CN111385821B - LTE carrier demand quantity prediction method and device - Google Patents
LTE carrier demand quantity prediction method and device Download PDFInfo
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Abstract
A method of LTE carrier demand quantity prediction, the method comprising: obtaining a cell with unrestricted capacity according to the traffic information, transmission data and uplink and downlink utilization rate data of the LTE cell; performing capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the cell with unrestricted capacity to obtain the time when the cell with unrestricted capacity reaches the capacity threshold of the restricted cell; acquiring the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted flow information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell; and performing capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell. The invention also discloses a device for predicting the LTE carrier demand quantity. The invention can realize accurate carrier demand prediction.
Description
Technical Field
The present invention relates to the mobile communication industry, and more particularly, to a mobile communication network optimization technique.
Background
With unlimited package popularization, the traffic of the whole network 4G continuously and rapidly grows, the problem of high load in a hot spot area is more and more remarkable due to service imbalance, the service guarantee requirement of the whole network on high-speed and low-delay requirements is sharply improved due to transition of user behavior habits, and huge pressure is brought to wireless network optimization work.
In order to relieve the pressure of network optimization work, the common practice is to extract LTE cell load indexes (flow, user number, uplink and downlink PRB utilization rate) from a platform and extract performance data for 3-12 months. And (3) carrying out scene division on the cells (mainly 41 types of scenes published by the mobile group), and extracting the industrial parameter data of the cells. And evaluating the health degree of the network capacity by using the cell historical performance data, the cell scene division and the cell industrial parameter data. And carrying out corresponding network optimization work according to the health degree.
In the prior art, an algorithm for carrying out capacity prediction according to scenes is lacking, and the capacity prediction is inaccurate due to the fact that a unified empirical algorithm is adopted. Moreover, the current capacity prediction has strong subjectivity, and the provincial companies and the local municipalities report at will, so that the carrier frequency resource demand planning of the provincial and local municipalities is inaccurate, and the resources are insufficient or excessive.
Therefore, a technology for predicting the number of capacity carriers according to the accuracy is needed.
Disclosure of Invention
The invention provides a method for predicting the number of LTE carrier demands, which comprises the following steps:
obtaining a cell with unrestricted capacity according to the traffic information, transmission data and uplink and downlink utilization rate data of the LTE cell;
performing capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the cell with unrestricted capacity to obtain the time when the cell with unrestricted capacity reaches the capacity threshold of the restricted cell;
acquiring the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted flow information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell;
and performing capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell.
In detail, the method for acquiring the cell with unrestricted capacity according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cell specifically comprises the following steps:
and obtaining a cell which does not reach the high-load cell standard to be expanded according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cell as a cell with unrestricted capacity.
More specifically, the method for predicting the capacity of the capacity unrestricted cell based on the traffic data, the transmission data and the uplink and downlink utilization rate data to obtain the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell specifically comprises the following steps:
obtaining a flow data predicted value of the capacity unrestricted cell in a period according to the product of the current flow data of the capacity unrestricted cell and a flow growth coefficient, and obtaining the time of the capacity unrestricted cell reaching a capacity threshold of the restricted cell according to the number of periods required by the flow data predicted value to reach the capacity threshold of the restricted cell;
according to the trend relationship between the historical transmission data amplification and the average daily flow of the capacity unrestricted cell, acquiring a transmission data predicted value of the capacity unrestricted cell and the time for reaching the transmission data predicted value by using a preset prediction model;
according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell, acquiring an uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model;
the transmission data is an RRC number with data transmission.
Further, the method for obtaining the carrier demand number when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted traffic information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard traffic information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell specifically comprises the following steps:
determining the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the capacity-unrestricted cell according to the cell predicted traffic information and the cell traffic standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization rate and the cell utilization rate standard;
and determining the maximum value of the predicted uplink and downlink carrier limited quantity and CCE carrier limited quantity of the cell as the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the limited cell.
Preferably:
the cell flow standard is a flow average value in the cell period;
the cell transmission data standard is an RRC (radio resource control) number standard average value with data transmission in the cell period;
the cell uplink and downlink utilization rate standard is an average value of uplink and downlink utilization rates in the cell period.
Preferably:
the flow increase coefficient is the product of the ratio of the cell flow to the average cell flow of the whole network and the increase multiple of the whole network flow;
the prediction model is a multiple regression prediction model.
The invention also discloses a device for predicting the number of LTE carrier demands, which comprises:
the capacity unrestricted cell acquisition unit is used for acquiring a capacity unrestricted cell according to the traffic information, transmission data and uplink and downlink utilization rate data of the LTE cell;
the capacity prediction unit is used for performing capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the capacity unrestricted cell acquired by the capacity unrestricted cell acquisition unit, and acquiring the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell;
the carrier demand prediction unit is used for obtaining the carrier demand quantity of the capacity unrestricted cell reaching the capacity threshold of the limited cell according to the predicted flow information, the predicted transmission data and the predicted uplink and downlink utilization rate data of the capacity unrestricted cell predicted by the capacity prediction unit in combination with the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data;
and the capacity expansion planning unit is used for carrying out capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell, which are determined by the carrier demand prediction unit.
Specifically, the capacity prediction unit further includes:
the traffic data prediction module is used for obtaining a traffic data prediction value of the capacity unrestricted cell in a period according to the product of the current traffic data of the capacity unrestricted cell and a traffic growth coefficient, and obtaining the time of the capacity unrestricted cell reaching the capacity threshold of the restricted cell according to the period number required by the traffic data prediction value reaching the capacity threshold of the restricted cell;
the transmission data prediction module is used for acquiring a transmission data prediction value of the capacity unrestricted cell and the time for reaching the transmission data prediction value by utilizing a preset prediction model according to the trend relationship between the historical transmission data amplification and the daily average flow of the capacity unrestricted cell;
the uplink and downlink utilization rate prediction module is used for acquiring an uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell;
the transmission data is an RRC number with data transmission.
More specifically, the carrier demand prediction unit further includes:
the carrier limited number determining module is used for determining the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the capacity-unrestricted cell according to the cell predicted flow information and the cell flow standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization rate and the cell utilization rate standard;
and the carrier demand quantity determining module is used for determining the maximum value of the carrier demand quantity when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted uplink and downlink carrier restricted quantity and the CCE carrier restricted quantity of the cell determined by the carrier restricted quantity determining module.
Preferably, the method is characterized in that:
the cell flow standard is a flow average value in the cell period;
the cell transmission data standard is a transmission standard average value in the cell period;
the cell uplink and downlink utilization rate standard is an average value of uplink and downlink utilization rates in the cell period;
the flow increase coefficient is the product of the ratio of the cell flow to the average cell flow of the whole network and the increase multiple of the whole network flow;
the prediction model is a multiple regression prediction model.
According to the technical scheme, the LTE carrier demand quantity prediction technology disclosed by the embodiment of the invention measures all the cells which do not reach high load by using the high load standard, predicts the capacity of the cells according to the scene, obtains the possible time for the cells to reach high load, and further obtains the predicted value of the carrier demand quantity of the cells according to the limited quantity of the carrier waves of the cells and the predicted value of the capacity of the cells. By predicting massive big data in real time, network capacity increase and carrier demand quantity are predicted, the process of manual participation is reduced, and accuracy and operation efficiency are improved; according to the final predicted value of the number of the carriers, planned capacity expansion can be performed, and the purpose of reasonably distributing resources is achieved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an LTE carrier demand number prediction method according to a first embodiment of the present application;
FIG. 2 is a flow chart of a method according to a second embodiment of the present disclosure;
FIG. 3 is a flow chart of a method according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an LTE carrier demand number predicting apparatus according to a fourth embodiment of the present application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a method for predicting the number of LTE carriers required according to a first embodiment of the present invention is provided.
Step S01: and obtaining the cells with unrestricted capacity according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cells.
And obtaining a cell which does not reach the high-load cell standard to be expanded according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cell as a cell with unrestricted capacity.
Whether the cell is limited in capacity or not is judged, the judgment can be carried out through a threshold of flow data, a threshold of transmission data and an uplink and downlink utilization rate threshold, the setting of the thresholds can be carried out according to unified standards in the industry, the setting can also be carried out according to actual conditions, and one or more of flow information, transmission data and uplink and downlink utilization rate can be set according to the actual conditions and reach the threshold at the same time, so that the cell is determined to be limited in capacity.
Such as: "the number of effective RRC users reaches the threshold" and "the uplink utilization rate reaches the threshold" and "the uplink traffic reaches the threshold" ] or [ "the number of effective RRC users reaches the threshold" and "the downlink utilization rate reaches the threshold (PDSCH or PDCCH)" and "the downlink traffic reaches the threshold".
Preferably, the cell data in a period may also be determined, and a determination may be made as to whether the capacity of the cell data in the period is limited, typically a week, a month, a quarter, etc.
Step S02: and carrying out capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the cell with unrestricted capacity to obtain the time when the cell with unrestricted capacity reaches the capacity threshold of the restricted cell.
By predicting the cell capacity, the time when the cell capacity reaches the threshold can be obtained according to the increasing speed of the cell capacity.
The preferred prediction of capacity may employ a predictive model to predict the capacity of the cell based on historical data and current data.
Step S03: and acquiring the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted flow information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell.
The standard flow information, the standard transmission data and the standard uplink and downlink data are all average data in a specific time period of a cell. Since the average data can more accurately reflect the level of cell capacity.
Step S04: and performing capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell.
And counting the number of carrier demands of the whole network by rolling prediction of the cells which do not reach high load to be expanded, so that a planning department can carry out resource budget and purchase in advance. And periodically feeding back the calculated value of the carrier demand, reporting the calculated value to a superior unit for approval, and carrying out purchasing flow to purchase License resources in advance to manufacturers.
It can be seen that the invention firstly obtains the cells with unrestricted capacity, predicts the capacity of the cells according to the standard with restricted capacity, obtains the time when the cells reach the standard with restricted capacity, determines the number of the carrier according to the predicted value and the time, and performs the capacity expansion plan according to the number of the carrier. By the scheme, accurate cell capacity expansion can be realized, and network resources are reasonably utilized and allocated.
In order to better illustrate the present invention, a second embodiment is provided, and as shown in fig. 2, the method steps for obtaining the capacity unrestricted cell reaching the capacity restricted cell threshold in the present invention are described in detail.
Step S201: obtaining a flow data predicted value of the capacity unrestricted cell in a period according to the product of the current flow data of the capacity unrestricted cell and a flow growth coefficient, and obtaining the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the number of periods required by the flow data predicted value to reach the capacity threshold of the restricted cell.
The flow rate increase coefficient is the product of the ratio of the cell flow rate to the average cell flow rate of the whole network and the increase multiple of the whole network flow rate.
The flow growth coefficient is obtained by adopting a trend extrapolation prediction method, wherein the trend extrapolation prediction method is a common prediction method for predicting the future condition of things by searching the law of the development and change of the things along with the time according to the history and the reality data of the things. And performing machine learning training on a large amount of sample data related to capacity, and temporarily ignoring the missing and blank data to obtain a mathematical model for predicting the flow increase coefficient.
Preferably, the traffic growth coefficient may be further divided into scenes, where the ratio (adjustment coefficient) of the scene traffic growth coefficient=single-cell traffic to the average single-cell traffic of the whole network is the whole network traffic growth multiple
The flow value is predicted according to the flow increase coefficient, and the flow increase coefficient is multiplied by the current flow.
The scene-division flow rate increase coefficient can obtain the flow rate increase prediction condition of each cell according to each cell scene.
The whole network flow increase multiple comes from the increase requirement of the whole network flow, the predicted flow of the corresponding month of the whole network is found according to the month of the flow to be predicted, and compared with the latest month flow, the estimated whole network flow increase multiple can be calculated.
Step S202: and acquiring a predicted value of the transmission data of the capacity-unrestricted cell and the time for reaching the predicted value of the transmission data by using a preset prediction model according to the trend relationship between the historical transmission data amplification and the average daily flow of the capacity-unrestricted cell.
The transmission data is an RRC number with data transmission.
The prediction model is a multiple regression prediction model.
The regression prediction method predicts based on the correlation between the independent variable and the dependent variable. The number of the independent variables can be one or more, and the independent variables can be classified into a unitary regression prediction and a multiple regression prediction according to the number of the independent variables. Meanwhile, according to the correlation between independent variables and dependent variables, the method is divided into a linear regression prediction method and a nonlinear regression method. Learning of regression problems is equivalent to function fitting: a function curve is selected to fit known data well and to predict unknown data well.
According to the historical data, the trend relationship between the data transmission RRC number increase and the daily average flow increase of each cell can be obtained. According to the linear regression of the multiple regression prediction model, the change trend of the RRC number with data transmission is y= 0.0877x along with the flow amplification change 3 -0.7459x 2 +1.9256x+1.1014, where y is the predicted value; and predicting the RRC number with data transmission in each scene cell through the trend relation by combining the acquired scene flow amplification.
Step S203: and acquiring the uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell.
According to the historical data, the trend relation between the utilization rate of each cell and the daily average flow can be obtained. According to the linear regression of the multiple regression prediction model, the utilization rate change trend of y= -8E-09x can be obtained along with the flow change 4 +3E-06x 3 -0.0004x 2 +0.0279x+0.0927, wherein y is a utilization prediction value; and predicting the utilization rate of each scene cell through the trend relationship by combining the acquired flow amplification of each scene.
And combining the three prediction methods, predicting the flow of each scene cell, the RRC number with data transmission, the utilization rate and other index change conditions, and screening the number of cells needing capacity expansion in the future according to capacity expansion standards.
In order to explain in detail the various steps of how the number of carrier needs is obtained, a third embodiment of the present invention is presented, as shown in fig. 3.
Step S301: and obtaining the cells with unrestricted capacity according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cells.
Step S302: obtaining a flow data predicted value of the capacity unrestricted cell in a period according to the product of the current flow data of the capacity unrestricted cell and a flow growth coefficient, and obtaining the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the number of periods required by the flow data predicted value to reach the capacity threshold of the restricted cell.
Step S303: and acquiring a predicted value of the transmission data of the capacity-unrestricted cell and the time for reaching the predicted value of the transmission data by using a preset prediction model according to the trend relationship between the historical transmission data amplification and the average daily flow of the capacity-unrestricted cell.
Step S304: and acquiring the uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell.
Step S305: and determining the predicted uplink and downlink carrier limited quantity and the CCE carrier limited quantity of the capacity-unrestricted cell according to the cell predicted flow information and the cell flow standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization rate and the cell utilization rate standard.
The cell traffic standard is a traffic average value in the cell period. As shown in the following formula 1:
equation 1:
the cell transmission data standard is an RRC (radio resource control) number standard average value with data transmission in the cell period. As shown in the following formula 2:
equation 2:
the cell uplink and downlink utilization rate standard is an average value of uplink and downlink utilization rates in the cell period. The following formulas 3-1 and 3-2 are shown:
equation 3-1:
equation 3-2:
the capacity problem can be solved by calculating the carrier resource requirements, namely considering the capacity expansion of several carriers.
Uplink limitation: uplink limited carrier number=min { uplink traffic/uplink traffic criteria, RRC number with data transmission/RRC number with data transmission criteria, utilization/utilization criteria }
Limited downlink: downlink limited carrier number=min { downlink traffic/downlink traffic criteria, RRC number with data transmission/RRC number with data transmission criteria, utilization/utilization criteria }
CCE limited: CCE limited carrier number=min { downstream traffic/downstream traffic standard, RRC number with data transmission/RRC number with data transmission standard, utilization/utilization standard }
The above are the minimum values in brackets.
Step S306: and determining the maximum value of the predicted uplink and downlink carrier limited quantity and CCE carrier limited quantity of the cell as the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the limited cell.
Number of required carriers = MAX { number of uplink limited required carriers, number of downlink limited required carriers, number of CCE limited required carriers }
The carrier demand number is the maximum value of the uplink limited demand carrier number, the downlink limited demand carrier number and the CCE limited demand carrier number as the demand carrier number.
The invention also discloses a device for predicting the required quantity of LTE carriers, and a fourth embodiment of the invention is provided first, as shown in fig. 4, for explaining the structural characteristics of the device.
The device comprises:
the capacity unrestricted cell obtaining unit 1 is configured to obtain a capacity unrestricted cell according to traffic information, transmission data, and uplink and downlink utilization data of the LTE cell.
And the capacity prediction unit 2 is used for performing capacity prediction based on the flow data, the transmission data and the uplink and downlink utilization rate data on the capacity unrestricted cell acquired by the capacity unrestricted cell acquisition unit, so as to acquire the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell.
Preferably, the capacity prediction unit 2 further includes:
the traffic data prediction module 21 is configured to obtain a traffic data prediction value of the capacity unrestricted cell in a period according to a product of current traffic data of the capacity unrestricted cell and a traffic growth coefficient, and obtain a time when the capacity unrestricted cell reaches a capacity threshold of the restricted cell according to a number of periods required for the traffic data prediction value to reach the capacity threshold of the restricted cell.
The flow rate increase coefficient is the product of the ratio of the cell flow rate to the average cell flow rate of the whole network and the increase multiple of the whole network flow rate.
And the transmission data prediction module 22 is configured to obtain a transmission data predicted value of the capacity unrestricted cell and a time for reaching the transmission data predicted value according to a trend relationship between historical transmission data amplification and daily average flow of the capacity unrestricted cell by using a preset prediction model.
The prediction model is a multiple regression prediction model.
And the uplink and downlink utilization rate prediction module 23 is configured to obtain an uplink and downlink utilization rate predicted value of the capacity unrestricted cell and a time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model according to a trend relationship between historical uplink and downlink utilization rate amplification and daily average flow of the capacity unrestricted cell.
The transmission data is an RRC number with data transmission.
And the carrier demand prediction unit 3 is configured to obtain, according to the predicted traffic information, the predicted transmission data, the predicted uplink and downlink utilization rate data, and the standard traffic information, the standard transmission data, and the standard uplink and downlink utilization rate data of the capacity unrestricted cell predicted by the capacity prediction unit, the carrier demand number when the capacity unrestricted cell reaches the capacity threshold of the restricted cell.
Preferably, the carrier demand amount prediction unit 3 further includes:
the carrier limited number determining module 31 is configured to determine the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the capacity-unrestricted cell according to the cell predicted traffic information and the cell traffic standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization and the cell utilization standard.
The cell traffic standard is a traffic average value in the cell period.
The cell transmission data standard is a transmission standard average value in the cell period.
The cell uplink and downlink utilization rate standard is an average value of uplink and downlink utilization rates in the cell period.
And the carrier demand number determining module 32 is configured to determine, according to the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the cell determined by the carrier limited number determining module, that the maximum value is the carrier demand number when the capacity unrestricted cell reaches the capacity threshold of the restricted cell.
And the capacity expansion planning unit 4 is configured to perform capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the number of carrier demands reaching the capacity threshold of the restricted cell, which are determined by the carrier demand prediction unit.
It will be clear to those skilled in the art that, for convenience and brevity of description, the corresponding process in the above-described apparatus embodiment may refer to the specific working process of the foregoing method, which is not described herein again.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the present application described herein may be capable of operation in sequences other than those illustrated herein.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method for predicting the number of LTE carriers required, the method comprising:
obtaining a cell with unrestricted capacity according to the traffic information, transmission data and uplink and downlink utilization rate data of the LTE cell;
performing capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the cell with unrestricted capacity to obtain the time when the cell with unrestricted capacity reaches the capacity threshold of the restricted cell;
acquiring the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted flow information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell;
performing capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell;
the method for acquiring the carrier demand quantity when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted flow information, the predicted transmission data, the predicted uplink and downlink utilization rate data, the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data of the capacity unrestricted cell specifically comprises the following steps:
determining the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the capacity-unrestricted cell according to the cell predicted traffic information and the cell traffic standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization rate and the cell utilization rate standard; the cell flow standard is a flow average value in the cell period, and the formula is as follows:
and determining the maximum value of the predicted uplink and downlink carrier limited quantity and CCE carrier limited quantity of the cell as the carrier demand quantity when the capacity of the capacity unrestricted cell reaches the capacity threshold of the limited cell.
2. The method according to claim 1, wherein the method for obtaining the cell with unrestricted capacity according to the traffic information, the transmission data and the uplink and downlink utilization data of the LTE cell specifically comprises:
and obtaining a cell which does not reach the high-load cell standard to be expanded according to the traffic information, the transmission data and the uplink and downlink utilization rate data of the LTE cell as a cell with unrestricted capacity.
3. The method according to claim 2, wherein the capacity prediction based on traffic data, transmission data and uplink and downlink utilization data is performed on the capacity unrestricted cell, and the method for obtaining the time for the capacity unrestricted cell to reach the capacity threshold of the restricted cell specifically comprises:
obtaining a flow data predicted value of the capacity unrestricted cell in a period according to the product of the current flow data of the capacity unrestricted cell and a flow growth coefficient, and obtaining the time of the capacity unrestricted cell reaching a capacity threshold of the restricted cell according to the number of periods required by the flow data predicted value to reach the capacity threshold of the restricted cell;
according to the trend relationship between the historical transmission data amplification and the average daily flow of the capacity unrestricted cell, acquiring a transmission data predicted value of the capacity unrestricted cell and the time for reaching the transmission data predicted value by using a preset prediction model;
according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell, acquiring an uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model;
the transmission data is an RRC number with data transmission.
4. The method according to claim 1, characterized in that:
the cell flow standard is a flow average value in the cell period;
the cell transmission data standard is an RRC (radio resource control) number standard average value with data transmission in the cell period;
the cell uplink and downlink utilization rate standard is an average value of uplink and downlink utilization rates in the cell period.
5. The method according to any one of claims 3-4, wherein:
the flow increase coefficient is the product of the ratio of the cell flow to the average cell flow of the whole network and the increase multiple of the whole network flow;
the prediction model is a multiple regression prediction model.
6. An LTE carrier demand number prediction apparatus, characterized in that the apparatus comprises:
the capacity unrestricted cell acquisition unit is used for acquiring a capacity unrestricted cell according to the traffic information, transmission data and uplink and downlink utilization rate data of the LTE cell;
the capacity prediction unit is used for performing capacity prediction based on flow data, transmission data and uplink and downlink utilization rate data on the capacity unrestricted cell acquired by the capacity unrestricted cell acquisition unit, and acquiring the time when the capacity unrestricted cell reaches the capacity threshold of the restricted cell;
the carrier demand prediction unit is used for obtaining the carrier demand quantity of the capacity unrestricted cell reaching the capacity threshold of the limited cell according to the predicted flow information, the predicted transmission data and the predicted uplink and downlink utilization rate data of the capacity unrestricted cell predicted by the capacity prediction unit in combination with the standard flow information, the standard transmission data and the standard uplink and downlink utilization rate data;
the capacity expansion planning unit is used for carrying out capacity expansion planning on the capacity unrestricted cell according to the time reaching the capacity threshold of the restricted cell and the carrier demand quantity reaching the capacity threshold of the restricted cell, which are determined by the carrier demand prediction unit;
the carrier demand prediction unit further includes:
the carrier limited number determining module is used for determining the predicted uplink and downlink carrier limited number and the CCE carrier limited number of the capacity-unrestricted cell according to the cell predicted flow information and the cell flow standard, the cell predicted transmission data and the cell transmission data standard, the cell predicted utilization rate and the cell utilization rate standard; the cell flow standard is a flow average value in the cell period, and the formula is as follows:
and the carrier demand quantity determining module is used for determining the maximum value of the carrier demand quantity when the capacity unrestricted cell reaches the capacity threshold of the restricted cell according to the predicted uplink and downlink carrier restricted quantity and the CCE carrier restricted quantity of the cell determined by the carrier restricted quantity determining module.
7. The apparatus of claim 6, wherein the capacity prediction unit further comprises:
the traffic data prediction module is used for obtaining a traffic data prediction value of the capacity unrestricted cell in a period according to the product of the current traffic data of the capacity unrestricted cell and a traffic growth coefficient, and obtaining the time of the capacity unrestricted cell reaching the capacity threshold of the restricted cell according to the period number required by the traffic data prediction value reaching the capacity threshold of the restricted cell;
the transmission data prediction module is used for acquiring a transmission data prediction value of the capacity unrestricted cell and the time for reaching the transmission data prediction value by utilizing a preset prediction model according to the trend relationship between the historical transmission data amplification and the daily average flow of the capacity unrestricted cell;
the uplink and downlink utilization rate prediction module is used for acquiring an uplink and downlink utilization rate predicted value of the capacity unrestricted cell and the time for reaching the uplink and downlink utilization rate predicted value by using a preset prediction model according to the trend relationship between the historical uplink and downlink utilization rate increase and the daily average flow of the capacity unrestricted cell;
the transmission data is an RRC number with data transmission.
8. The apparatus according to claim 7, wherein:
the cell flow standard is a flow average value in the cell period;
the cell transmission data standard is a transmission standard average value in the cell period;
the standard of the uplink and downlink utilization rate of the cell is the average of the uplink and downlink utilization rates in the cell period
A value;
the flow increase coefficient is the product of the ratio of the cell flow to the average cell flow of the whole network and the increase multiple of the whole network flow;
the prediction model is a multiple regression prediction model.
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