CN112312480B - Load balancing method and device of long term evolution network and base station equipment - Google Patents

Load balancing method and device of long term evolution network and base station equipment Download PDF

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CN112312480B
CN112312480B CN201910687741.4A CN201910687741A CN112312480B CN 112312480 B CN112312480 B CN 112312480B CN 201910687741 A CN201910687741 A CN 201910687741A CN 112312480 B CN112312480 B CN 112312480B
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service
cell
period
priority
ues
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CN112312480A (en
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刘毅
刘红梅
姜良军
袁鲲
张康
蒲承祖
邱伟娜
赵东升
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China Mobile Communications Group Co Ltd
China Mobile Group Shandong Co Ltd
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China Mobile Group Shandong Co Ltd
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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
    • 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

Abstract

The application provides a load balancing method, a device and base station equipment of a long-term evolution network, wherein the load balancing method of the long-term evolution network comprises the following steps: the load capacity of the cell is periodically monitored; when the load capacity of the cell is greater than or equal to a preset load threshold, performing priority ranking on the UE in the cell according to the service used by the UE in the cell in the period; transferring a predetermined number of UEs to the neighbor cell according to the result of the prioritization. According to the method and the device, when the load capacity of the cell is larger than or equal to the preset load threshold, the UE in the cell is subjected to priority sequencing according to the service used by the UE in the cell in the period, and the UE with the preset number is transferred to the adjacent cell according to the result of the priority sequencing, so that the QoS of the UE with high priority is guaranteed, and the perception of the load balance in the LTE network to the UE is improved.

Description

Load balancing method and device of long term evolution network and base station equipment
[ technical field ] A method for producing a semiconductor device
The present application relates to the field of communications technologies, and in particular, to a load balancing method and apparatus for a long term evolution network, and a base station device.
[ background of the invention ]
In a Long Term Evolution (Long Term Evolution; hereinafter referred to as LTE) network, when a part of cells are under a high load condition, a part of users can be migrated to a low load cell through a load balancing technology. The load balancing may be divided into a User Equipment (UE) pre-balancing mode in an idle state, a User data load balancing mode in a synchronous state, a Physical Resource Block (PRB) utilization rate/PRB evaluation value load balancing mode in a Physical Resource Block (hereinafter referred to as PRB) utilization rate/PRB evaluation value load balancing mode in a downlink data transfer User load balancing mode, and the like according to a trigger mode.
In the LTE load balancing method in the related art, users in a high-load Cell are only transferred to a low-load neighbor Cell from the viewpoints of terminal access, optimal target neighbor Cell selection, and/or optimal Cell Independent Offset (CIO) parameters, etc., so that the migrated UE has a certain blindness and cannot guarantee Quality of Service (QoS) of the UE.
[ summary of the invention ]
The embodiment of the application provides a load balancing method, a load balancing device and base station equipment of a Long Term Evolution (LTE) network, so that when the load capacity of a cell is greater than or equal to a preset load threshold, priority ranking is performed on UE in the cell according to the service used by the UE in the cell in the period, and a preset number of UE are transferred to adjacent cells according to the result of the priority ranking, so that the QoS of high-priority UE is guaranteed, and the perception of the load balancing in the LTE network to the UE is improved.
In a first aspect, an embodiment of the present application provides a load balancing method for a long term evolution network, including: periodically monitoring the load capacity of the cell; when the load capacity of the cell is greater than or equal to a preset load threshold, performing priority ranking on the UE in the cell according to the service used by the UE in the cell in the period; transferring a predetermined number of UEs to the neighbor cell according to the result of the prioritization.
In one possible implementation manner, the prioritizing the UEs in the cell according to the service used by the UE in the cell in the period includes: and according to the service type used by the UE in the cell in the period and the service volume of the service type, carrying out priority sequencing on the UE in the cell.
In a possible implementation manner, the prioritizing the UEs in the local cell according to the service types and the traffic volumes of the service types used by the UEs in the local cell in the current period includes: determining the service grade of the UE according to the service type used by the UE in the cell in the period and the service parameters of the service type; weighting the service grade of the UE by using the service volume of the service type used by the UE in the period to obtain the service priority of the UE in the period; and sequencing the priority of the UE in the local cell according to the service priority.
In one possible implementation manner, the determining, according to the service type used by the UE in the cell in the current period and the service parameter of the service type, the service class of the UE includes: and when the service type used by the UE in the cell in the period is the guaranteed bit rate service, determining the service level of the UE according to the service quality level corresponding to the guaranteed bit rate service, the target rate of the guaranteed bit rate service and the time delay requirement.
In a possible implementation manner, the determining, according to the service type used by the UE in the cell in the current period and the service parameter of the service type, the service class of the UE includes: when the service type used by the UE in the cell in the period is a non-guaranteed bit rate service, determining the service level of the UE according to the service quality level of the non-guaranteed bit rate service, the target rate of the non-guaranteed bit rate service and the packet loss requirement.
In a second aspect, an embodiment of the present application provides a load balancing apparatus for a long term evolution network, including: the monitoring module is used for periodically monitoring the load capacity of the cell; the sequencing module is used for carrying out priority sequencing on the UE in the cell according to the service used by the UE in the cell in the period when the load capacity of the cell is greater than or equal to a preset load threshold; and the transferring module is used for transferring the UE with the preset quantity to the adjacent cell according to the result of the priority ranking of the ranking module.
In one possible implementation manner, the sorting module is specifically configured to perform priority sorting on the UEs in the cell according to the service types and the traffic volumes of the service types used by the UEs in the cell in the period.
In one possible implementation manner, the sorting module includes: the determining submodule is used for determining the service grade of the UE according to the service type used by the UE in the cell in the period and the service parameter of the service type; the weighting submodule is used for weighting the service level of the UE by using the service volume of the service type used by the UE in the period to obtain the service priority of the UE in the period; and the priority ordering submodule is used for carrying out priority ordering on the UE in the cell according to the service priority.
In one possible implementation manner, the determining sub-module is specifically configured to determine, when the service type used by the UE in the local cell in the local period is a guaranteed bit rate service, a service level of the UE according to a quality of service level corresponding to the guaranteed bit rate service, a target rate of the guaranteed bit rate service, and a delay requirement.
In one possible implementation manner, the determining submodule is specifically configured to, when a service type used by the UE in the local cell in the current period is a non-guaranteed bit rate service, determine a service level of the UE according to a quality of service level of the non-guaranteed bit rate service, a target rate of the non-guaranteed bit rate service, and a packet loss requirement.
In a third aspect, an embodiment of the present application provides a base station device, including: at least one processor; and at least one memory communicatively coupled to the processor, wherein: the memory stores program instructions executable by the processor, which when called by the processor are capable of performing the method as described above.
In a fourth aspect, embodiments of the present application provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the method as described above.
In the above technical scheme, the load of the local cell is periodically monitored, when the load of the local cell is greater than or equal to the preset load threshold, the UEs in the local cell are subjected to priority ranking according to the services used by the UEs in the local cell in the current period, and a predetermined number of UEs are transferred to adjacent cells according to the result of the priority ranking, so that the QoS of the UEs with high priority is ensured, and the perception of the load balance in the LTE network to the UEs is improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of an embodiment of a load balancing method for a long term evolution network according to the present application;
fig. 2 is a flowchart of another embodiment of a load balancing method for a long term evolution network according to the present application;
fig. 3 is a flowchart of a load balancing method for a long term evolution network according to still another embodiment of the present application;
fig. 4 is a schematic diagram illustrating the number of transferred UEs in the load balancing method of the lte network according to the present application;
fig. 5 is a schematic structural diagram of an embodiment of a load balancing apparatus of a long term evolution network according to the present application;
fig. 6 is a schematic structural diagram of another embodiment of a load balancing apparatus of a long term evolution network according to the present application;
fig. 7 is a schematic structural diagram of an embodiment of a base station apparatus according to the present application.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present application, the following detailed descriptions of the embodiments of the present application are provided with reference to the accompanying drawings.
It should be understood that the embodiments described are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
In the LTE load balancing method provided in the related art, only from the angles of UE access, optimal target neighbor cell selection, and/or optimal cell independent offset CIO parameter, etc., the UE in the high-load cell is transferred to the low-load neighbor cell, but the priority of the transferred UE is not involved, so that the transferred UE has certain blindness.
The load balancing method for the long term evolution network provided by the embodiment of the application makes full use of the fact that Guaranteed Bit Rate (GBR) services and Non-Guaranteed Bit Rate (Non-GBR) services have different attention points, calculates the service grades of different services by combining multidimensional data comprehensive evaluation, performs service priority ranking on the service grades of different services by combining the service quantities of different services, and introduces the service grades into the judgment of transferred UE in the load balancing process, so that the QoS of high-priority UE is Guaranteed, and the perception of LTE load balancing on UE is improved.
Fig. 1 is a flowchart of an embodiment of a load balancing method for a long term evolution network according to the present application, and as shown in fig. 1, the load balancing method for the long term evolution network may include:
step 101, periodically monitoring the load capacity of the cell.
The length of the period may be set according to system performance and/or implementation requirements during specific implementation, and the length of the period is not limited in this embodiment, for example, the period may be 5 seconds, that is, 5 seconds may be a period to monitor the load of the cell.
And step 102, when the load capacity of the local cell is greater than or equal to a preset load threshold, performing priority ranking on the UEs in the local cell according to the services used by the UEs in the local cell in the period.
The preset load threshold may be set according to system performance and/or implementation requirements, and the size of the preset load threshold is not limited in this embodiment.
In the existing scheme, when UE is transferred, the utilization rate of PRBs occupied by the UE is mainly considered, but the priorities of different services are not considered, so that the transferred UE has certain blindness. In the embodiment, priority calculation of different services is realized by combining multidimensional data comprehensive evaluation by utilizing different attention points of GBR services and Non-GBR services.
Specifically, the services used by the UE in the cell may be classified into GBR services and Non-GBR services, and the attribute values of quality of service Class identifiers (QoS Class identifiers; hereinafter, abbreviated as QCI) of different services may be shown in table 1.
TABLE 1
Figure BDA0002146900150000061
Figure BDA0002146900150000071
The GBR service is sensitive to time delay comparison, and the QCI grade of the GBR service is QCI 1>, QCI 3>, QCI 2>, QCI 4, and the time delay requirement is QCI 3>, QCI 1>, QCI 2>, QCI 4. And for GBR services, combining the time delay requirements of the GBR services with the QCI grades and the target rates to arrange the grades of the GBR services.
The Non-GBR service is sensitive to the packet loss, and the QCI grade QCI 7= QCI 6>QCI 8>QCI 9, and the packet loss requires QCI 7= QCI 8= QCI 9>QCI 6. And combining the packet loss requirement of the Non-GBR service with the QCI level and the target rate to arrange the level of the Non-GBR service.
And then, according to the calculation results of the service levels of the GBR service and the Non-GBR service, combining the respective traffic volume ratios of the GBR service and the Non-GBR service, and after weighting, carrying out priority ranking on the UE in the cell.
Step 103, transferring a predetermined number of UEs to the neighboring cells according to the result of the prioritization.
Specifically, a predetermined number of UEs may be transferred to neighboring cells in order of priority from high to low, thereby guaranteeing QoS for high-priority UEs.
The predetermined number may be set according to system performance and/or implementation requirements, and the size of the predetermined number is not limited in this embodiment.
Further, after a predetermined number of UEs are transferred to an adjacent cell, a next load monitoring period is started, if the load of the cell is still greater than or equal to the preset load threshold, steps 102 to 103 are executed again to perform load balancing, and if the load of the cell is less than the preset load threshold, the next monitoring period is started.
In the load balancing method of the long term evolution network, the load of the cell is periodically monitored, when the load of the cell is greater than or equal to the preset load threshold, the UE in the cell is subjected to priority ranking according to the service used by the UE in the cell in the period, and the UE in the preset number is transferred to the adjacent cell according to the result of the priority ranking, so that the QoS of the UE with high priority is ensured, and the perception of the load balancing in the LTE network to the UE is improved.
Fig. 2 is a flowchart of another embodiment of the load balancing method for a long term evolution network according to the present application, as shown in fig. 2, in the embodiment shown in fig. 1 of the present application, step 102 may include:
step 201, when the load capacity of the local cell is greater than or equal to the preset load threshold, performing priority ranking on the UEs in the local cell according to the service types used by the UEs in the local cell in the period and the traffic of the service types.
Specifically, the services used by the UE in the cell may be classified into GBR services and Non-GBR services, and the UE in the cell is prioritized after weighting according to the calculation results of the service levels of the GBR services and the Non-GBR services and by combining the respective traffic volume ratios of the GBR services and the Non-GBR services.
Fig. 3 is a flowchart of another embodiment of a load balancing method for a long term evolution network according to the present application, as shown in fig. 3, in the embodiment shown in fig. 2 according to the present application, step 201 may include:
step 301, determining the service class of the UE according to the service type used by the UE in the cell in the current period and the service parameter of the service type.
In one implementation, when the service type used by the UE in the cell in the period is the GBR service, the service class of the UE is determined according to the QCI corresponding to the GBR service, the target rate of the GBR service, and the delay requirement.
In a specific implementation, when the service type used by the UE in the cell in the present period is GBR service, the service class of the UE may be calculated according to formula (1).
Figure BDA0002146900150000091
In the formula (1), k i When the service type used by the UE in the cell in the current period is GBR service, the service class of the UE is the GBR service;
Figure BDA0002146900150000092
wherein λ GBR The value of QCI grade corresponding to GBR service is1、2、3、4，f(QCI GRB ) To QCI level lambda GBR The larger the QCI rating, f (QCI) GRB ) The smaller the value of (c);
Figure BDA0002146900150000093
R i (t) is the target rate of the GBR traffic, the higher the target rate, the lower the priority;
f(Delay GRB )＝T Delay-GRB +γ，T(Delay GRB ) The time Delay threshold for different services is higher, T (Delay) GRB ) The greater the value of (A);
alpha, beta and gamma are auxiliary parameters and can be set differently according to big data statistics.
In another implementation manner, when the service type used by the UE in the local cell in the current period is a Non-GBR service, the service class of the UE is determined according to a QCI of the Non-GBR service, a target rate of the Non-GBR service, and a packet loss requirement.
In a specific implementation, when the type of the service used by the UE in the local cell in the current period is Non-GBR service, the service level of the UE may be calculated according to equation (2).
Figure BDA0002146900150000101
In the formula (2), k j When the service type used by the UE in the local cell in the current period is Non-GBR service, the service class of the UE is set;
Figure BDA0002146900150000102
λ Non-GBR the QCI grades corresponding to the Non-GBR service are set to be 6, 7, 8 and 9; f (QCI) Non-GRB ) To QCI level λ Non-GBR The larger the QCI rating, f (QCI) Non-GRB ) The smaller the value of (c);
Figure BDA0002146900150000103
R j (t) is a target rate of Non-GBR service, the higher the target rate is, the lower the priority is;
f(Lost Non-GRB )＝-log(T Lost-Non-GRB )+z，T(Lost Non-GRB ) For the logarithm function of the packet loss threshold that different services can bear, the higher the packet loss threshold is, T (Lost) Non-GRB ) The greater the value of (A);
x, y and z are auxiliary parameters and can be set differently according to big data statistics.
Step 302, weighting the service class of the UE by using the service volume of the service type used by the UE in the period to obtain the service priority of the UE in the period.
Specifically, the weighting of the service class of the UE by using the traffic of the service type used by the UE in the period may be: and multiplying the service quantity of the service type used by the UE in the period by the service grade of the UE.
Step 303, the UEs in the cell are prioritized according to the service priority.
In this embodiment, based on big data statistics, f (QCI) may be set for service emphasis and network quality of each local network GRB ) α, β, γ, f (QCI) of (C) Non-GRB ) The x, y and z in the system realize the personalized setting of LTE networks in various regions.
The load balancing method for the long term evolution network provided by the embodiment of the application performs load balancing on the UE in the cell based on the service priorities of different services, thereby overcoming the defect that the UE to be transferred in the existing scheme only depends on the utilization rate of the PRB, realizing the transfer of the UE with different service priorities, and ensuring the QoS of the UE with high priority. In-situ test, the number of UEs transferred in different service types is verified under the same load condition, and as can be seen from fig. 4, the load balancing method for the long term evolution network provided in the embodiment of the present application realizes that the UE with a high service priority is transferred preferentially, so that the perception of LTE load balancing on the UE is improved, and fig. 4 is a schematic diagram of the number of the transferred UEs in the load balancing method for the long term evolution network of the present application.
Fig. 5 is a schematic structural diagram of an embodiment of a load balancing apparatus of a long term evolution network according to the present application, where the load balancing apparatus of the long term evolution network in the present embodiment may be used as a base station device, or a part of the base station device, to implement the load balancing method of the long term evolution network according to the present application. As shown in fig. 5, the load balancing apparatus of the long term evolution network may include: a monitoring module 51, a sorting module 52 and a transfer module 53;
the monitoring module 51 is configured to periodically monitor a load amount of the local cell; the length of the period may be set according to system performance and/or implementation requirements during specific implementation, and the length of the period is not limited in this embodiment, for example, the period may be 5 seconds, that is, 5 seconds may be a period to monitor the load of the cell.
A sorting module 52, configured to, when the load amount of the local cell is greater than or equal to a preset load threshold, perform priority sorting on the UEs in the local cell according to the services used by the UEs in the local cell in the current period; the preset load threshold may be set according to system performance and/or implementation requirements, and the size of the preset load threshold is not limited in this embodiment.
In the existing scheme, when UE is transferred, the utilization rate of PRBs occupied by the UE is mainly considered, but the priorities of different services are not considered, so that the transferred UE has certain blindness. In the embodiment, priority calculation of different services is realized by combining multidimensional data comprehensive evaluation by utilizing different attention points of GBR services and Non-GBR services.
Specifically, the services used by the UE in the cell may be classified into GBR services and Non-GBR services, and QCI attribute values of different services may be as shown in table 1.
The GBR service is sensitive to time delay comparison, and the QCI grade of the GBR service is QCI 1>, QCI 3>, QCI 2>, QCI 4, and the time delay requirement is QCI 3>, QCI 1>, QCI 2>, QCI 4. And for GBR services, combining the time delay requirements of the GBR services with the QCI grades and the target rates to arrange the grades of the GBR services.
The Non-GBR service is sensitive to the packet loss, and the QCI grade QCI 7= QCI 6>QCI 8>QCI 9, and the packet loss requires QCI 7= QCI 8= QCI 9>QCI 6. And combining the packet loss requirement of the Non-GBR service with the QCI level and the target rate to arrange the level of the Non-GBR service.
Then, the ranking module 52 performs priority ranking on the UEs in the cell after weighting according to the calculation results of the GBR service and Non-GBR service levels and combining the respective traffic volume ratios of the GBR service and Non-GBR service.
A transferring module 53, configured to transfer a predetermined number of UEs to the neighboring cells according to the result of the priority ranking by the ranking module 52.
Specifically, the transferring module 53 may transfer a predetermined number of UEs to the neighboring cells in order of priority from high to low, thereby ensuring QoS for the high-priority UEs.
The predetermined number may be set according to system performance and/or implementation requirements, and the size of the predetermined number is not limited in this embodiment.
Further, after the transfer module 53 transfers a predetermined number of UEs to the adjacent cell, the next load monitoring period is entered, if the monitoring module 51 monitors that the load amount of the local cell is still greater than or equal to the preset load threshold, the sequencing module 52 and the transfer module 53 perform load balancing again, and if the load amount of the local cell is less than the preset load threshold, the next monitoring period is entered.
In the load balancing device of the long term evolution network, the monitoring module 51 periodically monitors the load capacity of the cell, when the load capacity of the cell is greater than or equal to the preset load threshold, the sorting module 52 performs priority sorting on the UEs in the cell according to the services used by the UEs in the cell in the period, and the transferring module 53 transfers a predetermined number of UEs to the adjacent cell according to the result of the priority sorting, so that the QoS of the high-priority UEs is ensured, and the perception of the load balancing in the LTE network to the UEs is improved.
Fig. 6 is a schematic structural diagram of another embodiment of a load balancing apparatus of a long term evolution network according to the present application, in this embodiment, a sorting module 52 is specifically configured to perform priority sorting on UEs in a local cell according to service types used by the UEs in the local cell in the current period and traffic volumes of the service types.
Specifically, the services used by the UE in the local cell may be classified into GBR services and Non-GBR services, and the ranking module 52 performs priority ranking on the UE in the local cell after weighting according to the calculation results of the service levels of the GBR services and the Non-GBR services and by combining the respective traffic occupancy ratios of the GBR services and the Non-GBR services.
In this embodiment, the sorting module 52 may include: a determination submodule 521, a weighting submodule 522 and a priority ranking submodule 523;
the determining submodule 521 is configured to determine a service level of the UE according to a service type used by the UE in the cell in the current period and a service parameter of the service type;
in an implementation manner, the determining submodule 521 is specifically configured to, when the service type used by the UE in the current cell in the current period is the GBR service, determine the service class of the UE according to the QCI corresponding to the GBR service, and the target rate and the delay requirement of the GBR service.
In a specific implementation, when the service type used by the UE in the cell in the present period is GBR service, the determining submodule 521 may calculate the service class of the UE according to formula (1).
In another implementation, the determining sub-module 521 is specifically configured to, when the service type used by the UE in the current cell in the current period is a Non-GBR service, determine the service class of the UE according to the QCI of the Non-GBR service, the target rate of the Non-GBR service, and a packet loss requirement.
In a specific implementation, when the type of service used by the UE in the local cell in the current period is Non-GBR service, the determining submodule 521 may calculate the service level of the UE according to equation (2).
A weighting submodule 522, configured to weight a service level of the UE by using a traffic volume of a service type used by the UE in the present period, so as to obtain a service priority of the UE in the present period;
specifically, the weighting of the service class of the UE by using the traffic of the service type used by the UE in the period may be: the weighting sub-module 522 multiplies the traffic of the traffic class of the UE by the traffic volume of the traffic class used by the UE in the present period.
The priority ranking submodule 523 is configured to perform priority ranking on the UEs in the cell according to the service priority.
The load balancing device for the long term evolution network, provided by the embodiment of the application, performs load balancing on the UE in the cell based on the service priorities of different services, thereby eliminating the disadvantage that the UE to be transferred in the existing scheme only depends on the utilization rate of the PRB, realizing the transfer of the UE with different service priorities, and ensuring the QoS of the UE with high priority. The field test verifies the number of UE transferred by different service types under the same load condition, and as can be seen from fig. 4, the load balancing device of the long term evolution network provided by the embodiment of the application realizes that UE with high service priority is transferred preferentially, and the perception of LTE load balancing on UE is improved.
Fig. 7 is a schematic structural diagram of an embodiment of a base station apparatus according to the present application, and as shown in fig. 7, the base station apparatus may include at least one processor; and at least one memory communicatively coupled to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the load balancing method of the long term evolution network provided by the embodiment of the application.
Fig. 7 shows a block diagram of an exemplary base station apparatus suitable for use in implementing embodiments of the present application. The base station apparatus shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 7, the base station apparatus is in the form of a general purpose computing device. Components of the base station apparatus may include, but are not limited to: one or more processors 410, a memory 430, and a communication bus 440 that connects the various system components (including the memory 430 and the processing unit 410).
Communication bus 440 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, industry Standard Architecture (ISA) bus, micro Channel Architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
The base station equipment typically includes a variety of computer system readable media. Such media may be any available media that is accessible by the base station device and includes both volatile and nonvolatile media, removable and non-removable media.
Memory 430 may include computer system readable media in the form of volatile Memory, such as Random Access Memory (RAM) and/or cache Memory. The base station device may further include other removable/non-removable, volatile/nonvolatile computer system storage media. Although not shown in FIG. 7, a disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a Compact disk Read Only Memory (CD-ROM), a Digital versatile disk Read Only Memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to the communication bus 440 by one or more data media interfaces. Memory 430 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility having a set (at least one) of program modules, including but not limited to an operating system, one or more application programs, other program modules, and program data, may be stored in memory 430, each of which examples or some combination may include an implementation of a network environment. The program modules generally perform the functions and/or methodologies of the embodiments described herein.
The base station device may also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), with one or more devices that enable a user to interact with the base station device, and/or with any devices (e.g., network card, modem, etc.) that enable the base station device to communicate with one or more other computing devices. Such communication may occur via communication interface 420. Furthermore, the base station device may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network such as the internet) through a Network adapter (not shown in fig. 7), which may communicate with other modules of the base station device through the communication bus 440. It should be appreciated that although not shown in fig. 7, other hardware and/or software modules may be used in conjunction with the base station device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive Arrays, disk array (RAID) systems, tape Drives, and data backup storage systems, among others.
The processor 410 executes programs stored in the memory 430 to perform various functional applications and data processing, for example, implement a load balancing method of a long term evolution network provided by the embodiment of the present application.
An embodiment of the present application further provides a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores a computer instruction, and the computer instruction causes the computer to execute the load balancing method for a long term evolution network provided in the embodiment of the present application.
The non-transitory computer readable storage medium described above may take any combination of one or more computer readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a flash Memory, an optical fiber, a portable compact disc Read Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a 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.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the 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 the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The word "if," as used herein, may be interpreted as "at \8230; \8230when" or "when 8230; \823030when" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.
It should be noted that the terminal in the embodiments of the present application may include, but is not limited to, a Personal Computer (Personal Computer; PC), a Personal Digital Assistant (PDA), a wireless handheld device, a Tablet Computer (Tablet Computer), a mobile phone, an MP3 player, an MP4 player, and the like.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer-readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims (8)

1. A method for load balancing of a long term evolution network is characterized by comprising the following steps:
periodically monitoring the load capacity of the cell;
when the load capacity of the cell is greater than or equal to a preset load threshold, performing priority ranking on the UE in the cell according to the service used by the UE in the cell in the period;
transferring a predetermined number of UEs to the neighboring cells according to the result of the prioritization;
the prioritizing the UEs in the cell according to the services used by the UEs in the cell in the period includes:
and according to the service type used by the UE in the cell in the period and the service volume of the service type, carrying out priority sequencing on the UE in the cell.
2. The method of claim 1, wherein the prioritizing the UEs in the local cell according to the service types and the traffic volumes of the service types used by the UEs in the local cell in the current period comprises:
determining the service grade of the UE according to the service type used by the UE in the cell in the period and the service parameters of the service type;
weighting the service grade of the UE by using the service volume of the service type used by the UE in the period to obtain the service priority of the UE in the period;
and carrying out priority sequencing on the UE in the cell according to the service priority.
3. The method of claim 2, wherein the determining the service class of the UE according to the service type used by the UE in the cell in the current period and the service parameter of the service type comprises:
when the service type used by the UE in the cell in the period is a guaranteed bit rate service, determining the service grade of the UE according to the service quality grade corresponding to the guaranteed bit rate service, the target rate of the guaranteed bit rate service and the time delay requirement.
4. The method of claim 2, wherein the determining the service class of the UE according to the service type used by the UE in the cell in the current period and the service parameter of the service type comprises:
when the service type used by the UE in the cell in the period is a non-guaranteed bit rate service, determining the service level of the UE according to the service quality level of the non-guaranteed bit rate service, the target rate of the non-guaranteed bit rate service and the packet loss requirement.
5. A load balancing apparatus for a long term evolution network, comprising:
the monitoring module is used for periodically monitoring the load capacity of the cell;
the sequencing module is used for carrying out priority sequencing on the UE in the cell according to the service used by the UE in the cell in the period when the load capacity of the cell is greater than or equal to a preset load threshold;
a transferring module, configured to transfer a predetermined number of UEs to an adjacent cell according to the result of the priority ranking by the ranking module;
the sorting module is specifically configured to perform priority sorting on the UEs in the local cell according to the service types used by the UEs in the local cell in the local period and the traffic of the service types.
6. The apparatus of claim 5, wherein the ordering module comprises:
the determining submodule is used for determining the service grade of the UE according to the service type used by the UE in the cell in the period and the service parameter of the service type;
the weighting submodule is used for weighting the service level of the UE by using the service volume of the service type used by the UE in the period to obtain the service priority of the UE in the period;
and the priority sequencing submodule is used for carrying out priority sequencing on the UE in the local cell according to the service priority.
7. A base station apparatus, comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1 to 4.
8. A non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the method of any one of claims 1 to 4.
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