CN107182067B - Network optimization method and device - Google Patents
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Abstract
The embodiment of the invention discloses a network optimization method, which comprises the following steps: drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate; obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate; and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph. Furthermore, the embodiment of the invention also discloses a network optimization device.
Description
Technical Field
The present invention relates to network optimization technologies in the field of communications, and in particular, to a network optimization method and apparatus.
Background
With the development of communication technology, the application of the 4G network is already mature, and as the 4G network can quickly transmit data, and further can quickly transmit high-quality audio/video files, images and the like, more and more users can select to use the 4G network.
In the prior art, since the 4G network may be affected by various factors, not all users using the 4G network can enjoy the high transmission rate of the 4G network. For example, where the Signal to interference plus Noise Ratio (SINR) is higher, the 4G user perception rate is higher, and where the SINR is lower, the 4G user perception rate is lower; the 4G user perception rate is the download rate experienced by the 4G network user terminal, and can be characterized by the ratio of the total flow of a cell PDCP layer to the download duration of all users in the cell.
In general, the perceived rate of 4G users in different areas can be improved by adjusting the SINR of 4G networks in different areas. However, since the 4G network is also affected by Modulation and Coding Scheme (MCS), the 4G user perception rate is not high in some areas with high signal-to-noise ratio. Therefore, it can be seen that the 4G user perception rate cannot be effectively improved by adjusting the 4G network by using the two-dimensional relationship between the SINR and the 4G user perception rate.
Disclosure of Invention
In order to solve the above technical problems, embodiments of the present invention are expected to provide a network optimization method and apparatus, which can improve effectiveness of optimizing a user perception rate, and further improve user experience.
The technical scheme of the invention is realized as follows:
in one aspect, an embodiment of the present invention provides a network optimization method, including:
drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate;
obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate;
and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph.
Optionally, before optimizing the user sensing rate of the target cell according to the SINR and the MCS corresponding to the area where the user sensing rate on the contour plane graph is greater than or equal to the preset threshold, the method further includes:
dividing the contour line plane graph into a plurality of cells according to preset scales;
acquiring the user perception rate of each cell;
the optimizing the user sensing rate of the target cell according to the SINR and the MCS corresponding to the area where the user sensing rate on the contour plane graph is greater than or equal to the preset threshold includes:
and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour plane graph.
Optionally, the obtaining the user perception rate of each cell includes:
acquiring user perception rates of a plurality of points in a first cell;
calculating an average of the user perception rates of the plurality of points;
and taking the average value as the user perception rate of the first cell.
Optionally, the optimizing the user sensing rate of the target cell according to the SINR and the MCS corresponding to the cell whose user sensing rate on the contour plane graph is greater than or equal to the preset threshold includes:
acquiring a user perception rate reference curve according to the cells of which the user perception rate is greater than or equal to a preset threshold value on the contour line plane graph;
and optimizing the user perception rate of the target cell according to the user perception rate reference curve.
Optionally, the obtaining a user perception rate reference curve according to the cell on the contour plane graph where the user perception rate is greater than or equal to the preset threshold includes:
sequentially connecting cells with user perception rates which are adjacent along a first direction and are larger than or equal to a preset threshold value, and acquiring a user perception rate reference curve; the first direction is a direction in which the SINR increases.
In another aspect, an embodiment of the present invention provides a network optimization apparatus, including:
the drawing unit is used for drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate;
a first obtaining unit, configured to obtain a contour line plan of the three-dimensional surface map on a two-dimensional plane formed by the SINR and the MCS, where each point included in the contour line plan has a corresponding user perception rate;
and the optimizing unit is used for optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph.
Optionally, the apparatus further comprises:
the dividing unit is used for dividing the contour line plane graph into a plurality of cells according to preset scales;
the second acquisition unit is used for acquiring the user perception rate of each cell;
the optimization unit is specifically configured to:
and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour plane graph.
Optionally, the second obtaining unit is specifically configured to:
acquiring user perception rates of a plurality of points in a first cell;
calculating an average of the user perception rates of the plurality of points;
and taking the average value as the user perception rate of the first cell.
Optionally, the optimization unit is specifically configured to:
acquiring a user perception rate reference curve according to the cells of which the user perception rate is greater than or equal to a preset threshold value on the contour line plane graph;
and optimizing the user perception rate of the target cell according to the user perception rate reference curve.
Optionally, the optimization unit is specifically configured to:
sequentially connecting cells with user perception rates which are adjacent along a first direction and are larger than or equal to a preset threshold value, and acquiring a user perception rate reference curve; the first direction is a direction in which the SINR increases.
The embodiment of the invention provides a network optimization method and a device, wherein the network optimization method comprises the following steps: drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate; obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate; and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph. Compared with the prior art, the user perception rate can be optimized through the SINR and MCS parameters, so that limitation caused by adjusting a single parameter to optimize the user perception rate is avoided, effectiveness of optimizing the user perception rate is improved, and user experience is improved.
Drawings
Fig. 1 is a schematic flowchart 1 of a network optimization method according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a network optimization method according to an embodiment of the present invention 2;
FIG. 3 is a three-dimensional surface graph of user perception rate provided by an embodiment of the present invention;
FIG. 4 is a plan view of a contour line of user perceived rate provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a partition of a contour plane diagram provided in an embodiment of the present invention;
FIG. 6 is a diagram illustrating a user perceived rate reference curve according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram 1 of a network optimization apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram 2 of a network optimization apparatus according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
An embodiment of the present invention provides a network optimization method, as shown in fig. 1, including:
In an example, a plurality of parameters affecting the user perception rate are provided, but it can be known through correlation analysis that the most important parameters affecting the user perception rate are SINR and MCS, in order to accurately reflect the value of the user perception rate under the influence of the SINR and MCS, a three-dimensional function of the SINR, the MCS and the user perception rate can be established, a three-dimensional surface graph of the three-dimensional function is drawn, and the fluctuation condition of the user perception rate under the influence of the SINR and MCS can be intuitively obtained through the three-dimensional surface graph.
And 102, obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate.
For example, although the three-dimensional surface graph can intuitively present the relationship between the user perception rate and the SINR, MCS, because the three-dimensional surface graph is a 3D solid graph, and the surface of the user perception rate is complicated in space and is not convenient to be directly applied in the wireless network optimization working process, the three-dimensional surface graph of the user perception rate can be cut parallel to the plane formed by the SINR and the MCS every time the difference D is from high to low, that is, points with the same user perception rate are connected by curves, and the obtained cut surface graph is vertically projected onto the plane formed by the SINR and the MCS, so that a contour line plane graph which projects the three-dimensional surface of the user perception rate onto the two-dimensional plane formed by the SINR and the MCS is obtained. Since the contour line plan is a projection of a three-dimensional surface graph of the user perception rate, each point included in the contour line plan has a corresponding user perception rate.
And 103, optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold, on the contour plane graph.
Illustratively, the contour plan includes different user perceived rates for each point, and each point has a corresponding SINR and MCS. If the user perception rate of the point A is larger than or equal to the preset threshold value, the user perception rate is good, and the user requirement is met. Therefore, when the target cell is optimized, the SINR and MCS of the target cell are made to be the same as those of the point a, which indicates that the user perceived rate optimization of the target cell is successful. However, countless points exist on the contour line plane graph, which is inconvenient for statistics, so in practical application, an area on the contour line plane graph where the user perception rate is greater than or equal to a preset threshold may be marked first, and then the value ranges of SINR and MCS corresponding to the area may be used as target values of SINR and MCS when the user perception rate of the target cell is optimized.
Therefore, the user perception rate can be optimized through the SINR and the MCS, so that limitation caused by adjusting a single parameter to optimize the user perception rate is avoided, the effectiveness of optimizing the user perception rate is improved, and further the user experience is improved.
Further, before optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area where the user perception rate on the contour plane graph is greater than or equal to the preset threshold, the contour plane graph may be further divided into a plurality of cells according to preset scales, and then the user perception rate of each cell is obtained. And then optimizing the user perception rate of the target cell according to the SINR and MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour line plane graph.
For example, in order to more accurately represent an area where the user sensing rate on the contour plane graph is greater than or equal to a preset threshold, the contour plane graph may be divided into a plurality of cells according to a preset scale, each cell has a value range of the corresponding SINR and MCS and a corresponding user sensing rate, and the SINR and the MCS within the value range of the SINR and the MCS corresponding to the cell where the user sensing rate is greater than or equal to the preset threshold may be both used as target values of the SINR and the MCS when the user sensing rate of the target cell is optimized.
Optionally, when the user perception rate of each cell is obtained, the user perception rates of a plurality of points in the first cell may be obtained first, and then an average value of the user perception rates of the plurality of points is calculated, and the average value is used as the user perception rate of the first cell.
For example, since countless points are included in each cell, statistics cannot be sequentially performed, and thus, the points included in the cells may be sampled. Specifically, taking the first cell as an example for description, the user perception rates of at least two points may be collected in the first cell, and then an average value of the user perception rates of the at least two points is calculated, and the average value may be used as the user perception rate of the first cell. It should be noted that sampling may be performed in the first cell according to a sampling method commonly used in the prior art, for example, an average sampling method, a random sampling method, and the like, which is not limited in this embodiment of the present invention. The first cell is any one cell obtained through division.
Optionally, when the user sensing rate of the target cell is optimized according to the SINR and the MCS corresponding to the cell with the user sensing rate greater than or equal to the preset threshold on the contour plane diagram, a user sensing rate reference curve may be first obtained according to the cell with the user sensing rate greater than or equal to the preset threshold on the contour plane diagram, and then the user sensing rate of the target cell is optimized according to the user sensing rate reference curve.
For example, because there are more cells on the plane of the SINR and the MCS, there are multiple cells with user perception rates greater than or equal to the preset threshold, which is equivalent to that there are multiple discrete points with user perception rates greater than or equal to the preset threshold on the plane of the SINR and the MCS, and a normalization curve of the discrete points may be obtained according to a statistical rule, where the normalization curve is a user perception rate reference curve.
Optionally, when a user perception rate reference curve is obtained according to the cells on the contour plane graph where the user perception rate is greater than or equal to the preset threshold, the cells adjacent to each other along the first direction where the user perception rate is greater than or equal to the preset threshold may be sequentially connected to obtain the user perception rate reference curve; the first direction is a direction in which the SINR increases.
For example, when normalization is performed according to a statistical rule, a situation that a deviation between a discrete point and a normalization curve is large may occur, so that the normalization curve is not accurate enough, in practical application, adjacent cells with a user perception rate greater than or equal to a preset threshold value may also be connected together by a straight line along a direction in which an SINR increases, and a user perception rate reference curve may be obtained by sequentially connecting two adjacent cells with a user perception rate greater than or equal to a preset threshold value.
The embodiment of the invention provides a network optimization method, which comprises the following steps: drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate; obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate; and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph. Compared with the prior art, the user perception rate can be optimized through the SINR and MCS parameters, so that limitation caused by adjusting a single parameter to optimize the user perception rate is avoided, effectiveness of optimizing the user perception rate is improved, and user experience is improved.
An embodiment of the present invention provides a network optimization method, as shown in fig. 2, including:
For example, there are many factors affecting the user sensing rate in the wireless environment, and some factors affect the user sensing rate by affecting the coverage area of the wireless network, for example, parameters such as reference signal received power, weak coverage coefficient, and over-coverage coefficient; some factors influence the user sensing rate by influencing the access capacity of the wireless network, such as parameters of average activated user number, MCS, Physical Resource Block (PRB) utilization rate and the like; other factors affect the user perception rate by affecting the communication quality of the wireless network, such as parameters like interference power, noise power, call completing rate, handover success rate, etc. And respectively carrying out relevance comparison on the parameters and the user perception rate, and acquiring parameters with higher relevance to the user perception rate for analysis. Specifically, a correlation coefficient can be introduced, wherein the correlation coefficient is a parameter for measuring the linear correlation degree between two random variables, and the specific formula is
Wherein, P is a user perception rate, Q is a parameter related to the user perception rate, N is an integer greater than or equal to 1, which represents the collection times of P and Q, and in order to ensure the validity of the calculation result, multiple groups of P and Q are usually collected for correlation calculation; piFor the ith acquired user perception rate, QiFor the ith acquired parameter related to the user perception rate, the method
Is the average of the P collected N times, the
The average of Q collected N times.
According to correlation coefficients of different parameters and user perception rates, the correlation degree of each parameter and the user perception rate can be determined, the value range of the correlation coefficient r is [ -1,1], if r >0 represents positive correlation, if r <0 represents negative correlation, and | r | represents the correlation degree between variables. Specifically, r ═ 1 is referred to as a complete positive correlation, r ═ 1 is referred to as a complete negative correlation, and r ═ 0 is referred to as an uncorrelated. According to calculation, the three most important parameters affecting the user perception rate are: reference signal received power (C), MCS, interference + noise power (I). Since the signal-to-noise ratio SINR is C/I, the most important factors affecting the user perceived rate are SINR and MCS. It can be seen that the user perceived rate is not only affected by the SINR or MCS, but also related to both SINR and MCS.
In order to accurately reflect the value of the user sensing rate under the influence of the SINR and the MCS, a three-dimensional function Z ═ f (X, Y) of the SINR, the MCS, and the user sensing rate Z may be established, and a three-dimensional curved surface graph of Z ═ f (X, Y) is drawn, as shown in fig. 3, where an X axis represents the value of the SINR, a Y axis represents the value of the MCS, and a Z axis represents the value of the user sensing rate Z. As can be seen from fig. 3, each point on the curved surface 301 has a group of corresponding SINR and MCS values, that is, each user sensing rate z has a group of corresponding SINR and MCS values, and under the same SINR value, the user sensing rate z varies according to different MCS values; under the same MCS value, the user perception rate z changes according to different SINR values.
For example, although a three-dimensional surface graph with z ═ f (x, y) intuitively presents the relationship between the user perception rate z and the SINR, MCS, since the three-dimensional surface graph is a 3D solid graph and the situation of the surface of the user perception rate z in space is complex and is not convenient to be directly applied in the wireless network optimization work process, a tangent plane parallel to the xy plane can be made for each phase difference D of the three-dimensional surface graph of the user perception rate z from high to low, that is, points with the same user perception rate z are connected by curves, and the obtained tangent plane graph is vertically projected to the xy plane, so that a contour plane graph which projects the three-dimensional surface of the user perception rate z to the two-dimensional plane composed of the SINR and the MCS is obtained. For example, taking the case that the SINR is greater than or equal to-4 dB, less than or equal to 4dB, the MCS is greater than or equal to-4 dB, and the MCS is less than or equal to 4dB, the distribution of the user perception rate z is described as an example, a three-dimensional curved surface of the user perception rate z in the above value range is projected to a two-dimensional plane formed by the SINR and the MCS to obtain a contour line plan, as shown in fig. 4, the user perception rate corresponding to each point on the contour line 401 is the same, the user perception rate inside the contour line 401 is greater than the user perception rate corresponding to each point on the contour line, an area surrounded by the contour line 401 is inside the contour line 401, and the user perception rate corresponding to a point located between the contour line 401 and the contour line 402 is less than the user perception rate corresponding to each. The d can be set to 10Mbps, and the setting is performed according to actual conditions in practical application, which is not limited in the embodiment of the present invention.
And 203, dividing the contour plane graph into a plurality of cells.
For example, the contour plane graph is projected on a plane of SINR and MCS, so that a value of the corresponding user perception rate z exists at each point on the plane. However, there are countless points on the SINR and MCS planes, which are not convenient for engineering use, so the SINR and MCS planes can be divided into several unit grids according to a preset scale. The preset scale may be 0.5dB by 0.5dB, and may be determined according to specific situations in practical applications, which is not limited in the embodiment of the present invention. For example, the contour plane graph obtained in fig. 4 is divided into cells, as shown in fig. 5, the value of the X axis of the cell 501 is greater than or equal to 0dB, and less than or equal to 0.2dB, and the value of the Y axis is greater than or equal to 0dB, and less than or equal to 0.2dB, which means that the SINR corresponding to the cell 501 is greater than or equal to 0dB, and less than or equal to 0.2dB, and the corresponding MCS is greater than or equal to 0dB, and less than or equal to 0.2 dB.
And 204, acquiring the user perception rate corresponding to each cell.
For example, taking the cell 501 in fig. 5 as an example for explanation, first, the user perception rate z corresponding to each point in the cell 501 is obtained, then an average value of the user perception rates z corresponding to each point is calculated, and the average value is used as the user perception rate z corresponding to the cell 501, that is, the user perception rate z corresponding to each point in the cell 501 is the average value. Similarly, the user perception rate z corresponding to each cell can be obtained at a time according to the above method.
And step 205, connecting the cells with the user perception rate being greater than or equal to a preset threshold value, and acquiring a user perception rate reference curve.
For example, when the user sensing rate corresponding to the cell 501 is greater than or equal to the preset threshold, it is described that when the SINR and the MCS corresponding to the cell satisfy the value ranges of the SINR and the MCS determined by the cell 501, the user sensing rate is good and meets the user requirement, and at this time, the value of the SINR and the MCS corresponding to the cell 501 may be used as a basis for adjusting the user sensing rate. As shown in fig. 6, since there are more cells on the plane of SINR and MCS, there are multiple cells with user perceived rate greater than or equal to the preset threshold, at this time, two adjacent cells along the X-axis direction may be connected by a straight line, so as to obtain a user perceived rate reference curve 601.
And step 206, when the user perception rate of the target cell is optimized, determining the SINR and MCS of the target cell according to the reference curve.
For example, in the process of optimizing the user sensing rate, the average MCS and SINR of the cell may be first queried, if the SINR value is lower, which indicates that the interference signal is too strong or the useful signal strength is insufficient, the interference may be reduced or the transmit power may be increased to raise the SINR value, when the SINR value cannot be raised any more, the MCS target value corresponding to the SINR is queried through the user sensing rate reference curve, and then the MCS of the target cell is adjusted to the MCS target value by adjusting the relevant parameters, so that the optimal user sensing rate of the target cell in the wireless environment may be obtained.
It should be noted that, the sequence of the steps of the network optimization method provided in the embodiment of the present invention may be appropriately adjusted, and the steps may also be increased or decreased according to the circumstances, and any method that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention shall be included in the protection scope of the present invention, and therefore, the details are not described again.
Compared with the prior art, the network optimization method provided by the embodiment of the invention can optimize the user perception rate through the SINR and MCS parameters, thereby avoiding the limitation generated when the user perception rate is optimized by adjusting a single parameter, improving the effectiveness of optimizing the user perception rate and further improving the user experience.
An embodiment of the present invention provides a network optimization apparatus 70, as shown in fig. 7, including:
the drawing unit 701 is configured to draw a three-dimensional surface graph of a three-dimensional function determined by the signal-to-noise ratio SINR, the modulation and coding coefficient MCS, and the user perception rate.
A first obtaining unit 702, configured to obtain a contour line plan of the three-dimensional surface map on a two-dimensional plane formed by the SINR and the MCS, where each point included in the contour line plan has a corresponding user perception rate.
An optimizing unit 703 is configured to optimize the user sensing rate of the target cell according to the SINR and the MCS corresponding to the area where the user sensing rate on the contour plane graph is greater than or equal to the preset threshold.
Therefore, the user perception rate can be optimized through the SINR and the MCS, so that limitation caused by adjusting a single parameter to optimize the user perception rate is avoided, the effectiveness of optimizing the user perception rate is improved, and further the user experience is improved.
Optionally, as shown in fig. 8, the apparatus 70 further includes:
a dividing unit 704, configured to divide the contour plane map into a plurality of cells according to a preset scale.
A second obtaining unit 705, configured to obtain a user perception rate of each cell.
The optimization unit 703 is specifically configured to: and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour plane graph.
Optionally, the second obtaining unit 705 is specifically configured to: acquiring user perception rates of a plurality of points in a first cell; calculating an average of the user perception rates of the plurality of points; and taking the average value as the user perception rate of the first cell.
Optionally, the optimization unit 703 is specifically configured to: acquiring a user perception rate reference curve according to the cells of which the user perception rate is greater than or equal to a preset threshold value on the contour line plane graph; and optimizing the user perception rate of the target cell according to the user perception rate reference curve.
Optionally, the optimization unit 703 is specifically configured to: sequentially connecting cells with user perception rates which are adjacent along a first direction and are larger than or equal to a preset threshold value, and acquiring a user perception rate reference curve; the first direction is a direction in which the SINR increases.
It should be noted that, for convenience and brevity of description, it may be clearly understood by those skilled in the art that the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Secondly, in practical applications, the drawing Unit 701, the first obtaining Unit 702, the optimizing Unit 703, the dividing Unit 704, and the second obtaining Unit 705 may be implemented by a Central Processing Unit (CPU), a microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like, which are located in the network optimizing device 70.
An embodiment of the present invention provides a network optimization apparatus, including: and the drawing unit is used for drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate. A first obtaining unit, configured to obtain a contour line plan of the three-dimensional surface map on a two-dimensional plane formed by the SINR and the MCS, where each point included in the contour line plan has a corresponding user perception rate. And the optimizing unit is used for optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the area, in which the user perception rate is greater than or equal to the preset threshold value, on the contour plane graph. Compared with the prior art, the user perception rate can be optimized through the SINR and MCS parameters, so that limitation caused by adjusting a single parameter to optimize the user perception rate is avoided, effectiveness of optimizing the user perception rate is improved, and user experience is improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (8)
1. A method for network optimization, comprising:
drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate;
obtaining a contour line plane graph of the three-dimensional surface graph on a two-dimensional plane formed by the SINR and the MCS, wherein each point included in the contour line plane graph has a corresponding user perception rate;
dividing the contour line plane graph into a plurality of cells according to preset scales;
acquiring the user perception rate of each cell;
and optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour plane graph.
2. The method of claim 1, wherein obtaining the user perceived rate for each cell comprises:
acquiring user perception rates of a plurality of points in a first cell;
calculating an average of the user perception rates of the plurality of points;
and taking the average value as the user perception rate of the first cell.
3. The method of claim 1, wherein the optimizing the user perceived rate of the target cell according to the SINR and MCS corresponding to the cell on the contour plane graph where the user perceived rate is greater than or equal to the preset threshold comprises:
acquiring a user perception rate reference curve according to the cells of which the user perception rate is greater than or equal to a preset threshold value on the contour line plane graph;
and optimizing the user perception rate of the target cell according to the user perception rate reference curve.
4. The method of claim 3, wherein the obtaining a user perception rate reference curve according to the cells on the contour plane graph, in which the user perception rate is greater than or equal to a preset threshold value, comprises:
sequentially connecting cells with user perception rates which are adjacent along a first direction and are larger than or equal to a preset threshold value, and acquiring a user perception rate reference curve; the first direction is a direction in which the SINR increases.
5. A network optimization apparatus, comprising:
the drawing unit is used for drawing a three-dimensional surface graph of a three-dimensional function determined by the signal to noise ratio SINR, the modulation and coding coefficient MCS and the user perception rate;
a first obtaining unit, configured to obtain a contour line plan of the three-dimensional surface map on a two-dimensional plane formed by the SINR and the MCS, where each point included in the contour line plan has a corresponding user perception rate;
the dividing unit is used for dividing the contour line plane graph into a plurality of cells according to preset scales;
the second acquisition unit is used for acquiring the user perception rate of each cell;
and the optimizing unit is used for optimizing the user perception rate of the target cell according to the SINR and the MCS corresponding to the cell with the user perception rate being greater than or equal to the preset threshold value on the contour plane graph.
6. The apparatus according to claim 5, wherein the second obtaining unit is specifically configured to:
acquiring user perception rates of a plurality of points in a first cell;
calculating an average of the user perception rates of the plurality of points;
and taking the average value as the user perception rate of the first cell.
7. The apparatus according to claim 6, wherein the optimization unit is specifically configured to:
acquiring a user perception rate reference curve according to the cells of which the user perception rate is greater than or equal to a preset threshold value on the contour line plane graph;
and optimizing the user perception rate of the target cell according to the user perception rate reference curve.
8. The apparatus according to claim 7, wherein the optimization unit is specifically configured to:
sequentially connecting cells with user perception rates which are adjacent along a first direction and are larger than or equal to a preset threshold value, and acquiring a user perception rate reference curve; the first direction is a direction in which the SINR increases.
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| CN102379135A (en) * | 2009-01-24 | 2012-03-14 | 华为技术有限公司 | Method and device for improving the management of wireless mesh networks |
| CN104200530A (en) * | 2014-09-22 | 2014-12-10 | 克拉玛依红有软件有限责任公司 | Painting method and system of contour line of spatial curved surface |
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| CN102131300A (en) * | 2009-07-06 | 2011-07-20 | 上海华为技术有限公司 | Queue scheduling method and device |
| CN104200530A (en) * | 2014-09-22 | 2014-12-10 | 克拉玛依红有软件有限责任公司 | Painting method and system of contour line of spatial curved surface |
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