CN108513311B - Cell power optimization method and device - Google Patents
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- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
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- H04W52/18—TPC being performed according to specific parameters
- H04W52/22—TPC being performed according to specific parameters taking into account previous information or commands
- H04W52/221—TPC being performed according to specific parameters taking into account previous information or commands using past power control commands
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Abstract
The application relates to the technical field of mobile communication, in particular to a cell power optimization method and a device, which are used for solving the problems of high labor cost and low optimization efficiency when cell transmitting power is optimized in the prior art; the cell power optimization method provided by the embodiment of the application comprises the following steps: determining a plurality of cells to be optimized according to the received cell power optimization instruction; determining the benefit of each cell to be optimized in different power adjustment directions according to the power of the cells to be optimized before optimization; the power adjustment direction comprises a power increase and a power decrease; judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains; if the maximum gain exists, determining a power adjustment direction corresponding to the maximum gain according to the maximum gain corresponding to the cells to be optimized; and adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction until the benefit corresponding to the cell to be optimized is zero, and returning to the judging step.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a cell power optimization method and apparatus.
Background
In the field of communication technology, in the process of optimizing the performance of a cell, it may be necessary to optimize the transmission power of the cell due to road testing, complaint handling, interference handling, and the like.
In the prior art, when the transmission power of a cell is optimized, the optimization range and the optimization amplitude of the transmission power depend on the experience of optimization personnel seriously. For example, a weak coverage area appears in the coverage area of a certain base station, and the transmission power of the base station generally needs to be increased in order to improve the signal coverage of the weak coverage area, but the transmission power can be optimized to some extent so as to improve the signal coverage of the weak coverage area, and the mode-triplet interference between adjacent base stations is not caused but cannot be predicted. Moreover, after optimizing the transmitting power of the base station according to experience, an optimizer needs to perform a test on site, and if the test result does not meet the requirement, the optimization and the test of the power of the cell need to be continued, which wastes time and labor.
Therefore, the problems of high labor cost and low optimization efficiency exist when the transmission power of the cell is optimized in the prior art.
Disclosure of Invention
The embodiment of the application provides a cell power optimization method and device, which are used for solving the problems of high labor cost and low optimization efficiency in the prior art when the transmitting power of a cell is optimized.
The cell power optimization method provided by the embodiment of the application comprises the following steps:
determining a plurality of cells to be optimized according to the received cell power optimization instruction;
according to the power of the cells to be optimized before optimization, determining the benefit of each cell to be optimized in different power adjustment directions; the power adjustment direction comprises a power increase and a power decrease;
judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains;
if the maximum gain exists, determining a power adjustment direction corresponding to the maximum gain according to the maximum gain corresponding to the cells to be optimized;
and adjusting the power of the cell to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cell to be optimized is zero, and returning to judge whether the cell with the corresponding profit being not zero exists in the cells to be optimized.
The cell power optimization device provided in the embodiment of the present application includes:
the cell determining module is used for determining a plurality of cells to be optimized according to the received cell power optimization instruction;
the profit determining module is used for determining the profit of each cell to be optimized in different power adjusting directions according to the power of the cells to be optimized before optimization; the power adjustment direction comprises a power increase and a power decrease;
the processing module is used for judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains; if the maximum profit is zero, determining a power adjustment direction corresponding to the maximum profit according to the maximum profit corresponding to the plurality of cells to be optimized, and adjusting the power of the cells to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cells to be optimized is zero; and returning to judge whether the corresponding cells with non-zero income exist in the plurality of cells to be optimized.
In the embodiment of the application, for each cell to be optimized in a plurality of cells to be optimized, the power of the cell to be optimized is adjusted according to two adjustment directions of power increase and power decrease, then the gains of the cell to be optimized are respectively determined in the two power adjustment directions, so as to obtain the two-way gains of each cell to be optimized, then whether a cell with a non-zero gain exists in the plurality of cells to be optimized is judged, if so, the power adjustment direction corresponding to the maximum gain is determined, the power of the cell to be optimized corresponding to the maximum gain is continuously adjusted according to the power adjustment direction until the gain of the cell to be optimized becomes zero, and the gain of the cell to be optimized is zero, which indicates that the power adjustment of the cell to be optimized has not improved the network performance of the plurality of cells to be optimized and has no reduction on the network performance of peripheral cells, and then returning to judge whether the corresponding cells with non-zero income exist in the plurality of cells to be optimized. When the gains of all the cells to be optimized are zero, the optimized power of each cell to be optimized is shown to enable the network performance indexes of the cells to be optimized to reach preset values, and the influence on the network performance of the surrounding cells is within a preset range, so that the optimized power of each cell to be optimized can be automatically determined according to set network performance parameters, manual repeated adjustment and testing are not needed, the labor cost can be saved, and the optimization efficiency is high.
Drawings
Fig. 1 is a flowchart of a cell power optimization method according to an embodiment of the present disclosure;
fig. 2 is a power flow chart of a cell to be optimized corresponding to adjusting a maximum gain according to the embodiment of the present application;
fig. 3 is a schematic diagram of a map rasterization division result provided in the embodiment of the present application;
fig. 4 is a schematic diagram of cells in an area to be optimized and a protection area according to an embodiment of the present application;
fig. 5 is a flowchart for determining optimized powers of a plurality of cells to be optimized according to an embodiment of the present application;
fig. 6 is a structural diagram of a cell power optimization apparatus according to an embodiment of the present application.
Detailed Description
In the embodiment of the application, for each cell to be optimized in a plurality of cells to be optimized, the power of the cell to be optimized is adjusted according to two adjustment directions of power increase and power decrease, then the gains of the cell to be optimized are respectively determined in the two power adjustment directions, so as to obtain the two-way gains of each cell to be optimized, then whether a cell with a non-zero gain exists in the plurality of cells to be optimized is judged, if so, the power adjustment direction corresponding to the maximum gain is determined, the power of the cell to be optimized corresponding to the maximum gain is continuously adjusted according to the power adjustment direction until the gain of the cell to be optimized becomes zero, and the gain of the cell to be optimized is zero, which indicates that the power adjustment of the cell to be optimized has not improved the network performance of the plurality of cells to be optimized and has no reduction on the network performance of peripheral cells, and then returning to judge whether the corresponding cells with non-zero income exist in the plurality of cells to be optimized. When the gains of all the cells to be optimized are zero, the optimized power of each cell to be optimized is shown to enable the network performance indexes of the cells to be optimized to reach preset values, and the influence on the network performance of the surrounding cells is within a preset range, so that the optimized power of each cell to be optimized can be automatically determined according to set network performance parameters, manual repeated adjustment and testing are not needed, the labor cost can be saved, and the optimization efficiency is high.
The embodiments of the present application will be described in further detail with reference to the drawings attached hereto.
Example one
As shown in fig. 1, a flowchart of a cell power optimization method provided in the embodiment of the present application includes the following steps:
s101: and determining a plurality of cells to be optimized according to the received cell power optimization instruction.
Here, the antennas in the area to be optimized may be determined according to the area to be optimized indicated in the cell power optimization instruction, and then the cells within the coverage area (for example, 500 meters) of these antennas are determined as the cells to be optimized, and the total influence range of these antennas may also be determined as a given area, which is a protection area except for the area to be optimized. The area to be optimized may be framed by a user through a GIS (Geographic Information System) interface, or may be determined by latitude, longitude and range input by the user.
S102: according to the power of a plurality of cells to be optimized before optimization, determining the benefit of each cell to be optimized in different power adjustment directions; wherein the power adjustment direction includes a power increase and a power decrease.
In a specific implementation process, the given area can be subjected to three-dimensional grid division by using a high-precision three-dimensional map, and the division granularity can be 1 meter, 5 meters, 20 meters and the like. After the power of a cell to be optimized is adjusted, the field intensity of each grid in a given area is changed, the field intensity change conditions of all grids in the given area are counted, indexes reflecting the network performance of the given area can be obtained, and then an optimization function is determined according to the indexes. The following optimization functions are more commonly used in practice:
In the above optimization function:
x＝(p1,…,pN) The decision variable is composed of the power of each cell to be optimized (N are assumed); p is a radical ofiAnd i is more than or equal to 1 and less than or equal to N for the power of the ith cell to be optimized.
M is the total number of grids in a given area;
Mweak(x) When the decision variable value is x, the weak coverage grid number of the given area is represented; the weak coverage grid refers to a grid of which the main control field intensity is smaller than a preset threshold in the field intensity prediction result of the grid;
Mbound(x) When the decision variable value is x, the cell boundary grid number of a given area is represented; the cell boundary grid refers to a grid in the field strength prediction result of the grid, which is different from the master control cell of at least one grid of the adjacent grid.
Further, when power optimization is performed on cells to be optimized in a given area, in order to enable the network performance of the cells to be optimized to reach a preset value, and to influence the network performance of cells around the cells to be optimized (cells excluding the cells to be optimized in the given area) within a preset range, the following constraint conditions are mainly considered:
(1)fk(x)≤fk(x0) K is 1, 2.. K, the constraint condition indicates that the value of the optimization function after power adjustment of any cell to be optimized does not become larger in the protection region, so that the grid statistical result of the protection region can be ensured not to be degraded, wherein f isk(x) Expressing the kth optimization function, wherein K is the total number of the optimization functions; x is the number of0The initial value of the decision variable is composed of the power of each cell to be optimized before optimization.
(2) X belongs to X, the constraint condition represents a feasible solution value range of the decision variable X, for example, the power adjustment amplitude of each cell to be optimized is 0.1dB, and the power adjustment upper limit of different cells to be optimized can be different.
Further, considering the constraint conditions of the optimization functions and the optimization functions comprehensively, an objective function f (x) for characterizing the multiple cells to be optimized and the comprehensive network performance index of the cells around the multiple cells to be optimized can be determined according to the following formula:
wherein,
wherein wkFor the k-th optimization function fk(x) The weight of (2) can be selected according to actual needs; p is a penalty factor when wkWhen the predetermined range is 0 to 10, P may beTo get 104(ii) a When w iskWhen the predetermined range is 0 to 1, P may be 105。
Further, according to the power of a plurality of cells to be optimized before optimization, determining an initial value of a target function, then adjusting the power of each cell to be optimized in any power adjustment direction of each cell to be optimized in the cells to be optimized according to a preset power adjustment amplitude; determining an adjustment value of an objective function based on the adjusted power of the cell to be optimized and the powers of other cells to be optimized except the cell to be optimized in the plurality of cells to be optimized before optimization; if the adjustment value of the objective function is larger than or equal to the initial value, determining that the benefit of the cell to be optimized is zero; and if the adjustment value of the objective function is smaller than the initial value, determining that the benefit of the cell to be optimized is equal to the value obtained by subtracting the adjustment value from the initial value.
S103: and judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains, if so, entering S104, otherwise, finishing the optimization.
S104: and determining a power adjustment direction corresponding to the maximum profit according to the maximum profit corresponding to the cells to be optimized.
S105: and adjusting the power of the cell to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cell to be optimized is zero, and returning to judge whether the cell with the corresponding profit being not zero exists in the cells to be optimized.
In the specific implementation process, the power of the cell to be optimized corresponding to the maximum benefit is adjusted until the benefit corresponding to the cell to be optimized is zero, which is shown in fig. 2:
s201 a: and adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction and the preset power adjustment amplitude.
For example, if the power adjustment direction is power increase, the power of the cell to be optimized corresponding to the maximum benefit is continuously increased.
S202 a: judging whether the adjusted power of the cell to be optimized is within the adjustable threshold range of the cell to be optimized, if so, entering S203 a; otherwise, the process proceeds to S205 a.
S203 a: and re-determining the benefit of the cell to be optimized based on the adjusted power of the cell to be optimized, the power of the cell to be optimized which is not subjected to power optimization and is not optimized in the plurality of cells to be optimized, and the optimized power of the cell to be optimized which is subjected to power optimization.
S204 a: and judging whether the redetermined gain is greater than zero, if so, returning to S201a to continue adjusting the power of the cell to be optimized, and otherwise, entering S205 a.
S205 a: and setting the corresponding gain of the cell to be optimized to be zero.
Example two
The method of the embodiment of the application is roughly divided into: preparing basic data, rasterizing a three-dimensional map, selecting an area to be optimized, determining a cell to be optimized, determining an optimization target and constraint conditions, running an optimization solving algorithm, and giving a power adjustment scheme according to an optimization algorithm result, wherein specific implementation modes of all the steps are described below.
Optionally, the prepared basic data includes:
(1) high-precision three-dimensional electronic map.
(2) And current network engineering parameter data, such as the power of each cell to be optimized before power optimization.
(3) And a grid-level MR (Measurement Report) data positioning result for determining the field intensity of each grid in the given area.
Here, the given region may be subjected to rasterization division of a × a, the division direction being parallel to the preset coordinate axis. The size of a can be determined according to actual requirements and the precision of the original three-dimensional map, such as 1 meter, 5 meters, 20 meters, and the like.
As shown in fig. 3, taking a building with a height of 35 meters and a size of 200m × 200m per floor as an example, the building is divided into 7 floors according to 5m floors, each floor is divided into 1600 planar grids of 5m × 5m, and then the whole building can be divided into 11200 three-dimensional grids of 5m × 5 m.
Optionally, the user may frame or input latitude, longitude and latitude and a range through a GIS interface to select an area to be optimized, where the area to be optimized may be a rectangle or any polygon, and then determine a cell to be optimized and a protection area according to the area to be optimized.
As shown in fig. 4, assuming that the middle rectangular dotted area represents an area to be optimized selected by a user, determining antennas included in the area to be optimized, determining cells in the coverage area (white rectangular area) of the antennas as cells to be optimized, assuming that arrows in the figure indicate the cells, solid cells are the cells to be optimized, determining the influence ranges (grid rectangular areas) of all the antennas, wherein the white rectangular area and the grid rectangular area are protection areas, and the whole area shown in fig. 4 is a given area. When optimizing the area to be optimized selected by the user, it is necessary to ensure that the network performance in the protection area is not deteriorated or within a preset range.
Further, optimization objectives and constraints are determined.
In the specific implementation process, after the power of a cell to be optimized is adjusted, the field intensity of each grid in a given area is changed, the field intensity of each grid in the given area is calculated to obtain some network performance indexes of the grid, all grids in the given area are counted, then the indexes reflecting the network performance of the given area can be obtained, and an optimization function can be given according to the indexes. The optimization function that is more commonly used in practice is as follows:
Constraint conditions are as follows:
(1)fk(x)≤fk(x0),k＝1,2,...K；
(2)x∈X。
the meaning and value of each parameter in the above optimization function and constraint condition are the same as those in the first embodiment, and are not described herein again.
The following describes a process of operating an optimization algorithm to solve the optimized power of each cell to be optimized.
Firstly, all optimization functions are weighted and summed to obtain:
wherein, wkFor the k-th optimization function fk(x) The weight of (c) can be determined according to the actual optimization objective. Taking the above 3 optimization functions as an example, if the optimization objective is mainly to reduce the overlapping coverage, then w may be made1＝0.1，w2＝1，w30.1; if the optimization goal is to consider both weak coverage and overlapping coverage, and not coverage continuity, then we can let w be1＝1，w2＝1，w3＝0。
Second, for constraint fk(x)≤fk(x0) K, the constraint may be placed into the objective function using a penalty function method to obtain an objective function f (x):
Where weak coverage and boundary grid scale are both numbers less than 1 and average overlap coverage is a number less than 10, each optimization function characterizing network performance may be given a corresponding reduction by dividing by a set value when w iskWhen the value is 0 to 1, P may be 105。
Taking the above three objective functions as an example, take w1＝w2＝w3＝1，P＝105And then:
thus, only the adjustment of the decision variable x limits this constraint, and the solution can be performed according to the flow shown in fig. 5.
S501: and determining an initial value of the objective function according to the power of each cell to be optimized before optimization.
Here, it is assumed that there are 3 cells to be optimized, and the powers of the 3 cells to be optimized before optimization are p1＝12.2，p2＝15.2，p3The optimization function is 9.2:
and
and w1＝w2＝w3＝1，P＝105. Assume at the beginning, f1(x0)＝0.2，f2(x0)＝6.5，f3(x0) When f is equal to 0.351(x)-f1(x0)、f2(x)-f2(x0) And f3(x)-f3(x0) All equal to 0, then the initial value of F (x) is:
F(x0)＝F(12.2,15.2,9.2)＝0.2+6.5+0.35＝7.05。
s502: and for each cell to be optimized in the plurality of cells to be optimized, determining the benefit of the cell to be optimized in different power adjustment directions.
Here, the adjustment of the power of each cell to be optimized includes an increase adjustment and a decrease adjustment. The following description will be made by taking the enlargement adjustment as an example.
For any cell to be optimized in a plurality of cells to be optimized, increasing the power of the cell to be optimized before optimization by a preset power adjustment amplitude, and if the power of the cell to be optimized is increased and is not within the adjustable threshold range of the cell to be optimized, setting the benefit of the cell to be optimized to be zero; otherwise, calculating new F (x) according to the increased power of the cell to be optimized and the power of other cells to be optimized before optimization.
E.g. p in the above example1P after 0.1 increase of 12.2112.3, if 12.3 is not in p1The adjustable threshold range of the corresponding cell to be optimized is (3, 12.2), then the increase p is not considered1The adjustment direction of (3); otherwise, the value of adjusted F (x) is calculated. Suppose for p in the above example1、p2、p3The values of f (x) obtained at different adjustment directions are shown in table 1:
table 1:
| power augmentation | 6.9 | 1625.5 | 7.03 |
| Power of | P1 | P2 | P3 |
| Power reduction | 7 | 6.98 |
Wherein, the first row represents the value of F (x) after the power of each cell to be optimized is increased by the minimum adjustment amplitude before optimization, the third row represents the value of F (x) after the power of each cell to be optimized is decreased by the minimum adjustment amplitude before optimization, and gray gridsSub-representation of p3Adjusted to be not in p3And the adjustable threshold range of the corresponding cell to be optimized. For p2The large value of f (x) after increasing the minimum adjustment amplitude is due to the increased value of the objective function of the protection zone after adjustment, which makes the value of f (x) large by the penalty factor.
In the specific implementation process, for each cell to be optimized, if the power of the cell to be optimized is not within the adjustable threshold range of the cell to be optimized after being adjusted or the value of f (x) after being adjusted is increased, the benefit of the cell to be optimized is 0; otherwise, the yield of the cell to be optimized is equal to the value of F (x) before adjustment minus the value of F (x) after adjustment. For the adjustment results in table 1, the gains for each cell to be optimized are shown in table 2:
table 2:
| power augmentation | 0.15 | 0 | 0.02 |
| Power of | P1 | P2 | P3 |
| Power reduction | 0.05 | 0.07 | 0 |
S503: and judging whether a cell to be optimized with the income greater than zero exists, if so, entering S504, and if not, finishing the optimization.
S504: and determining the cell to be optimized and the power adjustment direction corresponding to the maximum benefit.
For example, the results of the revenue calculation in Table 2, p1The corresponding cell to be optimized is the cell to be optimized corresponding to the maximum gain of 0.15, and when the maximum gain of 0.15 is obtained, the power adjustment direction of the cell to be optimized is power increase.
S505: and continuing to adjust the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction, and re-determining the benefit of the cell to be optimized.
Here, when the benefit of the cell to be optimized is re-determined, for any other cell to be optimized among the cells to be optimized except the cell to be optimized, if the cell to be optimized has completed the power optimization, the power of the cell to be optimized after the optimization is used, otherwise, the power of the cell to be optimized before the optimization is used.
S506: and judging whether the yield of the cell to be optimized with the maximum redetermined yield is greater than zero, if so, entering S505, and otherwise, entering S503.
Table 3: and optimizing a certain area to be optimized by using the method.
Table 4 shows the optimization results of the cell to be optimized.
Based on the same inventive concept, the embodiment of the present application further provides a cell power optimization apparatus corresponding to the cell power optimization method, and as the principle of the apparatus for solving the problem is similar to the cell power optimization method in the embodiment of the present application, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not repeated.
As shown in fig. 6, a structure diagram of a cell power optimization apparatus 60 provided in the embodiment of the present application includes:
a cell determining module 601, configured to determine multiple cells to be optimized according to a received cell power optimization instruction;
a benefit determining module 602, configured to determine, according to power of multiple cells to be optimized before optimization, a benefit of each cell to be optimized in a different power adjustment direction; wherein the power adjustment direction comprises a power increase and a power decrease;
a processing module 603, configured to determine whether there is a cell with a non-zero corresponding benefit in the multiple cells to be optimized; if the maximum profit is zero, determining a power adjustment direction corresponding to the maximum profit according to the maximum profit corresponding to the cells to be optimized, and adjusting the power of the cells to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cells to be optimized is zero; and returning to judge whether the corresponding yield is not zero in the plurality of cells to be optimized.
Optionally, the cell determining module 601 is specifically configured to:
determining an antenna in the area to be optimized according to the area to be optimized indicated in the cell power optimization instruction;
and determining the cell in the coverage area of the antenna as the cell to be optimized.
Optionally, the benefit determination module 602 is specifically configured to:
determining an initial value of an objective function according to the power of a plurality of cells to be optimized before optimization; the objective function is used for representing the comprehensive network performance indexes of a plurality of cells to be optimized and the cells around the cells to be optimized;
adjusting the power of each cell to be optimized according to a preset power adjustment range in any power adjustment direction of each cell to be optimized in the cells to be optimized;
determining an adjustment value of an objective function based on the adjusted power of the cell to be optimized and the powers of other cells to be optimized except the cell to be optimized in the plurality of cells to be optimized before optimization;
and determining the benefit of the cell to be optimized according to the adjustment value and the initial value of the objective function.
Optionally, the profit determination module 602 is specifically configured to include:
if the adjustment value of the objective function is larger than or equal to the initial value, determining that the benefit of the cell to be optimized is zero;
and if the adjustment value of the objective function is smaller than the initial value, determining that the benefit of the cell to be optimized is equal to the value obtained by subtracting the adjustment value from the initial value.
Optionally, the processing module 603 is specifically configured to:
adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction and the preset power adjustment amplitude;
if the adjusted power of the cell to be optimized is not within the adjustable threshold range of the cell to be optimized, setting the gain corresponding to the cell to be optimized to be zero;
otherwise, determining the benefit of the cell to be optimized based on the adjusted power of the cell to be optimized, the power of the cell to be optimized which is not subjected to power optimization in the plurality of cells to be optimized before optimization and the power of the cell to be optimized which is subjected to power optimization;
if the determined benefit is larger than zero, returning to adjust the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction and the preset power adjustment amplitude; otherwise, setting the corresponding gain of the cell to be optimized to be zero.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. 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.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (8)
1. A method for optimizing cell power, the method comprising:
determining a plurality of cells to be optimized according to the received cell power optimization instruction;
according to the power of the cells to be optimized before optimization, determining the benefit of each cell to be optimized in different power adjustment directions; the power adjustment direction comprises a power increase and a power decrease;
judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains;
if the maximum gain exists, determining a power adjustment direction corresponding to the maximum gain according to the maximum gain corresponding to the cells to be optimized;
adjusting the power of the cell to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cell to be optimized is zero, and returning to judge whether the cell with non-zero corresponding profit exists in the cells to be optimized;
the determining the gains of each cell to be optimized in different power adjustment directions according to the powers of the cells to be optimized before optimization includes:
determining an initial value of an objective function according to the power of the cells to be optimized before optimization; the objective function is used for representing the comprehensive network performance indexes of the cells to be optimized and the cells around the cells to be optimized;
adjusting the power of each cell to be optimized according to a preset power adjustment range in any power adjustment direction of each cell to be optimized;
determining an adjustment value of the objective function based on the adjusted power of the cell to be optimized and the powers of other cells to be optimized except the cell to be optimized in the plurality of cells to be optimized before optimization;
and determining the benefit of the cell to be optimized according to the adjustment value and the initial value of the objective function.
2. The method of claim 1, wherein determining a plurality of cells to be optimized based on the received cell power optimization commands comprises:
determining an antenna in the area to be optimized according to the area to be optimized indicated in the cell power optimization instruction;
and determining the cell in the antenna coverage range as the cell to be optimized.
3. The method of claim 1, wherein determining the benefit of the cell to be optimized based on the adjusted value and the initial value of the objective function comprises:
if the adjustment value of the objective function is larger than or equal to the initial value, determining that the benefit of the cell to be optimized is zero;
and if the adjustment value of the objective function is smaller than the initial value, determining that the benefit of the cell to be optimized is equal to the value obtained by subtracting the adjustment value from the initial value.
4. The method of claim 1, wherein the adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction until the benefit corresponding to the cell to be optimized is zero comprises:
adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction and a preset power adjustment amplitude;
if the adjusted power of the cell to be optimized is not within the adjustable threshold range of the cell to be optimized, setting the gain corresponding to the cell to be optimized to be zero;
otherwise, determining the benefit of the cell to be optimized based on the adjusted power of the cell to be optimized, the power of the cell to be optimized which is not subjected to power optimization and is not optimized in the plurality of cells to be optimized, and the power of the cell to be optimized which is subjected to power optimization and is optimized;
if the determined gain is larger than zero, returning to adjust the power of the cell to be optimized corresponding to the maximum gain according to the determined power adjustment direction and the preset power adjustment amplitude; otherwise, setting the corresponding gain of the cell to be optimized to be zero.
5. An apparatus for cell power optimization, the apparatus comprising:
the cell determining module is used for determining a plurality of cells to be optimized according to the received cell power optimization instruction;
the profit determining module is used for determining the profit of each cell to be optimized in different power adjusting directions according to the power of the cells to be optimized before optimization; the power adjustment direction comprises a power increase and a power decrease;
the processing module is used for judging whether a plurality of cells to be optimized have cells with non-zero corresponding gains; if the maximum profit is zero, determining a power adjustment direction corresponding to the maximum profit according to the maximum profit corresponding to the plurality of cells to be optimized, and adjusting the power of the cells to be optimized corresponding to the maximum profit according to the determined power adjustment direction until the profit corresponding to the cells to be optimized is zero; returning and judging whether the cells with the corresponding non-zero income exist in the plurality of cells to be optimized;
the revenue determination module is specifically configured to:
determining an initial value of an objective function according to the power of the cells to be optimized before optimization; the objective function is used for representing the comprehensive network performance indexes of the cells to be optimized and the cells around the cells to be optimized;
adjusting the power of each cell to be optimized according to a preset power adjustment range in any power adjustment direction of each cell to be optimized;
determining an adjustment value of the objective function based on the adjusted power of the cell to be optimized and the powers of other cells to be optimized except the cell to be optimized in the plurality of cells to be optimized before optimization;
and determining the benefit of the cell to be optimized according to the adjustment value and the initial value of the objective function.
6. The apparatus of claim 5, wherein the cell determination module is specifically configured to:
determining an antenna in the area to be optimized according to the area to be optimized indicated in the cell power optimization instruction;
and determining the cell in the antenna coverage range as the cell to be optimized.
7. The apparatus of claim 5, wherein the revenue determination module is specifically configured to include:
if the adjustment value of the objective function is larger than or equal to the initial value, determining that the benefit of the cell to be optimized is zero;
and if the adjustment value of the objective function is smaller than the initial value, determining that the benefit of the cell to be optimized is equal to the value obtained by subtracting the adjustment value from the initial value.
8. The apparatus of claim 5, wherein the processing module is specifically configured to:
adjusting the power of the cell to be optimized corresponding to the maximum benefit according to the determined power adjustment direction and a preset power adjustment amplitude;
if the adjusted power of the cell to be optimized is not within the adjustable threshold range of the cell to be optimized, setting the gain corresponding to the cell to be optimized to be zero;
otherwise, determining the benefit of the cell to be optimized based on the adjusted power of the cell to be optimized, the power of the cell to be optimized which is not subjected to power optimization and is not optimized in the plurality of cells to be optimized, and the power of the cell to be optimized which is subjected to power optimization and is optimized;
if the determined gain is larger than zero, returning to adjust the power of the cell to be optimized corresponding to the maximum gain according to the determined power adjustment direction and the preset power adjustment amplitude; otherwise, setting the corresponding gain of the cell to be optimized to be zero.
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| CN104053222A (en) * | 2013-03-14 | 2014-09-17 | 电信科学技术研究院 | Base station transmitting power adjusting method and apparatus |
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| CN105025562A (en) * | 2014-04-30 | 2015-11-04 | 中国电信股份有限公司 | Method, device and system for adjusting transmitting power of cell |
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| US8526957B2 (en) * | 2009-08-18 | 2013-09-03 | Nokia Siemens Networks Oy | De-centralized transmit power optimization |
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| CN104053222A (en) * | 2013-03-14 | 2014-09-17 | 电信科学技术研究院 | Base station transmitting power adjusting method and apparatus |
| CN104219693A (en) * | 2013-05-30 | 2014-12-17 | 中国电信股份有限公司 | Network optimization method and device based on base station parameters and base station |
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