Cell parameter adjustment method and device and storage medium
By obtaining the cell load index in the mobile communication network, determining high-load cells and establishing optimization clusters, adjusting broadcast beam weights, the problem of inter-cell load balancing is solved and the network experience is improved.
Patent Information
- Application Number
- CN202311324325.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-10-12
- Publication Date
- 2025-04-22
AI Technical Summary
The prior art is difficult to achieve inter-cell load balancing, especially when the mechanical parameters of the base station cannot be adjusted frequently.
By obtaining the load index of the cell, a high-load cell is determined and an optimization cluster is established based on its overlapping information. Then, according to the preset candidate configuration parameters, the broadcast beam weights of each target cell in the cluster are adjusted and optimized to achieve load balancing effect.
It realizes load balancing between cells, improves the network experience of user equipment in the target cell, and avoids the limitation of frequent adjustment of base station mechanical parameters.
Smart Images
Figure CN119865829A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of mobile communication technology, and in particular to a method, device and storage medium for adjusting cell parameters. Background Art
[0002] The loads in different areas of the network are different, and the load in the same area will also change over time. In order to cope with high load conditions in the network, related technologies usually adjust the pilot transmission power and the mechanical downtilt angle of the base station to shrink the coverage of high-load cells and expand the coverage of low-load neighboring cells, thereby achieving the purpose of load balancing. However, adjusting the pilot transmission power can only change the coverage of the cell, but cannot change the direction of the cell; although adjusting the mechanical downtilt angle of the antenna can change the direction of the cell to a certain extent, it cannot be adjusted frequently in real time according to changes in load. There is an urgent need for a cell parameter adjustment method that can effectively and flexibly achieve load balancing between cells. Summary of the invention
[0003] The embodiments of the present invention provide a method, device and storage medium for adjusting cell parameters, aiming to solve the problem of load imbalance among multiple cells.
[0004] In a first aspect, an embodiment of the present invention provides a method for adjusting cell parameters, including:
[0005] Acquire a load index of at least one cell, and determine a high-load cell from at least one of the cells according to the load index;
[0006] Determine the optimized cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell;
[0007] Determining target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric values corresponding to the preset candidate configuration parameters;
[0008] The broadcast beam weight of each target cell is adjusted according to the target configuration parameter.
[0009] In a second aspect, an embodiment of the present invention further provides a cell parameter adjustment device, which includes a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing connection and communication between the processor and the memory, wherein when the computer program is executed by the processor, the steps of any cell parameter adjustment method provided in the embodiments of the present invention are implemented.
[0010] In a third aspect, an embodiment of the present invention further provides a storage medium for computer-readable storage, characterized in that the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any cell parameter adjustment method provided in an embodiment of the present invention.
[0011] The embodiment of the present invention provides a method, device and storage medium for adjusting cell parameters. The embodiment of the present invention obtains the load index of at least one cell, and determines a high-load cell from at least one of the cells according to the load index; determines the optimization cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell; determines the target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric corresponding to the preset candidate configuration parameters; and adjusts the broadcast beam weights of each target cell according to the target configuration parameters. Since the mechanical parameters of the base station cannot be adjusted frequently, the technical solution of the present application adjusts the broadcast beam weights of the target cells in the optimization cluster to achieve the effect of load balancing between target cells, thereby improving the network experience of user devices residing in each target cell. BRIEF DESCRIPTION OF THE DRAWINGS
[0012] Figure 1 A schematic diagram of a step flow of a method for adjusting cell parameters provided by an embodiment of the present invention;
[0013] Figure 2 for Figure 1 A schematic flow chart of sub-steps of a method for determining a high-load cell;
[0014] Figure 3 for Figure 1 A schematic flow chart of the sub-steps of determining the optimization cluster method;
[0015] Figure 4 for Figure 1 A schematic flow chart of sub-steps of a method for determining target configuration parameters;
[0016] Figure 5 A schematic block diagram of the structure of a cell parameter adjustment device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0018] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.
[0019] It should be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.
[0020] The embodiment of the present invention provides a method, device and storage medium for adjusting cell parameters. The method for adjusting cell parameters can be applied to a mobile terminal, which can be an electronic device such as a mobile phone, a tablet computer, a laptop computer, a desktop computer, a personal digital assistant and a wearable device.
[0021] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.
[0022] Please refer to Figure 1 , Figure 1 A schematic flow chart of the steps of a method for adjusting cell parameters provided by an embodiment of the present invention.
[0023] like Figure 1 As shown, the cell parameter adjustment method includes steps S101 to S104.
[0024] Step S101: Obtain a load index of at least one cell, and determine a high-load cell from at least one of the cells according to the load index.
[0025] In the existing mobile communication network, a cell may have a large number of users, resulting in poor communication quality in the cell, while the neighboring cells around the cell have fewer users, resulting in an unbalanced load between different cells. In order to avoid this unbalanced load, when a high-load cell with a high load index is detected in the network, an optimization cluster is established based on the high-load cell to adjust the broadcast beam weight of the target cell in the optimization cluster, and the resident users of the high-load cell are shared by other cells in the optimization cluster to achieve a load balancing effect.
[0026] Please refer to Figure 2 , Figure 2 for Figure 1 Schematic diagram of the sub-step flow chart of the method for determining high-load cells.
[0027] like Figure 2 As shown, in some embodiments, step S101 obtains the load index of at least one cell, and determines a high-load cell from at least one of the cells based on the load index, including: step S1011, obtaining the number of resident users and physical resource block utilization of at least one cell, the physical resource block utilization including: at least one of uplink physical resource block utilization and downlink physical resource block utilization; step S1012, when the number of resident users is greater than a preset number of users and the physical resource utilization is greater than a preset utilization, determining the cell as a high-load cell.
[0028] Exemplarily, the number of resident users and the utilization rate of physical resource blocks (PRB) of each cell are monitored, which can be real-time monitoring or periodic monitoring, for example, the load index is monitored at a granularity of 15 minutes. Specifically, the number of resident users and the PRB utilization rate of a cell can reflect the load level of the cell. It can be understood that the more resident users a cell has, the higher the load of the cell; the higher the PRB utilization rate of a cell, the higher the load of the cell.
[0029] For example, the preset number of users may be 200, and the preset utilization rate may be 0.7, but this is certainly not limited thereto and is not limited here.
[0030] Exemplarily, the PRB utilization includes at least one of an uplink PRB utilization and a downlink PRB utilization. It can be understood that when the number of resident users is greater than the preset number of users and the physical resource utilization is greater than the preset utilization, the cell is determined as a high-load cell, including: when the number of resident users is greater than the preset number of users, and the uplink PRB utilization and / or downlink PRB utilization is greater than the preset utilization, the cell is determined as a high-load cell. Among them, the uplink PRB utilization and the downlink PRB utilization can correspond to the same preset utilization, or different preset utilizations can be set for the uplink PRB utilization and the downlink PRB utilization, respectively, which is not limited here.
[0031] In some embodiments, after step S101 obtains the load index of at least one cell and determines a high-load cell from at least one of the cells based on the load index, it also includes: determining a current load vector of the high-load cell based on the load index of the high-load cell; obtaining a historical load vector of the high-load cell, and determining whether the high-load cell is a periodic high-load cell or a sudden high-load cell based on the historical load vector and the current load vector.
[0032] Exemplarily, cells with high loads can be divided into periodic high load cells and sudden high load cells. For example, the network load in residential and office areas changes regularly over time, and the high load cells in such areas belong to periodic high load cells; while the network load in places such as stadiums will change suddenly due to concerts, large exhibitions, etc., and the high load cells in such areas belong to sudden high load cells.
[0033] Exemplarily, when the cell experiencing high load is a sudden high load cell, the target configuration parameters of each target cell in the optimization cluster are optimized under the current situation; and for periodic high load cells, it is only necessary to optimize the target configuration parameters of each target cell in the optimization cluster when the high load situation is first detected in the cell. When the high load situation occurs again in the same time period, the target configuration parameters obtained by the previous optimization can be used to adjust the broadcast beam weight of the target cell. By distinguishing between periodic high load cells and sudden high load cells, it is avoided to repeatedly determine the target configuration parameters of the optimization cluster for cells that periodically experience high load situations, and the calculation amount of the cell parameter adjustment method provided in the embodiment of the present application is reduced.
[0034] Exemplarily, after determining the current load vector, the vector correlation between the current load vector and the historical load vector preset in the high-load cell in the time period is calculated, and whether the high load situation in the high-load cell is periodic is determined according to the magnitude of the vector correlation. Specifically, when the vector correlation between the current load vector and the historical load vector is greater than a first correlation threshold, it is determined that the high-load cell is a periodic high-load cell; otherwise, it is determined that the high-load cell is a sudden high-load cell. The first correlation threshold may be, for example, 0.6.
[0035] In some embodiments, obtaining the historical load vector of the high-load cell includes: obtaining a first average load index of the high-load cell in at least one high-load historical time period, and determining the time period load vector of the high-load historical time period based on the first average load index; merging the high-load historical time periods based on the vector correlation of the load vectors of each time period to obtain a high-load merged time period; and determining the time period load vector of the high-load merged time period as the historical load vector based on the second average load index within the high-load merged time period.
[0036] Exemplarily, the historical load vector of the high-load cell is calculated at an hourly granularity to obtain the historical load vector corresponding to the high-load cell every hour, wherein the calculation method of the historical load vector can refer to the current load vector, which is not elaborated here.
[0037] Exemplarily, after determining the first average load index in at least one high-load historical time period of the high-load cell, for example, after determining the first average load index in each hour of a week, these high-load historical time periods are merged. Specifically, the correlation between the historical load vectors corresponding to adjacent high-load time periods is determined, and the high-load time periods whose correlation of the historical load vectors is greater than a second correlation threshold are merged into one high-load merged time period. The second correlation threshold may be, for example, 0.75.
[0038] Exemplarily, for the high-load merging time period obtained by merging, the historical load vector within the high-load merging time period is recalculated.
[0039]
[0040] Among them, α1, α2, α3, α4 are preset weights respectively, grid 1, ..., grid x is at least one grid obtained by dividing the physical area where the cell is located, and the number of users in grid 1, ..., grid x is the number of users resident in the corresponding grid obtained by division. Specifically, for the current load vector S, it is obtained by substituting the current number of users, uplink PRB utilization, downlink PRB utilization and the number of users in each grid into the expression of the load vector s; for the historical load vector S', it is obtained by substituting the average number of users in the historical time period, uplink PRB utilization, downlink PRB utilization and the number of users in each grid into the expression of the load vector s, for example, the average number of users, uplink PRB utilization, downlink PRB utilization and the number of users in each grid in one hour.
[0041] Step S102: Determine the optimized cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell.
[0042] Exemplarily, by jointly optimizing the target configuration parameters of the target cells in the optimization cluster, a portion of the resident users of the high-load cell are moved to other cells in the optimization cluster to achieve load balancing. Therefore, it is necessary to determine the target cell that belongs to the same optimization cluster as the high-load cell.
[0043] Exemplarily, the overlapping information includes: a first signal strength of the target user equipment in the high-load cell, a second signal strength of the target user equipment in a cell adjacent to the high-load cell, and a load index of a cell adjacent to the high-load cell, wherein the target user equipment is a user equipment residing in the high-load cell.
[0044] Please refer to Figure 3 , Figure 3 for Figure 1 Schematic diagram of the sub-steps flow of determining the optimized cluster method in .
[0045] like Figure 3 As shown, in some embodiments, step S102 determines the optimization cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell, including: step S1021, determining the target neighboring cell that together with the high-load cell constitutes the optimization cluster according to the first signal strength, the second signal strength, and the load index of the adjacent cell; step S1022, determining the optimization cluster corresponding to the high-load cell according to the target neighboring cell and the high-load cell.
[0046] Exemplarily, the target neighboring cells constituting the optimization cluster should have a lower load index, and the second signal strength of the target user equipment in the target neighboring cells is close to the first signal strength in the high-load cell. Therefore, based on the first signal strength, the second signal strength, and the load index of the adjacent cells, the target neighboring cells that together with the high-load cells form the optimization cluster are determined.
[0047] Exemplarily, the target neighboring cell and the high-load cell are jointly determined as the target cell in the optimization cluster, so as to jointly optimize the target configuration parameters of the target neighboring cell and the high-load cell.
[0048] In some embodiments, determining the target neighboring cell that forms an optimization cluster together with the high-load cell based on the first signal strength, the second signal strength, and the load index of the neighboring cell includes: calculating the difference between the second signal strength and the first signal strength; determining the target neighboring cell that forms an optimization cluster together with the high-load cell based on the difference between the second signal strength and the first signal strength and the load index of the neighboring cell.
[0049] Exemplarily, the difference between the second signal strength and the first signal strength is calculated, and a neighboring cell whose difference between the second signal strength and the first signal strength is greater than a preset difference and whose load index is less than a preset load index is determined as a target neighboring cell.
[0050] For example, since the target neighboring cell needs to share the resident users of the high-load cell, the target neighboring cell needs to have a lower load index. The load index can be determined based on at least one of the number of resident users and PRB utilization, or based on user business volume, historical traffic, etc., which is not limited here.
[0051] For example, if the difference between the second signal strength and the first signal strength of the target user equipment is greater than the preset difference, it means that the signal strength of the target user equipment in the adjacent cell is similar to the signal strength of the target user equipment in the high-load cell, and the broadcast weight of the adjacent cell can be adjusted so that the adjacent cell is used to share the resident users of the high-load cell, so the adjacent cell is determined as the target adjacent cell. The preset difference can be set according to actual needs, for example, it can be 6dB, of course, it is not limited to this, and is not limited here.
[0052] For example, a target user device whose difference between the second signal strength and the first signal strength is greater than a preset difference is determined as a disturbed user device of an adjacent cell, and the target adjacent cell is determined based on the number of disturbed user devices of each adjacent cell in the high-load cell and the load index of the adjacent cell. For example, at least one adjacent cell with the lowest load index among the top N adjacent cells with the largest number of disturbed user devices in the high-load cell is determined as a target adjacent cell, or at least one adjacent cell with the largest number of disturbed user devices in the high-load cell among the M adjacent cells with the lowest load index is determined as a target adjacent cell. No limitation is made here.
[0053] In some embodiments, the target neighboring cell that forms an optimization cluster together with the high-load cell is determined based on the difference between the second signal strength and the first signal strength and the load index of the neighboring cell, including: determining the interference level of the neighboring cell to the target user equipment residing in the high-load cell based on the difference between the second signal strength and the first signal strength; determining the number of disturbed user equipment corresponding to each interference level based on the interference level caused by the neighboring cell to each target user equipment in the high-load cell; determining the target neighboring cell that forms an optimization cluster together with the high-load cell based on the load index of each neighboring cell and the number of disturbed user equipment corresponding to each interference level of each neighboring cell.
[0054] Exemplarily, there are usually multiple target user devices residing in a high-load cell, and there may be more than one target user device for which the difference between the second signal strength and the first signal strength is greater than a preset difference. In order to more reasonably determine the target neighboring area, the interference level of each target user device can be determined according to the difference between the second signal strength and the first signal strength, and then the target neighboring area can be determined according to the number of target user devices corresponding to different interference levels of each adjacent cell.
[0055] Exemplarily, the greater the difference between the second signal strength and the first signal strength, the higher the interference level of the target user equipment. Specifically, a difference threshold can be set for each interference level. For example, if the difference between the second signal strength and the first signal strength is between 6dB-8dB, the interference level of the target user equipment is determined to be the first interference level; if the difference between the second signal strength and the first signal strength is between 8dB-10dB, the interference level of the target user equipment is determined to be the second interference level, and so on.
[0056] Exemplarily, if the number of disturbed user devices in adjacent cells is the same, the target adjacent area is determined by comparing the corresponding maximum disturbance levels of the adjacent cells; if the corresponding maximum disturbance levels of the adjacent cells are the same, the target adjacent area is determined by comparing the number of disturbed user devices at the maximum disturbance level.
[0057] Step S103: According to the target coverage and load balancing metric values corresponding to the preset candidate configuration parameters, the target configuration parameters of each target cell in the optimization cluster are determined from the candidate configuration parameters.
[0058] Exemplarily, after determining the target cell in the optimization cluster, configuration parameter optimization is performed for the target cell to determine target configuration parameters that enable the target neighboring cell to share the resident users of the high-load cell.
[0059] Exemplarily, based on a preset intelligent search algorithm, the load index of each target cell under each set of candidate configuration parameters is predicted, and the target configuration parameters that make the load index of each target cell reach a balance are determined. The intelligent search algorithm may be an ant colony algorithm, a particle swarm algorithm, etc., which are not limited here.
[0060] Please refer to Figure 4 , Figure 4 for Figure 1 Schematic diagram of the sub-step flow of the method for determining target configuration parameters in .
[0061] like Figure 4 As shown, in some embodiments, step S103 determines the target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric values corresponding to preset candidate configuration parameters, including: determining the target coverage according to the target signal strength of each user equipment residing in the optimization cluster; determining the load balancing metric value according to the load index of each target cell in the optimization cluster; and determining the candidate configuration parameter with the largest load balancing metric value as the target configuration parameter among the candidate configuration parameters whose target coverage is greater than the current coverage.
[0062] Exemplarily, the purpose of the cell parameter adjustment method provided in the embodiment of the present application is to balance the load index between the target cells after the configuration parameters are adjusted. Therefore, the degree of balance of the load index can be quantified by the variance, the variance of the load index of each target cell is calculated, and the inverse of the variance is determined as the load balancing measurement value.
[0063] Of course, it is not limited to this. The load balancing degree can also be the load retention ratio of the high-load cell, that is, the ratio of the load index of the high-load cell under the candidate configuration parameters to the load index under the current configuration parameters, which is not limited here.
[0064] Exemplarily, in order to ensure the network experience of user equipment residing in the target cell, the target cell after adjusting the configuration parameters also needs to ensure that the coverage is maintained at a certain level. For example, the target coverage under the target configuration parameters cannot be less than the current coverage before adjustment. Therefore, the target configuration parameters are determined among the candidate configuration parameters whose target coverage is greater than the current coverage. Among them, the target coverage is determined based on the target signal strength of each user equipment residing in the optimization cluster, and the target signal strength of each user equipment under the candidate configuration parameters is predicted, and the target coverage is calculated based on the ratio of the target signal strength greater than the signal strength threshold. The target signal strength can be, for example, the reference signal receiving power (RSRP) of the user equipment under the candidate configuration parameters.
[0065] Exemplarily, the target signal strength is determined by comparing the RSRP variation of the user equipment under the candidate configuration parameters and the current RSRP of the user equipment under the current configuration parameters. Specifically, the target signal strength is equal to the sum of the current RSRP and the RSRP variation.
[0066] For example, taking the optimization of the configuration parameters of cells 1, 2, and 3 in the optimization cluster by using the ant colony algorithm as an example, the current configuration parameters of cells 1, 2, and 3 are recorded as W his = {W 1,his ,W 2,his ,W 3,his}, and obtain at least one set of candidate configuration parameters W of cell 1, cell 2 and cell 3 new = {W 1,new ,W 2,new ,W 3,new}, where the current configuration parameters and candidate configuration parameters include broadcast beam azimuth, broadcast beam downtilt, horizontal beam width, vertical beam width and power, etc. Set the ant colony algorithm parameters, including the number of ants, number of iterations, pheromone volatilization factor, pheromone concentration initial value and heuristic function initial value, etc., and use ants to traverse each group of candidate configuration parameters. The target signal strength of user equipment m relative to cell n under the candidate configuration parameters is predicted, where RSRP m,n,his 、RSRP m,n,new They represent the current signal strength under the current configuration parameters and the target signal strength under the candidate configuration parameters respectively. Respectively represent the antenna gain under the current configuration parameters and the antenna gain under the candidate configuration parameters, HDOA and VDOA represent the horizontal direction of arrival and the vertical direction of arrival respectively. According to the target signal strength, the cell where each user equipment resides under the candidate configuration parameters is predicted, and the target coverage and load balancing metric value under the candidate configuration parameters are determined according to the target signal strength of the cell where each user equipment resides under the candidate configuration parameters. The pheromone concentration of the ants, such as pheromone, is calculated according to the load balancing metric value. in represents the load index of cell n under the candidate configuration parameters, It represents the load index of cell n under the current configuration parameters. After all candidate configuration parameters are traversed, among the candidate configuration parameters whose target coverage is greater than the current coverage, the candidate configuration parameter corresponding to the ant with the largest pheromone is selected as the target configuration parameter.
[0067] Step S104: Adjust the broadcast beam weight of each target cell according to the target configuration parameters.
[0068] In the related art, the coverage of the target cell is usually adjusted by adjusting the mechanical parameters of the base station. For example, by adjusting the mechanical downtilt angle of the base station antenna, the coverage of the high-load cell is reduced and the coverage of the low-load neighboring cell is expanded, thereby achieving the purpose of load balancing. However, the load of the cell changes all the time, and the mechanical parameters of the base station cannot be adjusted frequently, making it difficult for the coverage of the base station to change according to the actual situation. The cell parameter adjustment method provided in the embodiment of the present application achieves the purpose of load balancing by adjusting the broadcast beam weight of the cell, and the value of the broadcast beam weight can be adjusted frequently according to actual needs.
[0069] The broadcast beam weight may include the broadcast beam azimuth, broadcast beam downtilt, horizontal beam width, vertical beam width and power, etc., which are not limited here.
[0070] See also Figure 5 , Figure 5 A schematic block diagram of the structure of a cell parameter adjustment device provided in an embodiment of the present invention.
[0071] like Figure 5 As shown, the cell parameter adjustment device 300 includes a processor 301 and a memory 302, and the processor 301 and the memory 302 are connected via a bus 303, such as an I2C (Inter-integrated Circuit) bus.
[0072] Specifically, the processor 301 is used to provide computing and control capabilities to support the operation of the entire cell parameter adjustment device. The processor 301 can be a central processing unit (CPU), and the processor 301 can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.
[0073] Specifically, the memory 302 may be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a mobile hard disk.
[0074] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the embodiment of the present invention, and does not constitute a limitation on the cell parameter adjustment device to which the embodiment of the present invention is applied. The specific cell parameter adjustment device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0075] The processor is used to run a computer program stored in the memory, and implement any one of the cell parameter adjustment methods provided by the embodiments of the present invention when executing the computer program.
[0076] In one embodiment, the processor is used to run a computer program stored in the memory, and implements the following steps when executing the computer program:
[0077] Acquire a load index of at least one cell, and determine a high-load cell from at least one of the cells according to the load index;
[0078] Determine the optimized cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell;
[0079] Determining target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric values corresponding to the preset candidate configuration parameters;
[0080] The broadcast beam weight of each target cell is adjusted according to the target configuration parameter.
[0081] In one embodiment, when the processor implements the determining of the optimized cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell, the processor is configured to implement:
[0082] Determine, according to the first signal strength, the second signal strength, and the load index of the neighboring cell, a target neighboring cell that together with the high-load cell forms an optimized cluster;
[0083] An optimized cluster corresponding to the high-load cell is determined according to the target neighboring cell and the high-load cell.
[0084] In one embodiment, when the processor implements determining the target neighboring cell that forms an optimized cluster together with the high-load cell according to the first signal strength, the second signal strength, and the load index of the neighboring cell, it is configured to implement:
[0085] Calculating a difference between the second signal strength and the first signal strength;
[0086] A target neighboring cell that forms an optimized cluster together with the high-load cell is determined according to the difference between the second signal strength and the first signal strength and the load index of the neighboring cell.
[0087] In one embodiment, when the processor implements determining the target neighboring cell that forms an optimized cluster together with the high-load cell according to the difference between the second signal strength and the first signal strength and the load index of the neighboring cell, it is configured to implement:
[0088] Determining, according to a difference between the second signal strength and the first signal strength, an interference level of the neighboring cell to a target user equipment residing in the high-load cell;
[0089] Determining the number of disturbed user equipment corresponding to each disturbance level according to the disturbance level caused by the neighboring cell to each target user equipment in the high-load cell;
[0090] According to the load index of each adjacent cell and the number of disturbed user equipments corresponding to each adjacent cell at each disturbance level, a target adjacent cell that forms an optimized cluster together with the high-load cell is determined.
[0091] In one embodiment, after obtaining the load index of at least one cell and determining a high-load cell from at least one cell according to the load index, the processor is configured to implement:
[0092] Determining a current load vector of the high-load cell according to the load index of the high-load cell;
[0093] A historical load vector of the high-load cell is obtained, and according to the historical load vector and the current load vector, it is determined whether the high-load cell is a periodic high-load cell or a sudden high-load cell.
[0094] In one embodiment, when the processor implements the acquiring of the historical load vector of the high-load cell, the processor is configured to implement:
[0095] Acquire a first average load index of the high-load cell in at least one high-load historical time period, and determine a time period load vector of the high-load historical time period according to the first average load index;
[0096] According to the vector correlation of the load vectors of each time period, the high load historical time periods are merged to obtain a high load merged time period;
[0097] According to the second average load index in the high load merging time period, a time period load vector of the high load merging time period is determined as the historical load vector.
[0098] In one embodiment, when the processor determines the target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric value corresponding to the preset candidate configuration parameters, it is used to implement:
[0099] Determining the target coverage rate according to the target signal strength of each user equipment residing in the optimization cluster;
[0100] Determining the load balancing metric value according to the load index of each target cell in the optimization cluster;
[0101] Among the candidate configuration parameters whose target coverage is greater than the current coverage, the candidate configuration parameter with the largest load balancing metric value is determined as the target configuration parameter.
[0102] In one embodiment, when the processor implements the acquiring of the load index of at least one cell and determining a high-load cell from at least one of the cells according to the load index, it is configured to implement:
[0103] Acquire the number of resident users and physical resource block utilization of at least one cell, wherein the physical resource block utilization includes at least one of an uplink physical resource block utilization and a downlink physical resource block utilization;
[0104] When the number of resident users is greater than a preset number of users and the physical resource utilization rate is greater than a preset utilization rate, the cell is determined as a high-load cell.
[0105] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the cell parameter adjustment device described above can refer to the corresponding process in the aforementioned cell parameter adjustment method embodiment, and will not be repeated here.
[0106] An embodiment of the present invention also provides a storage medium for computer-readable storage, wherein the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any cell parameter adjustment method provided in the embodiment of the present invention.
[0107] The storage medium may be an internal storage unit of the cell parameter adjustment device described in the foregoing embodiment, such as a hard disk or memory of the cell parameter adjustment device. The storage medium may also be an external storage device of the cell parameter adjustment device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the cell parameter adjustment device.
[0108] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.
[0109] The serial numbers of the embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.
Claims
1. A method for adjusting cell parameters, characterized in that: include: Acquire a load index of at least one cell, and determine a high-load cell from at least one of the cells according to the load index; Determine the optimized cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell; Determining target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric values corresponding to the preset candidate configuration parameters; The broadcast beam weight of each target cell is adjusted according to the target configuration parameter.
2. The method for adjusting cell parameters according to claim 1, characterized in that: The overlapping information includes a first signal strength of a target user equipment in the high-load cell, a second signal strength of a neighboring cell of the high-load cell, and a load index of the neighboring cell. The target user equipment is a user equipment residing in the high-load cell. The determining the optimization cluster to which the high-load cell belongs based on the overlapping information corresponding to the high-load cell includes: Determine, according to the first signal strength, the second signal strength, and the load index of the neighboring cell, a target neighboring cell that together with the high-load cell forms an optimized cluster; An optimized cluster corresponding to the high-load cell is determined according to the target neighboring cell and the high-load cell.
3. The method for adjusting cell parameters according to claim 2, characterized in that: The determining, according to the first signal strength, the second signal strength, and the load index of the neighboring cell, a target neighboring cell that together with the high-load cell forms an optimized cluster, includes: Calculating a difference between the second signal strength and the first signal strength; A target neighboring cell that forms an optimized cluster together with the high-load cell is determined according to the difference between the second signal strength and the first signal strength and the load index of the neighboring cell.
4. The method for adjusting cell parameters according to claim 3, characterized in that: The determining, according to the difference between the second signal strength and the first signal strength and the load index of the neighboring cell, a target neighboring cell that forms an optimized cluster together with the high-load cell includes: Determining, according to a difference between the second signal strength and the first signal strength, an interference level of the neighboring cell to a target user equipment residing in the high-load cell; Determining the number of disturbed user equipment corresponding to each disturbance level according to the disturbance level caused by the neighboring cell to each target user equipment in the high-load cell; According to the load index of each adjacent cell and the number of disturbed user equipments corresponding to each adjacent cell at each disturbance level, a target adjacent cell that forms an optimized cluster together with the high-load cell is determined.
5. The method for adjusting cell parameters according to claim 1, characterized in that: After acquiring the load index of at least one cell and determining a high-load cell from at least one cell according to the load index, the method further includes: Determining a current load vector of the high-load cell according to the load index of the high-load cell; A historical load vector of the high-load cell is obtained, and according to the historical load vector and the current load vector, it is determined whether the high-load cell is a periodic high-load cell or a sudden high-load cell.
6. The method for adjusting cell parameters according to claim 5, characterized in that: The obtaining of the historical load vector of the high-load cell includes: Acquire a first average load index of the high-load cell in at least one high-load historical time period, and determine a time period load vector of the high-load historical time period according to the first average load index; According to the vector correlation of the load vectors of each time period, the high load historical time periods are merged to obtain a high load merged time period; According to the second average load index in the high load merging time period, a time period load vector of the high load merging time period is determined as the historical load vector.
7. The method for adjusting cell parameters according to claim 1, characterized in that: The step of determining target configuration parameters of each target cell in the optimization cluster from the candidate configuration parameters according to the target coverage and load balancing metric values corresponding to the preset candidate configuration parameters includes: Determining the target coverage rate according to the target signal strength of each user equipment residing in the optimization cluster; Determining the load balancing metric value according to the load index of each target cell in the optimization cluster; Among the candidate configuration parameters whose target coverage is greater than the current coverage, the candidate configuration parameter with the largest load balancing metric value is determined as the target configuration parameter.
8. The method for adjusting cell parameters according to any one of claims 1 to 7, characterized in that: The acquiring of the load index of at least one cell and determining a high-load cell from at least one cell according to the load index comprises: Acquire the number of resident users and physical resource block utilization of at least one cell, wherein the physical resource block utilization includes at least one of an uplink physical resource block utilization and a downlink physical resource block utilization; When the number of resident users is greater than a preset number of users and the physical resource utilization rate is greater than a preset utilization rate, the cell is determined as a high-load cell.
9. A cell parameter adjustment device, characterized in that: The cell parameter adjustment device includes a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing connection and communication between the processor and the memory, wherein when the computer program is executed by the processor, the steps of the cell parameter adjustment method according to any one of claims 1 to 8 are implemented.
10. A storage medium for computer-readable storage, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the cell parameter adjustment method according to any one of claims 1 to 8.