CN108235338B - TD-LTE user type identification method and base station - Google Patents
TD-LTE user type identification method and base station Download PDFInfo
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Abstract
The embodiment of the invention discloses a TD-LTE user type identification method and a base station. The method comprises the following steps: determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report; determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal; if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm. The base station is used for realizing the method. The TD-LTE user type identification method provided by the embodiment of the invention can identify the user type of the TD-LTE user terminal based on the measurement report sample (MRO) data.
Description
Technical Field
The invention relates to the field of wireless communication, in particular to a Time Division-Long Term Evolution (TD-LTE) user type identification method and device.
Background
MR (Measurement Report) refers to that UE measures and reports relevant network indexes of a main neighboring cell according to Measurement configuration delivered by a network, and these reported data can be used for network evaluation and optimization. The measurement report is completed by UE and eNodeB, UE executes and reports data such as cell downlink level intensity, quality and the like, and eNodeB executes and reports measurement of reception level intensity and quality of uplink UE. The processing of measurement reports is typically done at the eNodeB. Based on the traditional network optimization method, user experience information such as network coverage conditions, call quality conditions and the like can be obtained only through drive tests and fixed point tests, the drive tests and the fixed point tests can only be used for testing some main roads and key places, and the obtained sampling point data is much less than the user information of the MR, so that the analysis result is one-sidedness. If MR data replaces a large amount of routine drive tests and fixed point tests, and a measurement report when a user actually takes a business is used for evaluating the network, the operation and maintenance cost can be saved, the method is more targeted than the drive tests and the fixed point tests, the collected data can be mined, information such as behavior patterns of the user and distribution in a cell can be analyzed, and a network optimization strategy can be conveniently formulated.
MR data is divided into Measurement Report sample (MRO) data, Measurement Report Statistics (MRs) data, and Event triggered Measurement Report sample (MRE) data. The MRO data is periodic measurement report sample data, and represents original measurement report information periodically collected by an OMC-R (radio access network element management system).
With the rapid construction of LTE networks, more and more data is needed for network evaluation and optimization. The MR data is used as the most comprehensive, most detailed and most real user acquisition data, truly reflects the state of the current network of the user and is valuable data with great utilization value. The network analysis and optimization work by using the MR data can achieve the aim of the existing network optimization more quickly and better.
However, there is no attribute information of the user type in the MR data. In practice, the user type needs to be determined in many cases during the existing network optimization process. At present, nearly 80% of traffic of the existing LTE network occurs indoors, and the distinction between indoor and outdoor of users is an important basis for network construction and optimization. The user type identification can provide an important auxiliary effect for network planning construction, and the site construction is more scientific and valuable. Meanwhile, the user identification enables the network optimization work to be more targeted, the problem positioning, the problem analysis and the solution proposal can be more accurately carried out, and the efficiency of the network optimization work is greatly improved.
However, the macro station users cannot be divided into indoor and outdoor by the means in the prior art, which becomes a bottleneck of the current network optimization industry, and the difficulty of optimization and construction is increased.
Therefore, how to provide a method for identifying the TD-LTE user type based on the measurement report sample (MRO) data is of great significance.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the invention provides a TD-LTE user type identification method and a base station.
In one aspect, an embodiment of the present invention provides a TD-LTE user type identification method, including:
determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report;
determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal;
if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm.
According to the TD-LTE user type identification method provided by the embodiment of the invention, the MR data of the user terminal can be determined according to the measurement report sample (MRO) data, and then whether the user terminal is a room division user or not is determined, so that the function of identifying the TD-LTE user type based on the MRO data is realized. In addition, the method can further judge whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm, so the method has a very wide application prospect.
On the other hand, an embodiment of the present invention further provides a base station, including:
the data determining module is used for determining the MR data of the user terminal according to the preset corresponding field in the MR sample data of the measurement report;
the indoor distribution confirmation module is used for determining whether the user terminal is an indoor distribution user or not according to the occupied cell of the MR data sampling point of the user terminal by a user;
and the type identification module is used for judging whether the user terminal is a macro station indoor user type or a macro station outdoor user type according to a preset macro station user type identification algorithm when the user terminal is a non-indoor user.
According to the base station provided by the embodiment of the invention, the MR data of the user terminal can be determined according to the measurement report sample (MRO) data, and then whether the user terminal is a room division user or not is determined, so that the function of identifying the TD-LTE user type based on the MRO data is realized. In addition, the base station can further judge whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm, so that the base station has a very wide application prospect.
In another aspect, an embodiment of the present invention further provides a TD-LTE user type identifying device, including: a processor, a memory, and a bus;
wherein the processor and the memory are connected through the bus; the processor is used for calling the program instructions in the memory to execute the method.
In yet another aspect, the present invention also discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer being capable of executing the above method.
In a final aspect, embodiments of the present invention finally provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the above method.
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Fig. 1 is a schematic flowchart of an embodiment of a TD-LTE user type identification method according to the present invention;
FIG. 2 is a diagram illustrating an ideal case of determining the position of a target UE;
FIG. 3 is a diagram illustrating an actual situation of determining a target UE location;
FIG. 4 is a schematic structural diagram of a base station according to an embodiment of the present invention;
fig. 5 is a block diagram of a TD-LTE user type identifier according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments, but not all embodiments, of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flowchart of an embodiment of a TD-LTE user type identification method according to the present invention, and referring to fig. 3, the embodiment discloses a TD-LTE user type identification method, which includes:
s1, determining MR data of the user terminal according to corresponding preset fields in the MR sample data of the measurement report;
s2, determining whether the user terminal is an indoor branch user according to the occupied cell of the MR data sampling point of the user terminal;
and S3, if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm.
According to the TD-LTE user type identification method provided by the embodiment of the invention, the MR data of the user terminal can be determined according to the measurement report sample (MRO) data, and then whether the user terminal is a room division user or not is determined, so that the function of identifying the TD-LTE user type based on the MRO data is realized. In addition, the method can further judge whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm, so the method has a very wide application prospect.
It should be noted that the main implementation subject of the embodiment of the method is a base station.
Specifically, in step S1, the base station may filter out the MR data of the user terminal through the fields of MmeUeS1apId, MmeGroupId, and MmeCode in the measurement report sample data. Wherein, the preset corresponding field is a field capable of expressing the characteristics in the collected measurement report information, and the record characteristics of the preset corresponding field are shown in table 1:
table 1: the preset corresponding field expression measurement report sample data feature table
For example, in a sample data of a certain measurement report, if the MmeCode is 124, the MmeGroupId is 257, and the MmeUeS1apId is 537565967, it can be uniquely determined that the ID of the ue is 124&257& 537565967. From the ID of the user terminal, all MR data of the user terminal can then be determined.
In step S2, it can be determined whether the user terminal is a room division user according to the occupied cell of the MR data sampling point of the user terminal determined in step S1.
Specifically, the occupied cell of the MR data sampling point is matched with the cell basic information acquired in advance by the base station, and if the occupied cell of the MR data sampling point is matched with the cell basic information, the occupied cell of the MR data sampling point is known to be a room division cell, and the corresponding user terminal is a room division user.
For example, the occupied cell ID of the MR data sampling point is 65627-1, and in the cell basic information acquired in advance by the base station, the cell with the ID of 65627-1 is a room division system cell, and the corresponding user terminal is a room division user.
In step S3, the preset macro station user type identification algorithm includes:
if the duration of the ID of the user terminal in an extensible markup language (xml) file with a preset first duration exceeds a preset second duration, judging whether a change value of a position determined by an antenna arrival angle (AOA) of the user terminal and a Timing Advance (TA) in the duration is smaller than a preset distance value;
if yes, the user terminal is judged to be the macro station indoor user type;
it should be noted that the xml file of the preset first duration is generated by the base station, and the base station updates the xml file every other preset first duration. The preset first period of time is typically 15 minutes.
Specifically, if the duration of the ID of the ue in the xml file with the preset first duration exceeds a preset second duration, for example, 15 seconds, the base station obtains the values of AOA and TA by determining the mr.ltescaoa and the mr.ltesctadv in the MR data index field corresponding to the ID of the ue.
It can be understood that the preset second time period may be adjusted according to actual needs, and this embodiment does not limit this.
The MR data index fields corresponding to the ID of the user terminal are shown in the following table:
table 2: MR data index field corresponding to ID of user terminal
The specific principle of sampling point positioning through the values of AOA and TA is as follows:
the UE receives the TA command from the network side and adjusts the transmitting time of the uplink PUCCH/PUSCH/SRS, aiming at eliminating different transmission time delays among the UEs, aligning the time of the uplink signals of different UEs reaching the eNodeB, ensuring the uplink orthogonality and reducing the interference in the cell. TA characterizes the distance between the UE and the antenna port.
The time advance distance corresponding to 1Ts is equal to: (3 x 10 x 8 x 1/(15000 x 2048))/2 ═ 4.89 m. Meaning distance is the propagation speed (speed of light) 1Ts/2 (sum of up and down paths). The distance corresponding to the TA command value is calculated with reference to 1 Ts.
In the random access process: the eNodeB measures an uplink PRACH leader sequence, 11bit information is carried in MAC payload of the RAR (random access response), the range of TA is 0-1282, and according to the TA value in the RAR, the UE adjusts uplink transmission time Nta to TA 16, and the value is constant positive.
For example: TA is 1, then Nta is 1 x 16Ts, characterized by a distance of 16 x 4.89m, 78.12m, typically 78m for one TA.
And AOA represents the antenna angle of arrival, defining an estimated angle of the user with respect to a reference direction. The measurement reference direction should be due north, counterclockwise. That is, the angle at which the user is currently located counterclockwise to the north.
In this embodiment, the base station locates the MR data sampling point of the user terminal according to the AOA and TA locating algorithms based on the obtained AOA and TA values within the duration. And comparing the change values of the positions determined by the AOA and the TA in the duration with a preset distance value. And if the change value is smaller than the preset distance value, determining that the user terminal is the macro station indoor user type.
For example, the preset distance value is set to 20 m. Within the duration, if the TA of a certain user terminal in the MRO at a certain moment is 2 and the AOA is 90 degrees, the MR data sampling point of the user terminal determined by the TA and the AOA is located at a position between 156m and 234m of the righteast of the cell; and the next time TA and the MR data sampling point of the user terminal determined by the AOA are located at the position between 78m and 156m of the righteast of the cell, the variation value of the positions determined by the AOA and the TA in the duration is greater than 20m, and the base station can determine that the user terminal is the macro station outdoor user type.
If the MR data sampling point of the ue determined by the next time TA and the AOA is still located at a position between 156m and 234m of the righteast of the cell, the change value of the positions determined by the AOA and the TA in the duration is less than 20m, and the base station may determine that the ue is an indoor user type of the macro station.
Further, the preset macro station user type identification algorithm further includes:
if the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration and the AOA and TA values of the user terminal are null, the user terminal sends a message to the user terminal to start the call
Acquiring a position change value of the user terminal in the duration through a three-point positioning algorithm;
and if the position change value is not smaller than the preset distance value, judging that the user terminal is an outdoor user of the macro station.
Specifically, when the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration, but the reported AOA or TA value is null, or there is other abnormality, or the MR data sampling point is unavailable, the base station obtains the position change value of the user terminal within the duration through a three-point positioning algorithm.
The three-point positioning algorithm has the following basic principle:
the method comprises collecting multiple field strengths according to signals transmitted by multiple receivers by detecting transmitters, estimating the distance between the transceivers by using known channel fading model and the field strength value of the transmitted signals, and obtaining multiple distance values (path loss L)iTransmission poweri+ antenna gainiReception field strengthi，Ri＝f(Li) By solving the set of distance equations between the transceivers, the location of the target UE can be determined
The ideal situation is as follows: the terminal is positioned by taking three base stations as circle centers and R as distanceiThe intersection of the three circles (as shown in figure 2).
The practical situation is as follows: since the NLOS error is a large non-negative value, the measured distance is much larger than the true distance, and the position of the terminal should be in the overlapping region of multiple circles (as shown in fig. 3).
It should be noted that when the distance is inversely deduced by using the field strength value, it should be on the premise of having a relatively accurate propagation model. Therefore, the propagation model calibration needs to be performed first.
The standard macrocell propagation model is as follows:
L＝K1+K2log(d)+K3Hms+K4log(Hms)+K5log(Heff)+K6log(d)log(Heff)+K7Diffraction+Kclutter
wherein:
d: distance (m) between base station and mobile station
Hms: height of the ground (m) on which the mobile station is located
Heff: effective height (m) of base station antenna
Diffraction: diffraction losses (dB) via obstructed paths
Kclustter: loss parameter of ground feature
Typical parameters take the following values:
however, the wireless propagation environment is very different. If the influence of parameters such as different landforms, buildings, vegetation and the like is not considered according to the experience, the constructed network has coverage and quality problems, or the constructed base stations are too dense, so that the resource waste is caused. Therefore, it is necessary to perform testing for different geographical environments in each region and correct parameters of the propagation model by means of analysis, calculation, and the like. And finally, a propagation model which can reflect the local wireless propagation environment most and has the theoretical reliability is obtained.
In this embodiment, the three-point positioning algorithm includes:
Wherein the typical relief areas may be irregular dense urban areas, high-rise dense commercial areas, regular/irregular general urban areas, rural areas, open areas of urban areas, industrial parks, etc.
And 3, solving by a least square method to obtain:
vector quantity
The first two items are the estimated coordinates of the user terminal
Wherein,
wherein i is 1, 2, … n.
And if the position change value of the MR data sampling point corresponding to the ID of the user terminal is smaller than a preset distance value within the duration, judging that the user terminal is an outdoor user of the macro station.
And if the position change value is smaller than a preset distance value, the base station judges the user type of the user terminal according to a corresponding index field in preset MR data.
Specifically, the base station makes the following determination according to the mr.ltecscrsrp, the mr.ltecncrsrp, and the mr.ltecscphr index fields of the MR data sampling points:
1. and if the RSRP of the MR data sampling point is more than or equal to-90 dBm, the RSRP of the strongest adjacent cell is more than or equal to-95 dBm and the PHR is more than or equal to 20, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro station.
2. And if the RSRP of the MR data sampling point is less than or equal to-90 dBm and the RSRP of the strongest adjacent cell is greater than or equal to-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro-station.
3. And if the RSRP of the MR data sampling point is less than-100 dBm and the RSRP of the strongest adjacent cell is less than-105 dBm, judging that the user terminal corresponding to the MR data sampling point is a macro-station indoor user.
4. And if the MR.LtescRSRP, the MR.LtescRSRP and the MR.LtescPHR index fields of the MR data sampling points do not meet the judgment conditions of 1-3, judging that the user terminal corresponding to the MR data sampling points is the other type of user.
It should be noted that, if the duration of the ID of the user terminal in the xml file with the preset first duration is less than the preset second duration, the base station may also determine the user type of the user terminal according to the corresponding index field in the preset MR data:
specifically, the base station makes the following determination according to the mr.ltecscrsrp, the mr.ltecncrsrp, and the mr.ltecscphr index fields of the MR data sampling points:
21. and if the RSRP of the MR data sampling point is more than or equal to-90 dBm, the RSRP of the strongest adjacent cell is more than or equal to-95 dBm and the PHR is more than or equal to 20, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro station.
22. And if the RSRP of the MR data sampling point is less than or equal to-90 dBm and the RSRP of the strongest adjacent cell is greater than or equal to-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro-station.
23. And if the RSRP of the MR data sampling point is less than-90 dBm and the RSRP of the strongest adjacent cell is less than-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an indoor user of the macro station.
24. And if the MR.LtescRSRP, the MR.LtescRSRP and the MR.LtescPHR index fields of the MR data sampling points do not meet the judgment conditions of 1-3, judging that the user terminal corresponding to the MR data sampling points is the other type of user.
According to the TD-LTE user type identification method provided by the embodiment of the invention, due to the use of the preset macro station user type identification algorithm, whether the user terminal moves or not can be judged according to the AOA + TA and the three-point positioning algorithm, so that the user type of the user terminal is identified, and the obtained identification result has extremely high accuracy. In addition, the method can be combined with index fields such as the MR.LtescRSRP, the MR.LtescPHR and the like to effectively identify the user types of the user terminals with uncertain position and movement information, so that the method can realize the identification of the user terminal types under almost all conditions, and has a very wide application prospect.
Fig. 4 is a schematic structural diagram of an embodiment of a base station of the present invention, and referring to fig. 4, an embodiment of the present invention further provides a base station, which includes a data determining module 1, a room division confirming module 2, and a type identifying module 3, where:
the data determining module 1 is configured to determine MR data of the user terminal according to a preset corresponding field in MR sample data of the measurement report; the indoor distribution confirmation module 2 determines whether the user terminal is an indoor distribution user according to the occupied cell of the MR data sampling point of the user terminal; the type identification module 3 is used for judging whether the user terminal is a macro station indoor user type or a macro station outdoor user type according to a preset macro station user type identification algorithm when the user terminal is a non-indoor user.
According to the base station provided by the embodiment of the invention, the MR data of the user terminal can be determined according to the measurement report sample (MRO) data, and then whether the user terminal is a room division user or not is determined, so that the function of identifying the TD-LTE user type based on the MRO data is realized. In addition, the base station can further judge whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm, so that the base station has a very wide application prospect.
Specifically, the data determining module 1 may screen out MR data of the user terminal through fields of MmeUeS1apId, MmeGroupId, and MmeCode in the measurement report sample data.
For example, in a sample data of a certain measurement report, the MmeCode is 124, the MmeGroupId is 257, and the MmeUeS1apId is 537565967, the data determination module 1 can uniquely determine that the ID of the ue is 124&257& 537565967. Based on the ID of the user terminal, the data determination module 1 may then determine all MR data of the user terminal.
The indoor partition confirming module 2 may determine whether the user terminal is an indoor partition user according to the occupied cell of the MR data sampling point of the user terminal determined by the data determining module 1.
Specifically, the indoor partition confirming module 2 may match the occupied cell of the MR data sampling point with cell basic information acquired in advance by the base station, and if the occupied cell of the MR data sampling point is known as an indoor partition cell through matching, the corresponding user terminal is an indoor partition user.
For example, the occupied cell ID of the MR data sampling point is 65627-1, and in the cell basic information acquired in advance by the base station, the cell with the ID of 65627-1 is a room division system cell, and the corresponding user terminal is a room division user.
The type identification module 3 is specifically configured to:
if the duration of the ID of the ue in the xml file of the first preset duration exceeds a second preset duration, the type identifying module 3 determines whether a change value of the position determined by the antenna arrival angle AOA of the ue and the timing advance TA in the duration is smaller than a preset distance value;
if yes, the user terminal is judged to be the macro station indoor user type;
it should be noted that the xml file of the preset first duration is generated by the base station, and the base station updates the xml file every other preset first duration. The preset first period of time is typically 15 minutes.
Specifically, if the duration of the ID of the user terminal in the xml file with the preset first duration exceeds a preset second duration, for example, 15 seconds, the type identifying module 3 obtains the values of AOA and TA by determining the mr.ltescaoa and the mr.ltesctadv in the MR data index field corresponding to the ID of the user terminal.
It can be understood that the preset second time period may be adjusted according to actual needs, and this embodiment does not limit this.
Further, the type identification module 3 locates the MR data sampling point of the user terminal according to the AOA and TA locating algorithm based on the obtained AOA and TA values within the duration. And comparing the change values of the positions determined by the AOA and the TA in the duration with a preset distance value. And if the change value is smaller than the preset distance value, determining that the user terminal is the macro station indoor user type.
For example, the preset distance value is set to 20 m. Within the duration, if the TA of a certain user terminal in the MRO at a certain moment is 2 and the AOA is 90 degrees, the MR data sampling point of the user terminal determined by the TA and the AOA is located at a position between 156m and 234m of the righteast of the cell; and the next time TA and the MR data sampling point of the user terminal determined by the AOA are located at the position between 78m and 156m of the righteast of the cell, the variation value of the positions determined by the AOA and the TA in the duration is greater than 20m, and the type identification module 3 can determine that the user terminal is the macro-station outdoor user type.
If the MR data sampling point of the ue determined by the next time TA and the AOA is still located at a position between 156m and 234m of the righteast of the cell, the variation value of the positions determined by the AOA and the TA in the duration is less than 20m, and the type identifying module 3 may determine that the ue is the macro indoor user type.
Further, the type identification module 3 is further specifically configured to:
if the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration and the AOA and TA values of the user terminal are null, the user terminal sends a message to the user terminal to start the call
Acquiring a position change value of the user terminal in the duration through a three-point positioning algorithm;
and if the position change value is not smaller than the preset distance value, judging that the user terminal is an outdoor user of the macro station.
Specifically, when the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration, but the reported AOA or TA value is null, or there is another anomaly, or the MR data sampling point is unavailable, the type identifying module 3 obtains the position change value of the user terminal within the duration through a three-point positioning algorithm.
The three-point positioning algorithm comprises the following steps:
Wherein the typical relief areas may be irregular dense urban areas, high-rise dense commercial areas, regular/irregular general urban areas, rural areas, open areas of urban areas, industrial parks, etc.
And 3, solving by a least square method to obtain:
vector quantity
The first two items are the estimated coordinates of the user terminal
Wherein,
wherein i is 1, 2, … n.
And if the position change value of the MR data sampling point corresponding to the ID of the user terminal is smaller than a preset distance value within the duration, judging that the user terminal is an outdoor user of the macro station.
If the position change value is smaller than a preset distance value, the type identification module 3 judges the user type of the user terminal according to a corresponding index field in preset MR data.
Specifically, the type identification module 3 makes the following determination according to the mr.ltescrsrp, the mr.ltenncrrsrp, and the mr.ltescphr index fields of the MR data sampling points:
1. and if the RSRP of the MR data sampling point is more than or equal to-90 dBm, the RSRP of the strongest adjacent cell is more than or equal to-95 dBm and the PHR is more than or equal to 20, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro station.
2. And if the RSRP of the MR data sampling point is less than or equal to-90 dBm and the RSRP of the strongest adjacent cell is greater than or equal to-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro-station.
3. And if the RSRP of the MR data sampling point is less than-100 dBm and the RSRP of the strongest adjacent cell is less than-105 dBm, judging that the user terminal corresponding to the MR data sampling point is a macro-station indoor user.
4. And if the MR.LtescRSRP, the MR.LtescRSRP and the MR.LtescPHR index fields of the MR data sampling points do not meet the judgment conditions of 1-3, judging that the user terminal corresponding to the MR data sampling points is the other type of user.
It should be noted that, if the duration of the ID of the user terminal in the xml file with the preset first duration is less than the preset second duration, the type identifying module 3 may also determine the user type of the user terminal according to the corresponding index field in the preset MR data:
specifically, the type identification module 3 makes the following determination according to the mr.ltescrsrp, the mr.ltenncrrsrp, and the mr.ltescphr index fields of the MR data sampling points:
21. and if the RSRP of the MR data sampling point is more than or equal to-90 dBm, the RSRP of the strongest adjacent cell is more than or equal to-95 dBm and the PHR is more than or equal to 20, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro station.
22. And if the RSRP of the MR data sampling point is less than or equal to-90 dBm and the RSRP of the strongest adjacent cell is greater than or equal to-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an outdoor user of the macro-station.
23. And if the RSRP of the MR data sampling point is less than-90 dBm and the RSRP of the strongest adjacent cell is less than-95 dBm, judging that the user terminal corresponding to the MR data sampling point is an indoor user of the macro station.
24. And if the MR.LtescRSRP, the MR.LtescRSRP and the MR.LtescPHR index fields of the MR data sampling points do not meet the judgment conditions of 1-3, judging that the user terminal corresponding to the MR data sampling points is the other type of user.
According to the base station provided by the embodiment of the invention, the preset macro station user type identification algorithm is used, so that whether the user terminal moves can be judged according to the AOA + TA and the three-point positioning algorithm, and the user type of the user terminal is further identified, and the obtained identification result has extremely high accuracy. In addition, the base station can also effectively identify the user types of the user terminals with uncertain position and movement information by combining index fields such as MR.LtescRSRP, MR.LtescPHR and the like, so that the base station can realize the identification of the user terminal types under almost all conditions, and has a very wide application prospect.
Fig. 5 is a block diagram of a TD-LTE user type identifier according to the present invention, and referring to fig. 5, an embodiment of the present invention further provides a TD-LTE user type identifier, including:
a processor (processor)501, a memory (memory)502, a bus 503;
wherein,
the processor 501 and the memory 502 are connected through the bus 503;
the processor 501 is configured to call program instructions in the memory 502 to perform the methods provided by the above-mentioned method embodiments, for example, including: determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report; determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal; if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm.
Embodiments of the present invention also disclose a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which when executed by a computer, enable the computer to perform the methods provided by the above-mentioned method embodiments, for example, including: determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report; determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal; if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm.
Finally, an embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores computer instructions, where the computer instructions cause the computer to execute the method provided by the foregoing method embodiments, for example, the method includes: determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report; determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal; if not, judging whether the user terminal is the macro station indoor user type or the macro station outdoor user type according to a preset macro station user type identification algorithm.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A TD-LTE user type identification method is characterized by comprising the following steps:
determining MR data of the user terminal according to corresponding fields preset in the MR sample data of the measurement report;
determining whether the user terminal is a room division user or not according to the occupied cell of the MR data sampling point of the user terminal;
if not, judging whether the user terminal is a macro station indoor user type or a macro station outdoor user type according to a preset macro station user type identification algorithm;
the preset macro station user type identification algorithm comprises the following steps:
if the duration of the ID of the user terminal in an extensible markup language (xml) file with a preset first duration of a preset first duration exceeds a preset second duration, judging whether a change value of a position determined by an antenna arrival angle (AOA) of the user terminal and a Timing Advance (TA) in the duration is smaller than a preset distance value;
if yes, the user terminal is judged to be the macro station indoor user type;
wherein, the preset macro station user type identification algorithm further comprises:
if the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration and the AOA and TA values of the user terminal are null, the user terminal sends a message to the user terminal to start the call
Acquiring a position change value of the user terminal in the duration through a three-point positioning algorithm;
and if the position change value is not smaller than the preset distance value, judging that the user terminal is an outdoor user of the macro station.
2. The method of claim 1, wherein if the position change value is less than a preset distance value,
and judging the user type of the user terminal according to a corresponding index field in preset MR data.
3. The method according to claim 1, wherein if the duration of the ID of the ue in the xml file with the preset first duration is less than the preset second duration, the ue type of the ue is determined according to a corresponding indicator field in the preset MR data.
4. A base station, comprising:
the data determining module is used for determining the MR data of the user terminal according to the preset corresponding field in the MR sample data of the measurement report;
the indoor distribution confirmation module is used for determining whether the user terminal is an indoor distribution user or not according to the occupied cell of the MR data sampling point of the user terminal by a user;
the type identification module is used for judging whether the user terminal is a macro station indoor user type or a macro station outdoor user type according to a preset macro station user type identification algorithm when the user terminal is a non-indoor user;
the type identification module is specifically configured to:
if the duration of the ID of the user terminal in an extensible markup language (xml) file with a preset first duration exceeds a preset second duration, judging whether a change value of a position determined by an antenna arrival angle (AOA) of the user terminal and a Timing Advance (TA) in the duration is smaller than a preset distance value;
if yes, the user terminal is judged to be the macro station indoor user type;
the type identification module is further specifically configured to:
if the duration of the ID of the user terminal in the xml file with the preset first duration exceeds the preset second duration and the AOA and TA values of the user terminal are null, the user terminal sends a message to the user terminal to start the call
Acquiring a position change value of the user terminal in the duration through a three-point positioning algorithm;
and if the position change value is not smaller than the preset distance value, judging that the user terminal is an outdoor user of the macro station.
5. The base station of claim 4, wherein the type identification module is further specifically configured to:
if the position change value is smaller than the preset distance value,
and judging the user type of the user terminal according to a corresponding index field in preset MR data.
6. The base station of claim 4, wherein the type identification module is further specifically configured to:
and if the duration time of the ID of the user terminal in the xml file with the preset first duration is less than the preset second duration, judging the user type of the user terminal according to a corresponding index field in the preset MR data.
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