WO2024066801A1 - 通信网络负荷调整方法、电子设备和存储介质 - Google Patents
通信网络负荷调整方法、电子设备和存储介质 Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
- H04W16/10—Dynamic resource partitioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
- H04W72/044—Wireless resource allocation based on the type of the allocated resource
- H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/12—Wireless traffic scheduling
- H04W72/1263—Mapping of traffic onto schedule, e.g. scheduled allocation or multiplexing of flows
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Definitions
- the present application relates to but is not limited to the field of communication technology, and in particular to a communication network load adjustment method, electronic device and storage medium.
- Embodiments of the present application provide a communication network load adjustment method, an electronic device, and a storage medium.
- an embodiment of the present application provides a communication network load adjustment method, comprising: obtaining neighboring cell relationships and cell resource information of multiple communication cells, and determining the cell centroid of each of the communication cells, wherein the cell resource information is determined by a terminal located in the communication cell; dividing each of the communication cells into regions according to the neighboring cell relationships and the cell resource information, and determining a hotspot balancing region, wherein the hotspot balancing region includes multiple target communication cells; obtaining distance information of the terminal located in each of the target communication cells, wherein the distance information is used to characterize the distance between the terminal and the centroid of each of the cells; determining edge adjustment information of each of the target communication cells based on a preset machine learning algorithm according to the distance information, the neighboring cell relationships and the cell resource information, so as to adjust the coverage range of the target communication cells.
- the present application further provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor runs the computer program, the communication network load adjustment method as described in the first aspect above is executed.
- the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer-executable program, and the computer-executable program is used to enable a computer to execute the communication network load adjustment method as described in the first aspect above.
- FIG1 is a flow chart of a communication network load adjustment method provided by an embodiment of the present application.
- FIG2 is a flow chart of a method for determining a hotspot balancing area provided by another embodiment of the present application.
- FIG3 is a flow chart of a method for determining a core cell provided by another embodiment of the present application.
- FIG4 is a flow chart of a method for determining a load sharing cell provided in another embodiment of the present application.
- FIG5 is a flow chart of a method for determining edge adjustment information provided by another embodiment of the present application.
- FIG6 is a flow chart of another method for determining edge adjustment information provided by another embodiment of the present application.
- FIG. 7 is a flowchart of a specific method for determining edge adjustment information provided by another embodiment of the present application.
- FIG8 is a flowchart of a method for determining neighbor relationship and distance information provided by another embodiment of the present application.
- FIG9 is a flow chart of a method for determining capacity proportion and capacity gap provided by another embodiment of the present application.
- FIG10 is a schematic diagram of a hot spot balancing area provided by an embodiment of the present application.
- FIG11 is a schematic diagram of a communication cell coverage area provided by an embodiment of the present application.
- FIG. 12 is a structural diagram of an electronic device provided in another embodiment of the present application.
- the present application provides a communication network load adjustment method, electronic device and storage medium
- the communication network load adjustment method includes: obtaining neighboring cell relations and cell resource information of multiple communication cells, and determining the cell centroid of each communication cell, wherein the cell resource information is determined by a terminal located in the communication cell; dividing each communication cell into regions according to the neighboring cell relations and cell resource information, and determining a hotspot balancing region, wherein the hotspot balancing region includes multiple target communication cells; obtaining distance information of terminals located in each target communication cell, wherein the distance information is used to characterize the distance between the terminal and the centroid of each cell; determining each target communication cell according to the distance information, neighboring cell relations and cell resource information based on a preset machine learning algorithm.
- the edge adjustment information is used to adjust the coverage of the target communication cell.
- multiple target communication cells are divided into hot spot balancing areas according to the neighboring cell relationships and cell resource information of the communication cells.
- the hot spot balancing area refers to the area where load adjustment is required, and then through a machine learning algorithm, the distance between the terminal and the centroid of each cell, as well as the neighboring cell relationship and cell resource information of the target communication cell are used to determine the edge adjustment information of each target communication cell in the hot spot balancing area, and then adjust the coverage of the target communication cell, thereby realizing dynamic adjustment of the edge of the target communication cell and load adjustment of adjacent target communication cells, effectively improving the load adjustment effect of the communication cell.
- the load of each target communication cell in the hot spot balancing area can be dynamically balanced, and the entire hot spot balancing area can be used as a load adjustment unit, which makes it easier to achieve global optimality and improve the overall load adjustment effect of the region, thereby improving user experience.
- a communication network load adjustment method provided in an embodiment of the present application can be applied in a terminal or a server, and can also be software running in a terminal or a server.
- Figure 1 is a flow chart of a communication network load adjustment method provided by an embodiment of the present application.
- the communication network load adjustment method includes but is not limited to the following steps:
- Step S110 obtaining neighboring cell relations and cell resource information of multiple communication cells, and determining the cell centroid of each communication cell, wherein the cell resource information is determined by a terminal located in the communication cell;
- Step S120 dividing each communication cell into regions according to the neighboring cell relationship and the cell resource information, and determining a hot spot balancing region, wherein the hot spot balancing region includes a plurality of target communication cells;
- Step S130 obtaining distance information of the terminal located in each target communication cell, wherein the distance information is used to represent the distance between the terminal and the centroid of each cell;
- Step S140 according to the distance information, neighboring cell relationship and cell resource information, based on a preset machine learning algorithm, edge adjustment information of each target communication cell is determined to adjust the coverage of the target communication cell.
- a wireless communication subnet may include multiple communication cells, each of which may be connected to a number of terminals.
- a terminal accessing a communication cell is equivalent to a terminal being located in the communication cell.
- the cell resource information of the communication cell is associated with the terminal located in the communication cell.
- the cell resource information may refer to the capacity share and the capacity gap.
- neighboring cell relations are used to determine the neighboring cells of a communication cell. For example, if communication cell A is a neighboring cell of communication cell B, the neighboring cell relationship between communication cell A and communication cell B is adjacent. If communication cell A is not a neighboring cell of communication cell B, the neighboring cell relationship between communication cell A and communication cell B is non-adjacent. Using neighboring cell relations and cell resource information, a hotspot balancing area is divided, and the hotspot balancing area includes target communication cells with higher loads and lower loads.
- the communication cell can be set as the cell centroid, and the distance between the terminal and the centroid of each cell can be obtained; then, through the machine learning algorithm, the edge adjustment information of each target communication cell can be determined through the distance between the terminal and the centroid of each cell, as well as the cell resource information of each target communication cell, and then the coverage of the target communication cell can be adjusted according to the edge adjustment information, and the edge of the target communication cell with a higher load can be shrunk, and correspondingly, the edge of the target communication cell with a lower load can be expanded.
- the terminal located at the edge of the target communication cell with a higher load will switch to the target communication cell with a lower load, the number of terminals located in the target communication cell with a higher load will decrease, and the number of terminals located in the target communication cell with a lower load will increase, thus achieving load balancing of each target communication cell in the hotspot balancing area, without increasing redundant design capacity, and reducing operator costs; based on this, through the area Domain division, according to the neighboring cell relationship and cell resource information of the communication cell, multiple target communication cells are divided into hot spot balancing areas.
- the hot spot balancing area refers to the area where load adjustment is required.
- the distance between the terminal and the centroid of each cell, as well as the neighboring cell relationship and cell resource information of the target communication cell are used to determine the edge adjustment information of each target communication cell in the hot spot balancing area, and then adjust the coverage range of the target communication cell, so as to realize dynamic adjustment of the edge of the target communication cell and load adjustment of the adjacent target communication cells, effectively improving the load adjustment effect of the communication cell.
- it can dynamically balance the load of each target communication cell in the hot spot balancing area, and use the entire hot spot balancing area as the load adjustment unit, which makes it easier to achieve global optimization and improve the overall load adjustment effect of the region, thereby improving user experience.
- the edge adjustment information refers to the edge change of the communication cell.
- the edge change is 10db or -10db; if the edge change is a positive value, it means that the edge of the communication cell needs to be expanded. If the edge change is a negative value, it means that the edge of the communication cell needs to be shrunk.
- the coverage of the communication cell is adjusted through the cell edge management module.
- the cell edge management module adjusts the coverage of the corresponding target communication cell.
- the adjustment methods of the target communication cell by the cell edge management module include but are not limited to: adjusting the switching threshold, adjusting the antenna direction angle, adjusting the line power, adjusting the PRACH detection threshold, adjusting the access level threshold, adjusting the uplink maximum transmission power, and adjusting the reselection parameters; in addition, based on expert experience, it is possible to judge whether the current coverage is reasonable cell by cell, and manually adjust the coverage of the target communication cell through the cell edge management module.
- the first adjustment method is to modify the switching parameters or other parameters so that the terminals accessing other communication cells switch to this cell in advance or delay, thereby indirectly achieving the result of changing the coverage of the communication cell, but the actual coverage of the communication cell remains unchanged;
- the second adjustment method is to adjust the communication cell coverage parameters to change the actual coverage of the communication cell.
- the capacity share and capacity gap can be determined by the number of RRC connected users; the distance between the terminal and the centroid of each cell can be determined by data such as path loss distribution and terminal positioning data; and the time delay between the terminal and the communication cell can be used to replace the distance between the terminal and the cell centroid.
- the cell resource information includes capacity proportion;
- step S120 in the embodiment shown in FIG. 1 includes but is not limited to the following steps:
- Step S210 determining the load attribute of the communication cell according to the capacity proportion
- Step S220 dividing each communication cell into regions according to the neighboring cell relationship and load attributes, and determining the hot spot balancing region.
- the capacity share of a communication cell is determined by the number of terminals located in the communication cell.
- the capacity share refers to the utilization rate of the resource capacity of the communication cell. The larger the capacity share, the higher the load of the communication cell. Conversely, the smaller the capacity share, the lower the load of the communication cell. Therefore, the load attributes of the communication cell can be determined by the capacity share, and then the hot spot balancing area can be divided in each communication cell in combination with the neighboring cell relationship and load attributes.
- the hotspot balancing area in step S220 in the embodiment shown in FIG. 2 includes a core cell; the method for determining the core cell includes but is not limited to the following steps:
- Step S310 when the capacity ratio is greater than a preset first threshold, determining that the load attribute of the communication cell is a high-load cell;
- Step S320 Based on the neighboring cell relationship, any high-load cell is used as a core cell, and all high-load cells adjacent to the core cell are used as core cells.
- the capacity share of the communication cell is judged, and then the high-load cell is distinguished.
- the high-load cell is taken as the core cell, and combined with the neighboring cell relationship, all high-load cells that have a neighboring cell relationship with the core cell are taken as core cells.
- the hotspot balancing area in step S220 in the embodiment shown in FIG. 2 also includes a load sharing cell; the method for determining the load sharing cell includes but is not limited to the following steps:
- Step S410 when the capacity proportion is less than or equal to a preset second threshold, determining that the load attribute of the communication cell is a medium-low load cell, wherein the second threshold is less than or equal to the first threshold;
- Step S420 Based on the neighboring cell relationship, traverse each medium and low load cell, and use all medium and low load cells adjacent to the core cell as load sharing cells.
- the capacity share of the communication cell is judged, and then the medium and low load cells are distinguished.
- a hot spot balancing area needs to be determined, after the core cell is determined, all the medium and low load cells adjacent to each core cell are used as load sharing cells in combination with the neighboring cell relationship. Finally, all the core cells and load sharing cells are regarded as a whole area, namely, the hot spot balancing area.
- the hot spot balancing area since the load of the core cell is too high, it will affect the user experience. It is necessary to adjust the load of the core cell, and connect some terminals located in the core cell to the adjacent load sharing cell to reduce the load of the core cell, thereby ensuring the user experience.
- the second threshold value can be set manually or obtained through repeated experiments and tuning; the first threshold value and the second threshold value can be the same or different.
- the hotspot balancing area includes a core cell and a load sharing cell, and the cell resource information includes a capacity ratio and a capacity gap;
- step S140 in the embodiment shown in FIG1 includes but is not limited to the following steps:
- Step S510 traversing the core cells based on the sorting information of capacity proportion and capacity gap
- Step S520 for any core cell, a terminal located in the core cell is taken as a terminal to be processed, and based on a neighboring cell relationship, a load sharing cell adjacent to the core cell is taken as a cell to be processed;
- Step S530 input the distance information of the terminal to be processed, the neighboring cell relationship, the capacity proportion of the core cell, the capacity proportion of the cell to be processed and the capacity gap of the core cell into the machine learning algorithm to determine the edge adjustment information of each target communication cell.
- the core cells are traversed according to the capacity proportion and the size of the capacity gap, each core cell is processed in turn, and the capacity gap of each core cell is judged. If there are core cells with capacity gaps among the core cells to be processed, the core cells with larger capacity gaps are given priority. If the capacity gaps in the core cells to be processed are all zero, the core cells with larger capacity proportions are given priority. This can dynamically balance the load of each target communication cell in the hotspot balancing area to achieve global optimization, thereby improving user experience.
- the ranking information based on capacity share and capacity gap refers to the ranking information based on capacity share and capacity gap from high to low.
- the cell resource information includes capacity proportion and capacity gap
- the machine learning algorithm includes a classification model or a clustering model
- step S140 in the embodiment shown in FIG. 1 includes but is not limited to the following steps:
- Step S610 obtaining an initial belonging tag of each terminal, wherein the initial belonging tag is used to represent a target communication cell corresponding to the terminal;
- Step S620 inputting the distance information, neighboring cell relationship, capacity proportion and capacity gap into a classification model or a clustering model to determine a target attribution label of each terminal, wherein the target attribution label is used to characterize a target communication cell corresponding to the terminal;
- Step S630 determining edge adjustment information of each target communication cell according to the distance information, the initial belonging label, the target belonging label and the neighboring cell relationship.
- the initial attribution label of the terminal is first obtained, and the initial attribution label is used to characterize the target communication cell currently accessed by the terminal; then, based on the processing of the classification model or the clustering model, the target attribution label of each terminal is determined through the distance information, the neighboring area relationship, the capacity proportion of each communication cell and the capacity gap of each core cell, and the target attribution label is used to characterize the target communication cell that the terminal should access; through the initial attribution label and distance information of each terminal, as well as the neighboring area relationship of the target communication cell, the initial edge information of each target communication cell can be determined, and through the target attribution label and distance information of each terminal, as well as the neighboring area relationship of the target communication cell, the target edge information of each target communication cell can be determined, and the edge adjustment information of the target communication cell can be determined through the initial edge information and the target edge information, and then the edge adjustment information adjusts the coverage of each target communication cell, so that the terminal can access the target communication cell corresponding to the target attribution label.
- the target attribution label of each terminal can be determined through the classification model.
- the target attribution label of each terminal when classifying terminals located in any core cell, first determine that the maximum number of terminals that the core cell can accommodate is N, then pre-classify in combination with the distance information, and classify the N terminals closest to the cell centroid of the core cell into the core cell, and then classify the attribution of each terminal through the classification model, using the cell resource information of the core cell and its adjacent load sharing cells, determine the communication cell to which each terminal belongs, and classify several terminals that are far from the cell centroid of the core cell into the load sharing cell to which they belong, thereby determining the target attribution label of each terminal.
- the target attribution label of each terminal can also be determined through the clustering model.
- the terminals located in each communication cell are clustered according to the distance information of the terminal, and the terminals that are closer to the cell centroid of a certain communication cell are clustered into the same communication cell.
- the clustering results are adjusted in combination with the neighboring cell relationship, capacity share and capacity gap, and the target attribution label of each terminal is determined through the communication cell to which each terminal is targeted.
- step S630 in the embodiment shown in FIG. 6 includes but is not limited to the following steps:
- Step S710 for any terminal, when the target attribution tag is different from the initial attribution tag, determining a first target communication cell according to the initial attribution tag, and determining a second target communication cell according to the target attribution tag, wherein the first target communication cell is adjacent to the second target communication cell;
- Step S720 determine edge adjustment information based on the distance information, the first target communication cell, the second target communication cell and the neighboring cell relationship, wherein the edge adjustment information is used to adjust the coverage of the first target communication cell or the second target communication cell to minimize the difference in capacity share between the first target communication cell and the second target communication cell.
- the initial edge information of each target communication cell can be determined through the initial attribution label and distance information of each terminal, and the neighboring relationship of the target communication cell; the target edge information of each target communication cell can be determined through the target attribution label and distance information of each terminal, and the neighboring relationship of the target communication cell; when the target attribution label is different from the initial attribution label, it is equivalent to that the target edge information is different from the initial edge information, and the edge of the communication cell needs to be adjusted.
- the two target communication cells can be adjusted at the same time. For example, the first The coverage of the target communication cell expands and the coverage of the second target communication cell shrinks, or the coverage of the first target communication cell shrinks and the coverage of the second target communication cell expands.
- only one of the target communication cells can be adjusted to shrink or expand the coverage of the target communication cell, thereby achieving rapid switching of terminals that need to adjust the access cell to the new communication cell, thereby ensuring user experience.
- step S110 in the embodiment shown in FIG. 1 there are also but not limited to the following steps:
- Step S810 obtaining a measurement report of each communication cell, wherein the measurement report is generated by a terminal located in the communication cell;
- Step S820 Determine neighbor relationship and distance information according to the measurement report.
- the Measurement Report refers to the measurement information reported by the terminal in the cell overlapping area.
- the measurement report includes the identifier of the serving cell, the identifier of the neighboring cell detected by the terminal, the reference signal received power RSRP information of the distance from the terminal to the serving cell, and the RSRP information from the terminal to the neighboring cell. Therefore, by obtaining the measurement reports of each communication cell through the measurement report summary module, the neighboring cell relationship of each communication cell can be determined through the association relationship between the serving cell and the neighboring cell in the measurement report, and the distance information of the terminal can be determined through the RSRP information. Therefore, by analyzing the measurement report, it is possible to statically or dynamically adjust the coverage range of each communication cell, balance the load of each target communication cell, and improve the user experience.
- the cell resource information includes capacity proportion and capacity gap; before step S110 in the embodiment shown in FIG. 1 , the following steps are also included but not limited to:
- Step S910 obtaining resource utilization information, resource capacity information of the communication cell and the initial belonging tag of each terminal, wherein the initial belonging tag is used to characterize the target communication cell corresponding to the terminal;
- Step S920 determining the capacity ratio according to the resource utilization information
- Step S930 determining the capacity gap according to the resource capacity information and the initial attribution tag.
- the resource utilization information of the communication cell is used to characterize the resource utilization rate, and the resource capacity information of the communication cell is used to characterize the resource capacity.
- the resource capacity in the communication cell is fixed. Through the resource utilization rate, the capacity ratio can be determined.
- the capacity gap of the target communication cell since the upper limit of the capacity ratio is 100%, in order to accurately determine the load state of the communication cell, it is necessary to determine the capacity gap of the target communication cell.
- the capacity gap is used to characterize the value of the capacity exceeding the resource capacity.
- the capacity gap can be calculated through the initial attribution tag and the resource capacity information.
- each terminal is regarded as having the same resource occupancy, and the resource capacity of each target communication cell is fixed.
- the number of terminals corresponding to each target communication cell is determined by the initial attribution tag, and then the resource excess of each target terminal is calculated.
- the resource excess is the difference between the sum of the resource occupancy of all terminals in the target communication cell and the resource capacity of the target communication cell. If the resource excess is zero, the capacity gap is zero. If the resource excess is greater than zero, the capacity gap is the ratio of the resource excess to the resource capacity.
- the resource utilization information includes business resource utilization information and hardware resource utilization information; the business resource utilization information includes at least one of the following: frequency domain utilization, downlink power utilization; the hardware resource utilization information includes at least one of the following: the ratio of the number of connected users to the maximum number of supported users, CPU utilization.
- the load attributes of the communication cell can be determined through the business resource utilization information and the hardware resource utilization information.
- a high-load cell can be a high load on business resources or a high load on hardware resources. Hardware resources are used to characterize the performance of the communication cell. If business resources such as frequency domain resources are about to be exhausted or reach the upper limit, the business needs of the terminal will be restricted, affecting the user experience. Therefore, alleviating the high load on business resources can help increase the communication efficiency of the wireless communication subnet.
- the traffic of the communication cell can ensure the user experience; if the hardware resources such as CPU or memory are about to reach the upper limit or have reached the upper limit, the system will be unstable. Therefore, alleviating the high load on hardware resources can prevent the communication cell from entering an abnormal state.
- FIG. 10 is a schematic diagram of a hotspot balancing area provided by an embodiment of the present application.
- each communication cell is set as the cell centroid. If any two communication cells are adjacent, the cell centroids corresponding to the two communication cells are connected by a dotted line.
- all high-load cells of the wireless communication subnet are identified. For example, the cell centroids corresponding to the high-load cells are marked as H1, H2, H3, and H4 in turn.
- the high-load cell is taken as the core cell. For example, starting from H1, the high-load cell corresponding to H1 is taken as the core cell.
- the neighboring cell relationship since H2 is adjacent to H1, H3 and H4 are adjacent to each other.
- the high-load cells corresponding to H2, H3 and H4 are all taken as core cells; then, according to the neighboring cell relationship, all the medium and low-load cells adjacent to each core cell are determined, and the medium and low-load cells are taken as load-sharing cells, and the centroids corresponding to each load-sharing cell are marked L1, L2, L3, L4 and L5 in sequence; finally, the communication cells corresponding to H1, H2, H3, H4, L1, L2, L3, L4 and L5 are taken as a whole area, namely, the hotspot balancing area; the cell centroids outside the hotspot balancing area are marked O1, O2, O3 and O4 in sequence.
- the dotted rectangular box corresponding to the hotspot balancing area is for illustration only and does not represent the coverage range corresponding to the hotspot balancing area. Since the coverage range of each communication cell is usually a sector-shaped area, the coverage range of the hotspot balancing area can be formed by superimposing multiple sector-shaped areas.
- Figure 11 is a schematic diagram of the communication cell coverage provided by an embodiment of the present application.
- each communication cell is set as the cell centroid. If there is a dotted line connection between the terminal and the cell centroid, it means that the terminal can report a measurement report to the communication cell; for any cell centroid, there is a sector area formed by dotted lines, and the sector area is the coverage range of the communication cell; adjusting the coverage range of the communication cell is to adjust the direction or size of the sector area; through regional division, according to the neighboring relationship and cell resource information of the communication cell, multiple target communication cells are divided into hot spot balancing areas, and the hot spot balancing area refers to the area where load adjustment is required, and then through the machine learning algorithm, the distance between the terminal and the centroid of each cell, as well as the neighboring relationship and cell resource information of the target communication cell, the edge adjustment information of each target communication cell in the hot spot balancing area is determined, and then the coverage range of the target communication cell is adjusted, so as to realize dynamic adjustment of the edge of the target communication cell, load adjustment of the adjacent target communication cell, and
- the load of each target communication cell in the hot spot balancing area can be dynamically balanced, and the entire hot spot balancing area is used as the load adjustment unit, which is easier to achieve the global optimum, improve the overall load adjustment effect of the region, and thus improve the user experience.
- an embodiment of the present application further provides an electronic device.
- the electronic device includes: one or more processors and memory, and one processor and memory are taken as an example in Fig. 12.
- the processor and memory may be connected via a bus or other methods, and the connection via a bus is taken as an example in Fig. 12.
- the memory as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs, such as the communication network load adjustment method in the above-mentioned embodiment of the present application.
- the processor implements the communication network load adjustment method in the above-mentioned embodiment of the present application by running the non-transitory software programs and programs stored in the memory.
- the memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data required to execute the communication network load adjustment method in the above-mentioned embodiment of the present application, etc.
- the memory 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.
- the memory may include a memory remotely arranged relative to the processor, and these remote memories may be connected to the electronic device via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
- the non-transient software program and program required to implement the communication network load adjustment method in the above-mentioned embodiment of the present application are stored in the memory.
- the communication network load adjustment method in the above-mentioned embodiment of the present application is executed, for example, the method steps S110 to S140 in Figure 1, the method steps S210 to S220 in Figure 2, the method steps S310 to S320 in Figure 3, the method steps S410 to S420 in Figure 4, the method steps S510 to S530 in Figure 5, the method steps S610 to S630 in Figure 6, the method steps S710 to S720 in Figure 7, and the method steps S810 to S820 in Figure 8 are executed. 0.
- steps S910 to S930 of the method in FIG9 neighboring cell relations and cell resource information of multiple communication cells are obtained, and the cell centroid of each communication cell is determined, wherein the cell resource information is determined by a terminal located in the communication cell; each communication cell is divided into regions according to the neighboring cell relations and cell resource information, and a hotspot balancing region is determined, wherein the hotspot balancing region includes multiple target communication cells; distance information of the terminal located in each target communication cell is obtained, wherein the distance information is used to characterize the distance between the terminal and the centroid of each cell; according to the distance information, neighboring cell relations and cell resource information, based on a preset machine learning algorithm, edge adjustment information of each target communication cell is determined to adjust the coverage of the target communication cell.
- multiple target communication cells are divided into hot spot balancing areas according to the neighboring cell relationships and cell resource information of the communication cells.
- the hot spot balancing area refers to the area where load adjustment is required. Then, through the machine learning algorithm, the distance between the terminal and the centroid of each cell, as well as the neighboring cell relationship and cell resource information of the target communication cell are used to determine the edge adjustment information of each target communication cell in the hot spot balancing area, and then adjust the coverage range of the target communication cell, thereby realizing dynamic adjustment of the edge of the target communication cell and load adjustment of adjacent target communication cells, effectively improving the load adjustment effect of the communication cell.
- the load of each target communication cell in the hot spot balancing area can be dynamically balanced, and the entire hot spot balancing area can be used as the load adjustment unit, which makes it easier to achieve global optimality and improve the overall load adjustment effect of the region, thereby improving user experience.
- an embodiment of the present application further provides a computer-readable storage medium, which stores computer-executable instructions.
- the computer-executable instructions are executed by a processor or a controller, for example, by a processor in the above-mentioned electronic device embodiment, so that the above-mentioned processor can execute the communication network load adjustment method in the above-mentioned embodiment, for example, execute the method steps S110 to S140 in Figure 1, the method steps S210 to S220 in Figure 2, the method steps S310 to S320 in Figure 3, the method steps S410 to S420 in Figure 4, the method steps S510 to S530 in Figure 5, the method steps S610 to S630 in Figure 6, and the method steps S710 to S72 in Figure 7. 0.
- Steps S810 to S820 of the method in FIG8 and steps S910 to S930 of the method in FIG9 are performed by obtaining neighboring cell relations and cell resource information of multiple communication cells, and determining the cell centroid of each communication cell, wherein the cell resource information is determined by a terminal located in the communication cell; dividing each communication cell into regions according to the neighboring cell relations and the cell resource information, and determining a hotspot balancing region, wherein the hotspot balancing region includes multiple target communication cells; obtaining distance information of the terminal located in each target communication cell, wherein the distance information is used to characterize the distance between the terminal and the centroid of each cell; determining edge adjustment information of each target communication cell based on the distance information, neighboring cell relations and cell resource information and a preset machine learning algorithm to adjust the coverage of the target communication cell.
- the hot spot balancing area refers to the area where load adjustment is required. Then, through the machine learning algorithm, the distance between the terminal and the centroid of each cell, as well as the neighboring cell relationship and cell resource information of the target communication cell are used to determine the edge adjustment information of each target communication cell in the hot spot balancing area, and then adjust the coverage range of the target communication cell, realize dynamic adjustment of the edge of the target communication cell, and adjust the load of the adjacent target communication cell, effectively improving the load adjustment effect of the communication cell.
- computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data).
- Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer.
- communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.
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Abstract
本申请提供了一种通信网络负荷调整方法、电子设备和存储介质,该方法包括:获取多个通信小区的邻区关系和小区资源信息,并确定各个通信小区的小区质心(S110);根据邻区关系和小区资源信息,对各个通信小区进行区域划分,确定热点均衡区域,其中,热点均衡区域包括多个目标通信小区(S120);获取位于各个目标通信小区内的终端的距离信息,其中,距离信息用于表征终端与各个小区质心的距离(S130);根据距离信息、邻区关系和小区资源信息,基于预设的机器学习算法,确定各个目标通信小区的边缘调整信息,以调整目标通信小区的覆盖范围(S140)。
Description
相关申请的交叉引用
本申请基于申请号为202211189531.0、申请日为2022年9月28日的中国专利申请提出,并要求该中国专利申请的优先权,该中国专利申请的全部内容在此引入本申请作为参考。
本申请涉及但不限于通信技术领域,尤其涉及一种通信网络负荷调整方法、电子设备和存储介质。
随着移动通信的发展,无线通信网络中部分站点设计容量与实际业务量有时会形成缺口,影响用户体验。如果增加冗余的设计容量又会带来运营商成本的提升,所以动态协调小区覆盖范围,能够节省成本和缓解突发的高业务量,提高用户体验。
目前,对于待协调负荷的通信小区,只选择与该通信小区最近的邻区进行负荷调整,忽略了与该通信小区用户交互较多的其他邻区,通信小区的负荷调整效果差,另外,对于多个通信小区形成的区域,只能逐个通信小区进行负荷调整,导致区域整体的负荷调整效果差,用户体验差。
发明内容
以下是对本文详细描述的主题的概述。本概述并非是为了限制权利要求的保护范围。
本申请实施例提供了一种通信网络负荷调整方法、电子设备和存储介质。
第一方面,本申请实施例提供了一种通信网络负荷调整方法,包括:获取多个通信小区的邻区关系和小区资源信息,并确定各个所述通信小区的小区质心,其中,所述小区资源信息由位于所述通信小区内的终端确定;根据所述邻区关系和所述小区资源信息,对各个所述通信小区进行区域划分,确定热点均衡区域,其中,所述热点均衡区域包括多个目标通信小区;获取位于各个所述目标通信小区内的所述终端的距离信息,其中,所述距离信息用于表征所述终端与各个所述小区质心的距离;根据所述距离信息、所述邻区关系和所述小区资源信息,基于预设的机器学习算法,确定各个所述目标通信小区的边缘调整信息,以调整所述目标通信小区的覆盖范围。
第二方面,本申请还提供了一种电子设备,包括:存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,所述处理器运行所述计算机程序时执行如上第一方面所述的通信网络负荷调整方法。
第三方面,本申请还提供了一种计算机可读存储介质,所述计算机可读存储介质存储有计算机可执行程序,所述计算机可执行程序用于使计算机执行如上第一方面所述的通信网络负荷调整方法。
本申请的其它特征和优点将在随后的说明书中阐述,并且,部分地从说明书中变得显而易见,或者通过实施本申请而了解。本申请的目的和其他优点可通过在说明书、权利要求书以及附图中所特别指出的结构来实现和获得。
附图用来提供对本申请技术方案的理解,并且构成说明书的一部分,与本申请的实施例一起用于解释本申请的技术方案,并不构成对本申请技术方案的限制。
图1是本申请一个实施例提供的通信网络负荷调整方法的流程图;
图2是本申请另一个实施例提供的确定热点均衡区域的方法的流程图;
图3是本申请另一个实施例提供的确定核心小区的方法的流程图;
图4是本申请另一个实施例提供的确定负荷分担小区的方法的流程图;
图5是本申请另一个实施例提供的一种确定边缘调整信息的方法的流程图;
图6是本申请另一个实施例提供的另一种确定边缘调整信息的方法的流程图;
图7是本申请另一个实施例提供的确定边缘调整信息的具体方法的流程图;
图8是本申请另一个实施例提供的确定邻区关系和距离信息的方法的流程图;
图9是本申请另一个实施例提供的确定容量占比和容量缺口的方法的流程图;
图10是本申请一个实施例提供的热点均衡区域的示意图;
图11是本申请一个实施例提供的通信小区覆盖范围的示意图;
图12是本申请另一个实施例提供的电子设备的结构图。
为了使本申请的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本申请进行详细说明。应当理解,此处所描述的具体实施例仅用以解释本申请,并不用于限定本申请。
需要说明的是,虽然在装置示意图中进行了功能模块划分,在流程图中示出了逻辑顺序,但是在某些情况下,可以以不同于装置中的模块划分,或流程图中的顺序执行所示出或描述的步骤。说明书、权利要求书或上述附图中的术语“第一”、“第二”等是用于区别类似的对象,而不必用于描述特定的顺序或先后次序。
目前,对于待协调负荷的通信小区,只选择与该通信小区最近的邻区进行负荷调整,忽略了与该通信小区用户交互较多的其他邻区,通信小区的负荷调整效果差,另外,对于多个通信小区形成的区域,只能逐个通信小区进行负荷调整,导致区域整体的负荷调整效果差,用户体验差。
针对通信小区的负荷调整效果差而且区域整体的负荷调整效果差的问题,本申请提供了一种通信网络负荷调整方法、电子设备和存储介质,该通信网络负荷调整方法包括:获取多个通信小区的邻区关系和小区资源信息,并确定各个通信小区的小区质心,其中,小区资源信息由位于通信小区内的终端确定;根据邻区关系和小区资源信息,对各个通信小区进行区域划分,确定热点均衡区域,其中,热点均衡区域包括多个目标通信小区;获取位于各个目标通信小区内的终端的距离信息,其中,距离信息用于表征终端与各个小区质心的距离;根据距离信息、邻区关系和小区资源信息,基于预设的机器学习算法,确定各个目标通信小区
的边缘调整信息,以调整目标通信小区的覆盖范围。根据本申请实施例提供的方案,通过区域划分,根据通信小区的邻区关系和小区资源信息,将多个目标通信小区划分至热点均衡区域,热点均衡区域是指需要进行负荷调整的区域,然后通过机器学***衡热点均衡区域内各个目标通信小区的负荷,以整个热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而改善用户体验。
下面结合附图,对本申请实施例作阐述。
本申请实施例提供的一种通信网络负荷调整方法,可应用于终端中,也可应用于服务器中,还可以是运行于终端或服务器中的软件。
如图1所示,图1是本申请一个实施例提供的一种通信网络负荷调整方法的流程图。该通信网络负荷调整方法包括但不限于如下步骤:
步骤S110,获取多个通信小区的邻区关系和小区资源信息,并确定各个通信小区的小区质心,其中,小区资源信息由位于通信小区内的终端确定;
步骤S120,根据邻区关系和小区资源信息,对各个通信小区进行区域划分,确定热点均衡区域,其中,热点均衡区域包括多个目标通信小区;
步骤S130,获取位于各个目标通信小区内的终端的距离信息,其中,距离信息用于表征终端与各个小区质心的距离;
步骤S140,根据距离信息、邻区关系和小区资源信息,基于预设的机器学习算法,确定各个目标通信小区的边缘调整信息,以调整目标通信小区的覆盖范围。
可以理解的是,无线通信子网可包括多个通信小区,各个通信小区可接入有若干个终端,终端接入通信小区相当于终端位于通信小区内,通信小区的小区资源信息与位于通信小区内的终端关联,小区资源信息可指容量占比和容量缺口。在一些实施例中,位于通信小区内的终端数量越多,通信小区的可利用资源越少,通信小区内的容量占比越高,通信小区的负荷越高,终端数量超过小区的终端容量时,还会出现容量缺口,相对的,位于通信小区内的终端数量越少,通信小区的可利用资源越多,通信小区内的容量占比越低,通信小区的负荷越低;邻区关系用于确定通信小区的相邻小区,例如,若通信小区A是通信小区B的相邻小区,则通信小区A和通信小区B的邻区关系为相邻,若通信小区A不是通信小区B的相邻小区,则通信小区A和通信小区B的邻区关系为不相邻;利用邻区关系和小区资源信息,划分出热点均衡区域,热点均衡区域包含负荷较高和负荷较低的目标通信小区;可将通信小区设置为小区质心,并获取终端与各个小区质心的距离;然后通过机器学习算法,通过终端与各个小区质心的距离,以及各个目标通信小区的小区资源信息,确定各个目标通信小区的边缘调整信息,进而通过边缘调整信息调整目标通信小区的覆盖范围,将负荷较高的目标通信小区的边缘收缩,相应的,将负荷较低的目标通信小区的边缘扩张,此时,位于负荷较高的目标通信小区的边缘的终端会切换至负荷较低的目标通信小区,位于负荷较高的目标通信小区的终端数量会减少,位于负荷较低的目标通信小区的终端数量会增加,实现了热点均衡区域内各个目标通信小区的负荷均衡,无需增加冗余的设计容量,降低运营商成本;基于此,通过区
域划分,根据通信小区的邻区关系和小区资源信息,将多个目标通信小区划分至热点均衡区域,热点均衡区域是指需要进行负荷调整的区域,然后通过机器学***衡热点均衡区域内各个目标通信小区的负荷,以整个热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而提高用户体验。
需要说明的是,无需确定通信小区的覆盖范围,只需通过机器学习算法,确定通信小区的边缘调整信息即可,数据处理量更少,能够提高调整效率,边缘调整信息是指通信小区的边缘变化量,例如,边缘变化量为10db或-10db;若边缘变化量为正值,代表需要扩张通信小区的边缘,若边缘变化量为负值,代表需要收缩通信小区的边缘。
需要说明的是,通过小区边缘管理模块来调整通信小区的覆盖范围,小区边缘管理模块接收到边缘调整信息后,调整对应的目标通信小区的覆盖范围,小区边缘管理模块对目标通信小区的调整方式包括但不限于:调整切换门限,调整天线方向角,调整行功率,调整PRACH检测门限,调整接入电平门限,调整上行最大发射功率,调整重选参数;另外,可以根据专家经验,逐个小区判断当前的覆盖是否合理,通过小区边缘管理模块手动调整目标通信小区的覆盖范围。
值得注意的是,调整目标通信小区的覆盖范围的方式至少包括以下两种方式,第一种调整方式为通过修改切换参数或其它参数,以使接入其它通信小区的终端提前或延迟切换到本小区,从而间接实现改变通信小区覆盖范围的结果,但是通信小区实际的覆盖范围不变;第二种调整方式为调整通信小区覆盖参数来改变通信小区实际的覆盖范围。
值得注意的是,可通过RRC连接用户数来确定容量占比和容量缺口;可通过路损分布、终端定位数据等数据来确定终端与各个小区质心的距离;可利用终端与通信小区的时延来替代终端与小区质心的距离。
值得注意的是,如果出现群体性的急救事件或消防事件,对于决策中心,消防车或急救车的调度处理也会面临容量和距离的问题,可采用本申请实施例提供的通信网络负荷调整方法中的机器学习算法来完成消防车或急救车的调度处理。
另外,参照图2,在一实施例中,小区资源信息包括容量占比;图1所示实施例中的步骤S120,包括但不限于有以下步骤:
步骤S210,根据容量占比确定通信小区的负荷属性;
步骤S220,根据邻区关系和负荷属性,对各个通信小区进行区域划分,确定热点均衡区域。
可以理解的是,通信小区的容量占比由位于通信小区内的终端数量而确定,容量占比是指通信小区的资源容量的利用率,容量占比越大,通信小区的负荷越高,相对的,容量占比越小,通信小区的负荷越低,因此,能够通过容量占比确定通信小区的负荷属性,然后结合邻区关系和负荷属性,在各个通信小区中划分出热点均衡区域。
另外,参照图3,在一实施例中,图2所示实施例中的步骤S220中的热点均衡区域包括核心小区;核心小区的确定方法,包括但不限于有以下步骤:
步骤S310,在容量占比大于预设的第一阈值的情况下,确定通信小区的负荷属性为高负荷小区;
步骤S320,基于邻区关系,将任一高负荷小区作为核心小区,并将与核心小区相邻的所有高负荷小区作为核心小区。
可以理解的是,通过设置第一阈值,对通信小区的容量占比进行判断,进而区分出高负荷小区,需要确定一个热点均衡区域时,从任一高负荷小区出发,将该高负荷小区作为核心小区,结合邻区关系,将所有与核心小区存在邻区关系的高负荷小区作为核心小区。
另外,参照图4,在一实施例中,图2所示实施例中的步骤S220中的热点均衡区域还包括负荷分担小区;负荷分担小区的确定方法,包括但不限于有以下步骤:
步骤S410,在容量占比小于等于预设的第二阈值的情况下,确定通信小区的负荷属性为中低负荷小区,其中,第二阈值小于等于第一阈值;
步骤S420,基于邻区关系,遍历各个中低负荷小区,将与核心小区相邻的所有中低负荷小区作为负荷分担小区。
可以理解的是,通过设置第二阈值,对通信小区的容量占比进行判断,进而区分出中低负荷小区,需要确定一个热点均衡区域时,在确定核心小区后,结合邻区关系,将各个核心小区相邻的所有中低负荷小区作为负荷分担小区,最后将所有的核心小区和负荷分担小区作为一个整体区域,即热点均衡区域;在热点均衡区域中,由于核心小区的负荷过高,会影响用户体验,需要对核心小区进行负荷调整,将位于该核心小区内的部分终端接入到相邻的负荷分担小区,降低核心小区的负荷,从而保证用户体验。
值得注意的是,将热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而提高用户体验。
需要说明的是,第二阈值可通过人为设定,或者反复实验调优得到;第一阈值和第二阈值可相同或存在差异。
另外,参照图5,在一实施例中,热点均衡区域包括核心小区和负荷分担小区,小区资源信息包括容量占比和容量缺口;图1所示实施例中的步骤S140,包括但不限于有以下步骤:
步骤S510,基于容量占比和容量缺口的排序信息,遍历核心小区;
步骤S520,对于任一核心小区,将位于核心小区内的终端作为待处理终端,并基于邻区关系,将与核心小区相邻的负荷分担小区作为待处理小区;
步骤S530,将待处理终端的距离信息、邻区关系、核心小区的容量占比、待处理小区的容量占比和核心小区的容量缺口输入机器学习算法,确定各个目标通信小区的边缘调整信息。
可以理解的是,在机器学***衡热点均衡区域内各个目标通信小区的负荷,达到全局最优,从而提高用户体验。
值得注意的是,基于容量占比和容量缺口的排序信息是指基于容量占比和容量缺口由高到低的排序信息。
另外,参照图6,在一实施例中,小区资源信息包括容量占比和容量缺口,机器学习算法包括分类模型或聚类模型;图1所示实施例中的步骤S140,包括但不限于有以下步骤:
步骤S610,获取各个终端的初始归属标签,其中,初始归属标签用于表征终端对应的目标通信小区;
步骤S620,将距离信息、邻区关系、容量占比和容量缺口输入分类模型或聚类模型,确定各个终端的目标归属标签,其中,目标归属标签用于表征终端对应的目标通信小区;
步骤S630,根据距离信息、初始归属标签、目标归属标签和邻区关系,确定各个目标通信小区的边缘调整信息。
可以理解的是,先获取终端的初始归属标签,初始归属标签用于表征终端当前接入的目标通信小区;然后基于分类模型或聚类模型的处理,通过距离信息、邻区关系、各个通信小区的容量占比和各个核心小区的容量缺口,确定各个终端的目标归属标签,目标归属标签用于表征终端应该接入的目标通信小区;通过各个终端的初始归属标签和距离信息,以及目标通信小区的邻区关系,能够确定各个目标通信小区的初始边缘信息,并通过各个终端的目标归属标签和距离信息,以及目标通信小区的邻区关系,能够确定各个目标通信小区的目标边缘信息,通过初始边缘信息和目标边缘信息能够确定目标通信小区的边缘调整信息,进而边缘调整信息调整各个目标通信小区的覆盖范围,以使终端都能接入目标归属标签对应的目标通信小区,当各个终端都接入目标归属标签对应的目标通信小区,则实现动态平衡热点均衡区域内各个目标通信小区的负荷,达到全局最优,从而提高用户体验。
需要说明的是,通过分类模型能够确定各个终端的目标归属标签。在一些实施例中,对位于任一核心小区内的终端进行分类时,先确定核心小区最大可容纳的终端数量为N个,然后结合距离信息进行预分类,将距离该核心小区的小区质心最近的N个终端分类到该核心小区,然后通过分类模型,利用该核心小区及其相邻的负荷分担小区的小区资源信息,对各个终端的归属进行分类,确定各个终端目标归属的通信小区,将距离该核心小区的小区质心较远的若干个终端划分至目标归属的负荷分担小区中,进而确定各个终端的目标归属标签。
需要说明的是,通过聚类模型也能确定各个终端的目标归属标签。在一些实施例中,根据终端的距离信息,对位于各个通信小区内的终端进行聚类,将距离某个通信小区的小区质心较近的终端聚类到同一个通信小区,结合邻区关系、容量占比和容量缺口,对聚类结果进行调整,通过各个终端目标归属的通信小区,进而确定各个终端的目标归属标签。
另外,参照图7,在一实施例中,图6所示实施例中的步骤S630,包括但不限于有以下步骤:
步骤S710,对于任一终端,当目标归属标签与初始归属标签不同,根据初始归属标签确定第一目标通信小区,并根据目标归属标签确定第二目标通信小区,其中,第一目标通信小区与第二目标通信小区相邻;
步骤S720,根据距离信息、第一目标通信小区、第二目标通信小区和邻区关系,确定边缘调整信息,其中,边缘调整信息用于调整第一目标通信小区或第二目标通信小区的覆盖范围,以使第一目标通信小区与第二目标通信小区的容量占比之差最小化。
可以理解的是,通过各个终端的初始归属标签和距离信息,以及目标通信小区的邻区关系,能够确定各个目标通信小区的初始边缘信息;通过各个终端的目标归属标签和距离信息,以及目标通信小区的邻区关系,能够确定各个目标通信小区的目标边缘信息;当目标归属标签与初始归属标签不同,相当于目标边缘信息与初始边缘信息不同,需要调整通信小区的边缘,在对两个相邻的目标通信小区进行调整时,可同时调整两个目标通信小区,例如,第一
目标通信小区的覆盖范围扩张且第二目标通信小区的覆盖范围收缩,或者第一目标通信小区的覆盖范围收缩且第二目标通信小区的覆盖范围扩张,也可只调整其中一个目标通信小区,以使目标通信小区的覆盖范围收缩或扩张,实现了将需要调整接入小区的终端快速切换至新的通信小区,从而保证用户体验。
另外,参照图8,在一实施例中,图1所示实施例中的步骤S110之前,还包括但不限于有以下步骤:
步骤S810,获取各个通信小区的测量报告,其中,测量报告由位于通信小区内的终端生成;
步骤S820,根据测量报告,确定邻区关系和距离信息。
可以理解的是,测量报告(Measurement Report,MR),是指终端在小区交叠区域上报的测量信息,测量报告包含所属服务小区的标识,终端检测到的邻小区标识,终端到服务小区距离的参考信号接收功率RSRP信息,以及终端到邻小区的RSRP信息;因此,通过测量报告汇总模块获取各个通信小区的测量报告,能够通过测量报告中服务小区与邻小区的关联关系,确定各个通信小区的邻区关系,并通过RSRP信息确定终端的距离信息;因此,通过对测量报告进行分析,能够实现对各个通信小区的覆盖范围进行静态或动态调整,平衡各个目标通信小区的负荷,从而提高用户体验。
另外,参照图9,在一实施例中,小区资源信息包括容量占比和容量缺口;图1所示实施例中的步骤S110之前,还包括但不限于有以下步骤:
步骤S910,获取通信小区的资源利用信息、资源容量信息和各个终端的初始归属标签,其中,初始归属标签用于表征终端对应的目标通信小区;
步骤S920,根据资源利用信息,确定容量占比;
步骤S930,根据资源容量信息和初始归属标签,确定容量缺口。
可以理解的是,通信小区的资源利用信息用于表征资源利用率,通信小区的资源容量信息用于表征资源容量,通信小区内资源容量是固定的,通过资源利用率,能够确定容量占比,另外,在热点均衡区域中,由于容量占比的上限是100%,为了准确确定通信小区的负荷状态,需要确定目标通信小区的容量缺口,容量缺口用于表征容量超出资源容量的数值,通过初始归属标签和资源容量信息,能够计算得到容量缺口。在一些实施例中,各个终端视为具有相同的资源占用量,每个目标通信小区的资源容量是固定的,通过初始归属标签确定各个目标通信小区对应的终端的数量,进而计算出各个目标终端的资源超出量,资源超出量为位于目标通信小区中所有终端的资源占用量总和与该目标通信小区的资源容量的差值,若资源超出量为零,则容量缺口为零,若资源超出量大于零,则容量缺口为资源超出量与资源容量之比。
另外,在一实施例中,资源利用信息包括业务资源利用信息和硬件资源利用信息;业务资源利用信息至少包括如下之一:频域利用率、下行功率利用率;硬件资源利用信息至少包括如下之一:连接用户数与最大支持用户数的占比率、CPU利用率。
可以理解的是,通过业务资源利用信息和硬件资源利用信息都能确定通信小区的负荷属性,高负荷小区可以是业务资源上的高负荷,也可以是硬件资源上的高负荷,硬件资源用于表征通信小区的性能;若频域资源等业务资源即将耗尽或者达到上限后,终端的业务需求受到限制,影响用户体验,因此缓解业务资源上的高负荷,能够有助于增加无线通信子网的通
信小区的流量,保证用户体验;若CPU或内存等硬件资源即将达到上限或达到上限后,***会不稳定,因此缓解硬件资源上的高负荷,能够避免通信小区进入异常状态。
另外,参照图10,图10是本申请一个实施例提供的热点均衡区域的示意图。
可以理解的是,进行区域划分时,将各个通信小区设置为小区质心,若任意两个通信小区之间相邻,则用虚线连接该两个通信小区对应的小区质心;首先识别出无线通信子网的所有高负荷小区,例如,依次将各个高负荷小区对应的小区质心依次标记为H1、H2、H3、H4,然后从任一高负荷小区出发,将该高负荷小区作为核心小区,例如,从H1出发,将H1对应的高负荷小区作为核心小区;然后根据邻区关系,由于H2与H1相邻,H3和H4分别与H2相邻,因此,将H2、H3和H4对应的高负荷小区均作为核心小区;然后根据邻区关系,确定各个核心小区相邻的所有中低负荷小区,并将该中低负荷小区作为负荷分担小区,各个负荷分担小区对应的质心依次标记L1、L2、L3、L4和L5;最后将H1、H2、H3、H4、L1、L2、L3、L4和L5对应的通信小区作为一个整体区域,即热点均衡区域;热点均衡区域之外的小区质心依次标记为O1、O2、O3和O4。
需要说明的是,热点均衡区域对应的虚线矩形框仅作为示意,并不代表热点均衡区域对应的覆盖范围,由于各个通信小区的覆盖范围通常为扇形区域,因此,热点均衡区域的覆盖范围可由多个扇形区域叠加而成。
另外,参照图11,图11是本申请一个实施例提供的通信小区覆盖范围的示意图。
可以理解的是,进行区域划分时,将各个通信小区设置为小区质心,若终端与小区质心之间存在虚线连接,说明该终端能够向该通信小区上报测量报告;对于任一小区质心,存在由点划线形成的扇形区域,该扇形区域为通信小区的覆盖范围;调整通信小区的覆盖范围就是调整扇形区域的朝向或大小;通过区域划分,根据通信小区的邻区关系和小区资源信息,将多个目标通信小区划分至热点均衡区域,热点均衡区域是指需要进行负荷调整的区域,然后通过机器学***衡热点均衡区域内各个目标通信小区的负荷,以整个热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而提高用户体验。
另外,参照图12,本申请的一个实施例还提供了一种电子设备。
该电子设备包括:一个或多个处理器和存储器,图12中以一个处理器及存储器为例。处理器和存储器可以通过总线或者其他方式连接,图12中以通过总线连接为例。
存储器作为一种非暂态计算机可读存储介质,可用于存储非暂态软件程序以及非暂态性计算机可执行程序,如上述本申请实施例中的通信网络负荷调整方法。处理器通过运行存储在存储器中的非暂态软件程序以及程序,从而实现上述本申请实施例中的通信网络负荷调整方法。
存储器可以包括存储程序区和存储数据区,其中,存储程序区可存储操作***、至少一个功能所需要的应用程序;存储数据区可存储执行上述本申请实施例中的通信网络负荷调整方法所需的数据等。此外,存储器可以包括高速随机存取存储器,还可以包括非暂态存储器,例如至少一个磁盘存储器件、闪存器件、或其他非暂态固态存储器件。在一些实施方式中,
存储器可包括相对于处理器远程设置的存储器,这些远程存储器可以通过网络连接至该电子设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
实现上述本申请实施例中的通信网络负荷调整方法所需的非暂态软件程序以及程序存储在存储器中,当被一个或者多个处理器执行时,执行上述本申请实施例中通信网络负荷调整方法,例如,执行以上描述的图1中的方法步骤S110至步骤S140、图2中的方法步骤S210至步骤S220、图3中的方法步骤S310至步骤S320、图4中的方法步骤S410至步骤S420、图5中的方法步骤S510至步骤S530、图6中的方法步骤S610至步骤S630、图7中的方法步骤S710至步骤S720、图8中的方法步骤S810至步骤S820、图9中的方法步骤S910至步骤S930,通过获取多个通信小区的邻区关系和小区资源信息,并确定各个通信小区的小区质心,其中,小区资源信息由位于通信小区内的终端确定;根据邻区关系和小区资源信息,对各个通信小区进行区域划分,确定热点均衡区域,其中,热点均衡区域包括多个目标通信小区;获取位于各个目标通信小区内的终端的距离信息,其中,距离信息用于表征终端与各个小区质心的距离;根据距离信息、邻区关系和小区资源信息,基于预设的机器学***衡热点均衡区域内各个目标通信小区的负荷,以整个热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而提高用户体验。
此外,本申请的一个实施例还提供了一种计算机可读存储介质,该计算机可读存储介质存储有计算机可执行指令,该计算机可执行指令被一个处理器或控制器执行,例如,被上述电子设备实施例中的一个处理器执行,可使得上述处理器执行上述实施例中通信网络负荷调整方法,例如,执行以上描述的图1中的方法步骤S110至步骤S140、图2中的方法步骤S210至步骤S220、图3中的方法步骤S310至步骤S320、图4中的方法步骤S410至步骤S420、图5中的方法步骤S510至步骤S530、图6中的方法步骤S610至步骤S630、图7中的方法步骤S710至步骤S720、图8中的方法步骤S810至步骤S820、图9中的方法步骤S910至步骤S930,通过获取多个通信小区的邻区关系和小区资源信息,并确定各个通信小区的小区质心,其中,小区资源信息由位于通信小区内的终端确定;根据邻区关系和小区资源信息,对各个通信小区进行区域划分,确定热点均衡区域,其中,热点均衡区域包括多个目标通信小区;获取位于各个目标通信小区内的终端的距离信息,其中,距离信息用于表征终端与各个小区质心的距离;根据距离信息、邻区关系和小区资源信息,基于预设的机器学习算法,确定各个目标通信小区的边缘调整信息,以调整目标通信小区的覆盖范围。基于此,通过区域划分,根据通信小区的邻区关系和小区资源信息,将多个目标通信小区划分至热点均衡区域,热点均衡区域是指需要进行负荷调整的区域,然后通过机器学习算法,利用终端与各个小区质心的距离,以及目标通信小区的邻区关系和小区资源信息,确定热点均衡区域内各个目标通信小区的边缘调整信息,进而调整目标通信小区的覆盖范围,实现了对目标通信小区的边缘进行动态调整,对相邻的目标通信小区进行负荷调整,有效提高通信小区的负荷调整效果,
另外,能够动态平衡热点均衡区域内各个目标通信小区的负荷,以整个热点均衡区域作为负荷调整单元,更容易达到全局最优,提高区域整体的负荷调整效果,从而提高用户体验。
本领域普通技术人员可以理解,上文中所公开方法中的全部或某些步骤、***可以被实施为软件、固件、硬件及其适当的组合。某些物理组件或所有物理组件可以被实施为由处理器,如中央处理器、数字信号处理器或微处理器执行的软件,或者被实施为硬件,或者被实施为集成电路,如专用集成电路。这样的软件可以分布在计算机可读介质上,计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的,术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外,本领域普通技术人员公知的是,通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号中的其他数据,并且可包括任何信息递送介质。
以上是对本申请的部分实施进行了具体说明,但本申请并不局限于上述实施方式,熟悉本领域的技术人员在不违背本申请本质的前提下还可作出种种的等同变形或替换,这些等同的变形或替换均包含在本申请权利要求所限定的范围内。
Claims (12)
- 一种通信网络负荷调整方法,包括:获取多个通信小区的邻区关系和小区资源信息,并确定各个所述通信小区的小区质心,其中,所述小区资源信息由位于所述通信小区内的终端确定;根据所述邻区关系和所述小区资源信息,对各个所述通信小区进行区域划分,确定热点均衡区域,其中,所述热点均衡区域包括多个目标通信小区;获取位于各个所述目标通信小区内的所述终端的距离信息,其中,所述距离信息用于表征所述终端与各个所述小区质心的距离;根据所述距离信息、所述邻区关系和所述小区资源信息,基于预设的机器学习算法,确定各个所述目标通信小区的边缘调整信息,以调整所述目标通信小区的覆盖范围。
- 根据权利要求1所述的方法,其中,所述小区资源信息包括容量占比;所述根据所述邻区关系和所述小区资源信息,对各个所述通信小区进行区域划分,确定热点均衡区域,包括:根据所述容量占比确定所述通信小区的负荷属性;根据所述邻区关系和所述负荷属性,对各个所述通信小区进行区域划分,得到热点均衡区域。
- 根据权利要求2所述的方法,其中,所述热点均衡区域包括核心小区;所述核心小区通过如下步骤确定:在所述容量占比大于预设的第一阈值的情况下,确定所述通信小区的负荷属性为高负荷小区;基于所述邻区关系,将任一所述高负荷小区作为核心小区,并将与所述核心小区相邻的所有所述高负荷小区作为所述核心小区。
- 根据权利要求3所述的方法,其中,所述热点均衡区域还包括负荷分担小区;所述负荷分担小区通过如下步骤确定:在所述容量占比小于等于预设的第二阈值的情况下,确定所述通信小区的负荷属性为中低负荷小区,其中,所述第二阈值小于等于所述第一阈值;基于所述邻区关系,遍历各个所述中低负荷小区,将与所述核心小区相邻的所有所述中低负荷小区作为负荷分担小区。
- 根据权利要求1所述的方法,其中,所述热点均衡区域包括核心小区和负荷分担小区,所述小区资源信息包括容量占比和容量缺口;所述根据所述距离信息、所述邻区关系和所述小区资源信息,基于预设的机器学习算法,确定各个所述目标通信小区的边缘调整信息,包括:基于所述容量占比和所述容量缺口的排序信息,遍历所述核心小区;对于任一所述核心小区,将位于所述核心小区内的所述终端作为待处理终端,并基于所述邻区关系,将与所述核心小区相邻的所述负荷分担小区作为待处理小区;将所述待处理终端的距离信息、所述邻区关系、所述核心小区的容量占比、所述待处理小区的容量占比和所述核心小区的容量缺口输入所述机器学习算法,确定各个所述目标通信小区的边缘调整信息。
- 根据权利要求1所述的方法,其中,所述小区资源信息包括容量占比和容量缺口,所述机器学习算法包括分类模型或聚类模型;所述根据所述距离信息、所述邻区关系和所述小区资源信息,基于预设的机器学习算法,确定各个所述目标通信小区的边缘调整信息,包括:获取各个所述终端的初始归属标签,其中,所述初始归属标签用于表征所述终端对应的所述目标通信小区;将所述距离信息、所述邻区关系、所述容量占比和所述容量缺口输入所述分类模型或所述聚类模型,确定各个所述终端的目标归属标签,其中,所述目标归属标签用于表征所述终端对应的所述目标通信小区;根据所述距离信息、所述初始归属标签、所述目标归属标签和所述邻区关系,确定各个所述目标通信小区的边缘调整信息。
- 根据权利要求6所述的方法,其中,所述根据所述距离信息、所述初始归属标签、所述目标归属标签和所述邻区关系,确定各个所述目标通信小区的边缘调整信息,包括:对于任一所述终端,当所述目标归属标签与所述初始归属标签不同,根据所述初始归属标签确定第一目标通信小区,并根据所述目标归属标签确定第二目标通信小区,其中,所述第一目标通信小区与所述第二目标通信小区相邻;根据所述距离信息、所述第一目标通信小区、所述第二目标通信小区和所述邻区关系,确定所述边缘调整信息,其中,所述边缘调整信息用于调整所述第一目标通信小区或所述第二目标通信小区的覆盖范围,以使所述第一目标通信小区与所述第二目标通信小区的容量占比之差最小化。
- 根据权利要求1所述的方法,其中,所述获取各个通信小区的邻区关系和小区资源信息的步骤之前,还包括:获取各个所述通信小区的测量报告,其中,所述测量报告由位于所述通信小区内的所述终端生成;根据所述测量报告,确定所述邻区关系和所述距离信息。
- 根据权利要求1所述的方法,其中,所述小区资源信息包括容量占比和容量缺口;所述获取各个通信小区的邻区关系和小区资源信息的步骤之前,还包括:获取所述通信小区的资源利用信息、资源容量信息和各个所述终端的初始归属标签,其中,所述初始归属标签用于表征所述终端对应的所述目标通信小区;根据所述资源利用信息,确定所述容量占比;根据所述资源容量信息和所述初始归属标签,确定所述容量缺口。
- 根据权利要求9所述的方法,其中,所述资源利用信息包括业务资源利用信息和硬件资源利用信息;所述业务资源利用信息至少包括如下之一:频域利用率或下行功率利用率;所述硬件资源利用信息至少包括如下之一:连接用户数与最大支持用户数的占比率或CPU利用率。
- 一种电子设备,包括:存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,所述处理器运行所述计算机程序时执行如权利要求1至10中任意一项所述的通信网络负荷调整方法。
- 一种计算机可读存储介质,存储有计算机可执行程序,所述计算机可执行程序用于使计算机执行如权利要求1至10中任意一项所述的通信网络负荷调整方法。
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