference-and-Noise Ratio (SINR), and a priority, and the above-mentioned neighborhood information is sent by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, a time, and a cell capacity.

[0054] In one embodiment, the handover device outputs a handover priority list using the above-mentioned handover model according to signal criteria and neighbor information included in the measurement report, where the above-mentioned signal criteria include at least a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), a reference signal received power (RSRP), a sidelink channel occupancy rate, and a sidelink channel busy rate.

[0055] In step S515, the handover device instructs the above-mentioned user equipment to perform a handover procedure according to the above-mentioned handover priority list, and obtains a handover result.

[0056] In step S520, the handover device obtains handover parameters according to the abovementioned handover results, where the abovementioned handover parameters include at least handover attempt, handover success, handover cancellation and network cause.

[0057] In step S525, the handover device updates the above-mentioned handover priority list using the above-mentioned handover model according to the above-mentioned measurement report, the above-mentioned neighborhood information, and the above-mentioned handover parameters.

[0058] Then, the handover device repeats steps S515, S520, and S525 to continuously update the handover priority list.

[0059] As described above, the method and apparatus for determining a handover target of the present disclosure trains a handover model, generates a handover priority list, and determines a handover target according to the handover priority list. The handover model can process a large amount of calculation and achieve the purpose of quickly determining a handover target.

[0060] With the previously described embodiments of the present invention, the following describes an exemplary operating environment in which embodiments of the present invention may be implemented. As shown specifically in FIG. 6, FIG. 6 illustrates an exemplary operating environment for implementing embodiments of the present invention, generally referred to as electronic device 600. Electronic device 600 is only one example of a suitable computing environment and is not intended to limit the scope of use or functionality of the present invention. Neither electronic device 600 should be interpreted as having any dependency or requirement relating to any one or combination of illustrated elements.

[0061] As shown in Fig. 6, the electronic device 600 includes a bus 610 that is directly or indirectly coupled to one or more memories 612, one or more processors 614, one or more display elements 616, one or more input / output (I / O) ports 618, one or more I / O components 620, and an illustrative power source 622. The bus 610 may represent one or more types of buses (e.g., an address bus, a data bus, or any combination thereof). The various blocks in Fig. 6 are shown with lines for clarity, but in reality the boundaries between the various elements are not specific. For example, a display element of a display device may be considered an I / O component, and a processor may include a memory.

[0062] Electronic device 600 typically includes a variety of computer readable media. Computer readable media is any available media that can be accessed by electronic device 600, and the media includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media includes computer storage media and communication media. Computer readable media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information, such as computer readable instructions, data structures, program modules, or other data. The computer storage media includes, but is not limited to, random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium used to store the desired information and which can be accessed by electronic device 600. The computer storage media itself does not carry signals.

[0063] Communication media typically includes computer readable instructions, data structures, program modules, or data in a modularized data signal employing, for example, a carrier wave or other transport mechanism, and includes any information transmission media. The term "modularized data signal" means a signal that has one or more features or changes in some manner that encodes information in the signal. By way of example, and not limitation, communication media includes wired media, such as a wired network or direct-wired connection, and wireless media, such as acoustic, RF, infrared and other wireless media, or any combination thereof.

[0064] The memory 612 includes computer storage media in the form of volatile and non-volatile memory. The memory may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical disk drives, etc. The electronic device 600 includes one or more processors and may read data for each entity, for example, from the memory 612 or from the I / O components 620. The display element 616 displays an indication of the data to a user or another device. Exemplary display components include a display device, a speaker, a printing element, a vibrating element, etc.

[0065] The I / O port 618 allows the electronic device 600 to be logically coupled to other devices having I / O components 620, some of which are built-in devices. Illustrative components include microphones, joysticks, gamepads, satellite dishes, scanners, printers, wireless devices, etc. The I / O components 620 provide a natural user interface (NUI) that processes gestures, voice, or other physiological inputs generated by a user. In an example, these inputs are sent to an appropriate network element for further processing. The electronic device 600 includes a depth camera, e.g., a stereo camera system, an infrared camera system, an RGB camera system, or any combination thereof, to achieve detection and identification. In addition, the electronic device 600 includes sensors (e.g., radar, light sensors) that periodically sense the nearby environment within the surrounding sensor range and display sensory information related to itself and the surrounding environment. Additionally, the electronic device 600 includes an accelerometer or gyroscope that allows for motion detection. The output of the accelerometer, or gyroscope, is provided to a display of the electronic device 600 for display.

[0066] Further, the processor 614 in the electronic device 600 can execute the programs and instructions in the memory 612 to perform the operations and steps described above, or otherwise, as described herein. [Explanation of symbols]

[0067] 100 Wireless Network 110a~110e Base station 112a Macrocell 112b, 112c Picocell 120 Core Network 130 User Equipment 150 Handover Equipment S201, S202, S203, S204, S205, S206, S207 steps 200 Handover Priority List S301, S302, S303, S304, S305, S306 steps 400 Flowchart S405, S410, S415, S420, S425 Step 500 Flowchart S505, S510, S515, S520, S525 Step 600 Electronic equipment 610 Bus 612 Memory 614 processor 616 Display elements 618 Input / Output (I / O) Ports 620 Input / Output Components 622 Power supply

Claims

1. 1. A method for determining a handover target, comprising: receiving a measurement report sent by a user equipment; obtaining a handover priority list according to the measurement report; instructing the user equipment to perform a handover procedure according to the handover priority list, and obtaining a handover result; obtaining handover parameters according to a result of the handover; and training a handover model according to the measurement report, the handover parameters, and neighbor information, and updating the handover priority list; The measurement report includes a signal criterion, the signal criterion including at least a sidelink channel occupancy rate and a sidelink channel busy rate.

2. The method of claim 1, wherein the signal criteria further include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), and a reference signal received power (RSRP).

3. The method of claim 1 , wherein the handover parameters include at least handover attempt, handover success, and network cause.

4. The method of claim 1 , wherein the neighborhood information is transmitted by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, and a cell capacity.

5. The method of claim 1 , wherein the handover model is based on a Recurrent Neural Network (RNN) model or a Deep Recurrent Neural Network (DRNN) model.

6. A method for determining a handover target for use in an apparatus, comprising: training a handover model according to the handover data; when receiving a measurement report sent by a user equipment, generating a handover priority list using the handover model according to the measurement report and neighbor information; instructing the user equipment to perform a handover procedure according to the handover priority list, and obtaining a handover result; obtaining handover parameters according to a result of the handover; and updating the handover priority list using the handover model according to the measurement reports, the neighborhood information, and the handover parameters; The measurement report includes a signal criterion, the signal criterion including at least a sidelink channel occupancy rate and a sidelink channel busy rate.

7. The method of claim 6, wherein the signal criteria further include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), and a reference signal received power (RSRP).

8. The method of claim 6, wherein the handover parameters include at least handover attempt, handover success, and network cause.

9. The method of claim 6, wherein the neighborhood information is transmitted by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, and a cell capacity.

10. The method of claim 6 , wherein the handover model is based on a Recurrent Neural Network (RNN) model or a Deep Recurrent Neural Network (DRNN) model.

11. An apparatus for determining a handover target, comprising: one or more processors; and one or more computer storage media storing computer readable instructions, the processor using the computer storage media to: receiving a measurement report sent by a user equipment; obtaining a handover priority list according to the measurement report; instructing the user equipment to perform a handover procedure according to the handover priority list, and obtaining a handover result; obtaining handover parameters according to a result of the handover; and Perform the steps of training a handover model according to the measurement report, the handover parameters, and neighbor information, and updating the handover priority list; The measurement report includes a signal criterion, the signal criterion including at least a sidelink channel occupancy rate and a sidelink channel busy rate.

12. The apparatus of claim 11, wherein the signal criteria further include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), and a reference signal received power (RSRP).

13. The apparatus of claim 11 , wherein the handover parameters include at least handover attempt, handover success, and network cause.

14. 12. The apparatus of claim 11, wherein the neighborhood information is transmitted by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, and a cell capacity.

15. The apparatus of claim 11 , wherein the handover model is based on a Recurrent Neural Network (RNN) model or a Deep Recurrent Neural Network (DRNN) model.

16. An apparatus for determining a handover target, comprising: one or more processors; and one or more computer storage media storing computer readable instructions, the processor using the computer storage media to: training a handover model according to the handover data; when receiving a measurement report sent by a user equipment, generating a handover priority list using the handover model according to the measurement report and neighbor information; instructing the user equipment to perform a handover procedure according to the handover priority list, and obtaining a handover result; obtaining handover parameters according to a result of the handover; and performing a step of updating the handover priority list using the handover model according to the measurement report, the neighborhood information and the handover parameters; The measurement report includes a signal criterion, the signal criterion including at least a sidelink channel occupancy rate and a sidelink channel busy rate.

17. The apparatus of claim 16, wherein the signal criteria further include a user equipment address, a signal-to-interference-and-noise ratio (SINR), a received signal strength indicator (RSSI), and a reference signal received power (RSRP).

18. 17. The apparatus of claim 16, wherein the handover parameters include at least handover attempt, handover success, and network cause.

19. 17. The apparatus of claim 16, wherein the neighborhood information is transmitted by a base station or a core network and includes at least a General Packet Radio Service (GPRS), a cell type, and a cell capacity.

20. The apparatus of claim 16 , wherein the handover model is based on a Recurrent Neural Network (RNN) model or a Deep Recurrent Neural Network (DRNN) model.

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