Supplement uplink associated cell configuration methods, devices, equipment, and media

Abstract

This invention discloses a method, apparatus, device, and medium for configuring supplementary uplink associated cells. The method includes: collecting MR data of supplementary uplink demand cells and supplementary uplink cells; processing and associating the MR data of supplementary uplink demand cells and supplementary uplink cells to generate an associated cell set; performing rasterization processing on the associated cell set to obtain a rasterized result; and optimizing the supplementary uplink cells in the associated cell set based on the rasterized result to generate an adjustment scheme for supplementary uplink associated cells. This invention significantly reduces the cost of acquiring analytical data, improves the adaptability of the supplementary uplink function, and enhances the accuracy and rationality of associated cell configuration.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a method, apparatus, device, and medium for supplementing uplink associated cell configuration. Background Technology

[0002] With the diversified development of mobile internet, IoT, cloud storage, and other services, the demand for uploading massive amounts of data is rapidly increasing, requiring compliance with uplink data transmission requirements. Currently, the mainstream 5G commercial deployment frequency bands are mainly TDD-NR bands such as 3.5GHz / 2.6GHz. These bands are characterized by large bandwidth and high capacity, but due to relatively high penetration loss and low uplink duty cycle, their uplink coverage and capacity are insufficient. Therefore, to ensure the development of diversified services, improve user experience, and reduce deployment costs, it is urgent to improve the uplink performance of 5G networks.

[0003] Currently, the main technology used to improve uplink performance is 5G Supplemental Uplink (SUL) technology. Communication systems using SUL configure one DL band (NR band) and two uplink bands (NR band + SUL band) within the same cell. When the uplink coverage of the NR carrier is good, the terminal uses the NR carrier for data transmission and reception. When the coverage area of ​​the NR carrier is outside its range, the terminal uses the SUL carrier for data transmission. The terminal can dynamically select the transmission link between UL, NR, and SUL, but at any given time, the terminal can only select one uplink to transmit; it cannot use two uplinks simultaneously.

[0004] Supplementing uplink technology requires configuring additional carriers (SUL bands) on top of existing 5G cells to enhance uplink capabilities. However, existing configuration methods for uplink enhancement associated cells are all static configurations, mainly configuring SUL bands in 5G cells with shared baseband processing units and specific frequency bands to achieve enhanced uplink capabilities.

[0005] The above method has the following drawbacks:

[0006] First, this limits the application of uplink enhancement functions to cells with shared baseband control units and specific frequency bands in 5G cells.

[0007] Second, it makes the uplink extension cell fixed, while the optimal uplink extension cell will change with the user's location and the type of cell service.

[0008] Third, the static configuration method may lead to a decrease in customer experience due to insufficient consideration of factors such as expanded cell capacity and alarms. Summary of the Invention

[0009] The main objective of this invention is to provide a supplementary uplink associated cell configuration method, apparatus, device, and medium, which aims to improve the adaptability of uplink enhancement functions and the accuracy and rationality of uplink enhancement associated cell configuration.

[0010] To achieve the above objectives, embodiments of the present invention provide a method for supplementing uplink associated cell configuration, the method comprising the following steps:

[0011] Collect MR data for cells requiring supplementary uplink and cells requiring supplementary uplink.

[0012] The MR data of the supplementary uplink demand cells and supplementary uplink cells are processed and associated to generate an associated cell set;

[0013] The associated cell set is rasterized to obtain the rasterized result;

[0014] Based on the rasterization results, supplementary uplink cell optimization is performed on the associated cell set to generate a supplementary uplink associated cell adjustment scheme.

[0015] Optionally, the step of collecting MR data for supplementary uplink demand cells and supplementary uplink cells includes:

[0016] When a user terminal accesses the wireless network to perform services, the serving cell and surrounding neighboring cells occupied by the user terminal are measured, and NR and SUL site data of the serving cell and surrounding neighboring cells are collected at preset time intervals to obtain user MR sampling point information.

[0017] Collect cell parameter information;

[0018] Based on the user MR sampling point information and cell parameter information, the uplink signal strength values ​​of the serving cell and neighboring cells at each sampling point are calculated to obtain the MR data of the supplementary uplink demand cell and the supplementary uplink cell.

[0019] Optionally, the step of processing and associating the MR data of the supplementary uplink demand cell and the supplementary uplink cell to generate an associated cell set includes:

[0020] Based on the MR data, the supplementary uplink demand cells and supplementary uplink cells are divided into relatively independent cell sets.

[0021] Calculate the pairwise correlation coefficients between cells in the cell set to obtain the cell-to-cell correlation coefficients;

[0022] Cell pairs with a correlation coefficient greater than a preset threshold are selected as cells to be merged.

[0023] The cells to be merged are merged to generate a set of associated cells.

[0024] Optionally, the step of performing rasterization processing on the associated cell set to obtain the rasterization result includes:

[0025] The geographical area controlled by the wireless network system is rasterized to form a preset geographical area raster.

[0026] For each of the associated cell sets, the sampling points in the associated cell set are projected onto the preset geographical area grid, and the number of sampling points and the average uplink and downlink signal strength of each cell on the preset geographical area grid are calculated to obtain the rasterization result.

[0027] Optionally, the step of performing supplementary uplink cell optimization on the associated cell set based on the rasterization result to generate a supplementary uplink associated cell adjustment scheme includes:

[0028] Based on the rasterization results and the collected MR data, the proportion of weak uplink coverage rasteres covered by the supplementary uplink demand cell is calculated.

[0029] The priority order of the cells requiring supplementary uplink coverage is obtained by sorting the proportions of the uplink weak coverage grids.

[0030] Based on the priority order of the supplementary uplink demand cells, supplementary uplink cells are matched for the supplementary uplink demand cells, and the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell is evaluated to obtain the evaluation result.

[0031] Based on the evaluation results, the best supplementary uplink cell is selected, and a supplementary uplink associated cell adjustment scheme is generated.

[0032] Optionally, the step of matching supplementary uplink cells to supplementary uplink demand cells according to the priority order of the supplementary uplink demand cells, evaluating the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell, and obtaining the evaluation result includes:

[0033] Based on the priority order of the cells requiring supplementary uplink, the current cell with the highest uplink weak coverage grid ratio is first matched with supplementary uplink cells, and the uplink supplementation coefficient of the current cell is calculated.

[0034] The uplink supplementation coefficients are sorted in descending order, and the capacity matching of the supplementary uplink cells is performed sequentially.

[0035] If the capacity matching meets the requirements, the matching is completed, and the matched supplementary uplink cell is bound to the current required cell.

[0036] If the capacity matching does not meet the requirements, the next supplementary uplink cell in the candidate supplementary uplink cell ranking will be used for the calculation until the matching is completed or the matching fails.

[0037] Repeat the above steps until all supplementary uplink demand cells in the priority order of the supplementary uplink demand cells have completed the matching of uplink coverage and uplink capacity. Evaluate the uplink coverage compensation capability and uplink capacity compensation capability of each supplementary uplink cell for each supplementary uplink demand cell, and use this as the evaluation result.

[0038] Optionally, the method further includes:

[0039] Execute the supplementary uplink associated cell adjustment scheme.

[0040] Furthermore, this invention also proposes a supplementary uplink associated cell automatic configuration device, the device comprising:

[0041] The acquisition module is used to collect MR data of supplementary uplink demand cells and supplementary uplink cells;

[0042] The association module is used to process and associate the MR data of the supplementary uplink demand cell and the supplementary uplink cell to generate an associated cell set;

[0043] The rasterization processing module is used to perform rasterization processing on the associated cell set to obtain the rasterization result;

[0044] The optimization module is used to perform supplementary uplink cell optimization on the associated cell set based on the rasterization results, and generate a supplementary uplink associated cell adjustment scheme.

[0045] Furthermore, this embodiment of the invention also proposes a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the supplementary uplink associated cell configuration method as described above.

[0046] Furthermore, this embodiment of the invention also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the supplementary uplink associated cell configuration method as described above.

[0047] The supplementary uplink associated cell configuration method, apparatus, device, and medium proposed in this invention collect MR data of supplementary uplink demand cells and supplementary uplink cells; process and associate the MR data of the supplementary uplink demand cells and supplementary uplink cells to generate an associated cell set; perform rasterization processing on the associated cell set to obtain a rasterization result; and optimize the supplementary uplink cells in the associated cell set based on the rasterization result to generate a supplementary uplink associated cell adjustment scheme. Compared with the prior art, the solution of this invention makes up for the shortcomings of existing supplementary uplink associated cell configuration methods. This invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analysis data, and mine the data through big data processing and association technologies, greatly reducing the cost of obtaining analysis data; analysis based on MR data realizes the ability of network to follow traffic, that is, improves the adaptability of supplementary uplink function; in addition, the optimization of supplementary uplink cells in the associated cell set based on rasterization analysis improves the accuracy and rationality of the associated cell configuration. Attached Figure Description

[0048] Figure 1 This invention supplements the functional module diagram of the terminal equipment to which the uplink associated cell configuration device belongs;

[0049] Figure 2 A flowchart illustrating an exemplary embodiment of the uplink associated cell configuration method for this invention;

[0050] Figure 3 This is a detailed flowchart illustrating an embodiment of the uplink associated cell configuration method for this invention.

[0051] Figure 4 This is a schematic diagram illustrating the effect of the cluster analysis of the cells to be adjusted in an embodiment of the present invention;

[0052] Figure 5 This is a flowchart illustrating another exemplary embodiment of the uplink associated cell configuration method for the present invention.

[0053] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0054] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0055] The main solution of this invention is as follows: First, collect uplink demand cells and their MR data. Second, process and correlate the MR data of these cells to generate a set of correlated cells. Third, perform rasterization on the correlated cell set to obtain a rasterized result. Fourth, based on the rasterized result, optimize the correlated cell set for uplink access, generating an adjustment scheme for the correlated cells. Compared to existing technologies, this invention overcomes the shortcomings of existing uplink correlated cell configuration methods. This invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analytical materials, and mine the data through big data processing and correlation techniques, greatly reducing the cost of acquiring analytical materials. Analysis based on MR data enables network-following-traffic capabilities, thus improving the adaptability of the uplink function. Furthermore, based on rasterized analysis, it considers both the uplink coverage of demand cells and the uplink capacity of uplink-providing cells, and performs iterative optimization, improving the accuracy and rationality of the correlated cell configuration.

[0056] Technical terms involved in the embodiments of this invention:

[0057] MR: Measurement Report.

[0058] This invention takes into account that, among existing related solutions, 5G offers greater transmission capacity, higher reliability, and lower latency. With the diversified development of mobile internet, IoT, cloud storage, intelligent monitoring, and other services, the demand for uploading massive amounts of data is rapidly increasing. Whether for ToC or ToB services, uplink data transmission requirements must be met. Examples include the uploading of massive amounts of data in high-definition video communication, online games, big data collection, intelligent monitoring, and AR / VR video live streaming. Moreover, the bandwidth and latency requirements of these services are constantly increasing with the diversified development of mobile internet, IoT, cloud storage, and intelligent monitoring. Therefore, building a high-quality 5G commercial network that continuously meets the high-capacity and low-latency characteristics of uplink is one of the key concerns for commercial deployment.

[0059] Currently, the mainstream 5G commercial deployment frequency bands are mainly TDD-NR bands such as 3.5GHz and 2.6GHz. The main characteristics of these bands are large bandwidth and high capacity, but due to relatively high penetration loss and low uplink duty cycle, their uplink coverage and capacity are insufficient. Therefore, in order to ensure the development of diversified services, improve user experience, and reduce deployment costs, it is urgent to improve the uplink performance of 5G networks.

[0060] The primary technology currently used to enhance uplink performance is 5G Supplemental Uplink (SUL) technology. Communication systems using SUL configure one DL band (NR band) and two uplink bands (NR band + SUL band) within the same cell. When the uplink coverage of the NR carrier is good, the terminal uses the NR carrier for data transmission and reception. When the coverage area of ​​the NR carrier is outside its range, the terminal uses the SUL carrier for data transmission. The terminal can dynamically select the transmission link between UL, NR, and SUL, but at any given time, it can only select one uplink for transmission and cannot use both uplinks simultaneously. Supplemental uplink technology requires configuring additional carriers (SUL bands) on top of the existing 5G cell to enhance uplink capabilities. Existing configuration methods for uplink enhancement associated cells are all static configurations, primarily configuring cells sharing a baseband processing unit. Its disadvantages are: First, it limits the application of uplink enhancement functions to cells with a common baseband control unit and specific frequency bands in 5G cells, thus restricting the application of uplink enhancement functions; Second, it fixes the uplink extension cell, while the optimal uplink extension cell will change with the user's location and the type of cell service; Third, it cannot fully consider the capacity, alarms, and other conditions of the extension cell, and the static configuration method may cause a decrease in customer perception.

[0061] Therefore, this invention proposes a solution to provide an automatic configuration method for uplink associated cells based on 5G MR. This method can match neighboring associated cells, improve the adaptability of uplink enhancement functions, and dynamically adjust the associated neighboring cells of 5G cells based on MR, KPI indicators, etc. It establishes a complete set of methods and processes from data collection, data analysis, scheme output to scheme execution, thereby improving system efficiency.

[0062] Its main solutions may include:

[0063] Every hour, the system extracts 5G NR site (SUL demand site) and SUL site MR data at the granularity of the previous hour. Based on the collected MR sampling point information and acquired cell parameter information, it calculates the uplink signal strength value of each MR sampling point. SUL demand cells (i.e., 5G cells) and SUL provided cells are identified as the cells to be analyzed. The correlation coefficient between each pair of cells to be analyzed is calculated, and cell pairs with a correlation coefficient greater than c are identified. Through clustering and fusion, n sets of associated cells are obtained. Based on the sampling points of cells within each set of associated cells, the sampling points are mapped to a grid within a preset geographical area. The system obtains the associated cell set, grid number, covered cell, cell type (SUL demand cell or SUL provided cell), and sampling points. The correspondence between quantity, average uplink signal strength, and average downlink signal strength is established. The proportion of weak uplink coverage grids in the grids covered by SUL demand cells in the associated cell set is calculated. Then, in descending order of the proportion of weak uplink coverage grids, the uplink supplementation coefficient of each SUL providing cell for each SUL demand cell is calculated. Finally, in descending order of the uplink supplementation coefficient, each SUL providing cell is matched with the SUL demand cell for capacity. If the capacity match is successful, the current SUL providing cell is bound to the SUL demand cell, and the SUL providing cell provides SUL resources to the bound SUL demand cell.

[0064] Specifically, refer to Figure 1 , Figure 1 This is a schematic diagram of the functional modules of the terminal device to which the supplementary uplink associated cell configuration device belongs in this invention. This supplementary uplink associated cell configuration device can be a device independent of the terminal device, and it can be implemented on the terminal device in hardware or software form. The terminal device can be a smart mobile terminal such as a mobile phone or tablet computer, or it can be a network device such as a server.

[0065] In this embodiment, the terminal device to which the supplementary uplink associated cell configuration device belongs includes at least an output module 110, a processor 120, a memory 130, and a communication module 140.

[0066] The memory 130 stores the operating system and supplementary uplink associated cell configuration programs; the output module 110 can be a display screen, speaker, etc. The communication module 140 can include a WIFI module, a mobile communication module, and a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.

[0067] In one embodiment, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it performs the following steps:

[0068] Collect MR data for cells requiring supplementary uplink and cells requiring supplementary uplink.

[0069] The MR data of the supplementary uplink demand cells and supplementary uplink cells are processed and associated to generate an associated cell set;

[0070] The associated cell set is rasterized to obtain the rasterized result;

[0071] Based on the rasterization results, supplementary uplink cell optimization is performed on the associated cell set to generate a supplementary uplink associated cell adjustment scheme.

[0072] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0073] When a user terminal accesses the wireless network to perform services, the serving cell and surrounding neighboring cells occupied by the user terminal are measured, and NR and SUL site data of the serving cell and surrounding neighboring cells are collected at preset time intervals to obtain user MR sampling point information.

[0074] Collect cell parameter information;

[0075] Based on the user MR sampling point information and cell parameter information, the uplink signal strength values ​​of the serving cell and neighboring cells at each sampling point are calculated to obtain the MR data of the supplementary uplink demand cell and the supplementary uplink cell.

[0076] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0077] Based on the MR data, the supplementary uplink demand cells and supplementary uplink cells are divided into relatively independent cell sets.

[0078] Calculate the pairwise correlation coefficients between cells in the cell set to obtain the cell-to-cell correlation coefficients;

[0079] Cell pairs with a correlation coefficient greater than a preset threshold are selected as cells to be merged.

[0080] The cells to be merged are merged to generate a set of associated cells.

[0081] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0082] The geographical area controlled by the wireless network system is rasterized to form a preset geographical area raster.

[0083] For each of the associated cell sets, the sampling points in the associated cell set are projected onto the preset geographical area grid, and the number of sampling points and the average uplink and downlink signal strength of each cell on the preset geographical area grid are calculated to obtain the rasterization result.

[0084] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0085] Based on the rasterization results and the collected MR data, the proportion of weak uplink coverage rasteres covered by the supplementary uplink demand cell is calculated.

[0086] The priority order of the cells requiring supplementary uplink coverage is obtained by sorting the proportions of the uplink weak coverage grids.

[0087] Based on the priority order of the supplementary uplink demand cells, supplementary uplink cells are matched for the supplementary uplink demand cells, and the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell is evaluated to obtain the evaluation result.

[0088] Based on the evaluation results, the best supplementary uplink cell is selected, and a supplementary uplink associated cell adjustment scheme is generated.

[0089] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0090] Based on the priority order of the cells requiring supplementary uplink, the current cell with the highest uplink weak coverage grid ratio is first matched with supplementary uplink cells, and the uplink supplementation coefficient of the current cell is calculated.

[0091] The uplink supplementation coefficients are sorted in descending order, and the capacity matching of the supplementary uplink cells is performed sequentially.

[0092] If the capacity matching meets the requirements, the matching is completed, and the matched supplementary uplink cell is bound to the current required cell.

[0093] If the capacity matching does not meet the requirements, the next supplementary uplink cell in the candidate supplementary uplink cell ranking will be used for the calculation until the matching is completed or the matching fails.

[0094] Repeat the above steps until all supplementary uplink demand cells in the priority order of the supplementary uplink demand cells have completed the matching of uplink coverage and uplink capacity. Evaluate the uplink coverage compensation capability and uplink capacity compensation capability of each supplementary uplink cell for each supplementary uplink demand cell, and use this as the evaluation result.

[0095] Furthermore, when the supplementary uplink associated cell configuration program in memory 130 is executed by the processor, it also performs the following steps:

[0096] Execute the supplementary uplink associated cell adjustment scheme.

[0097] This embodiment collects uplink demand cells and MR data of these cells using the above-described scheme; processes and correlates the MR data of these cells to generate a set of correlated cells; performs rasterization on the correlated cell set to obtain a rasterized result; and optimizes the correlated cell set based on the rasterized result to generate an adjustment scheme for the correlated cells. Compared with existing technologies, this invention overcomes the shortcomings of existing methods for configuring correlated cells for supplementary uplinks. This invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analytical materials, and mines the data through big data processing and correlation techniques, greatly reducing the cost of acquiring analytical materials. Analysis based on MR data enables network-following-traffic capabilities, thus improving the adaptability of the supplementary uplink function. Furthermore, based on rasterized analysis, it considers both the uplink coverage supplementation of demand cells and the uplink capacity of supplementary uplink cells, and performs iterative optimization, improving the accuracy and rationality of the correlated cell configuration.

[0098] Based on, but not limited to, the terminal device architecture described above, embodiments of the method of the present invention are proposed.

[0099] Reference Figure 2 , Figure 2 This is a flowchart illustrating an exemplary embodiment of the supplementary uplink associated cell configuration method of the present invention. The supplementary uplink associated cell configuration method includes the following steps:

[0100] Step S101: Collect MR data of supplementary uplink demand cells and supplementary uplink cells;

[0101] Specifically, when a user terminal accesses the wireless network to perform services, the serving cell and surrounding neighboring cells occupied by the user terminal are measured, and NR and SUL site data of the serving cell and surrounding neighboring cells are collected every preset time to obtain user MR sampling point information. For example, the network system extracts 5G NR and SUL site MR data of the previous hour every hour.

[0102] Collect cell parameter information and compile traffic volume indicators;

[0103] Then, based on the user MR sampling point information and cell parameter information, the uplink signal strength values ​​of the serving cell and neighboring cells at each sampling point are calculated to obtain the MR data of the supplementary uplink demand cell and the supplementary uplink cell.

[0104] Taking 5G networks as an example, when 5G users access the wireless network to carry out 5G services, they continuously measure the occupied serving cell and surrounding neighboring cells, collect signal strength and quality related data, and use this as the basis for subsequent cell handover. This data can truly reflect the actual coverage of the cell and surrounding neighboring cells. By mining this data, the best uplink supplementary cell can be determined more precisely.

[0105] Step S102: Process and associate the MR data of the supplementary uplink demand cell and the supplementary uplink cell to generate an associated cell set;

[0106] Specifically, as one implementation method, firstly, based on the MR data, the supplementary uplink demand cells and supplementary uplink cells are divided to form a relatively independent set of cells;

[0107] Then, the pairwise correlation coefficients between each cell in the cell set are calculated to obtain the correlation coefficients between each cell pair.

[0108] Then, cell pairs with a correlation coefficient greater than a preset threshold are selected as cells to be merged;

[0109] Finally, the cells to be merged are merged to generate a set of associated cells.

[0110] Step S103: Perform rasterization processing on the associated cell set to obtain the rasterization result;

[0111] Specifically, as one implementation method, firstly, the geographical area controlled by the wireless network system is rasterized to form a preset geographical area raster;

[0112] Then, for each of the associated cell sets, the sampling points in the associated cell set are projected into the preset geographical area grid, and the number of sampling points and the average uplink and downlink signal strength of each cell in the preset geographical area grid are calculated to obtain the rasterization result.

[0113] Step S104: Based on the rasterization result, perform supplementary uplink cell optimization on the associated cell set to generate a supplementary uplink associated cell adjustment scheme.

[0114] Specifically, as one implementation method, firstly, based on the rasterization results and the collected MR data, the proportion of weak uplink coverage raster covered by the supplementary uplink demand cell is calculated.

[0115] Then, the uplink weak coverage grid ratios are sorted to obtain the priority order of the supplementary uplink demand cells;

[0116] Then, according to the priority order of the supplementary uplink demand cells, supplementary uplink cells are matched for the supplementary uplink demand cells, and the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell is evaluated to obtain the evaluation result.

[0117] Finally, based on the evaluation results, the best supplementary uplink cell is selected, and a supplementary uplink associated cell adjustment scheme is generated.

[0118] The step of matching supplementary uplink cells to supplementary uplink demand cells according to their priority order, evaluating the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell, and obtaining the evaluation result may include:

[0119] Based on the priority order of the cells requiring supplementary uplink, the current cell with the highest uplink weak coverage grid ratio is first matched with supplementary uplink cells, and the uplink supplementation coefficient of the current cell is calculated.

[0120] The uplink supplementation coefficients are sorted in descending order, and the capacity matching of the supplementary uplink cells is performed sequentially.

[0121] If the capacity matching meets the requirements, the matching is completed, and the matched supplementary uplink cell is bound to the current required cell.

[0122] If the capacity matching does not meet the requirements, the next supplementary uplink cell in the candidate supplementary uplink cell ranking will be used for the calculation until the matching is completed or the matching fails.

[0123] Repeat the above steps until all supplementary uplink demand cells in the priority order of the supplementary uplink demand cells have completed the matching of uplink coverage and uplink capacity. Evaluate the uplink coverage compensation capability and uplink capacity compensation capability of each supplementary uplink cell for each supplementary uplink demand cell, and use this as the evaluation result.

[0124] This embodiment collects uplink demand cells and MR data of these cells using the above-described scheme; processes and correlates the MR data of these cells to generate a set of correlated cells; performs rasterization on the correlated cell set to obtain a rasterized result; and optimizes the correlated cell set based on the rasterized result to generate an adjustment scheme for the correlated cells. Compared with existing technologies, this invention overcomes the shortcomings of existing methods for configuring correlated cells for supplementary uplinks. This invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analytical materials, and mines the data through big data processing and correlation techniques, greatly reducing the cost of acquiring analytical materials. Analysis based on MR data enables network-following-traffic capabilities, thus improving the adaptability of the supplementary uplink function. Furthermore, based on rasterized analysis, it considers both the uplink coverage supplementation of demand cells and the uplink capacity of supplementary uplink cells, and performs iterative optimization, improving the accuracy and rationality of the correlated cell configuration.

[0125] The following uses a 5G network as an example, but is not limited to 5G networks, to describe the solution in this embodiment in detail:

[0126] like Figure 3 As shown, a method for automatic configuration of supplementary uplink associated cells based on 5G MR is proposed. First, the system automatically collects MR data of 5G supplementary uplink demand cells and supplementary uplink cells (SUL). Then, the MR data of the 5G demand cells and SUL cells are processed and associated to generate an associated cell set. The MR sampling points of each associated cell set are projected onto a grid. The uplink coverage compensation capability and uplink capacity compensation capability of each SUL cell for the 5G demand cells are evaluated. Based on the evaluation results, the best SUL cell is selected, and an adjustment scheme for supplementary uplink associated cells is generated. The 5G supplementary uplink demand cell is a 5G cell with this function; due to functional license limitations, only some cells in the network have this function.

[0127] Specifically, firstly, MR data of supplementary uplink demand cells and supplementary uplink cells are collected, that is, 5G user data sample data is automatically collected. The specific implementation includes:

[0128] When 5G users access the wireless network to conduct 5G services, they continuously measure the occupied serving cell and surrounding neighboring cells, collecting signal strength and quality-related data, which serves as the basis for subsequent cell handover. This data can accurately reflect the actual coverage of the cell and surrounding neighboring cells. By mining this data, the best uplink supplementary cell can be determined more precisely.

[0129] (1) MR data acquisition

[0130] The network system extracts MR data of 5G NR sites and SUL sites at the granularity of the previous hour every hour. The collected SUL sites are sites used to supplement the uplink frequency band, and are generally 700MHz band sites.

[0131] The specific fields for 5G MR data extraction are specified as follows:

[0132] MR.TimeStamp: The time at which the measurement sampling point is generated;

[0133] MR.NRSiteid: Site number;

[0134] MR.NRScArfcn: Frequency number of the serving cell;

[0135] MR.NRScPci: PCI (Physical Cell Identifier) ​​of the serving cell;

[0136] MR.NRScSSRSRP: Signal strength of the 5G serving cell measured by the terminal;

[0137] MR.NRScSSSINR: Signal quality of the 5G serving cell measured by the terminal;

[0138] MR.NRScTadv: Reflects the signal propagation time from the terminal to the serving cell, and is the main indicator reflecting the distance between the terminal and the serving cell;

[0139] MR.NRScAOA: Reflects the reference azimuth angle of the terminal relative to the communication serving cell. The reference direction should be due north and counterclockwise.

[0140] MR.NRPwrCtl: Power control level value of the serving cell;

[0141] MR.NRNcArfcn: Frequency number of the neighboring cell;

[0142] MR.NRNcPci: PCI (Physical Cell Identifier) ​​of the neighboring cell;

[0143] MR.NRNcSSRSRP: Signal strength of neighboring cells measured by the terminal;

[0144] MR.NRScSSSINR: Signal quality of neighboring cells as measured by the terminal.

[0145] (2) Parameter data acquisition

[0146] The system extracts parameters such as 5G NR site transmit power NRPwr, UE maximum transmit power UEPwr, handover parameters, and supplementary uplink start threshold at 01:00 am every day, and then parses and stores them in the database.

[0147] (3) Business volume indicators statistics

[0148] The system extracts the uplink PRB utilization rate at the granularity of the previous hour every hour.

[0149] (4) Calculation of uplink coverage samples

[0150] Based on the user MR sampling point information extracted in (1) above and the cell parameter information extracted in (2) above, the uplink signal strength value, i.e. uplink level value, of each sampling point is calculated.

[0151] Assuming the uplink and downlink antennas have the same gain, the uplink signal strengths MR.NRScSSRSRPUL and MR.NRNcSSRSRPUL of the serving cell and neighboring cells at each sampling point are calculated.

[0152] Since the serving cell performs power control on the downlink, the uplink level calculation of the serving cell needs to be compensated for power control.

[0153] The uplink signal strength of the serving cell is MR.NRScSSRSRPUL = UEPwr - (NRPwr - MR.NRScSSRSRP - MR.NRPwrCtl), where UEPwr and NRPwr are the transmit power of the serving cell and the maximum transmit power of the UE in the serving cell, respectively, MR.NRScSSRSRP is the signal strength of the 5G serving cell measured by the terminal, and MR.NRPwrCtl is the power control level of the serving cell.

[0154] The uplink signal strength of the neighboring cell is MR.NRNcSSRSRPUL=UEPwr-(NRPwr-MR.NRScSSRSRP), where UEPwr and NRPwr are the transmit power of the neighboring cell and the maximum transmit power of the UE in the neighboring cell, respectively.

[0155] Based on this method, each data point in (1) above is supplemented with an uplink signal strength index.

[0156] The above methods were used to collect MR data for supplementary uplink demand cells and supplementary uplink cells.

[0157] Secondly, the MR data of the supplementary uplink demand cells and supplementary uplink cells are processed and associated to generate an associated cell set.

[0158] Adjusting uplink cells can impact the network structure of the entire region. Therefore, by processing and correlating data, cells that influence each other can be divided into several relatively independent sets. By performing overall uplink cell configuration adjustments within each set, the adjustments can be optimized and the negative impact on the network structure can be reduced.

[0159] In this embodiment, an uplink-associated cell set is established, and 5G cells (supplementary uplink demand cells) and candidate supplementary uplink cells are assigned to a set that does not interfere with each other during adjustment, for optimal solution iteration. The specific processing includes:

[0160] (1) Definition of uplink associated cell set

[0161] This step involves dividing all cells to be analyzed (5G cells that need to be supplemented and cells that need to be supplemented with uplinks), that is, dividing the above cells into relatively independent cell sets, seeking local optimal solutions within each set, and thus obtaining the overall best uplink supplementation scheme.

[0162] Let the total population of the communities to be analyzed be R = {x1, x2, ...}, and the resulting set after partitioning be E1, E2, ..., En, satisfying E1∪E2…∪En = R, and (i≠j, i, j∈{1…n});

[0163] (2) Cell division algorithm to be analyzed

[0164] The correlation coefficient between two cells is Xij = (Wi + Wj) / (Ui + Uj), where Wi is the number of times the user occupies serving cell i and measures cell j in the measurement report, Ui is the total number of measurements taken from cell i as the serving cell, Wj is the number of times cell j measures cell i as the serving cell, and Mj is the total number of measurements taken from cell j.

[0165] If the correlation coefficient Xij between two sub-intervals is greater than c, then the two sub-intervals are considered to be related.

[0166] ① Calculation of correlation coefficient between communities

[0167] Assuming that all the cells to be adjusted have x independent individuals, we calculate the pairwise correlation coefficients, thus obtaining x*(x-1) / 2 results;

[0168] ② Correlation coefficient threshold screening

[0169] The first clustering is formed when the correlation coefficient Xij > c, resulting in the Y-class community.

[0170] ③ Community integration

[0171] For Y-type cells, all overlapping sets are merged together, such as... Then they merge into {Y1, Y2}, if They then merge into {Y1, Y2, Y3}, ultimately forming a Z-class incompatible set.

[0172] ④ Form a set of n related communities to be analyzed

[0173] Cells that do not exist in all Z-class sets are classified into one class each because they have no connection with any other cells to be adjusted. Ultimately, the classes with connections and the classes without connections together form n sets of associated cells.

[0174] The effect of the specific method for adjusting the cell clustering analysis in this embodiment is illustrated as follows: Figure 4 As shown.

[0175] Then, the associated cell set is rasterized to obtain the rasterized result. The specific processing steps may include:

[0176] For the n associated cell sets formed above, perform the following rasterization operation within each associated cell set:

[0177] The sampling points obtained in the preceding steps are rasterized using MR.NRScTadv and MR.NRScAOA, projecting the sampling points of the associated cell set onto a 50m*50m grid. The uplink and downlink signal strengths of the main coverage cells in each grid within this associated cell set are then calculated. MR.NRScTadv reflects the signal propagation time from the terminal to the serving cell and is a primary indicator of the distance between the terminal and the serving cell. MR.NRScAOA reflects the reference azimuth angle of the terminal relative to the serving cell; the reference direction should be due north and counterclockwise.

[0178] (1) Region rasterization

[0179] The geographic area controlled by the system is rasterized into 50m*50m geographic grids, and each grid is numbered.

[0180] (2) Sampling point mapping

[0181] Using MR.NRScTadv and MR.NRScAOA, the sampling points of each cell in each associated cell are mapped to the grid formed in the previous step, and the number of sampling points and the average uplink and downlink levels of each cell in the grid are calculated.

[0182] If the number of sampling points for a cell within a grid is less than P, that cell is removed from the grid and not used in subsequent calculations. The number of sampling points for each cell in the grid is the sum of the sampling points for that cell as a serving cell and as neighboring cells.

[0183] The grid of the associated cell set is the grid where the cells in the set are effectively covered (no cells are excluded due to the number of sampling points being less than P). After completing the sampling point mapping, the following indicators are generated by aggregating the associated cell set:

[0184]

[0185]

[0186] Then, based on the above rasterization results, supplementary uplink cell optimization is performed on the associated cell set to generate a supplementary uplink associated cell adjustment plan.

[0187] Among them, independent supplementary uplink enhanced cell optimization is performed on the rasterization results of each associated cell set generated in the above steps. Each associated cell set contains two types of cells, the required cells for uplink enhancement and the supplementary uplink cells. The supplementary uplink cells are matched in the order of priority based on the proportion of the uplink weak coverage grid covered by the required cells. The specific processing process includes:

[0188] (1) Calculation of the proportion of the uplink weak coverage grid of the required cell

[0189] Calculate the proportion of the uplink weak coverage grid of the grid covered by the supplementary uplink required cells in the associated cell set, and sort them from large to small according to this proportion, where:

[0190] Proportion of the uplink weak coverage grid of the cell = (Number of grids where the average uplink signal strength < rsrp_thr_ul and the average downlink signal strength > rsrp_thr_dl) / Total number of grids covered by the cell;

[0191] Among them, rsrp_thr_ul is set to the supplementary uplink start threshold of this cell for the above data collection.

[0192] (2) Supplementary uplink cell optimization

[0193] Match the supplementary uplink cells according to the priority order of the required cells formed in the previous step.

[0194] First, match the supplementary uplink cells for the required cell with the highest proportion of the uplink weak coverage grid, and calculate the uplink compensation ability of each supplementary uplink cell in the associated cell set for this required cell, where:

[0195] Uplink supplementary coefficient = (Number of grids where the average uplink signal strength > rsrp_thr_ul + comp and the average downlink signal strength > rsrp_thr_dl) / Number of uplink weak coverage grids of the cell; where comp is the uplink supplementary target level and can be set to 5 - 15.

[0196] That is, on the uplink weak coverage grid of the required cell, the uplink signal strength of the evaluated supplementary uplink providing cell is statistically analyzed. If the above conditions are met, the grid can be supplemented by the uplink providing cell, and the proportion that can be supplemented is calculated, which is the uplink supplementary coefficient of the supplementary cell for the required cell.

[0197] After that, sort in descending order according to the supplementary coefficient and perform capacity matching for the supplementary uplink cells.

[0198] Take the uplink required cell with a 100 MHz bandwidth at 2.6 GHz and the uplink supplementary cell with a 30 MHz bandwidth at 700 MHz as an example for capacity matching calculation, where:

[0199] Required capacity = 100 * uplink time slot ratio of the cell / 30 / equivalent coefficient * ratio of weak coverage sampling points of the cell grid * uplink PRB utilization rate of the cell.

[0200] If the required capacity + uplink PRB utilization rate of the supplementary uplink cell < PRB_thr_ul, then the capacity of the supplementary uplink cell meets the requirement, and the matching is completed. The supplementary cell is bound to the required cell and does not participate in subsequent matching. The SUL providing cell provides SUL resources for the bound SUL required cell. Otherwise, substitute the next cell in the sorted candidate supplementary cells for calculation until the matching is completed or fails.

[0201] Loop through the above steps until the uplink coverage and uplink capacity matching of all the sorted supplementary uplink required cells in step (1) are completed, calculate the uplink compensation capabilities of each supplementary uplink cell in the associated cell set for each required cell, and thus obtain the adjustment scheme for the supplementary uplink associated cells.

[0202] Compared with the prior art, the solution of the present invention makes up for the deficiencies of the existing method for configuring supplementary uplink associated cells. The present invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analysis materials, and through big data processing technology and association technology, mine the data, greatly reducing the cost of obtaining analysis materials; based on MR data analysis, it realizes the ability of network following services, that is, improves the adaptability of the supplementary uplink function; in addition, based on grid analysis, it takes into account both the coverage supplement of the uplink of the required cell and the uplink capacity of the uplink supplementary providing cell, and performs iterative optimization step by step, improving the accuracy and rationality of the configuration of associated cells.

[0203] Refer to Figure 5 , Figure 5 is a schematic flowchart of another exemplary embodiment of the method for configuring supplementary uplink associated cells of the present invention. Based on the above Figure 2 In the embodiment shown, the method further includes:

[0204] Step S105: Execute the supplementary uplink associated cell adjustment scheme.

[0205] After all supplementary uplink demand cells have completed uplink coverage and uplink capacity matching, the uplink compensation capability of each supplementary uplink cell in the associated cell set for each demand cell is calculated, thus obtaining the supplementary uplink associated cell adjustment scheme. Based on the associated cell pairs of supplementary uplink demand cells and supplementary uplink cells generated in the supplementary uplink associated cell adjustment scheme, i.e. the associated cell pairs formed by the SUL-provided cells bound to the SUL demand cells, the system automatically connects to the 5G operation and maintenance system to perform the adjustment of the supplementary uplink association relationship.

[0206] This embodiment, through the above-described scheme, collects uplink demand cells and MR data of the uplink demand cells; processes and correlates the MR data of the uplink demand cells and the uplink demand cells to generate a set of correlated cells; performs rasterization processing on the set of correlated cells to obtain rasterized results; based on the rasterized results, optimizes the uplink cells in the set of correlated cells to generate and execute an adjustment scheme for the uplink correlated cells. Compared with the prior art, the present invention overcomes the shortcomings of existing uplink correlated cell configuration methods. The present invention can use a large amount of 5G MR, traffic volume indicators, and parameter data as analysis data, and mines the data through big data processing and correlation technologies, greatly reducing the cost of obtaining analysis data; based on MR data analysis, it realizes the ability of network to follow traffic, that is, improves the adaptability of the uplink function; in addition, based on rasterization analysis, it considers both the uplink coverage supplementation of the demand cells and the uplink capacity of the uplink supplementary cells, and performs iterative optimization step by step, improving the accuracy and rationality of the configuration of correlated cells.

[0207] Furthermore, this invention also proposes a supplementary uplink associated cell automatic configuration device, the device comprising:

[0208] The acquisition module is used to collect MR data of supplementary uplink demand cells and supplementary uplink cells;

[0209] The association module is used to process and associate the MR data of the supplementary uplink demand cell and the supplementary uplink cell to generate an associated cell set;

[0210] The rasterization processing module is used to perform rasterization processing on the associated cell set to obtain the rasterization result;

[0211] The optimization module is used to perform supplementary uplink cell optimization on the associated cell set based on the rasterization results, and generate a supplementary uplink associated cell adjustment scheme.

[0212] This embodiment explains the principle and implementation process of automatic configuration of supplementary uplink associated cells. Please refer to the above embodiments for details, which will not be repeated here.

[0213] Furthermore, this embodiment of the invention also proposes a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the supplementary uplink associated cell automatic configuration method as described above.

[0214] Since this supplementary uplink associated cell configuration program adopts all the technical solutions of all the aforementioned embodiments when it is executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be repeated here.

[0215] Furthermore, this embodiment of the invention also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the supplementary uplink associated cell automatic configuration method as described above.

[0216] Since this supplementary uplink associated cell configuration program adopts all the technical solutions of all the aforementioned embodiments when it is executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be repeated here.

[0217] Compared with existing technologies, the supplementary uplink associated cell configuration method, apparatus, device, and medium proposed in this embodiment of the invention collects MR data of supplementary uplink demand cells and supplementary uplink cells; processes and associates the MR data of the supplementary uplink demand cells and supplementary uplink cells to generate an associated cell set; performs rasterization processing on the associated cell set to obtain a rasterization result; and optimizes the associated cell set based on the rasterization result to generate a supplementary uplink associated cell adjustment scheme. Compared to existing technologies, the present invention addresses the shortcomings of current methods for configuring supplementary uplink associated cells. This invention utilizes a large amount of 5G MR, traffic volume indicators, and parameter data for analysis, and mines this data through big data processing and correlation techniques, significantly reducing the cost of acquiring analytical data. Based on MR data analysis, it achieves network-following-traffic capability, thus improving the adaptability of the supplementary uplink function. Furthermore, based on gridded analysis, it considers both the uplink coverage supplementation of the demanding cells and the uplink capacity of the supplementary cells, and iteratively optimizes the process, improving the accuracy and rationality of the associated cell configuration.

[0218] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0219] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0220] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the methods of each embodiment of the present invention.

[0221] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for supplementing uplink associated cell configuration, characterized in that, The method includes the following steps: Collect measurement report (MR) data for supplementary uplink demand cells and supplementary uplink cells; The MR data of the supplementary uplink demand cells and the supplementary uplink cells are processed and associated to generate an associated cell set; The associated cell set is rasterized to obtain the rasterized result; Based on the rasterization results, supplementary uplink cell optimization is performed on the associated cell set to generate a supplementary uplink associated cell adjustment scheme; The step of performing supplementary uplink cell optimization on the associated cell set based on the rasterization result and generating a supplementary uplink associated cell adjustment scheme includes: Based on the rasterization results and the collected MR data, the proportion of weak uplink coverage rasteres covered by the supplementary uplink demand cell is calculated. The priority order of the cells requiring supplementary uplink coverage is obtained by sorting the proportions of the uplink weak coverage grids. Based on the priority order of the supplementary uplink demand cells, supplementary uplink cells are matched for the supplementary uplink demand cells, and the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell is evaluated to obtain the evaluation result. Based on the evaluation results, the best supplementary uplink cell is selected, and a supplementary uplink associated cell adjustment scheme is generated.

2. The method according to claim 1, characterized in that, The steps for collecting MR data of supplementary uplink demand cells and supplementary uplink cells include: When a user terminal accesses the wireless network to perform services, the serving cell and surrounding neighboring cells occupied by the user terminal are measured, and NR and SUL site data of the serving cell and surrounding neighboring cells are collected at preset time intervals to obtain user MR sampling point information. Collect cell parameter information; Based on the user MR sampling point information and cell parameter information, the uplink signal strength values ​​of the serving cell and neighboring cells at each sampling point are calculated to obtain the MR data of the supplementary uplink demand cell and the supplementary uplink cell.

3. The method according to claim 1, characterized in that, The step of processing and associating the MR data of the supplementary uplink demand cells and the supplementary uplink cells to generate an associated cell set includes: Based on the MR data, the supplementary uplink demand cells and supplementary uplink cells are divided into relatively independent cell sets; Calculate the pairwise correlation coefficients between cells in the cell set to obtain the cell-to-cell correlation coefficients; Cell pairs with a correlation coefficient greater than a preset threshold are selected as cells to be merged. The cells to be merged are merged to generate a set of associated cells.

4. The method according to claim 2, characterized in that, The step of performing rasterization processing on the associated cell set to obtain the rasterized result includes: The geographical area controlled by the wireless network system is rasterized to form a preset geographical area raster. For each of the associated cell sets, the sampling points in the associated cell set are projected onto the preset geographical area grid, and the number of sampling points and the average uplink and downlink signal strength of each cell on the preset geographical area grid are calculated to obtain the rasterization result.

5. The method according to claim 4, characterized in that, The steps of matching supplementary uplink cells to supplementary uplink demand cells according to their priority order, evaluating the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell, and obtaining the evaluation result include: Based on the priority order of the cells requiring supplementary uplink, the current cell with the highest uplink weak coverage grid ratio is first matched with supplementary uplink cells, and the uplink supplementation coefficient of the current cell is calculated. The uplink supplementation coefficients are sorted in descending order, and the capacity matching of the supplementary uplink cells is performed sequentially. If the capacity matching meets the requirements, the matching is completed, and the matched supplementary uplink cell is bound to the current required cell. If the capacity matching does not meet the requirements, the next supplementary uplink cell in the candidate supplementary uplink cell ranking will be used for the calculation until the matching is completed or the matching fails. Repeat the above steps until all supplementary uplink demand cells in the priority order of the supplementary uplink demand cells have completed the matching of uplink coverage and uplink capacity. Evaluate the uplink coverage compensation capability and uplink capacity compensation capability of each supplementary uplink cell for each supplementary uplink demand cell, and use this as the evaluation result.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Execute the supplementary uplink associated cell adjustment scheme.

7. A supplementary uplink associated cell automatic configuration device, characterized in that, The device includes: The acquisition module is used to collect MR data of supplementary uplink demand cells and supplementary uplink cells; The association module is used to process and associate the MR data of the supplementary uplink demand cell and the supplementary uplink cell to generate an associated cell set; The rasterization processing module is used to perform rasterization processing on the associated cell set to obtain the rasterization result; The optimization module is used to perform supplementary uplink cell optimization on the associated cell set based on the rasterization results, and generate a supplementary uplink associated cell adjustment scheme. The optimization module is further configured to: calculate the proportion of weak uplink coverage grids covered by the supplementary uplink demand cells based on the rasterization results and the collected MR data; sort the proportions of weak uplink coverage grids to obtain the priority order of the supplementary uplink demand cells; match supplementary uplink cells for the supplementary uplink demand cells according to the priority order of the supplementary uplink demand cells; evaluate the uplink compensation capability of each supplementary uplink cell in the associated cell set for each supplementary uplink demand cell to obtain the evaluation result; and select the best supplementary uplink cell based on the evaluation result to generate a supplementary uplink associated cell adjustment scheme.

8. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the supplementary uplink associated cell configuration method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the supplementary uplink associated cell configuration method as described in any one of claims 1-6.

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