CN106572495B

CN106572495B - Network quality monitoring method and coverage evaluation method based on signaling and MR data

Info

Publication number: CN106572495B
Application number: CN201610866643.3A
Authority: CN
Inventors: 李勇; 李果; 郭惠军; 王栋; 卫钰; 张大伟; 崔红伟
Original assignee: Putian Information Engineering Design Services Co Ltd
Current assignee: Putian Information Engineering Design Services Co Ltd
Priority date: 2016-09-29
Filing date: 2016-09-29
Publication date: 2019-12-10
Anticipated expiration: 2036-09-29
Also published as: CN106572495A

Abstract

the invention discloses a network quality monitoring method based on signaling and MR data, which comprises the following steps: step (1): collecting and analyzing GGSNDATATEID and SGSNDATATEID, BeginTime and URI information through an S1-U interface, and extracting longitude and latitude information according to a longitude and latitude format; step (2): collecting XDR information through an S1-MME interface, and associating the XDR information with cell information through ERAB _ ULTEID, ERAB _ ULTEID and BeginTime association information; and (3): and obtaining RSRP data of the MR acquisition point by correlating the cell information and the starting time with the MRO data. The method does not need to carry out a large number of field test, saves resources, has strong stability, has the ductility of long-term stable tracking analysis, can correlate, analyze and output the weak coverage problem area of the wireless network, and can accurately position the network planning optimization problem through coverage.

Description

Network quality monitoring method and coverage evaluation method based on signaling and MR data

Technical Field

The invention relates to the technical field of communication, in particular to a network quality monitoring method and a network coverage evaluation method based on signaling and MR data.

Background

With the gradual scale expansion of the construction of the LTE network, the network structure is increasingly complex, the problems in the aspects of network coverage interference and the like are more and more prominent, and how to comprehensively, accurately and real-timely position and analyze the problems in the network, further optimize and quickly improve the perception of network users is an important task for the network optimization work of the LTE network. The background signaling and the MR data are real-time reported data of LTE network users, cover actual perception experience of indoor and outdoor users of the whole network, and objectively reflect network performance conditions.

The existing covering accurate positioning mainly comprises the following 3 methods:

Method 1-field test: coverage data are collected by a DT (drive test) and CQT (call quality dialing test) test method, a tester is required to carry a test instrument to carry out on-site network depth test, and the collected coverage data are accurately positioned in a coverage mode through a GPS (global positioning system) in the test process. The method has the defects that (1) a large amount of testing personnel and equipment are needed for positioning, and resources are occupied too much. (2) The test period is long, and the requirement of rapid construction of the current network cannot be met. (3) The test can only select partial point locations and roads for testing, and the test result cannot completely reflect the actual network situation

Method 2-measurement report analysis: the MR data acquired by the existing network is analyzed, and the mobile phone MR data comprises coverage accurate positioning according to TA (distance from the cell) and IOA (orientation from the cell) of sampling points in the MR data. Chinese patent application No. 201510767565.7 discloses a method for accurately positioning the position of an LTE terminal based on an MRO measurement report, which uses AOA (eNB received signal arrival angle) and TA (UE time advance) data in a standard measurement report of an LTE system to accurately position the specific position of the UE terminal, thereby solving the problem that the conventional positioning algorithm can only accurately position to a cell level and estimate the position in a cell by completely depending on a propagation model, and improving the positioning accuracy of the UE terminal to about 40 meters, and further, by the position change of the moving UE terminal on a time sequence, performing motion correction on the position of the terminal at each measurement report time by a mathematical calculation method, and further improving the positioning accuracy to about 20 meters. The disadvantages are that the positioning analysis by MR data is mainly limited by the complex wireless environment of the current network, the signal can not be transmitted in a straight line,

Method 3-signal simulation prediction: the coverage accurate positioning is mainly carried out by combining the current network parameters with the signal simulation prediction of the wireless environment according to the high-precision map through simulation software. The main defects are that the wireless environment is complex, software simulation is difficult to be consistent with the reality, and the precision of simulation is also limited by the problem of low precision of the existing network parameters.

disclosure of Invention

Aiming at the defects in the prior art, the invention aims to solve the technical problems that a network quality monitoring method based on signaling and MR data can effectively reflect the coverage condition of the existing network and user perception, accurately position the area of the problem, further analyze an optimization scheme and improve the network performance and the user perception.

In order to solve the technical problems, the invention adopts the following scheme:

The network quality monitoring method based on the signaling and the MR data comprises the following steps:

Step (1): collecting and analyzing GGSNDATATEID and SGSNDATATEID, BeginTime and URI information through an S1-U interface, and extracting longitude and latitude information according to a longitude and latitude format; step (2): collecting XDR information through an S1-MME interface, and associating the XDR information with cell information through ERAB _ ULTEID, ERAB _ DLTEID and BeginTime association information; and (3): and obtaining RSRP data of the MR acquisition point by correlating the cell information and the starting time with the MRO data.

The network coverage evaluation method based on the signaling and the MR data comprises the following steps: and drawing a coverage map of the cell according to the network quality monitoring method based on the signaling and MR data, and evaluating the network coverage.

The present invention has the following advantageous effects in that,

(1) The invention does not need to carry out a large amount of field test, saves a large amount of related resources, has strong stability and has the ductility of long-term stable tracking analysis.

(2) The invention can output the wireless network weak coverage problem area by correlation analysis, and the positioning precision can reach within 10 meters; the electronic map has building names and can be directly positioned to buildings, the main principle is that part of UE reports longitude and latitude information when in a connected state for service, the longitude and latitude information is generated by positioning through a GPS of a mobile phone, the longitude can be guaranteed within 10 meters, and the data can be obtained by collecting signaling at an S1-U port and analyzing the signaling

(3) The invention can accurately position the network planning optimization problem through coverage, quickly position the problem through backtracking of signaling, and provide strategy analysis for network construction and user development.

Drawings

Fig. 1 is a flow chart of an embodiment of the network quality monitoring method based on signaling and MR data of the present invention.

Fig. 2 is a flow chart of another embodiment of the network quality monitoring method based on signaling and MR data of the present invention.

Fig. 3 is a schematic diagram of a signal transmission path from a base station to a terminal.

Fig. 4 is a flow chart of screening valid sample data.

Fig. 5 is a rasterized cell coverage map.

Detailed Description

the invention is described in further detail below with reference to the figures and the examples, but without limiting the invention.

First, the meanings of terms (abbreviations) in the specification and claims of the present application are listed.

MR: MeasurementReport measurement report

MRO: MeasurementReport Original measurement report sample data

LTE: long Term Evolution of Long Term Evolution

MME: mobility Management Entity

SGSN: serving GPRS Support Node

GGSN: gateway GPRS Support Node

S1-U: s1 user interface

S1-MME: s1 control plane interface

NAS: network Attached Storage

EPC: improved Packet Core4G Core network

IMSI: international Mobile Subscriber identity Number

TMSI: temporary Mobile Subscriber Identity Temporary Mobile Subscriber Identity

globally Unique Temporary UE Identity for GUTI Global Unique temporal UE Identity

URI-Uniform Resource Identifier-Universal Resource Identifier

XDR External Data Representation

reference Signal Receiving Power Reference Signal received Power

Mmes1 apuId: MME side S1 link UE identification

RAB Radio Access Bearer

introduction to data interface

The S1 interface is a communication interface between LTE eNodeB (base station) and EPC (packet core network), and is divided into two interfaces, one for control plane (S1-MME) and one for user plane (S1-U), according to the concept of bearer and control separation.

The S1-MME is used for transmitting Session Management (SM) and Mobility Management (MM) information, namely signaling plane or control plane information, the S1-U establishes a tunnel between the GW and the eNodeB equipment and transmits user data service, namely user plane data, and the MRO data is MR data output according to the technical requirement specification of TD-LTE _ OMC-R measurement report of a communication provider.

the S1-MME interface acquisition information comprises context information (IP address, UE capability and the like), user identity information (IMSI, TMSI, GUTI and the like), switching information, position information (cell, TAC and the like), E-RAB bearer management information, NAS information (user attachment, authentication, paging, TA update and the like), and S1 interface management information (MME identification, load balance and the like); the S1-U interface acquisition information comprises wireless side information corresponding to user services, and the types of user service data such as HTTP, IM, Video and the like; the acquired MRO data comprises UE measurement information such as level and adjacent cells.

Integrated algorithm flow

Through analyzing the collected S1-U, S1-MME and MRO data, the three data can be associated by key fields to obtain user location information and corresponding measurement information, and the specific work flow is as shown in fig. 1:

(1) collecting and analyzing GGSNDATATEID and SGSNDATATEID, BeginTime and URI information through an S1-U interface, and extracting longitude and latitude information according to the existing longitude and latitude format;

(2) Collecting XDR information through an S1-MME interface, and associating the XDR information with cell information through ERAB _ ULTEID, ERAB _ DLTEID and BeginTime association information;

(3) And obtaining the RSRP data of the point location by correlating the cell information and the starting time with the MRO data.

preferably, the present embodiment further adds the following calibration steps: and obtaining an effective coverage accurate positioning point through calibration algorithm arrangement, wherein the purpose is to eliminate the influence of the geographic environment on the propagation path.

The detailed process of the data association algorithm is described in detail below with reference to the accompanying drawings.

According to the acquired signaling information of the S1-U, S1-MME interface and the MR data of the same time period, firstly, the data are analyzed, and key information is output.

First step, S1-U data parsing

XDR Data (External Data Representation) of S1-U is collected, which only needs to contain fields such as user longitude and latitude, GGSNDATATEID and SGSNDATATEID. The current format of the XDR data for S1-U according to the Mobile interface Specification is shown in Table 1 below

Table 1: XDR () data format of S1-U

Analyzing URL character strings of each line of S1-U signaling, and analyzing the associated information and longitude and latitude information, wherein the associated information is directly matched with fields GGSNDATATEID and SGSNDATATEID, the longitude and latitude are matched and searched based on the following 11 longitude and latitude character string matching rules, and if the matching is successful, the longitude and latitude are analyzed and output according to the following corresponding formats; the specific 11 latitude and longitude formats are shown in table 2.

TABLE 2 longitude and latitude Format Table

Serial number	Longitude and latitude key word
		1	lng＝&lat＝&
2	lng％3d％lat％3d％
		3	lat％22％3a％22％lng％22％3a％22％
4	-lat--lng.json
		5	lat＝&lon＝&
6	latitude％22％3a％22％longitude％22％3a％22％
		7	longitude＝&latitude＝&
8	slat＝&slon＝
		9	geoinfo＝&％2c
10	location＝&％2c
		11	？q＝xx,yy

TABLE 3 resolved URI data

The second step is that: S1-MME data resolution

Similar to the first step, the XDR information of the S1-MME needs to be collected and analyzed, and only the fields of ERAB _ ULTEID, ERAB _ DLTEID, BeginTime, MMEs1 apuld, and Eci used for association need to be analyzed and analyzed, where the ERAB _ ULTEID corresponds to GGSNDATATEID, ERAB _ DLTEID of the previous step and SGSNDATATEID of the previous step.

Example (c): one piece of S1-MME data is shown in table 4: (data corresponding to the aforementioned S1-U)

TABLE 4-S1-MME data

the third step: S1-U and S1-MME data association

The correlation method comprises the following steps:

1. GGSNDATATEID, SGSNDATATEID in S1-U is utilized to respectively correspond to ERAB _ ULTEID and ERAB _ DLTEID in S1-MME;

2, the S-MME is a control plane interface, the S1-U bit user plane interface, according to the call service flow, begintime in the S1-U should be later than begintime in the S1-MME, so that data meeting the condition 1 should also meet the condition that begintime in the S1-U is later than begintime in the S1-MME;

If the above conditions are satisfied, the information of the S1-U and the S1-MME can be matched, and the matching results of the S1-U and the S1-MME are output, as shown in Table 5.

TABLE 5-S1-U and S1-MME information matching Table

cellid	begintime	Mmes1apUEId	Latitude	Longitude
					137584897	2015-7-1516:16	50539622	31.46682739	104.7471008

the fourth step: associating with MRO data

The obtained information of Mmes1apueId, begintime and Eci is associated with Mmes1apueId, begintime and cellid in MRO (measurement report sample data file) data, the association method is a data field which corresponds to the cellid and MME UE S1AP ID and the reporting time of sampling points in begintime and MRO in the table is within 3 seconds before and after.

Remarking: (since the user update time set by the current cell MR report is 5120ms, the association time is set in three seconds before and after)

Example (c): one correlation result is shown in table 6.

TABLE 6 data associated with MRO data

The final output result is the corresponding level at a certain longitude and latitude, as shown in table 7.

TABLE 7-corresponding results of positioning results and RSRP

As shown in fig. 2, another embodiment of the present invention adds a step of calibration output, and uses a TA distance for calibration to obtain the precise longitude and latitude and RSRP of the user, which aims to select effective sampling points, and the specific calibration principle and flow are shown in fig. 3 and fig. 4.

Calibration output-selection of valid sampling points

Because the source of the partial longitude and latitude information is the base station positioning, the precision depends on the density of the base stations participating in the calculation and the distance from the base stations to the main cell, and the data part with poor precision needs to be removed. The specific principle and flow chart are shown in fig. 2 and 3.

The elimination method is to perform verification through a primary serving cell TA, as shown in fig. 3, due to the influence of the geographical environment on the propagation path, the base station cell signal received by the UE is not propagated straight in a general sense (the dotted line in fig. 3, especially in a dense urban area), and the TA (the distance from the UE to the base station reported by the MR, and the solid line in fig. 3) represents a true curved path. The distance difference S _ a (the dashed straight line in fig. 3) between the latitude and longitude of the UE and the latitude and longitude of the base station is S _ a < (S _ ta) compared with the distance S _ ta (the curve in fig. 3), and the point satisfying this condition is the valid sample point. The algorithm flow is shown in fig. 4, and the calibration algorithm process is to obtain and compare S _ a and S _ ta from the associated high-precision data, and further screen out effective sampling points.

Procedure for wireless network coverage assessment

As shown in fig. 4, a coverage map of a cell is drawn by the above network quality monitoring method based on signaling and MR data, so as to evaluate network coverage. Firstly, effective sampling points acquired by the positioning algorithm can be accurately positioned to a building level by combining a high-precision map, so that indoor and outdoor users can distinguish diseases and evaluate the signal quality.

Signal evaluation: the sampling points are combined with a high-precision map to perform rasterization analysis, if the positioning points are located on buildings such as commercial buildings, cells, factories and mines, the indoor users are determined, the positioned indoor coverage points are analyzed, and the whole network coverage depth can be evaluated; if the positioning point is positioned outside the building, the positioning point is an outdoor user, and the outdoor coverage can be evaluated in the same way.

And further performing network planning and verification on the basis of the wireless network coverage assessment, wherein the signal assessment result can extend the work of site planning guidance, planning and construction effect verification and the like, and a better effect is obtained.

While there has been described what are believed to be the preferred embodiments of the present invention, it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the principles of the invention, and it is intended to cover all such changes and modifications as fall within the true scope of the invention.

Claims

1. The network quality monitoring method based on the signaling and the MR data is characterized by comprising the following steps:

Step (1): collecting and analyzing GGSNDATATEID and SGSNDATATEID, BeginTime and URI information through an S1-U interface, and extracting longitude and latitude information according to a longitude and latitude format;

Step (2): collecting XDR information through an S1-MME interface, and associating the XDR information with cell information through ERAB _ ULTEID, ERAB _ DLTEID and BeginTime association information;

And (3): obtaining RSRP data of the MR acquisition point by correlating the cell information and the starting time with MRO data;

And (4): and comparing the distance difference S _ a between the longitude and latitude of the UE and the longitude and latitude of the base station with the distance S _ ta from the UE to the base station reported by the MR to screen out effective data, wherein the condition that S _ a < (S _ ta) is the effective data is met.

2. The method for monitoring network quality based on signaling and MR data according to claim 1, characterized by the addition of the steps of: and performing rasterization analysis by combining the high-precision map, and displaying the RSRP data on the high-precision map according to the positioning information.

3. The network coverage evaluation method based on the signaling and the MR data is characterized by comprising the following steps: the method for network quality monitoring based on signaling and MR data according to claim 2, wherein the coverage of the cell is mapped for network coverage evaluation.