CN108064051B

CN108064051B - Method, device and equipment for determining network radio frequency optimization scheme

Info

Publication number: CN108064051B
Application number: CN201610977127.8A
Authority: CN
Inventors: 潘星辰; 荣锋江; 刘淑祎; 安永红; 姚科春; 李蓓; 李晖; 张雅芳; 郝春霞
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Group Hebei Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Group Hebei Co Ltd
Priority date: 2016-11-07
Filing date: 2016-11-07
Publication date: 2021-08-06
Anticipated expiration: 2036-11-07
Also published as: CN108064051A

Abstract

The invention discloses a method, a device and equipment for determining a network radio frequency optimization scheme, which are used for the technical field of communication and can effectively improve the network quality and reduce the resource consumption. The method comprises the following steps: constructing a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item; constructing a network quality evaluation function based on a first proportion of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second proportion of an area where the reference signal received quality reaches a second predetermined threshold; and calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item which represents the radio frequency optimization scheme that the value of the network quality evaluation function is greater than the network quality threshold and the value of the resource consumption function is minimum after the target radio frequency optimization scheme is adopted.

Description

Method, device and equipment for determining network radio frequency optimization scheme

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method, an apparatus, and a device for determining a network radio frequency optimization scheme.

Background

With the development of the mobile internet technology, the network scale of the mobile internet is getting larger and larger, how to ensure the network quality becomes a main problem for mobile network operators, and the mobile internet often has a problem that the network quality is reduced due to improper base station location, improper antenna selection, improper antenna parameter setting and the like, and at this time, the network quality needs to be improved in a network optimization mode. In an LTE (Long Term Evolution) network, since the network is a single-frequency network, frequency optimization is not involved in network optimization, the network structure is optimized as a basis and a core of the LTE network optimization, the main means of the network structure optimization is radio frequency optimization, including adjustment of various optimization parameters such as antenna azimuth angle adjustment, mechanical downtilt adjustment, electronic downtilt adjustment, antenna type replacement, and transmission power adjustment, and the adjustment parameters of different radio frequency optimizations are adopted, and consumed resources have great differences. Because the existing mobile internet usually has a 2G network, a 3G network and an LTE network coexisting, and the three networks usually interfere with each other and affect each other, when the LTE network is optimized as a whole, engineers often need to select the above optimized adjustment parameters through experience to combine to form a radio frequency optimization scheme to optimize the network, which inevitably invests a lot of labor and time and consumes a lot of resources.

In order to reduce the resource consumption during the radio frequency optimization, the conventional radio frequency optimization usually reduces the number of radio frequency optimization parameter adjustments involved in the radio frequency optimization scheme, that is, abandons the adjustment of parameters which have less influence on the optimization target or are secondary parameters, and reduces the resource consumption of the radio frequency optimization. Although the traditional radio frequency optimization method can reduce the consumption of resources, the radio frequency optimization effect is correspondingly reduced, so that the improvement degree of the network structure performance is reduced, and the network quality cannot achieve the expected effect.

Disclosure of Invention

The embodiment of the invention provides a method, a device and equipment for determining a network radio frequency optimization scheme, which can reduce the resource consumption of radio frequency optimization while ensuring the effect of radio frequency optimization.

In a first aspect, a method for determining a network radio frequency optimization scheme according to an embodiment of the present invention includes: constructing a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item; constructing a network quality evaluation function based on a first proportion of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second proportion of an area where the reference signal received quality reaches a second predetermined threshold; and calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents the radio frequency optimization scheme which has the network quality evaluation function value larger than the network quality threshold and the resource consumption function value minimum after being adopted.

With reference to the first aspect, in a first implementation manner of the first aspect, before constructing the network quality assessment function based on a first proportion of an area where reference signal received power reaches a first predetermined threshold and a second proportion of an area where reference signal received quality reaches a second predetermined threshold in the target network, the method further includes:

setting a first weight value corresponding to the first proportion and a second weight value corresponding to the second proportion;

the process of constructing the network quality assessment function based on a first proportion of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second proportion of an area where the reference signal received quality reaches a second predetermined threshold includes:

and constructing a network quality evaluation function based on the first proportion, the second proportion, the first weight value and the second weight value.

With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the network quality evaluation function includes:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x)，

wherein x represents a radio frequency optimization scheme, f_{RS_RSRP}(x) Denotes the first ratio after execution of the x radio frequency optimization scheme, f_{RS_RSRQ}(x) Indicating a second ratio after the x-ray optimization is performed, L1 indicating a first weight value,l2 denotes a second weight value.

With reference to the first aspect, in a third implementation manner of the first aspect, before the process of constructing the resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item, the method further includes:

and setting the average resource consumption corresponding to the radio frequency optimization parameter items in the target network.

With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the radio frequency optimization parameter item includes at least one of the following items: the number of mechanical downward inclination angles of the antenna, the number of electronic downward inclination angles of the antenna, the number of azimuth angles of the antenna, the number of types of the antenna and the number of transmitting power of the antenna.

With reference to the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the resource consumption function includes: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E，

Wherein x represents a radio frequency optimization scheme, K1 represents the number of mechanical downtilts of antennas adjusted when the x radio frequency optimization scheme is executed, K2 represents the number of electronic downtilts of antennas adjusted when the x radio frequency optimization scheme is executed, K3 represents the number of azimuth angles of antennas adjusted when the x radio frequency optimization scheme is executed, K4 represents the number of types of antennas adjusted when the x radio frequency optimization scheme is executed, K5 represents the number of antenna transmission power adjustments when the x radio frequency optimization scheme is executed, a represents the average resource consumption degree of adjusting the mechanical downtilts of antennas in a target network, B represents the average resource consumption degree of adjusting the electronic downtilts of antennas in the target network, C represents the average resource consumption degree of adjusting the azimuth angles of antennas in the target network, D represents the average resource consumption degree of adjusting the types of antennas in the target network, and E represents the average resource consumption degree of antenna transmission power adjustment in the target network.

With reference to the fourth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the radio frequency optimization parameter item further includes the number of times that the base station needs to be reached and/or the number of base station towers that need to be climbed.

Sixth implementation manner combined with the first aspectIn a seventh implementation form of the first aspect, the resource cost function includes: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E+K6×F+K7×G，

Wherein x represents a radio frequency optimization scheme, K1 represents the number of mechanical downtilts of antennas adjusted when executing the x radio frequency optimization scheme, K2 represents the number of electronic downtilts of antennas adjusted when executing the x radio frequency optimization scheme, K3 represents the number of azimuth angles of antennas adjusted when executing the x radio frequency optimization scheme, K4 represents the number of types of antennas adjusted when executing the x radio frequency optimization scheme, K5 represents the number of antenna transmission power adjustments when executing the x radio frequency optimization scheme, K6 represents the number of times of reaching a base station when executing the x radio frequency optimization scheme, K7 represents the number of towers of base stations that need climbing when executing the x radio frequency optimization scheme, a represents the average resource consumption degree of antenna mechanical downtilts adjusted in a target network, B represents the average resource consumption degree of antenna electronic downtilts adjusted in the target network, and C represents the average resource consumption degree of antenna azimuth angles adjusted in the target network, d represents the average resource consumption of the antenna type in the target network, E represents the average resource consumption of the antenna transmitting power adjustment in the target network, F represents the average resource consumption of the base station in the target network, and G represents the average resource consumption of the base station tower climbing in the target network.

With reference to the first aspect, in an eighth implementation manner of the first aspect, before the process of constructing the network quality assessment function based on a first proportion of an area where the reference signal received power reaches a first predetermined threshold and a second proportion of an area where the reference signal received quality reaches a second predetermined threshold in the target network, the method further includes:

dividing a network area of a target network;

calculating the proportion of the network area with the maximum value of the reference signal received power larger than a first preset threshold value in all the network areas as a first proportion;

and calculating the proportion of the network area with the maximum value of the reference signal received quality larger than a second preset threshold value to all the network areas as a second proportion.

With reference to the eighth implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the processing for performing network area division on the target network includes:

and dividing the network area based on the number of the base stations in the target network and/or the distribution condition of the base stations.

With reference to the first aspect, in a tenth implementation manner of the first aspect, before the processing of calculating the target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource cost function, the method further includes:

setting an initial value of i to 0, i representing the number of times the following step A, B, C, D, E, F is performed;

the processing of calculating the target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function comprises the following steps:

randomly generating an initial scheme group based on adjustment parameters corresponding to radio frequency optimization modes adopted by all cells in a network, wherein the initial scheme group comprises a preset number of radio frequency optimization schemes;

A. respectively calculating network quality evaluation function values of all radio frequency optimization schemes in the initial scheme group;

B. incrementing the value of i by 1;

C. judging that the value of i reaches a preset value;

D. when the value of i does not reach a preset value, determining the fitness proportion of each radio frequency optimization scheme in the initial scheme group based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

E. generating a new scheme group based on the fitness proportion of each radio frequency optimization scheme in the initial scheme group, wherein the new scheme group comprises a preset number of radio frequency optimization schemes;

F. adjusting the adjustment parameters in each radio frequency optimization scheme in the new scheme group to generate a variation scheme group, taking the variation scheme group as an initial scheme group, and executing step A, B, C, D, E, F;

when the value of i reaches a preset value, determining a undetermined radio frequency optimization scheme with a network quality evaluation function value larger than a network quality threshold based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

calculating a resource consumption function value of the undetermined radio frequency optimization scheme;

and determining the undetermined radio frequency optimization scheme with the minimum resource consumption function value as a target radio frequency optimization scheme.

With reference to the tenth implementation manner of the first aspect, in an eleventh implementation manner of the first aspect, the adjusting the adjustment parameter in each radio frequency optimization scheme in the new scheme group includes:

and adjusting the adjustment parameters in each radio frequency optimization scheme in the new scheme group through a genetic algorithm.

In a second aspect, an apparatus for determining a network radio frequency optimization scheme according to an embodiment of the present invention includes:

the resource consumption function building unit is used for building a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the execution radio frequency optimization parameter item; a network quality evaluation function construction unit, configured to construct a network quality evaluation function based on a first ratio of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second ratio of an area where the reference signal received quality reaches a second predetermined threshold; and the radio frequency optimization scheme calculation unit is used for calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents the radio frequency optimization scheme which has the minimum value of the resource consumption function and the value of the network quality evaluation function is greater than the network quality threshold after being adopted.

With reference to the second aspect, in a first implementation manner of the second aspect, the apparatus further includes:

the weight setting unit is used for setting a first weight value corresponding to the first proportion and a second weight value corresponding to the second proportion;

the network quality evaluation function constructing unit is further configured to construct a network quality evaluation function based on the first proportion, the second proportion, the first weight value and the second weight value.

With reference to the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the network quality evaluation function includes:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x)，

wherein x represents a radio frequency optimization scheme, f_{RS_RSRP}(x) Denotes the first ratio after execution of the x radio frequency optimization scheme, f_{RS_RSRQ}(x) Indicating a second ratio after the x radio frequency optimization scheme is performed, L1 indicating a first weight value, and L2 indicating a second weight value.

With reference to the second aspect, in a third implementation manner of the second aspect, the apparatus further includes:

and the average resource consumption setting unit is used for setting the average resource consumption corresponding to the radio frequency optimization parameter item executed in the target network.

With reference to the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the radio frequency optimization parameter item includes at least one of the following items: the number of mechanical downward inclination angles of the antenna, the number of electronic downward inclination angles of the antenna, the number of azimuth angles of the antenna, the number of types of the antenna and the number of transmitting power of the antenna.

With reference to the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the resource consumption function includes: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E，

With reference to the fourth implementation manner of the second aspect, in a sixth implementation manner of the second aspect, the radio frequency optimization parameter item further includes the number of times that the base station needs to be reached and/or the number of base station towers that need to be climbed.

With reference to the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the resource consumption function includes: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E+K6×F+K7×G，

With reference to the second aspect, in an eighth implementation manner of the second aspect, the apparatus further includes:

the dividing unit is used for dividing the network area of the target network;

the proportion calculation unit is used for calculating the proportion of all network areas occupied by the network areas with the maximum reference signal received power value larger than a first preset threshold value as a first proportion;

the proportion calculation unit is further used for calculating the proportion of all the network areas occupied by the network areas with the reference signal received quality maximum value larger than a second preset threshold value as a second proportion.

With reference to the eighth implementation manner of the second aspect, in a ninth implementation manner of the second aspect, the dividing unit is further configured to divide the network area based on the number of base stations in the target network and/or a distribution status of the base stations.

With reference to the second aspect, in a tenth implementation manner of the second aspect, the apparatus further includes:

an initial value setting unit for setting an initial value of i to 0, the i indicating the number of times the following step A, B, C, D, E, F is performed;

the radio frequency optimization scheme calculation unit is further configured to:

B. incrementing the value of i by 1;

C. judging that the value of i reaches a preset value;

D. when the value of i does not reach a preset value, determining the fitness proportion of each radio frequency optimization scheme of the initial scheme group based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

E. generating a new scheme group based on the fitness proportion of each radio frequency optimization scheme in the initial scheme group, wherein the new scheme group comprises the radio frequency optimization schemes with the preset number;

when the value of i is larger than a preset value, determining a pending radio frequency optimization scheme with a network quality evaluation function value larger than a network quality threshold based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

With reference to the tenth implementation manner of the second aspect, in an eleventh implementation manner of the second aspect, the radio frequency optimization scheme calculating unit is further configured to adjust, through a genetic algorithm, an adjustment parameter in each radio frequency optimization scheme in the new scheme group.

In a third aspect, an apparatus for determining a network radio frequency optimization scheme according to an embodiment of the present invention includes:

a memory for storing an executable program;

the processor is used for executing the program stored in the memory, and specifically used for constructing a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the execution radio frequency optimization parameter item; constructing a network quality evaluation function based on a first proportion of an area in the target network, wherein the reference signal received power reaches a first preset threshold value, and a second proportion of an area in the target network, wherein the reference signal received quality reaches a second preset threshold value; and calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents a radio frequency optimization scheme which has the network quality evaluation function value larger than the network quality threshold and the resource consumption function value minimum after being adopted;

and the display is used for displaying the target radio frequency optimization scheme.

In the method, the device and the equipment for determining the network radio frequency optimization scheme according to the embodiment of the invention, because the resource consumption function can represent the resource consumption of the radio frequency optimization parameter item when the radio frequency optimization scheme is executed, the network quality evaluation function can represent the coverage degree and the interference degree of the target network after the radio frequency optimization scheme is executed through the proportion of the area of which the reference signal receiving power reaches the first preset threshold value and the proportion of the area of which the reference signal receiving quality reaches the second preset threshold value, thereby playing the effect of the target network optimization, therefore, the target radio frequency optimization scheme which can ensure good radio frequency optimization effect and can minimize the resource consumed by the radio frequency optimization scheme is determined through the resource consumption function and the network quality evaluation function, so that the network quality is effectively improved, and the consumption of resources such as manpower, time and the like is reduced.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic flow chart diagram of a method of determining a network radio frequency optimization scheme in accordance with an embodiment of the present invention;

FIG. 2 is a schematic flow chart diagram of the construction of an evaluation function in the method of determining a network radio frequency optimization scheme shown in FIG. 1;

FIG. 3 is a schematic flow chart diagram of a method of determining a network radio frequency optimization scheme in accordance with yet another embodiment of the present invention;

FIG. 4 is a schematic diagram of a fitness metric component area of an individual in a method of determining a network radio frequency optimization scheme according to another embodiment of the present invention;

FIG. 5 is a schematic block diagram of an apparatus for determining a network radio frequency optimization scheme according to another embodiment of the present invention;

FIG. 6 is a schematic block diagram of an apparatus for determining a network radio frequency optimization scheme in accordance with one or more further embodiments of the present invention;

fig. 7 is a block diagram of an exemplary hardware architecture of a device capable of implementing at least a portion of the method of determining a network radio frequency optimization scheme and the apparatus for determining a network radio frequency optimization scheme according to embodiments of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention.

The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the invention. The embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

The embodiment of the invention is used for determining the scene of the radio frequency optimization scheme when the radio frequency optimization is carried out on the network, and particularly, under the condition that a plurality of networks coexist, for example, under the condition that a 2G network, a 3G network and an LTE network coexist, the radio frequency optimization scheme is determined through the embodiment of the invention, so that the good radio frequency optimization effect can be ensured, and the execution resource consumption of the radio frequency optimization scheme can be reduced to the minimum.

Fig. 1 shows a schematic flow diagram of a method 100 of determining a network radio frequency optimization scheme according to an embodiment of the invention. As shown in fig. 1, the method 100 includes: step S110, constructing a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the execution radio frequency optimization parameter item; step S120, constructing a network quality evaluation function based on a first proportion of an area in the target network, wherein the reference signal receiving power reaches a first preset threshold value, and a second proportion of an area in the target network, wherein the reference signal receiving quality reaches a second preset threshold value; and step S130, calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function.

In step S110, the target network is a network that needs to perform radio frequency optimization, and the resource consumption represents the resource consumption for executing the radio frequency optimization parameter item, i.e. the resource consumed by executing the radio frequency optimization manner, such as time, labor, money, material, and so on. The resource consumption may be a specific value of resource consumption for executing the radio frequency optimization parameter item, or may be a coefficient representing the degree of resource consumption for executing the radio frequency optimization parameter item.

In step S120, the reference signal received power and the reference signal received quality are parameters that can represent the network quality. The first proportion of the area where the reference signal received power reaches the first predetermined threshold represents the coverage rate of the reference signal received power reaching the first predetermined threshold in the target network, and can reflect the degree of network signal coverage; the second proportion of the area where the reference signal received quality reaches the second predetermined threshold represents a satisfaction rate at which the reference signal received quality reaches the second predetermined threshold in the target network, which may reflect a degree of interference existing in the network. For different radio frequency optimization schemes, the first proportion and the second proportion after the target network executes the radio frequency optimization scheme can be obtained through simulation.

It should be noted that the execution sequence of step S110 and step S120 is not limited, and both may be executed simultaneously or sequentially.

In step S130, the target radio frequency optimization scheme includes at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents a radio frequency optimization scheme in which a value of the network quality assessment function is greater than a network quality threshold and a value of the resource consumption function is minimum after the target radio frequency optimization scheme is adopted. In this step, the evaluation function and the radio frequency optimized resource consumption function may be used as a target optimization function, and a radio frequency optimization scheme that satisfies that the corresponding evaluation function is greater than the network quality threshold and the corresponding radio frequency optimized resource consumption is minimum is calculated through a search algorithm, such as an enumeration algorithm, a genetic algorithm, and the like.

In the embodiment of the invention, the resource consumption function can reflect the resource consumption of the radio frequency optimization parameter item when the radio frequency optimization scheme is executed, and the network quality evaluation function can reflect the coverage degree and the interference degree of the target network after the radio frequency optimization scheme is executed through the proportion of the area of which the reference signal receiving power reaches the first preset threshold and the proportion of the area of which the reference signal receiving quality reaches the second preset threshold, so that the effect of optimizing the target network can be released, therefore, the target radio frequency optimization scheme which can ensure good radio frequency optimization effect and can reduce the resource consumed by the radio frequency optimization scheme to the minimum is determined through the resource consumption function and the network quality evaluation function, thereby effectively improving the network quality and reducing the consumption of resources such as manpower, time and the like. In addition, the target radio frequency optimization scheme calculated by the embodiment of the invention can ensure good radio frequency optimization effect, so that the performance of the network structure can be improved in time, and the problem that the performance of the network structure cannot be improved well during network optimization in the prior art, and the problems in the network gradually accumulate along with the expansion of the network, the performance of the network structure is worse and worse, and thus more resources are required to be spent for optimization is solved. Furthermore, in the embodiment of the invention, a network quality evaluation function and a resource consumption function are constructed, when radio frequency optimization is required to be carried out on the whole network, a target radio frequency optimization scheme can be obtained through accurate calculation based on the two functions, and a large number of radio frequency optimization parameter items in a debugging network do not need to be debugged through experience of an engineer, so that the target radio frequency optimization scheme which ensures a good radio frequency optimization effect and reduces the consumed resources to the minimum can be rapidly obtained, the time of the engineer is saved, and the working efficiency is improved.

Fig. 2 is a schematic flow chart of the evaluation function constructed in the method for determining the network radio frequency optimization scheme shown in fig. 1. As shown in fig. 2, before performing step S140, the method 100 may further include: step S121, setting a first weight value corresponding to the first proportion and a second weight value corresponding to the second proportion; step S120 may specifically be executed as step S121, and a network quality assessment function is constructed based on the first proportion, the second proportion, the first weight value and the second weight value.

In step S121, the first ratio may reflect a degree of network signal coverage, the second ratio may reflect a degree of interference in the network, and weight values of the first ratio and the second ratio represent a degree of attention of the network optimization to the above two aspects. For example, if the degree of network coverage is more concerned in the optimization, the weight value corresponding to the second proportion corresponding to the first proportion, and vice versa; if the attention degrees of the two are equal in the optimization, the weight value corresponding to the first proportion can be set to be equal to the weight value corresponding to the first proportion.

It should be noted that, in the embodiment of the present invention, the first weight value and the second weight value may be represented in a percentage manner, and a sum of the first weight value and the second weight value is limited to be equal to 1, so that a degree of attention to the first weight value and the second weight value by the current network optimization can be clearly embodied.

Network quality evaluation function f constructed in step S122_TDL(x) This can be shown as follows:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x) Wherein x represents a radio frequency optimization scheme, f_{RS_RSRP}(x) Denotes the first ratio after execution of the x radio frequency optimization scheme, f_{RS_RSRQ}(x) Indicating a second ratio after the x radio frequency optimization scheme is performed, L1 indicating a first weight value, and L2 indicating a second weight value.

It should be noted that the network quality evaluation function f is described above_TDL(x) In this case, L1+ L2 may be set to 1.

In this embodiment, the evaluation function is constructed based on the first weight value and the second weight value, and the degree of the network coverage and interference of the current network optimization can be expressed, that is, the actual requirement of the current network optimization can be embodied, so that the calculated radio frequency optimization scheme can better meet the requirement of the network optimization, and the effect of the network optimization is improved.

A further embodiment of the present invention provides a method for determining a network radio frequency optimization scheme, which is different from the embodiment of the method shown in fig. 1 in that before performing step S110, the method 100 may further include: step S150, setting the average resource consumption corresponding to the rf optimization parameter executed in the target network.

In this case, a large number of base stations (tens or even tens) are usually set in a network, and each base station is also provided with a plurality of antennas, so that if the resource consumption corresponding to the radio frequency optimization parameter item is executed on each base station to construct a resource consumption function, the resource consumption function is very complex to construct, and further, the process of calculating the target radio frequency optimization scheme is very complex and the calculation process consumes a large amount of time. In order to reduce the complexity of the calculation and reduce the calculation time, in this step, after determining the resource consumption corresponding to the radio frequency optimization parameter item executed by the antenna of each base station in the network, the average resource consumption corresponding to the radio frequency optimization parameter item is set, and then the corresponding resource consumption is calculated by the average resource consumption no matter which base station antenna in the network executes the radio frequency optimization parameter item.

Specifically, the radio frequency optimization parameter item may include at least one of the following items: the number of mechanical downward inclination angles of the antenna, the number of electronic downward inclination angles of the antenna, the number of azimuth angles of the antenna, the number of types of the antenna and the number of transmitting power of the antenna. Then, in the embodiment of the present invention, the resource consumption for adjusting each antenna azimuth angle in the network, the resource consumption for adjusting each antenna mechanical downtilt angle, the resource consumption for adjusting each antenna electronic downtilt angle, the resource consumption for adjusting each antenna type, and the resource consumption for adjusting each antenna transmission power may be determined first, and then the average resource consumption for adjusting the antenna azimuth angle, the average resource consumption for adjusting the antenna mechanical downtilt angle, the average resource consumption for adjusting the antenna electronic downtilt angle, the average resource consumption for adjusting the antenna type, and the average resource consumption for adjusting the antenna transmission power in the target network are calculated, so that when the resource consumption of the radio frequency optimization scheme is calculated, it is only necessary to count the number of times that the base station needs to be reached, the number of upper base stations, the number of adjusting the antenna azimuth angles, the number of adjusting the antenna mechanical downtilts angles, the number of the antenna mechanical downtilts, the antenna transmission power, and the number of the antenna azimuth angles in the radio frequency optimization scheme are calculated And adjusting the number of the electronic downward inclination angles of the antennas, the number of the types of the antennas and the number of the transmitting power of the antennas.

For example, the resource cost function includes: f. of_COST(x) K1 × a + K2 × B + K3 × C + K4 × D + K5 × E, where x denotes a radio frequency optimization scheme, K1 denotes the number of mechanical downtilts of the antenna adjusted when x radio frequency optimization schemes are performed, and K2 denotes the antenna adjusted when x radio frequency optimization schemes are performedThe number of electronic downtilts, K3 represents the number of antenna azimuth angles adjusted when an x radio frequency optimization scheme is executed, K4 represents the number of antenna types adjusted when the x radio frequency optimization scheme is executed, K5 represents the number of antenna transmission power adjustments when the x radio frequency optimization scheme is executed, a represents the average resource consumption degree for adjusting the mechanical downtilt of an antenna in a target network, B represents the average resource consumption degree for adjusting the electronic downtilt of the antenna in the target network, C represents the average resource consumption degree for adjusting the antenna azimuth angles in the target network, D represents the average resource consumption degree for adjusting the antenna types in the target network, and E represents the average resource consumption degree for adjusting the antenna transmission power in the target network.

It should be noted that, in the radio frequency optimization parameter item, generally, the adjustment parameter corresponding to each radio frequency optimization mode needs to be prepared through multiple steps, for example, when the mechanical downtilt angle of the antenna is adjusted, a worker needs to first reach the base station where the antenna is located and then reach the position of the antenna above the base station to adjust the mechanical downtilt angle of the antenna, and climb up the base station tower when reaching the position of the antenna above the base station, so that the preparation work of the radio frequency optimization parameter item during execution can be further divided into multiple steps, resource consumption is performed when each step is executed, and these steps also belong to resource consumption of the radio frequency optimization scheme.

The embodiment of the invention takes the preparation work of executing the radio frequency optimization parameter item as the radio frequency optimization parameter item, mainly because the steps have larger influence on the resource consumption of the radio frequency optimization scheme. For example, in the step of the staff arriving at the base station where the antenna is located, since the base stations are constructed more, the location traffic of some base stations is inconvenient, or it takes a long time for the staff to arrive at the location, the execution difficulty is increased, and further the resource consumption of the whole radio frequency optimization scheme is increased. In summary, in the embodiment of the present invention, when the resource consumption function is constructed, the resource consumption of the preparation work before the execution of each radio frequency optimization mode needs to be considered.

Specifically, the radio frequency optimization parameter item further includes the number of times that the base station needs to be reached and/or the number of base station towers that need to be climbed. Step 150 also entails determining an average resource cost to reach each base station in the target network and/or an average resource cost to climb a base station tower.

For example, taking the radio frequency optimization parameter item further including the base station that needs to be reached and the base station tower that needs to be climbed as an example, the constructed resource consumption function may be as follows:

f_COST(x) K1 × a + K2 × B + K3 × C + K4 × D + K5 × E + K6 × F + K7 × G, where x denotes a radio frequency optimization scheme, K1 denotes the number of antenna mechanical downtilts adjusted when performing the x radio frequency optimization scheme, K2 denotes the number of antenna electrical downtilts adjusted when performing the x radio frequency optimization scheme, K3 denotes the number of antenna azimuth angles adjusted when performing the x radio frequency optimization scheme, K4 denotes the number of antenna types adjusted when performing the x radio frequency optimization scheme, K5 denotes the number of antenna transmission power adjustments when performing the x radio frequency optimization scheme, K6 denotes the number of times of base stations that need to be reached when performing the x radio frequency optimization scheme, K7 denotes the number of base station towers that need to be climbed when performing the x radio frequency optimization scheme, a denotes the average resource consumption degree of adjusting antenna mechanical downtilts in the target network, B denotes the average resource consumption degree of adjusting antenna electrical downtilts in the target network, c represents the average resource consumption of the antenna azimuth angle in the target network, D represents the average resource consumption of the antenna type in the target network, E represents the average resource consumption of the antenna transmitting power adjustment in the target network, F represents the average resource consumption of the base station in the target network, and G represents the average resource consumption of the base station tower climbing in the target network.

It should be noted that, since it is necessary to adjust the azimuth angle of the antenna and adjust the mechanical downtilt angle of the antenna, and it is necessary for a worker to reach the base station where the antenna is located and climb the base station tower, and it is possible to adjust a plurality of parameters by climbing the base station tower once, the values of K1, K2, K3, K4, K5, K6, and K7 in the above function need to be determined by comprehensively considering the overall radio frequency optimization scheme. In the embodiment of the present invention, the resource consumption may be expressed as one or more of labor, time, money, materials, and the like required for executing the radio frequency optimization parameter item, and when the resource consumption expresses multiple aspects, the multiple aspects may be converted into one aspect to calculate the specific resource consumption, for example, the required labor and time are converted into money, and then the specific resource consumption is calculated by money. In the embodiment of the invention, the resource consumption for executing each step can be determined according to historical data or experience. For example, when adjusting the antenna parameters of a certain base station of the target network, the worker obtains the time required for reaching the base station, the required tools, whether the road is smooth, and the like according to the historical experience or the historical data, and further obtains the resource consumption for reaching the base station. In the embodiment of the invention, the resource consumption can be represented by preset levels, namely, a plurality of resource consumption levels are preset at first, and then the resource consumption level corresponding to each step of the optimization execution mode is determined according to the historical experience or historical data of workers.

Fig. 3 is a schematic flow chart diagram of a method of determining a network radio frequency optimization scheme according to yet another embodiment of the present invention. The method embodiment shown in fig. 3 differs from the method embodiment shown in fig. 1 in that, before performing step S120, the method 100 may further include: step S160, network area division is carried out on the target network; step S170, calculating the proportion of the network area with the maximum reference signal received power larger than a first preset threshold value to all the network areas as a first proportion; step S180, calculating a ratio of the network area with the maximum reference signal received quality greater than the second predetermined threshold to all the network areas as a second ratio.

The target network is divided, so that the first proportion and the second proportion can be calculated more conveniently. Specifically, the network area division manner for the target network may be set according to a specific scenario or a target to be optimized. For example, the division is performed according to the number of the base stations, so that the situation that the number of the base stations in the network area is too large or too small is avoided; or, dividing the network area according to the distribution status of the base stations (belonging to the base stations under the same gateway); or, the network area is divided equally according to the size of the target network coverage area, and so on.

Based on the method for determining the network radio frequency optimization scheme shown in fig. 1, another embodiment of the present invention provides a method for calculating a target radio frequency optimization scheme, that is, before step 130: setting an initial value of i to 0, i representing the number of times the following step A, B, C, D, E, F is performed; step 130 may be specifically performed as the following process: randomly generating an initial scheme group based on adjustment parameters corresponding to radio frequency optimization modes adopted by all cells in a target network, wherein the initial scheme group comprises a preset number of radio frequency optimization schemes; A. respectively calculating network quality evaluation function values of all radio frequency optimization schemes in the initial scheme group; B. incrementing the value of i by 1; C. judging whether the value of i reaches a preset value or not; D. when the value of i does not reach a preset value, determining the fitness proportion of each radio frequency optimization scheme in the initial scheme group based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group; E. generating a new scheme group based on the fitness proportion of each radio frequency optimization scheme in the initial scheme group, wherein the new scheme group comprises a preset number of radio frequency optimization schemes; F. adjusting adjustment parameters corresponding to the radio frequency optimization modes of the radio frequency optimization schemes in the new scheme group to generate a variation scheme group, taking the variation scheme group as an initial scheme group, and executing the step A, B, C, D, E, F again; when the value of i reaches a preset value, determining a undetermined radio frequency optimization scheme with a network quality evaluation function value larger than a network quality threshold based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group; calculating a resource consumption function value of the undetermined radio frequency optimization scheme; and determining the undetermined radio frequency optimization scheme with the minimum resource consumption function value as a target radio frequency optimization scheme.

The adjustment parameters corresponding to the radio frequency optimization method adopted by each cell in the target network may include: mechanical downtilt of the antenna, electrical downtilt of the antenna, azimuth of the antenna, transmission power of the antenna, type of antenna, etc.

The processing of adjusting the adjustment parameters in each radio frequency optimization scheme in the new scheme group may be: and adjusting the adjustment parameters in each radio frequency optimization scheme in the new scheme group through a genetic algorithm.

The embodiment of the present invention takes a genetic algorithm as an example to describe the implementation process of step 130 in detail as follows.

When using genetic algorithms, in order to discretize the target problem, it is usually necessary to encode it, which is convenient for computer processing, and the encoding method includes: binary coding, gray code coding, floating point number (real number) coding, permutation coding, and the like, and the embodiments of the present invention are described by taking binary coding as an example. The adjustment parameters corresponding to the radio frequency optimization mode adopted by each cell in the embodiment of the present invention are described by taking a mechanical downward inclination angle of an antenna, an electronic downward inclination angle of the antenna, an azimuth angle of the antenna, a transmission power of the antenna, and a type of the antenna as examples.

In the encoding stage of the genetic algorithm, a two-dimensional binary code is adopted for encoding schemes of mechanical downward inclination angles of the antenna, electronic downward inclination angles of the antenna, azimuth angles of the antenna, transmitting power of the antenna and types of the antenna, and the schemes are encoded into a 0 and 1 matrix form. Assuming that there are K cells in the target network, the adjustment parameters that can be used in radio frequency optimization of each cell are the mechanical downtilt of the antenna, the electronic downtilt of the antenna, the azimuth angle of the antenna, the transmitting power of the antenna, and the type of the antenna, and the adjustment range and the adjustment step length of each parameter are respectively: the adjustment range of the mechanical downward inclination angle is [ Min ]_mechtilt，Max_mechtilt]The Step length is adjusted to Step_mechtilt(ii) a The electronic downward inclination angle is adjusted within a range of [ Min ]_electilt，Max_electilt]The Step length is adjusted to Step_electilt(ii) a The azimuth angle adjustment range is [ Min_zaimuth，Max_zaimuth]The Step length is adjusted to Step_zaimuth(ii) a Transmission power range of [ Min_rspower，Max_rxpower]Step length is Step_rspower(ii) a The antenna type adjustment range is [ Min_antenna，Max_antenna]The Step length is adjusted to Step_antenna. Then, the length of the binary code is calculated according to the adjustment range and step length of each adjustment parameter, and the calculation formula of the code length is as follows:

max is the upper bound of the adjustment range, min is the lower bound of the adjustment range, and step is the adjustment step length. Respectively calculating to obtain N adjusting parameter code lengths of mechanical downward inclination angle, electronic downward inclination angle, azimuth angle, transmitting power and antenna type_mechtilt、N_electilt、N_zaimuth、N_rspower、N_antennaThen the parameter coding for the ith (1 ≦ i ≦ k) cell is:

[a_i，0...a_i，k1，a_i，k1+1...a_i，k2，a_i，k2+1...a_i，k3，a_i，k3+1...a_i，k4，a_i，k4+1...a_i，w-1]wherein a is_ij∈{0，1}，0≤j≤w-1，w＝N_mechtilt+N_electilt+N_zaimuth+N_rspower+N_antenna，[a_i，0...a_i，k1]For the coding of the mechanical downtilt, [ a ]_i，k1+1...a_i，k2]For coding of electronic downtilt, [ a ]_i，k2+1...a_i，k3]For encoding of azimuth angle, [ a ]_i，k3+1...a_i，k4]For coding of the transmission power, [ a ]_i，k4+1...a_i，w-1]For antenna type coding, the coding of the adjustment parameters for K cells can be represented by the following matrix:

generating an initial scheme group P (t) of a certain scale by a random method based on the coding mode₀) The initial solution group is the initial group in the genetic algorithm, and P (t) is generated generally₀) In this case, N (for example, 20) individual populations may be randomly generated within an allowable parameter range based on the original parameter data of the antennas in each cell before the network optimization.

For example, assuming that the code of each adjustment parameter is represented by a 3-bit binary number (i.e. containing 8 adjustable values, from 000 to 111), and k is 5, the original data of the antenna parameters in each cell before the network optimization is converted into a binary value g0, where the column g0 represents the code arrangement in the order of mechanical downtilt, electrical downtilt, azimuth, transmission power, and antenna type, and the rows g0 correspond to 5 cells:

then, an initial population containing a preset number of solutions is generated by a random method, and if the preset number is 4, P (t) is obtained₀) (g0, g1, g2, g3), wherein g0 may not be included in P (t)₀) In (1).

After determining P (t)₀) Then, the 4 schemes are calculated by using a network quality evaluation function, where L1-L2-0.5 is taken as an example, the network quality evaluation function values of the 4 schemes are calculated according to the network quality evaluation function, as shown in table one, where α is a network quality threshold and is set to 0.95.

Watch 1

P(t₀)	f_TDL(x)	α
			g0	0.62	0.95
g1	0.91	0.95
			g2	0.46	0.95
g3	0.23	0.95

And determining the fitness proportion of the 4 radio frequency optimization schemes in the initial scheme group based on the table I. The specific operation is as follows:

according to P (t)₀) The sum of the network quality evaluation function values of all the individuals calculates P (t)₀) Overall fitness f of the population_total2.22; secondly, f of each individual_TDL(x) Divided by f_totalThe fitness ratio of each individual was calculated as the probability that each individual was inherited into the next generation population as shown in table two.

Watch two

P(t₀)	f_TDL(x)	Individual fitness ratio
			g0	0.62	0.28
g1	0.91	0.41
			g2	0.46	0.21
g3	0.23	0.10

The fitness proportion of each individual in the second table forms a region, and the sum of all probability values is 1, as shown in fig. 4; then, a random number between 0 and 1 is generated, the selected individuals are determined according to which individual fitness proportion area the random number appears in, and the steps are sequentially executed until a population meeting the number of individuals with a preset number is obtained, namely the new scheme group. In this example, the number of the recipe groups is 4, and the generated new recipe group is P (t)₀+1)：(g4，g5，g6，g7)。

From the above, it can be seen that the regimen g3 in the starter population has been eliminated and the regimen g1 in the starter population was selected twice as g5 and g6, respectively.

The method for adjusting the parameters corresponding to the radio frequency optimization method of each radio frequency optimization scheme in the new scheme group may include crossover and variation in a genetic algorithm.

In the allocation of the available values of the radio frequency parameters, the number of the available value requirements is ensured to be unchanged. The crossing mode can be as follows: first in a population P (t)₀+1) random pairwise, i.e. determining the combination of individuals that cross pairwise, e.g. pairing g4 and g5, pairing g6 and g 7; secondly, two random numbers C1 and C2 are generated in the numerical range of 0 to kxj-1, wherein k is the number of cells, and j is the total coding length of each cell; when the codes of the C1 and the C2 corresponding to the individuals are in the same row, the codes of the rows where the C1 and the C2 are located in the two paired individuals are exchanged; when the codes of the C1 and the C2 respectively correspond to the individuals are not in the same row, codes from the C1 bit to the tail of the row in the C1 row and codes from the head of the row to the C2 bit in the C2 row in the two paired individuals are exchanged, and meanwhile, if the C1 and the C2 respectively correspond to other rows in the middle of two rows in which the codes in the individuals are located, codes of the C1 and the C2 respectively correspond to other rows in the middle of two rows in which the codes in the individuals are located in the two paired individuals are exchanged. For example: the pairing of g4 and g5, the pairing of g6 and g7, the range of generated random numbers is 0-75, and assuming that the generated random numbers are C1 ═ 2 and C2 ═ 35 as examples, the result after the crossover operation is g41, g51, g61 and g71 as follows, if the generated random numbers are C1 ═ 2 and C2 ═ 35, the code in the first row and the third code in the C1 corresponding individuals and the code in the third row and the sixth code in the C2 corresponding individuals are not in the same row.

The variation mode can be as follows: firstly, generating a random number, judging whether the random number is greater than a preset variation rate, if so, executing variation operation, and if not, executing no variation operation. The mutation operation may be performed by using a basic bit mutation method. Specifically, the mutation probability is set to be 0.01; then, starting from g4, generating a random number between (0, 1), if the random number is more than 0.01, generating the random number between 0 and kxj as a variation point, negating the original value of the variation point, and if the random number is not more than 0.01, not mutating g 4; mutation operations were performed on g4, g5, g6, and g7 in this order.

After parameters corresponding to the radio frequency optimization modes of the radio frequency optimization schemes in the new scheme group are adjusted, a variant population can be obtained. And repeating the steps for executing the preset value of i for times.

When the value of i reaches a preset value, f in the initial scheme group at the moment is calculated firstly_TDL(x) And determining the undetermined radio frequency optimization scheme with the minimum resource consumption function value in each undetermined radio frequency optimization scheme as a target radio frequency optimization scheme. Specifically, after the value of i is assumed to reach a preset value, the determined undetermined radio frequency optimization schemes are g8 and g 9.

F of g8 and g9_TDL(x) And if the network quality thresholds are met, counting the values of K1-K7 in g8 and g9, and the result is shown in the third table.

Watch III

Scheme(s)	K1	K2	K3	K4	K5	K6	K7
								g1	3	1	1	0	2	3	3
g2	5	2	1	1	3	5	5

Assuming that the average resource consumption of the target network to the base station is 50, the average resource consumption of the target network to climb a base station tower is 80, the average resource consumption of the target network to adjust the mechanical downward inclination of the antenna is 5, the average resource consumption of the target network to adjust the electronic downward inclination of the antenna is 3, the average resource consumption of the target network to adjust the azimuth angle of the antenna is 5, the average resource consumption of the target network to adjust the transmitting power of the antenna is 2, and the average resource consumption of the target network to adjust the type of the antenna is 100.

The resource cost function value for the solution g8 may be calculated as: 417; the resource consumption function value of the solution g9 is: 792. it can be seen that the resource consumption of the scheme g8 is much greater than that of g9, and the target rf optimization scheme is g 8.

Of course, in an actual system, it may be necessary to obtain a plurality of schemes that satisfy the network quality target simultaneously through a plurality of iterative operations, and in these schemes, a target radio frequency optimization scheme is finally obtained by calculating and comparing resource consumption function values.

The method for determining the network radio frequency optimization scheme according to the embodiment of the present invention is described in detail above with reference to fig. 1 and 4, and the apparatus for determining the network radio frequency optimization scheme according to the embodiment of the present invention is described in detail below with reference to fig. 5 and 6.

Fig. 5 shows a schematic block diagram of an apparatus 200 for determining a network radio frequency optimization scheme according to an embodiment of the present invention. As shown in fig. 5, the apparatus 200 includes:

a resource consumption function constructing unit 210, configured to construct a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item;

a network quality evaluation function constructing unit 220, configured to construct a network quality evaluation function based on a first ratio of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second ratio of an area where the reference signal received quality reaches a second predetermined threshold;

a radio frequency optimization scheme calculating unit 230, configured to calculate a target radio frequency optimization scheme of the target network according to the evaluation function and the radio frequency optimization resource consumption function, where the target radio frequency optimization scheme includes at least one radio frequency optimization parameter item, and where the target radio frequency optimization scheme represents a radio frequency optimization scheme in which a value of the network quality evaluation function is greater than a network quality threshold and a value of the resource consumption function is minimum after being adopted.

Fig. 6 is a schematic block diagram of an apparatus for determining a network radio frequency optimization scheme according to one or more further embodiments of the present invention.

In one embodiment, such as the schematic block diagram of the apparatus shown in fig. 6, the apparatus 200 may further comprise:

a weight setting unit 240, configured to set a first weight value corresponding to the first ratio and a second weight value corresponding to the second ratio;

the network quality assessment function constructing unit 230 is further configured to construct the network quality assessment function based on the first proportion, the second proportion, the first weight value, and the second weight value.

Specifically, the network quality evaluation function includes:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x)，

wherein x represents a radio frequency optimization scheme, f_{RS_RSRP}(x) Denotes the first ratio after execution of the x radio frequency optimization scheme, f_{RS_RSRQ}(x) Represents the second ratio after the execution of the xrf optimization scheme, L1 represents the first weight value, and L2 represents the second weight value.

In yet another embodiment, such as the schematic block diagram of the apparatus shown in fig. 6, the apparatus 200 may further comprise:

an average resource consumption setting unit 250, configured to set an average resource consumption corresponding to the radio frequency optimization parameter executed in the target network.

Wherein the radio frequency optimization parameter item comprises at least one of: the number of mechanical downward inclination angles of the antenna, the number of electronic downward inclination angles of the antenna, the number of azimuth angles of the antenna, the number of types of the antenna and the number of transmitting power of the antenna.

In particular, the resource consumptionThe cost function includes: f. of_COST(x) K1 × a + K2 × B + K3 × C + K4 × D + K5 × E, where x denotes a radio frequency optimization scheme, K1 denotes the number of antenna mechanical downtilts adjusted when performing the x radio frequency optimization scheme, K2 denotes the number of antenna electronic downtilts adjusted when performing the x radio frequency optimization scheme, K3 denotes the number of antenna azimuth angles adjusted when performing the x radio frequency optimization scheme, K4 denotes the number of antenna types adjusted when performing the x radio frequency optimization scheme, K5 denotes the number of antenna transmit power adjustments when performing the x radio frequency optimization scheme, a denotes the average resource consumption for adjusting antenna mechanical downtilts in the target network, B denotes the average resource consumption for adjusting antenna electronic downtilts in the target network, C denotes the average resource consumption for adjusting antenna azimuth angles in the target network, D denotes the average resource consumption for adjusting antenna types in the target network, e represents the average resource consumption for antenna transmit power adjustment in the target network.

The radio frequency optimization parameter items also comprise the times of reaching the base station and/or the number of base station towers needing to be climbed.

Specifically, the resource consumption function includes: f. of_COST(x) K1 × a + K2 × B + K3 × C + K4 × D + K5 × E + K6 × F + ktxg, where x denotes a radio frequency optimization scheme, K1 denotes the number of antenna mechanical downtilts adjusted when performing the x radio frequency optimization scheme, K2 denotes the number of antenna electronic downtilts adjusted when performing the x radio frequency optimization scheme, K3 denotes the number of antenna azimuths adjusted when performing the x radio frequency optimization scheme, K4 denotes the number of antenna types adjusted when performing the x radio frequency optimization scheme, K5 denotes the number of antenna transmission power adjustments when performing the x radio frequency optimization scheme, K6 denotes the number of times to reach the base station when performing the x radio frequency optimization scheme, K7 denotes the number of base station climbs required when performing the x radio frequency optimization scheme, a denotes the average resource consumption degree for adjusting the antenna mechanical downtilts in the target network, B denotes the average resource consumption degree for adjusting the antenna electronic downtilts in the target network, c represents the average resource consumption of the azimuth angle of the antenna in the target network, D represents the average resource consumption of the type of the antenna in the target network, and E represents the transmission power adjustment of the antenna in the target networkAnd F represents the average resource consumption of the base station in the target network, and G represents the average resource consumption of the base station tower climbing in the target network.

In yet another embodiment, such as the schematic block diagram of the apparatus shown in fig. 5, the apparatus 200 may further comprise:

a dividing unit 260, configured to perform network region division on the target network;

a ratio calculating unit 270, configured to calculate a ratio of a network area with a maximum value of the reference signal received power being greater than a first predetermined threshold to all the network areas as the first ratio;

the ratio calculating unit 270 is further configured to calculate, as the second ratio, a ratio of a network area with a maximum value of the reference signal received quality greater than a second predetermined threshold to all the network areas.

Specifically, the dividing unit 260 is configured to divide the network area based on the number of base stations in the target network and/or the distribution status of the base stations.

an initial value setting unit 280 for setting an initial value of i, which indicates the number of times the following step A, B, C, D, E, F is performed, to 0;

the radio frequency optimization scheme calculation unit 230 is further configured to:

the method comprises the steps that an initial scheme group is randomly generated based on adjustment parameters corresponding to radio frequency optimization modes adopted by cells in a network, wherein the initial scheme group comprises a preset number of radio frequency optimization schemes;

B. incrementing the value of i by 1;

C. judging that the value of i reaches a preset value;

D. when the value of i does not reach the preset value, determining the fitness proportion of each radio frequency optimization scheme of the initial scheme group based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

F. adjusting adjustment parameters in each radio frequency optimization scheme in the new scheme group to generate a variation scheme group, taking the variation scheme group as the initial scheme group, and executing the step A, B, C, D, E, F;

when the value of the i is larger than the preset value, determining a pending radio frequency optimization scheme with a network quality evaluation function value larger than the network quality threshold based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

and determining the undetermined radio frequency optimization scheme with the minimum resource consumption degree function value as the target radio frequency optimization scheme.

Specifically, the radio frequency optimization scheme calculating unit 230 is further configured to adjust an adjustment parameter in each radio frequency optimization scheme in the new scheme group through a genetic algorithm.

In one embodiment of the schematic block diagram of the apparatus shown in fig. 6, all the units shown in fig. 6 may not be included, that is, the units shown in fig. 6 may be added, subtracted or combined according to an actual application scenario.

Fig. 7 is a block diagram of an exemplary hardware architecture of a device capable of implementing at least a portion of the method of determining a network radio frequency optimization scheme and the apparatus for determining a network radio frequency optimization scheme according to embodiments of the present invention. As shown in fig. 7, the device 300 comprises a processor 301, a memory 302 and a display 303, wherein the memory 302 is used for storing executable programs, the processor 301 is used for executing the programs stored in the memory 301, the display 303 is used for displaying results obtained after the processor 301 executes the programs, and the device 300 further comprises a bus 304, wherein the bus 304 is used for connecting the processor 301, the memory 302 and the display 303, so that the processor 301, the memory 302 and the display 303 can communicate with each other through the bus 304.

Specifically, the processor 301 is specifically configured to construct a resource consumption function based on a radio frequency optimization parameter item in a target network and a resource consumption corresponding to the radio frequency optimization parameter item; constructing a network quality evaluation function based on a first proportion of an area in the target network, wherein the reference signal received power reaches a first preset threshold value, and a second proportion of an area in the target network, wherein the reference signal received quality reaches a second preset threshold value; and calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents a radio frequency optimization scheme which has the network quality evaluation function value larger than a network quality threshold and the resource consumption function value minimum after being adopted;

the display 303 is specifically configured to display the target radio frequency optimization scheme.

It should be noted that the processor 301 in the device 300 may also be configured to execute the method in the embodiment shown in fig. 1 to 4, and display data during and/or after the processing of the processor 301 through the display 303.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and the division of the units is only one logical functional division, and there may be other divisions when actually implementing, and a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented.

While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for determining a network radio frequency optimization scheme, comprising:

constructing a resource consumption function based on a radio frequency optimization parameter item in a target network and the resource consumption corresponding to the radio frequency optimization parameter item;

constructing a network quality evaluation function based on a first proportion of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second proportion of an area in the target network where the reference signal received quality reaches a second predetermined threshold;

calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents a radio frequency optimization scheme which has the network quality evaluation function value larger than a network quality threshold and the resource consumption function value minimum after being adopted;

before the process of constructing the resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item is executed, the method further includes:

setting the average resource consumption corresponding to the radio frequency optimization parameter item executed in the target network;

the radio frequency optimization parameter item comprises at least one of: the number of mechanical downward inclination angles of the antenna, the number of electronic downward inclination angles of the antenna, the number of azimuth angles of the antenna, the number of types of the antenna and the number of transmitting power of the antenna;

the resource cost function includes: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E，

Wherein x represents a radio frequency optimization scheme, K1 represents the number of antenna mechanical downtilts adjusted when executing the x radio frequency optimization scheme, K2 represents the number of antenna electronic downtilts adjusted when executing the x radio frequency optimization scheme, K3 represents the number of antenna azimuth angles adjusted when executing the x radio frequency optimization scheme, K4 represents the number of antenna types adjusted when executing the x radio frequency optimization scheme, K5 represents the number of antenna transmission power adjustments when executing the x radio frequency optimization scheme, a represents the average resource consumption degree for adjusting the antenna mechanical downtilts in the target network, B represents the average resource consumption degree for adjusting the antenna electronic downtilts in the target network, C represents the average resource consumption degree for adjusting the antenna azimuth angles in the target network, D represents the average resource consumption degree for adjusting the antenna types in the target network, and E represents the average resource consumption degree for adjusting the antenna transmission power in the target network.

2. The method of claim 1, wherein before the constructing a network quality assessment function based on a first proportion of an area of the target network where reference signal received power reaches a first predetermined threshold and a second proportion of an area where reference signal received quality reaches a second predetermined threshold, the method further comprises:

the process of constructing a network quality assessment function based on a first proportion of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second proportion of an area where the reference signal received quality reaches a second predetermined threshold includes:

constructing the network quality assessment function based on the first proportion, the second proportion, the first weight value, and the second weight value.

3. The method of claim 2, wherein the network quality assessment function comprises:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x)，

4. The method of claim 1, wherein the radio frequency optimization parameter items further comprise the number of times a base station needs to be reached and/or the number of base station towers needs to be climbed.

5. The method of claim 4, wherein the resource cost function comprises: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E+K6×F+K7×G，

Wherein x represents a radio frequency optimization scheme, K1 represents the number of adjusting mechanical downtilts of an antenna when executing the x radio frequency optimization scheme, K2 represents the number of adjusting electronic downtilts of the antenna when executing the x radio frequency optimization scheme, K3 represents the number of adjusting azimuth angles of the antenna when executing the x radio frequency optimization scheme, K4 represents the number of adjusting antenna types when executing the x radio frequency optimization scheme, K5 represents the number of adjusting transmission power of the antenna when executing the x radio frequency optimization scheme, K6 represents the number of reaching base stations when executing the x radio frequency optimization scheme, K7 represents the number of climbing base station towers when executing the x radio frequency optimization scheme, a represents the average resource consumption degree of adjusting mechanical downtilts of the antenna in the target network, B represents the average resource consumption degree of adjusting electronic downtilts of the antenna in the target network, and C represents the average resource consumption degree of adjusting azimuth angles of the antenna in the target network, d represents the average resource consumption of the antenna type adjustment in the target network, E represents the average resource consumption of the antenna transmitting power adjustment in the target network, F represents the average resource consumption of the base station reaching in the target network, and G represents the average resource consumption of the base station tower climbing in the target network.

6. The method of claim 1, further comprising, prior to the process of constructing a network quality assessment function based on a first proportion of an area of the target network where reference signal received power reaches a first predetermined threshold and a second proportion of an area where reference signal received quality reaches a second predetermined threshold:

dividing the network area of the target network;

calculating the proportion of all the network areas with the maximum value of the reference signal received power larger than a first preset threshold value as the first proportion;

and calculating the proportion of the network area with the maximum value of the reference signal received quality larger than a second preset threshold value to all the network areas as the second proportion.

7. The method of claim 1, wherein the network area partitioning of the target network comprises:

8. The method of claim 1, wherein prior to the computing a target radio frequency optimization solution for the target network based on the network quality assessment function and the resource cost function, the method further comprises:

setting an initial value of i to 0, the i indicating the number of times the following step A, B, C, D, E, F is performed;

the processing of calculating the target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function comprises:

randomly generating an initial scheme group based on adjustment parameters corresponding to radio frequency optimization modes adopted by cells in a network, wherein the initial scheme group comprises a preset number of radio frequency optimization schemes;

B. incrementing the value of i by 1;

C. judging that the value of i reaches a preset value;

when the value of the i reaches the preset value, determining a pending radio frequency optimization scheme with a network quality evaluation function value larger than the network quality threshold based on the network quality evaluation function value of each radio frequency optimization scheme in the initial scheme group;

9. The method according to claim 8, wherein the adjusting the adjustment parameters in the radio frequency optimization schemes in the new scheme group comprises:

10. An apparatus for determining a radio frequency optimization scheme for a network, comprising:

the resource consumption function building unit is used for building a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item;

a network quality evaluation function construction unit, configured to construct a network quality evaluation function based on a first ratio of an area in the target network where the reference signal received power reaches a first predetermined threshold and a second ratio of an area where the reference signal received quality reaches a second predetermined threshold;

a radio frequency optimization scheme calculation unit, configured to calculate a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, where the target radio frequency optimization scheme includes at least one radio frequency optimization parameter item, and where the target radio frequency optimization scheme represents a radio frequency optimization scheme in which a value of the network quality evaluation function is greater than a network quality threshold and a value of the resource consumption function is minimum after adoption;

the device further comprises:

an average resource consumption setting unit, configured to set an average resource consumption corresponding to the radio frequency optimization parameter item executed in the target network;

11. The apparatus of claim 10, further comprising:

a weight setting unit configured to set a first weight value corresponding to the first ratio and a second weight value corresponding to the second ratio;

the network quality assessment function construction unit is further configured to construct the network quality assessment function based on the first proportion, the second proportion, the first weight value, and the second weight value.

12. The apparatus of claim 11, wherein the network quality assessment function comprises:

f_TDL(x)＝L1×f_{RS_RSRP}(x)+L2×f_{RS_RSRQ}(x)，

13. The apparatus of claim 10, wherein the radio frequency optimization parameter items further comprise the number of times to reach the base station and/or the number of base station towers to climb.

14. The apparatus of claim 13, wherein the resource cost function comprises: f. of_COST(x)＝K1×A+K2×B+K3×C+K4×D+K5×E+K6×F+K7×G，

15. The apparatus of claim 10, further comprising:

the dividing unit is used for dividing the network area of the target network;

the proportion calculation unit is used for calculating the proportion of all the network areas occupied by the network areas with the maximum reference signal received power larger than a first preset threshold value as the first proportion;

the proportion calculation unit is further used for calculating the proportion of all the network areas with the maximum value of the reference signal received quality larger than a second preset threshold value as the second proportion.

16. The apparatus according to claim 15, wherein the dividing unit is further configured to divide the network area based on the number of base stations in the target network and/or the distribution status of the base stations.

17. The apparatus of claim 10, further comprising:

B. incrementing the value of i by 1;

C. judging that the value of i reaches a preset value;

18. The apparatus according to claim 17, wherein the radio frequency optimization scheme calculating unit is further configured to adjust the adjustment parameters in each radio frequency optimization scheme in the new scheme group through a genetic algorithm.

19. An apparatus for determining a radio frequency optimization scheme for a network, comprising:

a memory for storing an executable program;

the processor is used for executing the program stored in the memory, and specifically used for constructing a resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item; constructing a network quality evaluation function based on a first proportion of an area in the target network, wherein the reference signal received power reaches a first preset threshold value, and a second proportion of an area in the target network, wherein the reference signal received quality reaches a second preset threshold value; and calculating a target radio frequency optimization scheme of the target network according to the network quality evaluation function and the resource consumption function, wherein the target radio frequency optimization scheme comprises at least one radio frequency optimization parameter item, and the target radio frequency optimization scheme represents a radio frequency optimization scheme which has the network quality evaluation function value larger than a network quality threshold and the resource consumption function value minimum after being adopted;

a display for displaying the target radio frequency optimization scheme;

the processor is specifically configured to set an average resource consumption corresponding to the radio frequency optimization parameter item in the target network before the processing of constructing the resource consumption function based on the radio frequency optimization parameter item in the target network and the resource consumption corresponding to the radio frequency optimization parameter item is executed;