CN115835228A - Network coverage optimization method and system - Google Patents

Abstract

The present invention discloses a network coverage optimization method and system. The method includes: obtaining coverage problem areas and coverage problem area information; determining coverage compensation requirements according to the coverage problem area information; wherein, the coverage compensation requirements include coverage optimization strategies and coverage optimization requirements ; The coverage optimization strategy includes base station optimization, intelligent reflection surface optimization, and joint optimization of the base station and intelligent reflection surface; based on the coverage optimization strategy, coverage optimization is performed according to the coverage optimization requirements. The present invention identifies coverage problem areas and coverage problem area information and then adaptively selects base station optimization and/or intelligent reflection surface optimization to perform coverage compensation. Among them, by deploying intelligent reflective surface optimization, it is possible to reduce the adjustment of base station parameters, thereby avoiding the negative effects such as diffusion effects that may be brought about by traditional network optimization methods, and effectively enhancing network coverage, which can be widely used in the field of mobile communication technology.

Description

A network coverage optimization method and system

technical field

The invention relates to the technical field of mobile communication, in particular to a network coverage optimization method and system.

Background technique

In a mobile communication network, coverage and capacity are two key KPIs (Key Performance Indicator, KPI). When the coverage area of the base station is large, the capacity it supports will decrease accordingly, and when the coverage area of the base station is small, the capacity it supports will increase accordingly. Usually, network coverage and capacity are planned by using planning tools at the initial stage of network planning to plan base station layout and configuration.

Capacity that cannot meet user needs can also be considered a special case of the coverage problem. There are many reasons for the continuous changes in coverage, for example, planning errors in network planning, for example, coverage holes in planned areas; operators need to expand network deployment or propose a new network deployment plan for integration with the original network , such as adding a new base station; due to the intolerable discontinuity of network coverage caused by changes in network equipment, the service is interrupted or the service handed over to the area cannot be continued, such as base station abnormality or power-off, cell abnormality or deletion. In the above cases, it is necessary to optimize the network coverage, so that the network performance conforms to the network changes in time.

Traditionally, the optimization of network coverage or network capacity is to adjust base station parameters manually or through self-organized network (Self-Organized Network, SON) technology. The main adjustment parameters include base station antenna parameters such as antenna azimuth, antenna downtilt, and base station transmit power parameters.

Antenna azimuth refers to the horizontal angle between the north direction of the antenna and the clockwise direction to the main lobe direction of the antenna. Adjusting the antenna azimuth can reduce or increase the overlapping coverage area, accurate coverage, and increase the received signal strength in the required coverage area. Antenna downtilt refers to the angle between the horizontal plane where the antenna is located and the vertical line of the antenna plate. Adjusting the downtilt angle of the antenna can increase or decrease the coverage area, increase the received signal strength in the coverage area, avoid over-area coverage, and eliminate blind spots, etc. Antenna transmit power The RF signal power output from the RF end of the antenna, excluding antenna gain. Adjusting the transmitting power of the antenna can increase or decrease the coverage area, increase the received signal strength in the coverage area, and avoid over-area coverage, etc.

However, the adjustment of the base station parameters may cause the instability of the mobile network. The main reason is that the adjustment of a base station parameter may cause the adjustment of its adjacent base stations, and the adjustment of the adjacent base stations will also cause the adjacent base stations of the adjacent base stations. This kind of network diffusion effect is difficult to ensure that network performance is in line with network changes in a timely manner, especially under the trend of network densification and high-speed user mobility.

Therefore, how to optimize network coverage more efficiently is an urgent problem to be solved.

Contents of the invention

In view of this, the embodiments of the present invention provide a network coverage optimization method and system, which optimize network coverage more efficiently based on an intelligent reflection surface.

On the one hand, the embodiments of the present invention provide a network coverage optimization method, including:

Obtain coverage problem areas and coverage problem area information;

Wherein, the coverage problem area information includes reference signal received power and spectrum efficiency of the coverage problem area;

Determine coverage compensation requirements according to the coverage problem area information;

Wherein, the coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; the coverage optimization strategies include base station optimization, intelligent reflection surface optimization, and joint optimization of base stations and intelligent reflection surfaces;

Based on the coverage optimization policy, coverage optimization is performed according to the coverage optimization requirement.

Optionally, the acquiring coverage problem areas and coverage problem area information includes:

Based on the abnormal events reported by the terminal, determine the coverage problem area;

Or, determine the coverage problem area according to the coverage performance index of the network statistics.

Optionally, the determining coverage compensation requirements according to the coverage problem area information includes:

When the coverage problem area is an area where a high-quality customer group is located, set a high-level coverage optimization requirement; otherwise, set a low-level coverage optimization requirement;

Wherein, the coverage optimization requirement includes a signal-to-noise ratio threshold or a spectrum efficiency threshold of the coverage problem area.

Optionally, the determining coverage compensation requirements according to the coverage problem area information includes:

When the coverage problem area is larger than a preset range, determine that the coverage optimization strategy is joint optimization of the base station and the smart reflector.

Optionally, the determining coverage compensation requirements according to the coverage problem area information includes:

When the coverage problem area is less than or equal to the preset range, determine the base station antenna adjustment parameter, and when the base station antenna adjustment parameter meets the coverage optimization requirement and the base station antenna adjustment parameter meets the preset threshold range, determine the coverage optimization The policy is optimized for the base station; otherwise, it is determined that the coverage optimization policy is optimized for the reflecting surface.

Optionally, the determining the configuration parameters of the smart reflective surface includes:

The average signal-to-noise ratio of the coverage problem area is maximized, and the position (d _i ^* , r ^* ) of the intelligent reflective surface is determined, the incident angle θ _i ^* and the phase Ф ^* are expressed as;

SNR _n ≥ SNR _thr

In the formula, SNR _thr represents the coverage optimization requirement of the SNR threshold of the coverage problem area; M represents the number of grids covering the problem area; SNR _n represents the SNR of the nth grid.

Optionally, the coverage optimization objective can also use other indicators, for example, to maximize the SNR of the minimum coverage problem area grid, then the configuration parameters of the IRS are determined by the following formula:

(d _i ^* ,r ^* ,θ _i ^* ,Ф ^* )＝maxmin(SNR _n )

SNR _n ≥ SNR _thr

Optionally, the acquiring the structural information of the smart reflective surface includes:

The coverage compensation response message sent by the controller to the base station carries the structural information of the smart reflector;

The base station receives the coverage compensation response message sent by the controller, and obtains the structure information of the smart reflective surface.

Optionally, the determining coverage compensation requirements according to the coverage problem area information includes:

sending a coverage compensation request message to the controller through the base station, where the coverage compensation request message carries the coverage problem area information;

The controller determines the coverage optimization strategy and the coverage optimization requirement based on the coverage problem area information, and sends the coverage compensation requirement to the base station through a coverage compensation response message.

On the other hand, an embodiment of the present invention provides a network coverage optimization system, including:

The first module is used to obtain coverage problem areas and coverage problem area information;

Wherein, the coverage problem area information includes reference signal received power and spectrum efficiency of the coverage problem area;

The second module is configured to determine coverage compensation requirements according to the coverage problem area information;

Wherein, the coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; the coverage optimization strategies include base station optimization, intelligent reflection surface optimization, and joint optimization of base stations and intelligent reflection surfaces;

The third module is configured to perform coverage optimization according to the coverage optimization requirements based on the coverage optimization strategy.

On the other hand, an embodiment of the present invention provides an electronic device, including a processor and a memory;

The memory is used to store programs;

The processor executes the program to implement the method as described above.

On the other hand, an embodiment of the present invention provides a computer-readable storage medium, the storage medium stores a program, and the program is executed by a processor to implement the aforementioned method.

The embodiment of the present invention also discloses a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above method.

In the embodiment of the present invention, the coverage problem area and coverage problem area information are first obtained; wherein the coverage problem area information includes the reference signal received power and spectrum efficiency of the coverage problem area; according to the coverage problem area information, the coverage compensation requirement is determined; wherein , the coverage compensation requirement includes a coverage optimization strategy and a coverage optimization requirement; the coverage optimization strategy includes base station optimization, intelligent reflection surface optimization, and joint optimization of a base station and an intelligent reflection surface; based on the coverage optimization strategy, according to the coverage optimization requirement Perform coverage optimization. The present invention identifies coverage problem areas and coverage problem area information and then adaptively selects base station optimization and/or intelligent reflection surface optimization to perform coverage compensation. Among them, through the deployment of intelligent reflective surface optimization, it is possible to reduce the adjustment of base station parameters, thereby avoiding the negative effects such as diffusion effects that may be brought about by traditional network optimization methods, and effectively enhancing network coverage.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained based on these drawings without creative effort.

FIG. 1 is a schematic flow diagram of a network coverage optimization method provided by an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a method for obtaining a coverage compensation response provided by an embodiment of the present invention;

FIG. 3 is a schematic flowchart of a coverage optimization method based on a coverage compensation response provided by an embodiment of the present invention;

FIG. 4 is a schematic flowchart of a method for coverage optimization based on IRS provided by an embodiment of the present invention;

FIG. 5 is a schematic diagram of coverage optimization based on IRS provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of a signaling flow for coverage optimization based on the IRS provided by an embodiment of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

On the one hand, referring to FIG. 1, an embodiment of the present invention provides a network coverage optimization method, including:

S100. Obtain coverage problem areas and coverage problem area information;

It should be noted that the coverage problem area information includes reference signal received power and spectrum efficiency of the coverage problem area. In some embodiments, the coverage problem area is determined based on the abnormal event reported by the terminal; or, the coverage problem area is determined according to the coverage performance index collected by the network.

Specifically, first determine coverage problem areas:

Coverage problem areas are formed by the locations of coverage exceptions. The terminal measures the signal quality between itself and the wireless base station, and records the establishment of links and services.

When the service of the terminal fails, record the time, location, and cause of the abnormal event. The service failure indicates that a coverage hole anomaly occurs at the location of the terminal. When the reference signal receiving power (Reference Signal Receiving Power, RSRP) measured by the terminal is less than the preset threshold, the time, location and cause of the abnormal event are recorded. For example, when the RSRP is less than the preset threshold -119dB, it indicates that there is basically no signal at the location of the terminal, which is a coverage hole anomaly; when the RSRP is less than the preset threshold -105dB, it indicates that the received signal strength at the terminal is not strong enough, which is a weak coverage anomaly.

The terminal reports the above abnormal events to the base station, and the base station determines the coverage problem area based on these abnormal events. In addition, the base station may also determine coverage problem areas according to statistics on other abnormal events, such as radio link failure (Radio Link Failure, RLF) and radio resource control (Radio Resource Control, RRC) reconstruction failure. The base station can also count coverage KPIs to determine coverage problem areas. For example, the data rate of the worst 5% of users served by the base station is lower than the preset threshold, and the location of the terminal is a weak coverage area.

S200. Determine coverage compensation needs according to the coverage problem area information;

It should be noted that coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; coverage optimization strategies include base station optimization, intelligent reflection surface optimization, and joint optimization of base stations and intelligent reflection surfaces.

In some embodiments, when the coverage problem area is an area where a high-quality customer group is located, a high-level coverage optimization requirement is set; otherwise, a low-level coverage optimization requirement is set; wherein, the coverage optimization requirement includes a signal-to-noise ratio threshold of the coverage problem area or Spectral efficiency threshold.

Specifically, if the coverage problem area is the area where the high-quality customer group is located, then the requirement setting for coverage optimization is relatively large, and the requirement for coverage optimization is the signal-to-noise ratio threshold or spectrum efficiency threshold of the coverage problem area; otherwise, the requirement setting for coverage optimization is relatively large. Small.

In some embodiments, when the coverage problem area is larger than the preset range, it is determined that the coverage optimization strategy is joint optimization of the base station and the smart reflector.

Specifically, if the coverage problem area is relatively large, and only relying on base station optimization or intelligent reflective surface optimization cannot meet the requirements of coverage optimization, then the coverage optimization strategy is determined to be joint optimization of base station and intelligent reflective surface.

In some embodiments, when the coverage problem area is less than or equal to the preset range, determine the base station antenna adjustment parameters, and when the base station antenna adjustment parameters meet the coverage optimization requirements and the base station antenna adjustment parameters meet the preset threshold range, determine the coverage optimization strategy as base station optimization; Otherwise, the coverage optimization strategy is determined to be reflective surface optimization.

Specifically, if the coverage problem area is relatively small, adjust the antenna parameters of the base station. If the coverage optimization requirements can be met and the antenna parameter adjustment range is within the preset threshold, then it is determined that the coverage optimization strategy is base station optimization; otherwise, the coverage optimization strategy is determined. The strategy for intelligent reflective surface optimization.

In some embodiments, the base station sends a coverage compensation request message to the controller, and the coverage compensation request message carries coverage problem area information; the controller determines the coverage optimization strategy and coverage optimization requirements based on the coverage problem area information, and carries the coverage compensation response message The coverage compensation requirement is sent to the base station.

In some specific embodiments, as shown in FIG. 2, obtaining a coverage compensation response includes:

For areas with coverage problems, before performing coverage optimization, it is necessary to obtain coverage compensation responses, including coverage optimization strategies and coverage optimization requirements. Coverage optimization strategies include base station optimization (BS-only), intelligent reflection surface (Intelligent Reflection Surface, IRS) optimization (IRS-only) and joint optimization (Joint BS-IRS). The coverage optimization requirement includes a Signal-to-Noise Ratio (SNR) threshold and a spectrum efficiency threshold in a coverage problem area. The policy of coverage optimization and the requirement of coverage optimization can be obtained by a controller, such as an Operation Administration and Maintenance (OAM) system or a SON server; or the base station can determine according to the coverage area.

After the base station determines the coverage problem area, it sends a coverage compensation demand request message to the controller, carrying coverage problem area information in the message, and the coverage problem area information includes RSRP and spectrum efficiency of the coverage problem area. where spectral efficiency is the achievable data rate divided by the bandwidth used. is a well-known concept in the industry and can be obtained statistically from base stations.

The controller determines the coverage compensation response for the coverage problem area according to the received coverage problem area information, and sends it to the base station.

The controller can use the network operation strategy and coverage problem area information. For example, the network operator believes that the coverage problem area is a high-quality customer group area, and the coverage problem area is relatively large. Only relying on base station optimization or IRS optimization cannot guarantee user experience, then The strategy for determining the coverage optimization is joint optimization; the requirements for coverage optimization, such as the signal-to-noise ratio threshold or the spectral efficiency threshold of the coverage problem area, can be larger.

S300. Based on the coverage optimization strategy, perform coverage optimization according to coverage optimization requirements;

It should be noted that, in some embodiments, the coverage problem area is gridded to determine the set of reflection angles of the smart reflective surface; the structural information of the smart reflective surface is obtained, and the structural information includes the width of the smart reflective surface, The length and the number of units; based on the set of reflection angles of the intelligent reflective surface and the structural information, determine the configuration parameters of the intelligent reflective surface, and perform coverage optimization.

Wherein, in some embodiments, determining the configuration parameters of the intelligent reflective surface includes:

表达式为；Maximize the average signal-to-noise ratio of the coverage problem area, and determine the position (d _i ^* , r ^* ) of the smart reflector, the angle of incidence θ _i ^* and the phase

The expression is;

SNR _n ≥ SNR _thr

In the formula, SNR _thr represents the coverage optimization requirement of the SNR threshold of the coverage problem area; M represents the number of grids covering the problem area; SNR _n represents the SNR of the nth grid.

The coverage optimization objective can also use other indicators, for example, to maximize the SNR of the minimum coverage problem area grid, the configuration parameters of the IRS are determined by the following formula:

(d _i ^* ,r ^* ,θ _i ^* ,Ф ^* )＝maxmin(SNR _n )

SNR _n ≥ SNR _thr

Specifically, in some specific embodiments, as shown in FIG. 3, coverage optimization is performed based on coverage compensation requirements, including:

Different coverage problem areas may have different optimization strategies, and corresponding coverage compensation needs to be performed according to the optimization strategy.

If the coverage optimization strategy is BS-only, the base station adjusts its antenna parameters, such as the azimuth angle, downtilt angle, and transmission power of the antenna, to cover the coverage problem area according to the coverage optimization requirements of the coverage problem area.

If the coverage optimization strategy is IRS-only, the base station does not adjust its antenna parameters, and the base station performs IRS deployment and parameter configuration according to the coverage optimization requirements of the coverage problem area, and performs the coverage optimization of the coverage problem area by controlling the IRS.

If the coverage optimization strategy is neither BS-only nor IRS-only, the base station jointly adjusts the antenna parameters of the base station and the parameters of the IRS, and performs coverage optimization for the coverage problem area by controlling the base station and the IRS.

Among them, the method of coverage optimization based on IRS is shown in Figure 4, and the specific steps are as follows:

1) Cover the problem area with rasterization, and obtain the set of IRS reflection angles;

Rasterize the coverage problem area, as shown in Figure 5, under the given distance d _i from the base station to the IRS, a certain grid distance r from the IRS to the coverage problem area, and the incident angle θ _i of the base station signal to the IRS, determine A set of IRS reflection angles covering the problem area θ _r ={θ _rn ,n=1,2,...,M}, where M is the number of grids. Among them, θ _rn is the reflection angle of the nth grid, which means that the IRS points to the direction of grid n, and a and b are the size of the IRS.

2) Obtain the size of the IRS;

The IRS sizes a and b determine the reflection capability of the IRS, including beam bandwidth, beam scanning range and beam gain. The base station determines the size of the IRS according to the coverage problem area and the coverage optimization requirement; or obtains it from the controller. Wherein, based on the method for obtaining the coverage compensation requirement in FIG. 3 , the coverage compensation response message may carry the IRS size a and b information.

3) Determine the configuration parameters of the IRS

Based on IRS reflection, the signal f _n (s) received by grid n covering the problem area is:

为基站经过IRS某个单元到覆盖问题区域栅格n的级联信道增益，

为基站到覆盖问题区域栅格n的归一化信道。Among them, s is the transmitted signal of the base station, ω is the additive noise with variance σ ² , β _sd is the channel gain from the base station to the grid n in the coverage problem area,

is the concatenated channel gain from the base station to the coverage problem area grid n through a certain unit of the IRS,

is the normalized channel from the base station to grid n covering the problem area.

Among them, G _t and G _r are the transmit antenna gain of the base station and the receive antenna gain of the coverage problem area grid n, respectively, and Na and _{N b are} the number of units on both sides of the IRS.

为：Normalized channel from base station to IRS

for:

The normalized channel H _rd of the IRS to grid n covering the problem area is:

The phase Ф of each unit of the IRS is:

By adjusting the phase of each unit of IRS, the maximum received signal strength of grid n can be obtained. Therefore, the signal-to-noise ratio for raster n is:

Among them, P _s is the signal power transmitted by the base station, and σ ² is the noise power.

Based on the coverage optimization requirement, the configuration parameters of the IRS are determined, and the configuration parameters include the position (d _i ^* , r ^* ), incident angle θ _i ^* and phase Φ ^* of the IRS. When the coverage optimization requirement is the SNR threshold and the coverage optimization goal is to maximize the average SNR of the coverage problem area, the configuration parameters of the IRS are determined by the following formula:

SNR _n ≥ SNR _thr

The coverage optimization objective can also use other indicators, for example, to maximize the SNR of the minimum coverage problem area grid, the configuration parameters of the IRS are determined by the following formula:

(d _i ^* ,r ^* ,θ _i ^* ,Ф ^* )＝maxmin(SNR _n )

SNR _n ≥ SNR _thr

The signaling flow of coverage optimization based on the IRS is shown in Figure 6 .

Step 1: The terminal perceives the wireless environment

Measure the channel environment and service environment, including the measured RSRP, link connection failure, service failure and other events.

Step 2: The base station counts the information reported by the terminal, and determines the areas with coverage problems and the parameters that need to deploy IRS

1) Count the locations of coverage holes and weak coverage, and determine coverage problem areas;

2) Based on coverage optimization requirements, determine the parameters to be deployed for IRS, including location, incident angle, and phase.

Step 3: The base station controls the IRS according to the configuration information required by the IRS

1) Generate the required signal beam according to the incident angle of the IRS;

2) Control the reflected beam of the IRS according to the phase of the IRS.

To sum up, the present invention proposes a system and method for intelligent optimization of wireless network coverage. By identifying coverage problem areas and gridding, self-optimization of base stations and/or intelligent reflection surface optimization are adaptively selected for cover compensation. Solve the problem of coverage hole or weak coverage under stability. Deploying IRS and parameter configuration does not need to be adjusted or only adjusts base station parameters when necessary, thus avoiding the negative effects such as diffusion effects that may be brought about by traditional network optimization methods, and effectively enhancing network coverage.

On the other hand, an embodiment of the present invention provides a system for network coverage optimization, including: a first module, configured to obtain coverage problem areas and coverage problem area information; wherein, the coverage problem area information includes the reference signal reception of the coverage problem areas Power and spectrum efficiency; the second module is used to determine coverage compensation requirements according to coverage problem area information; wherein, coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; coverage optimization strategies include base station optimization, intelligent reflector optimization, and base station and Joint optimization of intelligent reflective surfaces; the third module is used to perform coverage optimization based on the coverage optimization strategy and according to the coverage optimization requirements.

The content of the method embodiment of the present invention is applicable to the system embodiment. The functions realized by the system embodiment are the same as those of the method embodiment above, and the beneficial effects achieved are also the same as those achieved by the above method.

Another aspect of the embodiments of the present invention also provides an electronic device, including a processor and a memory;

The memory is used to store programs;

The processor executes the program to implement the method as described above.

The content of the method embodiment of the present invention is applicable to the embodiment of the electronic device. The functions realized by the embodiment of the electronic device are the same as those of the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method.

Another aspect of the embodiments of the present invention also provides a computer-readable storage medium, where the storage medium stores a program, and the program is executed by a processor to implement the aforementioned method.

The content of the method embodiment of the present invention is applicable to the embodiment of the computer-readable storage medium. The functions realized by the embodiment of the computer-readable storage medium are the same as those of the above-mentioned method embodiment, and the beneficial effect achieved is the same as that achieved by the above-mentioned method. The effect is also the same.

The embodiment of the present invention also discloses a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above method.

In some alternative implementations, the functions/operations noted in the block diagrams may occur out of the order noted in the operational diagrams. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/operations involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flow presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.

Furthermore, although the invention has been described in the context of functional modules, it should be understood that one or more of the described functions and/or features may be integrated into a single physical device and/or unless stated to the contrary. or software modules, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to understand the present invention. Rather, given the attributes, functions and internal relationships of the various functional blocks in the devices disclosed herein, the actual implementation of the blocks will be within the ordinary skill of the engineer. Accordingly, those skilled in the art can implement the present invention set forth in the claims without undue experimentation using ordinary techniques. It is also to be understood that the particular concepts disclosed are illustrative only and are not intended to limit the scope of the invention which is to be determined by the appended claims and their full scope of equivalents.

If the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes. .

The logic and/or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium, For use with an instruction execution device, device or device (such as a computer-based device, a device including a processor, or other devices that can fetch instructions from an instruction execution device, device or device and execute instructions), or in conjunction with these instruction execution devices, devices or equipment used. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution device, device or device.

More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), Read Only Memory (ROM), Erasable and Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, since the program can be read, for example, by optically scanning the paper or other medium, followed by editing, interpretation or other suitable processing if necessary. processing to obtain the program electronically and store it in computer memory.

It should be understood that various parts of the present invention can be realized by hardware, software, firmware or their combination. In the above-described embodiments, various steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques known in the art: Discrete logic circuits, ASICs with suitable combinational logic gates, Programmable Gate Arrays (PGAs), Field Programmable Gate Arrays (FPGAs), etc.

In the description of this specification, descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific examples", or "some examples" mean that specific features described in connection with the embodiment or example , structure, material or characteristic is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although the embodiments of the present invention have been shown and described, those skilled in the art can understand that various changes, modifications, substitutions and modifications can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the invention is defined by the claims and their equivalents.

The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the described embodiments, and those skilled in the art can also make various equivalent deformations or replacements without violating the spirit of the present invention. These equivalent modifications or replacements are all within the scope defined by the claims of the present invention.

Claims (10)

1. A network coverage optimization method, characterized in that, comprising: Obtain coverage problem areas and coverage problem area information; Wherein, the coverage problem area information includes reference signal received power and spectrum efficiency of the coverage problem area; Determine coverage compensation requirements according to the coverage problem area information; Wherein, the coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; the coverage optimization strategies include base station optimization, intelligent reflection surface optimization, and joint optimization of base stations and intelligent reflection surfaces; Based on the coverage optimization policy, coverage optimization is performed according to the coverage optimization requirement. 2. A kind of network coverage optimization method according to claim 1, is characterized in that, described acquisition coverage problem area and coverage problem area information comprise: Based on the abnormal events reported by the terminal, determine the coverage problem area; Or, determine the coverage problem area according to the coverage performance index of the network statistics. 3. A kind of network coverage optimization method according to claim 1, it is characterized in that, described according to described coverage problem area information, determine coverage compensation demand, comprise: When the coverage problem area is an area where a high-quality customer group is located, set a high-level coverage optimization requirement; otherwise, set a low-level coverage optimization requirement; Wherein, the coverage optimization requirement includes a signal-to-noise ratio threshold or a spectrum efficiency threshold of the coverage problem area. 4. A method for optimizing network coverage according to claim 1, wherein said determining coverage compensation requirements according to said coverage problem area information comprises: When the coverage problem area is larger than a preset range, determine that the coverage optimization strategy is joint optimization of the base station and the smart reflector. 5. A method for network coverage optimization according to claim 1, wherein said determining coverage compensation requirements according to said coverage problem area information comprises: When the coverage problem area is less than or equal to the preset range, determine the base station antenna adjustment parameter, and when the base station antenna adjustment parameter meets the coverage optimization requirement and the base station antenna adjustment parameter meets the preset threshold range, determine the coverage optimization The policy is optimized for the base station; otherwise, it is determined that the coverage optimization policy is optimized for the reflecting surface. 6. A kind of network coverage optimization method according to claim 1, is characterized in that, based on described intelligent reflection surface optimization, carries out coverage optimization, comprising: Rasterize the coverage problem area, and determine the set of reflection angles of the intelligent reflection surface; Obtaining structural information of the intelligent reflective surface, the structural information including the width, length and number of units of the intelligent reflective surface; Based on the set of reflection angles of the intelligent reflective surface and the structural information, configuration parameters of the intelligent reflective surface are determined, and coverage optimization is performed. 7. A kind of network coverage optimization method according to claim 6, is characterized in that, described determining the configuration parameter of described intelligent reflection surface, comprises: Maximize the average signal-to-noise ratio of the coverage problem area, and determine the position (d _i ^* , r ^* ) of the smart reflector, the angle of incidence θ _i ^* and the phase

The expression is;

SNR _n ≥ SNR _thr In the formula, SNR _thr represents the coverage optimization requirement of the SNR threshold of the coverage problem area; M represents the number of grids covering the problem area; SNR _n represents the SNR of the nth grid. 8. A method for network coverage optimization according to claim 6, wherein said acquiring the structural information of said intelligent reflective surface comprises: The coverage compensation response message sent by the controller to the base station carries the structural information of the smart reflector; The base station receives the coverage compensation response message sent by the controller, and obtains the structure information of the smart reflective surface. 9. A method for network coverage optimization according to claim 1, wherein said determining coverage compensation requirements according to said coverage problem area information comprises: sending a coverage compensation request message to the controller through the base station, where the coverage compensation request message carries the coverage problem area information; The controller determines the coverage optimization strategy and the coverage optimization requirement based on the coverage problem area information, and sends the coverage compensation requirement to the base station through a coverage compensation response message. 10. A network coverage optimization system, characterized in that, comprising: The first module is used to obtain coverage problem areas and coverage problem area information; Wherein, the coverage problem area information includes reference signal received power and spectrum efficiency of the coverage problem area; The second module is configured to determine coverage compensation requirements according to the coverage problem area information; Wherein, the coverage compensation requirements include coverage optimization strategies and coverage optimization requirements; the coverage optimization strategies include base station optimization, intelligent reflection surface optimization, and joint optimization of base stations and intelligent reflection surfaces; The third module is configured to perform coverage optimization according to the coverage optimization requirements based on the coverage optimization strategy.

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