Cell selection method and device

Abstract

The invention provides a cell selection method and device, and relates to the field of communication. The method and the device are used for realizing that the terminal equipment automatically determines a stay point and more accurately selects a cell with better communication quality. The method comprises the steps that the terminal equipment determines a core point according to historical track data; the terminal equipment determines a stay point according to the core point; the terminal device obtains communication experience information corresponding to the stay point and the target time, wherein the communication experience information comprises service quality information and network quality information; and the terminal equipment determines a target cell according to the communication experience information, wherein the target cell is a cell with optimal service quality and network quality when the terminal equipment communicates at the stay point and the target time.

Description

Technical Field

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

[0002] In mobile communication network services, in order to improve the user experience, it is necessary to select the most suitable cell to provide services according to the location and scenario of the user's terminal device. For example, the mobile network can perform cell switching, cell reselection, and cell camping operations on the user's terminal device.

[0003] According to the mobile communication protocol, in the current cell selection scheme, the terminal device can first report the measured cell quality information to the network side device. After receiving the cell quality signal, the network side device determines whether to switch the cell based on the signal quality of the cell currently connected to the terminal device and the cell quality signals of other cells; if switching is required, determine the cell to be reconnected after the switch.

[0004] In existing cell selection schemes, the cell quality information measured by the terminal equipment is neither accurate nor complete. Summary of the invention

[0005] The embodiments of the present application provide a cell selection method and device, which can enable a terminal device to automatically determine a stay point and more accurately select a cell with better communication quality.

[0006] In a first aspect, an embodiment of the present application provides a cell selection method, the method comprising: a terminal device determines a core point based on historical trajectory data; the terminal device determines a stay point based on the core point; the terminal device obtains communication experience information corresponding to the stay point and the target time, the communication experience information including service quality information and network quality information; the terminal device determines a target cell based on the communication experience information, the target cell being a cell with the best service quality and network quality when the terminal device communicates at the stay point and the target time.

[0007] In this possible implementation, the terminal device automatically determines the core points and stay points based on the historical trajectory data, and determines the cell with the best communication quality for communication based on the communication experience information. The terminal device automatically determines the core points and stay points without manual intervention. At the same time, the target cell can be determined based on the historical experience information, and the reliability of selecting a cell with good communication quality is higher.

[0008] In a possible implementation, the terminal device determines the core point according to the historical trajectory data, including: the terminal device constructs a trajectory data set according to the historical trajectory data, the trajectory data set is a Kd two-dimensional tree data structure; the terminal device determines the core point according to the trajectory data set by using a K nearest neighbor algorithm.

[0009] In a possible implementation, the terminal device determines the core point according to the trajectory data set, including: the terminal device determines the spatiotemporal local density of each trajectory data point in the trajectory data set and the product of the spatiotemporal local density and the relative distance through a K-nearest neighbor algorithm; the terminal device determines the core point according to the spatiotemporal local density of each trajectory data point and the product of the spatiotemporal local density and the relative distance.

[0010] In the embodiment of the present application, the K nearest neighbor algorithm is used to replace the Gaussian kernel function density peak clustering algorithm. The Gaussian kernel function density peak clustering algorithm needs to manually set the cutoff distance to calculate the local density. The terminal device in the embodiment of the present application automatically selects the cutoff distance to replace the manual setting to perform local density calculation. Thus, the terminal device automatically determines the core point and the stop point without manual participation.

[0011] In a possible implementation manner, the terminal device determines the stay point according to the core point, including: the terminal device determines the stay point according to the core point and an average point of points around the core point.

[0012] In one possible implementation, the terminal device obtains communication experience information corresponding to the stop point and the target time, including: the terminal device sends an acquisition request to the cloud side device, the acquisition request instructs the cloud test device to send communication experience information to the terminal device; the terminal device receives the communication experience information corresponding to the stop point from the cloud side device.

[0013] In a possible implementation, before the terminal device determines the stay point based on the historical trajectory data, the method also includes: the terminal device normalizes the historical trajectory data; the terminal device determines the stay point based on the historical trajectory data, including: the terminal device determines the stay point based on the normalized historical trajectory data.

[0014] In one possible implementation, before the terminal device determines the target cell based on the communication experience information, the method also includes: the terminal device determines a cell selection strategy based on the communication experience information, the cell selection strategy instructs the terminal device to select the target cell based on the stay point and target time and the communication experience information; the terminal device determines the target cell based on the communication experience information, including: the terminal device determines the target cell based on the cell selection strategy, the target cell being the cell with the best service quality and network quality when the terminal device communicates at the stay point and target time.

[0015] In the second aspect, an embodiment of the present application provides a terminal device, which includes: a first determination module, used to determine a core point based on historical trajectory data; a second determination module, used to determine a stay point based on the core point; an acquisition module, used to obtain communication experience information corresponding to the stay point and the target time, the communication experience information including service quality information and network quality information; a third determination module, used to determine a target cell based on the communication experience information, the target cell being a cell with optimal service quality and network quality when the terminal device communicates at the stay point and the target time.

[0016] In a possible implementation, the first determination module includes: a first determination unit, configured to construct a trajectory data set according to historical trajectory data, wherein the trajectory data set is a Kd two-dimensional tree data structure; and a second determination unit, configured to determine a core point according to the trajectory data set by using a K nearest neighbor algorithm.

[0017] In a possible implementation, the second determination unit includes: a first determination subunit, used to determine the spatiotemporal local density of each trajectory data point in the trajectory data set and the product of the spatiotemporal local density and the relative distance by a K-nearest neighbor algorithm; and a second determination subunit, used to determine the core point according to the spatiotemporal local density of each trajectory data point and the product of the spatiotemporal local density and the relative distance.

[0018] In a possible implementation manner, the second determination module is specifically configured to determine the stay point according to the core point and an average point of points around the core point.

[0019] In a possible implementation, the acquisition module includes: a sending unit, used to send an acquisition request to a cloud-side device, the acquisition request instructs the cloud-side device to send communication experience information to the terminal device; and a receiving unit, used to receive communication experience information corresponding to a stop point from the cloud-side device.

[0020] In a possible implementation, the terminal device further includes: a processing module, configured to perform normalization processing on the historical trajectory data.

[0021] In a possible implementation, the terminal device further includes: a fourth determination module, configured to determine a cell selection strategy according to the communication experience information, wherein the cell selection strategy instructs the terminal device to select a target cell according to the stay point, the target time and the communication experience information.

[0022] In a third aspect, an embodiment of the present application provides a terminal device, including: a processor and a memory. The processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable the terminal device to implement any one of the methods provided in the first aspect.

[0023] In a fourth aspect, an embodiment of the present application provides a chip, comprising: a processor and an interface circuit; the interface circuit is used to receive code instructions and transmit them to the processor; the processor is used to run the code instructions to execute any one of the methods provided in the first aspect.

[0024] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which at least one computer program instruction is stored, and the computer program instruction is loaded and executed by a processor to implement any one of the methods provided in the first aspect above.

[0025] In a sixth aspect, an embodiment of the present application provides a computer program product, comprising computer execution instructions, which, when executed on a computer, enable the computer to execute any one of the methods provided in the first aspect.

[0026] The technical effects brought about by any implementation method in the second to sixth aspects can refer to the technical effects brought about by the corresponding implementation methods in the first and second aspects, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the architecture of a communication system provided in an embodiment of the present application;

[0028] Figure 2 A flowchart of a cell selection method provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of a scenario for processing historical trajectory data provided in an embodiment of the present application;

[0030] Figure 4 A schematic diagram of a scene for calculating local density provided in an embodiment of the present application

[0031] Figure 5 A schematic diagram of a scenario for establishing a spatiotemporal local density matrix provided in an embodiment of the present application;

[0032] Figure 6 A schematic diagram of a scenario for calculating relative distance provided in an embodiment of the present application;

[0033] Figure 7 A schematic diagram of a scenario for calculating the product of local density and relative distance provided in an embodiment of the present application;

[0034] Figure 8 A scenario diagram of a decision diagram provided in an embodiment of the present application;

[0035] Fig. 9 A schematic diagram of a scenario for determining a core point provided in an embodiment of the present application;

[0036] Fig.10 A schematic diagram of a scenario for determining a stop point provided in an embodiment of the present application;

[0037] Fig.11 A schematic diagram of the structure of a terminal device provided in an embodiment of the present application;

[0038] Fig.12 A schematic diagram of the structure of another terminal device provided in an embodiment of the present application;

[0039] Fig.13 A schematic diagram of the structure of a communication system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In the description of this application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship, for example, A / B can represent A or B; "and / or" in this application is merely a description of the association relationship between associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0041] In the description of this application, unless otherwise specified, "plurality" means two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0042] In addition, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference.

[0043] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0044] It is understood that the "embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the various embodiments in the entire specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It is understood that in various embodiments of the present application, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0045] It can be understood that some optional features in the embodiments of the present application may be implemented independently in certain scenarios without relying on other features, such as the solution on which they are currently based, to solve corresponding technical problems and achieve corresponding effects, or may be combined with other features according to needs in certain scenarios. Accordingly, the devices provided in the embodiments of the present application may also realize these features or functions accordingly, which will not be elaborated here.

[0046] In this application, unless otherwise specified, the same or similar parts between the various embodiments can refer to each other. In this application, if there is no special description or logical conflict between the various embodiments, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and different embodiments can be combined to form new embodiments according to their inherent logical relationships. The following implementation methods of this application do not constitute a limitation on the scope of protection of this application.

[0047] In mobile communication network services, in order to improve the user experience, it is necessary to select the most suitable cell to provide services according to the location and scenario of the user's terminal device. For example, the mobile network can perform cell switching, cell reselection, and cell camping operations on the user's terminal device.

[0048] According to the mobile communication protocol, in the current cell selection scheme, the terminal device can first report the measured cell quality information to the network side device. After receiving the cell quality signal, the network side device determines whether to switch the cell based on the signal quality of the cell currently connected to the terminal device and the cell quality signals of other cells; if switching is required, determine the cell to be reconnected after the switch.

[0049] In the existing cell selection scheme, the cell quality information measured by the terminal device is not accurate and complete. For example, the terminal device may measure the cell level information, but cannot measure the service quality information provided by the corresponding cell at this time, so the UE may not access the optimal cell. In addition, when the terminal user is at the cell boundary, there will be ping-pong switching, that is, frequent switching between two cells, and the switching process will affect the communication experience of the terminal device.

[0050] An embodiment of the present application provides a cell selection method for enabling a terminal device to automatically determine a stay point and more accurately select a cell with better communication quality. The method includes: the terminal device determines a core point based on historical trajectory data; the terminal device determines a stay point based on the core point; the terminal device obtains communication experience information corresponding to the stay point and a target time, the communication experience information includes service quality information and network quality information; the terminal device determines a target cell based on the communication experience information, the target cell being a cell with the best service quality and network quality when the terminal device communicates at the stay point and the target time.

[0051] like Figure 1 As shown, the cell selection method provided in the embodiment of the present application can be applied to the following Figure 1 In the communication system shown, the terminal device establishes communication with the cloud side device and the network device respectively through wireless communication, thereby achieving the acquisition of communication experience information and the selection and switching of the target cell.

[0052] Specifically, the communication system in the embodiment of the present application can be a fifth generation mobile communication technology (5G), satellite communication and short-range wireless communication system. The wireless communication system can also perform point-to-point communication, such as communication between multiple terminal devices. In the embodiment of the present application, the network device can also provide services to more or fewer terminal devices, and the number and type of terminal devices are determined according to actual needs, and are not specifically limited here.

[0053] It should be noted that the wireless communication systems mentioned in the embodiments of the present application include but are not limited to: narrowband Internet of Things (NB-IoT) systems, long term evolution (LTE) systems, and three application scenarios of 5G mobile communication systems: enhanced mobile broadband (eMBB), ultra-reliable & low-latency communication (URLLC) and massive machine type communications (mMTC), as well as other mobile communication systems that may appear in the future, which are not limited here.

[0054] In an embodiment of the present application, a network device is a device deployed in a wireless access network to provide wireless communication functions for terminal devices. The network device can provide wireless communication functions for multiple terminal devices. The network device may include various forms of macro base stations, micro base stations (also called small stations), relay stations, access points, etc. In systems using different wireless access technologies, the names of devices with network device functions may be different. For example, in an LTE system, it is called an evolved node B (evolved nodeB, eNB or eNodeB), and in a third generation (3rd generation, 3G) system, it is called a node B (Node B), etc. For the convenience of description, in an embodiment of the present application, the above-mentioned devices that provide wireless communication functions for terminal devices are collectively referred to as network devices or base stations (base station, BS).

[0055] The network device in the present application may be an evolutionary Node B (eNB or eNodeB) in LTE; or a base station in a 5G network, a broadband network gateway (BNG), an aggregation switch or a non-third generation partnership project (3GPP) access device, etc., and the present application embodiment does not specifically limit this. Optionally, the base station in the embodiment of the present application may include various forms of base stations, such as: macro base stations, micro base stations (also called small stations), relay stations, access points, next generation base stations (gNodeB, gNB), transmission points (transmitting and receiving point, TRP), transmission points (transmitting point, TP), mobile switching centers, and devices to devices (Device-to-Device, D2D), vehicle external connections (vehicle-to-everything, V2X), machine-to-machine (machine-to-machine, M2M) communications, Internet of Things (Internet of Things) communications. The equipment that assumes the function of a base station, etc., is not specifically limited in the present application embodiment.

[0056] The terminal devices involved in the embodiments of the present application may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem with wireless communication functions. The terminal device may also be referred to as a terminal, and the terminal device may also be a subscriber unit, a cellular phone, a smart phone, a wireless data card, a personal digital assistant (PDA) computer, a tablet computer, a wireless modem, a handheld device (handset), a laptop computer, a machine type communication (MTC) terminal, etc., which are not limited here.

[0057] In the embodiment of the present application, there may be more or fewer terminal devices in this communication system. The number and type of terminal devices are determined according to actual needs and are not specifically limited here.

[0058] The terminal device mentioned in the embodiments of the present application may be a device with wireless transceiver functions, and may specifically refer to user equipment (UE), access terminal, subscriber unit, user station, mobile station, remote station, remote terminal, mobile device, user terminal, wireless communication equipment, user agent or user device. The terminal device may also be a satellite phone, a cellular phone, a smart phone, a wireless data card, a wireless modem, a machine type communication device, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, an on-board device, a communication device carried on a high-altitude aircraft, a wearable device, a drone, a robot, a terminal in device-to-device (D2D) communication, a terminal in vehicle to everything (V2X), a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a mixed reality (MR) terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical, a smart grid, etc. This application does not limit the wireless terminals in the future communication network, such as wireless terminals in the smart grid, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, or terminal devices in future communication networks.

[0059] It is understandable that in the embodiments of the present application, the execution subject may execute some or all of the steps in the embodiments of the present application, and these steps or operations are only examples. The embodiments of the present application may also execute other operations or variations of various operations. In addition, the various steps may be executed in different orders presented in the embodiments of the present application, and it is possible that not all operations in the embodiments of the present application need to be executed.

[0060] It should be noted that the message names between the devices or the names of the parameters in the messages in the following embodiments of the present application are only examples, and other names may be used in the specific implementation, and the embodiments of the present application do not specifically limit this.

[0061] like Figure 2 As shown, a cell selection method provided in an embodiment of the present application comprises the following steps:

[0062] 201. The terminal device pre-processes the historical trajectory data.

[0063] The terminal device preprocesses the acquired historical trajectory data, and the preprocessed data is more standardized and more suitable for historical trajectory data for stop point identification.

[0064] Specifically, since the historical trajectory data has problems such as data deviation, missing points and noise points, the recognition effect of the stay points will be affected when the stay points are subsequently calculated. Therefore, it is necessary to perform preprocessing operations such as normalization on the historical trajectory data, filter out the noise points, and normalize the location data and the corresponding time data.

[0065] In a possible implementation, considering the three-dimensional density clustering of time and longitude and latitude, involving the standardized conversion of time and longitude and latitude, the terminal device processes the historical trajectory data with the following calculation formula:

[0066]

[0067] Taking the identification of user stay points and optimization of communication experience of students in a school as an example, the historical trajectory data can be the trajectory data collected by the student's smartphone as the user device (i.e., terminal device) as the input historical trajectory data. As shown in Table 1, the historical trajectory data includes positioning time, gateway time, and longitude and latitude information of positioning. In the collected historical trajectory data, the positioning time indicates the positioning time of the user device, and the gateway time indicates the communication time when the user device establishes a connection with the network device. Due to the differences in user devices, some user devices do not collect the positioning time, so only the network time can be used as the time information corresponding to the historical trajectory data.

[0068] Table 1

[0069] Data serial number longitude latitude Positioning time Gateway Time 1 113.934 22.5365 08:03:51 08:03:46 2 113.9345 22.53658 08:03:56 08:03:51 3 113.9343 22.53661 08:04:06 08:04:01 ... ... ... ... ... n 113.9343 22.53661 08:04:16 08:04:11

[0070] Since historical trajectory data have problems such as data deviation, missing points and noise points, the recognition effect of the stay points will be affected when the stay points are calculated later. Therefore, it is necessary to perform preprocessing operations such as normalization on the historical trajectory data.

[0071] For example, the longitude and latitude information in Table 1 may have certain errors due to measurement problems of the equipment, so they need to be preprocessed to improve the accuracy of the data.

[0072] In a possible implementation, when the time difference between two adjacent location points exceeds 20 seconds but does not exceed 3 hours, the terminal device can determine that a missed point has occurred at the location point, that is, the terminal device has not collected historical trajectory data within these 20 seconds, that is, a missed point in the historical trajectory data collection has occurred. If it does not exceed 3 hours, it means that the terminal device is not offline, so the terminal device can linearly fill in the difference in the longitude and latitude data of the two adjacent location points. The problem of missed points is solved by linear filling.

[0073] In a possible implementation, the terminal device can clean the deviation points outside the park by using the ray method. Specifically, the terminal device draws a ray in any direction with the target point as the vertex. If the number of intersections between the ray and the corresponding polygon outside the park is odd, the target point is inside the polygon, otherwise it is outside the polygon. If the terminal device determines that the target point is outside the park, the historical trajectory data corresponding to the target point is deleted; if the target point is inside the park, the historical trajectory data corresponding to the target point is retained.

[0074] It is understandable that the above two preprocessing methods are only two possible implementation modes. In addition, other preprocessing operations may also be performed, which are not specifically limited here.

[0075] In the embodiment of the present application, stays at different time periods within the same spatial range should be regarded as different stay points. If only the spatial density of longitude and latitude is considered, it is difficult to distinguish stays in the same space in different time periods. Therefore, it is necessary to consider the three-dimensional density clustering of time and longitude and latitude, and the terminal device needs to perform standardized conversion of time and longitude and latitude on the historical trajectory data.

[0076] 202. The terminal device determines the core point.

[0077] The terminal device determines the core point based on the historical trajectory data.

[0078] In the embodiment of the present application, the terminal device first constructs a trajectory data set based on the historical trajectory data, and the trajectory data set is a Kd two-dimensional tree data structure, and then determines the core point based on the trajectory data set through the K nearest neighbor algorithm, and finally determines the stop point based on the core point. The details are as follows:

[0079] a. The terminal device builds a trajectory data set based on the historical trajectory data.

[0080] like Figure 3 As shown, the terminal device first constructs a trajectory data set using historical trajectory data, and the trajectory data set is a Kd two-dimensional tree data structure.

[0081] Specific as Figure 3As shown, the terminal device calculates the variance of each attribute dimension of the historical trajectory data, and selects the attribute with the largest variance for priority division; taking the data (2,3,0.1), (4,7,0.2), (5,4,0.3), (7,2,0.4), (8,1,0.5) and (9,6,0.6) as examples, each data has three attribute dimensions, among which the dimension with the largest dimension variance is the target dimension (that is, the first attribute dimension of the 6 data). Then select the median (5) of the target dimension, divide the data into two parts, and put the data less than or equal to the median 5 on the left, and the data greater than the median 5 on the right.

[0082] In the embodiment of the present application, the trajectory data set is a Kd two-dimensional tree data structure, which has excellent search efficiency when performing nearest neighbor search, and is conducive to the calculation and determination of subsequent core points and stop points.

[0083] b. The terminal device determines the core point based on the trajectory data set using the K nearest neighbor algorithm.

[0084] The terminal device determines the core point according to the trajectory data set through the K-nearest neighbor (KNN) algorithm.

[0085] like Figure 4 As shown in Figure 1, the terminal device first calculates the local density based on the trajectory data set using the KNN algorithm. The terminal device first calculates the average distance k of the nearest k points of each trajectory point. pi , the specific calculation formula is:

[0086]

[0087] The terminal device then calculates the spatiotemporal local density p based on the average distance i , the specific calculation formula is:

[0088]

[0089] When calculating local density, the terminal device can use As k value, n is the number of data.

[0090] like Figure 5 As shown, when calculating the local space-time density p i Afterwards, the terminal device first sorts the local space-time density from large to small according to its size, and establishes a space-time local density matrix. Then, according to the sorting results, the relative distance of each data point is calculated, and each density corresponds to a relative distance.

[0091] In the embodiment of the present application, the KNN algorithm is used to replace the Gaussian kernel function density peak clustering algorithm. The Gaussian kernel function density peak clustering algorithm needs to manually set the cutoff distance to calculate the local density. The terminal device in the embodiment of the present application automatically selects the cutoff distance to replace the manual setting to perform local density calculation. Thus, the terminal device automatically determines the core point and the stop point without manual participation.

[0092] like Figure 6 As shown in FIG. 1 , firstly, the spatial-temporal local density is sorted in descending order to establish a spatial-temporal local density matrix, and then, starting from the second-ranked data point, the relative distance between each data point and the data point ranked before it is calculated. The terminal device determines the shortest distance as the relative distance. For data point p i , p j For the data point that is sorted before it, data point p i The specific calculation formula for the relative distance is:

[0093]

[0094] If the data point p i is the point with the highest local density, the terminal device determines the maximum value among the relative distances calculated previously as the relative distance. The specific calculation formula is:

[0095]

[0096] like Figure 7 As shown, the terminal device then calculates the product of each local density and the relative distance. The specific calculation formula is:

[0097] γ i =p i *δ i .

[0098] like Figure 8 As shown, after determining the product of the local density and the relative distance, the terminal device draws a decision diagram with the local density as the horizontal axis and the relative distance as the vertical axis.

[0099] like Fig. 9 As shown in the decision graph, the density of the core points is higher than that of the surrounding points, and the core points are relatively farther away from other data points with high density.

[0100] In the embodiment of the present application, the terminal device can automatically select the core point according to the decision graph. The terminal device arranges the product of the local density and the relative distance from large to small, and determines the core point according to the slope of each point on the decision graph. On the decision graph, the slope of the core point is large, and the slope of the non-core point is close to zero. The terminal device can automatically select the core point according to this feature.

[0101] 203. The terminal device determines a stop point according to the core point.

[0102] The terminal device determines the stop point based on the core point.

[0103] The terminal device determines a stay point based on the historical trajectory data, and the stay point is a trajectory point where the terminal device stays for a period of time.

[0104] In the embodiment, since the terminal device collects trajectory data at a high frequency, the trajectory points are not equally important. Some trajectory points are just places where the mobile terminal device passes by instantly. This set of trajectory points that reflects that the mobile terminal device stays at a certain place for a period of time is called a stay point. Since the terminal device stays at the stay point for a long time, the signal quality of the stay point has a greater impact on the cell selection of the terminal device.

[0105] Specifically, the terminal device uses the constructed kd-tree data structure to search for points around the core point based on the automatically selected core point, gradually merges and calculates the average point, determines whether the change in the average point is too large, determines the range of the stay point, and identifies and calculates the stay point.

[0106] like Fig.10 As shown, the terminal device first finds the data point b closest to the core point a. Then the terminal device determines the average position point c between the core point a and the data point b. The terminal device also calculates the distance between the core point a and the average position point c. If the distance is less than a preset value, the terminal device determines the average position point c as the stop point.

[0107] The terminal device then determines the two closest data points, namely data point b and data point d in the figure, and then determines the average position point e between the core point a and the data points b and d. The terminal device also calculates the distance between the core point a and the average position point e. If the distance is less than a preset value, the terminal device determines the average position point e as the stop point.

[0108] Then the terminal device determines the stay points one by one until the distance between a certain average position point and the core point a is greater than a preset value, and then stops determining the stay points. The stay points previously determined one by one by the terminal device are the finally determined stay points.

[0109] 204. The terminal device obtains communication experience information corresponding to the stop point.

[0110] The terminal experience information database is deployed on the cloud side device. The terminal experience information database contains service quality information, network quality information, and corresponding cell information, time information, historical stay information, and other information at the stay point.

[0111] After the terminal device determines the stay point and the corresponding time, the terminal device can send an acquisition request to the cloud-side device, where the acquisition request indicates that the terminal device needs to obtain the communication experience information corresponding to the stay point and the target time.

[0112] Accordingly, the terminal device can obtain communication experience information from the cloud-side device by receiving information, and the experience information includes service quality information, network quality information and corresponding stay points and times.

[0113] In the embodiment of the present application, the target time may be the current time or a time predicted by the terminal device, which is not specifically limited here.

[0114] In a possible implementation, as shown in Table 2, the communication experience information may include service quality information and network quality information corresponding to multiple time periods and multiple stop points.

[0115] Table 2

[0116]

[0117] As shown in Table 2, the communication experience information may include service quality information and network quality information corresponding to multiple time periods and multiple stop points, from which the terminal device can determine the communication experience information corresponding to the stop point and the target time.

[0118] In a possible implementation, when the communication experience information may include service quality information and network quality information corresponding to multiple time periods and multiple stop points, the terminal device may also determine a cell selection strategy based on the information, as follows:

[0119] 205. The terminal device determines a cell selection strategy according to the communication experience information.

[0120] The terminal device determines a cell selection strategy based on the communication experience information. The cell strategy instructs the terminal device to select a cell with the best service quality and network quality based on the stay point and time.

[0121] For example, as shown in Table 2, at 10 a.m. in classroom A105, the service quality of cell 112 is better than that of cell 113, so cell 112 is preferred; at 20 p.m., the service quality of cell 113 is better than that of cell 112, so cell 113 is preferred. At 10 a.m. in dormitory 11201, the service quality of cell 212 is better than that of cell 211, so cell 212 is preferred; at 20 p.m., the service quality of cell 211 is better than that of cell 212, so cell 211 is preferred.

[0122] 206. The terminal device determines a target cell.

[0123] The terminal device's stay point and time determine the target cell, which is the cell with the best communication quality for the terminal device at the above-mentioned stay point and time, that is, the cell with the best service quality and network quality.

[0124] In a possible implementation, the terminal device determines a cell selection strategy according to the communication experience information. After determining the stay point and time, the terminal device may determine a target cell according to the cell selection strategy.

[0125] In the embodiment of the present application, the terminal device automatically determines the core points and the stay points based on the historical trajectory data, and determines the cell with the best communication quality for communication in combination with the communication experience information. The terminal device automatically determines the core points and the stay points without manual intervention. At the same time, the target cell can be determined based on the historical experience information, and the reliability of selecting a cell with good communication quality is higher.

[0126] The embodiment of the present application provides a terminal device 1100. In the embodiment of the present application, the terminal device 1100 can be divided into functional modules according to the above method example. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0127] In the case of dividing each functional module into corresponding functional modules, Fig.11 FIG. 1 is a schematic diagram showing a possible structure of the terminal device 1100 involved in the above embodiment. Fig.11 As shown, the terminal device 1100 includes:

[0128] The processing module 1101 is used to perform normalization processing on the historical trajectory data. For example, the step 201 in the above method embodiment is performed: the terminal device pre-processes the historical trajectory data.

[0129] The first determination module 1102 is used to determine the core point according to the historical trajectory data; for example, the step 202 in the above method embodiment is executed: the terminal device determines the core point.

[0130] In a possible implementation, the first determination module 1102 includes: for example, executing step 202 in the above method embodiment: the terminal device determines a stay point.

[0131] The first determining unit 1103 is used to construct a trajectory data set according to the historical trajectory data, where the trajectory data set is a Kd two-dimensional tree data structure; for example, the step 202 in the above method embodiment is performed: the terminal device determines the core point.

[0132] The second determining unit 1104 is configured to determine the core point by using a K nearest neighbor algorithm according to the trajectory data set, for example, by executing step 202 in the above method embodiment: the terminal device determines the core point.

[0133] In a possible implementation, the second determining unit 1104 includes:

[0134] The first determining subunit 1105 is used to determine the spatiotemporal local density and the product of the spatiotemporal local density and the relative distance of each trajectory data point in the trajectory data set by using a K-nearest neighbor algorithm; for example, executing step 202 in the above method embodiment: the terminal device determines the core point.

[0135] The second determination subunit 1106 is configured to determine the core point according to the spatiotemporal local density of each trajectory data point and the product of the spatiotemporal local density and the relative distance. For example, step 202 in the above method embodiment is performed: the terminal device determines the core point.

[0136] The second determination module 1107 is used to determine the stay point according to the core point; for example, executing step 203 in the above method embodiment: the terminal device determines the stay point according to the core point.

[0137] In a possible implementation, the second determining module 1107 is specifically configured to:

[0138] The stay point is determined based on the core point and the average point of the points around the core point. For example, step 203 in the above method embodiment is performed: the terminal device determines the stay point based on the core point.

[0139] The acquisition module 1108 is used to obtain the communication experience information corresponding to the stop point and the target time, the communication experience information includes service quality information and network quality information; for example, executing step 204 in the above method embodiment: the terminal device obtains the communication experience information corresponding to the stop point.

[0140] In a possible implementation, the acquisition module 1108 includes:

[0141] The sending unit 1109 is used to send an acquisition request to the cloud-side device, and the acquisition request instructs the cloud-side device to send communication experience information to the terminal device; for example, executing step 204 in the above method embodiment: the terminal device obtains the communication experience information corresponding to the stop point.

[0142] The receiving unit 1110 is configured to receive the communication experience information corresponding to the stay point from the cloud-side device. For example, the step 204 in the above method embodiment is performed: the terminal device obtains the communication experience information corresponding to the stay point.

[0143] The fourth determination module 1111 is used to determine a cell selection strategy according to the communication experience information, wherein the cell selection strategy instructs the terminal device to select a target cell according to the stay point, target time and communication experience information. For example, step 205 in the above method embodiment is performed: the terminal device determines a cell selection strategy according to the communication experience information.

[0144] The third determination module 1112 is used to determine the target cell according to the communication experience information, where the target cell is the cell with the best service quality and network quality when the terminal device communicates at the stop point and the target time. For example, step 206 in the above method embodiment is performed: the terminal device determines the target cell.

[0145] The various modules of the above-mentioned terminal device can also be used to perform other actions in the above-mentioned method embodiment. All relevant contents of each step involved in the above-mentioned method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0146] Fig.12 It is a schematic diagram of the structure of a terminal device provided in an embodiment of the present application. The terminal device 1200 may include one or more central processing units (CPU) 1201 and a memory 1205. The memory 1205 stores one or more application programs or data.

[0147] The memory 1205 may be a volatile storage or a persistent storage. The program stored in the memory 1205 may include one or more modules, each of which may include a series of instruction operations on the terminal device. Furthermore, the central processor 1201 may be configured to communicate with the memory 1205 and execute a series of instruction operations in the memory 1205 on the terminal device 1200.

[0148] The central processor 1201 is used to execute the computer program in the memory 1205, so that the terminal device 1200 is used to execute: the terminal device determines the core point according to the historical trajectory data; the terminal device determines the stay point according to the core point; the terminal device obtains the communication experience information corresponding to the stay point and the target time, and the communication experience information includes service quality information and network quality information; the terminal device determines the target cell according to the communication experience information, and the target cell is the cell with the best service quality and network quality when the terminal device communicates at the stay point and the target time. For specific implementation methods, please refer to Figure 2 Steps 201-206 in the illustrated embodiment are not described in detail here.

[0149] The terminal device 1200 may also include one or more power supplies 1202, one or more wired or wireless network interfaces 1203, one or more input and output interfaces 1204, and / or one or more operating systems, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0150] The terminal device 1200 can execute the aforementioned Figure 2 The operations performed by the terminal device in the illustrated embodiment will not be described in detail here.

[0151] The embodiment of the present application provides a communication system 1800, wherein the communication system 1300 includes a network device 1301, a terminal device 1302, and a cloud side device 1303, wherein the network device 1301, the terminal device 1302, and the cloud side device 1303 can execute the aforementioned Figure 2 The operations performed by the network devices, terminal devices and cloud-side devices in the illustrated embodiment are not described in detail here.

[0152] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, 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 instructions. When loading and executing computer program instructions on a computer, all or part of the processes (or functions) of the embodiments of the present application are implemented. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. that contains one or more servers that can be integrated with a medium. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)), etc. In the embodiment of the present application, the computer may include the above device.

[0153] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other changes to the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

Claims

1. A cell selection method, characterized in that: The method comprises: The terminal device determines the core point based on the historical trajectory data; The terminal device determines a stay point according to the core point; The terminal device acquires communication experience information corresponding to the stop point and the target time, wherein the communication experience information includes service quality information and network quality information; The terminal device determines a target cell according to the communication experience information, and the target cell is a cell with the best service quality and network quality when the terminal device communicates at the stay point and the target time.

2. The method according to claim 1, characterized in that The terminal device determines the core point according to the historical trajectory data, including: The terminal device constructs a trajectory data set according to the historical trajectory data, and the trajectory data set is a Kd two-dimensional tree data structure; The terminal device determines the core point through a K nearest neighbor algorithm according to the trajectory data set.

3. The method according to claim 2, characterized in that The terminal device determines the core point according to the trajectory data set, including: The terminal device determines the spatiotemporal local density of each trajectory data point in the trajectory data set and the product of the spatiotemporal local density and the relative distance by using a K-nearest neighbor algorithm; The terminal device determines the core point according to the spatiotemporal local density of each trajectory data point and the product of the spatiotemporal local density and the relative distance.

4. The method according to claim 3, characterized in that: The terminal device determines the stay point according to the core point, including: The terminal device determines a stay point based on the core point and an average point of points around the core point.

5. The method according to claim 4, characterized in that The terminal device obtains communication experience information corresponding to the stop point and the target time, including: The terminal device sends an acquisition request to the cloud-side device, wherein the acquisition request instructs the cloud-side device to send the communication experience information to the terminal device; The terminal device receives communication experience information corresponding to the stop point from the cloud-side device.

6. The method according to claim 5, characterized in that Before the terminal device determines the stop point according to the historical trajectory data, the method further includes: The terminal device performs normalization processing on the historical trajectory data; The terminal device determines the stop point according to the historical trajectory data, including: The terminal device determines the stop point according to the normalized historical trajectory data.

7. The method according to claim 6, characterized in that Before the terminal device determines the target cell according to the communication experience information, the method further includes: The terminal device determines a cell selection strategy according to the communication experience information, wherein the cell selection strategy instructs the terminal device to select a target cell according to the stay point, the target time, and the communication experience information; The terminal device determines a target cell according to the communication experience information, including: The terminal device determines a target cell according to the cell selection strategy, and the target cell is a cell with the best service quality and network quality when the terminal device communicates at the stay point and the target time.

8. A terminal device, characterized in that: The terminal device comprises: A first determination module, used to determine the core point according to the historical trajectory data; A second determination module is used to determine a stop point according to the core point; An acquisition module, used to acquire communication experience information corresponding to the stop point and the target time, wherein the communication experience information includes service quality information and network quality information; The third determination module is used to determine a target cell according to the communication experience information, where the target cell is a cell with the best service quality and network quality when the terminal device communicates at the stay point and target time.

9. The terminal device according to claim 8, characterized in that: The first determining module comprises: A first determining unit, configured to construct a trajectory data set according to the historical trajectory data, wherein the trajectory data set is a Kd two-dimensional tree data structure; The second determining unit is used to determine the core point by using a K nearest neighbor algorithm according to the trajectory data set.

10. The terminal device according to claim 9, characterized in that: The second determining unit includes: A first determining subunit is used to determine the spatiotemporal local density of each trajectory data point in the trajectory data set and the product of the spatiotemporal local density and the relative distance by using a K-nearest neighbor algorithm; The second determining subunit is configured to determine the core point according to the spatiotemporal local density of each trajectory data point and the product of the spatiotemporal local density and the relative distance.

11. The terminal device according to claim 10, characterized in that: The second determining module is specifically used for: The stay point is determined according to the core point and the average point of the points around the core point.

12. The terminal device according to claim 11, characterized in that: The acquisition module comprises: A sending unit, configured to send an acquisition request to a cloud-side device, wherein the acquisition request instructs the cloud-side device to send the communication experience information to the terminal device; The receiving unit is used to receive the communication experience information corresponding to the stop point from the cloud side device.

13. The terminal device according to claim 12, characterized in that: The terminal device further includes: A processing module is used to perform normalization processing on the historical trajectory data.

14. The terminal device according to claim 13, characterized in that: The terminal device further includes: The fourth determination module is used to determine a cell selection strategy according to the communication experience information, wherein the cell selection strategy instructs the terminal device to select a target cell according to the stay point, the target time and the communication experience information.

15. A terminal device, characterized in that: The terminal device comprises a processor and a memory; the processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable the terminal device to implement the method according to any one of claims 1-7.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program instruction, and the computer program instruction is loaded and executed by a processor to implement the method according to any one of claims 1 to 7.

17. An optical communication system, characterized in that: The communication system includes a terminal device and a cloud-side device, the terminal device is used to execute the method described in any one of claims 1 to 7, and the cloud-side device is used to execute the method described in any one of claims 1 to 7.

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