JP2019041294A - Intensive range determination device, program to be executed by computer and computer readable recording medium recording program - Google Patents

Abstract

To provide an intensive range determination device for determining an intensive range capable of restraining deterioration of power estimation accuracy.SOLUTION: An intensive range determination device 1 includes calculation means 14 and determination means 15. The calculation means 14 calculates a sample number N_P required for calculation of data having reliability P in an evaluation area on the basis of a K factor in fading of an evaluation area becoming the object for determining the intensive range, and calculates the data sample number N_agg in the data intensive range on the basis of the density of terminals, data acquisition period, data aggregation time and the area of data aggregation range. The determination means 15 determines a processing range Rcapable of reducing the impact of fading so as to satisfy a relation N_agg>N_P, determines a processing range Rso that the power estimation error due to positional error of power estimation granularity indicating the interval for obtaining the power of electromagnetic wave and the processing range Rbecomes smaller than an allowance, and then determines such a processing range Ras R≥Ras the intensive range.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an aggregation range determination device, a program for causing a computer to execute, and a computer-readable recording medium on which the program is recorded.

  In order to satisfy various communication performance requirements in the fifth generation mobile communication system, additional frequency resources are required. Among them, a technique for sharing a frequency that is not used in time and place is attracting attention (Non-Patent Document 1). In order to share the frequency, it is necessary to sequentially grasp the usage status of the primary user so as not to interfere with the existing wireless system (primary user). On the other hand, a system that estimates the usage status (power distribution) of a primary user using a mobile device as a sensor terminal has been proposed (Non-Patent Document 2). In addition, in order to reduce the amount of data when the mobile device sends data to the server, a data aggregation method using passing communication of the mobile device has also been proposed (Non-Patent Document 3).

Ministry of Internal Affairs and Communications, “Radio Policy 2020 Roundtable Report”, June 2016. Matsuno, et al., "Efforts for frequency sharing between different radio systems in 5th generation mobile communication systems," IEICE Tech., RCS116, Oct. 2016. Tamai, et al., “Inter-terminal data collection method for reducing cellular communication load in participatory sensing,” Proc. 24th Multimedia Communication and Distributed Processing Workshop, pp.84-91, Oct. 2016.

  However, if the range in which data is aggregated is increased, the power estimation accuracy is lowered, so that the aggregation range must be optimized. In an actual radio wave environment, fading affects power.

  Therefore, according to the embodiment of the present invention, there is provided an aggregation range determination device that determines an aggregation range in which a decrease in power estimation accuracy can be suppressed.

  In addition, according to the embodiment of the present invention, there is provided a program for causing a computer to execute determination of an aggregation range that can suppress a decrease in power estimation accuracy.

  Furthermore, according to the embodiment of the present invention, there is provided a computer-readable recording medium in which a program for causing a computer to execute an aggregation range determination capable of suppressing a decrease in power estimation accuracy is recorded.

(Configuration 1)
According to the embodiment of the present invention, the aggregation range determination device includes a calculation unit and a determination unit. The calculating means calculates the number of samples N_P necessary for calculating data having reliability P in the evaluation area based on the K factor in fading of the evaluation area for which the aggregation range is determined, and the density of the terminal device Based on σ, the data acquisition cycle t ₀ in the terminal device, the data aggregation time T, and the area S of the data aggregation range, the number of data samples N_agg in the data aggregation range is calculated. The determining means determines a minimum processing range as a processing range R _{f in} which the influence of fading can be reduced in a range where the number of samples N_P is smaller than the number of data samples N_agg, and also indicates power estimation granularity indicating an interval for obtaining radio wave power determining the maximum processing range power estimation error due to the error in the position of the processing range R _d M and the data is smaller than the allowable error P _d as a processing range R _d of the data, processing range R _d is processing range R _f When this is the case, the processing range _Rf is determined as the aggregation range.

According to the configuration 1, the power estimation error, as the smaller the larger the determined processing range R _f by determination means, processing range R _d determined becomes smaller decreases by determination means. When the processing range R _d is _{equal to} or _larger than the processing range R _f , determining the processing range R _f as an aggregation range includes (A) a processing range R _d for reducing the power estimation error, and (B) a power estimation error. This is equivalent to achieving both the processing range R _f for reducing the process range R _f .
Therefore, when the processing range R _d is _{equal to} or greater than the processing range R _f , by determining the processing range R _f as an aggregation range, it is possible to determine the aggregation range while suppressing a decrease in power estimation accuracy.

(Configuration 2)
In the configuration 1, the calculation means calculates the number of data samples N_agg within the data aggregation range by σ × (T / t ₀ ) × S. The determining means detects the minimum area S _MIN that satisfies σ × (T / t ₀ ) × S> N, and determines the processing range R _f based on the detected area S _MIN .

According to Configuration 2, since the minimum area S _MIN of the data aggregation range is determined in a range where the number of data samples is larger than the number of samples N_P, the number of samples N_P necessary for calculating data having the reliability P is secured. The processing range R _f can be determined above.

(Configuration 3)
In the configuration 1 or the configuration 2, when the processing range R _d is larger than the processing range R _f , the determination unit relaxes the number of samples N_P or the allowable error P _d , and the power estimation error becomes the allowable error P _d or the relaxed allowable The determination process for determining the data processing range R _d so as to be smaller than the error P _d is repeatedly performed until the processing range R _d becomes _{equal to} or greater than the processing range R _f .

According to Configuration 3, because it determines the number of samples N_P or tolerances P _d relaxation and the processing range R _d, a small to aggregate possible range of power estimation error can be determined.

(Configuration 4)
In any one of the configurations 1 to 3, the power estimation error is 20 log (R _d −D), where D is the center point of the processing range R _d and the power estimation granularity M indicating the interval for obtaining the radio wave power. Determined by -20 log (MD).

  According to Configuration 4, the power estimation error can be accurately determined.

(Configuration 5)
Further, according to the embodiment of the present invention, the program calculates the data having the reliability P in the evaluation area based on the K factor in fading of the evaluation area for which the calculation range is determined. The number of data samples in the data aggregation range is calculated based on the density σ of the terminal device, the data acquisition period t ₀ in the terminal device, the data aggregation time T, and the area S of the data aggregation range. The first step of calculating N_agg and the determining means determine the minimum processing range as the processing range _{Rf that} can reduce the influence of fading in the range where the number of samples N_P is smaller than the number of data samples N_agg. by the error in the position of the processing range R _d power estimation granularity M and data indicating an interval for obtaining the power Determining the maximum processing range force estimation error is smaller than the allowable error P _d as a processing range R _d of the data, when the processing range R _d is greater than or equal to the processing range R _f, determined as an aggregate range processing range R _f This is a program for causing a computer to execute the second step.

According to the configuration 5, by causing the computer to execute the first and second steps, the power estimation error becomes smaller as the processing range R _f determined by the determining unit becomes larger, and the processing range determined by the determining unit The smaller _Rd is, the smaller it is. When the processing range R _d is _{equal to} or _larger than the processing range R _f , determining the processing range R _f as an aggregation range includes (A) a processing range R _d for reducing the power estimation error, and (B) a power estimation error. This is equivalent to achieving both the processing range R _f for reducing the process range R _f .
Therefore, when the processing range R _d is _{equal to} or greater than the processing range R _f , by determining the processing range R _f as an aggregation range, it is possible to determine the aggregation range while suppressing a decrease in power estimation accuracy.

(Configuration 6)
In the configuration 5, the calculating means calculates the number of data samples N_agg within the data aggregation range by σ × (T / t ₀ ) × S in the first step, and the determining means is σ in the second step. The minimum area S _MIN satisfying × (T / t ₀ ) × S> N is detected, and the processing range R _f is determined based on the detected area S _MIN .

According to the configuration 6, by causing the computer to execute the first step, the minimum area S _MIN of the data aggregation range is determined in the range where the number of data samples is larger than the number of samples N_P. The processing range _Rf can be determined after securing the number of samples N_P necessary for the calculation of data.

(Configuration 7)
In the configuration 5 or the configuration 6, in the second step, when the processing range R _d is larger than the processing range R _f , the determination unit relaxes the number of samples N_P or the allowable error P _d , and the power estimation error becomes the allowable error. A determination process for determining the data processing range R _d so as to be smaller than P _d or the relaxed allowable error P _d is repeatedly executed until the processing range R _d becomes _{equal to} or greater than the processing range R _f .

According to Configuration 7, the processing range R _d is determined by relaxing the number of samples N_P or the allowable error P _d by causing the computer to execute the second step. The range can be determined.

(Configuration 8)
In any one of the configurations 5 to 7, the power estimation error is 20 log (R _d −D), where D is the center point of the processing range R _d and the power estimation granularity M indicating the interval for obtaining the radio wave power. Determined by -20 log (MD).

  According to Configuration 8, the power estimation error can be accurately determined.

(Configuration 9)
Furthermore, according to the embodiment of the present invention, the recording medium is a computer-readable recording medium in which the program according to any one of Configurations 5 to 8 is recorded.

  The aggregation range can be determined while suppressing a decrease in power estimation accuracy.

It is the schematic which shows the radio | wireless communications system in embodiment of this invention. It is the schematic of the aggregation range determination apparatus shown in FIG. It is a conceptual diagram which shows the fluctuation | variation of the reception power by time. It is a figure which shows the relationship between the classification of an error, and the required reliability. It is a figure which shows the relationship between the magnitude | size of a sample, and an error range. It is a figure which shows the relationship between an allowable error range and the size of a sample. It is a figure which shows the sample in the case of determining whether receiving power is correct data. It is a flowchart for demonstrating operation | movement of the aggregation range determination apparatus. It is a flowchart for demonstrating the detailed operation | movement of step S1 of FIG. It is a figure which shows the simulation result of the relationship between data amount and an aggregation range. It is a figure which shows the simulation result of the relationship between an electric power estimation error and an aggregation range.

  Embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and description thereof will not be repeated.

  FIG. 1 is a schematic diagram showing a radio communication system according to an embodiment of the present invention. Referring to FIG. 1, a wireless communication system 10 according to an embodiment of the present invention includes an aggregation range determining device 1, a plurality of terminal devices 2, and a base station 3.

  The aggregation range determination device 1 is connected to the base station 3 by a wired cable 4. The aggregation range determining apparatus 1 receives a plurality of pieces of monitor information in the plurality of terminal apparatuses 2 from the base station 3 via the wired cable 4 and records the received pieces of monitor information. Here, each monitor information includes position information indicating the position of the terminal device 2, received power of the radio wave transmitted from the wave source S in the terminal device 2, time information indicating the time when the received power is detected, and the wave source S. Contains frequency information indicating the frequency of the transmitted radio wave.

  The aggregation range determination apparatus 1 also receives a plurality of monitor information transmitted from the base station (not shown in FIG. 1) to the base station 3 from the base station 3 via the wired cable 4, and the received plurality of monitors. Record information. That is, the aggregation range determination apparatus 1 receives and records monitor information of the terminal device 2 existing in the municipality area or prefecture area (target area REG for determining the aggregation range) from the base station 3.

  Then, the aggregation range determination apparatus 1 determines the aggregation range of the monitor information by a method to be described later based on the plurality of recorded monitor information, and sets the aggregation range of the determined monitor information via the base station 3. To the terminal device 2.

  As described above, the aggregation range determination apparatus 1 determines the aggregation range of the monitor information in the very wide target area REG.

The plurality of terminal devices 2 and the base station 3 are arranged in a wireless communication space. The plurality of terminal devices 2 are arranged around the wave source S. Each of the plurality of terminal devices 2 includes a plurality of frequencies included in any of a frequency band of 3 GHz or less, a frequency band of 3 GHz to 6 GHz, a frequency band of 6 GHz to 30 GHz, and a frequency band higher than 30 GHz. The terminal device 2 performs wireless communication with another terminal device 2 using the shared frequency _fcom shared by the wireless communication.

Each of the plurality of terminal devices 2 includes a mobile terminal or a stationary terminal. Then, each of the plurality of terminal devices 2 detects its own position by, for example, GPS (Global Positioning System). Each of the plurality of terminal devices 2 receives a radio wave having a shared frequency f _com from the wave source S and detects received power RSSI _i (i = 1, 2, 3,...) When the radio wave is received. To do. Furthermore, each of the plurality of terminal devices 2 has a built-in timer, and detects the time when the received power RSSI _i is detected.

Each of the plurality of terminal devices 2 detects its own identification information ID _i , position information (x _i , y _i ) indicating its own position, received power RSSI _i , and received power RSSI _i . monitoring information including the time information _{t i} indicating the time, and a shared frequency _{f com MNT_i = [ID i:} t i: (x i, y i), RSSI i, f com_i] to generate. In addition, each of the plurality of terminal devices 2 receives monitor information MNT_j = [ID _j : t _j : (x _j , y _j ), RSSI _j , f _{com_j} ] (j = 1, 2, 3, 3) from another terminal device. ...) is received. Further, each of the plurality of terminal devices 2 receives the aggregation range of the monitor information from the aggregation range determination device 1.

Then, each of the plurality of terminal devices 2 receives the monitor information MNT_i = [ID _i : t _i : (x _i , y _i ) generated by itself and other terminal devices existing within the aggregate range of the monitor information. The monitor information MNT_j = [ID _j : t _j : (x _j , y _j ), RSSI _j , f _{com_j} ] is aggregated, and the aggregated monitor information MNT is transmitted to the base station 3 by wireless communication. In this case, the terminal device 2 may directly transmit the monitor information MNT to the base station 3, or may transmit the monitor information MNT to the base station 3 by multihop.

Each of the plurality of terminal devices 2, except when performing wireless communication with other terminal devices 2, position information (x _i , y _i ), received power RSSI _i , time information t _i, and shared frequency f _{com_i} , Monitor information MNT_i = [ID _i : t _i : (x _i , y _i ), RSSI _i , f _{com_i} ] is generated, and the generated monitor information MNT_i = [ID _i : t _i : (x _i , Y _i ), RSSI _i , f _{com — i} ], and monitor information MNT_j received from other terminal devices existing in the aggregated range of monitor information = [ID _j : t _j : (x _j , y _j ), RSSI _j performs an operation of transmitting by aggregating fcom_ _j] and to the base station 3 periodically (e.g., every minute).

  The base station 3 receives monitor information MNT (monitor information that is not aggregated) from the plurality of terminal devices 2, and aggregates the received plurality of monitor information MNT (monitor information that is not aggregated) via the wired cable 4. It transmits to the range determination apparatus 1. In addition, the base station 3 transmits a plurality of monitor information MNT (monitor information that is not aggregated) received from a base station (not shown) to the aggregation range determination device 1 via the wired cable 4.

  The wave source S includes, for example, a radar, a radio relay transmission device (FPU: Field Pickup Unit) for television broadcasting, a relay station that relays radio waves to a remote island, a terminal device, and the like.

  FIG. 2 is a schematic diagram of the aggregation range determining apparatus 1 shown in FIG. Referring to FIG. 2, aggregation range determination apparatus 1 includes a reception unit 11, a storage unit 12, an extraction unit 13, an estimation unit 14, a processing unit 15, a determination unit 16, and a transmission unit 17. .

  The receiving unit 11 receives a plurality of monitor information MNT_i via the wired cable 4 and stores the received plurality of monitor information MNT_i in the storage unit 12.

  The storage unit 12 receives the plurality of monitor information MNNT_i from the reception unit 11 and stores the received plurality of monitor information MNT_i.

  For example, the extraction unit 13 receives the length R [m] of one side of the aggregation range having a square shape from the outside. The length R of one side is determined by the system designer of the wireless communication system 10 and is input to the extraction unit 13 by the system designer. Note that the extraction unit 13 may hold the length R of one side in advance.

The extraction unit 13 refers to the plurality of pieces of position information (x _i , y _i ) of the plurality of monitor information MNT_i stored in the storage unit 12, and is within a square aggregation range whose one side is R [m]. K (k is an integer satisfying 1 ≦ k ≦ i) pieces of monitor information MNT_1 to MNT_k are read from the storage unit 12 and the read k pieces of monitor information MNT_1 to MNT_k are estimated unit 14 and processing unit 15. Output to.

The estimation means 14 holds a fluctuation characteristic in which the fluctuation of the received power RSSI _i with time is associated with error factors such as noise and fading. Estimating means 14 receives the k pieces of monitor information MNT_1~MNT_k from the extraction unit 13, the error received signal RSSI ₁ ~RSSI _k of k contained in the received k pieces of monitor information MNT_1~MNT_k varies with time The factor is estimated by the method described later. Then, the estimation unit 14 outputs the estimated error factor to the processing unit 15.

  The processing means 15 receives k pieces of monitor information MNT_1 to MNT_k from the extraction means 13 and receives error factors from the estimation means 14. Further, the processing means 15 receives the data aggregation time T [s], the length R of one side, the reliability P, and the K factor K that is the fading strength from the outside. The data aggregation time T [s] depends on the time granularity (time interval for estimating power) for estimating power and is, for example, 60 seconds.

Processing means 15, among the k monitor information MNT_1～MNT_k, m associated with the same identification information ID _i (m is 1 ≦ m <integer satisfying the k) pieces of time information _t 1 ~t _m Based on the detected m pieces of time information t _{1 to} t _m , a data acquisition cycle t ₀ [s] (time interval for detecting received power RSSI _{i and the} like) in the terminal device 2 having the identification information ID _i Is calculated. More specifically, the processing means 15 calculates t ₂ −t ₁ , t ₃ −t ₂ ,..., T _m−1 −t _m−2 , t _m −t _m−1 and calculates the calculation. The average value t _{ave —} i of t ₂ −t ₁ , t ₃ −t ₂ ,..., T _m−1 −t _m−2 , t _m −t _m−1 is calculated. Processing means 15, the average value _{t Ave_i} performed for all the identification information ID _i of the process of calculating the identification information ID _i mean _t average data obtained by calculating the _{Ave_i} period t with the same number as the number of Calculate ₀ .

The processing unit 15 counts the number of identification information ID _i based on the k pieces of monitor information MNT_1 to MNT_k, and divides the counted number of identification information ID _i by the area (= R ² ) of the aggregation range. Thus, the density σ [pieces / m ² ] of the terminal devices 2 in the aggregation range is calculated.

  Then, the processing means 15 calculates the number of data samples N_agg within the data aggregation range by the following formula.

  The processing means 15 uses the K factor K and the error factor in the evaluation area for which the aggregation range is to be determined, and uses the number of samples N_P required to calculate the reliability P data in the evaluation area by a method described later. Ask for.

  Then, the processing unit 15 outputs the data sample number N_agg and the sample number N_P to the determination unit 16.

Determination means 16 receives a number of data samples N_agg and sample number N_P from the processing unit 15 receives power of the radio power estimation granularity indicating estimated every many meters M [m] and the tolerances P _d from the outside.

Then, the determination unit 16 detects the minimum processing range R _f that satisfies the following equation based on the data sample number N_agg and the sample number N_P.

The processing range R _f in Equation (2) is a processing range in which the influence of fading can be reduced.

Further, determining unit 16, based on the power estimation error due to the error in the position to detect the processing range R _d. More specifically, assuming that the center point of the processing range R _d and the power estimation granularity M is D, the position error from the center point D of the processing range R _d is (R _d −D), and the power estimation granularity is The position error from the center point D of M is (MD). The power estimation error with respect to this position error is, for example, 20 log (R _d −D) and 20 log (M−D) when free space propagation loss of radio waves is used. The difference between 20 log (R _d −D) and 20 log (M−D) (20 log (R _d −D) −20 log (M−D)) is an error due to the difference between the processing range R _d and the power estimation granularity M. become. Therefore, the determination unit 16 detects the maximum processing range R _d that satisfies the following expression.

P _d in Equation (3) is an allowable error. P _d depends on the interference power margin to be set, and is, for example, 5 dB.

That is, the determination unit 16 detects the maximum processing range R _d such that the difference (20 log (R _d −D) −20 log (M−D)) is smaller than the allowable error P _d .

Then, the determination unit 16 determines the final aggregation range R _agg based on the processing range R _f calculated from the fading and the processing range R _d calculated from the position error as follows.

When R _d ≧ R _{f The} determination unit 16 determines R _f as the aggregation range R _agg .

When R _d <R _f The determination unit 16 relaxes the condition of the number of samples N_P or the allowable error P _d and determines the aggregation range R _agg again. When the condition of the sample number N_P is relaxed, the determination unit 16 outputs a signal Sreq requesting to obtain the sample number N_P by relaxing the condition to the processing unit 15, and the processing unit 15 responds to the signal Sreq. Then, the conditions are relaxed, the number of samples N_P is obtained by a method described later, and the obtained number of samples N_P is output to the determining unit 16. Then, the determination unit 16 substitutes the number of samples N_P newly received from the processing unit 15 into the equation (2) to detect the minimum processing range _Rf . Further, when the allowable error P _d is relaxed, the determination unit 16 detects the maximum processing range R _d by substituting the increased allowable error P _d into Expression (3).

When the determination unit 16 determines the aggregation range R _agg by the above-described method, the determination unit 16 outputs the determined aggregation range R _agg to the transmission unit 17.

The transmission unit 17 receives the aggregation range R _agg from the determination unit 16 and transmits the received aggregation range R _agg to the plurality of terminal devices 2 via the wired cable 4 and the base station 3.

An error factor estimation method in the estimation unit 14 will be described. FIG. 3 is a conceptual diagram showing fluctuations in received power RSSI _{i with} time. Referring to FIG. 3, in a propagation environment that is affected by fading, received power RSSI _i varies with time as shown by curve k1.

When the propagation environment is a propagation environment affected by noise, the received power RSSI _i varies so as to differ from the curve k1 depending on time.

The estimation means 14 holds a fluctuation characteristic in which the fluctuation of the received power RSSI _i with time is associated with error factors such as noise and fading. Then, the estimation unit 14 determines to which variation characteristic the variation with time of the received power RSSI _i received from the extraction unit 13 matches or approximates, and detects an error factor corresponding to the variation characteristic to match or approximate. Thus, the error factor that the received power RSSI _i varies with time is estimated.

  The distribution of errors such as noise and fading is one of a normal distribution, a Rice distribution, and a Rayleigh distribution. The normal distribution is an error distribution when the error factor is noise, and the Rice distribution and the Rayleigh distribution are error distributions when the error factor is fading. The Rayleigh distribution is an error distribution when the scattering is intense.

Therefore, in the embodiment of the present invention, the propagation environment of radio waves is estimated, and according to the estimated propagation environment, the distribution of error factors is determined as one of a normal distribution, a Rice distribution, and a Rayleigh distribution, The received power RSSI _{i —} CFD that satisfies the reliability P corresponding to the determined distribution of error factors is detected.

Estimating means 14, the terminal information from the fixed terminal or on the basis of the terminal information of the moving speed from the slowest mobile terminal, detection of a variation with time of the received power RSSI _i, due to the time of the received power RSSI _i that the detected Based on the variation, a propagation environment such as a fading propagation environment or a noisy propagation environment is estimated.

  Then, the estimation unit 14 determines the distribution of the error factor to be any one of a normal distribution, a Rice distribution, and a Rayleigh distribution according to the estimated propagation environment, and sends the determined error factor distribution to the processing unit 15. Output.

  A method for obtaining the number of samples N_P will be described. FIG. 4 is a diagram illustrating the relationship between the type of error and the required reliability. Referring to FIG. 4, when the type of error is a normal distribution, the required reliability P is, for example, 0.95, and the distribution point α is a normal distribution point with a reliability of 0.95. . When the type of error is Rice distribution, the required reliability P is, for example, 0.90, and the distribution point β is a Rice distribution point having a reliability of 0.90. When the type of error is Rayleigh distribution, the required reliability P is, for example, 0.80, and the distribution point γ is a Rayleigh distribution point with a reliability of 0.80.

  The processing means 15 holds a correspondence table TBL indicating the correspondence between the error type and the required reliability P shown in FIG. When the processing unit 15 receives the distribution of error factors from the estimation unit 14, the processing unit 15 refers to the correspondence table TBL and detects the reliability P corresponding to the received distribution of error factors.

Thereafter, the processing means 15 on the basis of the k pieces of monitor information _MNT 1 _{~MNT k,} detects the reception power RSSI _i _CFD satisfying reliability P to request.

More specifically, the processing unit 15, by the following method, for detecting a received power RSSI _i _CFD. The processing unit 15 extracts a plurality of received powers RSSI _{1 to} RSSI _n having different times from the received power received from one terminal device 2. For example, the processing means 15 extracts _ten received powers RSSI _{1 to} RSSI 10 having different times. Then, the processing means 15 calculates Z by the following equation using 10 received powers having different times.

  In Expression (4), n is the size of the number of samples, e is an allowable error range, and Z is a distribution point having the reliability P. Q is the ratio of received power used to determine the aggregation range in the population. For example, when estimating the aggregation range using 10 received powers out of 100 received powers, Q = 0.1. N is the population.

  FIG. 5 is a diagram showing the relationship between the sample size n and the allowable error range e. FIG. 5 shows the relationship between the sample size n and the allowable error range e when the average received power is −100 dBm and the reliability P is 0.95.

  Referring to FIG. 5, the sample size n is, for example, any one of 10, 20, 50, and 100. The allowable error range e is set to, for example, 10% when the sample size n is 10, and is set to 7%, for example, when the sample size n is 20, and the sample size n is If it is 50, for example, it is set to 5%, and if the sample size n is 100, it is set to 3%, for example. Thus, the allowable error range e is set so as to decrease as the sample size n increases.

  When the sample size n is 10, there is a true value in a range of −110 to −90 dBm with a probability of 95% (reliability P = 0.95). When the sample size n is 100, there is a true value in the range of −103 to −97 dBm with a probability of 95% (reliability P = 0.95).

  Since the allowable error range e is set so as to decrease as the sample size n increases, the allowable error range e decreases as the sample size n increases, and the accuracy improves.

  The distribution point of the reliability P and the allowable error range e are set according to the required accuracy. If the sample size n does not increase, the restriction on the reliability P or the allowable error range e is reduced. If the sample size n does not increase, if the reliability P is set high or the allowable error range e is set narrow, there is no received power that satisfies the reliability P or the allowable error range e, and the aggregation range cannot be determined. It is.

  FIG. 6 is a diagram illustrating the relationship between the allowable error range and the sample size. In FIG. 6, the vertical axis represents the allowable error range e, and the horizontal axis represents the sample size n.

Referring to FIG. 6, the relationship between the allowable error range e and the sample size n is represented by a curve k2. As a result, the allowable error range e decreases exponentially as the sample size n increases. The curve k2 is represented by an equation of e = 32.118n− ^0.495 .

The processing means 15 holds the relationship between the allowable error range e represented by the curve k2 and the sample size n (e = 32.118n− ^0.495 ), and the received power used to determine the number of samples N_P. When counting the n (sample size) the number of RSSI _i, by substituting the number n which is the count in the equation of ^{e = 32.118n -0.495,} detects the tolerance e corresponding to the number n.

N is the total number of received power RSSI _i , n is 10 received powers with different times (the number of received powers of some of the total received power RSSI _i ), and e is Since it is determined by the relationship between the allowable error range e shown and the sample size n (e = 32.118n− ^0.495 ), it is known and Q is also known. 4), Z can be calculated.

Then, the processing means 15 determines whether or not the calculated Z satisfies the reliability P. More specifically, when Z satisfies the reliability P, the processing unit 15 determines the received power RSSI _{1 to} RSSI _n as correct data, and when Z does not satisfy the reliability P, the received power RSSI ₁ ~ RSSI _n is determined to be incorrect data.

  Here, whether or not Z satisfies the reliability P is determined by whether or not Z falls within a range in which the deviation is ± 0.05 in the normal distribution when the error distribution follows the normal distribution. When Z falls within a range where the deviation is ± 0.05 in the normal distribution, it is determined that Z satisfies the reliability P, and when Z does not fall within the range where the deviation is ± 0.05 in the normal distribution, It is determined that Z does not satisfy the reliability P.

Processing means 15, when the received power RSSI ₁ ~RSSI _n is determined to be the incorrect data, another received power RSSI _'1 ~RSSI' _n, by the method described above, received power RSSI _'1 ~RSSI' _n It is determined whether or not is correct data.

Even when the error distribution is the Rice distribution or the Rayleigh distribution, the processing means 15 determines whether or not the received power RSSI _{1 to} RSSI _n is the correct data in the same manner as when the error distribution is a normal distribution. To do.

  Further, the processing unit 15 extracts a plurality of received powers having the same time information from a plurality of received powers received from different terminal devices, and for each of the extracted received powers, the above-described method is used. It may be determined whether the received power is correct.

The processing unit 15 estimates an error factor that the received power RSSI _{1 to} RSSI _n varies with time, determines the distribution of the estimated error factor as one of a normal distribution, a Rice distribution, and a Rayleigh distribution, The received power RSSI _{i —} CFD that satisfies the reliability P corresponding to the determined distribution of error factors is detected.

FIG. 7 is a diagram illustrating a sample for determining whether or not the received power is correct data. Referring to (a) of FIG. 7, n (n is an integer satisfying 2 ≦ n <i) received powers RSSI _{1 to} RSSI _n are received with different time information at position (x ₁ , y ₁ ). It is electric power.

Referring to (b) of FIG. 7, n pieces of received power RSSI ′ _{1 to} RSSI ′ _n are received powers having different position information in time information t ₁ .

When determining whether or not the received power is correct data using the _n received powers P _{1 to} P _n , the processing unit 15 determines that the distribution of the _n received powers RSSI _{1 to} RSSI _n is a normal distribution, Rice It is judged whether it corresponds to distribution or Rayleigh distribution. When it is determined that the processing unit 15 corresponds to the normal distribution, the processing unit 15 refers to the correspondence table TBL and detects a reliability P of 0.95 corresponding to the normal distribution.

  Thereafter, the processing means 15 calculates Z using the equation (4), and determines whether or not the calculated Z satisfies the reliability P by the method described above.

Even when the distribution of the _n received powers RSSI _{1 to} RSSI _n is a Rice distribution or a Rayleigh distribution, the processing unit 15 similarly determines whether or not the calculated Z satisfies the reliability P by the method described above. To do.

When the processing unit 15 determines that Z satisfies the reliability P, that is, when it is determined that the n received powers RSSI _{1 to} RSSI _n are correct data, the processing unit 15 at the position (x ₁ , y ₁ ). detecting a received power RSSI ₁ ~RSSI _n as data for determining the aggregate range, obtaining the number n of received power RSSI ₁ ~RSSI _n as the number of samples N_P.

When determining whether or not the received power is correct data using the _n received powers RSSI ′ _{1 to} RSSI ′ _n , the processing unit 15 determines that the distribution of the _n received powers RSSI ′ _{1 to} RSSI ′ _n It is determined whether the distribution is normal distribution, Rice distribution, or Rayleigh distribution. When it is determined that the processing unit 15 corresponds to the normal distribution, the processing unit 15 refers to the correspondence table TBL and detects a reliability P of 0.95 corresponding to the normal distribution.

  Thereafter, the processing means 15 calculates Z using the equation (4), and determines whether or not the calculated Z satisfies the reliability P by the method described above.

Even when the distribution of the _n received powers RSSI ′ _{1 to} RSSI ′ _n is a Rice distribution or a Rayleigh distribution, the processing unit 15 similarly determines whether or not the calculated Z satisfies the reliability P. Judgment by.

When the processing unit 15 determines that Z satisfies the reliability P, that is, when it is determined that n pieces of received power RSSI ′ _{1 to} RSSI ′ _n are correct data, n pieces of received power RSSI ′. 'detects _n as data for determining the aggregate range, the received power RSSI' ₁ ~RSSI obtaining the number n of ₁ ～RSSI _'n as the number of samples N_P.

Therefore, the processing means 15 detects the _n received powers RSSI ′ _{1 to} RSSI ′ _n as a correct set of data.

On the other hand, when the processing unit 15 determines that the n received powers RSSI ′ _{1 to} RSSI ′ _n are not correct data, at least one of the _n received powers RSSI ′ _{1 to} RSSI ′ _n is different from another n. The received power is detected, and it is determined by the method described above whether the detected n received powers are correct data.

  Note that the processing unit 15 obtains the number of samples N_P by the method described above is based on the K factor K in fading of the evaluation area for which the aggregation range is determined, based on the data having the reliability P in the evaluation area. This corresponds to calculating the number of samples N_P necessary for calculation.

  FIG. 8 is a flowchart for explaining the operation of the aggregation range determination apparatus 1. Referring to FIG. 8, when the operation for determining the aggregation range is started, processing means 15 is necessary for calculating data of signal level P in the evaluation area from K factor K in fading of evaluation area. The number of samples N_P is calculated by the method described above (step S1).

Then, the processing means 15 calculates the data acquisition cycle t ₀ in each terminal device 2 and the density σ of the terminal device 2 by the method described above, the calculated data acquisition cycle t ₀ and density σ, and the data aggregation time T. Then, the length R of one side is substituted into the equation (1), and the number of data samples N_agg is calculated (step S2). Then, the processing means 15 outputs the calculated sample number N_P and data sample number N_agg to the determining means 16.

The determining unit 16 receives the number of samples N_P and the number of data samples N_agg from the processing unit 15. Then, the determination unit 16 detects the minimum processing range R _f satisfying the equation (2) based on the received sample number N_P and data sample number N_agg. That is, the determination unit 16 detects a processing range R _f that can reduce the influence of fading (step S3).

Thereafter, the determination unit 16 obtains the maximum processing range R _{d in} which the power estimation error due to the position error is smaller than the allowable error P _d using the equation (3) (step S4).

Then, the determination unit 16 determines whether or not the processing range R _d is _{equal to} or greater than the processing range R _f (step S5). In step S5, when the processing range _{R d} is determined not to be above processing range _{R f,} determining means 16, to relax the conditions or tolerances _{P d} number of samples N_P (step S6).

In step S6, if the relaxed condition of the number of samples N_P, the series of operations proceeds to step S1, in step S5, until processing range R _d is determined to be greater than or equal to the processing range R _f, step S1~ Step S6 is repeatedly executed.

On the other hand, in step S6, if the relaxed tolerances P _d, the series of operations proceeds to step S4, in step S5, until processing range R _d is determined to be greater than or equal to the processing range R _f, step S4 Step S6 is repeatedly executed.

Then, in step S5, the processing range _{R d} is determined to be greater than or equal to the processing range _{R f,} determining means 16 determines the processing range _{R f} as final aggregates range _{R agg} (step S7). Thereby, the operation for determining the aggregation range is completed.

FIG. 9 is a flowchart for explaining the detailed operation of step S1 of FIG. Referring to FIG. 9, when the operation of determining the aggregation range is started, extraction unit 13 extracts k pieces of monitor information MNT _{1 to} MNT _k from storage unit 12 (step S11), and the extracted k The pieces of monitor information MNT _{1 to} MNT _k are output to the estimation means 14 and the processing means 15.

The estimation unit 14 receives k pieces of monitor information MNT _{1 to} MNT _k from the extraction unit 13 and estimates the distribution of error factors by the above-described method based on the received k pieces of monitor information MNT _{1 to} MNT _k. (Step S12). Then, the estimating means 14 outputs the estimated error factor distribution to the processing means 15.

Processing means 15 receives the k pieces of monitor information _MNT 1 _{~MNT k} from the extraction unit 13 receives a distribution of error factor from estimating means 14. Then, the processing means 15 detects the reliability P corresponding to the error factor distribution by the method described above (step S13).

Further, the processing means 15 extracts received power RSSI _{1 to} RSSI _n from a plurality of received power RSSI _i included in k pieces of monitor information MNT _{1 to} MNT _k , and samples of the extracted received power RSSI _{1 to} RSSI _n . N is detected (step S14).

  Then, the processing means 15 detects an allowable error range e corresponding to the sample size n by the method described above (step S15). Then, the processing means 15 calculates Z using Expression (4) (step S16), and determines whether the calculated Z satisfies the reliability P by the method described above (step S17).

When it is determined in step S17 that Z does not satisfy the reliability P, the processing unit 15 extracts other received power RSSI _{1 to} RSSI _n (step S18). Thereafter, the series of operations returns to step S12, and steps S12 to S18 are repeatedly executed until it is determined in step S17 that Z satisfies the reliability P.

When it is determined in step S17 that Z satisfies the reliability P, the processing unit 15 determines that the received power RSSI _{1 to} RSSI _n is correct data (step S19), and the sample size n is determined as the number of samples. N_P (step S20). Then, a series of operation | movement transfers to step S2 of FIG.

  A simulation was performed on the relationship between the amount of data and the aggregation range and the relationship between the power estimation error and the aggregation range. The simulation was performed as follows. A range of 10 km × 10 km is used as an evaluation area, a wave source is installed near the center of the evaluation area, and mobile devices (moving terminal devices) are randomly arranged. The mobile moves in a random direction at a maximum speed of 6 km and detects position and power information every second. The mobile device communicates with other mobile devices that are close to each other within 50 m once every 10 seconds to aggregate the data, and transmits the aggregated data to the server every 100 seconds. The power received by the mobile device was calculated using a propagation model and a Rayleigh fading model.

  FIG. 10 is a diagram illustrating a simulation result of the relationship between the data amount and the aggregation range. In FIG. 10, the vertical axis represents the amount of data, and the horizontal axis represents the aggregation range. The amount of data on the vertical axis is the ratio of the number of data after aggregation to the number of data before aggregation. A circle indicates the relationship between the data amount and the aggregation range when the number of nodes (number of terminal devices 2) is 100, and a triangle indicates when the number of nodes (number of terminal devices 2) is 200. The rhombus indicates the relationship between the data amount and the aggregation range when the number of nodes (the number of terminal devices 2) is 500.

  Referring to FIG. 10, the amount of data decreases as the aggregation range increases in the number of nodes. However, when the aggregation range is 200 [m] or more, the data amount does not fluctuate greatly and the aggregation effect slows down.

  FIG. 11 is a diagram illustrating a simulation result of the relationship between the power estimation error and the aggregation range. In FIG. 11, the vertical axis represents the power estimation error, and the horizontal axis represents the aggregation range. The circle indicates the relationship between the power estimation error and the aggregation range when the number of nodes (number of terminal apparatuses 2) is 100, and the triangle indicates when the number of nodes (number of terminal apparatuses 2) is 200. The relationship between the power estimation error and the aggregation range is shown, and the rhombus indicates the relationship between the power estimation error and the aggregation range when the number of nodes (the number of terminal devices 2) is 500.

  Referring to FIG. 11, the power estimation error increases as the aggregation range increases. However, the power estimation error does not increase monotonously with respect to the aggregation range, and becomes smaller as the aggregation range is larger up to the aggregation range 200 [m]. This is considered to be because the influence of power fluctuation due to fading or the like can be reduced by data aggregation.

  Therefore, from the simulation results shown in FIGS. 10 and 11, it can be seen that in the range up to 200 [m], the larger the aggregation range, the smaller the data amount and the lower the power estimation error.

In the flowchart shown in FIG. 8, the power estimation error tolerances P _d largest processing range R _d which is smaller than is required (see step S4). As shown in FIGS. 10 and 11, the amount of data is reduced by setting the maximum processing range R _d1 (or R _d2 ) as the aggregation range in a range where the power estimation error is smaller than the allowable error P _d. This corresponds to the simulation result indicating that the aggregation effect is reduced.

Further, in the flowchart shown in FIG. 8, when R _d ≧ R _f , the processing range R _f is determined as the final aggregation range R _agg (see step S5 and step S7). This is due to the following reason. According to the simulation result shown in FIG. 11, in the range where the aggregation range exceeds 200 [m], the power estimation error becomes smaller as the aggregation range (processing range R _d ) becomes smaller. On the other hand, the processing range R _f is a processing range in which the influence of fading can be reduced, and is the minimum processing range that satisfies Expression (2). As a result of reducing the influence of fading by data aggregation, the power estimation error becomes smaller. Therefore, the larger the processing range _Rf , the smaller the power estimation error.

Therefore,
(A) The power estimation error decreases as the processing range R _d decreases.
(B) The power estimation error decreases as the processing range _Rf increases.
In order to make the two conditions (A) and (B) compatible, when R _d ≧ R _f , the processing range R _f is determined as the final aggregation range R _agg .

Further, in step S5 of the flowchart shown in FIG. 8, if R _d ≧ R _f is not satisfied, the condition of the sample number N_P or the allowable error P _d is relaxed, and step S1 to step S6 or step S4 to step S6 are executed again. The reason is as follows. Relaxing the condition of the sample number N_P reduces the sample number N_P. As a result, the processing range R _f becomes smaller, and the relationship R _d ≧ R _f is easily established. Moreover, relaxing the tolerances P _d will be increased tolerances P _d. As a result, as apparent from FIG. 11, it can increase the processing range R _d, because the relationship R _d ≧ R _f is easily satisfied.

Therefore, by determining the aggregation range R _agg according to the flowchart shown in FIG. 8 (including the flowchart shown in FIG. 9), it is possible to determine the aggregation range while suppressing a decrease in power estimation accuracy.

When determining the aggregation range R _agg , the aggregation range determination device 1 transmits the determined aggregation range R _agg to the plurality of terminal devices 2 via the wired cable 4 and the base station 3. Each of the plurality of terminal devices 2 receives the aggregation range R _agg from the aggregation range determination device 1. Each of the plurality of terminal devices 2 communicates with other terminal devices within the aggregation range R _agg once every fixed period to aggregate data (monitor information MNT), and the aggregated data ( Monitor information MNT) is transmitted to the server. In this case, the data aggregation method is, for example, calculating an average value for each element such as the received power RSSI _i included in the plurality of monitor information MNT, but the data aggregation method is any method. May be.

Server receives the aggregated data (monitor information MNT), position information included in the aggregated data (monitor information _{MNT) (x i, y i} ) on the basis of and received power RSSI _i, received power RSSI _i The wave source position is estimated from the average of the positions weighted by. Then, the server sets a circle including all points from the wave source that are equal to or higher than the power value POW (points determined by the position information (x _i , y _i ) and the received power RSSI _i ) as an isoelectric line of the power value POW. In addition, the server calculates a power value at a position away from the equal power line of the power value POW by a desired distance using a radio wave free propagation model, and estimates a power value for each desired location. In this case, since the server estimates the power value for each equal power line and a desired location based on the data (monitor information MNT) aggregated within the aggregation range R _agg where the power estimation error is small, the estimated iso power line And the error of the electric power value for every desired place can be made small.

  In the embodiment of the present invention, the operation of the aggregation range determining apparatus 1 may be executed by software. In this case, the aggregation range determination apparatus 1 includes a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory).

The ROM stores a program Prog_A composed of a pro chart shown in FIG. 8 (including the flowchart shown in FIG. 9). Then, the CPU reads the program Prog_A from the ROM and executes the read program Prog_A to determine the aggregation range R _agg . The RAM temporarily stores the density σ, the data acquisition cycle t ₀ , the sample number N_P, and the data sample number N_agg of the terminal device 2.

The program Prog_A may be recorded and distributed on a recording medium such as a CD or DVD. In this case, the CPU reads and executes the program Prog_A from the loaded recording medium, and determines the aggregation range R _agg . Therefore, a recording medium such as a CD or a DVD in which the program Prog_A is recorded is a recording medium that can be read by a computer (CPU).
In the above description, the aggregation range has been described as having a square shape. However, in the embodiment of the present invention, the aggregation range is not limited to this, and the aggregation range includes polygons (triangles, quadrangles, pentagons, etc.), circles, and ellipses. It may be a shape or the like, and generally may be an arbitrary shape.

  When the aggregation range is circular, a radius or a diameter is used instead of the above-described length R of one side, and when the aggregation range is an ellipse, a long diameter or a short diameter is used instead of the above-described length R of one side. Is used, and the aggregation range is a polygon, the distance from the center of the polygon to one vertex is used instead of the length R of one side described above.

Further, since R ² in the formula (1) is an area of the aggregation range, the area S of the aggregation range may be used instead of R ² in the formula (1). The minimum area S _MIN satisfying the following expression is obtained using the equation, the processing range R _f ′ indicating the size of the aggregate range is obtained based on the obtained minimum area S _MIN , and the processing is performed instead of the processing range R _f The range R _f ′ may be used.

According to the embodiment described above, the aggregation range determination apparatus according to the embodiment of the present invention has the reliability P in the evaluation area based on the K factor in the fading of the evaluation area for which the aggregation range is determined. While calculating the number of samples N_P necessary for calculating the data, and based on the density σ of the terminal device, the data acquisition period t ₀ in the terminal device, the data aggregation time T, and the area S of the data aggregation range, The calculation means for calculating the number of data samples N_agg and the minimum processing range in the range where the number of samples N_P is smaller than the number of data samples N_agg are determined as the processing range _{Rf that} can reduce the influence of fading, and power estimation caused by errors in the position of the processing range R _d power estimation granularity M and data indicating an interval for obtaining Determining the maximum processing range error is smaller than the allowable error P _d as a processing range R _d of the data, when the processing range R _d is greater than or equal to the processing range R _f, determining for determining a processing range R _f as an aggregate range And means.

  This is because if the above-described calculation means and determination means are provided, the aggregation range can be determined while suppressing a decrease in power estimation accuracy.

Further, the program according to the embodiment of the present invention is necessary for the calculation means to calculate data having the reliability P in the evaluation area based on the K factor in fading of the evaluation area for which the aggregation range is determined. The number of samples N_P is calculated, and the number N_agg of data samples in the data aggregation range is calculated based on the density σ of the terminal device, the data acquisition period t ₀ in the terminal device, the data aggregation time T, and the area S of the data aggregation range. And determining means determines a minimum processing range as a processing range R _{f that} can reduce the influence of fading in a range where the number of samples N_P is smaller than the number of data samples N_agg, and power due to an error between the positions of the processing range R _d power estimation granularity M and data indicating an interval for obtaining Determining the maximum processing range constant error becomes smaller than the allowable error P _d as a processing range R _d of the data, when the processing range R _d is greater than or equal to the processing range R _f, determines a processing range R _f as an aggregate range What is necessary is just a program for making a computer perform a 2nd step.

  This is because if the computer executes the first and second steps, the aggregation range can be determined while suppressing a decrease in power estimation accuracy.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is shown not by the above description of the embodiments but by the scope of claims for patent, and is intended to include meanings equivalent to the scope of claims for patent and all modifications within the scope.

  The present invention is applied to an aggregation range determination apparatus, a program for causing a computer to execute, and a computer-readable recording medium on which the program is recorded.

  DESCRIPTION OF SYMBOLS 1 Aggregation range determination apparatus, 2 Terminal device, 3 Base station, 4 Wired cable, 10 Wireless communication system, 11 Reception means, 12 Storage means, 13 Extraction means, 14 Calculation means, 15 Determination means, 16 Transmission means

Claims (9)

Based on the K factor in the fading of the evaluation area for which the aggregation range is determined, the number N_P of samples necessary for calculating the data having the reliability P in the evaluation area is calculated, and the density σ of the terminal device, the terminal An arithmetic means for calculating the number of data samples N_agg within the data aggregation range based on the data acquisition cycle t ₀ , the data aggregation time T, and the area S of the data aggregation range in the apparatus;
In the range where the number of samples N_P is smaller than the number of data samples N_agg, a minimum processing range is determined as a processing range R _{f that} can reduce the influence of fading, and a power estimation granularity M indicating an interval for obtaining radio wave power; the error due to power estimation error between the positions of the processing range R _d of data is determined as the allowable error P processing range data maximum processing range to be smaller than _d R _d, wherein the processing range R _d is the processing range R _An aggregation range determination apparatus comprising: a determination unit that determines the processing range R _f as an aggregation range when the number is greater than or _equal to _f . The computing means computes the number of data samples N_agg within the data aggregation range by σ × (T / t ₀ ) × S,
2. The determination unit according to claim 1, wherein the determination unit detects a minimum area S _MIN that satisfies σ × (T / t ₀ ) × S> N, and determines a processing range R _f based on the detected area S _MIN. Aggregation range determination device. It said determining means, when the processing range R _d is greater than the processing range R _f, mitigate the sample number N_P or the tolerances P _d, the power estimation error is the tolerance P _d or the relaxed tolerance The determination process for determining the processing range R _{d of the} data so as to be smaller than the error P _d is repeatedly performed until the processing range R _d becomes _{equal to} or greater than the processing range R _f. Aggregation range determination device. The power estimation error is expressed by 20 log (R _d −D) −20 log (M−D), where D is a central point between the processing range R _d and a power estimation granularity M indicating an interval for obtaining radio wave power. The aggregation range determination apparatus according to claim 1, wherein the aggregation range determination apparatus is determined. The calculation means calculates the number of samples N_P necessary for calculating data having the reliability P in the evaluation area based on the K factor in the fading of the evaluation area for which the aggregation range is to be determined. A first step of calculating the number of data samples N_agg in the data aggregation range based on the density σ, the data acquisition cycle t ₀ in the terminal device, the data aggregation time T, and the area S of the data aggregation range;
The determining means determines the minimum processing range as the processing range R _{f in} which the influence of fading can be reduced in the range where the number of samples N_P is smaller than the number of data samples N_agg, and power indicating an interval for obtaining the power of radio waves determining the maximum processing range power estimation error due to the error in position between the estimated particle size M and the processing range R _d of the data is smaller than the allowable error P _d as a processing range R _d of data, the processing range R _d is A program for causing a computer to execute the second step of determining the processing range _Rf as an aggregation range when the processing range is _{equal to} or greater than the processing range _Rf . In the first step, the calculating means calculates the number of data samples N_agg within the data aggregation range by σ × (T / t ₀ ) × S,
In the second step, the determining means detects a minimum area S _MIN that satisfies σ × (T / t ₀ ) × S> N, and determines a processing range R _f based on the detected area S _MIN. The program for making the computer of Claim 5 perform. In the second step, when the processing range R _d is larger than the processing range R _f , the determination unit relaxes the number of samples N_P or the allowable error P _d , and the power estimation error becomes the allowable error. The determination process for determining the processing range R _{d of the} data so as to be smaller than P _d or the relaxed allowable error P _d is repeatedly performed until the processing range R _d becomes _{equal to} or greater than the processing range R _f. A program for causing a computer according to claim 5 or 6 to be executed. The power estimation error is expressed by 20 log (R _d −D) −20 log (M−D), where D is a central point between the processing range R _d and a power estimation granularity M indicating an interval for obtaining radio wave power. The program for making the computer of any one of Claims 5-7 determined determine.   The computer-readable recording medium which recorded the program of any one of Claims 5-8.

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