KR20100016807A - In-building signal environment estimation method using drive-test data - Google Patents

Abstract

PURPOSE: A building inside propagation environment prediction method using measurement data for predicting the propagation environment of the building inside the measurement data is provided to accurately predict propagation environment inside the building inside by calculating a signal attenuation degree. CONSTITUTION: Measure points are searched based on a central point of a target building. Each of measure point, road, measurement data obtains. The signal degrade to center from each measure point is calculated(24, 25). The propagation environment at center is expected by using measurement data, signal degrade value and signal deterioration value.

Description

Propagation environment prediction method inside building using road measurement data {IN-BUILDING SIGNAL ENVIRONMENT ESTIMATION METHOD USING DRIVE-TEST DATA}

The present invention is to predict the propagation environment in the building (indoor) using the actual measurement data (road measurement data) measured along the road, and to realize the propagation environment prediction method in the building using the road measurement data and to realize the method. The present invention relates to a computer-readable recording medium that records a program. More specifically, to measure signal strength in a building that is difficult to measure in practice, actual measured data measured along the road around the building (eg signal strength, etc.) Computer-readable record of the method of predicting the propagation environment inside the building using road measurement data and the program for realizing the method. It is about the medium.

In general, wireless network optimization refers to a series of procedures for optimizing communication service quality provided to subscribers and minimizing the possibility of a call failure by changing settings such as the direction of the base station antenna, tilt, and radio wave strength.

Therefore, the computational complexity required for wireless network optimization is determined by the number of parameters to be optimized. In the general case, the parameters to be optimized include parameters such as the propagation strength which determines the direction and tilt of the base station antenna and the signal strength.

Next, a conventional method for measuring signal strength inside a building is as follows.

Conventionally, by implementing in-building call quality measurement data in association with maps and building information on the web, it is possible to easily check and share call quality visually from related departments, not measurement departments, so that the call quality of mobile communication networks can be collectively This study aimed to be able to manage the status of call quality and analyze the cause of failure.

To this end, the conventional in-building wireless terminal call quality management method, the first step of collecting the call quality measurement data for the call quality measurement area for each floor in the building (in-building) through a measuring instrument, and call quality When importing measurement data, the second step of analyzing each call quality measurement data into polygons (minimum units of the map) and classifying them into call quality measurement areas (by floor), and for each polygon in the entire measurement target area in the building. A third step of comparing and analyzing the ranks of the carrier quality and the floors of the call quality measurement data existing in the corresponding polygon; and according to the user's request on the web, the analyzer compares and analyzes the call quality measurement area (building) Including the fourth step of displaying the call quality measurement data for each service provider and floor by linking the building information and geographic information on the user terminal screen Is done.

In this case, the measuring device may be used as a portable diagram that allows the measurer to carry the wireless section call quality measurement while directly carrying each floor in the building. In this case, the measured data measured by the measuring instrument is manually input on the terminal or the web. Or copy it to DB and enter it.

In addition, the measuring device may be used for a fixed purpose that can be fixedly arranged and operated in an area where the call quality of the wireless section needs to be intensively checked. When the measuring device is used as a fixed purpose, the absolute coordinate value of the fixed position is measured. Since it is necessary to know the absolute coordinates (two-dimensional coordinate information added with three-dimensional coordinates or floor information (location information)) of a fixedly arranged position, and maps the coordinate values of the fixed position and the call quality measured at these coordinates. To the storage medium.

In the prior art as described above, since the measurer must directly enter the building inside the building with a measuring device to perform the wireless section call quality measurement, it is not only easy to measure the wireless section call quality, but also a costly and time-consuming problem. have.

On the other hand, signal strength in a building is generally difficult to measure because the GPS signal does not reach.

On the other hand, customers want to know if they are communicating inside a building, such as in the home or office.

The prior art as described above has a problem that it is difficult to measure the radio wave environment inside a building, and it is an object of the present invention to solve this problem and to meet the demand.

Therefore, the present invention uses the road measurement data to predict the radio wave environment inside the building that has not been known until now using actual measurement data (road measurement data) measured along the road around the building. It is an object of the present invention to provide a computer-readable recording medium recording a radio wave environment prediction method in a building and a program for realizing the method.

That is, the present invention uses the actual measurement data (for example, signal strength, etc.) measured along the road around the building in order to determine the radio wave environment (for example, signal strength, etc.) in a building that is difficult to measure in reality. The present invention provides a method of predicting the propagation environment in a building using road measurement data and a computer-readable recording medium recording a program for realizing the method. There is a purpose.

The objects of the present invention are not limited to the above-mentioned objects, and other objects and advantages of the present invention which are not mentioned above can be understood by the following description, and will be more clearly understood by the embodiments of the present invention. Also, it will be readily appreciated that the objects and advantages of the present invention may be realized by the means and combinations thereof indicated in the claims.

According to an aspect of the present invention, there is provided a method for predicting a propagation environment in a building, the method comprising: a search step of searching for a measurement point based on a center point of a target building to predict signal strength; Calculating road measurement data at each searched measurement point and calculating a degree of signal attenuation from each measurement point to the center point; And a propagation environment prediction step of predicting a propagation environment at the center point using the obtained road measurement data and the calculated signal attenuation value.

On the other hand, the present invention, within the building propagation environment prediction system having a processor, the function of searching for a measurement point based on the center point of the target building to predict the signal strength; Obtaining road measurement data at each searched measurement point and calculating a degree of signal attenuation from each measurement point to the center point; And a computer readable recording medium having recorded thereon a program for realizing a function of predicting a propagation environment at the center point using the obtained road measurement data and the calculated signal attenuation value.

The present invention as described above, the effect that can be predicted by using the actual measurement data (road measurement data) measured along the road around the building, the radio wave environment inside the building that has not been known so far until the actual measurement have.

That is, the present invention uses the actual measurement data (for example, signal strength, etc.) measured along the road around the building in order to determine the radio wave environment (for example, signal strength, etc.) in a building that is difficult to measure in reality. By calculating the degree of signal attenuation up to, it is possible to more accurately predict the propagation environment inside the building.

BRIEF DESCRIPTION OF THE DRAWINGS The above and other objects, features and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings, It can be easily carried out. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1a and 1b is a configuration diagram of an embodiment of a building propagation environment prediction system to which the present invention is applied.

As shown in FIG. 1A, the propagation environment prediction system in a building to which the present invention is applied includes a computer 11 for performing calculations necessary for the present invention, a keyboard 12 which is an input device for inputting data or commands, and the like. And a printer 14, which is an output device for outputting a calculation result.

As shown in FIG. 1B, the computer 11 of the building propagation environment prediction system to which the present invention is applied includes a central processing unit 15, a main memory device 16 connected to the central processing unit 15, An auxiliary memory device 17 connected to the main memory device 16 and a peripheral device 18 connected to the main memory device 16 are provided.

As described above, the system for predicting the propagation environment inside the building to which the present invention is applied includes a central processing unit 15 that controls and manages the overall operation of a computer, and stores a program performed by the central processing unit 15 and is used while performing work. Alternatively, the main memory device 16 and the auxiliary memory device 17 for storing various data generated while performing a job, the input / output devices 12 to 14 for inputting / outputting data with a user, and a communication interface for Peripheral device 18 is included.

In addition, the auxiliary memory device 17 serves to store a large amount of data, and the input / output devices 12 to 14 include a general keyboard 12, a mouse 13, a display device, a printer 14, and the like. It includes.

However, since the computer hardware environment having the configuration as described above is only a technique well known in the art, detailed description thereof will be omitted herein. However, the main memory device 16 of the hardware system described above includes actual measurement data measured along the road around the building in order to determine the radio wave environment (eg, signal strength, etc.) in the building, which is difficult to measure. A signal propagation environment prediction algorithm for predicting the propagation environment inside the building by calculating the signal attenuation to the inside of the building using signal strength, etc.) is stored, and is performed under the control of the central processing unit 15. .

In the present invention, an interior radio wave propagation prediction algorithm for predicting a radio wave environment inside a building using road measurement data searches for a measurement point based on a center point of a target building to predict signal strength. Obtaining road measurement data at each measurement point, calculating a degree of signal attenuation from each measurement point to the center point, and predicting a propagation environment at the center point using the obtained road measurement data and the calculated signal attenuation value. Algorithm.

FIG. 2 is a flowchart illustrating a method for predicting a propagation environment inside a building using road measurement data according to an embodiment of the present invention, and FIG. 3 illustrates a method of finding a measurement point that is located at the shortest distance to each surface from a center point of a target building. It is for the drawing.

First, the target building to predict the propagation environment in the building, that is, the signal strength in the building, which is difficult to measure in practice (21).

Then, the center point of the target building is determined (22). In other words, the center point is determined to be equidistant from four sides of the target building.

Thereafter, the measurement point in each direction is searched based on the determined center point (23). That is, the point where the determined point meets the road at the shortest distance in the four-direction direction of the target building is determined as the measurement point. These measurement points are labeled A, B, C, D in FIG.

Then, the signal strength of each measuring point is obtained, that is, the actual measurement data (road measurement data) measured along the road around the building is calculated, and the degree of signal attenuation from each plane direction (each measuring point) to the center point is calculated. In operation 24, the best received signal strength (meaning the received signal strength from the best server) and the received signal strength (RSSI: Received Signal Strength Indicator) at the center point are calculated (predicted).

In other words, the signal strength of each measuring point is measured, that is, the signal strength (road measurement data) is measured along the road around the building. The signal attenuation value from each measurement point to the center point is then calculated. Subsequently, the best received signal strength and the received signal at the center point are subtracted from the measured "signal strength value of each measurement point" from the calculated "signal attenuation value from each measurement point to the center point". The strength (RSSI) is calculated (predicted).

Then, the signal-to-noise ratio (SNR) at the center point using the best received signal strength and the received signal strength (RSSI) at the center point predicted from the signal strength of each of four surfaces (each measurement point) as described above. Signal-to-Noise Ratio) value is calculated (25).

Next, the process of estimating the best received signal strength and the received signal strength (RSSI) at the center point 24 and the process of calculating the signal-to-noise ratio (SNR) at the center point 25 will be described in more detail. Is the same as

As described above, the signal strength value of the found measurement points is obtained, that is, the actual measurement data (road measurement data) measured along the road around the building is obtained, and the best server of each measurement point is obtained. . At this time, in order to reduce the possibility that the incorrect value caused by the measurement error is used in the calculation (prediction), the average value can be used after summing three values back and forth in time together with the signal strength value of the shortest distance. .

Subsequently, when the straight line S from any one of the four measurement points is obtained from the center point of the target building, and the distance from the measurement point to the outer wall of the target building is D _i , the measurement point Considers the radio wave to be transmitted as the radio wave intensity measured at the measurement point, and estimates the radio wave intensity using free space loss for this distance D _i . When the building meets the straight line S from the measurement point to the center point of the building, the transmission loss value when a predefined radio wave enters the building or the shortest distance from the building is used. If there is an in-building measurement data value, the transmission loss value is obtained by using the in-building measurement data value and the signal strength value measured on the road adjacent to the target building. As the transmission loss value into the building, the best received signal strength and the received signal strength (RSSI) at the center point of the target building are calculated (predicted).

For each of the four surfaces of the target building, the best received signal strength and the received signal strength (RSSI) at the center point of the target building are calculated (predicted) in the same manner as described above. After the calculation process for each of the four sides, the base station of each signal is identified for the four signals from each side, and the best received signal strength and signal-to-noise ratio (SNR) values are calculated.

In this case, if all four signals considered in the calculation are signals transmitted from different base stations, the best received signal strength value is a value having the maximum signal strength among the four signals.

However, if there are signals transmitted from the same base station among the four signals considered in the calculation, the signal strengths of the signals from the same base station are combined into one and compared with the signal strengths of the other signals.

The signal-to-noise ratio (SNR) at the center point of the target building is a denominator of the received signal strength (RSSI) value from four planes at the center point of the target building, and the best received signal strength value obtained above is determined. Calculate as a denominator.

That is, the received signal strength (RSSI) values at the center points of the target buildings calculated from each of the four sides are RSSI_A, RSSI_B, RSSI_C, and RSSI_D, respectively. (Best Received Signal Strength) is referred to as BRSSI_A, BRSSI_B, BRSSI_C, and BRSSI_D, and it is assumed that signals having the best received signal strength (BRSSI) from each of four sides come from different base stations, and the best received signal strength (BRSSI) Assuming that the BRSSI_A value is the largest, the signal-to-noise ratio (SNR) at the center point of the target building is calculated as shown in Equation 1 below.

SNR = BRSSI_A / (RSSI_A + RSSI_B + RSSI_C + RSSI_D + Thermal_Noise-BRSSI_A)

For example, when predicting the propagation environment for the target building in Figure 3, first find the center point equidistant from each building surface, and find the measuring points A, B, C, D that is the shortest distance from the center point. At this time, the best received signal strength (BRSSI), best server (Best Server) and received signal strength (RSSI) values at each measurement point are stored, and first, the best received signal strength (BRSSI) and received signal strength ( Predict RSSI).

For example, when the best received signal strength (BRSSI) at point D is BRSSI_D0, the signal from point D will experience Free Space Loss to Penet_Point (the building wall of the target building) and Penet_Point (target). The building walls of buildings) suffer from transmission losses. From then on, Dist_InDoor from the center point will experience the loss of propagation in the building.

Therefore, at the center point of the target building, the Best Received Signal Strength and the Received Signal Strength (RSSI) from D are calculated as shown in Equation 2 below.

BRSSI_D = BRSSI_D-Free Space Loss-Penetration Loss-In-Building Propagation Loss

RSSI_D = RSSI_D-Free Space Loss-Penetration Loss-In-Building Propagation Loss

For each of the points A, B, and C, the best received signal strength (BRSSI) and the received signal strength (RSSI) at the center point of the target building can be calculated in the same manner as described above.

At this time, BRSSI_X, which is the best received signal strength (BRSSI) at the center point of the target building, may be calculated as shown in Equation 3 below.

BRSSI_X = Max [BRSSI_A, BRSSI_B, BRSSI_C, BRSSI_D]

In this case, when BRSSI_X = BRSSI_A, SNR_X, which is a signal-to-noise ratio (SNR) at the center point of the target building, may be calculated as shown in Equation 4 below.

SNR_X = BRSSI_A / (RSSI_A + RSSI_B + RSSI_C + RSSI_D + Thermal_Noise-BRSSI_A)

As described above, the present invention relates to a method for predicting signal strength in a building using signal strength measured along a road around the building, in order to identify signal strength in a building that is difficult to measure. When the drive test is performed for the signal strength data measured along the road, it is used to predict the propagation environment in the building adjacent to the road.

On the other hand, the method of the present invention as described above can be written in a computer program. And the code and code segments constituting the program can be easily inferred by a computer programmer in the art. In addition, the written program is stored in a computer-readable recording medium (information storage medium), and read and executed by a computer to implement the method of the present invention. The recording medium may include any type of computer readable recording medium.

The present invention described above is capable of various substitutions, modifications, and changes without departing from the technical spirit of the present invention for those skilled in the art to which the present invention pertains. It is not limited by the drawings.

The present invention can be used for the propagation environment prediction system inside a building.

1a and 1b is a configuration diagram of an embodiment of a building propagation environment prediction system to which the present invention is applied,

2 is a flowchart illustrating a method for predicting a propagation environment inside a building using road measurement data according to the present invention;

FIG. 3 is a view for explaining a method of finding a measuring point located at the shortest distance with respect to each surface from a center point of a target building.

* Explanation of symbols for the main parts of the drawings

11: computer 12: keyboard

13: mouse 14: printer

15: central processing unit 16: main memory unit

17: auxiliary storage device 18: peripheral device

Claims (5)

In the building radio wave environment prediction method, A search step of searching for a measurement point based on a center point of a target building to predict signal strength; Calculating road measurement data at each searched measurement point and calculating a degree of signal attenuation from each measurement point to the center point; And A propagation environment prediction step of predicting a propagation environment at the center point using the obtained road measurement data and the calculated signal attenuation value. Interior propagation environment prediction method using the road measurement data comprising a. The method of claim 1, The operation step, Measuring signal strength (road measurement data) of each measurement point along a road around the target building; And Calculating a signal attenuation value from each measurement point to the center point Interior propagation environment prediction method using the road measurement data comprising a. The method according to claim 1 or 2, The propagation environment prediction step, Calculating a best received signal strength and a received signal strength (RSSI) at the center point by using the obtained road measurement data and the calculated signal attenuation value; And Calculating a signal-to-noise ratio (SNR) at the center point using the calculated best received signal strength at the center point and received signal strength (RSSI) Interior propagation environment prediction method using the road measurement data comprising a. The method of claim 3, wherein The search step, Determining a target building to predict the signal strength; Determining a center point of the determined target building; And Searching for a road point at the shortest distance in each direction based on the determined center point as a measurement point Interior propagation environment prediction method using the road measurement data comprising a. In-building propagation environment prediction system equipped with a processor, Searching for a measurement point based on a center point of a target building to predict signal strength; Obtaining road measurement data at each of the searched measurement points and calculating a degree of signal attenuation from each measurement point to the center point; And A function of predicting the propagation environment at the center point using the obtained road measurement data and the calculated signal attenuation value A computer-readable recording medium having recorded thereon a program for realizing this.

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