Station installation design method, station installation design program, station installation design device, and wireless communication system building method

Abstract

Provided are a station installation design method, a station installation design program, a station installation design device, and a wireless communication system building method that make it possible to perform a station installation design satisfying target quality in consideration of a construction load burden when installing a wireless base station. In the station installation design method, wireless terminals 2 and installation candidate points 13 are arranged for an object area, and condition setting for setting an objective function is performed so that a construction burden can be calculated. Subsequently, a generation change for updating a plurality of individuals of a population using a genetic algorithm approach is performed on the basis of an evaluation using the objective function for each individual of the population. Each individual has genetic information indicating whether or not a wireless base station 4 is installed at each installation candidate point 13. Subsequently, by selecting an individual from the population after the generation change has been performed multiple times, a station installation design pattern corresponding to the individual is obtained. The objective function is calculated on the basis of the wireless communication quality of the wireless terminal 2 when the wireless base station 4 is installed at the installation candidate point 13 and a penalty corresponding to the construction burden.

Description

Site design method, site design program, site design device, and method for constructing a wireless communication system

[0001] This disclosure relates to a site design method, a site design program, a site design device, and a method for constructing a wireless communication system.

[0002] There is a limit to the range of radio waves that can reach from a wireless base station. Furthermore, there is a limit to the number of wireless terminals that a single wireless base station can accommodate. Therefore, if the number of wireless base stations is insufficient, problems arise such as inadequate coverage and insufficient capacity for wireless terminals. On the other hand, if the number of wireless base stations is excessive, it becomes inefficient due to increased costs for the base station equipment itself. For these reasons, when determining the placement of wireless base stations, it is necessary to place a sufficient number of base stations in appropriate locations, and various base station placement design methods, such as those disclosed in Non-Patent Document 1, are being considered.

[0003] Furthermore, site design is a combinatorial optimization problem, and various methods have been proposed for solving general combinatorial optimization problems. For example, the evolutionary algorithm shown in Non-Patent Document 2 is proposed as a population-based metaheuristic optimization algorithm inspired by evolutionary mechanisms such as reproduction, mutation, genetic modification, natural selection, and survival of the fittest.

[0004] Toshiro Nakahira, Daisuke Murayama, Satoshi Takaya, Kenichi Kawamura, Takayoshi Moriyama, "Multi-Wireless Area Design Method Based on Communication Capacity and Base Station Costs," IEICE Technical Review, IEICE General Convention, B-5-97, Mar. 2022. Shota Yagami, Sho Kuwajima, "Evolutionary Algorithms," [online], April 2014, [Retrieved September 6, 2024], Internet <URL: http: / / mikilab.doshisha.ac.jp / dia / monthly / monthly2014 / mlm152 / syagami / syagami.pdf>

[0005] For example, when actually installing a wireless base station on-site according to a site design pattern obtained using a site design method such as that disclosed in Non-Patent Document 1, the construction method and difficulty may change depending on the location and other conditions of the installation site, and the construction costs may also change. Therefore, there may be a difference between the equipment cost evaluated by the method in Non-Patent Document 1 and the actual total cost when constructing a wireless communication system based on that method, depending on the conditions of the installation site.

[0006] This disclosure relates to the solution of such problems. This disclosure provides a base station design method, a base station design program, and a base station design device that can design base stations that meet target quality while taking into account the construction burden when installing wireless base stations, such as construction costs, as well as a method for constructing a wireless communication system using the same.

[0007] The station placement design method relating to this disclosure involves a computer setting conditions for a design area, including the placement of one or more wireless terminals and one or more candidate installation points; generating a population containing multiple individuals such that each of the multiple individuals has genetic information that encodes a station placement design pattern by representing the placement or non-placement of a wireless base station at each of the one or more candidate installation points in a binary manner; performing generational changes to update the multiple individuals in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals in the population; and after performing the generational changes multiple times, selecting the genetic information of individuals from the multiple individuals in the population based on pre-set criteria. A site placement design method that obtains a site placement design pattern represented by and performs the following, wherein the condition setting includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at a location corresponding to one or more candidate installation points, and the objective function is calculated for the site placement design pattern represented by the genetic information of the target individual, based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the candidate installation points designated as installation in the site placement design pattern, and a penalty corresponding to the construction burden when installing a wireless base station at a location corresponding to each of the candidate installation points designated as installation in the site placement design pattern.

[0008] The station placement design program described herein involves: setting conditions for a design area on a computer, including the placement of one or more wireless terminals and one or more candidate installation points; generating a population containing multiple individuals such that each of the multiple individuals has genetic information that encodes a station placement design pattern by representing the placement or non-placement of a wireless base station at each of the one or more candidate installation points in a binary manner; performing generational changes to update the multiple individuals in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals in the population; and after performing the generational changes multiple times, selecting the individuals from the multiple individuals in the population based on pre-set criteria and applying the genetic information of those individuals to the population. The program is a site design program that obtains a site design pattern represented by the above, and the condition setting includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at a location corresponding to one or more candidate installation points, and the objective function is calculated for the site design pattern represented by the genetic information of the target individual, based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the candidate installation points designated as installation in the site design pattern, and a penalty corresponding to the construction burden when installing a wireless base station at a location corresponding to each of the candidate installation points designated as installation in the site design pattern.

[0009] The station placement design device according to this disclosure includes: a setting unit that sets conditions for the area to be designed, including the placement of one or more wireless terminals and the placement of one or more candidate installation points; a generation unit that generates a population including multiple individuals such that each of the multiple individuals has genetic information in which a station placement design pattern is encoded by representing the installation or non-installation of a wireless base station at each of the one or more candidate installation points as a binary value; an update unit that performs generational change to update the multiple individuals included in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals included in the population; and after performing the generational change multiple times, the genetic information of individuals selected from the multiple individuals included in the population based on pre-set criteria. The system includes a selection unit that obtains a site location design pattern represented by the genetic information, wherein the condition setting includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at a location corresponding to one or more candidate installation points, and the objective function is calculated for the site location design pattern represented by the genetic information of the target individual, based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the candidate installation points designated as installation points in the site location design pattern, and a penalty corresponding to the construction burden when installing a wireless base station at a location corresponding to each of the candidate installation points designated as installation points in the site location design pattern.

[0010] The method for constructing a wireless communication system relating to this disclosure includes obtaining a site design pattern by having a computer execute the above-described site design method, and installing a wireless base station in the area to be designed at a location corresponding to one or more candidate installation points that have been designated as installation points according to the obtained site design pattern.

[0011] According to the base station design method, base station design program, or base station design device, or the method for constructing a wireless communication system using the same, it becomes possible to meet the target quality while taking into account the construction burden, such as construction costs, when installing wireless base stations.

[0012] This is a configuration diagram of a wireless communication system according to Embodiment 1. This is a configuration diagram of a site design device according to Embodiment 1. This is a diagram illustrating an example of site design for a wireless communication system according to Embodiment 1. This is a block diagram showing an example of the functions of the site design device according to Embodiment 1. This is a table showing an example of item information used by the site design device according to Embodiment 1 when calculating construction burden. This is a flowchart showing an example of the operation of the site design device according to Embodiment 1. This is a flowchart showing an example of the operation of the site design device according to Embodiment 1.

[0013] Embodiments of this disclosure will be described with reference to the attached drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals, and redundant explanations are simplified or omitted as appropriate. This disclosure is not limited to the following embodiments, and any combination of embodiments, any modification of any component of each embodiment, or any omission of any component of each embodiment is permitted without departing from the spirit of this disclosure.

[0014] Embodiment 1. Figure 1 is a configuration diagram of the wireless communication system 1 according to Embodiment 1.

[0015] The wireless communication system 1 is a system that provides wireless communication functionality to one or more wireless terminals 2 in the applicable area. Each wireless terminal 2 is, for example, an information processing terminal device capable of wireless communication. Each wireless terminal 2 may be, for example, a general-purpose information processing device such as a tablet computer, smartphone, or smartwatch, or it may be a vehicle, robot, mobility device, or other device equipped with a wireless communication module. The wireless terminal 2 may be a device that moves around the target area, or it may be a device that is fixedly installed in the target area.

[0016] In the area where the wireless communication system 1 is applied, there is one or more shielding objects 3. In this example, there are multiple shielding objects 3 in the area. The shielding objects 3 are objects that block the wireless signals from the wireless communication system 1. The shielding objects 3 may be fixed objects such as buildings, or moving objects such as vehicles.

[0017] The wireless communication system 1 comprises one or more wireless base stations 4. In this example, the wireless communication system 1 comprises a plurality of wireless base stations 4. Each wireless base station 4 is located in an area to which the wireless communication system 1 is applied. Each wireless base station 4 is equipped with the function of transmitting and receiving wireless signals of the wireless communication system 1. The wireless communication system 1 may comprise a plurality of wireless base stations 4 that correspond to different wireless communication methods. Each wireless base station 4 is configured to communicate wirelessly or wired with equipment inside or outside the wireless communication system 1. Each wireless base station 4 provides wireless communication functionality to a wireless terminal 2 by transmitting and receiving wireless signals to and from the wireless terminal 2.

[0018] The wireless communication system 1 is constructed by actually installing one or more wireless base stations 4 in locations determined by a pre-determined site placement design within the target area. Here, the process of constructing the wireless communication system 1 so that it can operate is sometimes referred to as manufacturing the wireless communication system 1. The site placement design for the wireless communication system 1 is performed, for example, using a site placement design device 5 not shown in Figure 1.

[0019] Figure 2 is a configuration diagram of the site location design device 5 according to Embodiment 1.

[0020] The site design device 5 is, for example, a computer system consisting of one or more server devices, or a device including such a system. Here, a computer system consisting of one or more devices may be simply referred to as a computer. When the site design device 5 is composed of multiple server devices, these multiple server devices may be located in different locations. Some or all of the functions of the site design device 5 may be implemented, for example, by a virtual machine on a cloud service, or by processing or storage resources on a cloud service. The site design device 5 includes a communication unit 6, an external input / output unit 7, a processing unit 8, and a database 9.

[0021] The communication unit 6 communicates with the input / output device 10 located outside the site design device 5 via wired or wireless connection. The input / output device 10 accepts information input from the operator and displays the input information and the information output from the site design device 5 on a display.

[0022] The external input / output unit 7 is an interface between the communication unit 6 and the processing unit 8, and the communication unit 6 inputs information received from the input / output device 10 to the processing unit 8. The external input / output unit 7 also outputs information obtained from calculation processing by the processing unit 8 to the communication unit 6 and transmits it to the input / output device 10 via the communication unit 6.

[0023] The processing unit 8 comprises a processor 11 and a memory 12. The processor 11 is typically a CPU. The memory 12 stores programs that can be executed by the processor 11. The processor 11 is, for example, a CPU, arithmetic unit, microprocessor, or microcomputer. The memory 12 is, for example, a non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, and EEPROM, or a magnetic disk, flexible disk, optical disk, compact disk, minidisc, or DVD. The memory 12 stores programs, for example, as software or firmware. The site design device 5 then performs pre-set processing by having the processor 11 execute the programs stored in the memory 12, and realizes each function as a result of the cooperation between hardware and software. Programs can be stored on computer-readable storage media. Programs can also be provided via a communication network. A program may be a program package that includes multiple subprograms, modules, or libraries. A program is sometimes called a program product. Each function of the site design device 5 may be implemented by a processing circuit. Alternatively, some or all of the functions of the site design device 5 may be implemented together by a processing circuit. Furthermore, the processing circuit may be implemented as, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, or an FPGA, or a combination thereof.

[0024] Database 9 stores information such as calculation conditions or calculation results in site design. Information such as calculation conditions stored in database 9 can be read from database 9 by the processing unit 8 during site design. Various types of information, such as calculation results in site design, can be written to database 9 by the processing unit 8. Various types of information in site design can be written to database 9 by the operator operating the input / output device 10. Information stored in database 9 can be read from database 9 by the operator operating the input / output device 10. Information read from database 9 can be displayed on the input / output device 10 or transmitted externally via a communication network.

[0025] Figure 3 is a diagram illustrating an example of a station layout design for a wireless communication system 1 according to Embodiment 1.

[0026] In site placement design, for example, the area to which the wireless communication system 1 is applied is designated as the design area, and the number and placement of wireless base stations 4 within the area are determined. The wireless base stations 4 are installed in part or all of one or more candidate installation points 13 located within the area. The candidate installation points 13 are set to locations where wireless base stations 4 can be installed, depending on the area. The candidate installation points 13 are identified, for example, by their location within the area. In site placement design, for example, a site placement design pattern is determined that indicates, among the candidate installation points 13 within the area, at which wireless base stations 4 are installed and at which candidate installation points 13 are not.

[0027] In site placement design, for example, the communication quality when wireless base stations 4 are installed at some or all of the candidate installation points 13 is evaluated. The evaluation of communication quality is performed by simulation of a wireless communication system 1 virtually constructed on the site placement design device 5 for the area under design. At this time, one or more wireless terminals 2 are placed in the virtual area. One or more wireless terminals 2 may be placed, for example, on a grid within the area, randomly, based on previously observed placements, or by other methods.

[0028] Figure 4 is a block diagram showing an example of the functions of the site location design device 5 according to Embodiment 1.

[0029] In this example, the site placement design device 5 performs site placement design for the wireless communication system 1 by solving a combinatorial optimization problem using a genetic algorithm. The site placement design device 5 comprises a setting unit 14, a generation unit 15, an update unit 16, and a selection unit 17 as functional units. The functions of each functional unit of the site placement design device 5 are realized, for example, as calculation processing in the processing unit 8.

[0030] The setting unit 14 is a part equipped with a function for setting site design conditions for the area to be designed. Setting site design conditions includes setting the size of a virtual area on the site design device 5, the arrangement of shielding objects 3 within the area, and other calculation conditions. The virtual area on the site design device 5 is set, for example, based on a model of the actual area to be designed. Setting site design conditions includes placing one or more wireless terminals 2 in the virtual area on the site design device 5. Setting site design conditions also includes placing one or more candidate installation points 13 in the virtual area on the site design device 5. The setting unit 14 sets site design conditions, for example, based on information input by the operator to the input / output device 10. The operator inputs, for example, the arrangement of one or more wireless terminals 2 and the arrangement of one or more candidate installation points 13 within the area to the site design device 5 via the input / output device 10.

[0031] The generation unit 15 is a part equipped with the function of generating a population containing multiple individuals as an initial population as a processing of a genetic algorithm. Each individual included in the population has genetic information that represents the corresponding base station design pattern. The genetic information is information that encodes the base station design pattern. In the genetic information of this example, the base station design pattern is encoded by representing the installation or non-installation of a wireless base station 4 at each candidate installation point 13 with a binary value such as "1" or "0". For example, for numbered candidate installation points 13, the genetic information that encodes a base station design pattern in which a wireless base station 4 is installed at the first candidate installation point 13, not installed at the second candidate installation point 13, and a wireless base station 4 is installed at the third candidate installation point 13 is represented as "101...". The generation unit 15 generates multiple individuals with random genetic information according to the base station design conditions set by the setting unit 14, for example, and uses the population containing the generated multiple individuals as the initial population.

[0032] The update unit 16 is a part equipped with the function of performing generational change processing on a population that includes multiple individuals, such as the initial population generated by the generation unit 15. The generational change processing is a process of updating multiple individuals included in the population using the methods of a genetic algorithm. The generational change processing is performed based on an evaluation using a pre-set objective function for each individual included in the current generation population. The generational change processing includes processes such as elite preservation, tournament selection, uniform crossover, and mutation.

[0033] Elite preservation is a process that carries over individuals with good evaluation scores based on the objective function from the current generation to the next generation. Here, in optimization problems where the goal is to maximize the objective function, a higher evaluation score is considered better, while in optimization problems where the goal is to minimize the objective function, a lower evaluation score is considered better. In elite preservation, for example, one or more individuals are carried over to the next generation in order of their evaluation scores based on the objective function, in descending order of quality. As a result, the individual with the best evaluation score in each generation, i.e., the evaluation score of the optimal solution, is updated in a direction that improves.

[0034] Tournament selection is a process of selecting individuals with good evaluation values according to an objective function from a population randomly selected from the current generation population. Uniform crossover is a process of randomly swapping each element represented by a binary value of genetic information for two individuals selected by tournament selection or the like from the current generation population and passing it on to the next generation population. Mutation is a process of randomly converting genetic information, for example, by bit flipping or swapping of bit strings, for an individual selected from the current generation population or an individual that has undergone a process such as uniform crossover, and passing it on to the next generation population. As a result, the genetic information of the next generation population diversifies.

[0035] The update unit 16 performs the process of elite preservation, and then repeats processes such as tournament selection, uniform crossover, and mutation until the number of individuals included in the next generation population reaches the required number, thereby forming the next generation population. The update unit 16 may perform generation alternation by means of processes in genetic algorithm methods other than the above, for example, roulette selection, ranking selection, two-point crossover, or other processes. The update unit 16 repeats the process of generation alternation for the updated population. The update unit 16 performs the process of generation alternation, for example, for a preset number of generations.

[0036] The selection unit 17 is a part equipped with a function of selecting any individual from a plurality of individuals included in the latest generation population after generation alternation for the population has been performed a plurality of times. The selection unit 17 selects, for example, one individual from the population based on a preset criterion. The selection unit 17 selects, for example, the individual with the best evaluation value according to the objective function among the individuals included in the latest generation population. The selection unit 17 obtains the placement design pattern represented by the genetic information of the selected individual as the result of the placement design.

[0037] The operator acquires and refers to the result of the placement design obtained by the selection unit 17 from the placement design device 5 through the input / output device 10.

[0038] Next, the objective function used in the placement design device 5 will be described. The objective function is a function that returns an evaluation value for each individual having genetic information. The objective function is calculated using the wireless communication quality of the wireless terminal 2 when the wireless base station 4 is installed at the installation candidate point 13 based on the placement design pattern represented by the genetic information of the target individual. Further, the objective function is calculated using a penalty according to the construction burden when installing the wireless base station 4 at the location corresponding to each of the installation candidate points 13 according to the placement design pattern. The objective function is represented by, for example, the following equation (1).

[0039]

[0040] Here, the first term of Equation (1) represents the wireless communication quality, and the second term represents the penalty according to the construction burden. The coefficient α and the coefficient μ are positive weights that determine the strength of the influence of the wireless communication quality and the penalty on the evaluation value of the objective function. The subscript j, which is an element of the set J, corresponds to each wireless terminal 2. The number of elements |J| of the set J is the number of wireless terminals 2 arranged in the area to be designed in the condition setting of the setting unit 14. The subscript n, which is an element of the set N, corresponds to each placement design pattern. The number of elements of the set N is the total number of possible placement design patterns for one or more installation candidate points 13 arranged in the area to be designed in the condition setting of the setting unit 14. The degree of goal achievement z ｊ，ｎ is a value indicating whether the maximum reception power at the j-th wireless terminal 2 achieves the target value in the placement design pattern n. The degree of goal achievement z ｊ，ｎ is represented by, for example, the following equation (2).

[0041]

[0042] The maximum reception power p ｊ，ｎ represents the maximum reception power at the j-th wireless terminal 2 in the placement design pattern n. The target reception power p ｔ１ is the target value of the reception intensity of the wireless signal from the wireless base station 4 at each wireless terminal 2. The target reception power p ｔ１ is set, for example, so that wireless communication at the wireless terminal 2 can be achieved with sufficient quality. The maximum reception power p ｊ，ｎ is the reception power rｊ，ｋ is the maximum value over the radio base stations 4. Here, the set K ｎ The subscript k, which is an element of, corresponds to each radio base station 4 arranged in the area to be designed in the station placement design pattern n. The set K ｎ The number of elements |K ｎ | is the number of radio base stations 4 arranged in the area to be designed in the station placement design pattern n. The received power r ｊ，ｋ is the reception intensity at the j-th radio terminal 2 of the radio signal transmitted from the k-th radio base station 4. The received power r ｊ，ｋ is calculated, for example, by the signal intensity of the radio signal transmitted by the radio base station 4, the distance between the radio base station 4 and the radio terminal 2, and the presence or absence of the shielding object 3 between the radio base station 4 and the radio terminal 2. The received power r ｊ，ｋ may be calculated in consideration of, for example, the reflection of the radio signal between the radio base station 4 and the radio terminal 2. The degree of goal achievement z ｊ，ｎ for the j-th radio terminal 2 has a value of 1 if the maximum received power p ｊ，ｎ achieves the target received power p ｔ１ . Therefore, the first term of the objective function represented by Equation (1) is the ratio of the radio terminals 2 in which the maximum received power achieves the target value in the station placement design pattern n among one or more radio terminals 2 arranged in the area to be designed in the condition setting of the setting unit 14, multiplied by the coefficient α. That is, if this value is sufficiently large, it can be said that the radio communication quality in the station placement design pattern n is good.

[0043] The penalty P is represented by the following Equation (3) using C(n), which represents the construction burden when installing the radio base station 4 at each location corresponding to each installation candidate point 13 according to the station placement design pattern n.

[0044]

[0045] The construction burden C(n) is, for example, the construction cost, which represents the financial burden during construction. Thus, the evaluation value of the objective function expressed in equation (1) is the value obtained by subtracting from the first term, which represents the wireless communication quality in site design pattern n, the penalty P due to the construction burden C(n) multiplied by the coefficient μ. For this reason, site design that satisfies the target quality while considering the construction burden becomes a problem of maximizing the objective function expressed by the following equation (4), under the conditions of equations (2) and (3).

[0046]

[0047] Next, an example of a method for calculating the construction burden C(n) will be explained using Figure 5. Figure 5 is a table showing an example of the item information used by the site design device 5 according to Embodiment 1 when calculating the construction burden.

[0048] The site design device 5 stores item information in the database 9, for example. The item information is set by the setting unit 14 based on information that the operator inputs to the input / output device 10 when setting site design conditions, for example. Setting item information is an example of setting an objective function.

[0049] Item information is set using, for example, an ID that identifies the candidate installation point 13 as the key. For each candidate installation point 13, item information includes, for example, information such as base station model, base station cost, wiring configuration, wiring length, wiring equipment cost, and construction cost. The base station model represents the model of the wireless base station 4 to be installed at the candidate installation point 13. The base station cost represents the cost of the wireless base station 4 equipment itself to be installed at the candidate installation point 13. The base station cost is set, for example, according to the base station model. The base station cost may also include necessary licensing costs, etc., depending on the model of the wireless base station 4. The wiring configuration represents, for example, whether the wireless base station 4 installed at the candidate installation point 13 in the wireless communication system 1 is connected to other equipment by wire or wireless. The wiring length represents the length of wiring required when the wireless base station 4 is installed at the candidate installation point 13. The wiring equipment cost represents the cost of cables and other wiring equipment when the wireless base station 4 is installed at the candidate installation point 13. The wiring equipment cost is set, for example, according to the wiring length, etc. The construction cost represents the personnel costs and other expenses incurred when the wireless base station 4 is installed at the candidate installation site 13.

[0050] The site design device 5 calculates the construction burden C(n) for a site design pattern n, for example, as follows: The site design device 5 identifies candidate installation points 13 where the wireless base station 4 is to be installed in the site design pattern n. For each identified candidate installation point 13, the site design device 5 calculates the cost of installing the wireless base station 4 by referring to item information. For example, the site design device 5 calculates the sum of wiring equipment costs and labor costs as the cost of installing the wireless base station 4. The item information may include the value of the cost calculated in advance. The site design device 5 calculates the construction burden C(n) by summing the costs calculated for each candidate installation point 13.

[0051] In this example, the construction burden C(n) does not include the base station cost itself. The base station design device 5 may calculate the objective function including a penalty representing the base station cost itself, in addition to communication quality and construction burden. The base station design device 5 may also calculate the base station cost and construction burden together when calculating the penalty for the objective function.

[0052] Next, an example of the operation of the site location design device 5 will be explained using Figures 6 and 7. Figures 6 and 7 are flowcharts illustrating an example of the operation of the site location design device 5 according to Embodiment 1.

[0053] Figure 6 shows an example of the overall processing in the site design device 5 during site design.

[0054] In step S1, the setting unit 14 places the wireless terminal 2 and candidate installation points 13 in the area to be designed, based on information input by the operator to the input / output device 10, as a condition setting for site placement design. After that, the site placement design device 5 proceeds to step S2.

[0055] In step S2, the setting unit 14 sets item information used to calculate the construction burden as a penalty to the objective function, based on information input by the operator to the input / output device 10, as a condition setting for site design. The setting unit 14 may perform the processes of step S1 and step S2 in parallel. After that, the processing of the site design device 5 proceeds to step S3.

[0056] In step S3, the setting unit 14 calculates the received power at each wireless terminal 2 for the wireless signals transmitted by each wireless base station 4, based on the arrangement of wireless terminals 2 and candidate installation points 13 in the area to be designed, as well as the arrangement of shielding objects 3. After that, the site design device 5 proceeds to step S4.

[0057] In step S4, the site design device 5 searches for a site design pattern that optimizes the objective function using a genetic algorithm. In this example, the site design device 5 searches for a site design pattern that maximizes the objective function. After storing the searched site design pattern as a design result in a database 9 or the like, the processing of the site design device 5 is completed.

[0058] Figure 7 shows an example of the processing performed by the site design device 5 when searching for site design patterns using a genetic algorithm.

[0059] In step S41, the generation unit 15 generates, for example, multiple individuals with random genetic information. The generation unit 15 generates a population including these multiple individuals as the initial population. After that, the processing of the location design device 5 proceeds to step S42.

[0060] In step S42, the update unit 16 calculates an evaluation value using the objective function for each individual included in the group. After that, the site design device 5 proceeds to step S43.

[0061] In step S43, the update unit 16 performs generational change processing using the calculated evaluation values. In this example, as part of the generational change processing, the update unit 16 performs elite preservation processing, which involves passing on individuals with good evaluation values ​​based on the objective function to the next generation. The update unit 16 also performs processing to pass on individuals that have undergone tournament selection, uniform crossover, and mutation in sequence to the next generation as part of the generational change processing. After the required number of individuals are included in the next generation's population through the generational change processing, the processing of the location design device 5 proceeds to step S44.

[0062] In step S44, the update unit 16 determines whether the current group's generation count has reached a predetermined end generation count. If the end generation count has not been reached, the site design device 5 proceeds to step S42. On the other hand, if the end generation count has been reached, the site design device 5 proceeds to step S45.

[0063] In step S45, the selection unit 17 calculates an evaluation value using the objective function for each individual included in the latest generation of the population. The selection unit 17 selects the individual with the best evaluation value using the objective function from among the multiple individuals included in the population. In this example, the selection unit 17 selects the individual with the largest evaluation value using the objective function. The selection unit 17 obtains a location design pattern represented by the genetic information of the selected individual as the result of location design. After that, the processing of the location design device 5 for the search of location design patterns is completed.

[0064] As described above, the site placement design method according to Embodiment 1 is performed by a site placement design device 5, which is a computer. The site placement design method includes setting conditions for the area to be designed. The condition setting includes the placement of one or more wireless terminals 2 and the placement of one or more candidate installation points 13. The site placement design method includes generating a population containing multiple individuals as an initial population. Each individual in the population has genetic information in which a site placement design pattern is encoded by representing the installation or non-installation of a wireless base station 4 at each candidate installation point 13 as a binary value. The site placement design method includes performing generational changes to update multiple individuals in the population using a genetic algorithm method based on an evaluation using an objective function for each individual in the population. After performing generational changes multiple times, the site placement design method includes obtaining a site placement design pattern represented by the genetic information of individuals selected from multiple individuals in the population based on predetermined criteria. The condition setting includes setting an objective function so as to be able to calculate the construction burden when installing a wireless base station 4 at the location corresponding to each candidate installation point 13. The objective function is calculated based on the wireless communication quality of each wireless terminal 2 when a wireless base station 4 is installed at each candidate installation point 13 designated by the site placement design pattern represented by the genetic information of the target individual, and on the penalty corresponding to the construction burden when installing the wireless base station 4.

[0065] With this configuration, the objective function for site placement design as a combinatorial optimization problem includes the construction burden of installing the wireless base station 4, such as construction costs, as a penalty. This makes it possible to design a site placement that satisfies the target quality while considering the construction burden. In a site placement design method that selects and places one wireless base station 4 at each of the candidate installation points 13 using a local search such as a greedy algorithm, a solution can be found with a small amount of computation even if there are many candidate installation points 13, but the solution tends to fall into a local optimum. Also, in a method that solves the optimization problem by exhaustive search for the candidate installation points 13, the computational load becomes enormous and computation becomes difficult as the number of candidate installation points 13 increases. In contrast, in the site placement design method according to Embodiment 1, the diversity of genetic information in the genetic algorithm makes it easier to obtain a global optimal solution than in the case of local search. Furthermore, even when there are many candidate installation points 13, the increase in computational load is suppressed compared to the case of exhaustive search. As a result, site placement design that satisfies the target quality while considering the construction burden can be performed more efficiently. Furthermore, the wireless communication system 1 is constructed by actually installing wireless base stations 4 in locations specified by the site placement design pattern obtained by the site placement design device 5, etc., within the target area. This reduces construction costs and other construction burdens when constructing the wireless communication system 1, which is designed to meet the target quality.

[0066] Furthermore, the candidate installation points 13 may be identified not only by their location within the area, but also by the wireless communication method of the wireless base station 4 to be installed. For the same location within the area, for example, candidate installation points 13 for a wireless base station 4 using a first wireless communication method and candidate installation points 13 for a wireless base station 4 using a second wireless communication method may be set separately. The first wireless communication method is, for example, a wireless communication method using radio signals in the 5.2 GHz band. The second wireless communication method is, for example, a wireless communication method using radio signals in the 28 GHz band. In addition, the candidate installation points 13 may be identified not only by their location within the area, but also by the type of antenna or the direction of the antenna of the wireless base station 4. For example, for the same location within the area, candidate installation points 13 for a wireless base station 4 with its antenna pointed in the first direction and candidate installation points 13 for a wireless base station 4 with its antenna pointed in the second direction may be set separately.

[0067] Furthermore, while the site design method was explained using an example objective function that evaluates wireless communication quality based on the received power at the wireless terminal 2, other objective functions that evaluate wireless communication quality may also be used in the site design method. The objective function may evaluate wireless communication quality based on indicators such as the signal-to-interference and noise ratio or throughput. Estimates of these indicators are calculated, for example, based on the received power at the wireless terminal 2.

[0068] Furthermore, the objective function may include the construction burden, which is evaluated by taking into account factors such as the work period or the difficulty of the construction. For example, since the work period increases with the number of wireless base stations 4 to be installed, the objective function may include a penalty for the construction burden, which takes into account labor costs etc. corresponding to the work period. Also, if the candidate installation point 13 is located at a height higher than a predetermined height, it will be necessary to arrange for an aerial work platform during the installation work. For this reason, the objective function may evaluate the construction burden by adding the cost of an aerial work platform when installing a wireless base station 4 at a candidate installation point 13 located at a height higher than a predetermined height. Here, information such as the height of the candidate installation point 13 or whether an aerial work platform is necessary for installation is included, for example, in the item information when calculating the construction burden. Also, depending on other circumstances of the candidate installation point 13, the installation of the wireless base station 4 may require work by highly skilled technicians. The objective function may evaluate the construction burden by adding costs in a similar manner to the cost of an aerial work platform, depending on the difficulty of the work according to the circumstances of the candidate installation point 13.

[0069] The objective function may, for example, gradually add the cost of aerial work platforms to the construction burden in proportion to the number of wireless base stations 4 to be installed that require them during installation. For example, if the number of wireless base stations 4 that require aerial work platforms during installation is small, the work using the aerial work platforms may be completed in one day. In this case, the cost of the aerial work platforms required will be for one day. For example, if the cost of aerial work platforms is charged on a daily basis, and the number of wireless base stations 4 to be installed is within the range that the work can be completed in one day, the cost of the aerial work platforms will not depend on the number of wireless base stations 4 to be installed. On the other hand, if the number of wireless base stations 4 that require aerial work platforms during installation is large, the work using the aerial work platforms may extend to two or more days. In this case, the cost of the aerial work platforms required will be for two or more days. Reflecting these circumstances, the construction burden in the objective function may increase gradually in proportion to the number of wireless base stations 4 to be installed. Similarly, for costs other than aerial work platforms, the construction burden in the objective function may increase gradually in proportion to the number of wireless base stations 4 to be installed. The number of wireless base stations 4 to be installed may be the number of those that meet conditions such as whether or not an aerial work platform is required during installation, or it may be the number of wireless base stations 4 that are installed in the target area and are tallied without any other particular conditions being imposed.

[0070] The site design method, site design program, site design device, and construction method relating to this disclosure are applicable to wireless communication systems.

[0071] 1. Wireless communication system, 2. Wireless terminal, 3. Shielding device, 4. Wireless base station, 5. Site design device, 6. Communication unit, 7. External input / output unit, 8. Processing unit, 9. Database, 10. Input / output device, 11. Processor, 12. Memory, 13. Installation candidate points, 14. Setting unit, 15. Generation unit, 16. Update unit, 17. Selection unit

Claims

1. A base station design method comprising: a computer performing the following: setting conditions for an area to be designed, including the placement of one or more wireless terminals and the placement of one or more candidate installation points; generating a population of multiple individuals such that each of the multiple individuals has genetic information in which a base station design pattern is encoded by representing the installation or non-installation of a wireless base station at each of the one or more candidate installation points as a binary value; performing generational changes to update the multiple individuals in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals in the population; and, after performing the generational changes multiple times, obtaining a base station design pattern represented by the genetic information of individuals selected from the multiple individuals in the population based on pre-set criteria, wherein the setting of conditions includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at the locations corresponding to the one or more candidate installation points, and the objective function, for the base station design pattern represented by the genetic information of the target individuals, at least, A site placement design method calculated based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the one or more candidate installation points designated for installation in the site placement design pattern, and a penalty corresponding to the construction burden when installing a wireless base station at each of the locations corresponding to each of the one or more candidate installation points designated for installation in the site placement design pattern.

2. A site design program that causes a computer to perform the following: setting conditions for an area to be designed, including the placement of one or more wireless terminals and the placement of one or more candidate installation points; generating a population of multiple individuals such that each of the multiple individuals has genetic information in which a site design pattern is encoded by representing the installation or non-installation of a wireless base station at each of the one or more candidate installation points as a binary value; performing generational changes to update the multiple individuals in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals in the population; and, after performing the generational changes multiple times, obtaining a site design pattern represented by the genetic information of individuals selected from the multiple individuals in the population based on pre-set criteria, wherein the setting of conditions includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at the locations corresponding to the one or more candidate installation points, and the objective function, for the site design pattern represented by the genetic information of the target individuals, at least, A site design program calculated based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the site candidate locations designated for installation in the site design pattern, and a penalty corresponding to the construction burden when installing a wireless base station at each of the site candidate locations designated for installation in the site design pattern.

3. The system comprises: a setting unit that sets conditions for the area to be designed, including the placement of one or more wireless terminals and the placement of one or more candidate installation points; a generation unit that generates a population including multiple individuals such that each of the multiple individuals has genetic information in which a base station design pattern is encoded by representing the installation or non-installation of a wireless base station at each of the one or more candidate installation points as a binary value; an update unit that performs generational changes to update the multiple individuals included in the population using a genetic algorithm method based on an evaluation using an objective function for each of the multiple individuals included in the population; and a selection unit that, after performing the generational changes multiple times, obtains a base station design pattern represented by the genetic information of individuals selected from the multiple individuals included in the population based on pre-set criteria, wherein the condition setting includes setting the objective function so as to be able to calculate the construction burden when installing a wireless base station at the locations corresponding to the one or more candidate installation points, and the objective function includes, at least, the base station design pattern represented by the genetic information of the target individuals. A site placement design device that calculates based on the wireless communication quality of one or more wireless terminals when a wireless base station is installed at each of the site placement design patterns selected from the one or more site placement candidate points, and a penalty corresponding to the construction burden when installing a wireless base station at each of the site placement design patterns selected from the one or more site placement candidate points.

4. A method for constructing a wireless communication system, comprising: having a computer execute the site location design method described in claim 1 to obtain a site location design pattern; and installing a wireless base station in the area to be designed at a location corresponding to one or more candidate installation points that have been designated as installation points in the obtained site location design pattern.

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