Uplink and downlink subframe matching method and device, and medium

Abstract

The embodiment of the invention provides an uplink and downlink subframe matching method and device and a medium, and the uplink and downlink subframe matching method comprises the steps: obtaining initial service data of an initial cell; performing region cluster division on the initial cell according to the initial service data to obtain a target region cluster and target service data corresponding to the target region cluster; and determining target subframe matching data of the target area cluster according to the target service data, and performing uplink and downlink subframe matching on a corresponding cell in the target area cluster according to the target subframe matching data. According to the embodiment of the invention, the initial cell is subjected to cluster division according to the initial service data of the initial cell, and the difference between the uplink subframe ratio and the downlink subframe ratio of the corresponding cell in the divided target cluster is small, so that when the target subframe ratio data of the target cluster is determined according to the target service data, the target sub-frame ratio data of the target cluster is determined; the accuracy of the uplink and downlink subframe ratio of the corresponding cell in the target cluster can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an uplink and downlink subframe matching method, device and medium. Background Art

[0002] In a mobile communication system in the time division duplexing (TDD) mode, reception and transmission are in different time slots of the same frequency channel (i.e., carrier), and the reception and transmission channels are separated by guaranteed time. In order to give full play to the advantages of the TDD system, the wireless frame structure of the Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) or Time Division Long Term Evolution (TD-LTE) system can adopt different uplink and downlink time slot ratios to meet different uplink and downlink data transmission requirements.

[0003] At present, the methods for automatically adjusting the uplink and downlink subframe ratio in the relevant technology include: (1) selecting the optimal subframe ratio based on the uplink and downlink services of a single cell, that is, each cell independently adjusts the uplink and downlink subframe ratio according to its own uplink and downlink services; (2) each cell selects its own optimal subframe ratio before coordinating between cells. However, the first method is prone to serious cross-time slot interference after adjustment. Although the second method takes into account the disadvantages of the first method, due to the inconsistency of the subframe ratios of each cell, it is easy to cause negotiation failure or ping-pong effect in order to satisfy the unilateral result. Therefore, how to effectively improve the accuracy of the uplink and downlink subframe ratio is a technical problem that needs to be solved at present. Summary of the invention

[0004] The embodiment of the present invention provides an uplink and downlink subframe matching method, device and medium. The uplink and downlink subframe matching method can improve the accuracy of uplink and downlink subframe matching of a cell.

[0005] In a first aspect, an embodiment of the present invention provides an uplink and downlink subframe ratio method, the method comprising:

[0006] Obtaining initial service data of the initial cell;

[0007] Clustering the initial cell according to the initial service data to obtain a target cluster and target service data corresponding to the target cluster;

[0008] The target subframe ratio data of the target cluster is determined according to the target service data, and the uplink and downlink subframe ratios are performed on the corresponding cells in the target cluster according to the target subframe ratio data.

[0009] In a second aspect, an embodiment of the present invention provides an uplink and downlink subframe matching device, including:

[0010] Processor and memory;

[0011] The memory stores program instructions, and when the program instructions are executed by the processor, the processor executes the uplink and downlink subframe ratio method as described in the first aspect above.

[0012] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium storing program instructions, wherein when the program instructions are executed by a computer, the uplink and downlink subframe ratio method as described in the first aspect above is implemented.

[0013] In an embodiment of the present invention, initial service data of an initial cell is obtained, and the initial cell is clustered according to the initial service data to obtain a target cluster and target service data corresponding to the target cluster. After clustering, target subframe ratio data of the target cluster is determined according to the target service data. At this time, the target subframe ratio data is the better subframe ratio data determined by balancing each cell in the target cluster, that is, uplink and downlink subframe ratios are performed for the corresponding cells in the target cluster according to the target subframe ratio data. In an embodiment of the present invention, the initial cell is clustered according to the initial service data of the initial cell. The uplink and downlink subframe ratios of the cells in the divided target cluster are less different. Therefore, when the target subframe ratio data of the target cluster is determined by the target service data, the accuracy of the uplink and downlink subframe ratios of the corresponding cells in the target cluster can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0015] Figure 1 It is a scenario system architecture diagram of uplink and downlink subframe ratio in practical applications of an embodiment of the present invention;

[0016] Figure 2 is a flowchart of the steps of the uplink and downlink subframe matching method provided by an embodiment of the present invention;

[0017] Figure 3 is a step flow chart of step S210 provided in an embodiment of the present invention;

[0018] Figure 4 is another step flow chart of step S210 provided by an embodiment of the present invention;

[0019] Figure 5is another step flow chart of step S220 provided by an embodiment of the present invention;

[0020] Figure 6 is a flowchart of step S510 provided by an embodiment of the present invention;

[0021] Figure 7 is a schematic diagram of the structure of a raster image provided by an embodiment of the present invention;

[0022] Figure 8 is a flowchart of step S520 provided in an embodiment of the present invention;

[0023] Fig. 9 is a flowchart of step S840 provided by an embodiment of the present invention;

[0024] Fig.10 is a schematic diagram of the structure of an edge cell in a cluster provided by an embodiment of the present invention;

[0025] Fig.11 is a flowchart of step S920 provided by an embodiment of the present invention;

[0026] Fig.12 is a flowchart of step S1180 provided by an embodiment of the present invention;

[0027] Fig.13 is a schematic diagram of a grid image of an initial region cluster 1 provided in an embodiment of the present invention;

[0028] Fig.14 is a schematic diagram of a grid image of an initial region cluster 2 provided in an embodiment of the present invention;

[0029] Fig.15 is a schematic diagram of a grid image of an initial area cluster 3 provided in an embodiment of the present invention;

[0030] Fig.16 is a specific execution flow chart of the uplink and downlink subframe matching method provided by an embodiment of the present invention;

[0031] Fig.17 It is a structural schematic diagram of an uplink and downlink subframe matching device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0033] It should be understood that in the description of the embodiments of the present invention, if there is a description of "first", "second", etc., it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or implicitly indicating the order of the indicated technical features. "At least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any group of these items, including any group of single or plural items. For example, at least one of a, b and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0034] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0035] The following is an analysis of several terms involved in the present invention:

[0036] Time Division Duplexing (TDD): It is a full-duplex communication technology used in mobile communication systems. It is also a technology that distinguishes wireless channels in a timely manner and continues uplink operations in the downlink operation of the frame period. In the TDD mode mobile communication system, reception and transmission are in different time slots of the same frequency channel (i.e., carrier), and the reception and transmission channels are separated by guaranteed time.

[0037] In the TDD frame structure, the frame length is 10 milliseconds (ms), which is divided into 10 subframes of 1 ms in length. The uplink and downlink data are transmitted in different subframes in the same frame. TDD specifies different uplink and downlink time ratios. The uplink and downlink time ratios can be adjusted according to different service types to meet the asymmetric uplink and downlink service requirements.

[0038] Cell: also known as cellular cell, refers to the area covered by a base station or a part of a base station (sector antenna) in a cellular mobile communication system, within which the mobile station can communicate reliably with the base station through a wireless channel.

[0039] Ping-Pong Effect: refers to the switching back and forth between two different states. In different fields, the ping-pong effect has different interpretations. In a mobile communication system, if the signal strength of two base stations changes dramatically in a certain area, the mobile phone will switch back and forth between the cells corresponding to the two base stations, resulting in the so-called "ping-pong effect".

[0040] Beam angle: It refers to the angle from the extension line of the ultrasonic sensor's central axis to the point where the energy intensity is reduced by half (-3dB). When the ultrasonic sensor transmits ultrasonic waves, the energy of the ultrasonic ray along the extension line of the sensor's central axis (perpendicular to the sensor surface) is the largest. From this point onward, the sound wave energy in other directions gradually weakens.

[0041] In a mobile communication system in time division duplexing (TDD) mode, reception and transmission are in different time slots of the same frequency channel (i.e., carrier), and guaranteed time is used to separate the reception and transmission channels. In order to give full play to the advantages of the TDD system, the wireless frame structure of the Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) or Time Division Long Term Evolution (TD-LTE) system can adopt different uplink and downlink time slot ratios to meet different uplink and downlink data transmission requirements. Figure 1As shown, it is a schematic diagram of a scenario in which signal interference occurs between cells in mobile communication in TDD mode. The first initial cell 110 and the second initial cell 120 are adjacent cells, and the first initial cell 110 and the second initial cell 120 correspond to different base stations 130. The first initial cell 110 corresponds to the first TDD frame structure 111, and the second initial cell 120 corresponds to the second TDD frame structure 121. The structures of the first TDD frame structure 111 and the second TDD frame structure 121 are the same, except that there are differences in the uplink and downlink subframe ratios. The TDD frame structure of an embodiment of the present invention includes 10 subframes with a length of 1 ms, which are represented as slot0-slot9 from left to right, and each subframe contains 2 time slots of 0.5 ms, that is, two time slots are grouped together for scheduling, and U in the TDD frame structure represents uplink signal scheduling, D represents downlink signal scheduling, and S represents shared signal scheduling. Since there are relatively more uplink services based on the terminal 140 in the first initial cell 110, the uplink time slot ratio in the first TDD frame structure 111 corresponding to the first initial cell 110 is adjusted and increased, but at this time, the uplink signal sent by the terminal in slot 6 and slot 7 of the first initial cell 110 will be interfered by the downlink signal in slot 6 and slot 7 corresponding to the second initial cell 120. Similarly, since there are relatively more downlink services based on the terminal 140 in the second initial cell 120, the downlink time slot ratio in the second TDD frame structure 121 corresponding to the second initial cell 120 is adjusted and increased, but at this time, the downlink signal sent by the terminal in slot 6 and slot 7 of the second initial cell 120 will be interfered by the uplink signal in slot 6 and slot 7 corresponding to the first initial cell 110. Therefore, when more and more surrounding cells have this type of subframe ratio, serious cross-time slot interference problems are likely to occur, which ultimately leads to deterioration of network performance and user perception.

[0042] At present, the methods for automatically adjusting the uplink and downlink subframe ratio in the related art include: (1) selecting the optimal subframe ratio based on the uplink and downlink services of a single cell, that is, each cell independently adjusts the uplink and downlink subframe ratio according to its own uplink and downlink services; (2) each cell selects its own optimal subframe ratio before coordinating between cells. However, the first method does not consider the consistency of the frame structure with the surrounding cells, which is likely to cause serious cross-time slot interference after adjustment. Although the second method takes into account the disadvantages of the first method, since each cell makes a selection separately and then uses the selected result to negotiate with the surrounding cells, it will bring two types of problems. One is that the subframe ratios of the two cells are inconsistent, the negotiation cannot be reached, the optimization fails, and the uplink and downlink subframe ratio cannot be adjusted; the other is that the negotiation parties take effect according to the unilateral result, but it may not meet the service needs of the other cell, or the subframe ratio adjustment produces a ping-pong effect. Therefore, how to effectively improve the accuracy of the uplink and downlink subframe ratio is a technical problem that needs to be solved at present.

[0043] In order to solve the above problems, the embodiments of the present invention provide an uplink and downlink subframe ratio method, device and medium, which can improve the accuracy of uplink and downlink subframe ratio of a cell.

[0044] The embodiments described in the present invention may be implemented in a communication system, such as in at least one of the following systems: a global system for mobile communications (GSM) or any other second generation cellular communication system, a universal mobile telecommunications system (UMTS, 3G) based on basic wideband code division multiple access (W-CDMA), high speed packet access (HSPA), long term evolution (LTE), advanced LTE, a system based on the IEEE 802.11 specification, a system based on the IEEE 802.15 specification and / or a fifth generation (5G) mobile or cellular communication system; and future mobile communication systems. However, the embodiments are not limited to the systems given in the above examples, but those skilled in the art may apply the solutions to other communication systems having the necessary properties.

[0045] like Figure 2 As shown, it is a flow chart of an uplink and downlink subframe ratio method provided by an embodiment of the present invention. The implementation process of the method includes but is not limited to the following steps S210 to S230, and each step is introduced in turn below:

[0046] Step S210, obtaining initial service data of the initial cell.

[0047] Specifically, the initial cell refers to the cell object before inter-cell coordination. The initial cell includes at least one target terminal, and the initial service data refers to the set of service data corresponding to all target terminals in the initial cell. The terminal in the cell refers to a smart phone, tablet computer, laptop computer, desktop computer, etc. used in the communication network corresponding to the cell.

[0048] It should be noted that the initial cells in the embodiment of the present invention are the cells under the contiguous area, and the contiguous area is the set area range. For example, the contiguous area is divided according to the area of ​​the set area, or the area range is divided according to the number of cells contained in the contiguous area.

[0049] It should be noted that the initial service data includes service data of each corresponding target terminal, and the service data refers to uplink and downlink service indicators of the terminal in the corresponding cell.

[0050] It should be noted that, if the embodiment of the present invention detects that the uplink and downlink subframe ratio of a cell in the network changes dynamically, and the change is an overall change in the region, an action to cause cell migration will be performed before the change.

[0051] It should be noted that when a change in a terminal in a cell is detected, the initial service data of the initial cell at the current moment is collected in real time to execute the uplink and downlink subframe ratio method of the implementation example of the present invention.

[0052] In one embodiment, Figure 3 As shown, it is a specific flow chart of step S210 provided in an embodiment of the present invention. Step S210 specifically includes but is not limited to the following steps S310 to S330. Each step is introduced in turn below:

[0053] Step S310, determining the data collection type, the data collection type includes a time collection type;

[0054] It can be understood that the data collection type refers to a data collection method for obtaining the initial service data corresponding to the initial cell. The data collection type includes a time collection type. The time collection type refers to a method for uniformly considering the uplink and downlink service conditions of each cell in a contiguous area within a specific time period, and realizing a method for uniformly adjusting the uplink and downlink subframe ratio of each cell within a specific time period.

[0055] Step S320: When the data collection type is a time collection type, data is collected from the target terminal in the initial cell according to a preset sampling interval to obtain first characteristic data.

[0056] It is understandable that in order to increase the uplink and downlink subframe ratio speed of each cell in a contiguous area, the embodiment of the present invention can collect data from the target terminal in the initial cell according to a preset sampling interval when the data collection type is the time collection type to obtain the first characteristic data.

[0057] It is understandable that the preset sampling interval is a time interval before the current uplink and downlink subframe matching time. The preset sampling interval can be 1 minute, 5 minutes, etc., and can be flexibly set according to actual needs, which will not be described here.

[0058] It can be understood that the first characteristic data refers to the service data collected from the target terminal in the corresponding initial cell within the preset sampling interval. For example, the contiguous area contains 3 initial cells, each of which contains 10 target terminals, and the preset sampling interval is 1 minute. The service data of the target terminal in each initial cell within 1 minute before the current uplink and downlink subframe matching is collected separately to obtain the first characteristic data of the target terminal in the corresponding initial cell. At this time, the number of first characteristic data is 3*10=30.

[0059] Step S330: combine the first characteristic data to obtain initial service data corresponding to the initial cell.

[0060] Specifically, the first characteristic data of the target terminal in the same initial cell are combined, and the initial service data can be obtained in the form of a table, a list, a tuple, etc.

[0061] It can be understood that the advantage of step S310 to step S330 is that data collection is performed on the target terminal in the initial cell according to the preset sampling interval to obtain initial service data, which can effectively improve the uplink and downlink subframe ratio speed of each cell in the contiguous area.

[0062] In one embodiment, Figure 4 As shown, another specific flow chart of step S210 provided in an embodiment of the present invention. After step S310, the method for obtaining the initial service data of the initial cell in step S210 may also include but is not limited to the following steps S410 to S430, and each step is introduced in turn below:

[0063] Step S410: When the data collection type is a prediction collection type, a pre-trained data prediction model and historical feature data of the target terminal in the initial cell are obtained.

[0064] It can be understood that the data collection type also includes a prediction collection type, which refers to a method of inferring possible business data of the terminal in the future cell by combining the business data of the target terminal in the initial cell. The data prediction model refers to predicting the business data of the target terminal in the initial cell at the next time based on the business data of the target terminal in the initial cell at the current time. Therefore, when the prediction collection type is specifically implemented, it can be based on the data prediction model combined with the business data of the target terminal in the initial cell to infer the possible business data of the terminal in the future cell.

[0065] It should be noted that the data prediction model is a model that can realize intelligent learning of feature data such as business data, etc. The network structure of the data prediction model can be a back propagation (BP) neural network, a radial basis function neural network (RBF neural network), etc.

[0066] It should be noted that when training the data prediction model, a training sample set is first obtained, and the training sample set includes multiple business samples. The business sample includes sample business data and sample label data, and the sample label data is a label of the sample business data, that is, the sample label data refers to the business data set of the corresponding terminal in the cell collected at the next collection time according to the collection time corresponding to the sample business data. The sample business data is similar to the above-mentioned initial business data and will not be repeated here. The sample business data includes sample business sub-data corresponding to each terminal, and the sample label data includes sample label sub-data corresponding to each terminal. Each sample business sub-data is input into the data prediction model for data prediction to obtain the predicted business sub-data of each terminal. The loss is calculated based on the sample label sub-data and the predicted business sub-data to obtain the loss value. According to the loss value, the parameters of the data prediction model are adjusted until the model after the parameter adjustment can meet the preset end condition, and the required data prediction model is obtained according to the model parameters and model structure at this time.

[0067] It should be noted that the preset end condition can be that the prediction accuracy of the sample business sub-data reaches a preset threshold, such as 90%, 95%, etc., or the number of adjustment times for the model parameters reaches an iteration threshold, etc., which can be set according to actual needs and will not be repeated here.

[0068] It can be understood that the historical feature data refers to the service data corresponding to the target terminal in the initial cell collected at the current time, and the historical feature data is used to predict the service data of the terminal in the initial cell at a future time.

[0069] Step S420: input the historical feature data into the data prediction model to perform data prediction to obtain second feature data.

[0070] Specifically, the historical feature data corresponding to each target terminal in the initial cell at the current time is input into the data prediction model for data prediction, and the service data corresponding to each target terminal in the initial cell at the future time is obtained, that is, the second feature data. The data quantity of the second feature data is the same as the data quantity of the target terminal.

[0071] It can be understood that the embodiment of the present invention predicts the service data of terminals in the cell in the future through the data prediction model, and can obtain more effective second feature data, thereby reducing the service data collection process for terminals in the cell in the future and improving the accuracy of the subsequent uplink and downlink subframe ratios of each cell in the contiguous area.

[0072] Step S430: combine the second characteristic data to obtain initial service data corresponding to the initial cell.

[0073] Specifically, the second characteristic data of the target terminal in the same initial cell are combined, and the initial service data can be obtained in the form of a table, a list, a tuple, etc.

[0074] It can be understood that the advantage of step S410-step S430 is that based on the data prediction model and the service data of the target terminal in the initial cell at the current time, the possible second characteristic data of the target terminal in the initial cell in the future time is predicted, so as to obtain high-quality initial service data based on the second characteristic data, which can effectively improve the accuracy of the uplink and downlink subframe ratio of each cell in the contiguous area.

[0075] Step S220: cluster the initial cell according to the initial service data to obtain a target cluster and target service data corresponding to the target cluster.

[0076] It is understandable that in order to jointly analyze similar cells, reduce the impact of cross-time slot interference between cells on the boundary, and improve the success rate of dynamic adjustment of uplink and downlink subframe ratios, the embodiment of the present invention clusters multiple initial cells according to initial service data to obtain multiple target clusters and target service data corresponding to each target cluster.

[0077] It should be noted that the target cluster includes at least one target cell, and the target cell is used to represent the initial cell divided into the target cluster. The target service data refers to the set of service data of the target cell in the current target cluster after the cluster is divided.

[0078] like Figure 5 As shown, it is a specific flow diagram of step S220 provided in an embodiment of the present invention. Step S220 specifically includes but is not limited to the following steps S510 to S530. Each step is introduced in turn below:

[0079] Step S510, constructing a grid according to the initial business data to obtain an initial grid image.

[0080] It can be understood that the initial grid image corresponding to the initial cell is constructed according to the initial service data corresponding to each initial cell. The initial grid image can be understood as an uplink and downlink service grid matrix, and the uplink and downlink service grid matrix includes multiple cell logical grids, and each cell logical grid is used to store the uplink and downlink service data corresponding to each terminal belonging to the grid.

[0081] It should be noted that each cell logic grid can be represented as a terminal belonging grid of service data of one or more target terminals. When all terminals in the initial cell belong to the corresponding grid, a grid image of the entire cell is obtained.

[0082] It should be noted that the grid in the embodiment of the present invention is used to represent corresponding uplink and downlink characteristic information.

[0083] like Figure 6 As shown, it is a specific flow chart of step S510 provided in an embodiment of the present invention. Step S510 specifically includes but is not limited to the following steps S610 to S630. Each step is introduced in turn below:

[0084] Step S610: performing position selection on the initial service data according to the terminal position element to obtain the terminal grid position.

[0085] It should be noted that the initial service data collected within the current time includes a terminal location element and a terminal service element. The initial service data includes initial service sub-data corresponding to each target terminal, and each initial service sub-data includes a terminal location sub-element and a terminal service sub-element of the corresponding terminal. The terminal location element refers to a set of terminal location sub-elements, and the terminal service element refers to a set of terminal service sub-elements. The terminal location sub-element refers to the location information of each terminal. The terminal location sub-element refers to data indicating the position of the terminal relative to the cell according to at least one positioning method such as direction of arrival (DOA), beam sequence number (New Radio Beam Id, BeamId) of the new wireless / new air interface, and beam angle (Tilt and Azi, TA). The terminal service sub-element refers to any indicator that can reflect the uplink and downlink traffic, including but not limited to uplink and downlink service indicators, uplink and downlink bandwidth speed, etc.

[0086] It can be understood that the positioning method of the terminal position sub-element and the constructed initial grid image contain a corresponding relationship. For example, if the positioning method of the terminal position sub-element is the DOA method, then an initial grid image based on the DOA method is constructed to achieve accurate alignment of the target terminal and the grid. When the terminal in the cell is assigned to the corresponding grid of the grid image, the terminal position sub-element corresponding to each target terminal is matched with the corresponding position in the grid image, and the terminal grid position is obtained according to the position of the cell logical grid to which the initial service sub-data corresponding to the target terminal is assigned in the grid image. The terminal grid position refers to the coordinate data of the grid to which each target terminal belongs in the grid image.

[0087] Step S620: determining a target service element according to the terminal grid position and the terminal service element.

[0088] Specifically, because each terminal grid position may contain at least one terminal service sub-element of a target terminal, when the terminal grid position is attributed to the terminal service sub-elements of at least two target terminals, the uplink service indicators and downlink service indicators of all the terminal service sub-elements in the same grid position are respectively accumulated and calculated to obtain the accumulated uplink indicator and the accumulated downlink indicator. According to the number of target terminals in the same grid position, the accumulated uplink indicator and the accumulated downlink indicator are respectively averaged to obtain the grid uplink service indicator and the grid downlink service indicator corresponding to the same grid position. For example, when the uplink and downlink service indicators are uplink and downlink service flows, a terminal grid position is attributed to terminal 1, terminal 2, and terminal 3, the terminal service sub-element of terminal 1 includes 1115 kilobytes (KB) of uplink service flow and 1221KB of downlink service flow, the terminal service sub-element of terminal 2 includes 1121KB of uplink service flow and 1002KB of downlink service flow, and the terminal service sub-element of terminal 3 includes 257KB of uplink service flow and 456KB of downlink service flow. The uplink traffic and downlink traffic of all terminal service sub-elements in the same grid position are accumulated and calculated respectively, and the accumulated uplink index is 1115+1121+257=2493KB, and the accumulated downlink index is 1221+1002+456=2679KB. According to the number of target terminals in the same grid position, the accumulated uplink index and the accumulated downlink index are averaged, and the grid uplink service index corresponding to the same grid position is 2493 / 3=831KB, and the grid downlink service index is 2679 / 3=893KB.

[0089] It should be noted that the target service element includes a grid uplink service indicator and a grid downlink service indicator corresponding to the same grid position.

[0090] Step S630, constructing a grid according to the terminal grid position and the target service element to obtain an initial grid image.

[0091] It can be understood that after the target service element of each terminal grid position in the grid image is calculated, an initial grid image corresponding to each initial cell is obtained.

[0092] For example, Figure 7 As shown in FIG. 1 , a schematic diagram of the structure of a grid image provided by an embodiment of the present invention is shown. For example, the cell logic grid in the grid image is divided by beam angle TA, and each column in the grid image represents the vertical angle Tilt corresponding to the terminal position sub-element, and as shown in FIG. Figure 7 Tilt0 to Tilt7 are set, and Tilt0 to Tilt7 represent different vertical angles; each row represents the horizontal angle Azi corresponding to the terminal position sub-element, and Figure 7Azi0 to Azi7 are set, and Azi0 to Azi7 represent different horizontal angles. A rectangular block corresponding to a vertical angle Tilt and a horizontal angle Azi in the grid image represents a cell logical grid, and each grid is used to store the uplink and downlink service indicators of the target terminal belonging to the grid. Assuming that the terminal position sub-element of the terminal service sub-data corresponding to the collected target terminal is (t, azi), the beam angle Tilt2≤t<Tilt3, and the horizontal angle Azi3≤azi<Azi4, the target terminal belongs to the grid corresponding to the column Tilt3 and the line Azi4, that is, the grid to which it belongs is Tilt3Azi4.

[0093] It can be understood that the advantage of step S610-step S630 is that a corresponding initial grid image is constructed for each initial cell, and uplink and downlink subframe ratios are performed for all cells in the contiguous area according to the initial grid image, which can effectively reduce the impact of cross-time slot interference between cells on the boundary.

[0094] Step S520 , clustering the initial cells according to the initial grid image to obtain a target cell cluster.

[0095] Specifically, after constructing the initial grid image corresponding to each initial cell, the initial cell is divided into cell clusters for the first time according to the initial grid image, that is, the initial cell is clustered to obtain the target cluster. The embodiment of the present invention uses a clustering algorithm to cluster the uplink and downlink services of all cells in the contiguous area, that is, the initial cells with similar uplink and downlink service characteristics are clustered into one category to form multiple target clusters, so as to select a better uplink and downlink subframe ratio for each cluster, thereby improving the success rate of dynamic adjustment of the uplink and downlink subframe ratio and effectively reducing the interference effect of cross-time slots between cells on the boundary.

[0096] It should be noted that the embodiment of the present invention adopts a clustering algorithm to divide the cells into clusters. Other algorithms may also be adopted to divide the cells with similar uplink and downlink service characteristics into cell clusters, which is not specifically limited here.

[0097] like Figure 8 As shown, it is a specific flow chart of step S520 provided in an embodiment of the present invention. Step S520 specifically includes but is not limited to the following steps S810 to S840. Each step is introduced in turn below:

[0098] Step S810: Select a first number of initial cluster cells from the initial cells.

[0099] Specifically, assuming that the preset contiguous area includes N c initial cells, and N c≥2, c represents a cell. The first cluster number M is randomly selected from the initial cell according to the initial grid image corresponding to the initial cell. c Initial clustering cells, and 1≤M c ≤K, where K is the preset maximum expected number of clusters. The grid image similarity value between the initial grid images of any two initial clustering cells is less than the preset grid dissimilarity threshold. The smaller the similarity value, the farther the distance between the two initial grid images, that is, the less similar the uplink and downlink service indicators of the corresponding two initial clustering cells.

[0100] It should be noted that the raster image similarity value between the initial raster images of any two initial clustering cells may be determined by an average or a weighted average.

[0101] In one embodiment, the grid image similarity value between the initial grid images of any two initial clustering cells is determined by using an average. Figure 7 The 7*7=49 grids shown in the figure are used to calculate the similarity of the data of the corresponding grids in the two initial grid images, and 49 grid similarity values ​​are obtained. The 49 grid similarity values ​​are added and the average is calculated to obtain the grid image similarity value. The advantage of using the average method to calculate the initial grid image is that the influence of each pair of corresponding grid data in the two initial grid images on the grid image similarity value is the same, which improves the fairness of determining the grid image similarity value.

[0102] In another embodiment, the grid image similarity value between the initial grid images of any two initial clustering cells is determined by weighted average. Figure 7 The 7*7=49 grids shown in the figure set the same grid weight value for the corresponding grids in the two initial grid images, and the sum of all grid weight values ​​in one initial grid image is 1. The data of the corresponding grids in the two initial grid images are similarity calculated to obtain 49 grid similarity values. The 49 grid similarity values ​​are multiplied by the corresponding grid weight values ​​and then added to obtain the grid image similarity value. The advantage of using the weighted average method to calculate the initial grid image is that different weights can be flexibly set for each grid in the grid image according to the needs of the actual application, which improves the flexibility of determining the similarity value of the raster image.

[0103] It should be noted that when calculating the raster image similarity value, the data corresponding to the raster in the initial raster image includes an uplink service indicator and a downlink service indicator. According to the above embodiment, the uplink raster image similarity value corresponding to the uplink service indicator and the downlink raster image similarity value corresponding to the downlink service indicator are respectively solved. After that, the uplink raster image similarity value and the downlink raster image similarity value are averaged to obtain the final raster image similarity value between the initial raster images of any two initial clustering cells.

[0104] It should be noted that the similarity between two data may be calculated using a cosine function, a Euclidean distance function, etc., which is not specifically limited here.

[0105] Step S820: Screen out a first cell from the initial cells according to the initial cluster cells. The first cell is different from the initial cluster cells, and the number of cells of the first cell is the difference between the number of cells of the initial cells and the number of cells of the first cluster.

[0106] Specifically, when determining M c After the initial clustering cells, N c The initial clustering cells are excluded from the initial cells, and each cell in the remaining initial cells is used as the first cell, the first cell is not the initial clustering cell, and the number of the first cells is (N c -M c )indivual.

[0107] Step S830: performing cluster division according to the initial cluster cells and the first cells to obtain a first number of initial clusters, and taking the cells divided into the initial clusters as second cells.

[0108] It is understandable that in determining M c The initial clustering cells and (N c -M c ) first cells, each first cell is divided into a cluster based on the initial cluster cells. Each first cell is assigned to the cluster represented by the initial cluster cell closest to the first cell. After all the first cells are assigned, M c An initial cluster is created, and the first cell divided into the corresponding initial cluster is used as the second cell.

[0109] For example, by traversing N c The initial grid image of the initial cell, if according to the function Func(Cell i ,Cell j ) is greater than or equal to the preset grid image similarity threshold, i∈M c , j∈(N c -M c ), and i≠j, then Celli and Cell j Belong to the same cluster and finally complete M c The cell clusters are divided and the current cluster center cell of each cell cluster is determined respectively.

[0110] The Func(·) function expresses the calculation of the similarity value of the raster images corresponding to the two cells, and the specific calculation process is the same as the calculation process of the raster image similarity value, which will not be repeated here.

[0111] It should be noted that, since the initial clustering cell determined by one clustering is not necessarily the most suitable clustering center cell, it is necessary to re-execute steps S810 to S830 for all cells after clustering, that is, to re-determine new initial clustering cells, first cells, target clusters, and second cells. Through iterative cycles, until all initial clustering cells obtained twice in a row are the same cells, or the number of clustering iterations reaches a preset number of iterations, the initial cluster after clustering and the second cell divided into the initial cluster are determined.

[0112] Step S840: when the first cluster number is greater than the preset second cluster number, the target terminal corresponding to the initial grid image in the initial cluster is updated in clusters until the number of remaining initial clusters after the cluster update is the second cluster number, and the remaining initial clusters are used as target clusters.

[0113] It can be understood that the second cluster number is the preset minimum acceptable number of adjacent cluster types, and the second cluster number is recorded as P. When the first cluster number is greater than the preset second cluster number, it means that there are more than P areas of different cluster types adjacent to the cell in the initial cluster after cluster division, and the initial cluster needs to be optimized for the cell cluster. The target terminal corresponding to the initial grid image in the initial cluster is clustered, that is, the cell terminal in the initial cluster that meets the conditions is migrated or the cluster is changed, until the number of the remaining initial clusters after the cluster update is the second cluster number, and the remaining initial cluster is used as the target cluster.

[0114] It can be understood that the advantage of step S810-step S840 is that the embodiment of the present invention performs cluster division according to the initial clustering cell and the first cell, can divide the cells with similar uplink and downlink service indicators into the same cell cluster, and re-analyze and reclassify the adjacent areas of multiple cluster divisions, which can effectively reduce the number of cell clusters and reduce the impact of cross-slot interference between cells on the boundaries.

[0115] like Fig. 9As shown, it is a specific flow chart of step S840 provided in an embodiment of the present invention. Step S840 specifically includes but is not limited to the following steps S910 to S930. Each step is introduced in turn below:

[0116] Step S910, determine the edge cell and the first adjacent cell and the second adjacent cell adjacent to the edge cell from the initial cluster, the edge cell, the first adjacent cell and the second adjacent cell belong to different initial clusters respectively, and use the initial raster image of the edge cell as the first raster image, the initial raster image of the first adjacent cell as the second raster image, and the initial raster image of the second adjacent cell as the third raster image.

[0117] It can be understood that an edge cell refers to a cell that is located in the closest position to another adjacent cell cluster in the cell cluster. Fig.10 As shown, for example, an initial cluster 1010 includes 5 second cells, and the middle 3 second cells 1011 are surrounded by the second cells on both sides. Then the middle three second cells 1011 have no adjacent relationship with the cells in other initial clusters 1020. However, since the second cells 1011 on both sides of the initial cluster 1010 have adjacent relationships with the cells in other adjacent initial clusters 1020, they are edge cells 1012. Since the edge cells 1020 are located in adjacent positions of adjacent initial clusters, and the uplink and downlink subframe ratios of different initial clusters may be different, the edge cells 1020 are prone to cross-slot interference between cells.

[0118] Specifically, since the number of cells adjacent to the edge cell is at least 2, the edge cell and the first adjacent cell and the second adjacent cell adjacent to the edge cell are determined from the initial cluster, and the edge cell, the first adjacent cell and the second adjacent cell belong to different initial clusters respectively. The initial raster image of the edge cell is used as the first raster image, the initial raster image of the first adjacent cell is used as the second raster image, and the initial raster image of the second adjacent cell is used as the third raster image, so as to facilitate the subsequent description of the transformation of the cluster change between the edge cell and the adjacent cell.

[0119] It is understandable that by traversing M c N of the initial clusters c Cells, determine the edge cell in an initial cluster as Cell x , and with the edge cell Cell x The adjacent cell is the first adjacent cell Cell y and the second adjacent cell z Among them, edge cells x Belongs to the initial cluster C x , the first adjacent cellCelly Belongs to the initial cluster C y , the second adjacent cell Cell z Belongs to the initial cluster C z .

[0120] Step S920: changing the cluster of the target terminal corresponding to the first raster image according to the second raster image and the third raster image, and updating the initial cluster according to the result of the cluster change to obtain a candidate cluster.

[0121] Specifically, the grid data in the first grid image is calculated according to the second grid image and the third grid image to determine whether the target terminal corresponding to the grid in the first grid image can be changed to other clusters, and P candidate clusters are obtained.

[0122] like Fig.11 As shown, it is a specific flow chart of step S920 provided in an embodiment of the present invention. Step S920 specifically includes but is not limited to the following steps S1110 to S1180. Each step is introduced in turn below:

[0123] Step S1110 , performing raster data selection on the first raster image to obtain first unit raster data and second unit raster data.

[0124] It can be understood that the first grid image includes a plurality of grids, such as Figure 7 As shown, the grid image includes 49 grids. The first unit grid data and the second unit grid data are randomly selected from the grids of the first grid image, the first unit grid data and the second unit grid data are two different grids in the first grid image, and the corresponding terminals in the first unit grid data and the second unit grid data are not the same.

[0125] Specifically, the edge cell x The first unit grid data in is denoted as Grad x1 , the edge cell x The second unit grid data in is denoted as Grad x2 .

[0126] Step S1120 , selecting third unit raster data from the second raster image, and selecting fourth unit raster data from the third raster image.

[0127] Specifically, the first adjacent cell Cell y The corresponding third unit grid data is recorded as Grad y , the second adjacent cell Cell z The corresponding fourth unit grid data is recorded as Grad z .

[0128] Step S1130 , performing similarity calculation on the first unit grid data and each third unit grid data to obtain first similarity data.

[0129] Specifically, according to the function Func(Grad x1 ,Grad y ) The similarity calculation is performed on the first unit grid data and each third unit grid data to obtain the first similarity data S1, and the specific calculation process is the same as the calculation process of the above-mentioned grid image similarity value, which will not be repeated here.

[0130] Step S1140 , performing similarity calculation on the first unit grid data and the fourth unit grid data to obtain second similarity data.

[0131] Specifically, according to the function Func(Grad x1 ,Grad z ) performs similarity calculation on the first unit grid data and each fourth unit grid data to obtain second similarity data S2, and the specific calculation process is the same as the calculation process of the above-mentioned grid image similarity value, which will not be repeated here.

[0132] Step S1150 , performing similarity calculation on the second unit grid data and the third unit grid data to obtain third similarity data.

[0133] Specifically, according to the function Func(Grad x2 ,Grad y ) performs similarity calculation on the second unit raster data and the third unit raster data to obtain third similarity data S3, and the specific calculation process is the same as the calculation process of the raster image similarity value, which will not be repeated here.

[0134] Step S1160 , performing similarity calculation on the second unit grid data and the fourth unit grid data to obtain fourth similarity data.

[0135] Specifically, according to the function Func(Grad x2 ,Grad z ) performs similarity calculation on the second unit raster data and the fourth unit raster data to obtain fourth similarity data S4, and the specific calculation process is the same as the calculation process of the raster image similarity value, which will not be repeated here.

[0136] Step S1170 , performing terminal migration on the target terminal corresponding to the first unit grid data according to the first preset grid similarity threshold, the first similarity data and the second similarity data, and updating the target terminal included in the edge cell according to the result of the terminal migration.

[0137] In one embodiment, the process of performing terminal migration on the target terminal corresponding to the first unit grid data according to the first preset grid similarity threshold, the first similarity data, and the second similarity data, and updating the target terminal included in the edge cell according to the result of the terminal migration is any one of the following scenarios 1 to 3:

[0138] Scenario 1: When the first similarity data is greater than or equal to the first preset grid similarity threshold and the second similarity data is greater than or equal to the first preset grid similarity threshold, the first target similarity data is determined according to the first similarity data and the second similarity data, and the migration cell is determined according to the unit grid data corresponding to the first target similarity data; the target terminal corresponding to the first unit grid data is migrated to the migration cell, and the second grid image or the third grid image is updated according to the result of the terminal migration.

[0139] Specifically, the first similarity data S1 is greater than or equal to the first preset grid similarity threshold, indicating that the uplink and downlink service indicators in the first unit grid data and the third unit grid data are relatively similar. The second similarity data S2 is greater than or equal to the first preset grid similarity threshold, indicating that the uplink and downlink service indicators in the first unit grid data and the fourth unit grid data are relatively similar. Perform a numerical comparison on the first similarity data and the second similarity data, take the similarity data with a larger value as the first target similarity data, and take the cell to which the unit grid data corresponding to the first target similarity data belongs as the migration cell. Migrate the target terminal corresponding to the first unit grid data to the migration cell. For example, if the first similarity data S1 is greater than the second similarity data S2, it means that the uplink and downlink service indicators in the first unit grid data and the third unit grid data are more similar. Move the edge cell Cell x The first unit grid data Grad x1 The target terminal migrates to the first adjacent cell Cell y Grad y In the middle, it is equivalent to the edge cell Cell x The first unit grid data Grad x1 Therefore, since the terminals included in the adjacent cells change after the migration, the corresponding second grid image or third grid image is updated according to the result of the terminal migration. For example, when the first unit grid data Grad x1 When the target terminal under the first cell migrates to the grid corresponding to the first adjacent cell, the second grid image is updated; when the first cell grid data Grad x1 If the target terminal under the control of the edge cell migrates to the grid corresponding to the second adjacent cell, the third grid image is updated. In addition, the target terminal included in the edge cell is updated according to the result of the terminal migration.

[0140] It should be noted that the first preset grid similarity threshold at this time may be the same as the above-mentioned grid image similarity threshold, and may also be flexibly adjusted according to the current migration accuracy, which is not specifically limited here.

[0141] Scenario 2: When the first similarity data is less than the first preset grid similarity threshold and the second similarity data is greater than or equal to the first preset grid similarity threshold, the target terminal corresponding to the first unit grid data is migrated to the second adjacent cell, and the target terminal included in the edge cell is updated according to the result of the terminal migration.

[0142] Specifically, when the first similarity data is less than the first preset grid similarity threshold and the second similarity data is greater than or equal to the first preset grid similarity threshold, it means that the uplink and downlink service indicators in the first unit grid data and the fourth unit grid data are more similar.

[0143] Scenario three: When the first similarity data is greater than or equal to the first preset grid similarity threshold and the second similarity data is less than the first preset grid similarity threshold, the target terminal corresponding to the first unit grid data is migrated to the first adjacent cell, and the target terminal included in the edge cell is updated according to the result of the terminal migration.

[0144] Specifically, when the first similarity data is greater than or equal to the first preset grid similarity threshold and the second similarity data is less than the first preset grid similarity threshold, it means that the uplink and downlink service indicators in the first unit grid data and the third unit grid data are more similar.

[0145] Step S1180, performing cluster change on the updated edge cells according to the second preset grid similarity threshold, the third similarity data and the fourth similarity data, and updating the initial cluster according to the result of the cluster change to obtain a candidate cluster.

[0146] It can be understood that the first unit grid data is used to represent grid data of cells that are migrated to the same adjacent cluster, and the second unit grid data is used to represent grid data similar to cells in another adjacent cluster. After the target terminal corresponding to the first unit grid data in the edge cell is migrated to the cell of the same adjacent cluster, the target terminal corresponding to other grid data that is more similar to another adjacent cell is not migrated, but the new edge cell composed of the remaining other grid data is directly merged into the cluster to which the other adjacent cell belongs, so as to update the initial cluster according to the result of the cluster change and obtain the candidate cluster.

[0147] For example, edge cell x Belongs to the initial cluster C x , the first adjacent cellCell y Belongs to the initial cluster C y, the second adjacent cell Cell z Belongs to the initial cluster C z According to the calculations in steps S1110 to S1140, the edge cell Cell x The first unit grid data Grad x1 The first adjacent cell y The corresponding third unit grid data Grad y If the cells are more similar, adjust the edge cells. x The first adjacent cell y The beam coverage makes the first unit grid data Grad x1 The terminal under migrates to the third unit grid data Grad y , and from the edge cell x Delete the first unit grid data Grad x1 Among them, the first adjacent cell Cell y Not limited to a single cell, can be a cell belonging to the initial cluster C y Then, when the remaining second cell grid data Grad x2 The second adjacent cell z The corresponding fourth unit grid data Grad z More similar, and at this time the edge cell x Only the second unit grid data Grad x2 , then directly set the current edge cell Cell x Merge to the second adjacent cell z Initial cluster C z middle.

[0148] like Fig.12 As shown, it is a specific flow chart of step S1180 provided in an embodiment of the present invention. Step S1180 specifically includes but is not limited to the following steps S1210 to S1240. Each step is introduced in turn below:

[0149] Step S1210: when the third similarity data is greater than or equal to the second preset grid similarity threshold and the fourth similarity data is greater than or equal to the second preset grid similarity threshold, determine the second target similarity data according to the third similarity data and the fourth similarity data.

[0150] It can be understood that the third similarity data S3 is greater than or equal to the second preset grid similarity threshold, indicating that the uplink and downlink service indicators in the second unit grid data and the third unit grid data are relatively similar. The fourth similarity data S4 is greater than or equal to the second preset grid similarity threshold, indicating that the uplink and downlink service indicators in the second unit grid data and the fourth unit grid data are relatively similar. The third similarity data and the fourth similarity data are numerically compared, and the similarity data with the larger value is used as the second target similarity data.

[0151] Step S1220: determining a merged cluster from the initial clusters according to the second target similarity data.

[0152] Step S1230: merge the updated edge cells into the merged area cluster.

[0153] It should be noted that at this time, the edge cell only contains unit grid data that is more similar to the same adjacent cell, and the merged cluster is determined from the initial clusters according to the second target similarity data. Then, the current edge cell is directly merged into the determined merged cluster.

[0154] Step S1240: updating the merged cluster according to the result of cluster merging, and determining a candidate cluster according to the updated merged cluster.

[0155] It can be understood that, after all terminals in an edge cell are migrated or merged to other clusters, the edge cell is deleted from its corresponding cluster, and a candidate cluster is determined based on the updated merged cluster.

[0156] Step S930: determining the number of currently remaining initial clusters according to the candidate clusters.

[0157] It is understandable that when all the terminals in all cells in a cluster are migrated or merged to other clusters, it means that all the cells in the cluster are deleted, and the cluster is deleted. At this time, the number of initial clusters will change, and the number of current remaining initial clusters is determined according to the candidate clusters.

[0158] For example, Fig.13 The grid image corresponding to the cluster center of the initial cluster 1 is shown as follows: Fig.14 The figure shows the grid image corresponding to the cluster center of initial cluster 2. Initial cluster 3 is a cluster adjacent to initial cluster 1 and initial cluster 2, and the composition of the grid images corresponding to initial cluster 1, initial cluster 2 and initial cluster 3 is the same as the composition of the above-mentioned initial grid images, which will not be repeated here. Among them, U / D 1 represents the uplink and downlink subframe ratio corresponding to each grid in the cluster center of initial cluster 1; U / D 2 represents the uplink and downlink subframe ratio corresponding to each grid in the cluster center of initial cluster 2. After executing the uplink and downlink subframe ratio method of the embodiment of the present invention, as shown in FIG. Fig.15 The figure shows the cluster change image in the grid image corresponding to the cluster center of the initial cluster 3. The cell grid corresponding to the initial cluster 3 is partially assigned to the initial cluster 1 and partially assigned to the initial cluster 2. The terminals assigned to the initial cluster 1 are migrated to the cells of the initial cluster 1, and the remaining cells of the initial cluster 3 are assigned to the initial cluster 2.

[0159] It can be understood that the embodiment of the present invention effectively reduces the number of initial clusters by performing terminal migration and cluster changes between edge cells and adjacent cells adjacent to the edge cells, so that the number of remaining clusters meets the preset acceptable minimum number of clusters, that is, the second cluster number.

[0160] Step S530: determining a target cluster center image according to the raster image of the target cluster, and determining target service data corresponding to the target cluster according to the target cluster center image.

[0161] Specifically, after determining the second number of clustered target area clusters, the target cluster center image in the raster image contained in the current target area cluster is determined according to the clustering algorithm, and the method for obtaining the target cluster center image of the corresponding target cluster cell is the same as the method for obtaining the above-mentioned initial cluster cell, which will not be repeated here.

[0162] Step S230: determine target subframe ratio data of the target cluster according to the target service data, and perform uplink and downlink subframe ratio on the corresponding cells in the target cluster according to the target subframe ratio data.

[0163] Specifically, after determining the target cluster center image and target service data of each of the P target clusters, the optimal uplink and downlink subframe ratio of the corresponding target cluster, i.e., the target subframe ratio data, is determined by using the target cluster center image. Afterwards, all cells in the target cluster, i.e., the terminals included in the target cells, use the corresponding target subframe ratio data to synchronize and take effect the optimal uplink and downlink subframe ratio, i.e., send the target subframe ratio data to each terminal under the target cell to perform uplink and downlink subframe ratio.

[0164] The embodiment of the present invention can be continuously and repeatedly used to continuously monitor the uplink and downlink service changes of each cell in a contiguous area, so as to realize continuous periodic dynamic adjustment of the uplink and downlink subframe ratio of the cell.

[0165] For example, Fig.16 The figure is a specific execution flow chart of the uplink and downlink subframe ratio method provided by the embodiment of the present invention. In practical applications, the uplink and downlink subframe ratio method provided by the embodiment of the present invention includes but is not limited to steps S1610 to S1686. Each step is introduced in turn below:

[0166] Step S1610, start execution;

[0167] Step S1620, determine the data collection type, when the data collection type is the time collection type, execute step S1631; when the data collection type is the prediction collection type, execute step S1632;

[0168] Step S1631, collecting the locations of all terminals in the initial cell within a certain period of time and uplink and downlink service indicator information, and executing step S1640;

[0169] Step S1632, generating the positions of all terminals in the initial cell and uplink and downlink service indicator information based on the data prediction model, and executing step S1640;

[0170] Step S1640, constructing an initial grid image of the initial cell according to the initial service data;

[0171] Step S1650, clustering the initial cells according to the initial grid image, clustering the initial cells with similar service characteristics to obtain initial cell clusters;

[0172] Step S1660, cells under the same cluster area cluster adjust the uplink and downlink service indicators in their initial grid images to obtain a suitable uplink and downlink subframe ratio;

[0173] Step S1670, determining whether the number of initial clusters remaining after the cluster update is greater than or equal to the second cluster number. When the number of initial clusters remaining after the cluster update is less than the second cluster number, that is, no, executing step S1681; when the number of initial clusters remaining after the cluster update is greater than or equal to the second cluster number, that is, yes, executing step S1684;

[0174] Step S1681, determining the cluster center of the target cluster;

[0175] Step S1682, determining the optimal uplink and downlink subframe ratio of each target cluster based on the cluster center;

[0176] Step S1683, the optimal uplink and downlink subframe ratio is effective for each cell in the target cluster, and step S1620 is executed again;

[0177] Step S1684, determining edge cells of different initial clusters, and determining the belonging cluster of each grid according to the features on the grid;

[0178] Step S1685, determining whether the belonging cell cluster belongs to the cell cluster to which the current cell belongs. If the belonging cell cluster is the cell cluster to which the current cell belongs, that is, yes, re-execute step S1684; if the belonging cell cluster is not the cell cluster to which the current cell belongs, that is, no, execute step S1686;

[0179] Step S1686: Perform terminal migration and cluster change for the terminal in the grid to the adjacent cell of the belonging cluster, and then re-execute step S1670.

[0180] The scheme of the embodiment of the present invention can uniformly consider the uplink and downlink service conditions of each cell in a contiguous area, and uniformly adjust the uplink and downlink subframe ratios of each cell by analyzing the uplink and downlink service conditions of the cells in a unified contiguous area, thereby improving the success rate of dynamic adjustment of the uplink and downlink subframe ratios and reducing the influence of cross-time slot interference between cells on the boundaries. The uplink and downlink subframe ratio method provided by the embodiment of the present invention constructs an uplink and downlink service grid image of each cell, clusters cells with high grid image similarity, and determines a unified uplink and downlink subframe ratio according to the uplink and downlink service conditions in the clusters. Then, a single grid uplink and downlink service in a cell of multiple adjacent clustering area clusters is clustered with adjacent clusters for analysis, and the terminal is migrated to an adjacent clustering area cluster that is similar to its uplink and downlink service, so that the retained terminal uplink and downlink service characteristics can be merged with another adjacent clustering area cluster, thereby reducing differentiated uplink and downlink subframe ratio types.

[0181] It should be noted that the uplink and downlink subframe matching method of the embodiment of the present invention can be deployed on the network element side or the network management side, or on other systems that can interact with the network element, or on any other system that can interact with the cell grid portrait construction results.

[0182] It should be noted that, although the operations are described in a specific order in the drawings in the embodiments of the present invention, it should not be understood as requiring the operations to be performed in the specific order or serial order shown, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0183] In addition, in the embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0184] The embodiment of the present invention also provides an uplink and downlink subframe ratio device, such as Fig.17 As shown, the uplink and downlink subframe matching device 1700 includes but is not limited to:

[0185] Processor 1710 and memory 1720;

[0186] The memory 1720 stores program instructions, and when the program instructions are executed by the processor 1710, the processor 1710 executes the uplink and downlink subframe matching method described in any of the above embodiments.

[0187] The processor 1710 and the memory 1720 may be connected via a bus or other means.

[0188] It should be understood that the processor 1710 may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. Alternatively, the processor 1710 may be one or more integrated circuits for executing related programs to implement the technical solutions provided in the embodiments of the present invention.

[0189] The memory 1720 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs and non-transitory computer executable programs, such as the uplink and downlink subframe ratio method described in any embodiment of the present invention. The processor 1710 implements the above-mentioned uplink and downlink subframe ratio method by running the non-transitory software program and instructions stored in the memory 1720.

[0190] The memory 1720 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store and execute the above-mentioned uplink and downlink subframe matching method. In addition, the memory 1720 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 1720 may optionally include a memory remotely disposed relative to the processor 1710, and these remote memories may be connected to the processor 1710 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0191] The non-transient software program and instructions required to implement the above-mentioned uplink and downlink subframe ratio method are stored in the memory 1720. When executed by one or more processors 1710, the uplink and downlink subframe ratio method provided by any embodiment of the present invention is executed.

[0192] An embodiment of the present invention further provides a computer-readable storage medium, which stores program instructions. When the program instructions are executed by a computer, the uplink and downlink subframe ratio method described in any of the above embodiments is implemented.

[0193] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0194] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0195] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0196] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0197] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above implementation. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A method for allocating uplink and downlink subframes, the method comprising: Obtaining initial service data of the initial cell; Clustering the initial cell according to the initial service data to obtain a target cluster and target service data corresponding to the target cluster; The target subframe ratio data of the target cluster is determined according to the target service data, and the uplink and downlink subframe ratios are performed on the corresponding cells in the target cluster according to the target subframe ratio data.

2. The method according to claim 1, characterized in that The initial cell includes a target terminal, and the acquiring initial service data of the initial cell includes: Determine a data collection type, wherein the data collection type includes a time collection type; When the data collection type is the time collection type, data is collected from the target terminal in the initial cell according to a preset sampling interval to obtain first feature data; The first characteristic data is combined to obtain the initial service data corresponding to the initial cell.

3. The method according to claim 2, characterized in that The data collection type further includes a prediction collection type. After the data collection type is determined, the obtaining of initial service data of the initial cell further includes: When the data collection type is the prediction collection type, obtaining a pre-trained data prediction model and historical feature data of the target terminal in the initial cell; Inputting the historical feature data into the data prediction model to perform data prediction to obtain second feature data; The second characteristic data is combined to obtain the initial service data corresponding to the initial cell.

4. The method according to claim 2, characterized in that: The clustering the initial cell according to the initial service data to obtain a target cluster and target service data corresponding to the target cluster includes: Performing grid construction according to the initial business data to obtain an initial grid image; Performing clustering processing on the initial cells according to the initial grid image to obtain the target area cluster; A target cluster center image is determined according to the raster image of the target cluster, and the target service data corresponding to the target cluster is determined according to the target cluster center image.

5. The method according to claim 4, characterized in that The initial service data includes a terminal location element and a terminal service element, and the grid construction is performed according to the initial service data to obtain an initial grid image, including: Performing position selection on the initial service data according to the terminal position element to obtain a terminal grid position; Determine a target service element according to the terminal grid position and the terminal service element; A grid is constructed according to the terminal grid position and the target service element to obtain the initial grid image.

6. The method according to claim 4, characterized in that The clustering process of the initial cells according to the initial grid image to obtain the target area cluster includes: Selecting a first number of initial clustering cells from the initial cells; Filtering a first cell from the initial cells according to the initial cluster cells, where the first cell is different from the initial cluster cells, and the number of cells of the first cell is the difference between the number of cells of the initial cell and the number of cells of the first cluster; Performing cluster division according to the initial cluster cells and the first cells to obtain the first number of initial cluster cells, and using the cells divided into the initial clusters as second cells; When the first cluster number is greater than the preset second cluster number, the target terminal corresponding to the initial raster image in the initial cluster is clustered until the number of the remaining initial clusters after the cluster update is the second cluster number, and the remaining initial clusters are used as the target clusters.

7. The method according to claim 6, characterized in that The updating of the cluster of the target terminal corresponding to the initial grid image in the initial cluster includes: Determine an edge cell and a first adjacent cell and a second adjacent cell adjacent to the edge cell from the initial cluster, wherein the edge cell, the first adjacent cell and the second adjacent cell belong to different initial clusters respectively, and use the initial raster image of the edge cell as a first raster image, the initial raster image of the first adjacent cell as a second raster image, and the initial raster image of the second adjacent cell as a third raster image; Performing a cluster change on the target terminal corresponding to the first raster image according to the second raster image and the third raster image, and updating the initial cluster according to the result of the cluster change to obtain a candidate cluster; The number of the initial clusters currently remaining is determined according to the candidate clusters.

8. The method according to claim 7, characterized in that The step of changing the cluster of the target terminal corresponding to the first raster image according to the second raster image and the third raster image, and updating the initial cluster according to the result of the cluster change to obtain a candidate cluster includes: Performing raster data selection on the first raster image to obtain first unit raster data and second unit raster data; selecting third unit raster data from the second raster image, and selecting fourth unit raster data from the third raster image; Performing similarity calculation on the first unit grid data and the third unit grid data to obtain first similarity data; Performing similarity calculation on the first unit grid data and the fourth unit grid data to obtain second similarity data; Performing similarity calculation on the second unit grid data and the third unit grid data to obtain third similarity data; Performing similarity calculation on the second unit grid data and the fourth unit grid data to obtain fourth similarity data; Perform terminal migration on the target terminal corresponding to the first unit grid data according to a first preset grid similarity threshold, the first similarity data and the second similarity data, and update the target terminal included in the edge cell according to the result of the terminal migration; The updated edge cells are clustered according to the second preset grid similarity threshold, the third similarity data and the fourth similarity data, and the initial cluster is updated according to the result of the cluster change to obtain the candidate cluster.

9. The method according to claim 8, characterized in that The performing terminal migration on the target terminal corresponding to the first unit grid data according to the first preset grid similarity threshold, the first similarity data and the second similarity data, and updating the target terminal included in the edge cell according to the result of the terminal migration, comprises: When the first similarity data is greater than or equal to the first preset grid similarity threshold and the second similarity data is greater than or equal to the first preset grid similarity threshold, first target similarity data is determined according to the first similarity data and the second similarity data, and a migration cell is determined according to the unit grid data corresponding to the first target similarity data; the target terminal corresponding to the first unit grid data is migrated to the migration cell, and the second grid image or the third grid image is updated according to the result of the terminal migration; or, When the first similarity data is less than the first preset grid similarity threshold and the second similarity data is greater than or equal to the first preset grid similarity threshold, the target terminal corresponding to the first unit grid data is migrated to the second adjacent cell, and the target terminal included in the edge cell is updated according to the result of the terminal migration; or, When the first similarity data is greater than or equal to the first preset grid similarity threshold and the second similarity data is less than the first preset grid similarity threshold, the target terminal corresponding to the first unit grid data is migrated to the first adjacent cell, and the target terminal included in the edge cell is updated according to the result of terminal migration.

10. The method according to claim 8, characterized in that The step of changing the cluster of the updated edge cells according to the second preset grid similarity threshold, the third similarity data, and the fourth similarity data, and updating the initial cluster according to the result of the cluster change to obtain the candidate cluster includes: When the third similarity data is greater than or equal to the second preset grid similarity threshold and the fourth similarity data is greater than or equal to the second preset grid similarity threshold, determining second target similarity data according to the third similarity data and the fourth similarity data; Determining a merged cluster from the initial clusters according to the second target similarity data; Merging the updated edge cells into the merged area cluster; The merged cluster is updated according to the result of cluster merging, and the candidate cluster is determined according to the updated merged cluster.

11. An uplink and downlink subframe matching device, comprising: Processor and memory; The memory stores program instructions, and when the program instructions are executed by the processor, the processor executes the uplink and downlink subframe matching method according to any one of claims 1-10.

12. A computer-readable storage medium storing program instructions, wherein when the program instructions are executed by a computer, the uplink and downlink subframe matching method according to any one of claims 1 to 10 is implemented.

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