CN112836911A - Method, device, electronic device and storage medium for determining energy saving parameters of a cell - Google Patents

Method, device, electronic device and storage medium for determining energy saving parameters of a cell Download PDF

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CN112836911A
CN112836911A CN201911166458.3A CN201911166458A CN112836911A CN 112836911 A CN112836911 A CN 112836911A CN 201911166458 A CN201911166458 A CN 201911166458A CN 112836911 A CN112836911 A CN 112836911A
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龚和平
卢东华
李平华
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ZTE Corp
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Abstract

本申请公开了一种小区节能参数的确定方法、装置、电子设备及存储介质，方法包括：获取小区的历史数据信息和小区属性信息；根据历史数据信息和小区属性信息确定小区的节能方式；周期性获取小区执行节能方式的关键性能指标，并根据关键性能指标获取节能评估结果；根据节能评估结果获得小区的节能参数，其中，节能参数包括节能门限和节能时间段。通过每个小区的历史数据信息以及每一个小区的属性信息，确定出小区的节能方式，通过评估小区关键性能指标，通过自学习获得的小区节能门限，通过对每个小区的差异化建模，预测每个小区未来的节能时间段，使得在保证小区通信质量良好的情况下，根据所确定的差异化节能参数达到最佳的节能效果。

Figure 201911166458

The present application discloses a method, device, electronic device and storage medium for determining energy saving parameters of a cell. The method includes: acquiring historical data information and cell attribute information of a cell; determining a cell energy saving method according to the historical data information and cell attribute information; The key performance indicators of the energy-saving mode implemented by the cell are obtained, and the energy-saving evaluation results are obtained according to the key performance indicators; energy-saving parameters of the cell are obtained according to the energy-saving evaluation results, wherein the energy-saving parameters include energy-saving thresholds and energy-saving time periods. Through the historical data information of each cell and the attribute information of each cell, the energy-saving mode of the cell is determined, by evaluating the key performance indicators of the cell, and obtaining the energy-saving threshold of the cell through self-learning, and through the differentiated modeling of each cell, The future energy-saving time period of each cell is predicted, so that the best energy-saving effect can be achieved according to the determined differentiated energy-saving parameters under the condition of ensuring good communication quality of the cell.

Figure 201911166458

Description

Method and device for determining cell energy-saving parameter, electronic equipment and storage medium
Technical Field
The embodiment of the application relates to the technical field of communication, in particular to a method and a device for determining a cell energy-saving parameter, electronic equipment and a storage medium.
Background
With the development of communication technology and the rapid growth of mobile users, the number of devices built in a wireless network by an operator is increasing, which also means that a cell covered by a base station needs to consume more energy to support the normal operation of the cell, so that the operator performs unified energy saving by performing parameter setting on the whole network cell for the problem.
In the prior art, the method of performing unified energy saving by using the parameters of the whole network cells often causes the setting of some cell parameters to be unreasonable, thereby causing poor energy saving effect and affecting the network communication quality.
Disclosure of Invention
The application provides a method and a device for determining cell energy-saving parameters, electronic equipment and a storage medium, wherein the energy-saving parameters of each cell are determined according to historical data information of each cell, so that the optimal energy-saving effect is achieved.
The embodiment of the application provides a method for determining and self-learning a cell energy-saving parameter, which comprises the following steps:
acquiring historical data information and cell attribute information of a cell;
determining an energy-saving mode of the cell according to the historical data information and the cell attribute information;
periodically acquiring key performance indexes of a cell executing an energy-saving mode, and acquiring an energy-saving evaluation result according to the key performance indexes;
and obtaining energy-saving parameters of the cell according to the energy-saving evaluation result, wherein the energy-saving parameters comprise an energy-saving threshold and an energy-saving time period, the energy-saving threshold is obtained in a self-learning mode, and the energy-saving time period is obtained in a prediction mode.
The embodiment of the application provides a device for determining a cell energy-saving parameter, which comprises:
the cell related information acquisition module is used for acquiring historical data information and cell attribute information of the cell;
the energy-saving mode determining module is used for determining the energy-saving mode of the cell according to the historical data information and the cell attribute information;
the evaluation result acquisition module is used for periodically acquiring key performance indexes of the energy-saving execution mode of the cell and acquiring an energy-saving evaluation result according to the key performance indexes;
and the energy-saving parameter acquisition module is used for acquiring energy-saving parameters of the cell according to the energy-saving evaluation result, wherein the energy-saving parameters comprise an energy-saving threshold and an energy-saving time period, and the energy-saving threshold is acquired in a self-learning manner.
An embodiment of the present application provides an apparatus, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the methods in the embodiments of the present application.
Embodiments of the present application provide a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements a method in embodiments of the present application.
According to the method and device for determining the cell energy-saving parameters, the electronic equipment and the storage medium, the key performance indexes of the cells are evaluated, the cell energy-saving threshold is obtained through self-learning, the future energy-saving time period of each cell is predicted through differential modeling of each cell, and the best energy-saving effect is achieved according to the determined differential energy-saving parameters under the condition that the good communication quality of the cells is guaranteed.
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Fig. 1 is a flowchart illustrating a method for determining a cell energy saving parameter according to an embodiment of the present application;
fig. 2 is a flowchart illustrating a method for determining a cell energy saving time period according to an embodiment of the present application;
fig. 3 is a flowchart illustrating a method for determining a cell energy saving mode according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an apparatus for determining a cell energy saving parameter according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of the apparatus provided in the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more apparent, embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
As shown in fig. 1, a schematic flow chart of a method for determining a cell energy saving parameter provided by the present application is shown. The method can be applied to the situation of determining the energy-saving parameters of the cell. The method can be executed by the device for determining the cell energy-saving parameter provided by the application, and the device for determining the cell energy-saving parameter is realized by software and/or hardware and is integrated on a device.
As shown in fig. 1, a flowchart of a method for determining a cell energy saving parameter according to an embodiment of the present application may include:
step 101, obtaining historical data information and cell attribute information of a cell.
In one example, the historical data information includes: the utilization rate of a downlink physical resource block, the utilization rate of an uplink physical resource block and the number of user connections; the cell attribute information includes: a multi-mode overlay or a base overlay. Of course, this embodiment is only described by way of example, and history data information and cell attribute information of other specific contents are also within the scope of the present application, and are not described in detail in this embodiment.
It should be noted that the number of cells in the embodiment of the present application may be multiple, that is, historical data information of each cell is obtained. And the basic coverage in the attribute information indicates that the cell can only provide basic coverage service, and the multimode coverage indicates that a network covered by multiple standards still exists in the coverage of the current cell, for example, the coverage of a certain 4G cell and the coverage of other 3G cells also exist in the coverage of the current cell.
And 102, determining an energy-saving mode of the cell according to the historical data information and the cell attribute information.
In one example, determining the energy saving mode of the cell according to the historical data information and the cell attribute information may include: determining the tide characteristics of the cell according to the historical data information, wherein the tide characteristics represent the daily load regular change of the cell; determining an energy-saving mode of the cell according to the tide characteristics and the cell attribute information, wherein the energy-saving mode comprises the following steps: at least one of carrier off, symbol off, and channel off.
It should be noted that, in the embodiment of the present application, the energy saving mode mapping table of the cell on the weekday and the weekend may also be obtained according to the specific tidal characteristics of the cell on the weekday and the weekend.
Step 103, periodically obtaining key performance indexes of the energy-saving mode executed by the cell, and obtaining an energy-saving evaluation result according to the key performance indexes.
The energy-saving threshold is obtained in a self-learning mode, and the energy-saving time period is obtained in a prediction mode.
In one example, obtaining a key performance index of the cell executing the energy saving mode and obtaining the energy saving evaluation result according to the key performance index may include: periodically obtaining key performance indexes of a cell executing an energy-saving mode, wherein the key performance indexes comprise: the method comprises the following steps of (1) carrying out cell wireless connection rate, cell wireless disconnection rate, switching success rate, cell uplink average rate or cell downlink average rate; acquiring historical key performance indexes before the energy-saving mode is not executed in a cell; obtaining an energy-saving evaluation result according to the key performance index and the historical key performance index, wherein the energy-saving evaluation result comprises the following steps: normal and abnormal. Of course, this embodiment is only described by way of example, and other types of key performance indexes are also within the protection scope of the present application, and are not described in detail in this embodiment.
In a specific implementation, taking a key performance index as a cell radio access rate as an example, periodically acquiring data of historical key performance indexes 2 months (with days as granularity) before a cell starts an energy-saving mode, calculating a mean value of the cell radio access rates from monday to sunday, when it is determined that the mean value of the radio access rates of a tuesday cell obtained according to historical data is m, an actual value of the current tuesday cell radio access rate obtained after energy saving is performed is a, and a set tolerance threshold value for the cell radio access rate is d, comparing (m-a)/m with d, and if the former is smaller than the latter, it is indicated that the key performance index is not degraded after energy saving, so that an evaluation result is normal; if the former is larger than the latter, the key performance index is deteriorated after energy saving, so that the evaluation result is abnormal. Of course, this embodiment is only described as an example, and other ways of obtaining the energy saving evaluation result are also within the scope of the present application, and no further description is given in this embodiment.
And 104, acquiring energy-saving parameters of the cell according to the energy-saving evaluation result.
In one example, the power saving parameter includes a power saving threshold and a power saving time period. Obtaining the energy saving parameter of the cell according to the energy saving evaluation result may include: acquiring an energy-saving threshold of the cell according to an energy-saving evaluation result; according to the key performance indexes obtained periodically, carrying out differential modeling on each cell to obtain a differential model of each cell; and obtaining the future energy-saving time period of each cell in a prediction mode according to the differential model and the energy-saving threshold of each cell.
In one example, obtaining the energy saving threshold of the cell according to the energy saving evaluation result may include: judging whether the energy-saving evaluation result is normal or not, if so, determining the type of the cell according to the condition of the current energy-saving threshold of the cell, otherwise, determining the type of the cell according to the condition causing abnormal results, wherein the type of the cell comprises a steady-state cell, an up-regulation cell and a down-regulation cell; and determining an energy-saving threshold according to the type of the cell.
The method comprises the steps of determining the type of a cell according to the current energy-saving threshold condition of the cell, specifically adopting a mode that whether the current energy-saving threshold reaches a learning adjustment target or not is judged, namely the current energy-saving threshold reaches a highest preset threshold or the current energy-saving evaluation reaches a tolerance threshold, if so, determining that the type of the cell is a steady-state cell without adjusting the current threshold, and if not, determining that the type of the cell is an up-regulated cell according to an energy-saving evaluation result, and if the type of the cell can be normally determined to be the up-regulated cell, performing up-regulation processing on the current threshold.
The type of the cell is determined according to the condition that the energy-saving evaluation result has an abnormal result, and the specific adopted mode is to judge whether the time period of the deterioration index appears in the energy-saving time period, if so, the type of the cell is determined to be a down-regulation cell, the current threshold needs to be subjected to down-regulation processing, and if not, the type of the cell is determined to be a steady-state cell.
In one example, determining the energy saving threshold according to the type of the cell may include: determining the energy-saving threshold adjustment step length of the cell according to the historical data information; when the type of the cell is determined to be a stable cell, the current energy-saving threshold is used as an energy-saving threshold without adjustment; when the type of the cell is determined to be the up-regulation cell, the current energy-saving threshold plus the energy-saving threshold adjustment step length is taken as the energy-saving threshold; and when the type of the cell is determined to be the down-regulation cell, subtracting the energy-saving threshold adjustment step length from the current energy-saving threshold to be used as the energy-saving threshold.
In a specific implementation, the step length of the energy saving threshold adjustment of the cell is determined according to the historical data information, and the step length can be obtained by calculation in the following manner: for each selected cell, taking days as granularity according to historical data information, sorting the 15-minute granularity data within one day, namely 96 granularity data in the order of load from high to low, and then for m days, the load information of n cells is shown in the following table 1:
TABLE 1
Cell numbering Day 1 load Day 2 load … Load of day m
cell1 Load sorting (96 pieces)
cell2
…
celln
The load data may be clustered by using a distance-based clustering method such as Kmeans, so that each cell belongs to a certain class, and the specific content of the clustering is not the key point of the present application, and thus, the detailed description is not repeated in the embodiments of the present application. Assuming that N cells are clustered into N types after clustering, calculating the weight of the j-th type load classification by using the following formula (1):
Figure BDA0002287585770000071
wherein M represents 96 × M load data, i represents values 1-M as sequence numbers of time granularity in an iteration cycle, j represents values 1-N as sequence numbers of load classification, and centLoadi,jRepresents the centroid value, weight, of the load class j at the ith time granularityjRepresenting the weight of the class j load classification.
Obtaining an energy-saving threshold adjustment step length k according to the following formula (2):
k＝weightj*L (2)
wherein k represents the energy-saving threshold adjustment step length, weightjAnd the weight of the j-th class load classification is represented, and L represents the configured step threshold.
When the type of the cell is determined to be a steady-state cell, taking the current energy-saving threshold as an energy-saving threshold; when the type of the cell is determined to be an up-regulation cell, adding the current energy-saving threshold and an energy-saving threshold adjustment step length k as an energy-saving threshold; and when the type of the cell is determined to be the down-regulation cell, subtracting the energy-saving threshold adjustment step length k from the current energy-saving threshold to be used as the energy-saving threshold.
In one example, the obtaining the future energy-saving time period of each cell in a predictive manner according to the differentiation model and the energy-saving threshold of each cell comprises: predicting future load information of each cell according to the differential model of each cell, wherein the differential model of each cell is updated in real time or periodically; determining a time range lower than an energy-saving threshold according to future load information; the time range is taken as the future energy-saving time period of the cell.
The prediction accuracy in this embodiment can be improved by updating the differentiated model of each cell in real time or periodically, and the updating time in the period specifically may be once every other day, or once every other hour, and the specific time in the period is not limited in this embodiment.
Wherein, step 103 and step 104 can be executed periodically and circularly, so as to achieve the purpose of obtaining the optimal energy-saving parameter through self-learning and continuous adjustment. And the cell energy-saving parameter is determined by the method, so that the condition that the network communication index is influenced due to unreasonable parameter setting caused by network change of certain cells can be avoided.
Fig. 2 is a flowchart illustrating a method for determining a cell energy saving time period according to an embodiment of the present application, where the method may include:
step 201, acquiring historical data of day granularity data, calculating positive effect of holidays, and determining holiday factors.
Specifically, data information of z holidays at the latest time in one year is extracted from historical data information for each cell, load data of each cell before, during and after the holidays are obtained, and if the load of the holiday start increases, the holiday end index decreases and falls to the level before the holidays, the holiday end index is a positive effect cell; if the load at the beginning of the vacation is reduced, the load at the end of the vacation is increased and is increased back to the level before the nodes, the cell is a negative effect cell; if the load index does not change obviously before and after holidays, the cell is an invalid cell. And the holiday factor of the no-effect cell is 1, and the holiday factor of the positive effect cell and the negative effect cell is the average value of the loads in holidays/loads before holidays of z holidays.
At step 202, the subsequence is split.
Wherein, historical day T data is split into 7 subsequences, each subsequence being the g-th day of the week.
Step 203, applying a prediction algorithm to predict the data of each day in the future for each subsequence.
Load prediction is carried out on 7 subsequences by using a prediction algorithm through a differentiation model, if a holiday happens, the predicted load is corrected through a holiday factor, for example, cell historical load data of t days of a certain sequence is input, and future data of k days in the future is predicted by using a time series prediction method, wherein t & gt & lt4 & gtk.
And step 204, merging the predicted data of each day.
Wherein, after 7 subsequences are predicted, the subsequences are combined in the week to obtain data of k days in the future.
And step 205, obtaining a future energy-saving time period according to the prediction result and the energy-saving threshold.
And determining the time range of the historical load information of each day in the prediction result, which is lower than the energy-saving threshold, and taking the time range as the future energy-saving time period of the cell.
According to the method for determining the cell energy-saving parameters, the key performance indexes of the cells are evaluated, the cell energy-saving threshold is obtained through self-learning, the differential modeling of each cell is carried out, and the future energy-saving time period of each cell is predicted, so that the best energy-saving effect is achieved according to the determined differential energy-saving parameters under the condition that the good communication quality of the cells is guaranteed.
Fig. 3 is a flowchart illustrating a method for determining a cell energy saving mode according to an embodiment of the present application, where the method may include:
step 301, obtaining historical data information and attribute information of a cell.
Wherein the historical data information comprises: the utilization rate of a downlink physical resource block, the utilization rate of an uplink physical resource block and the number of user connections; the attribute information includes: a multi-mode overlay or a base overlay.
Step 302, determine whether the cell has tidal characteristics, if yes, go to step 303, otherwise go to step 304.
Specifically, the tidal characteristics indicate the change of the load regularity of a cell every day, and if a certain cell has the characteristics that the call traffic volume suddenly increases in the last working time period of Monday and the call traffic volume remarkably decreases in the next working time period, the cell can be proved to have the tidal characteristics. Of course, this is merely an overview, and the following description will exemplify the determination of whether a cell has tidal characteristics based on historical data.
Taking the downlink physical resource block utilization rate as an example, extracting the index data of one month from the historical data for the selected cell, taking the hour as the data granularity, the cell has 30 × 24 ═ 720 dimensional data, comparing the physical resource block utilization rate of each hour granularity of the cell with a preset threshold value d, if the physical resource block utilization rate is greater than d, marking the physical resource block utilization rate as 1, if the physical resource block utilization rate is less than d, marking the physical resource block utilization rate as 0, thereby obtaining a string of 0 and 1 digit strings, and if the obtained digit strings have the following conditions, indicating that the cell has the tide characteristic:
(1) the number of 1 and 0 in a day is different by no more than 8;
(2) the number of consecutive 1 s and consecutive 0 s in a day is not less than 5.
In the present application, 8 and 5 are merely examples, and the specific value range of the above numerical values is not limited in the present application, and any positive integer greater than 0 and less than 24 is included in the protection range of the present application.
It should be noted that the tidal characteristics of the cells can be further specifically divided into weekday tides and weekend tides according to specific time ranges of weekdays and weekends.
Step 303, judging whether the cell is multi-mode covered, if so, determining that the energy-saving mode is carrier turn-off, otherwise, determining that the energy-saving mode is a mode of simultaneously turning on channel turn-off and symbol turn-off.
Step 304, determining whether the cell is the basic coverage, if so, determining that the energy saving mode is the symbol off, otherwise, executing step 305.
And 305, judging whether the cell is in multi-mode coverage, if so, determining that the energy-saving mode is a combined mode of optional carrier cut-off or channel + symbol cut-off, and otherwise, determining that the energy-saving mode is a mode of simultaneously turning on the symbol cut-off and the channel cut-off.
Fig. 4 is a schematic structural diagram of a cell energy saving parameter determining apparatus according to an embodiment of the present application, and as shown in fig. 4, the apparatus includes: a cell correlation obtaining module 41, configured to obtain historical data information and cell attribute information of a cell; an energy saving mode determining module 42, configured to determine an energy saving mode of the cell according to the historical data information and the cell attribute information; an evaluation result obtaining module 43, configured to periodically obtain a key performance index of the cell executing the energy saving mode, and obtain an energy saving evaluation result according to the key performance index; and the energy saving parameter obtaining module 44 is configured to obtain an energy saving parameter of the cell according to the energy saving evaluation result, where the energy saving parameter includes an energy saving threshold and an energy saving time period, and the energy saving threshold is obtained in a self-learning manner. The evaluation result obtaining module 43 and the energy saving parameter obtaining module 44 may be executed circularly and continuously, and adjust the self-adapting continuously to obtain the optimal energy saving parameter.
The device for determining a cell energy saving parameter provided in this embodiment is used to implement the method for determining a cell energy saving parameter of this application, and the implementation principle and technical effect of the device for determining a cell energy saving parameter provided in this embodiment are similar to those of the method for determining a cell energy saving parameter of this application, and are not described here again.
In one example, the historical data information includes: the utilization rate of a downlink physical resource block, the utilization rate of an uplink physical resource block and the number of user connections; the cell attribute information includes: a multi-mode overlay or a base overlay.
In one example, the energy-saving mode determining module is specifically used for determining the tide characteristics of the cell according to the historical data information, wherein the tide characteristics represent the daily load regular change of the cell; determining an energy-saving mode of the cell according to the tide characteristics and the cell attribute information, wherein the energy-saving mode comprises the following steps: at least one of carrier off, symbol off, and channel off.
In one example, the evaluation result obtaining module is specifically configured to: periodically obtaining key performance indexes of a cell executing an energy-saving mode, wherein the key performance indexes comprise: the method comprises the following steps of (1) carrying out cell wireless connection rate, cell wireless disconnection rate, switching success rate, cell uplink average rate or cell downlink average rate; acquiring historical key performance indexes before the energy-saving mode is not executed in a cell; obtaining an energy-saving evaluation result according to the key performance index and the historical key performance index, wherein the energy-saving evaluation result comprises the following steps: normal and abnormal.
In one example, the energy saving parameter obtaining module is specifically configured to: acquiring an energy-saving threshold of the cell according to an energy-saving evaluation result; according to the key performance indexes obtained periodically, carrying out differential modeling on each cell to obtain a differential model of each cell; and obtaining the future energy-saving time period of each cell in a prediction mode according to the differential model and the energy-saving threshold of each cell.
In an example, the energy saving parameter obtaining module, when performing the obtaining of the energy saving threshold of the cell according to the energy saving evaluation result, is specifically configured to: judging whether the energy-saving evaluation result is normal or not, if so, determining the type of the cell according to the condition of the current energy-saving threshold of the cell, otherwise, determining the type of the cell according to the condition that the energy-saving evaluation result has an abnormal result, wherein the type of the cell comprises a stable cell, an up-regulation cell and a down-regulation cell; and determining an energy-saving threshold according to the type of the cell.
In an example, when determining the energy saving threshold according to the type of the cell, the energy saving parameter obtaining module is specifically configured to: determining the energy-saving threshold adjustment step length of the cell according to the historical data information; when the type of the cell is determined to be a steady-state cell, taking the current energy-saving threshold as an energy-saving threshold; when the type of the cell is determined to be the up-regulation cell, the current energy-saving threshold plus the energy-saving threshold adjustment step length is taken as the energy-saving threshold; and when the type of the cell is determined to be the down-regulation cell, subtracting the energy-saving threshold adjustment step length from the current energy-saving threshold to be used as the energy-saving threshold.
In one example, predicting a future energy saving time period for each cell based on the differentiation model and the energy saving threshold for each cell comprises: the differential model of each cell predicts the future load information of the cell according to the historical data information; determining a time range lower than an energy-saving threshold according to future load information; the time range is taken as the future energy-saving time period of the cell.
As shown in fig. 5, an electronic device according to an embodiment of the present application includes: one or more processors 51 and storage 52; the processor 51 of the device may be one or more, and one processor 51 is taken as an example in fig. 5; storage 52 is used to store one or more programs; the one or more programs are executed by the one or more processors 51, so that the one or more processors 51 implement the method for determining the cell energy saving parameter as in the embodiment of the present invention.
The processor 51 and the storage 52 in the device may be connected by a bus or other means, and fig. 4 illustrates the connection by a bus as an example.
The storage device 52 is a computer-readable storage medium, and can be configured to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the method for determining the cell energy saving parameter in the embodiment of the present application. The storage device 52 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the device, and the like. Further, the storage 52 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the storage 52 may further include memory located remotely from the processor 51, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The present application provides a storage medium having a computer program stored thereon, where the computer program, when executed by a processor, implements the method for determining a cell energy saving parameter in any of the embodiments of the present application.
The method for determining the cell energy-saving parameter comprises the following steps: acquiring historical data information and cell attribute information of a cell; determining an energy-saving mode of the cell according to the historical data information and the cell attribute information; periodically acquiring key performance indexes of a cell executing an energy-saving mode, and acquiring an energy-saving evaluation result according to the key performance indexes; and obtaining energy-saving parameters of the cell according to the energy-saving evaluation result, wherein the energy-saving parameters comprise an energy-saving threshold and an energy-saving time period, and the energy-saving threshold is obtained in a self-learning manner.
The above description is only exemplary embodiments of the present application, and is not intended to limit the scope of the present application.
In general, the various embodiments of the application may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the application is not limited thereto.
Embodiments of the application may be implemented by a data processor of a mobile device executing computer program instructions, for example in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.
Any logic flow block diagrams in the figures of this application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored on a memory. The Memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, Read-Only Memory (ROM), Random Access Memory (RAM), optical storage devices and systems (Digital Video Disc (DVD) or Compact Disc (CD)), etc. The computer readable medium may include a non-transitory storage medium. The data processor may be of any type suitable to the local technical environment, such as but not limited to general purpose computers, special purpose computers, microprocessors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Programmable logic devices (FGPAs), and processors based on a multi-core processor architecture.
The foregoing has provided by way of exemplary and non-limiting examples a detailed description of exemplary embodiments of the present application. Various modifications and adaptations to the foregoing embodiments may become apparent to those skilled in the relevant arts in view of the following drawings and the appended claims without departing from the scope of the invention. Therefore, the proper scope of the invention is to be determined according to the claims.

Claims (11)

1. A method for determining cell energy saving parameters is characterized by comprising the following steps:
acquiring historical data information and cell attribute information of a cell;
determining an energy-saving mode of the cell according to the historical data information and the cell attribute information;
periodically acquiring a key performance index of the cell for executing the energy-saving mode, and acquiring an energy-saving evaluation result according to the key performance index;
and obtaining energy-saving parameters of the cell according to the energy-saving evaluation result, wherein the energy-saving parameters comprise an energy-saving threshold and an energy-saving time period, and the energy-saving threshold is obtained in a self-learning manner.
2. The method of claim 1, wherein the historical data information comprises: the utilization rate of a downlink physical resource block, the utilization rate of an uplink physical resource block and the number of user connections;
the cell attribute information includes: a multi-mode overlay or a base overlay.
3. The method of claim 2, wherein the determining the energy saving mode of the cell according to the historical data information and the cell attribute information comprises:
determining a tidal characteristic of the cell from the historical data information, wherein the tidal characteristic represents a daily load regularity change of the cell;
determining an energy saving mode of the cell according to the tide characteristics and the cell attribute information, wherein the energy saving mode comprises the following steps: at least one of carrier off, symbol off, and channel off.
4. The method according to claim 1, wherein the periodically obtaining a key performance indicator of the cell performing the energy saving mode and obtaining an energy saving evaluation result according to the key performance indicator comprises:
periodically obtaining a key performance index of the cell executing the energy saving mode, wherein the key performance index includes: the method comprises the following steps of (1) carrying out cell wireless connection rate, cell wireless disconnection rate, switching success rate, cell uplink average rate or cell downlink average rate;
acquiring historical key performance indexes before the energy-saving mode is not executed by the cell;
obtaining the energy-saving evaluation result according to the key performance index and the historical key performance index, wherein the energy-saving evaluation result comprises: normal and abnormal.
5. The method of claim 4, wherein obtaining the energy saving parameter of the cell according to the energy saving evaluation result comprises:
obtaining an energy-saving threshold of the cell according to the energy-saving evaluation result;
according to the key performance indexes obtained periodically, carrying out differential modeling on each cell to obtain a differential model of each cell;
and obtaining the future energy-saving time period of each cell in a prediction mode according to the differential model of each cell and the energy-saving threshold.
6. The method of claim 5, wherein obtaining the energy-saving threshold of the cell according to the energy-saving evaluation result comprises:
judging whether the energy-saving evaluation result is normal or not, if so, determining the type of the cell according to the condition of the current energy-saving threshold of the cell, otherwise, determining the type of the cell according to the condition that an abnormal result occurs in the energy-saving evaluation result, wherein the type of the cell comprises a steady-state cell, an up-regulation cell and a down-regulation cell;
and determining the energy-saving threshold according to the type of the cell.
7. The method of claim 6, wherein the determining the energy-saving threshold according to the type of the cell comprises:
determining the energy-saving threshold adjustment step length of the cell according to the historical data information;
when the type of the cell is determined to be a steady-state cell, taking the current energy-saving threshold as the energy-saving threshold;
when the type of the cell is determined to be an up-regulation cell, the current energy-saving threshold plus the energy-saving threshold adjustment step length is taken as the energy-saving threshold;
and when the type of the cell is determined to be a down-regulation cell, subtracting the energy-saving threshold adjustment step length from the current energy-saving threshold to be used as the energy-saving threshold.
8. The method of claim 5, wherein the obtaining the future energy-saving time period of each cell in a predictive manner according to the differentiation model of each cell and the energy-saving threshold comprises:
predicting future load information of each cell according to the differential model of each cell, wherein the differential model of each cell is updated in real time or periodically;
determining a time range lower than the energy-saving threshold according to the future load information;
and taking the time range as the future energy-saving time period of the cell.
9. An apparatus for determining a cell energy saving parameter, comprising:
the cell related information acquisition module is used for acquiring historical data information and cell attribute information of the cell;
an energy saving mode determining module, configured to determine an energy saving mode of the cell according to the historical data information and the cell attribute information;
an evaluation result obtaining module, configured to periodically obtain a key performance index of the cell executing the energy saving mode, and obtain an energy saving evaluation result according to the key performance index;
and the energy-saving parameter acquisition module is used for acquiring energy-saving parameters of the cell according to the energy-saving evaluation result, wherein the energy-saving parameters comprise an energy-saving threshold and an energy-saving time period, and the energy-saving threshold is acquired in a self-learning manner.
10. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.
11. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
CN201911166458.3A 2019-11-25 2019-11-25 Method, device, electronic device and storage medium for determining energy saving parameters of a cell Pending CN112836911A (en)

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