Method and device for identifying neighbor cell based on fingerprint database, electronic equipment and storage medium

Abstract

The invention provides a method for identifying neighbor cells based on a fingerprint database, electronic equipment, a device and a storage medium. The method comprises the following steps: acquiring measurement report (MR) data of a plurality of service cells; for MR data of any service cell, counting the number of MR sampling points corresponding to physical cell identifications (PCIs) of all adjacent cells in the MR data, selecting the first N adjacent cell PCIs with a large number of MR sampling points, and constructing MR fingerprints of the service cell based on the first N adjacent cell PCIs; constructing a cell MR fingerprint database based on the MR fingerprints of the plurality of service cells; and determining a cell corresponding to the target adjacent cell PCI based on the cell MR fingerprint database. According to the method, the influence of maintenance operation of external data such as work parameters and configuration files on the identification accuracy can be effectively avoided, the accuracy and the reliability of adjacent region identification are improved, meanwhile, the complexity of an identification scheme is reduced, the self-closed loop capability in a network element is improved, and the implementation of a high-order self-intelligence network is further promoted.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method, electronic device, apparatus, and storage medium for identifying neighboring cells based on a fingerprint library. Background Art

[0002] In Long Term Evolution (LTE) and New Radio (NR) wireless communication networks, terminals report their current wireless environment status through Measurement Reports (MRs). The Physical Cell Identity (PCI) corresponding to the serving cell in the MR contains site identity (ID) information, and the serving cell can be easily identified based on the site ID, frequency band, and PCI. However, since neighboring cells do not have site information, it is impossible to directly determine the cell corresponding to the neighboring cell PCI. Existing solutions for identifying neighboring cells (searching for the cell corresponding to the neighboring cell PCI) mostly use engineering parameters or neighboring cell configuration to find the cell corresponding to the neighboring cell PCI. This solution relies on manual maintenance of engineering parameters or neighboring cell configuration, and is prone to misjudgment. Summary of the Invention

[0003] In response to the problems existing in the prior art, the present application provides a method, electronic device, apparatus and storage medium for identifying neighboring areas based on a fingerprint library.

[0004] In a first aspect, the present application provides a method for identifying neighboring cells based on a fingerprint library, comprising:

[0005] Obtain measurement report MR data of multiple serving cells;

[0006] For any serving cell's MR data, count the number of MR sampling points corresponding to each neighboring cell physical cell identifier (PCI) in the MR data, select the top N neighboring cell PCIs with the largest number of MR sampling points, and construct the serving cell's MR fingerprint based on the top N neighboring cell PCIs; where N is an integer greater than 1;

[0007] Constructing a cell MR fingerprint database based on the MR fingerprints of multiple serving cells;

[0008] The cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint library. The target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

[0009] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0010] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0011] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0012] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0013] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0014] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0015] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0016] In some embodiments, the method further comprises:

[0017] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0018] In some embodiments, the method further comprises:

[0019] Determine that duplicate PCIs exist in PCIs of multiple serving cells, and construct a duplicate PCI list based on the duplicate PCIs;

[0020] If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one serving cell PCI that is the same as the target neighboring cell PCI among the multiple serving cells.

[0021] In a second aspect, the present application further provides an electronic device, comprising a memory, a transceiver, and a processor;

[0022] A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations:

[0023] Obtain measurement report MR data of multiple serving cells;

[0024] For any serving cell's MR data, count the number of MR sampling points corresponding to each neighboring cell physical cell identifier (PCI) in the MR data, select the top N neighboring cell PCIs with the largest number of MR sampling points, and construct the serving cell's MR fingerprint based on the top N neighboring cell PCIs; where N is an integer greater than 1;

[0025] Constructing a cell MR fingerprint database based on the MR fingerprints of multiple serving cells;

[0026] The cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint library. The target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

[0027] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0028] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0029] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0030] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0031] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0032] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0033] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0034] In some embodiments, the operations further include:

[0035] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0036] In some embodiments, the operations further include:

[0037] Determine that duplicate PCIs exist in PCIs of multiple serving cells, and construct a duplicate PCI list based on the duplicate PCIs;

[0038] If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one serving cell PCI that is the same as the target neighboring cell PCI among the multiple serving cells.

[0039] In a third aspect, the present application further provides a device for identifying neighboring cells based on a fingerprint library, comprising:

[0040] an acquiring unit, configured to acquire measurement report MR data of a plurality of serving cells;

[0041] a fingerprint construction unit configured to, for MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs; wherein N is an integer greater than 1;

[0042] A fingerprint library construction unit, configured to construct a cell MR fingerprint library based on the MR fingerprints of multiple serving cells;

[0043] The identification unit is used to determine the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library, where the target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

[0044] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0045] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0046] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0047] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0048] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0049] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0050] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0051] In some embodiments, the recognition unit is further configured to:

[0052] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0053] In some embodiments, the apparatus further comprises:

[0054] a list construction unit, configured to determine whether duplicate PCIs exist in the PCIs of the plurality of serving cells, and to construct a duplicate PCI list based on the duplicate PCIs;

[0055] The determining unit is configured to determine that, if the target neighboring cell PCI is in the duplicate PCI list, there is more than one serving cell with the same PCI as the target neighboring cell among the multiple serving cells.

[0056] In a fourth aspect, the present application further provides a non-transitory readable storage medium storing a computer program, wherein the computer program is used to enable a processor to execute the method for identifying neighboring areas based on a fingerprint library as described in the first aspect.

[0057] In a fifth aspect, the present application further provides a communication device, wherein a computer program is stored in the communication device, and the computer program is used to enable the communication device to execute the method for identifying neighboring cells based on a fingerprint library as described in the first aspect above.

[0058] In a sixth aspect, the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable a processor to execute the method for identifying neighboring areas based on a fingerprint library as described in the first aspect above.

[0059] In a seventh aspect, the present application further provides a chip product, wherein a computer program is stored in the chip product, and the computer program is used to enable the chip product to execute the method for identifying neighboring areas based on a fingerprint library as described in the first aspect.

[0060] The method, electronic device, apparatus, and storage medium for identifying neighboring cells based on a fingerprint library provided in the present application select multiple neighboring cell PCIs based on the number of MR sampling points to construct the MR fingerprint of the service cell, and then construct a cell MR fingerprint library. The cell MR fingerprint library is used to determine the cell corresponding to the neighboring cell PCI, thereby reducing dependence on external data such as working parameters and configuration files, effectively avoiding the impact of maintenance operations on external data such as working parameters and configuration files on identification accuracy, improving the accuracy and reliability of neighboring cell identification, and at the same time reducing the complexity of the identification scheme, improving the self-closed-loop capability within the network element, and further promoting the realization of high-order self-intelligent networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0062] Figure 1 A schematic diagram of cell distribution provided for related technologies;

[0063] Figure 2 A schematic diagram of a flow chart of a method for identifying neighboring areas based on a fingerprint library provided in an embodiment of the present application;

[0064] Figure 3 Flowchart of the implementation of the method for identifying neighboring areas based on a fingerprint database provided in an embodiment of the present application;

[0065] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0066] Figure 5 A schematic diagram of the structure of a device for identifying neighboring areas based on a fingerprint library provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] In the embodiments of this application, the term "and / or" describes the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0068] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0069] In the embodiments of the present application, the terms "first," "second," and the like are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than that illustrated or described herein. Furthermore, the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects. For example, the first object can be one or more.

[0070] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0071] In order to facilitate a clearer understanding of the technical solutions of the various embodiments of the present application, some technical contents related to the various embodiments of the present application are first introduced.

[0072] In existing communication protocols, terminals only measure information such as the Reference Signal Received Power (RSRP) and Signal to Interference plus Noise Ratio (SINR) associated with each PCI. However, the number of PCIs is limited (504 for LTE and 1008 for NR), and the probability of duplication is high in dense networks. Therefore, when analyzing MRs, it is necessary to identify duplicate PCIs and determine which cell they belong to.

[0073] The PCI corresponding to the serving cell in the MR includes site ID information, making it easy to identify the serving cell based on the site ID, frequency band, and PCI. However, neighboring cells lack site information, making it impossible to directly determine the cell corresponding to the neighboring cell's PCI. There are two mainstream solutions for neighboring cell identification: one associates the PCI with engineering parameters, and the other associates the PCI with cell configuration. Both solutions have drawbacks and rely on manual maintenance of engineering parameters or neighboring cell configuration.

[0074] The two solutions have similar preliminary processing. First, both solutions format the MR to generate a corresponding table between the serving cell and the neighboring cell PCI, as shown in Table 1. The table generally includes time, serving cell base station ID (site ID), serving cell PCI, serving cell local cell identity (LCID), serving cell RSRP, neighboring cell PCI, neighboring cell RSRP, etc.

[0075] Table 1 Correspondence between serving cell and neighboring cell PCI

[0076]

[0077] Then if:

[0078] ① According to the working parameter association method. This solution finds the corresponding cell in the working parameter table based on the neighboring cell PCI and annotates it with the cell name or other unique identifier. If the same neighboring cell PCI corresponds to multiple cells, the distances between these multiple cells and the serving cell are calculated, and the cell with the closest distance is selected as the neighboring cell corresponding to the neighboring cell PCI.

[0079] Figure 1 A schematic diagram of cell distribution provided for related technologies, such as Figure 1As shown in the figure, when the serving cell PCI is 47 and the neighboring cell PCI is 7. Because there are 4 cells with PCI=7 in the area, it is necessary to calculate the distance between each cell with PCI=7 and the serving cell (47) according to the longitude and latitude of the site, and take the cell with PCI=7 that is closer as the neighboring cell. Figure 1 Generally, the cell with PCI=7 slightly to the north of the cell with PCI=47 is taken as the neighboring cell.

[0080] ②According to the method of associating the cell configuration files. Figure 1 For example, when it is found that the cell with PCI=47 receives a signal from the neighboring cell with PCI=7, the site ID and other information corresponding to the neighboring cell with PCI=7 are found from the configured neighboring cell relationship through the cell configuration file of PCI=47.

[0081] Both of the above solutions rely on the accuracy of external input. For example, the first solution requires manual maintenance of the engineering parameters, which can easily lead to inaccurate parameters due to delayed updates or misoperation. The second solution relies on the accuracy of neighboring cell configurations, which carries the risk of missed or incorrect configurations.

[0082] Furthermore, the concept of self-intelligent networks is gaining widespread popularity, with the vision of eliminating human intervention in network operations and maintenance. High-level self-intelligent networks should minimize reliance on external input and human input. Both of the aforementioned solutions require manual location maintenance and updates to engineering parameters or configuration files, making it impossible to achieve a closed-loop solution to network issues within the self-intelligent process.

[0083] Figure 2 A flow chart of a method for identifying neighboring areas based on a fingerprint database provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes the following steps:

[0084] Step 200: Obtain measurement report MR data of multiple serving cells.

[0085] Specifically, the execution subject of the method can be any device used for MR analysis, and this application does not impose any limitation on this.

[0086] Before constructing the MR fingerprint of each serving cell, it is necessary to obtain the MR data of each serving cell. For example, Table 1 shows the MR data of a serving cell (site ID: 12345, PCI: 47). The serving cell information is the same, but includes multiple different neighboring cell PCIs. These neighboring cell PCIs are not associated with neighboring cell information in the MR data, so it is currently impossible to determine which cell these neighboring cell PCIs correspond to.

[0087] Step 201: For MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs; where N is an integer greater than 1.

[0088] Specifically, after obtaining the MR data of each serving cell, the number of MR sampling points corresponding to each neighboring cell PCI can be counted. For example, each row in Table 1 can be regarded as an MR sampling point. Taking neighboring cell PCI=7 as an example, if there are n MR sampling points with neighboring cell PCI=7 in the MR data of a serving cell, then the number of MR sampling points corresponding to neighboring cell PCI 7 is n.

[0089] For a particular serving cell, after counting the number of MR sampling points corresponding to each neighboring cell PCI in the MR data of the serving cell, the first N neighboring cell PCIs with the largest number of MR sampling points are selected. For example, in some embodiments, the neighboring cell PCIs may be sorted in descending order based on the number of MR sampling points, and the first to N neighboring cell PCIs are selected.

[0090] Then, the MR fingerprint of the serving cell can be constructed based on the N neighboring cell PCIs, where N can be set as needed and is not limited here.

[0091] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0092] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0093] For example, assuming N = 8, the PCI of the serving cell = 47, and the PCIs of the first N neighboring cells with the largest number of MR sampling points are 7, 8, 11, 15, 16, 17, 30, and 32, respectively, then the set {47, 7, 8, 11, 15, 16, 17, 30, 32} is the MR fingerprint of the serving cell with PCI = 47.

[0094] Step 202: Construct a cell MR fingerprint database based on the MR fingerprints of multiple serving cells.

[0095] Specifically, after obtaining the MR fingerprint of each serving cell, a cell MR fingerprint library can be constructed for neighboring cell identification. For example, a blank cell MR fingerprint library can be pre-established. After obtaining the MR fingerprint of each serving cell, the MR fingerprint of each serving cell is added to the cell MR fingerprint library, and a fingerprint index is created for each serving cell's MR fingerprint.

[0096] In some implementations, each MR fingerprint in the cell MR fingerprint library is associated with a serving cell site ID, a serving cell PCI, and a serving cell frequency band (these three items can be used as fingerprint indexes).

[0097] Step 203: Determine the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint database. The target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

[0098] Specifically, the target serving cell refers to a serving cell that currently needs to perform neighbor cell identification, and the target neighbor cell PCI refers to the neighbor cell PCI that currently needs to be identified in the MR data of the target serving cell.

[0099] After building the cell MR fingerprint library, the cell MR fingerprint library can be used to determine the cell corresponding to the target neighboring cell PCI without using external data such as engineering parameters and configuration files.

[0100] The method for identifying neighboring cells based on a fingerprint library provided in the embodiment of the present application selects multiple neighboring cell PCIs according to the number of MR sampling points to construct the MR fingerprint of the service cell, and then constructs a cell MR fingerprint library. The cell MR fingerprint library is used to determine the cell corresponding to the neighboring cell PCI, thereby reducing the dependence on external data such as working parameters and configuration files, and can effectively avoid the impact of maintenance operations on external data such as working parameters and configuration files on recognition accuracy, thereby improving the accuracy and reliability of neighboring cell identification, reducing the complexity of the identification scheme, improving the self-closed loop capability within the network element, and further promoting the realization of high-order self-intelligent networks.

[0101] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0102] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0103] Specifically, due to the limited number of PCIs (504 for LTE and 1008 for NR), the probability of duplication is high in dense networks. Therefore, when performing MR analysis, it is crucial to identify duplicate PCIs and determine which cell they belong to. For example, if the target neighboring cell has PCI = 7, and the MR data contains multiple serving cells with PCI = 7, it is impossible to determine which of these serving cells with PCI = 7 is the same cell as the neighboring cell with PCI = 7. In this case, a pre-built cell MR fingerprint library can be used to determine the specific cell of the neighboring cell with PCI = 7.

[0104] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0105] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0106] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0107] Specifically, because the distribution of cells around a serving cell and its neighboring cells is largely similar, the MR fingerprints of several candidate serving cells (i.e., the first serving cell) can be compared with the MR fingerprint of the target serving cell for similarity. The first serving cell with the highest similarity can be considered the cell corresponding to the neighboring cell PCI. The similarity metric can be flexibly selected and is not limited here. For example, the Jaccard similarity coefficient or the Pearson coefficient can be used as a similarity metric.

[0108] Taking the Jaccard similarity coefficient as an example, the calculation formula of the Jaccard similarity coefficient is:

[0109]

[0110] Where Jsc(x,y) represents the Jaccard similarity coefficient, x and y represent the two sets whose similarity needs to be calculated, and the len(M) function is used to calculate the number of elements in the set M.

[0111] Assuming that the MR fingerprint of the target serving cell is {47, 7, 8, 11, 15, 16, 17, 30, 32}, the MR fingerprints of the first serving cells are:

[0112] #1: {9, 11, 45, 25, 30, 7, 20, 45, 12};

[0113] #2: {7, 8, 11, 18, 21, 25, 30, 32, 47};

[0114] #3: {125, 210, 65, 11, 7, 51, 19, 32, 322};

[0115] #4: {84, 7, 23, 77, 12, 51, 126, 234, 32}.

[0116] The MR fingerprint similarities between the first serving cell and the target serving cell (using the Jaccard similarity coefficient as an example) are: 0.21 (#1); 0.50 (#2); 0.20 (#3); and 0.13 (#4). This confirms that cell #2 is the cell corresponding to the neighboring cell PCI. The site ID, frequency band, and other information of cell #2 can be used as the cell information for the neighboring cell PCI.

[0117] In some embodiments, the method further comprises:

[0118] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0119] For example, if the target neighboring cell has a PCI of 7, and the MR data contains only one serving cell with a PCI of 7, then the serving cell with PCI of 7 and the neighboring cell with PCI of 7 can be considered the same cell. The site ID, frequency band, and other information of the serving cell with PCI of 7 can be used as the cell information for the neighboring cell's PCI.

[0120] In some embodiments, the method further comprises:

[0121] Determine that duplicate PCIs exist in PCIs of multiple serving cells, and construct a duplicate PCI list based on the duplicate PCIs;

[0122] If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one serving cell PCI that is the same as the target neighboring cell PCI among the multiple serving cells.

[0123] Specifically, to quickly determine whether there are multiple serving cells with the same PCI as the target neighboring cell, a duplicate PCI list can be pre-built. In this duplicate PCI list, the same PCI corresponds to multiple different serving cells. If the target neighboring cell PCI is in the duplicate PCI list, it means that more than one serving cell has the same PCI as the target neighboring cell PCI. The pre-built cell MR fingerprint library can then be used to determine the specific cell corresponding to the target neighboring cell PCI.

[0124] In some implementations, the repeated PCI list includes information such as the serving cell site ID and serving cell frequency band corresponding to each PCI, so that the information can be used as an index to read the MR fingerprints of the aforementioned first serving cells from the cell MR fingerprint library.

[0125] The following describes the methods provided in the above embodiments of the present application through examples of specific application scenarios.

[0126] Figure 3The implementation flow chart of the method for identifying neighboring areas based on the fingerprint library provided in the embodiment of the present application is as follows: Figure 3 As shown, the main process includes:

[0127] 1. Establish a fingerprint database

[0128] All MR data for each serving cell is collated, using the serving cell site ID, serving cell frequency band, serving cell PCI, and neighboring cell PCI as indexes. Information such as the number of MR sampling points, serving cell average RSRP, neighboring cell average RSRP, serving cell average SINR, and neighboring cell average SINR for each index is collected. The specific features collected are not limited to the features listed above; additional or reduced content can be collected as needed. The MR collection information is listed in Table 2, sorted in descending order by the number of MR sampling points.

[0129] Table 2 MR collection information list

[0130]

[0131] Based on the generated MR collection information list, a cell MR fingerprint library is established, using the serving cell site ID, serving cell frequency band, and serving cell PCI as indexes. The serving cell PCI and the set of TOP_N (the N with the largest number of MR sampling points) neighboring cell PCIs are used as the serving cell's MR fingerprint. TOP_N is the neighboring cell fingerprint length, meaning the total fingerprint length is TOP_N + 1 (serving cell). The cell MR fingerprint library shown in Table 3 below uses TOP_N = 8 as an example. In actual applications, TOP_N can be set as needed, but the default is generally 20.

[0132] Table 3 Cell MR fingerprint database

[0133]

[0134] 2. Identify Repeat PCI

[0135] Based on the MR collection information list or cell MR fingerprint database generated in step 1, extract the serving cell site ID, serving cell frequency band, and serving cell PCI, remove duplicates, and retain the serving cell dimension information. Count any duplicate PCIs in the serving cell dimension and record them as a duplicate PCI list, as shown in Table 4.

[0136] Table 4 Repeated PCI list

[0137] Serving cell site ID Serving cell PCI Serving cell frequency band 52345 7 13467 13456 7 13467 25894 7 13467 33651 7 13467 52345 11 13467 13456 11 13467 25894 11 13467 …… …… ……

[0138] 3. Process the neighboring cell PCI of each cell one by one

[0139] After completing the preparatory actions in steps 1 and 2, each index (each row) in the MR acquisition information list is processed. The ultimate goal is to determine the cell corresponding to each neighboring cell PCI and to supplement each neighboring cell PCI with the corresponding neighboring cell site ID and neighboring cell frequency band to complete the neighboring cell association, as shown in Table 5. The neighboring cell LCID is supplemented as needed.

[0140] Table 5 Supplementary list of MR collection information

[0141]

[0142]

[0143] 4. Determine whether the neighboring area PCI is repeated

[0144] Process the neighboring area PCI corresponding to each index in the MR acquisition information list one by one, and determine whether the neighboring area PCI is in the duplicate PCI list generated in step 2. If the neighboring area PCI is not in the duplicate PCI list, jump to step 9; if the neighboring area PCI is in the duplicate PCI list, jump to step 5.

[0145] 5. Read the fingerprint of the service cell

[0146] When processing the neighboring cell PCI corresponding to each index in the MR collection information list one by one and encountering a neighboring cell PCI in the duplicate PCI list, it is impossible to directly associate the corresponding site ID and frequency band based on the PCI. Fingerprint comparison is required to determine the cell corresponding to the neighboring cell PCI. First, read the corresponding cell MR fingerprint based on the site ID, frequency band, and PCI of the serving cell in the index corresponding to the neighboring cell PCI in the MR collection information list. Taking the first row of indexes in Table 5 as an example, the MR fingerprint of the serving cell corresponding to neighboring cell PCI 7 is shown in Table 6.

[0147] Table 6 Serving cell MR fingerprint

[0148] Serving cell site ID Serving cell PCI Serving cell frequency band fingerprint 12345 47 13467 {47、7、8、11、15、16、17、30、32}

[0149] 6. Read the fingerprint of the PCI cell in the same neighboring area as a candidate neighboring area

[0150] Taking the processing of the neighboring cell with PCI=7 as an example, the MR fingerprints of all service cells with PCI equal to 7 (i.e., the first service cell mentioned above) are read from the cell MR fingerprint library generated in step 1. As shown in Table 7, these service cells are used as candidate neighboring cells (i.e., the cell finally identified by the neighboring cell PCI 7 is one of these service cells).

[0151] Table 7 Alternative neighboring cell MR fingerprints

[0152]

[0153]

[0154] 7. Calculate the fingerprint similarity between the serving cell and the candidate neighboring cells

[0155] Here, the Jaccard similarity coefficient method can be used to calculate the fingerprint similarity between the serving cell and each candidate neighboring cell. As shown in Table 8, the Jaccard similarity coefficient calculation formula is used to calculate the Jaccard similarity coefficient of each candidate neighboring cell (PCI=7) and the serving cell (PCI=47). As shown in Table 8, the cell with site ID 13456 has the highest similarity.

[0156] Table 8 Similarity calculation results

[0157]

[0158] 8. Take the neighboring area with the highest similarity as the associated neighboring area

[0159] According to the respective similarities calculated between each candidate neighboring area and the serving cell, the candidate neighboring area with the highest similarity is taken as the associated neighboring area. The associated neighboring area refers to the cell corresponding to the neighboring area PCI that needs to be identified, that is, the cell with site ID 13456 in step 7 is the neighboring area associated with the serving cell with PCI47 (corresponding neighboring area PCI is 7). The cell information with site ID 13456 is used to complete the first row in Table 5, as shown in Table 9.

[0160] Table 9 Completed MR acquisition information list

[0161]

[0162]

[0163] 9. Find cell information based on PCI as the associated neighboring cell

[0164] For the neighboring cell PCI that is not in the duplicate PCI list, directly use the neighboring cell PCI to search the service cell PCI in the MR collection information list or the cell MR fingerprint library, and use the service cell with the same PCI as the neighboring cell PCI as the associated neighboring cell. The associated neighboring cell refers to the cell corresponding to the neighboring cell PCI. The site ID and frequency band of the service cell found can be added to the neighboring cell site ID and neighboring cell frequency band corresponding to the neighboring cell PCI to complete Table 5.

[0165] The methods and devices provided in the various embodiments of the present application have similar principles for solving problems, so the implementation of the devices and methods can refer to each other, and the repeated parts will not be repeated.

[0166] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 4 As shown, the electronic device includes a memory 420, a transceiver 410 and a processor 400; wherein the processor 400 and the memory 420 may also be arranged physically separately.

[0167] The memory 420 is used to store computer programs; the transceiver 410 is used to send and receive data under the control of the processor 400.

[0168] Specifically, the transceiver 410 is configured to receive and send data under the control of the processor 400 .

[0169] Among them, Figure 4 In the embodiment of the present invention, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 400 and memory represented by memory 420. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described in this application. The bus interface provides an interface. The transceiver 410 may be a plurality of components, i.e., a transmitter and a receiver, providing a unit for communicating with various other devices over a transmission medium, such as a wireless channel, a wired channel, an optical cable, or the like.

[0170] The processor 400 is responsible for managing the bus architecture and general processing, and the memory 420 can store data used by the processor 400 when performing operations.

[0171] The processor 400 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor may also adopt a multi-core architecture.

[0172] The processor 400 calls the computer program stored in the memory 420 to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions, for example: obtaining measurement report MR data of multiple service cells; for the MR data of any service cell, counting the number of MR sampling points corresponding to each neighboring physical cell identifier PCI in the MR data, selecting the top N neighboring PCIs with the largest number of MR sampling points, and constructing the MR fingerprint of the service cell based on the top N neighboring PCIs; where N is an integer greater than 1; constructing a cell MR fingerprint library based on the MR fingerprints of the multiple service cells; and determining the cell corresponding to the target neighboring PCI based on the cell MR fingerprint library, where the target neighboring PCI is the neighboring PCI in the MR data of the target service cell.

[0173] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0174] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0175] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0176] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0177] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0178] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0179] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0180] In some embodiments, the method further comprises:

[0181] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0182] In some embodiments, the method further comprises:

[0183] Determine that duplicate PCIs exist in PCIs of multiple serving cells, and construct a duplicate PCI list based on the duplicate PCIs;

[0184] If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one serving cell PCI that is the same as the target neighboring cell PCI among the multiple serving cells.

[0185] It should be noted here that the above-mentioned electronic device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0186] Figure 5 A schematic diagram of the structure of the device for identifying neighboring areas based on a fingerprint library provided in an embodiment of the present application is shown as follows: Figure 5 As shown, the device includes:

[0187] An acquiring unit 500 is configured to acquire measurement report MR data of multiple serving cells;

[0188] The fingerprint construction unit 510 is configured to, for MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs, where N is an integer greater than 1.

[0189] The fingerprint library construction unit 520 is configured to construct a cell MR fingerprint library based on the MR fingerprints of multiple serving cells;

[0190] The identification unit 530 is configured to determine a cell corresponding to a target neighboring cell PCI based on the cell MR fingerprint library, where the target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

[0191] In some embodiments, constructing a MR fingerprint of a serving cell based on the first N neighboring cell PCIs includes:

[0192] The PCI set consisting of the serving cell's PCI and the first N neighboring cells' PCIs is used as the serving cell's MR fingerprint.

[0193] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0194] When there is more than one serving cell with the same PCI as the target neighboring cell PCI among multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

[0195] In some embodiments, determining the cell corresponding to the target neighboring cell PCI based on the cell MR fingerprint library includes:

[0196] Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint database; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells;

[0197] The MR fingerprint similarities between each first serving cell and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0198] In some embodiments, the identification unit 530 is further configured to:

[0199] In the case that there is only one serving cell among multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

[0200] In some embodiments, the apparatus further comprises:

[0201] a list construction unit, configured to determine whether duplicate PCIs exist in the PCIs of the plurality of serving cells, and to construct a duplicate PCI list based on the duplicate PCIs;

[0202] The determining unit is configured to determine that, if the target neighboring cell PCI is in the duplicate PCI list, there is more than one serving cell with the same PCI as the target neighboring cell among the multiple serving cells.

[0203] It should be noted that the division of units in the embodiments of the present application is schematic and is merely a logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0204] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a processor-readable storage medium. Based on such an understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0205] It should be noted that the above-mentioned device provided by the embodiments of the present application can realize all the method steps realized by the method embodiments and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments will not be described in detail.

[0206] In another aspect, the embodiments of the present application also provide a non-transitory readable storage medium, which stores a computer program. The computer program is used to make a processor execute the method for identifying a neighbor cell based on a fingerprint library provided by the above-mentioned embodiments.

[0207] It should be noted that the non-transitory readable storage medium provided by the embodiments of the present application can realize all the method steps realized by the method embodiments and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments will not be described in detail.

[0208] The non-transitory readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to a magnetic storage (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical storage (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor memory (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid-state disk (SSD)), etc.

[0209] The technical solution provided in the embodiments of the present application can be applicable to a variety of systems, especially 5G systems. For example, applicable systems may be global system of mobile communication (GSM) systems, code division multiple access (CDMA) systems, wideband code division multiple access (WCDMA) general packet radio service (GPRS) systems, long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, long term evolution advanced (LTE-A) systems, universal mobile telecommunication systems (UMTS), worldwide interoperability for microwave access (WiMAX) systems, 5G new radio (NR) systems, etc. These various systems include terminal devices and network equipment. The system may also include a core network part, such as an evolved packet system (EPS), a 5G system (5GS), etc.

[0210] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage, etc.) that contain computer-usable program code.

[0211] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0212] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor-readable memory produce an article of manufacture comprising an instruction device that implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0213] These processor-executable instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0214] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for identifying neighboring areas based on a fingerprint database, characterized in that: include: Obtain measurement report MR data of multiple serving cells; For MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs; where N is an integer greater than 1; Building a cell MR fingerprint library based on the MR fingerprints of the multiple serving cells; The cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint library, where the target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

2. The method for identifying neighboring areas based on a fingerprint database according to claim 1, characterized in that: The constructing the MR fingerprint of the serving cell based on the first N neighboring cell PCIs includes: A PCI set consisting of the PCI of the serving cell and the PCIs of the first N neighboring cells is used as the MR fingerprint of the serving cell.

3. The method for identifying neighboring areas based on a fingerprint database according to claim 1 or 2, characterized in that: The determining, based on the cell MR fingerprint library, a cell corresponding to the target neighboring cell PCI includes: In a case where there is more than one serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

4. The method for identifying neighboring areas based on a fingerprint database according to claim 3, characterized in that: The determining, based on the cell MR fingerprint library, a cell corresponding to the target neighboring cell PCI includes: Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint library; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells; MR fingerprint similarities between each of the first serving cells and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

5. The method for identifying neighboring areas based on a fingerprint database according to claim 3, characterized in that: The method further comprises: In the case that there is only one serving cell among the multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

6. The method for identifying neighboring areas based on a fingerprint database according to claim 3, characterized in that: The method further comprises: Determining that duplicate PCIs exist among the PCIs of the multiple serving cells, and constructing a duplicate PCI list based on the duplicate PCIs; If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one PCI of the serving cell that is the same as the target neighboring cell PCI among the multiple serving cells.

7. An electronic device, characterized in that: Including memory, transceiver, processor; A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations: Obtain measurement report MR data of multiple serving cells; For MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs; where N is an integer greater than 1; Building a cell MR fingerprint library based on the MR fingerprints of the multiple serving cells; The cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint library, where the target neighboring cell PCI is the neighboring cell PCI in the MR data of the target serving cell.

8. The electronic device according to claim 7, wherein: The constructing the MR fingerprint of the serving cell based on the first N neighboring cell PCIs includes: A PCI set consisting of the PCI of the serving cell and the PCIs of the first N neighboring cells is used as the MR fingerprint of the serving cell.

9. The electronic device according to claim 7 or 8, characterized in that: The determining, based on the cell MR fingerprint library, a cell corresponding to the target neighboring cell PCI includes: In a case where there is more than one serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells, the cell corresponding to the target neighboring cell PCI is determined based on the cell MR fingerprint database.

10. The electronic device according to claim 9, characterized in that The determining, based on the cell MR fingerprint library, a cell corresponding to the target neighboring cell PCI includes: Reading the MR fingerprint of the target serving cell and the MR fingerprints of all first serving cells from the cell MR fingerprint library; wherein the first serving cell is a serving cell having the same PCI as the target neighboring cell PCI among the multiple serving cells; MR fingerprint similarities between each of the first serving cells and the target serving cell are calculated respectively, and the first serving cell having the highest MR fingerprint similarity with the target serving cell is determined as the cell corresponding to the target neighboring cell PCI.

11. The electronic device according to claim 9, wherein: The operations further include: In the case that there is only one serving cell among the multiple serving cells whose PCI is the same as the target neighboring cell PCI, the only serving cell is determined as the cell corresponding to the target neighboring cell PCI.

12. The electronic device according to claim 9, wherein: The operations further include: Determining that duplicate PCIs exist among the PCIs of the multiple serving cells, and constructing a duplicate PCI list based on the duplicate PCIs; If the target neighboring cell PCI is in the duplicate PCI list, it is determined that there is more than one PCI of the serving cell that is the same as the target neighboring cell PCI among the multiple serving cells.

13. A device for identifying neighboring areas based on a fingerprint database, characterized in that: include: an acquiring unit, configured to acquire measurement report MR data of a plurality of serving cells; a fingerprint construction unit, configured to, for MR data of any serving cell, count the number of MR sampling points corresponding to each neighboring physical cell identifier (PCI) in the MR data, select the top N neighboring PCIs with the largest number of MR sampling points, and construct the MR fingerprint of the serving cell based on the top N neighboring PCIs; wherein N is an integer greater than 1; A fingerprint library construction unit, configured to construct a cell MR fingerprint library based on the MR fingerprints of the multiple serving cells; An identification unit is configured to determine a cell corresponding to a target neighboring cell PCI based on the cell MR fingerprint library, where the target neighboring cell PCI is a neighboring cell PCI in the MR data of the target serving cell.

14. A non-transitory readable storage medium, characterized in that The non-transitory readable storage medium stores a computer program, and the computer program is used to enable a processor to execute the method according to any one of claims 1 to 6.

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