Resource allocation method and device, equipment, storage medium and program product

Abstract

The invention discloses a resource allocation method and device, equipment, a storage medium and a program product, and the method comprises the steps: respectively quantifying the configuration information of a to-be-allocated resource and the network configuration index of a target cell into a resource quantized value and a network quantized value, and then carrying out the matching of the to-be-allocated resource and a to-be-allocated region based on the resource quantized value and the network quantized value. And allocating the to-be-allocated resources to all cells in the to-be-allocated area. In the resource allocation process, the quantitative data is used as a drive for matching, so that subjective judgment depending on artificial experience is avoided, the matching of the resource and the cell demand is more in line with the actual situation, and the rationality of resource allocation is improved. Besides, resources of different specifications can be distributed more reasonably based on the matching of the quantized values, the contradiction between high-specification resource shortage and low-specification resource idling is avoided, the use efficiency of the stock resources of the existing network can be effectively improved, and the maximum utilization of the stock resources is promoted.

Description

Technical Field

[0001] The present invention relates to the field of communications, and in particular to a resource allocation method, apparatus, device, storage medium and program product. Background Art

[0002] As 5G network construction progresses, new investment in 4G networks is declining annually. Operation and maintenance strategies are shifting from "incremental construction" to "leveraging existing resources," reducing costs and improving efficiency through the reuse of existing resources. Among existing 4G network resources, RRUs (Remote Radio Units) come in a wide variety of specifications and demand scenarios. Therefore, achieving efficient utilization of RRU resources in various demand scenarios is crucial for network operations and maintenance. Existing technologies lack unified rules for the utilization of existing RRU resources, relying instead on subjective judgment based on the experience of optimization engineers. These engineers tend to prioritize high-specification RRUs (e.g., high-power, multi-port) due to their perceived compatibility and future adaptability, ignoring the fact that lower-specification equipment may actually meet real-world requirements. This overuse of high-specification RRUs rapidly depletes existing inventory, leaving resources unavailable for scenarios where they are truly needed (e.g., wide-coverage macro sites). This also leaves lower-specification equipment (e.g., low-power, single-port) idle and underutilized. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a resource allocation method, apparatus, device, storage medium and program product, which can effectively improve the utilization efficiency of existing network resources and make the allocation of existing network resources more reasonable.

[0004] To achieve the above objectives, an embodiment of the present invention provides a resource allocation method, comprising:

[0005] Obtaining resource configuration information of at least one resource to be allocated, and quantifying the resource configuration information to obtain a resource quantization value;

[0006] Obtaining network configuration indicators of all target cells in at least one area to be allocated, and quantifying the network configuration indicators to obtain a network quantization value of the area to be allocated; wherein the area to be allocated includes at least one target cell;

[0007] The resource to be allocated and the area to be allocated are matched according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

[0008] As an improvement to the above solution, the resource configuration information includes at least one of the following information:

[0009] Device time attributes;

[0010] Equipment performance parameters, including at least one of single-channel power, equivalent bandwidth, average time advance, and number of carriers.

[0011] As an improvement to the above solution, quantizing the resource configuration information to obtain a resource quantization value includes:

[0012] Obtain resource configuration information of the same type among all resources to be allocated, and sort the resource configuration information of the same type;

[0013] quantifying the sorted resource configuration information to obtain at least two reference quantization values;

[0014] The resource quantization value of each resource configuration information is determined according to the reference quantization value.

[0015] As an improvement to the above solution, the sorted resource configuration information is quantized to obtain at least two reference quantization values, including:

[0016] Dividing the sorted resource configuration information into at least two data sets;

[0017] Assigning first sort numbers to the at least two divided data sets in order from left to right;

[0018] According to the ascending order of the first sorting numbers, each data set is assigned a value in an incremental assignment manner to obtain a reference quantization value of each data set.

[0019] As an improvement to the above solution, determining the resource quantization value of each resource configuration information according to the reference quantization value includes:

[0020] For each resource configuration information, index the corresponding target data set from all data sets;

[0021] The reference quantization value of the target data set is used as the resource quantization value of the resource configuration information.

[0022] As an improvement to the above solution, obtaining network configuration indicators of all target cells in at least one area to be allocated includes:

[0023] Obtaining the benchmark indicators and at least two indicators to be evaluated for all target cells in the area to be allocated;

[0024] Obtaining a correlation value between each indicator to be evaluated and the benchmark indicator;

[0025] The benchmark indicator and the indicator to be evaluated whose correlation value meets the set conditions are used as the network configuration indicator.

[0026] As an improvement to the above scheme, the benchmark indicator includes a first indicator related to the cell coverage requirement and a second indicator related to the cell capacity requirement; the indicator to be evaluated includes at least one first performance indicator corresponding to the first indicator, and at least one second performance indicator corresponding to the second indicator.

[0027] As an improvement to the above solution, quantifying the network configuration indicator to obtain the network quantization value of the area to be allocated includes:

[0028] Acquire sampling data of the same type of network configuration indicators in all target cells in the area to be allocated, and sort the sampling data of the same type of network configuration indicators;

[0029] quantizing the sorted sample data to obtain at least two standard quantization values;

[0030] Determine the indicator quantization value corresponding to each network configuration indicator according to the standard quantization value;

[0031] The index quantization values ​​corresponding to all target cells in the area to be allocated are added together to obtain the network quantization value of the area to be allocated.

[0032] As an improvement to the above solution, the sorted sampled data is quantized to obtain at least two standard quantization values, including:

[0033] Dividing the sorted sampled data into at least two data groups;

[0034] The sampled data in each data group are averaged and aggregated to obtain at least two segmentation points;

[0035] Segmenting the sorted sampled data using the segmentation points to obtain at least three quantization intervals;

[0036] assigning second ranking numbers to the at least three divided quantization intervals in order from left to right;

[0037] According to the ascending order of the second sort numbers, each quantization interval is assigned a value in an increasing manner to obtain a standard quantization value of each quantization interval.

[0038] As an improvement to the above solution, determining the indicator quantization value corresponding to each network configuration indicator according to the standard quantization value includes:

[0039] For each network configuration indicator, index the corresponding target quantization interval from all quantization intervals;

[0040] The standard quantization value of the target quantization interval is used as the indicator quantization value corresponding to the network configuration indicator.

[0041] As an improvement to the above solution, matching the resource to be allocated and the area to be allocated according to the resource quantization value and the network quantization value includes:

[0042] Determining coverage capability quantification values ​​and capacity capability quantification values ​​of the to-be-allocated resources in different application scenarios according to the resource quantification values ​​and the preset scenario usage probabilities;

[0043] Determining a coverage requirement quantified value and a capacity requirement quantified value of each target cell in the area to be allocated according to the network quantified value;

[0044] The resources to be allocated and the areas to be allocated are matched by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value.

[0045] As an improvement to the above solution, matching the to-be-allocated resources and the to-be-allocated areas by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value includes:

[0046] For all target cells in each area to be allocated, calculating the total demand value and demand ratio of the area to be allocated according to the coverage demand quantified value and the capacity demand quantified value;

[0047] For each resource to be allocated, calculating the total capacity value and the capacity ratio of the resource to be allocated in each application scenario according to the coverage capacity quantified value and the capacity capacity quantified value;

[0048] The resources to be allocated and the areas to be allocated are matched using the total demand value, the demand ratio, the total capacity value, and the capacity ratio.

[0049] As an improvement to the above solution, matching the to-be-allocated resources and the to-be-allocated areas by using the total demand value, the demand ratio, the total capacity value, and the capacity ratio includes:

[0050] According to the preset sorting rules, all areas to be allocated are sorted according to the total demand value, and all resources to be allocated in different application scenarios are sorted according to the total capacity value;

[0051] Perform a one-to-one match between the sorted regions to be allocated and the resources to be allocated for the corresponding application scenarios until the smaller number of regions is matched, resulting in an equal number of candidate regions and candidate resources.

[0052] According to a preset sorting rule, the candidate regions are sorted according to the demand ratio, and the candidate resources are sorted according to the capability ratio;

[0053] Perform one-to-one matching on the sorted candidate regions and candidate resources.

[0054] As an improvement to the above solution, matching the to-be-allocated resources and the to-be-allocated areas by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value includes:

[0055] When the area to be allocated takes into account the overall demand, a first matching function is constructed according to the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the first matching function;

[0056] When the area to be allocated takes coverage requirements into consideration, a second matching function is constructed according to the coverage capability quantified value and the coverage requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the second matching function;

[0057] When the area to be allocated takes capacity requirements into consideration, a third matching function is constructed according to the capacity capability quantified value and the capacity requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the third matching function.

[0058] To achieve the above objectives, an embodiment of the present invention further provides a resource allocation device, comprising:

[0059] A resource configuration information acquisition module, configured to acquire resource configuration information of at least one resource to be allocated;

[0060] A resource configuration information quantification module, configured to quantify the resource configuration information to obtain a resource quantification value;

[0061] A network configuration indicator acquisition module, configured to acquire network configuration indicators of all target cells in at least one area to be allocated; wherein the area to be allocated includes at least one target cell;

[0062] A network configuration indicator quantification module is used to quantify the network configuration indicator to obtain a network quantification value;

[0063] The resource allocation module is configured to match the resource to be allocated with the area to be allocated according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

[0064] To achieve the above objectives, an embodiment of the present invention also provides a resource allocation device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the resource allocation method described in any of the above embodiments.

[0065] To achieve the above-mentioned purpose, an embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the resource allocation method as described in any of the above-mentioned embodiments.

[0066] To achieve the above objectives, an embodiment of the present invention further provides a computer program product, including a computer program / instruction, which implements the resource allocation method as described in any of the above embodiments when executed by a processor.

[0067] Compared with the prior art, the resource allocation method, device, equipment, storage medium and program product disclosed in the present invention are quantified into resource quantization values ​​and network quantization values ​​respectively for the configuration information of the resources to be allocated and the network configuration indicators of the target cell, and then the resources to be allocated and the areas to be allocated are matched based on the resource quantization values ​​and the network quantization values, so as to allocate the resources to the areas to be allocated. In the resource allocation process, matching is driven by quantitative data, which avoids subjective judgment based on manual experience, makes the matching of resources and cell needs more in line with the actual situation, and improves the rationality of resource allocation. In addition, matching based on quantitative values ​​can more reasonably allocate resources of different specifications, avoid the contradiction of "shortage of high-specification resources and idleness of low-specification resources", effectively improve the utilization efficiency of existing network resources, and promote the maximum utilization of existing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is a flow chart of a resource allocation method provided by an embodiment of the present invention;

[0069] Figure 2 is another flow chart of a resource allocation method provided by an embodiment of the present invention;

[0070] Figure 3 This is a flow chart of quantifying resource configuration information provided by an embodiment of the present invention;

[0071] Figure 4 This is a flow chart of obtaining network configuration indicators provided by an embodiment of the present invention;

[0072] Figure 5 This is a flow chart for quantifying network configuration indicators provided by an embodiment of the present invention;

[0073] Figure 6 Schematic diagram of the division of quantization intervals provided by an embodiment of the present invention;

[0074] Figure 7 This is a flow chart of matching resources to be allocated and areas to be allocated provided by an embodiment of the present invention;

[0075] Figure 8 is another flow chart for matching resources to be allocated and areas to be allocated provided by an embodiment of the present invention;

[0076] Figure 9 This is a structural block diagram of a resource allocation device provided by an embodiment of the present invention;

[0077] Figure 10 This is a structural block diagram of a resource allocation device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0078] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0079] See also Figure 1 , Figure 1 1 is a flow chart of a resource allocation method provided by an embodiment of the present invention, wherein the resource allocation method includes:

[0080] S1. Obtain resource configuration information of at least one resource to be allocated, and quantify the resource configuration information to obtain a resource quantization value;

[0081] S2. Obtain network configuration indicators of all target cells in at least one area to be allocated, and quantify the network configuration indicators to obtain network quantization values; wherein the area to be allocated includes at least one target cell;

[0082] S3. Match the resource to be allocated and the area to be allocated according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

[0083] For example, see Figure 2 , Figure 2This is another flowchart of a resource allocation method provided by an embodiment of the present invention. First, evaluation data must be obtained, namely, resource configuration information for the resources to be allocated, as well as network configuration indicators for the target cells. These evaluation data are then quantified to obtain resource quantization values ​​and network quantization values ​​for the area to be allocated. When there is only one target cell in an area to be allocated, the quantization value of the indicator for that target cell is directly equal to the network quantization value for the area to be allocated. When there are two or more target cells in an area to be allocated, the quantization values ​​of the indicators for all target cells are added together to equal the network quantization value for the area to be allocated. Finally, based on the resource quantization value and network quantization value, reusable resources are analyzed and matched with network requirements to achieve optimal resource allocation. Furthermore, in response to the limitations of existing technologies, the embodiments of the present invention collect 10 subcategories of existing network data from three dimensions, including resource (such as RRU resources) hardware, cell coverage, and cell capacity, including cell performance, MR (Measurement Report), and MDT (Minimization Drive Test). A quantitative assessment of resource capabilities and network requirements is achieved through a quantification method, and then the optimal matching and reuse of cell requirements and existing resources is achieved based on a secondary index sorting matching algorithm.

[0084] In an embodiment of the present invention, the configuration information of the resources to be allocated and the network configuration indicators of the target cell are quantified into corresponding quantitative values, and then the resources to be allocated and the area to be allocated are matched based on the resource quantization value and the network quantization value, so that the resources to be allocated are allocated to the area to be allocated. In the resource allocation process, the matching is driven by quantitative data, which avoids the subjective judgment based on human experience, makes the matching of resources and cell needs more in line with the actual situation, and improves the rationality of resource allocation. The quantized values ​​are easy to calculate and compare quickly through algorithms, and can realize the automatic matching of large-scale resources and cells. Compared with manual screening and judgment one by one, the allocation time is greatly shortened, which is particularly suitable for efficient resource scheduling in complex network scenarios. In addition, matching based on quantitative values ​​can more reasonably allocate resources of different specifications, avoid the contradiction of "shortage of high-specification resources and idleness of low-specification resources", effectively improve the utilization efficiency of existing network resources, and promote the maximum utilization of existing resources.

[0085] It should be noted that the resources to be allocated in this embodiment of the present invention are RRU resources. The relationship between RRUs and target cells is one-to-one (in this case, the area to be allocated includes one target cell) or one-to-many (in this case, the area to be allocated includes multiple target cells). Sixteen items of data in three categories, including "RRU-level hardware data," "cell-level performance data," and "cell engineering parameters," are obtained and used as the source of resource configuration information and network configuration indicators. This data is derived from product specifications and capabilities, MR servers, MDT servers, base station northbound interfaces, and the operator's network optimization platform. See Table 1 below for specific data.

[0086] Table 1 Example of source data for resource configuration information and network configuration indicators

[0087]

[0088] It should be noted that quantization algorithms are widely used in various fields of daily production and life. In the field of digital signal processing, quantization refers to the process of approximating the continuous value of a signal to a finite number of discrete values. In the field of data processing, quantization refers to the process of discretizing floating-point data into integer data, further improving data processing efficiency. The embodiments of the present invention, drawing on the above-mentioned quantization algorithm ideas, based on the full amount of RRU specification data from mainstream equipment manufacturers, use a scalar uniform quantization algorithm to perform data dimensionality reduction mapping, ultimately achieving numerical measurement of the coverage and capacity support capabilities of various RRU models.

[0089] Currently, the RRU's main hardware specifications include the six data items listed in Table 1: production date, years of use, supported frequency bands, number of supported carriers, number of transmit channels, and maximum output power. The RRU's production date and years of use determine the device's age; the number of supported carriers determines the RRU's capacity expansion support within the same frequency band; the RRU's maximum output power determines the RS reference signal transmit power capability of the cell connected to the RRU, which in turn determines the cell's coverage capability. The RRU's supported frequency bands and number of transmit channels have a weak correlation with the RRU's coverage or capacity support capability, and the RRU's supported frequency bands are non-numeric data, making them difficult to quantify. Therefore, secondary processing of the original hardware specification data is required before quantification, which yields resource configuration information.

[0090] Specifically, the resource configuration information includes at least one of the following information:

[0091] 1) Device time attributes, including device usage time and device aging status;

[0092] 2) Equipment performance parameters, including at least one of single-channel power, equivalent bandwidth, average time advance, and number of carriers.

[0093] For example, based on the "RRU-level hardware data" recorded in Table 1, resource configuration information can be obtained after secondary processing. The secondary processing process example can be referred to Table 2. The subsequent quantization process and calculation process can directly use the abbreviations in Table 2 to represent the corresponding resource configuration information.

[0094] Table 2 Calculation example of resource configuration information

[0095]

[0096] In this embodiment of the present invention, by integrating this resource configuration information, a comprehensive assessment of the resources to be allocated can be performed, enabling rational resource allocation. In network construction or optimization projects, devices with matching performance parameters can be allocated to appropriate areas based on the network requirements and device resource configuration information of different areas. This avoids wasting resources on high-specification devices or preventing low-specification devices from meeting requirements, thereby improving resource utilization and reducing operating costs.

[0097] See also Figure 3 , Figure 3 This is a flow chart of quantizing resource configuration information provided by an embodiment of the present invention. In step S1, quantizing the resource configuration information to obtain a resource quantization value includes:

[0098] S11. Obtain resource configuration information of the same type among all resources to be allocated, and sort the resource configuration information of the same type;

[0099] S12. quantize the sorted resource configuration information to obtain at least two reference quantization values;

[0100] S13: Determine a resource quantization value for each piece of resource configuration information according to the reference quantization value.

[0101] Exemplarily, a scalar uniform quantization algorithm is used to quantize the resource configuration information, and the above six resource configuration information of all models of RRUs in the area to be allocated are arranged in ascending order according to the numerical value, and then the data is evenly divided into N parts according to the sorting number, and finally each interval is assigned a one-dimensional incremental value according to the size of the interval sorting number. The final quantization result is a set of values ​​​​(Z / N, 2Z / N,…,Z).

[0102] It should be noted that the scalar uniform quantization algorithm uniformly divides a one-dimensional quantization target into several parts, each corresponding to a quantization result. The main control parameters are the quantization interval N and the total quantization value Z. Specifically, RRU capability quantization maps multiple resource configuration information into the coverage and capacity dimensions for capability assessment. The main purpose is to reduce the data dimension. Therefore, the value of the quantization interval N should refer to the data characteristics of the RRU hardware specifications and must satisfy 2≤N<min (number of RRU single-channel power specification categories, number of RRU supported frequency band equivalent bandwidth specification categories, number of RRU supported frequency band average timing advance specification categories, and number of RRU supported carrier number specification categories). A larger N value results in more accurate quantization results but increases complexity. Therefore, it is recommended to set N to an integer less than 10. The total quantization value Z can be flexibly set but must be an integer multiple of N. To ensure the availability and consistency of quantization results, the quantization interval N and total quantization value Z should be consistent for all types of resource configuration information.

[0103] In this embodiment of the present invention, by acquiring and sorting resource configuration information of the same type, disorganized resource data can be organized and presented in an orderly manner. Quantifying the sorted resource configuration information to obtain reference values ​​provides a unified numerical measurement standard for resource evaluation. Quantifying different types of resource configuration information allows for comparison and analysis on the same scale, which helps accurately assess the relative value and importance of each resource within the overall resource pool and avoids evaluation bias caused by differences in units or magnitude.

[0104] Specifically, in step S11, resource configuration information of the same type in all resources to be allocated is obtained, and the resource configuration information of the same type is sorted.

[0105] For example, assume there are nine RRUs, each corresponding to the six resource configuration information items LS, LY, PG, DB, CT, and ZB in Table 2, N = 3, Z = 6. Taking LY as an example, the corresponding LYs for the nine RRUs are: [RRU1, 0.2], [RRU2, 0.3], [RRU3, 0.1], [RRU4, 0.5], [RRU5, 0.1], [RRU6, 0.1], [RRU7, 0.7], [RRU8, 0.6], and [RRU9, 0.7]. Sorting LYs in ascending order yields the following order: 0.1, 0.1, 0.1, 0.2, 0.3, 0.5, 0.6, 0.7, and 0.7. The sorting process for the remaining five resource configuration information items is similar and will not be repeated here.

[0106] Specifically, in step S12, the sorted resource configuration information is quantized to obtain at least two reference quantization values, including: dividing the sorted resource configuration information into at least two data sets; assigning a first sorting number to the at least two divided data sets in order from left to right; and assigning a value to each data set in an ascending order of the first sorting number to obtain a reference quantization value for each data set.

[0107] For example, the LYs after the aforementioned sorting are divided into three data sets: a[0.1, 0.1, 0.2], b[0.2, 0.3, 0.5], and c[0.6, 0.7, 0.7]. These data sets are assigned first sort numbers from left to right: 1 (corresponding to data set a), 2 (corresponding to data set b), and 3 (corresponding to data set c). Since the total quantization value is 6, according to the "Z / N, 2Z / N, Z" rule, the resulting reference quantization values ​​are 2, 4, and 6. Based on the ascending order of the first sort number, each data set is assigned a value in ascending order: data set a = 2, data set b = 4, and data set c = 6. The data set division and reference quantization value determination process for the remaining five resource configuration information items are similar and will not be further elaborated here.

[0108] In the embodiment of the present invention, by dividing the data set and assigning incremental values, the hierarchy and relative value of different resource configuration information can be clearly distinguished. In addition, after clarifying the reference quantitative values ​​of different data sets, resource combination strategies can be better planned.

[0109] Specifically, in step S13, the resource quantization value of each resource configuration information is determined based on the reference quantization value, including: for each resource configuration information, indexing the corresponding target data set from all data sets; and using the reference quantization value of the target data set as the resource quantization value of the resource configuration information.

[0110] For example, after obtaining the reference quantization value corresponding to each data set, for each RRU's LY, find which target data set its sorted position belongs to, and then obtain the corresponding resource quantization value LY'. For example, if RRU2's LY is in data set a, then RRU2's LY' = 2. The same applies to the other five data sets. At this point, the resource quantization values ​​of the six types of resource configuration information for all RRUs can be obtained. The resource quantization values ​​are represented by LS', LY', PG', DB', CT', and ZB', respectively.

[0111] In this embodiment of the present invention, by mapping resource configuration information to partitioned data sets and using the set's reference quantization value as the resource quantization value, a unified quantization standard is established for all resource configuration information. This allows resources of different types and specifications to be compared on the same scale. This quantization allows resource configuration information corresponding to various performance parameters of different RRU models to be quantified, enabling clear comparisons of their performance and making the resource quantization value an important reference.

[0112] Furthermore, step S1 quantifies the resource configuration information corresponding to the resources to be allocated, while step S2 quantifies the network configuration indicators of the target cell. This process quantifies the network requirements of the existing communication cells based on actual data, allowing for an intuitive assessment of the capacity and coverage requirements of each cell in the existing network, providing a basis for subsequent network resource matching. Network demand quantification primarily encompasses two dimensions: coverage demand quantification and capacity demand quantification. The recommended scope of network demand quantification assessment is prefecture-level cities.

[0113] See also Figure 4 , Figure 4 This is a flowchart of obtaining network configuration indicators provided by an embodiment of the present invention. In step S2, obtaining network configuration indicators of all target cells in at least one area to be allocated includes:

[0114] S21. Obtaining benchmark indicators and at least two indicators to be evaluated for all target cells in the area to be allocated;

[0115] S22, obtaining the correlation value between each indicator to be evaluated and the benchmark indicator;

[0116] S23: The benchmark indicator and the indicator to be evaluated whose correlation value meets the set conditions are used as the network configuration indicator.

[0117] Exemplarily, in step S21, the benchmark indicator includes a first indicator related to the cell coverage requirement and a second indicator related to the cell capacity requirement; the indicator to be evaluated includes at least one first performance indicator corresponding to the first indicator, and at least one second performance indicator corresponding to the second indicator. The first indicator is MR coverage (%), and the first performance indicators include average time advance (meters), azimuth station spacing (meters), and cell grid average level (dBm); the second indicator is full-time total traffic (GB), and the second performance indicators include wireless utilization (%), maximum number of RRC connections, uplink average experience rate (Mbps), and downlink average experience rate (Mbps). There are about 100 wireless performance indicators of a communication cell. In the embodiment of the present invention, several cell-level performance data related to cell coverage and capacity requirements are selected (as shown in Table 1). In order to simplify the subsequent quantification process and further improve the overall quantification efficiency, it is also necessary to accurately screen the quantification indicators and screen out the network configuration indicators.

[0118] For example, in step S22, the algorithm for determining the correlation of indicators is intended to measure the degree of relationship between two or more variables. Common algorithms for determining the correlation between variables include the following:

[0119] 1) Pearson correlation coefficient; The Pearson correlation coefficient is a classic statistical method used to measure the linear correlation between two variables. Its value range is -1 to +1. The closer it is to -1 or +1, the stronger the linear correlation between the variables. If it is equal to 0, it means there is no linear correlation.

[0120] 2) Spearman rank correlation coefficient; The Spearman rank correlation coefficient does not depend on the normal distribution of the data and can capture the monotonic relationship between variables. It is obtained by calculating the correlation between the ranks (i.e., sorting positions) of two variables and takes a value between -1 and +1.

[0121] 3) Kendall's Tau; Kendall's Tau is also a nonparametric test that measures the monotonic relationship between two variables. Unlike Spearman's Tau, Kendall focuses on the number of observed order inconsistencies. A value of -1 indicates a complete reverse order, and a value of +1 indicates a complete positive order.

[0122] 4) Distance Correlation: Distance correlation can capture any form of correlation (including linear and nonlinear). Its definition is based on the difference in distance between variables and has a wide range of applicability.

[0123] It should be noted that choosing an appropriate method to measure the correlation between variables depends on the characteristics of the target problem and the characteristics of the data. If the focus is on linear relationships, the Pearson correlation coefficient may be the first choice; if the data is nonlinear, distance correlation may be more appropriate. In this embodiment of the present invention, the Pearson correlation coefficient is used for indicator determination and correlation analysis (the other three algorithms mentioned above can also be used in other embodiments) to obtain the correlation value between the indicator to be evaluated and the benchmark indicator.

[0124] The Pearson correlation coefficient can be used to measure the strength of the linear relationship between two variables. This coefficient is widely used in data analysis. The calculation of the correlation coefficient is based on the deviation of the observed values ​​of the two variables from their respective means. By calculating the sum of the products of these deviations and dividing them by the standard deviation, the correlation value r is obtained. The calculation formula is as follows:

[0125]

[0126] Where n is the number of samples; x i and y i There are 2 comparison samples (sample 1 and sample 2); and They are the average values ​​of the two comparison samples AVERAGE (sample 1) and AVERAGE (sample 2); the value range of r is between -1 and 1, where 1 indicates that the two variables are completely linearly positively correlated; -1 indicates that the two variables are completely linearly negatively correlated; and 0 indicates no linear relationship, that is, there is no linear relationship between the two variables. When the above formula is applied specifically to the embodiment of the present invention, when sample 1 is the MR coverage rate, sample 2 is the average time advance, the azimuth station spacing, and the average cell grid level, respectively. When sample 1 is the full-time total traffic, sample 2 is the wireless utilization rate, the maximum number of RRC connections, the uplink average experience rate, and the downlink average experience rate, respectively. A total of 7 correlation values ​​r can be calculated, as shown in Table 3.

[0127] Table 3 Examples of correlation values

[0128]

[0129] For example, in step S23, MR coverage and total all-time traffic are first selected as network configuration indicators, and then the indicators to be evaluated whose absolute values ​​are greater than a set value (such as 0.5) are selected from the seven indicators to be evaluated as network configuration indicators. The absolute values ​​of r corresponding to the average time advance, cell grid average level, wireless utilization, and maximum number of RRC connections in Table 3 are all greater than 0.5, so these indicators are selected as network configuration indicators. At this time, a total of 6 network configuration indicators are selected, which can be expressed as: MR coverage-FG, average time advance-FA, cell grid average level-DP, total all-time traffic-LL, wireless utilization-WL, and maximum number of RRC connections-YH.

[0130] In an embodiment of the present invention, by obtaining the benchmark indicators and multiple indicators to be evaluated of the target cell and analyzing the correlation values ​​therebetween, it is possible to accurately find the indicators to be evaluated that are closely related to the benchmark indicators and use them as network configuration indicators. These network configuration indicators often have a key impact on the performance and service quality of the cell, avoiding blind groping among numerous indicators and improving resource allocation effects.

[0131] See also Figure 5 , Figure 5 This is a flowchart of quantifying a network configuration indicator provided by an embodiment of the present invention. In step S2, quantifying the network configuration indicator to obtain a network quantization value of the area to be allocated includes:

[0132] S24. Acquire sampling data of the same type of network configuration indicators in all target cells in the area to be allocated, and sort the sampling data of the same type of network configuration indicators;

[0133] S25. quantize the sorted sample data to obtain at least two standard quantization values;

[0134] S26. Determine the indicator quantization value corresponding to each network configuration indicator according to the standard quantization value;

[0135] S27. Add the index quantization values ​​corresponding to all target cells in the area to be allocated to obtain a network quantization value of the area to be allocated.

[0136] In this embodiment of the present invention, by sorting sampled data for the same type of network configuration indicators, disorganized data can be organized into an ordered sequence. Quantizing the sorted sampled data to obtain standardized values ​​effectively eliminates the evaluation barriers caused by the varying dimensions of different network configuration indicators. Determining the indicator quantization values ​​based on the standardized values ​​more accurately describes the characteristics and level of each target cell's network configuration indicator. Different indicator quantization values ​​can reflect the cell's performance on the corresponding indicator, providing precise data support for network optimization.

[0137] Specifically, in step S24, sampled data of the same type of network configuration indicators in all target cells are obtained, and the sampled data of the same type of network configuration indicators are sorted.

[0138] Exemplarily, first obtain sampling data of the same type of network configuration indicators in all target cells. In this case, one network configuration indicator corresponds to one sampling data. Assuming there are 24 target cells, each target cell corresponds to the six network configuration indicators FG, FA, DP, LL, WL, and YH determined in step S23. Then, the cells are arranged in ascending / descending order within the planning area according to the coverage, capacity requirement dimensions, and correlation values. The sorting rules are as follows:

[0139] 1) In the coverage dimension, the first indicator is sorted in descending order, and the first performance indicator is sorted according to the correlation value. If the correlation value is positive, it is sorted in descending order, and vice versa;

[0140] 2) In the capacity dimension, the second indicator is arranged in ascending order, and the second performance indicator is sorted according to the correlation value, which is ascending if positive and descending if negative.

[0141] Combining the above two sorting rules, the sorting of the six network configuration indicators FG, FA, DP, LL, WL and YH in the embodiment of the present invention can be obtained, as shown in Table 4.

[0142] Table 4 Network configuration indicator arrangement example

[0143] Network configuration indicators abbreviation Arrangement MR coverage FG Sort descending Average lead time FA r is negative, ascending order Average grid level of the cell DP r is positive, descending order Total flow rate at all times LL Sort ascending Wireless Utilization WL r is positive, ascending order Maximum number of RRC connections YH r is positive, ascending order

[0144] Specifically, in step S25, the sorted sampling data is quantized to obtain at least two standard quantization values, including: dividing the sorted sampling data into at least two data groups; averaging the sampling data in each data group to obtain at least two segmentation points; using the segmentation points to segment the sorted sampling data to obtain at least three quantization intervals; assigning second sorting numbers to the at least three quantization intervals after division in order from left to right; and assigning values ​​to each quantization interval in an ascending order of the second sorting numbers to obtain a standard quantization value for each quantization interval.

[0145] For example, to ensure the consistency and referenceability of the overall quantization results, the number of division intervals and the total quantization value of the demand quantization are consistent with the RRU capacity quantization, that is, the same N value and Z value are used. The sampled data are evenly divided into N-1 groups according to the sorting number, and then the sampled data in each group are averaged and aggregated to obtain N-1 quantization interval split points. Finally, N quantization intervals are determined based on the N-1 split points. Figure 6 , Figure 6This is a schematic diagram of the division of quantization intervals provided by an embodiment of the present invention. When N=4, the sampled data is evenly divided into 3 data groups according to the sorting order. An aggregated average value can be calculated for each data group. The sorted sampled data is re-divided with these 3 aggregated average values ​​as the dividing points to obtain 4 quantization intervals. The 4 divided quantization intervals are assigned second sorting numbers in order from left to right, such as quantization interval 1, quantization interval 2, quantization interval 3 and quantization interval 4 in the figure. The standard quantization value corresponding to each quantization interval is further obtained based on the total quantization value Z. Then, according to the ascending order of the second sorting numbers, each quantization interval is assigned a one-dimensional incremental quantization value. The final quantization result is a set of values ​​(Z / N, 2Z / N,…,Z), each of which represents the standard quantization value of a quantization interval.

[0146] In this embodiment of the present invention, the sorted sampled data is divided into data groups, breaking down the originally large and disordered data set into multiple relatively smaller subsets with more concentrated features. By averaging the sampled data within the data groups, segmentation points are generated. These segmentation points accurately divide the data into different levels. Using these segmentation points, multiple quantization intervals are generated, giving the data a clear quantization hierarchy. Each quantization interval represents a range of data values, and the boundaries between different intervals are clear.

[0147] Specifically, in step S26, the network quantization value of each network configuration indicator is determined based on the standard quantization value, including: for each network configuration indicator, indexing the corresponding target quantization interval from all quantization intervals; and using the standard quantization value of the target quantization interval as the indicator quantization value corresponding to the network configuration indicator.

[0148] For example, after obtaining the standard quantization value corresponding to each quantization interval, for each target cell's FG, FA, DP, LL, WL, and YH, find out which target quantization interval its position after sorting belongs to, and you can get the corresponding index quantization value, which are FG', FA', DP', LL', WL', and YH' respectively.

[0149] Specifically, in step S27, when there is only one target cell in an area to be allocated, the index quantization value of the target cell is directly equal to the network quantization value of the area to be allocated. When there are two or more target cells in an area to be allocated, the index quantization values ​​of all target cells need to be added together to equal the network quantization value of the area to be allocated.

[0150] In this embodiment of the present invention, by indexing a target quantization interval from all quantization intervals and using its standard quantization value as the indicator quantization value of the network configuration indicator, the actual state of the network configuration indicator can be accurately mapped to a specific value. This approach allows for more refined quantization of network configuration indicators and avoids general evaluations. Different network configuration indicators can be meticulously characterized through dedicated quantization intervals and standard quantization values, facilitating a comprehensive and accurate assessment of the overall performance of the cell network.

[0151] See also Figure 7 , Figure 7 This is a flowchart of matching the resources to be allocated and the area to be allocated provided by an embodiment of the present invention. In step S3, matching the resources to be allocated and the area to be allocated according to the resource quantization value and the network quantization value includes:

[0152] S31. Determine, based on the resource quantization value and the preset scenario usage probability, the coverage capability quantization value and the capacity capability quantization value of the to-be-allocated resource in different application scenarios;

[0153] S32. Determine, based on the network quantization value, a coverage requirement quantization value and a capacity requirement quantization value of each target cell in the area to be allocated;

[0154] S33: Match the resources to be allocated and the areas to be allocated by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value.

[0155] In an embodiment of the present invention, the coverage capability quantification value and the capacity capability quantification value are determined based on the resource quantification value and the scenario usage probability, and the actual capacity of the resources to be allocated is finely evaluated from the two key dimensions of coverage and capacity, combined with the requirements of different scenarios. The coverage demand quantification value and the capacity demand quantification value of the target cell are determined based on the network quantification value, and the actual demand level of the cell in terms of coverage range and capacity is accurately analyzed. By using the coverage capability quantification value, the capacity capability quantification value, the coverage demand quantification value and the capacity demand quantification value to match resources with regions, resource supply and cell demand can be accurately matched from the dual dimensions of coverage and capacity. Resources with strong coverage capabilities are allocated to cells with large coverage requirements, and resources with high capacity capabilities are matched to cells with high capacity requirements, so that resources are used more reasonably and waste or inefficiency caused by resource mismatch is avoided.

[0156] Specifically, in step S31, due to the significant differences in propagation models across different coverage scenarios, the final quantification of RRU resources needs to further consider the device usage scenario. The RRU usage probability for the corresponding scenario, G, is calculated as: the number of RRUs of the model used in the scenario / the total number of RRUs used in the scenario. The coverage capability quantification value FN and the capacity capability quantification value RN of the RRU in the corresponding scenario then satisfy the following formula:

[0157] FN=(LS'+LY'+PG'+CT')*(1+G);

[0158] RN=(LS'+LY'+DB'+ZB')*(1+G).

[0159] Specifically, in step S32, the coverage requirement quantified value FX and the capacity requirement quantified value RX of each target cell satisfy the following formula:

[0160] FX=FG'+FA'+DP';

[0161] RX=LL'+WL'+YH'.

[0162] Specifically, in step S33, the resources to be allocated and the areas to be allocated are matched using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value.

[0163] For example, before matching, the scope of reusable RRU resources to be matched needs to be flexibly determined based on the actual situation of the existing network. The subsequent matching results only achieve the best match within the selected reusable RRU resource range, not the global best match. Examples of commonly used flexible settings for reusable RRU matching ranges are as follows:

[0164] Scenario 1: The arithmetic mean of the proportion of 5G terminal users in the 4G cells to be evaluated in the aggregation area is greater than 70%. In this case, RRUs that support 5G networks need to be screened for matching first. If the number of RRU resources after matching does not meet the demand, the remaining RRU resources will be matched.

[0165] Scenario 2: Partial coverage or capacity requirements specify the frequency bands supported by the RRUs. In this scenario, RRUs that support the required frequency bands are prioritized for matching. If the number of RRU resources after matching does not meet the requirements, the remaining RRU resources are matched.

[0166] For example, before matching, network coverage and capacity requirements must be collected based on actual conditions. Typically, network coverage requirements are defined as coverage holes on a map, while network capacity requirements are defined as the coverage sectors of the communication base stations to be expanded. However, these quantified network requirements are all cell-level data. Therefore, before matching, relevant cell-level data must be aggregated based on the different characteristics of capacity and coverage requirements to select appropriate RRU resources for the areas to be allocated based on different demand types. The aggregation rules are shown in Table 5.

[0167] Table 5 Example of cell aggregation rules

[0168]

[0169]

[0170] It should be noted that, in terms of coverage requirements, it is recommended to select cells within a range of 500 meters in urban areas and general urban areas, it is recommended to select cells within a range of 1000 meters in county towns and townships, and it is recommended to select cells within a range of 3000 meters in rural areas. There is no demand for ultra-long-distance coverage of cells within 3000 meters, and this evaluation method is not currently applicable.

[0171] Furthermore, the present invention provides two matching methods when matching the resources to be allocated and the areas to be allocated. The first is a secondary index sorting algorithm, and the second is a matching algorithm based on Manhattan distance. The two algorithms can be used independently or in combination.

[0172] In the first embodiment, a secondary index sorting algorithm is adopted, and step S33 includes: for all target cells in each area to be allocated, the total demand value and the demand ratio of the area to be allocated are calculated according to the coverage demand quantification value and the capacity demand quantification value; for each resource to be allocated, the total capacity value and the capacity ratio of the resource to be allocated in each application scenario are calculated according to the coverage capability quantification value and the capacity capability quantification value; and the resource to be allocated and the area to be allocated are matched using the total demand value, the demand ratio, the total capacity value and the capacity ratio.

[0173] For example, for all target cells in each area to be allocated, assuming that there are three target cells in the area to be allocated, the total demand value X of the area to be allocated is calculated based on the coverage demand quantified values ​​FX and capacity demand quantified values ​​RX of the three target cells. sum , and calculate the demand ratio X of different demands in the area to be allocated in all areas to be allocated avg For each resource to be allocated that can be reused, the total capacity value N of the resource to be allocated in each application scenario is calculated based on the coverage capability quantization value FN and the capacity capability quantization value RN. sum , and calculate the capacity ratio N of the different capacities of the resource to be allocated in all the resources to be allocated avg The resources to be allocated and the areas to be allocated are matched using the total demand value, the demand ratio, the total capacity value, and the capacity ratio.

[0174] In this embodiment of the present invention, by calculating the total capacity value and capacity ratio of the resources to be allocated in each application scenario, the coverage capacity quantification value and the capacity capacity quantification value are comprehensively considered, comprehensively describing the overall characteristics of the resources in different application scenarios. The total capacity value reflects the comprehensive capacity level of the resource in a specific scenario, while the capacity ratio reflects the relative importance or proportion of coverage capacity and capacity capacity in that scenario. Different application scenarios have different requirements for the coverage capacity and capacity capacity of resources. By calculating the total capacity value and capacity ratio, a detailed analysis can be performed for each specific scenario, better adapting to the complex and diverse scenario requirements. In addition, the introduction of the total demand value and demand ratio to match the total capacity value and capacity ratio further refines the matching dimension between resources and the area to be allocated. The total demand value and demand ratio reflect the comprehensive demand level of the target cell in the area to be allocated, as well as the relative relationship between coverage demand and capacity demand. By comprehensively comparing the resource capacity index with the area demand index, the optimal matching point between resources and areas can be more accurately found. Matching based on these quantitative values ​​can avoid blindness and arbitrariness in resource allocation, improving the efficiency and accuracy of resource allocation.

[0175] Furthermore, the use of the total demand value, the demand ratio, the total capacity value and the capacity ratio to match the resources to be allocated and the areas to be allocated includes: sorting all areas to be allocated according to the total demand value in accordance with a preset sorting rule, and sorting all resources to be allocated in different application scenarios according to the total capacity value; performing one-to-one matching on the sorted areas to be allocated and the resources to be allocated of the corresponding application scenarios until the side with the smaller number is matched, thereby obtaining an equal number of candidate areas and candidate resources; sorting the candidate areas according to the demand ratio in accordance with a preset sorting rule, and sorting the candidate resources according to the capacity ratio; and performing one-to-one matching on the sorted candidate areas and candidate resources.

[0176] For example, see Figure 8 , Figure 8 This is another flow chart for matching resources to be allocated and areas to be allocated provided by an embodiment of the present invention.

[0177] Total demand value X sum The calculation process satisfies the following formula:

[0178] X sum =FX i +RX i (1);

[0179] Demand ratio X avg The calculation process can consider a variety of calculation methods, which are as follows:

[0180] 1) When giving priority to meeting the coverage requirements of the areas to be allocated, the coverage requirement quantified value FX is directly compared with the capacity requirement quantified value RX, or the coverage requirement quantified value FX is compared with the sum of the coverage requirement quantified values ​​of all areas to be allocated. Both ratios reflect the relative importance or proportion of coverage requirements. The corresponding formulas are as follows:

[0181]

[0182] Among them, FX i is the coverage requirement quantified value of the i-th area to be allocated, RX i is the quantitative value of the capacity demand of the i-th area to be allocated, FX sum It is the sum of the coverage requirements of all areas to be allocated.

[0183] 2) When giving priority to meeting the capacity requirements of the areas to be allocated, the ratio of the capacity requirement quantified value RX to the coverage requirement quantified value FX is directly used, or the capacity requirement quantified value RX is used to compare with the sum of the capacity requirement quantified values ​​of all areas to be allocated. Both ratios reflect the relative importance or proportion of capacity requirements. The corresponding formulas are as follows:

[0184]

[0185] Among them, RX sum The sum of the capacity requirements of all areas to be allocated.

[0186] Similarly, the total ability value N sum The calculation process satisfies the following formula:

[0187] N sum =FN i +RN i (6);

[0188] Capacity ratio N avg The calculation process can consider a variety of calculation methods, which are as follows:

[0189] 1) When giving priority to meeting the coverage requirements of the area to be allocated, the coverage capability quantified value FN and the capacity capability quantified value RN are directly used as the ratio, or the coverage capability quantified value FN and the sum of the coverage capability quantified values ​​of all resources to be allocated are used as the ratio. Both ratios reflect the relative importance or proportion of coverage capability. The corresponding formulas are as follows:

[0190]

[0191] Among them, FN i is the coverage capability quantified value of the i-th resource to be allocated, RN iis the capacity quantification value of the i-th resource to be allocated, FN sum It is the sum of the coverage capability quantification values ​​of all resources to be allocated.

[0192] 2) When giving priority to meeting the capacity requirements of the area to be allocated, the ratio of the capacity capability quantified value RN to the coverage capability quantified value FN is directly used, or the ratio of the capacity capability quantified value RN to the sum of the capacity capability quantified values ​​of all resources to be allocated is used. Both ratios reflect the relative importance or proportion of capacity capabilities. The corresponding formulas are as follows:

[0193]

[0194] Among them, RN sum It is the sum of the capacity quantification values ​​of all resources to be allocated.

[0195] First, according to the total demand value X sum Sort all areas to be allocated in descending order, and sort them according to the total capacity value N sum All resources to be allocated in different application scenarios are sorted in descending order, and the areas to be allocated in descending order are matched one-to-one with the resources to be allocated in the corresponding application scenarios until the side with the smaller number is matched. An equal number of candidate areas and candidate resources are obtained. For example, if there are 10 areas to be allocated and 8 RRUs for a certain application scenario, the first 8 areas to be allocated are matched with 8 RRUs respectively, and the remaining 2 areas to be allocated are not processed for the time being.

[0196] Secondly, after screening candidate areas and candidate resources, according to the demand ratio X avg and capability ratio N avg Perform secondary matching on candidate regions and candidate resources. The following situations may occur:

[0197] A. When giving priority to meeting the coverage requirements of the candidate area, according to X avg1 Sort the 8 candidate regions in descending order, and avg1 Sort the 8 candidate resources in descending order, and perform one-to-one matching again on the 8 candidate regions and 8 candidate resources after descending order; or, according to X avg2 Sort the 8 candidate regions in descending order, and avg2 Sort the eight candidate resources in descending order, perform one-to-one matching again between the eight candidate areas and the eight candidate resources, and use the final matching result as the optimal RRU resource reuse solution.

[0198] B. When giving priority to meeting the capacity requirements of candidate areas, according to X avg3 Sort the 8 candidate regions in descending order, and avg3Sort the 8 candidate resources in descending order, and perform one-to-one matching again on the 8 candidate regions and 8 candidate resources after descending order; or, according to X avg4 Sort the 8 candidate regions in descending order, and avg4 The 8 candidate resources are sorted in descending order, and the 8 candidate areas and 8 candidate resources after descending order are matched one-to-one again. The final matching result is used as the optimal RRU resource reuse solution.

[0199] In this embodiment of the present invention, multiple rounds of sorting and matching enable optimal resource allocation, avoiding irrational resource allocation, such as allocating resources with strong coverage but weak capacity to areas with high capacity demands. This refined matching process maximizes the effectiveness of each resource, improving overall resource utilization, reducing operating costs, and enhancing network service quality and user experience.

[0200] In a second embodiment, a matching algorithm based on Manhattan distance is adopted, and step S33 includes: when the area to be allocated considers the overall demand, a first matching function is constructed according to the coverage capability quantification value, the capacity capability quantification value, the coverage demand quantification value and the capacity demand quantification value, and the resource to be allocated and the area to be allocated are matched according to the matching result of the first matching function; when the area to be allocated considers the coverage demand, a second matching function is constructed according to the coverage capability quantification value and the coverage demand quantification value, and the resource to be allocated and the area to be allocated are matched according to the matching result of the second matching function; when the area to be allocated considers the capacity demand, a third matching function is constructed according to the capacity capability quantification value and the capacity demand quantification value, and the resource to be allocated and the area to be allocated are matched according to the matching result of the third matching function.

[0201] Exemplarily, when the area to be allocated considers the overall (capacity + coverage) requirements, the first matching function constructed is a Manhattan distance function that satisfies the following formula:

[0202]

[0203] Where f(X,N) j Indicates the jth area to be allocated, FN i Indicates the coverage capability quantization value corresponding to the i-th resource to be allocated, RN i f(X,N) represents the capacity quantization value corresponding to the i-th resource to be allocated, i = 1, 2, ... n, and n is the total number of resources to be allocated. j The smaller the value, the better the match.

[0204] When the area to be allocated takes coverage requirements into consideration, the constructed second matching function satisfies the following formula:

[0205]

[0206] When the area to be allocated takes capacity requirements into consideration, the constructed third matching function satisfies the following formula:

[0207]

[0208] It should be noted that due to the matching algorithm based on Manhattan distance, there will be two situations: ① There are at least two areas to be allocated that match the same resources to be allocated; ② One area to be allocated matches at least two resources to be allocated. At this time, the secondary index sorting algorithm can be further combined for screening. Suppose there are 10 areas to be allocated and 8 RRUs. For these areas to be allocated, the matching algorithm is calculated at the same time. If there are 5 resources to be allocated that can be matched one-to-one (that is, the corresponding RRUs are also matched 5), there are 5 resources to be allocated that cannot be matched one-to-one, and there are 3 RRUs. For these resources to be allocated and RRUs, match them according to the above-mentioned secondary index sorting algorithm. Or, for situation ①, when there are at least two areas to be allocated that match the same resources to be allocated, the total demand value X max Priority matching, at this time you can directly select the total demand value X max The largest area to be allocated is matched first, and the remaining areas to be allocated participate in the matching process of the next round of matching algorithm; for situation ②, when an area to be allocated matches at least two resources to be allocated, the total capacity value N max Priority matching, at this time you can directly select the total value of ability N max The largest resource to be allocated is matched first, and the remaining resources to be allocated participate in the matching process of the next round of matching algorithm.

[0209] In an embodiment of the present invention, by constructing a matching function based on different situations, accurate adaptation to different business scenarios (such as regional priority coverage, priority capacity expansion, and comprehensive resource balance) is achieved to meet the resource allocation needs in complex scenarios. The matching degree is calculated using Manhattan distance, which is simple to calculate and can be processed in parallel, significantly improving the operating efficiency of the matching algorithm and making it suitable for large-scale resource allocation scenarios. In addition, for key needs, such as priority coverage in emergency communication scenarios and priority consideration of capacity in large-scale event scenarios, by focusing on supply and demand matching in a single dimension and quickly responding to core needs, it is possible to shorten resource scheduling time and enhance the service quality of the system.

[0210] See also Figure 9 , Figure 9 1 is a structural block diagram of a resource allocation device 100 provided in an embodiment of the present invention, wherein the resource allocation device 100 includes:

[0211] The resource configuration information acquisition module 11 is used to obtain resource configuration information of at least one resource to be allocated;

[0212] The resource configuration information quantification module 12 is used to quantify the resource configuration information to obtain a resource quantization value;

[0213] The network configuration indicator acquisition module 13 is configured to acquire network configuration indicators of all target cells in at least one area to be allocated; wherein the area to be allocated includes at least one target cell;

[0214] The network configuration index quantification module 14 is used to quantify the network configuration index to obtain the network quantification value of the area to be allocated;

[0215] The resource allocation module 15 is configured to match the resource to be allocated with the area to be allocated according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

[0216] Specifically, the resource configuration information quantification module 12 includes:

[0217] A resource configuration information sorting unit is used to obtain resource configuration information of the same type from all resources to be allocated and sort the resource configuration information of the same type;

[0218] The resource configuration information quantization unit is used to quantize the sorted resource configuration information to obtain at least two reference quantization values, and determine the resource quantization value of each resource configuration information according to the reference quantization values.

[0219] Specifically, the resource configuration information quantization unit is specifically used to: divide the sorted resource configuration information into at least two data sets; assign a first sorting number to the at least two divided data sets in order from left to right; assign values ​​to each data set in an ascending order of the first sorting number to obtain a reference quantization value of each data set; for each resource configuration information, index to the corresponding target data set from all data sets; and use the reference quantization value of the target data set as the resource quantization value of the resource configuration information.

[0220] Specifically, the network configuration indicator acquisition module 13 is specifically used to: obtain the benchmark indicators and at least two indicators to be evaluated of all target cells in the area to be allocated; obtain the correlation value between each indicator to be evaluated and the benchmark indicator; and use the indicator to be evaluated whose benchmark indicator and the correlation value meet the set conditions as the network configuration indicator.

[0221] Specifically, the network configuration indicator quantification module 14 includes:

[0222] A sampling data sorting unit is used to obtain sampling data of the same type of network configuration indicators in all target cells in the area to be allocated, and sort the sampling data of the same type of network configuration indicators;

[0223] A network configuration indicator quantization unit is configured to quantize the sorted sampled data to obtain at least two standard quantization values; and determine the indicator quantization value corresponding to each network configuration indicator according to the standard quantization values;

[0224] The network quantization value determining unit is used to add the index quantization values ​​corresponding to all target cells in the area to be allocated to obtain the network quantization value of the area to be allocated.

[0225] Specifically, the network configuration indicator quantization unit is specifically used to: divide the sorted sampling data into at least two data groups; average the sampling data in each data group to obtain at least two segmentation points; use the segmentation points to segment the sorted sampling data to obtain at least three quantization intervals; assign second sorting numbers to the at least three divided quantization intervals in order from left to right; assign values ​​to each quantization interval in an ascending order of the second sorting numbers to obtain a standard quantization value for each quantization interval; for each network configuration indicator, index to the corresponding target quantization interval from all quantization intervals; and use the standard quantization value of the target quantization interval as the indicator quantization value corresponding to the network configuration indicator.

[0226] Specifically, the resource allocation module 15 includes:

[0227] a comprehensive quantitative value calculation unit, configured to determine, based on the resource quantization value and the preset scenario usage probability, the coverage capability quantization value and the capacity capability quantization value of the to-be-allocated resource in different application scenarios; and determine, based on the network quantization value, the coverage requirement quantization value and the capacity requirement quantization value of each target cell in the to-be-allocated area;

[0228] An allocating unit is configured to match the resources to be allocated and the areas to be allocated by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value.

[0229] Specifically, the allocation unit is specifically used to: for all target cells in each area to be allocated, calculate the total demand value and demand ratio of the area to be allocated according to the coverage demand quantification value and the capacity demand quantification value; for each resource to be allocated, calculate the total capacity value and capacity ratio of the resource to be allocated in each application scenario according to the coverage capability quantification value and the capacity capability quantification value; use the total demand value, the demand ratio, the total capacity value and the capacity ratio to match the resource to be allocated and the area to be allocated.

[0230] Specifically, the use of the total demand value, the demand ratio, the total capacity value and the capacity ratio to match the resources to be allocated and the areas to be allocated includes: sorting all areas to be allocated according to the total demand value in accordance with a preset sorting rule, and sorting all resources to be allocated in different application scenarios according to the total capacity value; performing one-to-one matching on the sorted areas to be allocated and the resources to be allocated of the corresponding application scenarios until the side with the smaller number is matched, thereby obtaining an equal number of candidate areas and candidate resources; sorting the candidate areas according to the demand ratio in accordance with a preset sorting rule, and sorting the candidate resources according to the capacity ratio; and performing one-to-one matching on the sorted candidate areas and candidate resources.

[0231] Specifically, the allocation unit is specifically used to: when the area to be allocated considers the overall demand, construct a first matching function according to the coverage capability quantification value, the capacity capability quantification value, the coverage demand quantification value and the capacity demand quantification value, and match the resources to be allocated and the area to be allocated according to the matching result of the first matching function; when the area to be allocated considers the coverage demand, construct a second matching function according to the coverage capability quantification value and the coverage demand quantification value, and match the resources to be allocated and the area to be allocated according to the matching result of the second matching function; when the area to be allocated considers the capacity demand, construct a third matching function according to the capacity capability quantification value and the capacity demand quantification value, and match the resources to be allocated and the area to be allocated according to the matching result of the third matching function.

[0232] It is worth noting that the working process of each module in the resource allocation device 100 according to the embodiment of the present invention can refer to the working process of the resource allocation method according to the above embodiment, and will not be described in detail here.

[0233] See also Figure 10 , Figure 102 is a block diagram of a resource allocation device 200 provided in an embodiment of the present invention. The resource allocation device 200 includes a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, the steps of the above-mentioned resource allocation method embodiments are implemented, such as steps S1 to S3, S11 to S13, S21 to S26, and S31 to S33.

[0234] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 22 and executed by the processor 21 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the resource allocation device 200.

[0235] The resource allocation device 200 may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will appreciate that the schematic diagram is merely an example of the resource allocation device 200 and does not limit the resource allocation device 200. The resource allocation device 200 may include more or fewer components than shown, or may combine certain components or different components. For example, the resource allocation device 200 may also include input and output devices, network access devices, buses, and the like.

[0236] The processor 21 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor 21 is the control center of the resource allocation device 200 and connects various parts of the entire resource allocation device 200 using various interfaces and lines.

[0237] The memory 22 can be used to store the computer programs and / or modules. The processor 21 implements the various functions of the resource allocation device 200 by running or executing the computer programs and / or modules stored in the memory 22 and accessing the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area may store data generated based on the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory 22 may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0238] If the modules / units integrated in the resource allocation device 200 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 21, it can implement the steps of the above-mentioned various method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0239] Furthermore, the present invention also provides a computer program product, including a computer program / instruction, which implements the resource allocation method as described in any of the above embodiments when executed by a processor.

[0240] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A resource allocation method, characterized in that: include: Obtaining resource configuration information of at least one resource to be allocated, and quantifying the resource configuration information to obtain a resource quantization value; Obtaining network configuration indicators of all target cells in at least one area to be allocated, and quantifying the network configuration indicators to obtain a network quantization value of the area to be allocated; wherein the area to be allocated includes at least one target cell; The resource to be allocated and the area to be allocated are matched according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

2. The resource allocation method according to claim 1, wherein: The resource configuration information includes at least one of the following information: Device time attributes; Equipment performance parameters, including at least one of single-channel power, equivalent bandwidth, average time advance, and number of carriers.

3. The resource allocation method according to claim 1, wherein: The quantizing the resource configuration information to obtain a resource quantization value includes: Obtain resource configuration information of the same type among all resources to be allocated, and sort the resource configuration information of the same type; quantifying the sorted resource configuration information to obtain at least two reference quantization values; The resource quantization value of each resource configuration information is determined according to the reference quantization value.

4. The resource allocation method according to claim 3, wherein: The sorted resource configuration information is quantized to obtain at least two reference quantization values, including: Dividing the sorted resource configuration information into at least two data sets; Assigning first sort numbers to the at least two divided data sets in order from left to right; According to the ascending order of the first sorting numbers, each data set is assigned a value in an incremental assignment manner to obtain a reference quantization value of each data set.

5. The resource allocation method according to claim 4, wherein: The determining the resource quantization value of each resource configuration information according to the reference quantization value includes: For each resource configuration information, index the corresponding target data set from all data sets; The reference quantization value of the target data set is used as the resource quantization value of the resource configuration information.

6. The resource allocation method according to claim 1, wherein: The obtaining of network configuration indicators of all target cells in at least one area to be allocated includes: Obtaining the benchmark indicators and at least two indicators to be evaluated for all target cells in the area to be allocated; Obtaining a correlation value between each indicator to be evaluated and the benchmark indicator; The benchmark indicator and the indicator to be evaluated whose correlation value meets the set conditions are used as the network configuration indicator.

7. The resource allocation method according to claim 6, wherein: The benchmark indicators include a first indicator related to the cell coverage requirement and a second indicator related to the cell capacity requirement; the indicators to be evaluated include at least one first performance indicator corresponding to the first indicator, and at least one second performance indicator corresponding to the second indicator.

8. The resource allocation method according to claim 1, wherein: The quantifying the network configuration indicator to obtain a network quantization value of the area to be allocated includes: Acquire sampling data of the same type of network configuration indicators in all target cells in the area to be allocated, and sort the sampling data of the same type of network configuration indicators; quantizing the sorted sample data to obtain at least two standard quantization values; Determine the indicator quantization value corresponding to each network configuration indicator according to the standard quantization value; The index quantization values ​​corresponding to all target cells in the area to be allocated are added together to obtain the network quantization value of the area to be allocated.

9. The resource allocation method according to claim 8, wherein: The sorted sample data is quantized to obtain at least two standard quantization values, including: Dividing the sorted sampled data into at least two data groups; The sampled data in each data group are averaged and aggregated to obtain at least two segmentation points; Segmenting the sorted sampled data using the segmentation points to obtain at least three quantization intervals; assigning second ranking numbers to the at least three divided quantization intervals in order from left to right; According to the ascending order of the second sort numbers, each quantization interval is assigned a value in an increasing manner to obtain a standard quantization value of each quantization interval.

10. The resource allocation method according to claim 8, wherein: The determining, according to the standard quantized value, the indicator quantized value corresponding to each network configuration indicator includes: For each network configuration indicator, index the corresponding target quantization interval from all quantization intervals; The standard quantization value of the target quantization interval is used as the indicator quantization value corresponding to the network configuration indicator.

11. The resource allocation method according to claim 1, wherein: The matching of the to-be-allocated resource and the to-be-allocated area according to the resource quantization value and the network quantization value includes: Determining coverage capability quantification values ​​and capacity capability quantification values ​​of the to-be-allocated resources in different application scenarios according to the resource quantification values ​​and the preset scenario usage probabilities; Determining a coverage requirement quantified value and a capacity requirement quantified value of each target cell in the area to be allocated according to the network quantified value; The resources to be allocated and the areas to be allocated are matched by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value.

12. The resource allocation method according to claim 11, wherein: The matching of the to-be-allocated resources and the to-be-allocated areas by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value includes: For all target cells in each area to be allocated, calculating the total demand value and demand ratio of the area to be allocated according to the coverage demand quantified value and the capacity demand quantified value; For each resource to be allocated, calculating the total capacity value and the capacity ratio of the resource to be allocated in each application scenario according to the coverage capacity quantified value and the capacity capacity quantified value; The resources to be allocated and the areas to be allocated are matched using the total demand value, the demand ratio, the total capacity value, and the capacity ratio.

13. The resource allocation method according to claim 12, wherein: The matching of the to-be-allocated resources and the to-be-allocated areas by using the total demand value, the demand ratio, the total capacity value, and the capacity ratio includes: According to the preset sorting rules, all areas to be allocated are sorted according to the total demand value, and all resources to be allocated in different application scenarios are sorted according to the total capacity value; Perform a one-to-one match between the sorted regions to be allocated and the resources to be allocated for the corresponding application scenarios until the smaller number of regions is matched, resulting in an equal number of candidate regions and candidate resources. According to a preset sorting rule, the candidate regions are sorted according to the demand ratio, and the candidate resources are sorted according to the capability ratio; Perform one-to-one matching on the sorted candidate regions and candidate resources.

14. The resource allocation method according to claim 11, wherein: The matching of the to-be-allocated resources and the to-be-allocated areas by using the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value includes: When the area to be allocated takes into account the overall demand, a first matching function is constructed according to the coverage capability quantified value, the capacity capability quantified value, the coverage requirement quantified value, and the capacity requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the first matching function; When the area to be allocated takes coverage requirements into consideration, a second matching function is constructed according to the coverage capability quantified value and the coverage requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the second matching function; When the area to be allocated takes capacity requirements into consideration, a third matching function is constructed according to the capacity capability quantified value and the capacity requirement quantified value, and the resources to be allocated and the area to be allocated are matched according to a matching result of the third matching function.

15. A resource allocation device, characterized in that: include: A resource configuration information acquisition module, configured to acquire resource configuration information of at least one resource to be allocated; A resource configuration information quantification module, configured to quantify the resource configuration information to obtain a resource quantification value; A network configuration indicator acquisition module, configured to acquire network configuration indicators of all target cells in at least one area to be allocated; wherein the area to be allocated includes at least one target cell; A network configuration indicator quantification module is used to quantify the network configuration indicator to obtain a network quantification value; The resource allocation module is configured to match the resource to be allocated with the area to be allocated according to the resource quantization value and the network quantization value, so as to allocate the resource to be allocated to the area to be allocated.

16. A resource allocation device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the resource allocation method according to any one of claims 1 to 14 when executing the computer program.

17. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the resource allocation method according to any one of claims 1 to 14.

18. A computer program product, characterized in that The method comprises a computer program / instruction, which implements the resource allocation method according to any one of claims 1 to 14 when executed by a processor.

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