Indoor distributed antenna parameter optimization method, device, equipment, medium and product

Abstract

The invention discloses a parameter optimization method and device for an indoor distributed antenna, equipment, a medium and a product, and belongs to the technical field of communication. The method comprises the following steps: discretizing antenna configuration parameters to obtain multiple groups of antenna parameter initial values; based on each group of antenna parameter initial values, determining reference signal receiving powers of the plurality of receiving point locations, and determining fitness function values corresponding to each group of antenna parameter initial values according to a first number of the plurality of receiving point locations and a second number of target receiving point locations in the plurality of receiving point locations; and according to the fitness function value corresponding to each group of antenna parameter initial values, carrying out selection, intersection and mutation operation on the multiple groups of antenna parameter initial values until a preset termination condition is met, and obtaining an antenna parameter target value. Through the mode, the antenna parameter target value of the indoor distributed antenna can be quickly determined, and the signal quality of a network coverage area is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of communication technology, and in particular to a method, device, equipment, medium and product for optimizing parameters of an indoor distributed antenna. Background Art

[0002] In large buildings such as office buildings, shopping malls or hospitals, indoor distribution system antennas can be used to improve the coverage of Wi-Fi or mobile signals and ensure stable signal transmission throughout the indoor area.

[0003] Due to the dense and complex distribution of indoor distributed antennas, network coverage optimization usually relies on testers to repeatedly adjust the adjustable parameters of the antennas based on experience. This method is time-consuming and difficult to ensure that the optimal parameters are found, resulting in unsatisfactory signal quality in the network coverage area. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment, medium and product for optimizing parameters of an indoor distributed antenna, so as to at least solve the problem that parameters of the indoor distributed antenna are difficult to adjust and the signal quality in the network coverage area is not ideal.

[0005] In order to solve the above technical problems, this application is implemented as follows: In a first aspect, an embodiment of the present application provides a parameter optimization method for an indoor distributed antenna, comprising: discretizing antenna configuration parameters to obtain multiple groups of antenna parameter initial values; based on each group of antenna parameter initial values, determining the reference signal receiving power of multiple receiving points, and determining the fitness function value corresponding to each group of antenna parameter initial values ​​according to a first number of the multiple receiving points and a second number of target receiving points among the multiple receiving points; wherein the target receiving point is a receiving point among the multiple receiving points whose reference signal receiving power is greater than a preset power threshold; according to the fitness function value corresponding to each group of antenna parameter initial values, selecting, crossing, and mutating the multiple groups of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value.

[0006] In the second aspect, an embodiment of the present application provides a parameter optimization device for an indoor distributed antenna, including: a discretization module, used to discretize antenna configuration parameters to obtain multiple groups of antenna parameter initial values; a determination module, used to determine the reference signal receiving power of multiple receiving points based on each group of antenna parameter initial values, and determine the fitness function value corresponding to each group of antenna parameter initial values ​​according to a first number of the multiple receiving points and a second number of target receiving points among the multiple receiving points; wherein the target receiving point is a receiving point among the multiple receiving points whose reference signal receiving power is greater than a preset power threshold; an optimization module, used to select, crossover, and mutate the multiple groups of antenna parameter initial values ​​according to the fitness function values ​​corresponding to each group of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in the first aspect above are implemented.

[0008] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect above are implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the steps of the method described in the first aspect above.

[0010] In the embodiment of the present application, the antenna configuration parameters are discretized to obtain multiple groups of antenna parameter initial values; based on each group of antenna parameter initial values, the reference signal receiving power of multiple receiving points is determined, and the fitness function value corresponding to each group of antenna parameter initial values ​​is determined according to the first number of multiple receiving points and the second number of target receiving points in the multiple receiving points; according to the fitness function value corresponding to each group of antenna parameter initial values, multiple groups of antenna parameter initial values ​​are selected, crossed, and mutated until the preset termination condition is met to obtain the antenna parameter target value. In this way, the antenna parameter target value of the indoor distributed antenna can be quickly determined to improve the signal quality of the network coverage area. It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0012] Figure 1 A schematic diagram of a process flow of a parameter optimization method for an indoor distributed antenna provided in an embodiment of the present application is shown; Figure 2 A schematic diagram of antenna position coding provided in an embodiment of the present application is shown; Figure 3 A schematic diagram of a process for obtaining a target value of an antenna parameter provided in an embodiment of the present application is shown; Figure 4 An example diagram of a single-point crossover provided by an embodiment of the present application is shown; Figure 5 An example diagram showing basic bit variation provided by an embodiment of the present application is shown; Figure 6 A schematic diagram of the structure of a parameter optimization device for indoor distributed antennas provided in an embodiment of the present application is shown; Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0013] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0014] Figure 1 A flow chart of the parameter optimization method for indoor distributed antennas provided in an embodiment of the present application is shown. The execution subject of the method may be a terminal device or a server, wherein the terminal device may be a device such as a personal computer, or a mobile terminal device such as a mobile phone or a tablet computer, and the terminal device may be a terminal device used by a user. The server may be an independent server, or a server cluster composed of multiple servers, and the server may be a background server for a certain business, or a background server for a certain platform or application (for example, a network management platform, a wireless network simulation tool, a signal strength analysis system, etc.). In the embodiment of the present application, the execution subject is taken as an example to illustrate. For the case of the terminal device, it can be processed according to the following related content, which will not be repeated here. As shown in the figure, the parameter optimization method 100 for indoor distributed antennas may include the following steps: Step 101: discretize antenna configuration parameters to obtain multiple groups of antenna parameter initial values.

[0015] Among them, the antenna configuration parameters include the antenna's azimuth angle, downtilt angle, antenna position information, gain, etc.

[0016] In a specific implementation, the antenna configuration parameters are discretized to obtain multiple sets of antenna parameter initial values. For example, the azimuth angle of the antenna is discretized into 0°, 45°, 90°, 135°, and 180°, and the downtilt angle of the antenna is discretized into 0°, 5°, 10°, 15°, and 20°. The antenna position information is encoded and discretized into 0, 1, and 2. These discretized values ​​are combined to obtain multiple sets of antenna parameter initial values.

[0017] Step 102: Based on the initial values ​​of each group of antenna parameters, determine the reference signal receiving power of multiple receiving points, and determine the fitness function value corresponding to the initial values ​​of each group of antenna parameters according to the first number of the multiple receiving points and the second number of target receiving points among the multiple receiving points.

[0018] The target receiving point is a receiving point among the multiple receiving points whose reference signal receiving power is greater than a preset power threshold.

[0019] In a specific implementation, multiple receiving points may be set in the network coverage area, and the reference signal received power (RSRP) of each receiving point may be determined according to the initial value of each group of antenna parameters. For example, the RSRP of each receiving point may be determined according to a path loss model. A target receiving point whose RSRP is greater than a preset power threshold is determined, and a fitness function value corresponding to the initial value of each group of antenna parameters is determined according to a first number of the multiple receiving points and a second number of the target receiving points. For example, the fitness function value corresponding to the initial value of the i-th group of antenna parameters is ,in, R is a first number of the plurality of receiving points, R th The second number of target receiving points.

[0020] Step 103: According to the fitness function value corresponding to each group of antenna parameter initial values, the multiple groups of antenna parameter initial values ​​are selected, crossed, and mutated until a preset termination condition is met to obtain the antenna parameter target value.

[0021] In a specific implementation, a better antenna parameter combination is selected according to the fitness function corresponding to each group of antenna parameter initial values, and the selected antenna parameter combination is cross-operated to generate a new antenna parameter combination; a mutation operation is performed on the new parameter combination generated by the cross-operation to introduce randomness and avoid falling into a local optimum until a preset termination condition is met, such as reaching the maximum number of iterations, or the change in the fitness function value is less than a preset threshold, or the fitness function value is within a preset value range, and the optimal antenna parameter combination is determined as the antenna parameter target value.

[0022] In this way, the antenna parameter target values ​​of the indoor distributed antennas can be quickly determined to improve the signal quality of the network coverage area.

[0023] In a possible implementation, the antenna configuration parameters include antenna position information, azimuth angle, and downtilt angle; in the above step 101, the antenna configuration parameters are discretized to obtain multiple groups of antenna parameter initial values, including: Determine multiple antenna position information according to the antenna layout rule of the target area, encode the multiple antenna position information to obtain antenna position code; Discretize the first value range of the azimuth angle to obtain an azimuth angle code; Discretizing the second value range of the downtilt angle to obtain a downtilt angle code; The antenna position coding, azimuth coding and downtilt coding are combined to obtain the multiple groups of antenna parameter initial values.

[0024] In the embodiment of the present application, according to the antenna layout rule of the target area, multiple antenna position information is determined, such as Figure 2 As shown in FIG. 2 , the target area 201 in the plan view of the building is an area for placing antennas. The target area 201 is used to set the positions of antennas at certain intervals to obtain multiple antenna position information 202, and the coordinates of each antenna position information are recorded. , and then encode each position coordinate to get the antenna position code ; Discretize the first value range of the azimuth angle to obtain the azimuth angle code ; Discretize the second value range of the downtilt angle to obtain the downtilt angle code , the above antenna position coding, azimuth coding and downtilt coding are combined to obtain multiple groups of antenna parameter initial values, each group of antenna parameter initial values ​​is a solution.

[0025] Assumptions is the solution space of all states, where C i (i=1, , N) represents a set of antenna parameters, which are composed of the above parameters The components correspond to the position, direction angle, and downtilt angle of the antenna. Fitness function F It can be the ratio of the area where the reference signal received power (RSRP) exceeds the preset power threshold to the total area within the network coverage area. The optimization problem of antenna parameters can be expressed as: ; ; The above problem belongs to combinatorial optimization problem. The optimal solution to the problem can be obtained by substituting the finite states into the objective function one by one. However, the exhaustive method requires exponential complexity to complete, which is time-consuming and laborious. Therefore, a multi-objective optimization method, such as a genetic algorithm, can be used to determine the target value of the antenna parameters.

[0026] Among them, the ratio of the area in the network coverage area where the reference signal receiving power exceeds the preset power threshold to the total area can be determined according to the ratio between the second number of target receiving points and the first number of multiple receiving points.

[0027] In a possible implementation, in the above step 102, based on each group of antenna parameter initial values, determining the reference signal received powers of multiple receiving points includes: Discretize the preset network coverage area to obtain multiple receiving points; For each of the receiving points, the reference signal receiving power of the receiving point is determined according to each group of antenna parameter initial values ​​and the receiving point.

[0028] In the embodiment of the present application, the preset network coverage area can be discretized at a certain interval to obtain R receiving points, and the reference signal receiving power P of each receiving point is calculated according to the initial value of each group of antenna parameters. R .

[0029] The above-mentioned determining the reference signal received power of the receiving point according to each group of antenna parameter initial values ​​and the receiving point includes: Determine multiple transmitting points based on initial values ​​of each set of antenna parameters; The reference signal receiving power of the receiving point is determined according to the signal transmission distance between the multiple transmitting points and the receiving point.

[0030] In the embodiment of the present application, the reference signal receiving power P of the receiving point can be determined by the following method: R : ; in, is the transmission power, For the mThe directional gain of the transmitting antenna of the strip ray, For the m The receiving antenna directivity gain of the strip ray, Indicates m The first ray n Secondary reflection coefficient, Indicates m The first ray l Secondary transmission coefficient, For the m The distance attenuation factor of the ray, is the wavelength, d m Indicates m The actual distance traveled by the ray: ; in,( x 1, y 1, z 1) is the coordinate of the launch point, ( x 2, y 2, z 2) is the coordinate of the receiving point.

[0031] In a possible implementation, in the above step 103, according to the fitness function value corresponding to each group of the initial values ​​of the antenna parameters, the multiple groups of initial values ​​of the antenna parameters are selected, crossed, and mutated until a preset termination condition is met to obtain the target value of the antenna parameters, including: Take each group of antenna parameter initial values ​​as an individual to form an initial population; Determining the next generation of individuals in the initial population according to the fitness function value corresponding to each individual in the initial population; Performing crossover and mutation operations on the next generation individuals to obtain new individuals; Update the initial population according to the new individuals to obtain the next generation population; Determine the fitness function value of each individual in the next generation population until the preset termination condition is met, and obtain the target individual in the next generation population whose fitness function value is greater than the preset threshold; The antenna parameter value corresponding to the target individual is determined as the antenna parameter target value.

[0032] The above-mentioned crossover and mutation operations are performed on the next generation individuals to obtain new individuals, including: Selecting a crossover individual from the next generation individuals according to the crossover probability; According to a preset crossover rule, a crossover operation is performed on the crossover individuals to obtain a combined individual; According to the preset mutation rule, the combination individual is mutated to obtain the new individual.

[0033] In the present application embodiment, Figure 3 As shown in , the above-mentioned method for obtaining the target value of the antenna parameter may include the following steps: Step 301: Population initialization: taking each group of antenna parameter initial values ​​as an individual to form an initial population; Step 302: Calculate the fitness function: calculate the fitness function value corresponding to each individual in the initial population; Step 303: Selection operator: Determine the next generation of individuals in the initial population according to the fitness function value corresponding to each individual in the initial population. For example, a proportional selection strategy can be adopted so that individuals with high fitness function values ​​are selected as the next generation of individuals. i The probability of being selected is: ; Step 304: Crossover operator: using the crossover probability P c Select several next generation individuals as parent individuals for crossover pairing, and perform crossover operations on the parent individuals according to the preset crossover rules to generate combined individuals. The crossover rules include single-point crossover and two-point crossover. Take single-point crossover as an example, Figure 4 As shown, the parent individuals selected are exchanged at the crossover point A and B Genes of new combinations and .

[0034] Step 305: Mutation operator: In order to maintain the diversity of individuals in the population and prevent falling into the local optimum, the mutation probability P m Randomly determine the mutation individual and perform the mutation operation according to the preset mutation rules, where the mutation rules include gene mutation and basic bit mutation. Figure 5 As shown, through the individual A Perform basic bit mutation operations to obtain individual .

[0035] Step 306: Iteration termination: If the preset termination condition is met, the iteration is terminated and the antenna parameter target value is output; otherwise, go to the above step 302.

[0036] Figure 6 The schematic diagram of the structure of the parameter optimization device for indoor distributed antennas provided in the embodiment of the present application is shown. The parameter optimization device for indoor distributed antennas implements the following Figure 1 In the embodiment shown, all or part of the contents, the parameter optimization device 600 includes: The discrete module 610 is used to discretize the antenna configuration parameters to obtain multiple groups of antenna parameter initial values; The determination module 620 is used to determine the reference signal received power of multiple receiving points based on each group of antenna parameter initial values, and determine the fitness function value corresponding to each group of antenna parameter initial values ​​according to the first number of the multiple receiving points and the second number of target receiving points among the multiple receiving points; wherein the target receiving point is a receiving point among the multiple receiving points whose reference signal received power is greater than a preset power threshold; The optimization module 630 is used to select, crossover and mutate the multiple groups of antenna parameter initial values ​​according to the fitness function value corresponding to each group of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value.

[0037] In a possible implementation, the antenna configuration parameters include antenna position information, azimuth angle, and downtilt angle; the discrete module 610, when used to discretize the antenna configuration parameters to obtain multiple groups of antenna parameter initial values, is specifically used to: Determine multiple antenna position information according to the antenna layout rule of the target area, encode the multiple antenna position information to obtain antenna position code; Discretize the first value range of the azimuth angle to obtain an azimuth angle code; Discretizing the second value range of the downtilt angle to obtain a downtilt angle code; The antenna position coding, azimuth coding and downtilt coding are combined to obtain the multiple groups of antenna parameter initial values.

[0038] In a possible implementation, the determination module 620, when used to determine the reference signal received powers of multiple receiving points based on each group of antenna parameter initial values, is specifically used to: Discretize the preset network coverage area to obtain multiple receiving points; For each of the receiving points, the reference signal receiving power of the receiving point is determined according to each group of antenna parameter initial values ​​and the receiving point.

[0039] The determination module 620, when used to determine the reference signal received power of the receiving point according to each group of antenna parameter initial values ​​and the receiving point, is specifically used to: Determine multiple transmitting points based on initial values ​​of each set of antenna parameters; The reference signal receiving power of the receiving point is determined according to the signal transmission distance between the multiple transmitting points and the receiving point.

[0040] In a possible implementation, the optimization module 630, when used to select, cross, and mutate the multiple groups of antenna parameter initial values ​​according to the fitness function value corresponding to each group of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value, is specifically used to: Take each group of antenna parameter initial values ​​as an individual to form an initial population; Determining the next generation of individuals in the initial population according to the fitness function value corresponding to each individual in the initial population; Performing crossover and mutation operations on the next generation individuals to obtain new individuals; Update the initial population according to the new individuals to obtain the next generation population; Determine the fitness function value of each individual in the next generation population until the preset termination condition is met, and obtain the target individual in the next generation population whose fitness function value is greater than the preset threshold; The antenna parameter value corresponding to the target individual is determined as the antenna parameter target value.

[0041] The optimization module 630, when used to perform crossover and mutation operations on the next generation individuals to obtain new individuals, is specifically used to: Selecting a crossover individual from the next generation individuals according to the crossover probability; According to a preset crossover rule, the crossover individuals are combined to obtain a combined individual; The combined individuals are mutated according to a preset mutation rule to obtain the new individuals.

[0042] The embodiment of the present application provides a parameter optimization device for an indoor distributed antenna, including a discrete module, a determination module and an optimization module; the discrete module discretizes the antenna configuration parameters to obtain multiple groups of antenna parameter initial values; the determination module determines the reference signal receiving power of multiple receiving points based on each group of antenna parameter initial values, and determines the fitness function value corresponding to each group of antenna parameter initial values ​​according to the first number of the multiple receiving points and the second number of target receiving points in the multiple receiving points; the optimization module selects, crosses and mutates the multiple groups of antenna parameter initial values ​​according to the fitness function value corresponding to each group of antenna parameter initial values ​​until the preset termination condition is met to obtain the antenna parameter target value. In this way, the antenna parameter target value of the indoor distributed antenna can be quickly determined to improve the signal quality of the network coverage area.

[0043] Figure 7The hardware structure diagram of the electronic device provided by the embodiment of the present application is shown. Referring to the figure, at the hardware level, the electronic device 700 includes a processor 710, and optionally, includes an internal bus 720, a network interface 730, and a memory 740. Among them, the memory 740 may include a memory 741, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory 742 (non-volatile memory), such as at least one disk storage, etc. Of course, the electronic device 700 may also include hardware required for other services.

[0044] The processor 710, the network interface 730 and the memory may be interconnected via an internal bus 720, which may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0045] The memory 740 stores programs. Specifically, the programs may include program codes, and the program codes include computer operation instructions. The memory 740 may include a memory 741 and a non-volatile memory 742 , and provide instructions and data to the processor 710 .

[0046] The processor 710 reads the corresponding computer program from the non-volatile memory 742 into the memory and then runs it, forming a device for locating the target user at the logical level. The processor 710 executes the program stored in the memory and specifically performs: Figure 1 or Figure 3 The method disclosed in the illustrated embodiment realizes the functions and beneficial effects of each method described in the foregoing method embodiments, which will not be described in detail here.

[0047] The above application Figure 1 or Figure 3The method disclosed in the illustrated embodiment can be applied to the processor 710 or implemented by the processor 710. The processor 710 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 710. The above processor 710 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0048] The computer device can also execute the methods described in the foregoing method embodiments, and realize the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0049] Of course, in addition to software implementation, the electronic device 700 of the present application does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0050] The embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable medium stores one or more programs, and when the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes Figure 1 or Figure 3 The method disclosed in the illustrated embodiment realizes the functions and beneficial effects of each method described in the foregoing method embodiments, which will not be described in detail here.

[0051] The computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0052] Furthermore, an embodiment of the present application also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the following process is implemented: Figure 1 or Figure 3 The method disclosed in the illustrated embodiment realizes the functions and beneficial effects of each method described in the foregoing method embodiments, which will not be described in detail here.

[0053] The embodiments of the present application can be applied to various electronic device collaboration or interconnection scenarios, including: collaboration and interconnection between mobile phones and laptops / tablet computers; collaboration and interconnection between mobile terminals and smart TVs / displays; collaboration and interconnection between mobile phones or tablet computers and in-car entertainment systems; collaboration and interconnection between mobile terminals and smart conference systems, etc., so as to meet the needs of users in various scenarios such as smart homes, smart offices, and smart travel.

[0054] In short, the above is only a preferred embodiment of the present application and does not limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0055] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0056] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0057] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0058] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

Claims

1. A parameter optimization method for indoor distributed antennas, characterized in that: include: Discretize the antenna configuration parameters to obtain multiple groups of antenna parameter initial values; Based on each group of antenna parameter initial values, determine the reference signal receiving power of multiple receiving points, and determine the fitness function value corresponding to each group of antenna parameter initial values ​​according to the first number of the multiple receiving points and the second number of target receiving points among the multiple receiving points; wherein the target receiving point is a receiving point among the multiple receiving points whose reference signal receiving power is greater than a preset power threshold; According to the fitness function value corresponding to each group of the antenna parameter initial values, the multiple groups of antenna parameter initial values ​​are selected, crossed, and mutated until a preset termination condition is met to obtain the antenna parameter target value.

2. The method according to claim 1, characterized in that The antenna configuration parameters include antenna position information, azimuth angle and downtilt angle; the antenna configuration parameters are discretized to obtain multiple groups of antenna parameter initial values, including: Determine multiple antenna position information according to the antenna layout rule of the target area, encode the multiple antenna position information to obtain antenna position code; Discretize the first value range of the azimuth angle to obtain an azimuth angle code; Discretizing the second value range of the downtilt angle to obtain a downtilt angle code; The antenna position coding, azimuth coding and downtilt coding are combined to obtain the multiple groups of antenna parameter initial values.

3. The method according to claim 1, characterized in that The determining of the reference signal receiving power of multiple receiving points based on each group of antenna parameter initial values ​​includes: Discretize the preset network coverage area to obtain multiple receiving points; For each of the receiving points, the reference signal receiving power of the receiving point is determined according to each group of antenna parameter initial values ​​and the receiving point.

4. The method according to claim 3, characterized in that The step of determining the reference signal received power of the receiving point according to each group of antenna parameter initial values ​​and the receiving point includes: Determine multiple transmitting points based on initial values ​​of each set of antenna parameters; The reference signal receiving power of the receiving point is determined according to the signal transmission distance between the multiple transmitting points and the receiving point.

5. The method according to claim 1, characterized in that The selecting, crossover and mutation operations are performed on the multiple groups of antenna parameter initial values ​​according to the fitness function values ​​corresponding to the groups of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value, including: Take each group of antenna parameter initial values ​​as an individual to form an initial population; Determining the next generation of individuals in the initial population according to the fitness function value corresponding to each individual in the initial population; Performing crossover and mutation operations on the next generation individuals to obtain new individuals; Update the initial population according to the new individuals to obtain the next generation population; Determine the fitness function value of each individual in the next generation population until the preset termination condition is met, and obtain the target individual in the next generation population whose fitness function value is greater than the preset threshold; The antenna parameter value corresponding to the target individual is determined as the antenna parameter target value.

6. The method according to claim 5, characterized in that The step of performing crossover and mutation operations on the next generation individuals to obtain new individuals includes: Selecting a crossover individual from the next generation individuals according to the crossover probability; According to a preset crossover rule, a crossover operation is performed on the crossover individuals to obtain a combined individual; According to the preset mutation rule, the combination individual is mutated to obtain the new individual.

7. A parameter optimization device for indoor distributed antenna, characterized in that: include: A discrete module is used to discretize antenna configuration parameters to obtain multiple groups of antenna parameter initial values; A determination module, configured to determine the reference signal received power of multiple receiving points based on each group of antenna parameter initial values, and determine the fitness function value corresponding to each group of antenna parameter initial values ​​according to a first number of the multiple receiving points and a second number of target receiving points among the multiple receiving points; wherein the target receiving point is a receiving point among the multiple receiving points whose reference signal received power is greater than a preset power threshold; The optimization module is used to select, crossover and mutate the multiple groups of antenna parameter initial values ​​according to the fitness function value corresponding to each group of antenna parameter initial values ​​until a preset termination condition is met to obtain the antenna parameter target value.

8. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises a program or instructions, and when the program or instructions are executed, the steps of the method according to any one of claims 1 to 6 are implemented.

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