JP5538286B2 - Position detection device and position detection program - Google Patents

Description

  The present invention relates to a position detection device and a position detection program in station placement design.

  In a wireless communication system, particularly a mobile communication system typified by a mobile phone, a station station design is performed in which a designer considers a position where a base station is installed in advance before actually building a communication area. In the in-station design, the map data in the range for which the communication area is to be constructed is divided into a plurality of areas having a predetermined size. The position where the base station is installed is examined so as to satisfy a constraint condition (for example, a traffic demand condition) based on the received signal strength for each region.

  Patent Document 1 discloses a base station arrangement pattern determination method that aims to obtain an optimum arrangement pattern while omitting the trouble of creating an arrangement pattern of base stations in such an arrangement design.

JP 2001-285923 A

  However, since there is a geographical restriction in actual installation, it is not always possible to install a base station at a position determined in advance by station design. Therefore, when the base station is actually installed at a position away from that position instead of the position determined in advance by the station placement design, the constraints satisfied by the station placement design and the optimum The realization conditions (for example, conditions for minimizing the installation cost) are not always satisfied in actual installation. As described above, the position detected by the method disclosed in Patent Document 1 has a problem that the degree of freedom is low as the position where the base station is installed.

  The present invention has been made in view of the above points, and an object thereof is to provide a position detection device and a position detection program for detecting a position with a high degree of freedom in installing a base station.

  The present invention has been made to solve the above-described problem, and includes map data including a predetermined range, data indicating a predetermined size, and data indicating a predetermined optimization condition. Data representing a predetermined constraint condition, and dividing the map by the size to determine a plurality of areas of the size in the map, the constraint condition for each area, and for each area A region setting unit that calculates the optimization condition; a characteristic calculation unit that calculates a propagation loss for each region based on a transmission power and a frequency band of a base station; the constraint condition for each region; and traffic And the number of base stations required to secure the capacity that satisfies the constraints in the range, and one or more base stations, respectively, based on data representing the capacity of each base station Install 1 From the vicinity of the first candidate position and the second candidate position where the first candidate position and one or more second candidate positions are calculated, and the base station that is the number of units is installed. A region selection unit for selecting each of the regions; a plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position; and the region selected from the vicinity of the second candidate position. Among the partial graphs constituting the graph having a plurality of fourth candidate positions as nodes, the value satisfying the constraint condition in the range and the value determined by the optimization condition for each region is optimal A graph selection unit that selects the largest complete subgraph of the possible complete subgraphs, and an output unit that outputs an area determined by the node position of the selected complete subgraph. A position detecting device according to.

  Further, according to the present invention, the area setting unit calculates the installation cost for each area by acquiring data indicating the installation cost of a base station as the data indicating the optimization condition, and is determined in advance. By obtaining data representing traffic demand as data representing the constraint conditions, the traffic demand for each area is calculated, and the area selection unit is configured to calculate the traffic demand for each area and the traffic demand. And the number of base stations required to secure the capacity that satisfies the traffic demand in the range, the first candidate position, and the first 2 candidate positions are calculated, and the regions are respectively selected from the vicinity of the first candidate position and the second candidate position where the number of base stations corresponding to the number of units is installed, and the group A plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidates defined in the region selected from the vicinity of the second candidate position. For each area where the base station is installed and the value determined by the price and the number of base stations satisfying the traffic demand in the range from among the partial graphs constituting the graph with the position as a node The position detecting device is characterized in that the largest complete subgraph is selected from complete subgraphs composed of feasible solutions that have the minimum total installation cost.

  Further, in the present invention, the area setting unit, as the data representing the optimization condition, data representing the required received power, data representing the required signal-to-interference noise ratio, data representing the installation height of the base station, By calculating the received power and the signal-to-interference noise ratio for each region, and obtaining data representing the traffic demand as the data representing the predetermined constraint condition, The traffic demand is calculated, and the area selection unit satisfies the traffic demand in the range based on the traffic demand for each area and data representing the traffic capacity for each base station. The number of base stations required to secure the capacity, the first candidate position, and the second candidate position are calculated, and the base station that is the total number is installed. A plurality of third candidate positions defined in the area selected from the vicinity of the first candidate position, wherein the areas are respectively selected from the vicinity of the first candidate position and the second candidate position. And satisfying the traffic demand in the range from among the partial graphs constituting a graph having a plurality of fourth candidate positions defined in the region selected from the vicinity of the second candidate position as nodes, And a position detection device that selects a maximum complete subgraph of complete subgraphs composed of feasible solutions in which the region group satisfying the required reception power and the required signal-to-interference noise ratio is maximum. is there.

  In the present invention, the region setting unit calculates data representing an antenna pattern, data representing traffic demand, and traffic capacity for each base station as data representing the optimization condition. By calculating the traffic capacity for each area by acquiring data representing the base station, and by obtaining data representing the installation cost of the base station as data representing the predetermined constraint condition, The installation cost for each area is calculated, and the area selection unit has a value determined by the price and the number of base stations, and the sum of the installation costs for each area where the base station is installed is equal to or less than a predetermined threshold. Calculating the maximum value of the number, the first candidate position and the second candidate position, and the first candidate position and the first candidate position where the base station that is less than or equal to the maximum value is installed, and Each of the regions is selected from the vicinity of two candidate positions, and the graph selection unit selects a plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and the second candidate positions. Among the partial graphs constituting a graph having a plurality of fourth candidate positions determined in the region selected from the neighborhood as a node, the sum is equal to or less than the predetermined threshold value, and a base station is installed. The position detecting device is characterized in that the largest complete subgraph is selected from complete subgraphs composed of feasible solutions having the maximum total traffic capacity for each region.

  The present invention also provides a computer with map data including a predetermined range, data indicating a predetermined size, data indicating a predetermined optimization condition, and a predetermined constraint condition. A plurality of regions of the size in the map by dividing the map by the size, and calculating the constraint condition for each region and the optimization condition for each region Based on the procedure, the procedure for calculating the propagation loss for each region based on the transmission power and frequency band of the base station, the constraint condition for each region, and the data representing the traffic capacity for each base station, Based on the number of base stations required to secure the capacity that satisfies the constraint condition in the range, and one or more first candidate positions and one place each installing one or more base stations that's all Calculating a second candidate position, and selecting each of the regions from the vicinity of the first candidate position and the second candidate position where the number of the base stations to be combined is installed, and the first A graph having a plurality of third candidate positions defined in the region selected from the vicinity of the candidate positions and a plurality of fourth candidate positions defined in the region selected from the vicinity of the second candidate position as nodes. Is the largest complete subgraph of complete subgraphs that are feasible solutions that satisfy the constraints in the range and that have the optimum value determined by the optimization condition for each region. Is a position detection program for executing a graph selection unit for selecting and a procedure for outputting a region determined by the position of the node of the selected complete subgraph.

  According to the present invention, the position satisfying the constraint condition and the optimization condition is detected from the graph using the candidate position where the base station is installed as a node, and the region determined by the detected position is output. Can detect a position with a high degree of freedom in installing a base station, and can output an area determined by the detected position.

It is a block diagram showing the structure of the position detection apparatus in one Embodiment of this invention. It is a figure showing the example of the map data in one Embodiment of this invention. It is a figure showing the predetermined range of the map containing the position which installs a base station in one Embodiment of this invention. It is a table | surface which shows the example of the MCS table in one Embodiment of this invention. It is a table | surface which shows the example of a relationship of the frequency bandwidth in one Embodiment of this invention, the number of subcarriers, and the number of resource blocks (RB). It is a figure showing an example of the combination of the 3rd candidate position and the 4th candidate position in one embodiment of the present invention. It is a figure showing an example of the combination of the 3rd candidate position and 4th candidate position which satisfy | fill restrictions conditions in one Embodiment of this invention. It is a figure showing an example of the complete subgraph in which all the combinations of the candidate position of a base station are feasible solutions by setting the candidate position that satisfies the constraint condition and the optimization condition as a node in an embodiment of the present invention. It is a figure showing the example of the area | region defined by the 3rd candidate position which satisfy | fills restrictions and optimization conditions in one Embodiment of this invention. It is a figure showing the example of the area | region output in one Embodiment of this invention. It is a flowchart showing the operation | movement procedure of the position detection apparatus in one Embodiment of this invention. It is a flowchart showing the operation | movement procedure of the optimization part in one Embodiment of this invention.

[First Embodiment]
A first embodiment of the present invention will be described in detail with reference to the drawings. In the first embodiment, as an example of an optimization condition in station placement design, a condition is set such that the sum of the amount determined by the price of base stations and the number of installed base stations and the installation cost of each base station is minimized. In addition, as an example of a constraint condition in station placement design, a condition is set that accommodates all traffic demands in the communication area (secures a capacity that satisfies the traffic demands in the communication area).

  FIG. 1 is a block diagram illustrating the configuration of the position detection device. The position detection device 100 is based on various data acquired from the input device 200, a condition that all traffic demands are accommodated (constraint condition), and a condition that the installation cost of the base station is minimized (optimization condition). Is detected based on a graph (which will be described later with reference to FIGS. 7 and 8) with candidate positions for installing base stations as nodes, and an installation area determined by the detected installation position is output. To do. Thereby, the position detection apparatus 100 can detect a position having a high degree of freedom in installing the base station, and can output an area determined by the detected position.

First, the configuration of the position detection device and the input device will be described.
The input device 200 includes map data, data representing a predetermined size, data representing a predetermined optimization condition, data representing a predetermined constraint condition, predetermined land classification data, Is input to the position detection apparatus 100.

  The map data is map data representing a predetermined range (communication area). The data representing the predetermined size is data representing the size of each area (hereinafter referred to as “BIN”) obtained by dividing the map into a mesh shape. In addition, the data representing the predetermined optimization condition is data representing the installation cost of the base station in the present embodiment. Note that the data representing the optimization condition may include data representing an end condition (such as a threshold) in the optimization process.

  Further, in the present embodiment, the data representing a predetermined constraint condition is data representing the traffic demand (required capacity). The data representing the traffic demand may be data in which future traffic demand is predicted (hereinafter referred to as “traffic demand forecast data”).

  Predetermined land classification data is data representing, for each BIN, whether the location where the base station is installed is a residential area or a forested area. This land classification data is referred to, for example, when the base station installation cost is calculated for each BIN. In addition, when land classification does not need to be considered, land classification data does not need to be input into the position detection apparatus 100.

  The input device 200 inputs data representing the frequency band of the base station, data representing the transmission power of the base station, and data representing a model equation for propagation loss to the position detection device 100. Here, the propagation loss model expression is an expression representing a procedure for calculating the propagation loss, and is, for example, a propagation loss model expression such as a ray trace or a Walfisch-Ikegami model.

  The parameter of the propagation loss model formula may include a parameter representing land classification data. By including this parameter in the model expression of the propagation loss, the position detection device 100 can accurately calculate the propagation loss for each land section. Note that the input device 200 may input data directly representing the propagation loss to the position detection device 100 instead of the data representing the model expression of the propagation loss.

  The input device 200 transmits signal-to-interference and noise ratio (SINR) -packet error rate (PER) conversion table data and MCS (Modulation and Coding Scheme) table data (described later with reference to FIG. 4) to the position detection device 100. input.

  The position detection apparatus 100 includes an area setting unit 110, a characteristic calculation unit 120, a storage unit 130, an optimization unit 140, and an output unit 150.

  The area setting unit 110 includes map data, data representing a predetermined size, data representing a predetermined optimization condition, data representing a predetermined constraint condition, and a predetermined land classification Data is input from the input device 200.

  The area setting unit 110 determines a plurality of BINs having the input size in the map by dividing the map into a mesh shape with the input size. FIG. 2 shows an example of map data. Each BIN has a rectangular shape, for example.

  The area setting unit 110 calculates traffic demand (required capacity) for each BIN based on a BIN determined in the map and a predetermined constraint (data indicating traffic demand). In addition, the area setting unit 110 calculates the base station installation cost for each BIN based on the BIN determined in the map and data indicating the predetermined optimization conditions (data indicating the base station installation cost). To do. Here, the area setting unit 110 may calculate the installation cost of the base station for each BIN based on the land classification data for each BIN. Here, the area setting unit 110 may set a land classification (representative) having the highest area ratio among a plurality of land classifications included in one BIN as the land classification of the BIN.

  The area setting unit 110 causes the storage unit 130 to store data representing the installation cost of the base station for each BIN, data representing the traffic demand for each BIN, and map data in a predetermined range (communication area).

  Data representing the transmission power of the base station, data representing the frequency band of the base station, and data representing a model equation for propagation loss are input from the input device 200 to the characteristic calculation unit 120.

  The characteristic calculation unit 120 calculates the propagation loss for each BIN based on the data representing the transmission power of the base station, the data representing the frequency band, and the data representing the model expression of the propagation loss, and calculates the calculated for each BIN. Is stored in the storage unit 130.

  The storage unit 130 includes data representing the installation cost of the base station for each BIN, data representing the traffic demand for each BIN, map data for a predetermined range (communication area), and data representing the propagation loss for each BIN. Remember.

  In addition, data representing the price of the base station is input from the input device 200 to the storage unit 130. The storage unit 130 also receives data representing a model formula (capacity calculation formula) for calculating the traffic capacity (accommodated traffic volume), or data representing the traffic capacity for each base station. Input from the device 200. The storage unit 130 also stores these data. Here, the storage unit 130 may store data directly representing the traffic capacity instead of storing data representing a model formula for calculating the traffic capacity. The parameter of the model formula for calculating the traffic capacity may include a parameter representing the building height for each building existing in the predetermined range (communication area) of the map.

  The optimization unit 140 satisfies the constraint condition of securing a capacity that satisfies the traffic demand within a predetermined range (communication area) of the map, and the amount determined by the price and the number of installed base stations and the installation cost of each base station A complete partial graph (to be described later with reference to FIG. 8) that satisfies the optimization condition of minimizing the total amount of money is selected (optimization processing).

  The optimization unit 140 includes an acquisition unit 141, a region selection unit 142, and a graph selection unit 143. The acquisition unit 141 includes data representing the base station installation cost for each BIN, data representing the traffic demand for each BIN, map data for a predetermined range (communication area), data representing the propagation loss for each BIN, Data representing the price of the base station is acquired from the storage unit 130. In addition, the acquisition unit 141 selects the data stored in the storage unit 130 among data representing a model expression for calculating the traffic capacity and data representing the traffic capacity for each base station. , Acquired from the storage unit 130.

  The area selection unit 142 receives these data acquired from the storage unit 130 by the acquisition unit 141 from the acquisition unit 141 (initial setting). The area selection unit 142 uses an objective function (described later) based on data representing a model formula for calculating traffic capacity, or data representing traffic capacity for each base station, and traffic demand for each BIN. ) The first candidate position and the second candidate position where the base stations required for securing the capacity that satisfies the traffic demand in the predetermined range (communication area) of the map are installed. And the number of base stations.

  Here, the 1st candidate position is one or more candidate positions which respectively install one or more base stations which constitute one side of base stations used as one set at the time of station placement design. In addition, the second candidate position is one or more candidate positions where one or more base stations constituting the other of the base stations that are set as one set at the time of station placement design are respectively installed.

  Hereinafter, as an example, the description will be continued assuming that the number of base stations calculated by the area selection unit 142 is two. Even when the calculated number of base stations is three or more, the optimization unit 140 may handle the installation positions of the base stations as one set.

  The area selection unit 142 selects a BIN from the vicinity of the first candidate position and the second candidate position where the calculated two base stations are installed. FIG. 3 shows a predetermined range (communication area) of the map including the position where the base station is installed. In FIG. 3, it is assumed that the BINs 420-1 to 420-4 included in the vicinity range 410 centered on the first candidate position 400 are selected from the plurality of BINs by the region selection unit 142. Similarly, it is assumed that the BINs 520-1 to 520-4 included in the vicinity range 510 centered on the second candidate position 500 are selected from the plurality of BINs by the region selection unit 142.

  In addition, it is assumed that a plurality of third candidate positions are determined by the area selection unit 142 in the BINs 420-1 to 420-4. Similarly, in the BINs 520-1 to 520-4, a plurality of fourth candidate positions are determined by the region selection unit 142. The arrangement of these candidate positions is an example.

  Next, an example of a method for calculating the installation cost of the base station and an example of a method for calculating the traffic capacity of the base station will be described. Here, although it is assumed that OFDMA (Orthogonal Frequency Multiple Access) is used in the communication system, the communication system is not limited to OFDMA. For example, the communication system may be a CDMA (Wideband Code Division Multiple Access) system.

In the following, i represents the identifier of BIN. The set is denoted as I. J represents the identifier of the installation position of the base station. The set is denoted as J. I _j represents a set of BIN _i covered by the base station installed at the position j. T _x represents the transmission power of the base station. C represents the price of the base station. C _j represents the installation cost when a base station is installed at position j. W _i represents the traffic demand in BIN _i . Η represents noise. G _ij represents a propagation loss from the base station installed at j to BIN _i . Further, d _ij represents a throughput value when it is assumed that all radio resources are allocated when a radio station in BIN _i is connected to a base station installed at position j. When the value of x _j is 1, x _j denotes that the base station is arranged to j. On the other hand, if the value of x _j is 0, x _j denotes that the base station is not located in j.

  First, an example of a method for calculating the installation cost of the base station will be described. The area selection unit 142 calculates the base station installation cost according to the equation (1).

Next, an example of a method for calculating the traffic capacity of the base station will be described. The area selection unit 142 calculates a throughput value for the BIN based on the signal-to-interference noise ratio (SINR) for the BIN covered by the base station. Further, the area selection unit 142 calculates the traffic capacity accommodated by the base station using the calculated throughput value. In addition, the area selection unit 142 calculates SINR _ij for BIN _i covered by the base station installed at the position j, using Expression (2).

  Here, the first term of the denominator of Equation (2) represents interference from other base stations. Further, the second term of the denominator of Equation (2) represents a noise component.

  Further, the region selection unit 142 calculates a throughput value for each BIN. Here, the region selection unit 142 refers to signal-to-interference and noise ratio (SINR) -packet error rate (PER) conversion table data and MCS (Modulation and Coding Scheme) table data.

  In the signal-to-interference noise ratio (SINR) -packet error rate (PER) conversion table, the signal-to-interference noise ratio (SINR) and the packet error rate (PER) are registered in association with each other. In the MCS table, a modulation scheme, a coding rate, and an SINR threshold are associated and registered. FIG. 4 shows an example of the MCS table. The modulation scheme includes, for example, QPSK (2), 16QAM (4), and 64QAM (6).

  Here, the calculation of the throughput value will be described by taking LTE (Long Term Evolution) adopting OFDMA for downlink communication as an example. In LTE, time × frequency radio resources are configured in units of resource blocks (Resource Blocks, RBs). Further, the resource block is composed of 7 OFDM symbols (0.5 [ms]) × 12 subcarriers. The number of bits that can be transmitted by one resource block is expressed by equation (3).

  In Equation (3), [MIMO efficiency] represents the efficiency of MIMO in the BIN. [Modulation] represents a modulation method (see FIG. 4). [Coding rate] represents a coding rate (see FIG. 4). [# Of subcarrier / RB] represents the number of subcarriers per resource block. In this example, [# of subcarrier / RB] = 12. [# Of OFDM symbol / RB] represents the number of OFDM symbols per resource block. In this example, [# of subcarrier / RB] = 7. PER represents a packet error rate. The PER is calculated using the SINR value by a signal-to-interference noise ratio (SINR) -packet error rate (PER) conversion table.

Since one resource block is 0.5 [ms], the number of resource blocks in the frequency direction of the target system is #RB, and all resource blocks are included in BIN _i covered by the base station installed at the position j. When assigned, the throughput d _ij is expressed by equation (4).

  Note that the amount of radio resources to be allocated may be limited. For example, when radio resources are allocated up to 80% of all radio resources as a margin for fluctuation factors such as fading, by replacing #RB in equation (4) with 0.8 × # RB, The region selection unit 142 can cope with such a case.

  The number of resource blocks in the frequency direction depends on the frequency bandwidth of the target system. FIG. 5 shows a table illustrating an example of the relationship among the frequency bandwidth, the number of subcarriers, and the number of resource blocks (RB). For example, the number of subcarriers corresponding to the frequency bandwidth 1.4 [MHz] is 76. The number of resource blocks corresponding to the frequency bandwidth 1.4 [MHz] is 6.

The ratio of the required radio resource amount to BIN _i covered by the base station installed at the position j is expressed by Expression (5).

  When the value of equation (6) is 1 or less, equation (6) indicates that the base station installed at position j can accommodate all traffic demands in all BINs covered by the own station. Indicates what can be done.

  On the other hand, when the value of equation (6) exceeds 1, equation (6) indicates that the base station installed at position j accommodates all traffic demands in all BINs covered by the own station. Indicates that it cannot be done. Therefore, the conditional expression of the traffic capacity (accommodated traffic volume) is expressed by Expression (7).

  Here, ξ is a coefficient representing a ratio (0 <ξ ≦ 1) of the traffic amount to be accommodated in each BIN in the communication area. Note that the value of ξ is predetermined as a parameter. In this embodiment, ξ = 1.

  Returning to FIG. 1, the description of the configuration of the position detection device will be continued. The graph selection unit 143 detects a partial graph constituting a graph having a plurality of third candidate positions and a plurality of fourth candidate positions (see FIG. 3) as nodes (nodes).

  A graph having candidate positions as nodes will be described. In FIG. 6, an example of a combination of the third candidate position and the fourth candidate position is represented by a chain line or the like. Hereinafter, the first candidate position 400 is referred to as a third candidate position 430-1. In addition, the second candidate position 500 is referred to as a fourth candidate position 530-1. Further, in FIG. 6, the graph selection unit 143 accommodates traffic demand for all combinations of the third candidate positions 430-1 to 430-13 and the fourth candidate positions 530-1 to 530-13. Is determined for each combination (see equation (7)).

  In addition, the graph selection unit 143 satisfies the traffic demand (see Equation (7)) within the predetermined range (communication area) of the map from the detected graph, and the value determined by the price of the base station and the number of base stations The largest complete subgraph is selected from complete subgraphs of feasible solutions that have the smallest total (see equation (1)) with the installation cost for each BIN where the station is installed.

  The graph selection unit 143 determines whether or not all traffic demands are accommodated for each combination of the third candidate position and the fourth candidate position. FIG. 7 shows an example of combinations of the third candidate position and the fourth candidate position that satisfy the constraint condition (condition that all traffic demands in the communication area are accommodated). In FIG. 7, among the combinations, the third candidate position 430-1, the fourth candidate position 530-1, the third candidate position 430-2, the fourth candidate position 530-1, and the third candidate position 430-2. And the fourth candidate position 530-2, the third candidate position 430-3 and the fourth candidate position 530-1, and the third candidate position 430-3 and the fourth candidate position 530-2 satisfy the constraint condition. Suppose that

  Here, the graph selection unit 143 treats candidate positions for installing base stations as nodes (nodes) in graph theory.

  The location where the base station is installed needs to be a feasible solution that is a location that does not depend on the location of other base stations. The graph selection unit 143 selects a complete subgraph that maintains a combination of candidate positions of each base station that is an executable solution, from a graph having candidate positions of each base station that constitute an executable solution as a node.

  Hereinafter, a process (optimization process) for detecting a candidate position that satisfies the optimization condition (a condition that minimizes the total amount of the base station price and the number of installed base stations and the installation cost of each base station) explain. In the optimization process, the number of base stations and the installation area are detected so that the largest complete subgraph is selected, that is, the value of the evaluation function is maximized.

  The algorithm for detecting candidate positions that satisfy the optimization condition is not limited to the algorithm shown as an example below, and may be another algorithm as long as it is an algorithm for obtaining a complete subgraph from a graph.

  First, the graph selection unit 143 selects a partial graph G that is an initial value from a plurality of graphs that use the candidate positions of the base stations that are feasible solutions as nodes. For example, the graph selection unit 143 selects a plurality of combinations at random from the combinations of candidate positions, and sets the partial graph G having the installation positions constituting the selected combinations as nodes as initial values. Note that the subgraph G set as the initial value does not have to be a complete subgraph.

  In addition, the graph selection unit 143 is a complete partial graph in which the value of the evaluation function is maximized, and stores all the complete graphs when all combinations of candidate positions of the base station are feasible solutions. A variable “Best” is prepared.

  The graph selection unit 143 performs the following operation on the initial value of the subgraph G until the end condition is satisfied. Here, the end condition is, for example, the number of times the candidate position p is added to or excluded from the subgraph G (number of iterations) or the number of times that the value of the evaluation function (evaluation value) is not updated. The end condition may be one of these two end conditions, or a combination of these two end conditions, that is, “the number of iterations 反復 the number of times that the evaluation value is not updated” or “the number of iterations”. The number of consecutive times that the evaluation value is not updated ") may be used.

  The value of the evaluation function (evaluation value) is the number of branches included in the subgraph G currently selected by the graph selection unit 143. In addition, data representing candidate positions p added to the subgraph G (subset) and candidate positions p excluded from the subgraph G are added to the tabu list. The candidate position p added to the tabu list is prohibited from being added to or removed from the subgraph G during the period of being added to the tabu list. Note that the taboo length is predetermined as a parameter.

  When the currently selected subgraph G is a complete subgraph and all combinations of base station candidate positions are feasible solutions, the graph selection unit 143 determines that the evaluation value of the complete subgraph is a variable It is determined whether or not the evaluation value is higher than the evaluation value of the complete subgraph already stored in “Best”. When the evaluation value is higher than the evaluation value of the complete subgraph already stored in the variable “Best”, the graph selection unit 143 converts the complete subgraph stored in the variable “Best” into the newly evaluated complete subgraph. Update.

  Further, the graph selection unit 143 adds the candidate position p having the maximum evaluation function (G∪ {p}) among the candidate positions p not included in the subgraph G to the subgraph G, and creates a new part. A graph G is created. In addition, the graph selection unit 143 adds the candidate position p added to the subgraph G to the tabu list. The graph selection unit 143 does not exclude the candidate position p from the subgraph G during the period when the candidate position p is added to the taboo list.

  On the other hand, when the currently selected subgraph G is not a complete subgraph, the graph selection unit 143 has the smallest value of the evaluation function (G− {p}) among the candidate positions p included in the subgraph G. The candidate position p which becomes is excluded from the subgraph G, and a new subgraph G is created. In addition, the graph selection unit 143 adds the candidate position p excluded from the partial graph G to the taboo list. The graph selection unit 143 prevents the candidate position p from being added to the subgraph G while the candidate position p is added to the taboo list.

  Further, from the graph shown as an example in FIG. 7, a complete partial graph in which candidate positions satisfying the constraints and optimization conditions are nodes and all combinations of candidate positions (nodes) of the base station are feasible solutions, It is selected by the graph selection unit 143 (installation position listing process).

  FIG. 8 illustrates an example of a complete subgraph in which candidate positions that satisfy the constraint conditions and the optimization conditions are nodes, and all combinations of base station candidate positions are feasible solutions. In FIG. 8, as an example, the third candidate position 430-2 and the fourth candidate position 530-1, the third candidate position 430-2 and the fourth candidate position 530-2, the third candidate position 430-3 and the Assume that all combinations of the four candidate positions 530-1, the third candidate position 430-3, and the fourth candidate position 530-2 are feasible solutions.

  The graph selection unit 143 detects a region determined by a candidate position that is a node of the selected complete subgraph (region detection processing). FIG. 9 shows an example of a region determined by the third candidate position that satisfies the constraint condition and the optimization condition. In FIG. 9, an area 440-2 having the third candidate position 430-2 as a representative point is represented. Further, an area 440-3 having the third candidate position 430-3 as a representative point is shown. Thus, the region where the constraint condition and the optimization condition are satisfied is determined such that the candidate position becomes a representative point. Further, data representing an area where the constraint condition and the optimization condition are satisfied is stored in the storage unit 130 by the graph selection unit 143.

  The output unit 150 acquires and outputs data representing an area where the constraint condition and the optimization condition are satisfied from the storage unit 130 (output process). FIG. 10 shows an example of the output area. For example, the output unit 150 acquires data representing the regions 440 and 540 that satisfy the constraint condition and the optimization condition, and map data including a predetermined range (communication area), and maps the regions 440 and 540 to the map. Is displayed on the screen. Further, the output unit 150 may display a graphic representing BIN on the screen by superimposing it on a map.

Next, the operation procedure of the position detection device will be described.
FIG. 11 is a flowchart showing an operation procedure of the position detection apparatus. The optimization unit 140 includes data representing the installation cost of the base station for each BIN, data representing the traffic demand for each BIN, map data in a predetermined range, data representing the propagation loss for each BIN, Data representing a price and data representing a model expression for calculating the traffic capacity or data representing the traffic capacity for each base station is acquired from the storage unit 130 as an initial setting (step S1). .

  The optimization unit 140 determines a predetermined range of the map based on data representing a model expression for calculating traffic capacity, or data representing traffic capacity for each base station, and traffic demand for each BIN. The number of base stations required to secure a capacity that satisfies the traffic demand in (communication area), and the first candidate position and the second candidate position where the base station is installed are calculated.

  The optimization unit 140 satisfies the constraint condition that all traffic demands are accommodated in the communication area, and minimizes the sum of the amount determined by the price and the number of installed base stations and the installation cost of each base station. The complete subgraph that satisfies the optimization condition is selected. The optimization unit 140 causes the storage unit 130 to store data representing a region where the constraint condition and the optimization condition are satisfied (step S2).

  The output unit 150 acquires data representing an area where the constraint condition and the optimization condition are satisfied from the storage unit 130 and outputs the data. For example, the output unit 150 acquires data representing the regions 440 and 540 that satisfy the constraint condition and the optimization condition, and map data including a predetermined range (communication area), and maps the regions 440 and 540 to the map. And is displayed on the screen (step S3).

  FIG. 12 is a flowchart showing the operation procedure of the optimization unit. The area selection unit 142 (see FIG. 1) represents data representing the installation cost of the base station for each BIN, data representing the traffic demand for each BIN, map data in a predetermined range, and propagation loss for each BIN. From the acquisition unit 141, data, data representing the price of the base station, data representing a model expression for calculating the traffic capacity, or data representing the traffic capacity for each base station are set as initial settings. Receive (step Sa1).

  The area selection unit 142 is configured to generate a predetermined range of the map based on data representing a model expression for calculating traffic capacity, or data representing traffic capacity for each base station, and traffic demand for each BIN. The number of base stations required to secure a capacity that satisfies the traffic demand in (communication area), and the first candidate position and the second candidate position where the base station is installed are calculated.

The graph selection unit 143 detects a partial graph that constitutes a graph having a plurality of third candidate positions and a plurality of fourth candidate positions (see FIG. 3) as nodes. Further, the graph selection unit 143 satisfies the traffic demand (see Expression (7)) within a predetermined range (communication area) of the map from the detected partial graphs, and is determined by the price of the base station and the number of the base stations. The largest complete subgraph is selected from complete subgraphs consisting of feasible solutions having the smallest sum of the value and the installation cost for each BIN where the base station is installed (see equation (1)) (step Sa2). .
The graph selection unit 143 detects a region determined by a candidate position that is a node of the selected complete subgraph (step Sa3).

As described above, the position detection apparatus 100 includes map data including a predetermined range (communication area), data indicating a predetermined size, and predetermined optimization conditions (such as base station installation costs). ) And data representing a predetermined constraint condition (traffic demand), and by dividing the map by the size, a plurality of BINs of the size are determined on the map. Based on the region setting unit 110 that calculates the constraint condition (traffic demand) and the optimization condition (base station installation cost, etc.) for each BIN, and the transmission power and frequency band of the base station, Based on the characteristic calculation unit 120 for calculating the propagation loss for each BIN, the restriction condition for each BIN, and data representing the traffic capacity for each base station, the restriction condition in the range. The number of base stations required to secure the capacity that satisfies (traffic demand), and one or more first candidate positions 400 and one or more first stations respectively installed with one or more base stations. BIN 420-1 to 420-4, BIN520-1 to BIN520-1 from the vicinity of the first candidate position 400 and the second candidate position 500 where the number of base stations corresponding to the number is calculated. Area selection unit 142 for selecting 520-4, third candidate positions 430-1 to 430-13 determined for BINs 420-1 to 420-4 selected from the vicinity of first candidate position 400, and second candidates Of the partial graphs constituting the graph having the fourth candidate positions 530-1 to 530-13 defined for the BINs 520-1 to 520-4 selected from the vicinity of the position 500 as nodes In addition, the value (total of installation costs, etc.) determined by the optimization conditions (base station installation costs, etc.) for each BIN is optimal (minimum) while satisfying the constraint conditions (traffic demand) within the range. A graph selection unit 143 that selects the largest complete subgraph of the complete subgraphs of feasible solutions, and an output unit 150 that outputs the region 440 and the region 540 determined by the position of the node of the selected complete subgraph. Prepare.
With this configuration, the position satisfying the constraint condition and the optimization condition is detected from the graph with the candidate position where the base station is installed as a node, and the region determined by the detected position is output. A position with a high degree of freedom for installing the base station can be detected, and an area determined by the detected position can be output.

Further, the area setting unit 110 obtains data representing the installation cost of the base station as data representing a predetermined optimization condition, thereby calculating the installation cost for each of the BINs. By obtaining data representing traffic demand as data representing conditions, the traffic demand for each BIN is calculated, and the area selecting unit 142 determines the traffic demand and traffic capacity for each BIN. And the number of base stations required to secure the capacity that satisfies the traffic demand in the range, the first candidate position 400, and the second candidate position BIN 420-1 to BIN 420-1 from the vicinity of the first candidate position 400 and the second candidate position 500 in which the number of base stations to be combined is calculated. 20-4 and BIN520-1 to 520-4 are selected, respectively, and the graph selection unit 143 selects the third candidate position 430-1 determined for the BIN420-1 to 420-4 selected from the vicinity of the first candidate position 400. -430-13 and a partial graph constituting a graph having nodes as fourth candidate positions 530-1 to 530-13 defined in BINs 520-1 to 520-4 selected from the vicinity of the second candidate position 500 The feasible solution that satisfies the traffic demand in the range, and that the sum of the value determined by the price and the number of base stations and the installation cost for each BIN in which the base stations are installed is minimized. Select the largest complete subgraph of the complete subgraphs.
With this configuration, the location that satisfies the conditions for minimizing traffic demand conditions and base station installation costs, etc., is detected from the graph with the candidate location for installing the base station as a node, and the region determined by the detected location is output. As a result, the position detection device can detect a position with a high degree of freedom in installing the base station and output an area determined by the detected position.

<About constraints>
The combination of candidate positions that satisfy the constraint conditions changes according to the data that is referred to in determining whether the constraint conditions are met.
When the amount of traffic accommodated is used as the constraint, one of data representing traffic demand in the communication area (service area), traffic demand prediction data, data representing traffic capacity, and data representing the capacity calculation formula The above is referred to in determining whether the constraint condition is satisfied.

  Here, one or more of the signal-to-interference and noise ratio (SINR) -packet error rate (PER) conversion table data and the SINR-MCS conversion table data according to the data representing the capacity calculation formula are constraints. It may be referred to in determining whether or not the above is satisfied.

  When the required received power is used as the constraint condition, data representing the required received power is referred to in determining whether the constraint condition is satisfied. When the required SINR is used as the constraint condition, data representing the required SINR is referred to in determining whether the constraint condition is satisfied.

<About propagation loss>
Data representing building height, data representing building shape, data representing altitude, data representing antenna height, data representing antenna gain, data representing antenna pattern, antenna tilt angle, depending on data representing a model equation for propagation loss One or more of the data representing the base station and the data representing the installed height of the base station may be referred to when the propagation loss is calculated.

  Here, when changing the model formula of the propagation loss for each land classification, the land classification data may be referred to when the propagation loss is calculated. Thereby, the position detection apparatus can calculate the propagation loss with high accuracy.

[Second Embodiment]
A second embodiment of the present invention will be described in detail with reference to the drawings. In the second embodiment, a condition for maximizing a coverage range that satisfies the required received power is set as an example of an optimization condition in station placement design. In addition, as an example of a constraint condition in station placement design, a condition that satisfies traffic demand (capacity) is set. Only the differences from the first embodiment will be described below.

  The area setting unit 110 (see FIG. 1) includes map data, data representing a predetermined size, data representing a predetermined optimization condition, data representing a predetermined constraint condition, Predetermined land classification data is input from the input device 200 (see FIG. 1). Here, as the data representing the optimization condition, the region setting unit 110 includes data representing the required received power, data representing the required signal-to-interference noise ratio, and data representing the installation height of the base station as input devices. 200 is input.

  The region setting unit 110 calculates received power and a signal-to-interference noise ratio for each BIN. In addition, the area setting unit 110 calculates traffic demand for each BIN by acquiring data representing traffic demand as data representing predetermined constraint conditions.

  The area selection unit 142 (see FIG. 1) satisfies the traffic demand in a predetermined range (communication area) of the map based on the traffic demand for each BIN and the data representing the traffic capacity for each base station. The number of base stations required to secure the capacity, one or more first candidate positions 400, and one or more second candidate positions 500 are calculated. Hereinafter, as an example, the description is continued assuming that the calculated number of base stations is two. The area selection unit 142 selects BINs from the vicinity of the first candidate position and the second candidate position where the two calculated base stations are installed.

  The graph selection unit 143 includes a plurality of third candidate positions defined in the BIN selected from the vicinity of the first candidate position (see FIG. 3) and the BIN selected from the vicinity of the second candidate position (see FIG. 3). BIN groups satisfying the traffic demand in the predetermined range (communication area) of the map and satisfying the required received power from among the partial graphs constituting the graph having a plurality of fourth candidate positions defined in the node as nodes. The largest complete subgraph (see FIG. 8) is selected from the complete subgraphs having the maximum feasible solution.

As described above, the area setting unit 110 includes, as data representing predetermined optimization conditions, data representing required received power, data representing a required signal-to-interference noise ratio, and data representing installation height. By calculating the received power and the signal-to-interference / noise ratio for each BIN, and acquiring data representing traffic demand as data representing a predetermined constraint condition, the traffic for each BIN is obtained. Based on the traffic demand for each BIN and the data representing the traffic capacity for each base station, the area selecting unit 142 satisfies the traffic demand in the range. The number of base stations required to secure the quantity, the first candidate position 400 and the second candidate position 500 are calculated, and the base stations that are the number of the total are calculated. BIN 420-1 to 420-4 and BIN 520-1 to 520-4 are selected from the vicinity of the first candidate position 400 and the second candidate position 500 to be installed, respectively, and the graph selection unit 143 selects the first candidate position 400. The third candidate positions 430-1 to 430-13 determined for the BINs 420-1 to 420-4 selected from the vicinity and the BINs 520-1 to 520-4 selected from the vicinity of the second candidate positions 500 The BIN group (coverage) that satisfies the traffic demand in the range and satisfies the required received power from among the partial graphs constituting the graph having the four candidate positions 530-1 to 530-13 as nodes. Select the largest complete subgraph of feasible solutions with the largest.
With this configuration, the traffic demand condition and the position that satisfies the coverage maximization condition are detected from the graph with the candidate position where the base station is installed as a node, and an area determined by the detected position is output. The position detection device can detect a position with a high degree of freedom in installing the base station, and can output an area determined by the detected position.

<About constraints>
When installation cost or the like is used as the constraint condition, one or more of data representing the price of the base station and data representing the installation cost of the base station are referred to in determining whether or not the constraint condition is satisfied.

  In addition, in the case where the accommodation traffic volume is used as the constraint condition, the data representing the traffic demand in the communication area (service area), the traffic demand prediction data, the data representing the traffic capacity, and the data representing the capacity calculation formula One or more are referred to in determining whether the constraint condition is satisfied.

  Here, one or more of the signal-to-interference and noise ratio (SINR) -packet error rate (PER) conversion table data and the SINR-MCS conversion table data according to the data representing the capacity calculation formula are constraints. It may be referred to in determining whether or not the above is satisfied.

<About propagation loss>
Data representing building height, data representing building shape, data representing altitude, data representing antenna height, data representing antenna gain, data representing antenna pattern, antenna tilt angle, depending on data representing a model equation for propagation loss One or more of the data representing the base station and the data representing the installed height of the base station may be referred to when the propagation loss is calculated.

  Here, when changing the model formula of the propagation loss for each land classification, the land classification data may be referred to when the propagation loss is calculated. Thereby, the position detection apparatus can calculate the propagation loss with high accuracy.

[Third Embodiment]
A third embodiment of the present invention will be described in detail with reference to the drawings. In the third embodiment, a condition for maximizing the traffic capacity is set as an example of an optimization condition in station placement design. In addition, as an example of a constraint condition in the station placement design, a condition is set such that the total of base station installation costs and the like is set to a predetermined threshold value or less. Hereinafter, only differences from the first embodiment and the second embodiment will be described.

  The area setting unit 110 (see FIG. 1) includes map data, data representing a predetermined size, data representing a predetermined optimization condition, data representing a predetermined constraint condition, Predetermined land classification data is input from the input device 200 (see FIG. 1). Here, the area setting unit 110 includes, as data representing the optimization conditions, data representing an antenna pattern, data representing traffic demand, and data representing a procedure for calculating the traffic capacity for each base station. Are input from the input device 200.

  The area setting unit 110 calculates the traffic capacity for each BIN. In addition, the area setting unit 110 calculates the base station installation cost for each BIN by acquiring data representing the base station installation cost as data representing a predetermined constraint.

  The area selection unit 142 (see FIG. 1) indicates the number of base stations in which the sum of the value determined by the price and the number of base stations and the base station installation cost for each BIN in which the base stations are installed is equal to or less than a predetermined threshold. , One or more first candidate positions 400 and one or more second candidate positions 500 are calculated. The area selection unit 142 selects each BIN from the vicinity of the first candidate position and the second candidate position where the base stations that are equal to or less than the maximum value of the number are installed.

  The graph selection unit 143 includes a plurality of third candidate positions defined in the BIN selected from the vicinity of the first candidate position (see FIG. 3) and a plurality of BINs selected in the vicinity of the second candidate position. Among the partial graphs constituting the graph with the fourth candidate position (see FIG. 3) as a node, the value determined by the price and number of base stations, and the installation of the base station for each BIN where the base station is installed The largest complete subgraph (Fig. 8) is composed of feasible solutions whose total cost is equal to or less than a predetermined threshold and which has the maximum total traffic capacity for each BIN in which the base station is installed. Select).

  Further, according to the data representing the capacity calculation formula, one or more of the signal-to-interference and noise ratio (SINR) -packet error rate (PER) conversion table data and the SINR-MCS conversion table data have a constraint condition. It may be referred to in the determination of whether or not it is satisfied.

As described above, the area setting unit 110 calculates data representing an antenna pattern, data representing traffic demand, and traffic capacity for each base station as data representing predetermined optimization conditions. By calculating the traffic capacity for each BIN, and acquiring data representing the installation cost of the base station as data representing a predetermined constraint condition. The area selection unit 142 calculates the installation cost for each BIN, and the total of the installation cost for each BIN in which the base station is installed is equal to or less than a predetermined threshold. The first candidate position in which the base station that calculates the maximum value of the number of units, the first candidate position, and the second candidate position is set to be equal to or less than the maximum value is calculated. 400 and BIN 420-1 to 420-4 and BIN 520-1 to 520-4 are selected from the vicinity of the second candidate position 500, and the graph selection unit 143 selects the BIN 420-1 selected from the vicinity of the first candidate position 400. To fourth candidate positions 530-1 to 430-1 determined for BINs 520-1 to 520-4 selected from the vicinity of the second candidate position 500. 530-13, and the total of the traffic capacity for each BIN in which the base station is installed is the maximum, and the total is less than the predetermined threshold value. The largest complete subgraph is selected from complete subgraphs consisting of feasible solutions.
With this configuration, a position satisfying conditions such as installation costs and traffic capacity maximization is detected from a graph with a candidate position for installing a base station as a node, and an area determined by the detected position is output. Thus, the position detection device can detect a position with a high degree of freedom in installing the base station, and can output an area determined by the detected position.

<About constraints>
When the cost is used for the constraint condition, one or more of the data representing the price of the base station and the data representing the installation cost of the base station are referred to in determining whether or not the constraint condition is satisfied.
When the required received power is used as the constraint condition, data representing the required received power is referred to in determining whether the constraint condition is satisfied. When the required SINR is used as the constraint condition, data representing the required SINR is referred to in determining whether the constraint condition is satisfied.

<About propagation loss>
Data representing building height, data representing building shape, data representing altitude, data representing antenna height, data representing antenna gain, data representing antenna pattern, antenna tilt angle, depending on data representing a model equation for propagation loss One or more of the data representing the base station and the data representing the installed height of the base station may be referred to when the propagation loss is calculated.

  Here, when changing the model formula of the propagation loss for each land classification, the land classification data may be referred to when the propagation loss is calculated. Thereby, the position detection apparatus can calculate the propagation loss with high accuracy.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes designs and the like that do not depart from the gist of the present invention.

  For example, the position detection device may include a database that stores in advance various data input from the input device. Each unit of the position detection device may acquire the various data stored in the database instead of the various data input from the input device, and execute the operation described above.

  In addition, for example, in the above-described embodiment, a case where a base station is newly installed in a communication area where the base station is not deployed has been described. However, the position detection device may be installed in a communication area where the base station is already deployed. It can also be applied when adding more stations. In this case, the area setting unit acquires data representing the position where the existing base station is installed from the input device or the database.

  Further, for example, in the above-described embodiment, the placement arrangement in the placement station design has been described. However, not only the placement arrangement, but also the position detection device can transmit base station transmission power and base station parameters (for example, antenna tilt). (Corner) may be optimized together with the station placement.

  Further, for example, the number of installed base stations is not limited to one type, and may be a plurality of types such as a macro base station and a pico base station. In this case, a model equation for propagation loss may be determined for each type of base station.

  Further, for example, the data representing the candidate position may be represented by a set of data representing each coordinate (for example, latitude and longitude) of the candidate position, or represented by data representing an area (range) including each candidate position. May be. When the candidate position is expressed by data representing the area, in addition to the data representing the area including the candidate position, the data representing the total number of candidate positions or the data representing the number of candidate positions for each BIN is stored in the position detection device. It may be entered.

  Note that a program for realizing the position detection device described above may be recorded on a computer-readable recording medium, and the program may be read into a computer system and executed. Here, the “computer system” includes an OS and hardware such as peripheral devices. The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Further, the “computer-readable recording medium” refers to a volatile memory (RAM) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, those holding programs for a certain period of time are also included. The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, what is called a difference file (difference program) may be sufficient.

DESCRIPTION OF SYMBOLS 100 ... Position detection apparatus 110 ... Area | region setting part 120 ... Characteristic calculation part 130 ... Memory | storage part 140 ... Optimization part 141 ... Acquisition part 142 ... Area selection part 143 ... Graph selection part 150 ... Output , 200 ... input device, 400 ... first candidate position, 410 ... neighborhood range, 420-1 to 420-4 ... BIN, 430-1 to 430-13 ... third candidate position, 440, 440-2, 440- 3 ... area, 500 ... second candidate position, 510 ... neighborhood range, 520-1 to 520-4 ... BIN, 530-1 to 530-13 ... fourth candidate position, 540, 540-2, 540-3 ... area

Claims (5)

Map data including a predetermined range, data representing a predetermined size, data representing a predetermined optimization condition, and data representing a predetermined constraint condition, and acquiring the map A plurality of regions of the size by dividing the map by the size, a region setting unit for calculating the constraint condition for each region and the optimization condition for each region;
Based on the transmission power and frequency band of the base station, a characteristic calculation unit that calculates a propagation loss for each region;
The number of base stations required to secure the capacity that satisfies the constraint condition in the range based on the constraint conditions for each area and the data representing the traffic capacity for each base station And one or more first candidate positions and one or more second candidate positions for installing one or more base stations, respectively, and the number of the base stations to be installed is calculated. An area selection unit that selects each of the areas from the vicinity of one candidate position and the second candidate position;
A plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidate positions defined in the region selected from the vicinity of the second candidate position Among the subgraphs constituting the graph, the largest of the complete subgraphs that are feasible solutions that satisfy the constraint condition in the range and that have the optimum value determined by the optimization condition for each region. A graph selector for selecting a complete subgraph;
An output unit for outputting an area determined by the position of the node of the selected complete subgraph;
A position detection device comprising: The area setting unit obtains data representing the installation cost of a base station as data representing the optimization condition, thereby calculating the installation cost for each area, and data representing the predetermined constraint condition By calculating data representing the traffic demand, the traffic demand for each region is calculated,
In order to secure the capacity that satisfies the traffic demand in the range based on the traffic demand for each area and data that represents the traffic capacity for each base station, the area selection unit The required number of base stations, the first candidate position and the second candidate position are calculated, and the first candidate position and the second candidate where the number of the base stations to be installed together are calculated. Select each of the regions from the vicinity of the position,
The graph selection unit includes a plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidates defined in the region selected from the vicinity of the second candidate position. For each of the areas where the base station is installed and the value determined by the price and the number of base stations satisfying the traffic demand in the range from among the partial graphs constituting the graph with the candidate position as a node The position detection device according to claim 1, wherein the largest complete subgraph is selected from among the complete subgraphs that are feasible solutions that have the smallest total of the installation costs. The area setting unit obtains, as data representing the optimization condition, data representing required received power, data representing a required signal-to-interference noise ratio, and data representing a base station installation height, The received power and signal-to-interference / noise ratio for each region are calculated, and the traffic demand is calculated for each region by obtaining data representing the traffic demand as data representing the predetermined constraint conditions. And
In order to secure the capacity that satisfies the traffic demand in the range based on the traffic demand for each area and data that represents the traffic capacity for each base station, the area selection unit The required number of base stations, the first candidate position and the second candidate position are calculated, and the first candidate position and the second candidate where the number of the base stations to be installed together are calculated. Select each of the regions from the vicinity of the position,
The graph selection unit includes a plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidates defined in the region selected from the vicinity of the second candidate position. Among the partial graphs constituting the graph with the candidate position as a node, the region group satisfying the traffic demand in the range and satisfying the required reception power and the required signal-to-interference noise ratio is the maximum. The position detection device according to claim 1, wherein the largest complete subgraph is selected from among the complete subgraphs including the feasible solutions. The area setting unit includes, as data representing the optimization condition, data representing an antenna pattern, data representing traffic demand, and data representing a procedure for calculating the traffic capacity for each base station. Obtaining the traffic capacity for each area by obtaining and obtaining the data representing the installation cost of a base station as the data representing the predetermined constraint condition, thereby obtaining the installation for each area Calculate the cost,
The area selection unit includes a maximum value of the number of units in which a sum of a value determined by the price of the base station and the number of the base stations and the installation cost for each of the areas in which the base stations are installed is equal to or less than a predetermined threshold, and the first The candidate position and the second candidate position are calculated, and the areas are respectively selected from the vicinity of the first candidate position and the second candidate position where the base station that is equal to or less than the maximum value is installed. ,
The graph selection unit includes a plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidates defined in the region selected from the vicinity of the second candidate position. Among the partial graphs constituting the graph with the candidate position as a node, the sum is equal to or less than the predetermined threshold, and the total traffic capacity for each region in which the base station is installed is the maximum. The position detection device according to claim 1, wherein the largest complete subgraph is selected from among the complete subgraphs including the feasible solutions. On the computer,
Map data including a predetermined range, data representing a predetermined size, data representing a predetermined optimization condition, and data representing a predetermined constraint condition, and acquiring the map A plurality of regions of the size in the map by dividing the map by the size, and calculating the constraint condition for each region and the optimization condition for each region;
A procedure for calculating a propagation loss for each region based on the transmission power and frequency band of the base station,
The number of base stations required to secure the capacity that satisfies the constraint condition in the range based on the constraint conditions for each area and the data representing the traffic capacity for each base station And one or more first candidate positions and one or more second candidate positions for installing one or more base stations, respectively, and the number of the base stations to be installed is calculated. Selecting each of the regions from the vicinity of one candidate position and the second candidate position;
A plurality of third candidate positions defined in the region selected from the vicinity of the first candidate position and a plurality of fourth candidate positions defined in the region selected from the vicinity of the second candidate position Among the subgraphs constituting the graph, the largest of the complete subgraphs that are feasible solutions that satisfy the constraint condition in the range and that have the optimum value determined by the optimization condition for each region. A graph selector for selecting a complete subgraph;
Outputting a region determined by the position of the node of the selected complete subgraph;
Position detection program to execute.

Images