CN116980826A - Method, device and storage medium for distinguishing indoor and outdoor terminals - Google Patents
Method, device and storage medium for distinguishing indoor and outdoor terminals Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- H—ELECTRICITY
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- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H04W4/02—Services making use of location information
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- H—ELECTRICITY
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Abstract
The application discloses a distinguishing method, a distinguishing device and a storage medium of indoor and outdoor terminals, wherein the method comprises the following steps: acquiring first measurement data and second measurement data, wherein the first measurement data comprises data related to the position of a terminal to be distinguished, and the second measurement data comprises RSRP measured by the terminal to be distinguished or comprises RSRP and RSRQ measured by the terminal to be distinguished; determining a position partition to which the position of the terminal to be distinguished belongs according to the first measurement data and the plurality of divided position partitions of the serving cell; according to the indoor and outdoor partition thresholds corresponding to the position partitions to which the terminal to be distinguished belongs and second measurement data, determining that the terminal to be distinguished is an indoor terminal or an outdoor terminal, wherein each position partition of a service cell corresponds to one indoor and outdoor partition threshold, the indoor and outdoor partition thresholds are obtained according to a plurality of fourth measurement data of each position partition, and the fourth measurement data comprises RSRP measured by the first terminal or RSRP and RSRQ measured by the first terminal. In this way, the method and the device can improve the accuracy of distinguishing the indoor terminal from the outdoor terminal.
Description
Technical Field
The present application relates to the field of mobile communications technologies, and in particular, to a method, an apparatus, and a storage medium for distinguishing indoor and outdoor terminals.
Background
It is very important for operators to distinguish whether a terminal is indoor or outdoor based on radio signal measurement data. When a user accesses a room substation, all wireless signal measurement data can be simply determined as indoor. When a user accesses a macro station, the indoor and outdoor terminal distinction based on wireless signal measurement data is a difficult problem in the industry, and at present, when the terminal is judged to be indoor or outdoor, the terminal is directly based on a fixed threshold obtained by statistics on all data in a service cell, which is easy to cause misjudgment.
Disclosure of Invention
Based on the above, the embodiment of the application provides a method, a device and a storage medium for distinguishing indoor and outdoor terminals, which can improve the accuracy of distinguishing the indoor and outdoor terminals.
In a first aspect, the present application provides a method for distinguishing indoor and outdoor terminals, the method comprising:
acquiring first measurement data and second measurement data, wherein the first measurement data comprises data related to the position of a terminal to be distinguished, and the second measurement data comprises Reference Signal Received Power (RSRP) measured by the terminal to be distinguished or comprises RSRP and Reference Signal Received Quality (RSRQ) measured by the terminal to be distinguished;
determining a position partition to which the position of the terminal to be distinguished belongs according to the first measurement data and the plurality of divided position partitions of the service cell;
and determining the terminal to be distinguished as an indoor terminal or an outdoor terminal according to an indoor and outdoor partition threshold corresponding to the position partition to which the terminal to be distinguished belongs and second measurement data, wherein each position partition of the service cell corresponds to one indoor and outdoor partition threshold, the indoor and outdoor partition thresholds are obtained according to a plurality of fourth measurement data of each position partition under the service cell, and the fourth measurement data comprises RSRP measured by the first terminal or RSRP and RSRQ measured by the first terminal.
In a second aspect, the present application provides a distinguishing device for indoor and outdoor terminals, the device including a communication circuit, a memory, and a processor, the communication circuit being used for communication; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the method for distinguishing indoor and outdoor terminals as described above when the computer program is executed.
In a third aspect, the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement the indoor and outdoor terminal distinguishing method as described above.
The embodiment of the application provides a method, a device and a storage medium for distinguishing indoor and outdoor terminals, which divide a service cell into a plurality of position partitions, each position partition corresponds to an indoor and outdoor partition threshold, the position partition to which the position of the terminal to be distinguished belongs is determined according to first measurement data, and further, second measurement data can be compared with the indoor and outdoor partition threshold corresponding to the position partition to which the position of the terminal to be distinguished belongs to determine that the terminal to be distinguished is an indoor terminal or an outdoor terminal.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for distinguishing between indoor and outdoor terminals according to the present application;
fig. 2 is a schematic diagram of an embodiment of a serving cell division position partition in the indoor and outdoor terminal division method according to the present application;
fig. 3 is a schematic structural diagram of an embodiment of an indoor and outdoor terminal distinguishing device according to the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
In the following description, suffixes such as "module", "part" or "unit" for representing elements are used only for facilitating the description of the present application, and have no particular meaning in themselves. Thus, "module," "component," or "unit" may be used in combination.
Referring to fig. 1, fig. 1 is a flow chart of an embodiment of a method for distinguishing between indoor and outdoor terminals according to the present application, where the method includes: step S101, step S102, and step S103.
Step S101: and acquiring first measurement data and second measurement data, wherein the first measurement data comprises data related to the position of the terminal to be distinguished, and the second measurement data comprises Reference Signal Received Power (RSRP) measured by the terminal to be distinguished or comprises RSRP and Reference Signal Received Quality (RSRQ) measured by the terminal to be distinguished.
The first measurement data and the second measurement data both belong to radio signal measurement data, which may be from Measurement Report (MR), minimization of drive tests data (MDT, minimization of Drive Test), etc.
The first measurement data comprise data related to the position of the terminal to be distinguished, and the position of the terminal to be distinguished in the service cell can be obtained according to the first measurement data.
In an embodiment, the first measurement data includes a first Timing Advance (TA) and a first horizontal azimuth (hDoA, horizontal Direction of Arrival); or a first beam comprising a first time advance and a serving cell having a strongest RSRP; or a first neighbor cell comprising a first time advance and the strongest RSRP.
The time advance TA may refer to a difference between an actual time when a signal of the terminal arrives at the base station and a time when the signal of the terminal arrives at the base station assuming that a distance between the terminal and the base station is 0; the base station determines the TA value of each terminal by measuring the uplink transmission of the terminal, wherein the TA value can represent the distance between the terminal and the base station, and the unit is Ts,1Ts is approximately equal to 4.88 meters. The first time advance is TA of the terminal to be distinguished, which is measured by the base station.
The horizontal azimuth, also called as the horizontal direction of arrival, may refer to the direction of connection between the base station and the terminal, which is zero degrees in the north direction, and is increased as a reference standard in the clockwise direction, where hDoA may represent the specific direction in which the terminal is located in the serving cell, and the unit is °; at 5g 8tr and above, the base station may measure the horizontal azimuth. The first horizontal azimuth may be a connection direction of the base station and the terminal to be distinguished.
5g 8tr and above typically form multiple narrow beams covering different directions. The terminal may measure signal strengths of different beams of the serving cell, wherein the strongest RSRP beam (StrongestBeam) of the serving cell may characterize the specific direction in which the terminal is located in the serving cell. The first beam with the strongest RSRP of the serving cell is the beam (StrongestBeam) with the strongest RSRP of the serving cell measured by the terminal to be distinguished.
For 4G or 5G 8tr or less, hDoA is not usually measured, and a narrow beam is not formed, and a neighbor cell (strongestnCellkey) with the strongest RSRP may be used to characterize that the terminal is located in a specific direction of the serving cell. The first neighbor cell with the strongest RSRP may characterize a specific direction in which the terminal to be differentiated is located in the serving cell.
The embodiment of the application can determine the position of the terminal to be distinguished in the service cell by the distance between the terminal to be distinguished and the base station and the specific direction of the terminal to be distinguished in the service cell.
The second measurement data comprises a reference signal received power (RSRP, reference Signal Receiving Power) measured by the terminal to be distinguished or comprises an RSRP and a reference signal received quality (RSRQ, reference Signal Receiving Quality) measured by the terminal to be distinguished.
The reference signal received power RSRP may refer to the average value of the signal power received on all Resource Elements (REs) carrying cell-specific reference signals on the frequency band considered for measurement, which is a main indicator reflecting the coverage of the serving cell. Antenna shielding and hardware faults can cause weak signals, are easy to generate call drop and reduce call completing rate, and are used for checking blind spot coverage and weak coverage areas of cells.
The reference signal received quality (RSRQ, reference Signal Receiving Quality) represents the received quality of the reference signal, and this measure mainly orders the different candidate cells according to signal quality, which is used as input for handover and cell reselection decisions. RSRQ is defined as the ratio of N RSRP/RSSI, where N is the number of Resource Blocks (RBs) of the RSSI measurement bandwidth. The received signal strength indicator (RSSI, received Signal Strength Indication), which is a base station side indicator, is a power average value of all signals on a measurement frequency, and is used to determine the link quality and whether to increase the broadcast transmission strength.
The strength of the RSRP can reflect whether the antenna is shielded or not very sensitively and sufficiently, and the RSRP measured when the terminal is indoor is smaller than the RSRP measured when the terminal is outdoor. Of course, RSRP may also be combined with other measurement data that are different between indoor and outdoor terminals, so as to increase the feasibility and accuracy of the distinction between indoor and outdoor terminals. For example: RSRP and RSRQ.
Step S102: and determining the position partition to which the position of the terminal to be distinguished belongs according to the first measurement data and the plurality of divided position partitions of the service cell.
In the embodiment of the application, the service cell is divided into a plurality of position partitions in advance, and the specific position partition of the terminal to be distinguished in the service cell can be obtained according to the first measurement data.
The service cell may be divided into a plurality of location areas by manual operation, or the locations of a plurality of terminals except the terminal to be distinguished in the service cell may be counted and then divided, or the directions and distances may be split to realize the location areas, etc. As shown in fig. 2, fig. 2 is a position division implemented by dividing directions and distances.
Step S103: and determining the terminal to be distinguished as an indoor terminal or an outdoor terminal according to an indoor and outdoor partition threshold corresponding to the position partition to which the terminal to be distinguished belongs and second measurement data, wherein each position partition of the service cell corresponds to one indoor and outdoor partition threshold, the indoor and outdoor partition thresholds are obtained according to a plurality of fourth measurement data of each position partition under the service cell, and the fourth measurement data comprises RSRP measured by the first terminal or RSRP and RSRQ measured by the first terminal.
In the embodiment of the present application, each location partition of the serving cell corresponds to an indoor and outdoor partition threshold, that is, each location partition of the serving cell has previously obtained an indoor and outdoor partition threshold. The indoor and outdoor partition threshold is obtained according to a plurality of fourth measurement data of each position partition under the service cell, wherein the fourth measurement data comprises RSRP measured by the first terminal or RSRP and RSRQ measured by the first terminal.
And obtaining an indoor and outdoor partition threshold according to the fourth measurement data of each position partition under the service cell, and adopting various modes. In the embodiment of the application, the indoor and outdoor division threshold can be used for distinguishing the indoor and outdoor terminals, and the specific forms of the indoor and outdoor division threshold can be various. The indoor and outdoor partition thresholds are obtained in different modes, and the specific modes are different. For example, a simple statistical method may be used for the fourth measurement data, where the indoor and outdoor partition threshold may be a simple indoor and outdoor partition threshold; for another example, a training method may be used for the plurality of fourth measurement data, where the indoor and outdoor area division threshold may be a classifier obtained by training and used for distinguishing the indoor and outdoor terminals; for another example, a gaussian mixture model may be used for the fourth measurement data, and when the data is one-dimensional RSRP, the indoor and outdoor partition threshold may be the average value of two average values corresponding to the fitted two gaussian distributions (i.e., the two average values are averaged); for another example, a gaussian mixture model may be used for the fourth measurement data, where the data is two-dimensional data, such as RSRP and RSRQ, the fitted gaussian distribution is two-dimensional, the mean value is a two-dimensional vector, and the indoor and outdoor partition thresholds may be a straight line (i.e., the mean value of two gaussian distributions in the two-dimensional space is a point, and the perpendicular bisectors of the two-point lines), where the straight line divides the two-dimensional space into two parts, the side with the larger RSRP is outdoor, and the side with the smaller RSRP is indoor.
Compared with the prior art that all terminals to be distinguished in a service cell are uniformly fixed with a threshold, the embodiment of the application divides the service cell into a plurality of position partitions, each position partition corresponds to an indoor and outdoor partition threshold, the position partition to which the position of the terminal to be distinguished belongs is determined according to the first measurement data, and further the second measurement data can be compared with the indoor and outdoor partition threshold corresponding to the position partition to which the position of the terminal to be distinguished belongs to determine that the terminal to be distinguished is an indoor terminal or an outdoor terminal.
Details of the serving cell partition into a plurality of location partitions are described in detail below.
In an embodiment, the plurality of location partitions of the serving cell are obtained by dividing a plurality of third measurement data under the serving cell, where the third measurement data includes data related to a location where the first terminal is located.
The embodiment of the application divides the service cell according to the positions of the first terminals in the service cell to obtain a plurality of position partitions, so that the plurality of position partitions are more in line with the actual distribution situation of the first terminals in the service cell, and the position partition of the terminal to be distinguished can be more accurately determined.
In an embodiment, the third measurement data includes a third time advance and a third horizontal azimuth; or a third beam including a third time advance and a serving cell with the strongest RSRP; or a third neighbor cell comprising a third time advance and the strongest RSRP of the serving cell.
In an embodiment, in order to ensure that a certain amount of third measurement data can be counted later in each location partition, and also in order to ensure the efficiency of serving cell division, the third measurement data can be discretized.
Step S102, before determining, according to the first measurement data and the plurality of location areas divided by the serving cell, a location area to which the location of the terminal to be distinguished belongs, the method may further include: step A1 and step A2.
Step A1: and discretizing the third time advance and the third horizontal azimuth angle in each third measurement data under the serving cell respectively to obtain a plurality of groups of discretized time advance and horizontal azimuth angles.
Step A2: and dividing the service cell according to the plurality of groups of discretized time advance and horizontal azimuth angles to obtain a plurality of position partitions.
The multiple groups of discretized time advance and horizontal azimuth angle can divide the distance and angle of the service cell respectively, so that the service cell can be divided into multiple position partitions.
For the third horizontal azimuth discretization in each third measurement data, hdoagroup=round (hdoa/t 1 )*t 1 Round () is rounded, t 1 Is a parameter, and is determined according to practical conditions, such as default value t 1 ＝10。
For the third time advance discretization in each third measurement data, tagroup=round (TA/t 2 )*t 2 ，t 2 Is a parameter, and is determined according to practical conditions, such as default value t 2 ＝4。
At this time, the location partition key of the serving cell is: scellkey_hdoagroup_tagroup.
According to the embodiment of the application, the plurality of third measurement data are divided into a plurality of groups through discretization, each group corresponds to a pair of discretization time advance and horizontal azimuth angle (hdoagroup_tagroup), and the service cell can be divided into a plurality of position partitions by the plurality of groups of discretization time advance and horizontal azimuth angle.
Or, in step S102, before determining the location partition to which the location of the terminal to be distinguished belongs according to the first measurement data and the plurality of location partitions divided by the serving cell, the method may further include: step B1 and step B2.
Step B1: discretizing the third time advance in each third measurement data under the serving cell to obtain a plurality of discretized time advances.
Step B2: and dividing the service cell according to the plurality of discretized time advance and the plurality of third beams to obtain a plurality of position partitions.
The third beams of the serving cell with the strongest RSRP can divide the angle of the serving cell, and the discretized time advance can divide the distance of the serving cell, so that the serving cell can be divided into a plurality of position partitions.
At this time, the location partition key of the serving cell is: sCel lkey_StronestBeam_TAGRoup.
Or, in step S102, before determining the location partition to which the location of the terminal to be distinguished belongs according to the first measurement data and the plurality of location partitions divided by the serving cell, the method may further include: step C1 and step C2.
Step C1: discretizing the third time advance in each third measurement data under the serving cell to obtain a plurality of discretized time advances.
Step C2: and dividing the service cell according to the plurality of discretized time advance amounts and the plurality of third neighbor cells to obtain a plurality of position partitions.
The third neighbor cells with the strongest RSRP of the serving cell can divide the serving cell in angle, and the discretized time advance can divide the distance of the serving cell, so that the serving cell can be divided into a plurality of position partitions.
At this time, the location partition key of the serving cell is: scellkey_strongstncllkey_tagroup.
Details of determining the indoor and outdoor discrimination threshold are described in detail below.
In one embodiment, a clustered gaussian mixture model is used to accurately determine the indoor and outdoor partition thresholds.
Step S103, before determining that the terminal to be distinguished is an indoor terminal or an outdoor terminal according to the indoor and outdoor partition threshold corresponding to the location partition to which the location of the terminal to be distinguished belongs and the second measurement data, the method may further include: step S104 and step S105.
Step S104: and obtaining outdoor Gaussian distribution and indoor Gaussian distribution of each position zone by using the plurality of fourth measurement data of each position zone under the service cell and the Gaussian mixture model.
Step S105: and determining the indoor and outdoor partition thresholds of each position partition according to the outdoor Gaussian distribution and the indoor Gaussian distribution of each position partition.
The gaussian mixture model precisely quantizes things by using a gaussian probability density function (normal distribution curve), which is a model formed by decomposing things into a plurality of gaussian probability density functions (normal distribution curve). The indoor and outdoor partition thresholds are determined through the Gaussian mixture model, so that the indoor and outdoor partition thresholds can be more accurate.
In an embodiment, in order to avoid manual participation, to avoid manually acquiring training data of indoor and outdoor labels, the plurality of fourth measurement data of each location partition under the serving cell has no indoor and outdoor labels; and determining the indoor and outdoor partition thresholds by adopting an unsupervised learning mode.
Two cases can be distinguished, the first being: the fourth measurement data comprises RSRP and RSRQ of the serving cell measured by the first terminal; at this time, step S103, the obtaining an outdoor gaussian distribution and an indoor gaussian distribution of each location partition by using the plurality of fourth measurement data and the gaussian mixture model of each location partition under the serving cell may include: substep S103A1, substep S103A2 and substep S103A3.
Substep S103A1: and discretizing the RSRP and the RSRQ in each fourth measurement data in each position partition respectively to obtain a plurality of pairs of discretized RSRP and RSRQ value pairs.
Substep S103A2: the frequency of occurrence of each pair of discretized RSRP, RSRQ value pairs within each location partition is counted.
Substep S103A3: and fitting the Gaussian mixture model by using an unsupervised learning mode by taking frequency of occurrence of each pair of discrete RSRP and RSRQ value pairs and a plurality of pairs of discrete RSRP and RSRQ value pairs in each position partition as inputs to obtain two-dimensional outdoor Gaussian distribution and two-dimensional indoor Gaussian distribution of each position partition.
Discretizing the RSRP and RSRQ in each fourth measurement data in each location partition respectively:
RSRPGroup＝round(RSRP/t 3 )*t 3
RSRQGroup＝round(RSRQ/t 4 )*t 4
wherein t is 3 、t 4 Is a parameter, and is determined according to practical conditions, such as default value t 3 ＝5，t 4 ＝2。
The frequency of occurrence of each pair of discretized RSRP, RSRQ value pairs (RSRPGroup, RSRQGroup) within each location partition is then counted as cnt. x is a set of discretized value pairs (RSRPGroup, RSRQGroup), N number of value pairs (RSRPGroup, RSRQGroup) in total, N is a set of frequencies for each pair of value pairs (RSRPGroup, RSRQGroup). Wherein (RSRPGroup) j ,RSRQGroup j ) Represents the j-th value pair (RSRPGroup, RSRQGroup), cnt j Indicating how frequently the jth value pair (RSRPGroup, RSRQGroup) appears.
With the generated set of numerical pairsSum frequency set->For the input of the gaussian mixture model, a position-partitioned indoor and outdoor signal vector x= (RSRP, RSRQ) is fitted T Is divided into (1)Cloth P (x).
Where k=2 is the number of gaussian models in the gaussian mixture model, d=2 is the data dimension, α k To measure the probability that the data belongs to the kth sub-Gaussian model, φ (x|μ k ,∑ k ) Probability density function, μ, as a k-th sub-Gaussian model k Sigma is the data mean vector of the kth sub-Gaussian model k The upper corner marks (0), (i-1) and (i) in the following formulas respectively represent parameters updated by the 0 th iteration, the i-1 th iteration and the i-th iteration for the covariance matrix of the kth sub-Gaussian model, wherein the 0 th iteration parameter is a preset initial value, can be set arbitrarily and is set as follows by default
The first element (μ) in the mean vector of the above Gaussian distribution 1 and Gaussian distribution 2 1,1 、μ 2,1 ) The second element (μ) is the mean value corresponding to RSRP 1,2 、μ 2,2 ) The average value corresponding to the RSRQ. When determining the indoor and outdoor thresholds, the first element in the mean vector, i.e. the mean corresponding to the RSRP, is taken and compared with the first element (mu) 1,1 、μ 2,1 ) The first element in the mean vector has a large gaussian distribution outside the room, and the first element in the mean vector has a small gaussian distribution inside the room. The second element in the mean vector of gaussian distribution 1 and gaussian distribution 2Plain (mu) 1,2 、μ 2,2 ) For the average value corresponding to RSRQ, it can be used to check the rationality of gaussian distribution 1 and gaussian distribution 2, and the second element in the average vector determined to be outdoor gaussian distribution (i.e. the average value corresponding to RSRQ of outdoor gaussian distribution) should be larger than the second element in the average vector determined to be indoor gaussian distribution (i.e. the average value corresponding to RSRQ of indoor gaussian distribution); if the second element in the mean vector determined to be the outdoor gaussian (i.e., the mean corresponding to the RSRQ of the outdoor gaussian) is less than or equal to the second element in the mean vector determined to be the indoor gaussian (i.e., the mean corresponding to the RSRQ of the indoor gaussian), then gaussian 1 and gaussian 2 are unreasonable, and the location partition cannot distinguish between the indoor and outdoor terminals.
The second case is: the fourth measurement data comprises a first RSRP, a first RSRQ of a serving cell, a second RSRP and a second RSRQ of a neighbor cell with the strongest RSRP, which are measured by the first terminal; that is, in the embodiment of the present application, the fourth measurement data includes not only the first RSRP and the first RSRQ of the serving cell measured by the first terminal, but also the second RSRP and the second RSRQ of the neighboring cell with the strongest RSRP measured by the first terminal.
At this time, step S103, the obtaining an outdoor gaussian distribution and an indoor gaussian distribution of each location partition by using the plurality of fourth measurement data and the gaussian mixture model of each location partition under the serving cell may include: substep S103B1, substep S103B2, substep S103B3 and substep S103B4.
Substep S103B1: the method comprises the steps of obtaining the average RSRP of a first RSRP and a second RSRP in each fourth measured data in each position partition, and obtaining the average RSRQ of the first RSRQ and the second RSRQ.
The first RSRP and the second RSRP in each fourth measurement data are summed, then the average RSRP is obtained, the first RSRQ and the second RSRQ in each fourth measurement data are summed, and then the average RSRQ is obtained.
Substep S103B2: and discretizing each average RSRP and each average RSRQ in each position partition respectively to obtain a plurality of pairs of discretized RSRP and RSRQ value pairs.
Substep S103B3: the frequency of occurrence of each pair of discretized RSRP, RSRQ value pairs within each location partition is counted.
Substep S103B4: and fitting the Gaussian mixture model by using an unsupervised learning mode by taking frequency of occurrence of each pair of discrete RSRP and RSRQ value pairs and a plurality of pairs of discrete RSRP and RSRQ value pairs in each position partition as inputs to obtain two-dimensional outdoor Gaussian distribution and two-dimensional indoor Gaussian distribution of each position partition.
In an embodiment, in order to ensure the accuracy of the indoor and outdoor division threshold, when the indoor and outdoor division threshold is determined, whether an abnormal situation occurs is determined, and if the abnormal situation occurs, the location division cannot distinguish the indoor and outdoor terminals. I.e. the method further comprises: step S106.
Step S106: if abnormal conditions occur in the fitting of the Gaussian mixture model corresponding to the position partition, determining that the indoor terminal and the outdoor terminal cannot be distinguished in the position partition.
Wherein the abnormal condition includes that each pair of discretized RSRP, RSRQ value pairs of the location partition occurs less frequently than a first preset number threshold, or that the logarithm of the discretized RSRP, RSRQ value pairs (i.e., the logarithm of the value pairs) is less than a second preset number threshold.
When the frequency of occurrence of each pair of discrete RSRP and RSRQ value pairs in the position partition is smaller than a first preset quantity threshold, or the number of pairs of discrete RSRP and RSRQ value pairs is smaller than a second preset quantity threshold, the fourth measurement data in the position partition is too small, the follow-up fitting distribution can not be ensured, at the moment, two Gaussian distribution fitting fails, and the position partition can not be distinguished from indoor terminals and outdoor terminals.
That is, in order to ensure that the following fitting distribution can be accurately performed, the following two conditions are required to be satisfied:
condition 1: (RSRPGroup, RSRQGroup) the frequency of the value pair is equal to or greater than t 5 Wherein t is 5 Is a parameter (i.e. a first preset quantity threshold), and is determined according to practical conditions, such as default value t 5 ＝100；
Condition 2: the corresponding number of the numerical values meeting the condition 1 is more than or equal to t 6 Wherein t is 6 Is a parameter (i.e. a second preset quantity threshold), and is determined according to practical conditions, such as default value t 6 ＝5。
Or the abnormal condition comprises that the weight of any Gaussian distribution in the two Gaussian distributions obtained by fitting is smaller than a preset weight threshold.
One of the two Gaussian distributions is outdoor Gaussian distribution, the other Gaussian distribution is indoor Gaussian distribution, if the weight of any Gaussian distribution in the two Gaussian distributions is smaller than a preset weight threshold value, the fact that fourth measurement data used for fitting the two Gaussian distributions are unbalanced can be explained, the number of first terminals located indoors is greatly different from the number of first terminals located outdoors, the two Gaussian distributions cannot accurately distinguish the indoor and outdoor terminals, at the moment, fitting of the two Gaussian distributions fails, and the position partition cannot distinguish the indoor and outdoor terminals.
Taking the above fitting as an example: alpha 1 <t 7 Or alpha 2 <t 7 At this time, the fitting of two Gaussian distributions fails, and the position partition cannot be distinguished indoors and outdoors, where t 7 Is a parameter (namely a preset weight threshold), and is determined according to practical conditions, for example, a default value t 7 ＝0.05。
Or, the abnormal condition comprises that the covariance of any one of the two Gaussian distributions obtained by fitting is smaller than a preset covariance threshold.
The covariance of any one of the two gaussian distributions is smaller than the preset covariance threshold, and the fact that fourth measurement data for fitting the two gaussian distributions are unbalanced can also be explained, the number of first terminals located indoors is greatly different from the number of first terminals located outdoors, the two gaussian distributions cannot accurately distinguish the indoor terminals from the outdoor terminals, at the moment, fitting of the two gaussian distributions fails, and the position partition cannot distinguish the indoor terminals from the outdoor terminals.
Taking the above fitting as an example: sigma of I 1 |<t 8 Or |Σ 2 |<t 8 At this time, the two Gaussian distributions fail to fit, and the location partition cannot be usedAnd distinguishing indoor and outdoor terminals. Where |·| represents determinant computation, t 8 Is a parameter (namely a preset covariance threshold), and is determined according to practical conditions, for example, a default value t 8 ＝1。
Or the abnormal condition comprises that the distance between the average values corresponding to the two Gaussian distributions obtained by fitting is smaller than a preset distance threshold value.
The distance between the average values corresponding to the two gaussian distributions is smaller than a preset distance threshold, that is, the average values corresponding to the two gaussian distributions are close, which can lead to the fact that indoor and outdoor terminals cannot be accurately distinguished.
Taking the above fitting as an example: [ mu ] (mu ] 1 -μ 2 ) T (μ 1 -μ 2 )|<t 9 At this time, the fitting of two Gaussian distributions fails, and the position partition cannot distinguish between indoor and outdoor terminals, where t 9 Is a parameter, and is determined according to practical conditions, such as default value t 9 ＝5。
Alternatively, the abnormal situation includes a contradictory relationship of the means of the two-dimensional gaussian distributions.
The mean value relationship of the two-dimensional gaussian distributions contradicts each other, that is, the mean value relationship of the two normal distributions is unreasonable, when the second element of the mean value vector of the determined outdoor gaussian distribution (i.e., the mean value corresponding to the RSRQ of the determined outdoor gaussian distribution) is not larger than the second element of the mean value vector of the determined indoor gaussian distribution (i.e., the mean value corresponding to the RSRQ of the determined indoor gaussian distribution), the fitted mean value relationship of the two normal distributions is unreasonable, and at this time, the fitting of the two-dimensional gaussian distributions fails, and the position partition cannot distinguish indoor and outdoor terminals.
For the terminal to be distinguished, the distance between the second measurement data and the center of the two Gaussian distributions can be calculated, and the terminal to be distinguished is judged to be an indoor terminal when the distance is close to the center of the indoor Gaussian distribution, and the terminal to be distinguished is judged to be an outdoor terminal when the distance is close to the center of the outdoor Gaussian distribution. The center of the gaussian distribution may be the center of the gaussian distribution obtained by one-dimensional RSRP fitting, or the center of the gaussian distribution obtained by two-dimensional RSRP and RSRQ fitting.
For example, for a terminal to be distinguished, the location partition to which the location of the terminal to be distinguished belongs is first determined, and the signal characteristic s= (RSRP, RSRQ) of the second measurement data is calculated T Mean vector mu corresponding to indoor Gaussian distribution of location partition to which it belongs in Distance d of (2) in ＝|(s-μ in ) T (s-μ in ) |, and signal characteristics s= (RSRP, RSRQ) T Mean vector mu corresponding to outdoor Gaussian distribution of location partition to which it belongs out Distance d of (2) out ＝|(s-μ out ) T (s-μ out )|。
If d in ＜d out Illustrating that the signal characteristics of the second measurement data are closer to the mean vector mu corresponding to the indoor Gaussian distribution in It can thus be determined that the terminal to be distinguished is located indoors if d in ≥d out Illustrating that the signal characteristics of the second measurement data are closer to the mean vector μ corresponding to the outdoor gaussian distribution out It can be determined that the terminal to be distinguished is located outdoors.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an embodiment of an indoor and outdoor terminal distinguishing device according to the present application, and the device according to the embodiment of the present application may be applied to a base station. It should be noted that, the device of this embodiment can implement the above-mentioned method for distinguishing between indoor and outdoor terminals, and detailed description of related content is referred to the above-mentioned method section, and will not be repeated here.
The apparatus 100 comprises a communication circuit 3, a memory 1 and a processor 2, the communication circuit 3 being for communication; the memory 1 is used for storing a computer program; the processor 2 is configured to execute the computer program and implement the method for distinguishing indoor and outdoor terminals according to any one of the above when the computer program is executed.
The processor 2 may be a micro control unit, a central processing unit or a digital signal processor, among others. The memory 1 may be a Flash chip, a read-only memory, a magnetic disk, an optical disk, a usb disk, a removable hard disk, or the like.
The present application also provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement the indoor and outdoor terminal distinguishing method as described in any one of the above.
The computer readable storage medium may be an internal storage unit of the above apparatus, such as a hard disk or a memory. The computer readable storage medium may also be an external storage device of the above apparatus, such as a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, etc.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.
In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The preferred embodiments of the present application have been described above with reference to the accompanying drawings, and thus do not limit the scope of the claims of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the present application shall fall within the scope of the appended claims.
Claims (10)
1. A method for distinguishing between indoor and outdoor terminals, the method comprising:
acquiring first measurement data and second measurement data, wherein the first measurement data comprises data related to the position of a terminal to be distinguished, and the second measurement data comprises Reference Signal Received Power (RSRP) measured by the terminal to be distinguished or comprises RSRP and Reference Signal Received Quality (RSRQ) measured by the terminal to be distinguished;
determining a position partition to which the position of the terminal to be distinguished belongs according to the first measurement data and the plurality of divided position partitions of the service cell;
and determining the terminal to be distinguished as an indoor terminal or an outdoor terminal according to an indoor and outdoor partition threshold corresponding to the position partition to which the terminal to be distinguished belongs and second measurement data, wherein each position partition of the service cell corresponds to one indoor and outdoor partition threshold, the indoor and outdoor partition thresholds are obtained according to a plurality of fourth measurement data of each position partition under the service cell, and the fourth measurement data comprises RSRP measured by the first terminal or RSRP and RSRQ measured by the first terminal.
2. The method of claim 1, wherein the first measurement data comprises a first time advance and a first horizontal azimuth; or a first beam comprising a first time advance and a serving cell having a strongest RSRP; or a first neighbor cell comprising a first time advance and the strongest RSRP.
3. The method of claim 1, wherein the plurality of location partitions of the serving cell are partitioned based on a plurality of third measurement data for the serving cell, the third measurement data including data related to a location of the first terminal.
4. A method according to claim 3, wherein the third measurement data comprises a third time advance and a third horizontal azimuth; or a third beam including a third time advance and the strongest RSRP of the serving cell; or a third neighbor cell including a third time advance and the strongest RSRP.
5. The method of claim 4, wherein before determining the location partition to which the location of the terminal to be distinguished belongs according to the first measurement data and the plurality of divided location partitions of the serving cell, further comprises:
discretizing a third time advance and a third horizontal azimuth angle in each third measurement data under the serving cell respectively to obtain a plurality of groups of discretized time advance and horizontal azimuth angles;
dividing the service cell according to the plurality of groups of discretized time advance and horizontal azimuth angles to obtain a plurality of position partitions;
or alternatively, the process may be performed,
discretizing a third time advance in each third measurement data under the serving cell to obtain a plurality of discretized time advances;
dividing the service cell according to the plurality of discretized time advance and the plurality of third beams to obtain a plurality of position partitions;
or alternatively, the process may be performed,
discretizing each third time advance under the serving cell to obtain a plurality of discretized time advances;
and dividing the service cell according to the discretized time advance and the third neighbor cells to obtain a plurality of position partitions.
6. The method of claim 1, wherein before determining that the terminal to be distinguished is an indoor terminal or an outdoor terminal according to the indoor and outdoor partition threshold corresponding to the location partition to which the location of the terminal to be distinguished belongs and the second measurement data, further comprises:
obtaining outdoor Gaussian distribution and indoor Gaussian distribution of each position partition by using a plurality of fourth measurement data of each position partition under the service cell and a Gaussian mixture model;
and determining the indoor and outdoor partition thresholds of each position partition according to the outdoor Gaussian distribution and the indoor Gaussian distribution of each position partition.
7. The method of claim 6, wherein the fourth plurality of measurement data for each location partition under the serving cell is devoid of indoor and outdoor tags;
the fourth measurement data comprises RSRP and RSRQ of the serving cell measured by the first terminal;
the obtaining outdoor gaussian distribution and indoor gaussian distribution of each location partition by using the plurality of fourth measurement data and the gaussian mixture model of each location partition under the serving cell comprises the following steps:
performing discretization on RSRP and RSRQ in each fourth measurement data in each position partition respectively to obtain a plurality of pairs of discretized RSRP and RSRQ value pairs;
counting the occurrence frequency of each pair of discrete RSRP and RSRQ value pairs in each position partition;
fitting the Gaussian mixture model by using an unsupervised learning mode by taking frequency of occurrence of each pair of discrete RSRP and RSRQ value pairs and a plurality of pairs of discrete RSRP and RSRQ value pairs in each position partition as input to obtain two-dimensional outdoor Gaussian distribution and two-dimensional indoor Gaussian distribution of each position partition;
or alternatively, the process may be performed,
the fourth measurement data comprises a first RSRP, a first RSRQ of a serving cell, a second RSRP and a second RSRQ of a neighbor cell with the strongest RSRP, which are measured by the first terminal;
the obtaining outdoor gaussian distribution and indoor gaussian distribution of each location partition by using the plurality of fourth measurement data and the gaussian mixture model of each location partition under the serving cell comprises the following steps:
acquiring a mean value RSRP of a first RSRP and a second RSRP in each fourth measured data in each position partition, and a mean value RSRQ of the first RSRQ and the second RSRQ;
discretizing each average value RSRP and each average value RSRQ in each position partition respectively to obtain a plurality of pairs of discretized RSRP and RSRQ value pairs;
counting the occurrence frequency of each pair of discrete RSRP and RSRQ value pairs in each position partition;
and fitting the Gaussian mixture model by using an unsupervised learning mode by taking frequency of occurrence of each pair of discrete RSRP and RSRQ value pairs and a plurality of pairs of discrete RSRP and RSRQ value pairs in each position partition as inputs to obtain two-dimensional outdoor Gaussian distribution and two-dimensional indoor Gaussian distribution of each position partition.
8. The method of claim 7, wherein the method further comprises:
if abnormal conditions occur in the fitting of the Gaussian mixture model corresponding to the position partition, determining that the indoor terminal and the outdoor terminal cannot be distinguished in the position partition;
the abnormal condition comprises that the frequency of occurrence of each pair of discrete RSRP, RSRQ value pairs of the position partition is smaller than a first preset quantity threshold, or the number of pairs of discrete RSRP, RSRQ value pairs is smaller than a second preset quantity threshold;
or the abnormal condition comprises that the weight of any Gaussian distribution in the two Gaussian distributions obtained by fitting is smaller than a preset weight threshold;
or the abnormal condition comprises that the covariance of any Gaussian distribution in the two Gaussian distributions obtained by fitting is smaller than a preset covariance threshold;
or the abnormal condition comprises that the distance between the average values corresponding to the two Gaussian distributions obtained by fitting is smaller than a preset distance threshold value;
alternatively, the abnormal situation includes a contradictory relationship of the means of the two-dimensional gaussian distributions.
9. An indoor and outdoor terminal distinguishing device is characterized by comprising a communication circuit, a memory and a processor, wherein the communication circuit is used for communication; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the indoor and outdoor terminal distinguishing method according to any one of claims 1 to 8 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program, which when executed by a processor causes the processor to implement the method of distinguishing between indoor and outdoor terminals according to any one of claims 1-8.
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| CN202210327032.7A CN116980826A (en) | 2022-03-30 | 2022-03-30 | Method, device and storage medium for distinguishing indoor and outdoor terminals |
| PCT/CN2022/127514 WO2023184952A1 (en) | 2022-03-30 | 2022-10-26 | Method and apparatus for distinguishing indoor and outdoor terminals, and storage medium |
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| CN202210327032.7A CN116980826A (en) | 2022-03-30 | 2022-03-30 | Method, device and storage medium for distinguishing indoor and outdoor terminals |
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| CN104349335B (en) * | 2013-08-09 | 2017-11-21 | 中国移动通信集团安徽有限公司 | A kind of network coverage planning index analysis method and system |
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