Traffic analysis system and method

Abstract

This traffic analysis system 200 comprises: mirroring devices 40 that acquire data pertaining to communication from mobile base station devices 20, which communicate with terminals 10, to mobile networks 30; traffic rate acquisition devices 50 that acquire the data from the mirroring devices 40 and calculate communication amounts per unit time from the data; and a wireless quality analysis device 60 that acquires the communication amounts per unit time from the traffic rate acquisition devices 50 and analyzes the wireless quality of the mobile base station devices 20 on the basis of the communication amounts per unit time.

Description

Traffic analysis system and method

[0001] The present disclosure relates to a method for analyzing wireless quality based on traffic data.

[0002] In recent years, with the advancement of mobile technology and the rise of IoT, a configuration in which various operators install and operate local base stations that use carrier bands is becoming increasingly widespread.

[0003] There are two issues to be addressed when installing local base stations. One is that radio waves from a local base station may travel too far, causing interference between the wireless areas of multiple base stations. The other is that changes in the external environment may cause changes in the wireless area. These issues can result in a deterioration of wireless quality. For this reason, it is desirable to properly understand the wireless conditions at the local base station and analyze the wireless quality.

[0004] To analyze the wireless quality of a base station, Non-Patent Document 1 discloses a technology for detecting wireless interference by measuring power and communication quality in cooperation with terminals connected to the base station itself and surrounding base stations. Non-Patent Document 2 also discloses a technology for measuring radio wave propagation characteristics over the long term in a greenhouse and measuring the shape of the wireless area depending on the presence or absence of crops.

[0005] "Technology Developed to Autonomously Reduce Radio Wave Interference for LTE Home Femto Base Stations," Fujitsu Laboratories Ltd., September 10, 2013, Internet, <https: / / pr.fujitsu.com / jp / news / 2013 / 09 / 10.html>; "Evaluation of 920 MHz Band Radio Wave Propagation Characteristics for Wireless Networks in Farm Fields," Tomoya Moribe, Kei Okada, Kentaro Kobayashi, Masaaki Katayama, J-STAGE, Agricultural Information Research 26(1), 2017, Internet, <https: / / www.jstage.jst.go.jp / article / air / 26 / 1 / 26_1 / _pdf>

[0006] However, when analyzing wireless quality using the technology disclosed in Non-Patent Document 1, cooperation between the base station and the terminal is required, which requires additional functions to be added to the base station. Furthermore, with the technology disclosed in Non-Patent Document 2, when the wireless area becomes relatively large, continuing to measure radio wave propagation characteristics requires power supply to the measuring device and manpower, which places a heavy burden on the operational side. As such, neither technology is economical, and there is a need for a system that can appropriately grasp the wireless situation at a local base station and analyze wireless quality with a more economical configuration.

[0007] In order to solve the above problems, the present disclosure aims to provide a traffic analysis system that is economically configured and capable of properly grasping the wireless conditions at local base stations and analyzing wireless quality.

[0008] To achieve the above object, the traffic analysis system of the present disclosure employs a technique for analyzing wireless quality based on data relating to communications between a base station and a network above the base station.

[0009] Specifically, the traffic analysis system of the present disclosure includes a data acquisition unit that acquires data regarding communications between a base station that communicates with a terminal and a network higher than the base station; a calculation unit that acquires the data from the data acquisition unit and calculates the communication volume per unit time from the data; and an analysis unit that acquires the communication volume per unit time from the calculation unit and analyzes the wireless quality of the base station based on the communication volume per unit time.

[0010] In addition, the traffic analysis method of the present disclosure acquires data regarding communication between a base station that communicates with a terminal and a network above the base station, calculates the communication volume per unit time from the data, and analyzes the wireless quality of the base station based on the communication volume per unit time.

[0011] According to the above configuration, it is possible to estimate the occurrence of a change in the wireless situation and analyze the wireless quality without adding functions to the base station or terminals or requiring manpower.

[0012] The analysis unit may also calculate the acceleration of change in the communication volume per unit time, calculate the correlation of the acceleration of change between base stations, and estimate that radio interference has occurred between base stations that have a negative correlation.

[0013] According to the above configuration, it is possible to estimate the occurrence of radio interference between base stations based on a simple algorithm and to appropriately analyze radio quality.

[0014] The analysis unit may also calculate the change in communication volume per unit time for each of a plurality of base stations, and estimate that interference has occurred in the wireless areas of the plurality of base stations based on the correlation of the change in communication volume per unit time between the plurality of base stations.

[0015] According to the above configuration, it is possible to estimate the occurrence of a change in the radio environment based on a simple algorithm and to appropriately analyze the radio quality.

[0016] The above disclosures can be combined as much as possible.

[0017] According to the traffic analysis system of the present disclosure, it is possible to appropriately grasp the wireless conditions at local base stations and analyze the wireless quality with an economical configuration.

[0018] Fig. 1 is a diagram for explaining the basic configuration of a wireless communication system. Fig. 2 is a diagram for explaining that wireless quality is affected by interference between base stations and changes in the environment. Fig. 3 is a diagram for explaining that a data transfer rate is reduced due to the occurrence of simultaneous traffic. Fig. 4 is a diagram for explaining rule 1. Fig. 5 is a diagram for explaining rule 2. Fig. 6 is a diagram for explaining rule 3. Fig. 7 is a flowchart for explaining the processing of a traffic analysis system.

[0019] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the present disclosure is not limited to the embodiments shown below. These implementation examples are merely illustrative, and the present disclosure can be implemented in various forms with various modifications and improvements based on the knowledge of those skilled in the art. Note that components with the same reference numerals in this specification and drawings indicate the same components.

[0020] A wireless communication system 100 according to an embodiment of the present disclosure will be described with reference to Fig. 1 to Fig. 6. First, a basic configuration of the wireless communication system 100 will be described with reference to Fig. 1.

[0021] 1, wireless communication system 100 mainly comprises traffic analysis system 200, the Internet consisting of multiple mobile networks 30A, 30B, and 30C, and multiple mobile base station devices 20A, 20B, and 20C. In the following description, unless otherwise specified, the multiple mobile networks 30A, 30B, and 30C will be referred to as mobile network 30. Furthermore, unless otherwise specified, the multiple mobile base station devices 20A, 20B, and 20C will be referred to as mobile base station device 20.

[0022] The mobile base station device 20 is, for example, a local 5G base station, and communicates with terminals 10 located within the wireless area. Note that the scope of the present disclosure is not limited to cases where the mobile base station device 20 is a local 5G base station, but may also be, for example, a base station constituting a 4G or lower wireless communication system. Also, while the figure shows a case where there are three mobile base station devices 20, the number of mobile base station devices 20 is not limited to this and may be more or less than this. Furthermore, the installation location of the mobile base station device 20 is not particularly limited, and may be, for example, installed indoors or on the street.

[0023] The multiple mobile base station devices 20A, 20B, and 20C may be different types. For example, mobile base station device 20A may be a local 5G base station, and mobile base station devices 20B and 20C may be other types of base stations. Mobile base station device 20A establishes a communication network with mobile network 30A, mobile base station device 20B establishes a communication network with mobile network 30B, and mobile base station device 20C establishes a communication network with mobile network 30C. For example, mobile base station device 20 establishes a communication network with mobile network 30 via a base facility that serves as a connection point for mobile network 30.

[0024] Traffic analysis system 200 mirrors the traffic of upstream lines C1, C2, and C3 of multiple mobile base station devices 20A, 20B, and 20C, acquires traffic rates from the mirrored data, and uses the acquired traffic rates to analyze the wireless quality between each of mobile base station devices 20A, 20B, and 20C and terminal 10. In other words, traffic analysis system 200 estimates the wireless quality between mobile base station device 20 and terminal 10 based on the acquired traffic rates. Here, traffic rate in the present disclosure refers to the amount of data transmitted and received over a communication line per unit time, that is, the traffic flow rate per unit time.

[0025] Here, the upstream lines C1, C2, and C3 refer to fixed-line networks connecting multiple mobile base station devices 20A, 20B, and 20C with mobile networks 30A, 30B, and 30C. In other words, the upstream lines C1, C2, and C3 are assumed to be mobile backhauls or midhauls. The types of the upstream lines C1, C2, and C3 are not particularly limited, and may be wired lines using optical fiber lines or high-capacity wireless lines using microwaves. The types of the upstream lines C1, C2, and C3 may be different from each other; for example, some may be wired lines and the rest may be wireless lines.

[0026] Traffic analysis system 200 includes multiple mirroring devices 40A, 40B, and 40C, multiple traffic rate acquisition devices 50A, 50B, and 50C, and wireless quality analysis device 60. Mirroring device 40A and traffic rate acquisition device 50A are provided corresponding to mobile base station device 20A. Mirroring device 40B and traffic rate acquisition device 50B are provided corresponding to mobile base station device 20B. Mirroring device 40C and traffic rate acquisition device 50C are provided corresponding to mobile base station device 20C. When no particular distinction is made between the multiple mirroring devices 40A, 40B, and 40C, they will be referred to as mirroring devices 40. When no particular distinction is made between the multiple traffic rate acquisition devices 50A, 50B, and 50C, they will be referred to as traffic rate acquisition devices 50. The mirroring device 40 functions as a "data acquisition unit," the traffic rate acquisition device 50 functions as a "calculation unit," and the wireless quality analysis device 60 functions as an "analysis unit."

[0027] Specifically, the traffic analysis system 200 of the present disclosure includes: a mirroring device 40 that acquires data regarding communication between a mobile base station device 20 that communicates with a terminal 10 and a mobile network 30; a traffic rate acquisition device 50 that acquires the data from the mirroring device 40 and calculates the communication volume per unit time from the data; and a wireless quality analysis device 60 that acquires the communication volume per unit time from the traffic rate acquisition device 50 and analyzes the wireless quality of the mobile base station device 20 based on the communication volume per unit time.

[0028] The mirroring device 40 mirrors the traffic on the upper lines C1, C2, and C3. Mirroring here refers to copying packets transmitted and received on the upper lines using a specified device or function. For example, as an example of the mirroring device 40, a network tap may be used to copy physical signals and supply them to the traffic rate acquisition device 50. Alternatively, as an example of the mirroring device 40, a switch or router may be used to supply copied packets to the traffic rate acquisition device 50 using a mirroring function provided in the switch or router.

[0029] The traffic rate acquisition device 50 acquires and stores the traffic rate of the data mirrored by the mirroring device 40. The traffic rate acquisition device 50 transmits the acquired traffic rate to the wireless quality analysis device 60. The traffic rate acquisition device 50 is, for example, a LAN analyzer.

[0030] In this embodiment, one mobile base station device 20 is configured to correspond to one set of mirroring device 40 and traffic rate acquisition device 50, but multiple mobile base stations 20 may be configured to correspond to one set of mirroring device 40 and traffic rate acquisition device 50.

[0031] The wireless quality analysis device 60 analyzes the wireless quality between each of the mobile base station devices 20A, 20B, 20C and the terminal 10 based on the traffic rate acquired from the traffic rate acquisition device 50. The method of analyzing wireless quality by the wireless quality analysis device 60 will be described later. The wireless quality analysis device 60 may feed back the analysis results to the mobile base station device 20 or the terminal 10. The mobile base station device 20 or the terminal 10 functions to improve the wireless quality based on the feedback. The mobile base station device 20 or the terminal 10 may also display the feedback content from the wireless quality analysis device 60 so that the user can check it. The user who installed the mobile base station device 20 can improve the wireless quality based on the feedback.

[0032] Next, with reference to Figures 2 and 3, the effects on wireless quality due to interference between base stations and changes in the environment will be described. In Figure 2, network taps 40A, 40B, and 40C are provided as an example of a mirroring device 40. Furthermore, in addition to the network taps 40A, 40B, and 40C, switches or routers 70A, 70B, and 70C are also provided. In this manner, multiple devices with mirroring functionality may be provided for each upper line. In this case, the wireless quality analysis device 60 acquires the traffic rate via either the network tap 40 or the switch or router 70. Furthermore, as shown in Figure 2, the wireless quality analysis device 60 may acquire the traffic rate directly from either the network tap 40 or the switch or router 70 without going through the traffic rate acquisition device 50.

[0033] As shown in FIG. 2, mobile base station device 20A has wireless area A1, mobile base station device 20B has wireless area A2, and mobile base station device 20C has wireless area A3.

[0034] With advances in mobile technology and the rise of IoT, the practice of operators installing and operating local 5G base stations using carrier bands is becoming increasingly common. In particular, it is expected that in the future, it will become easier to obtain licenses for base station installation, allowing users to freely purchase local 5G base stations, and that large numbers of local 5G base stations will be installed in various locations. This future vision raises the following three challenges:

[0035] (1) Even if interference adjustments are made in advance, there is a possibility that radio waves may travel further than expected, resulting in interference between local 5G base stations. Specifically, although interference with neighboring base stations is taken into consideration when issuing licenses, radio wave propagation is affected by the shape of the land and the location of buildings, so radio waves may travel too far. In addition, it is difficult to design a system that takes into account the shape of the land and the location of buildings in advance. When radio interference occurs, radio quality may deteriorate. For this reason, it is desirable to appropriately detect or estimate the occurrence of radio interference. Figure 2 shows an example of interference between a radio area A1 of a mobile base station device 20A and a radio area A2 of a mobile base station device 20B.

[0036] (2) The wireless area may change due to changes in obstacles such as vegetation. In particular, in mountainous areas and agricultural regions, the presence or absence of obstacles changes depending on the vegetation, so the wireless area of ​​a base station may vary depending on the season, resulting in dead zones. Changes in the wireless area may result in a decrease in wireless quality. Therefore, it is desirable to appropriately detect or estimate changes in the wireless area. Figure 2 shows an example in which the wireless area A3 of a mobile base station device 20C changes due to environmental changes.

[0037] (3) To solve the above-mentioned problems, it is difficult to add a function to analyze wireless quality to the base station equipment itself. This is because, unlike communication carriers operated by telecommunications carriers, local 5G, which operates wirelessly in a spot manner, will use general-purpose base station equipment and terminals as they are.

[0038] In contrast, in this embodiment, by analyzing the traffic rate for each upper line and analyzing the correlation between traffic rates between upper lines, it is possible to estimate changes in wireless areas due to interference within the wireless area or changes in the environment without adding any functions to the base station device itself. Note that in this embodiment, the upstream traffic rate from the downstream mobile base station device 20 to the upstream Internet 300 is analyzed. However, since data congestion may occur in downstream communications when the wireless quality of the mobile base station device 20 deteriorates, the downstream traffic rate may also be analyzed.

[0039] For example, as shown in Fig. 3, interference between wireless areas A1 and A2 may cause a change in the traffic rate in the wireless areas A1 and A2. Specifically, Fig. 3 shows a case in which the traffic rate in wireless area A1 decreases over time, while the traffic rate in wireless area A2 increases. Conversely, by analyzing the change in the traffic rate in the wireless area, it is possible to estimate whether interference is occurring in each wireless area. In other words, it is possible to estimate the occurrence of a change in the wireless situation and analyze the wireless quality without adding functions to the base station or terminals or requiring human intervention. A more detailed analysis method using the wireless quality analysis device 60 will be described later.

[0040] 4 to 6, a detailed description will be given of an analysis method used by the wireless quality analysis device 60 to analyze the wireless quality in the wireless area of ​​the mobile base station device 20. Specifically, in this embodiment, the wireless quality analysis device 60 analyzes the wireless quality based on the following rules 1 to 3. The wireless quality analysis device 60 may analyze the wireless quality based on all of rules 1 to 3, or may analyze the wireless quality based on one or two of rules 1 to 3.

[0041] [Rule 1] FIG. 4 is a diagram illustrating Rule 1, a wireless quality analysis method used by the wireless quality analysis device 60. According to Rule 1, the wireless quality analysis device 60 estimates the possibility of poor wireless quality when the data communication speed is equal to or lower than a certain level relative to the total data communication volume. In other words, the wireless quality analysis device 60 estimates that a change has occurred in the wireless conditions between the terminal 10 and the mobile base station device 20 when the total communication volume in a predetermined period exceeds a predetermined volume and the communication speed of communication from the mobile base station device 20 to the mobile network 30 is equal to or lower than a predetermined value. Here, the total data communication volume is calculated as the area of ​​a graph with time on the horizontal axis and the upstream traffic flow rate per unit time (traffic rate) on the vertical axis. Furthermore, the communication speed increases as the upstream traffic flow rate per unit time increases, and therefore increases as the graph moves higher.

[0042] In the following description, it is assumed that the communication speed is set higher as the total data communication volume increases. In this embodiment, predetermined thresholds are set for the total data communication volume and the communication speed, and when the communication speed is lower than the predetermined threshold for any wireless area even though the total data communication volume exceeds the predetermined threshold, the wireless quality analysis device 60 estimates that the wireless quality of the wireless area is low.

[0043] In wireless area A1, the upstream traffic flow rate is zero for most of the time except for the rectangular pulse rising portion, indicating that the total data communication volume is small. Furthermore, the low position of the graph indicates that the communication speed is low. In this case, the communication speed may have been set low to match the low total data communication volume, so the wireless quality analysis device 60 does not estimate that the wireless quality of wireless area A1 is low.

[0044] In wireless area A2, data communication is ongoing, and it can be seen that the total data communication volume is large. Furthermore, the high position on the graph indicates that the communication speed is high. In this case, since the communication speed may be set high in accordance with the total data communication volume, the wireless quality analysis device 60 does not estimate that the wireless quality of wireless area A2 is low.

[0045] In wireless area A3, data communication is ongoing, and it can be seen that the total data communication volume is large. On the other hand, the low position on the graph indicates that the communication speed is low. In this case, since the communication speed is normally limited to a low level despite the total data communication volume being large, the wireless quality analysis device 60 estimates that the wireless quality of wireless area A3 is low.

[0046] According to the present disclosure, it is possible to estimate that a change has occurred in the radio conditions between the terminal 10 and the mobile base station device 20 using a simple algorithm based on the total communication volume and communication speed.

[0047] [Rule 2] Figure 5 is a diagram illustrating Rule 2, a wireless quality analysis method used by the wireless quality analysis device 60. Rule 2 acquires the change acceleration of the traffic rate over a certain time window, calculates the correlation of the change acceleration between mobile base station devices 20, and estimates the possibility of wireless interference occurring between mobile base station devices 20 that have a negative correlation. In other words, the wireless quality analysis device 60 calculates the change in communication volume per unit time for each of multiple mobile base station devices 20, and estimates that interference has occurred in the wireless areas of the multiple mobile base station devices 20 based on the correlation of the change in communication volume per unit time between the multiple mobile base station devices 20. Here, a negative correlation refers to a relationship in which the change acceleration of the traffic rate (traffic flow rate per unit time) between wireless areas changes in opposite directions.

[0048] 5 shows an example of analyzing wireless quality in wireless areas A1 and A2 using rule 2. First, the wireless quality analysis device 60 generates a graph of the acceleration of change in traffic rate for each of the wireless areas A1 and A2 from the graph of the traffic rate for each of the wireless areas A1 and A2. Specifically, the wireless quality analysis device 60 generates the graph of the acceleration of change in traffic rate by differentiating the graph of the traffic rate.

[0049] Next, the wireless quality analysis device 60 compares the graph of the change acceleration of the traffic rate in wireless area A1 with the graph of the change acceleration of the traffic rate in wireless area A2. In this case, it is found that a negative correlation appears twice within a certain time window. Therefore, the wireless quality analysis device 60 estimates that wireless interference is occurring between wireless areas A1 and A2. Note that it may also be estimated that wireless interference is occurring between wireless areas based on the negative correlation appearing multiple times within a certain time window.

[0050] In this manner, in this embodiment, wireless quality analysis device 60 analyzes wireless quality based on Rule 2, thereby making it possible to estimate when wireless areas are interfering with each other between mobile base station devices 20. According to the present disclosure, it is possible to estimate that wireless interference has occurred between mobile base station devices 20 based on a simple algorithm and to appropriately analyze wireless quality.

[0051] [Rule 3] FIG. 6 is a diagram illustrating Rule 3, a wireless quality analysis method used by the wireless quality analysis device 60. Rule 3 acquires the amount of change in traffic rate over a certain time window, calculates autocorrelation between the acquired data, and, if the correlation coefficient decreases, estimates the possibility of a change in the wireless environment under the mobile base station device 20. In other words, the wireless quality analysis device 60 acquires the communication volume per unit time for each predetermined period, calculates autocorrelation between the acquired data for each predetermined period, and, if the correlation coefficient decreases, estimates that a change in the wireless environment has occurred. Here, autocorrelation is a measure of how closely a traffic rate in a specific wireless area matches the original traffic rate when shifted over time. In other words, autocorrelation is an index for determining how much the traffic rate in a specific wireless area has changed over time. The greater the degree of change, the smaller the correlation coefficient. The wireless quality analysis device 60 sets a threshold for the correlation coefficient and estimates that the wireless area has changed if the actual correlation coefficient falls below the threshold.

[0052] Generally, it may take a considerable amount of time for changes in the wireless area to occur due to environmental changes such as vegetation. Therefore, in Rule 3, the amount of change in traffic rate may be obtained over a longer time window than in Rules 1 and 2, and the autocorrelation may be calculated between the obtained data.

[0053] 6 shows an example of analyzing wireless quality in wireless area A1 using rule 3. In wireless area A1, there is no change in the traffic rate between period T1 and period T2. Therefore, the autocorrelation coefficient does not decrease, and the wireless quality analysis device 60 does not estimate that there has been a change in wireless area A1.

[0054] In the wireless area A1, a change occurs in the traffic rate between the period T1 or T2 and the period T3. Specifically, in the wireless area A1, a decrease in the traffic rate occurs in the period T3. As a result, the autocorrelation coefficient decreases, and the wireless quality analysis device 60 estimates that a change has occurred in the wireless area A1.

[0055] In this manner, in this embodiment, the wireless quality analysis device 60 can estimate that the wireless area has changed due to environmental changes such as changes in vegetation by analyzing the wireless quality based on Rule 3. According to the present disclosure, it is possible to estimate that a change in the wireless environment has occurred based on a simple algorithm and appropriately analyze the wireless quality.

[0056] [Flowchart] Next, the processing by the traffic analysis system 200 will be described with reference to the flowchart of FIG.

[0057] In step S1, the mirroring device 40 of the traffic analysis system 200 mirrors the traffic on the upper lines C1, C2, and C3.

[0058] In step S2 , the traffic rate acquisition device 50 of the traffic analysis system 200 acquires the traffic rate of the data mirrored by the mirroring device 40 , and transmits it to the wireless quality analysis device 60 .

[0059] In steps S3 to S8, the wireless quality analysis device 60 analyzes the wireless quality between each mobile base station device 20A, 20B, 20C and the terminal 10 based on the traffic rate acquired from the traffic rate acquisition device 50, and outputs the analysis results.

[0060] Specifically, in step S3, the wireless quality analysis device 60 estimates whether the wireless quality of each wireless area is low based on rule 1. If the wireless quality of a certain wireless area is estimated to be low (step S3: Yes), the wireless quality analysis device 60 outputs an estimation result indicating that the wireless quality is low (step S4). There are no limitations on the output mode, and the result may be output to an external device so that a user can confirm that the wireless quality of a specific wireless area is low. Note that even if the wireless quality of a certain wireless area is estimated not to be low (step S3: No), the wireless quality analysis device 60 may also output an estimation result indicating that the wireless quality is not low.

[0061] Furthermore, in step S5, the wireless quality analysis device 60 estimates whether wireless interference is occurring between wireless areas based on rule 2. If it estimates that wireless interference is occurring between one wireless area and another wireless area (step S5: Yes), the wireless quality analysis device 60 outputs an estimation result indicating that wireless interference is occurring (step S6). In this case, too, there are no limitations on the output format, and the output may be sent to an external device so that a user can confirm that wireless interference is occurring. Note that even if it estimates that wireless interference is not occurring (step S5: No), the wireless quality analysis device 60 may output an estimation result indicating that wireless interference is not occurring.

[0062] Furthermore, in step S7, the wireless quality analysis device 60 estimates whether or not a change has occurred in each wireless area based on rule 3. If it is estimated that a change has occurred in a certain wireless area (step S7: Yes), the wireless quality analysis device 60 outputs an estimation result indicating that a change has occurred in the wireless area (step S8). There are no limitations on the output format, and the result may be output to an external device so that a user can confirm that a change has occurred in a specific wireless area. Note that even if it is estimated that no change has occurred in a certain wireless area (step S7: No), the wireless quality analysis device 60 may output an estimation result indicating that no change has occurred in the wireless area.

[0063] The traffic analysis system 200 repeats the above flow. The order in which the processes based on rules 1 to 3 are performed is arbitrary. As described above, it may generally take a considerable amount of time for changes in the wireless area due to environmental changes such as vegetation to occur. For this reason, the frequency with which the process based on rule 3 is performed may be lower than the frequency with which the processes based on rules 1 and 2 are performed.

[0064] The device of the present disclosure can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network. The program of the present disclosure is a program for causing a computer to realize each function of the device according to the present disclosure, and a program for causing a computer to execute each procedure of the method executed by the device according to the present disclosure.

[0065] 10: Terminal 20, 20A, 20B, 20C: Mobile base station device 300: Internet 30, 30A, 30B, 30C: Mobile network 40, 40A, 40B, 40C: Mirroring device, TAP 50, 50A, 50B, 50C: Traffic rate acquisition device 60: Wireless quality analysis device 70A, 70B, 70C: Switch or router 100: Wireless communication system 200: Traffic analysis system

Claims

1. A traffic analysis system comprising: a data acquisition unit that acquires data related to communication between a base station that communicates with a terminal and a network superior to the base station; a calculation unit that acquires the data from the data acquisition unit and calculates a communication volume per unit time from the data; and an analysis unit that acquires the communication volume per unit time from the calculation unit and analyzes the radio quality of the base station based on the communication volume per unit time.

2. The traffic analysis system according to claim 1, wherein there are a plurality of the base stations, and the analysis unit calculates a change in the communication volume per unit time for each of the plurality of base stations, and estimates that interference has occurred in the radio areas of the plurality of base stations based on a correlation of the changes in the communication volume per unit time among the plurality of base stations.

3. The traffic analysis system according to claim 1, wherein the analysis unit acquires the communication volume per unit time for each predetermined period, calculates a correlation between the acquired data for each predetermined period, and estimates that a radio environment change has occurred when a correlation coefficient decreases.

4. A traffic analysis method comprising: acquiring data related to communication between a base station that communicates with a terminal and a network superior to the base station; calculating a communication volume per unit time from the data; and analyzing the radio quality of the base station based on the communication volume per unit time.

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