CN105828365A - LTE cell overlapping coverage analysis method based on MR data - Google Patents

LTE cell overlapping coverage analysis method based on MR data Download PDF

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CN105828365A
CN105828365A CN201610378656.6A CN201610378656A CN105828365A CN 105828365 A CN105828365 A CN 105828365A CN 201610378656 A CN201610378656 A CN 201610378656A CN 105828365 A CN105828365 A CN 105828365A
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cell
coverage
overlapping
analysis
cells
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陈�峰
王伟
杨然
胡志勇
阳许军
王婕
郑继东
叶仕祥
肖伟明
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Wuhan Hong Xin Technological Service Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention provides an LTE cell overlapping coverage analysis method based on the MR data. The method comprises steps that MR data acquisition is carried out, and an LTE MR data file and a cell information table are acquired; cell overlapping coverage analysis is carried out, screening is carried out, overlapping adjacent regions after screening and main cells form overlapping coverage adjacent region pairs, weight of the overlapping coverage adjacent region pairs is calculated according to the overlapping adjacent region signal point number, after priority of the overlapping coverage cells is determined according to the sequence, screening is further carried out, coverage distance analysis on the cells after weight screening is carried out, and to-be-optimized high overlapping coverage cells are determined; multi-factor association analysis is carried out, including weak coverage association analysis, useful signal proportion analysis and user concentration association analysis. Through the method, problem cells can be more accurately positioned, more reasonable optimization advices can be proposed, and omnibearing inspection and problem investigation for the overlapping coverage cells can be carried out.

Description

LTE cell overlapping coverage analysis method based on MR data
Technical Field
The invention relates to the field of mobile communication, in particular to a method for analyzing LTE cell overlapping coverage based on MR data.
Background
The continuous development of communication technology brings great convenience to the high-speed transmission in the current data era, a TD-LTE (time division Long term evolution) network is a high-speed wireless communication technology with the transmission speed exceeding 100Mbps, the same and different frequency networking is adopted in the TD-LTE networking, and because the frequency resources are limited, the interference between cells is difficult to reduce through frequency optimization, so the interference risk under the same frequency condition is greatly increased. An ideal cellular network can make a cell at a lower level in an overlapping area on the premise of ensuring user mobility, but when the network structure is unreasonable, such as an area with small station distance and high station address, the overlapping coverage is difficult to control, and the influence on the network is large. The influence of the overlapping coverage on the SINR is mainly tested by performing field tests on different experimental areas. Experiment results show that the SINR (signal to interference plus noise ratio) counted in each region is substantially consistent with the change curve of the overlapping coverage (i.e., the more serious the region overlapping coverage is, the worse the SINR is), and the overall network performance is greatly influenced by the overlapping coverage of the region.
Therefore, how to effectively reduce the cell overlapping coverage becomes a topic of important attention in the industry.
Currently, the traditional method of combining frequency sweep and manual analysis is mainly adopted for analyzing the overlapping coverage of the LTE cell, and the following problems exist:
(1) the sweep frequency data or MR data needs to be manually analyzed one by one, the workload is large, and the efficiency is not high; LTEMR (measurement report) refers to data that a network device periodically reports to measure a wireless network, and the data can be used for network evaluation and optimization.
(2) The high-overlapping coverage cell is optimized by network optimization personnel through experience and intuition, and the accuracy depends on the experience of the network optimization personnel.
(3) The accuracy and authenticity of high overlap and interferer cells calculated by the network optimizers is low.
(4) The determination of the aggressor cell requires too much data to be easily determined accurately.
Disclosure of Invention
The invention aims to overcome the defects of the existing method and provides a method for analyzing LTE cell overlapping coverage by using MR data.
The technical scheme of the invention provides an LTE cell overlapping coverage analysis method based on MR data, which comprises the following steps,
step 1, MR data acquisition is carried out, and an LTEMR data file and a cell information table are obtained;
step 2, determining a high-overlapping coverage cell to be optimized, comprising the following substeps,
step 2.1, analyzing the cell overlapping coverage;
2.2, screening according to the overlapping coverage analysis result of the overlapping coverage cells of the whole network and a corresponding preset threshold; step 2.3, overlapping covering adjacent cell pairs are formed by the screened overlapping adjacent cells and the master cell respectively, the weights of the overlapping adjacent cell pairs are calculated according to the number of the overlapping adjacent cell signals, and finally the overlapping covering adjacent cell pairs are sequenced according to the weights, the priority of the overlapping covering cells is determined, and screening is carried out according to a preset weight threshold value;
step 2.4, performing coverage distance analysis on the cells after weight screening to determine high-overlap coverage cells to be optimized;
step 3, multi-factor association analysis, including the following 3 analysis,
weak coverage correlation analysis, including calculating the average level value of the main cell in the problem area, comparing the main coverage level value with a weak coverage threshold, and if the average level value is lower than the preset weak coverage threshold, considering that the cell has weak coverage in the overlapping coverage area and needs to strengthen the coverage;
useful signal ratio analysis, including useful signal ratio analysis of each adjacent cell, if the adjacent cell with more interference is manufactured, the adjacent cell is regarded as a key optimization object;
and (4) performing user concentration correlation analysis, including calculating the user concentrations of all the cells with high overlapping coverage respectively, and regarding the cells with high user concentration as needing to be optimized preferentially.
And, determining a corresponding remediation scheme according to the multi-factor correlation analysis result.
Furthermore, the MR signal occupancy analysis is as follows,
UsefUsigRate (a) ═ a cell MR total sampling point ÷ (a cell total sampling point + a cell as the total number of interference sampling points in the neighborhood)
Wherein, useful signal ratio analysis result of the cell a is UseUul SigRate (a).
The scheme has the following technical advantages:
(1) the algorithm is more optimal: different from the traditional cell overlapping coverage optimization idea, the method combines a weight algorithm and a wireless signal propagation model algorithm, can more accurately position the problem cell, and can provide more reasonable optimization suggestions;
(2) the analysis is more comprehensive: a multi-factor correlation analysis algorithm is introduced, the problem collection process is more comprehensive, and all-around inspection and problem troubleshooting can be performed on the overlapped coverage cells.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
The invention provides a method for analyzing LTE cell overlapping coverage by using MR data, which is characterized in that MR test data are input, signals are clustered and analyzed according to information of a main service cell and an adjacent cell reported by an MR, and the signals of the same cell can be converged under the cell according to MR sampling points ENodeBId and CI. Firstly, a set cell overlapping coverage analysis algorithm is used for automatically screening cells with high overlapping coverage, and then, aiming at the cells with high overlapping coverage, the multi-factor correlation analysis algorithm is used for optimizing. And analyzing the optimization idea of the cell with higher cell overlapping coverage by adopting multi-factor correlation. The proposal carries out multi-factor correlation comprehensive analysis on the high overlapping coverage cell, wherein the analysis comprises weight analysis, coverage distance analysis, weak coverage analysis, useful signal ratio analysis, user concentration analysis and the like of the overlapping coverage cell. The specific idea of the multi-factor association analysis is as follows:
(1) weight association analysis: carrying out weight analysis on the overlapped coverage cells entering the envelope band according to sampling number and level factors, and carrying out priority ranking on the overlapped coverage cells according to the weight; overlapping adjacent cells entering the envelope band and the main cell can respectively form overlapping covering adjacent cell pairs one by one, the weights of the overlapping adjacent cell pairs are calculated according to the number of the signal points of the overlapping adjacent cells, and finally the overlapping covering adjacent cell pairs are sequenced according to the weights, so that the interference priority of the adjacent cells is determined.
(2) And (3) coverage distance correlation analysis: evaluating and analyzing the coverage distance of the overlapped coverage cells entering the envelope band, and finding out the cells with abnormal coverage distance;
(3) and (3) weak coverage correlation analysis: level value evaluation and analysis are carried out on the main cell and the cell entering the envelope band, the level is compared with an actual propagation model, and the cell with weak coverage level and abnormal coverage level is found out;
(4) interference source index analysis: analyzing the number of interference signals originally generated by the main service cell as interference;
(5) useful signal ratio analysis: analyzing whether the main service cell provides services or generates much interference;
(6) and (3) user concentration correlation analysis: and analyzing the user concentration of the high-overlapping coverage cell, and determining the optimized priority ranking of the high-overlapping coverage cell according to the user concentration.
The technical scheme of the invention is explained in detail in the following by combining the drawings and the embodiment.
According to the embodiment of the invention, the high-overlapping coverage cell is analyzed according to the MR data, and the multi-factor correlation analysis is carried out on the high-overlapping coverage cell, so that a reasonable high-overlapping coverage cell remediation scheme is finally output. The analysis flow of the high-overlapping coverage cell is shown in the figure.
1. MR data acquisition
The information to be imported in the data import process includes:
(1) an LTEMR data file; typical MR data includes: reportTime, lteScData, Longitude, Latitude, LteScSinrUL, MmeUeS1apId, MmeCode, MmeGroupID, LteNc1, LteNc2, LteNc3, LteNc4, LteNc5, LteNc6, and the like.
(2) The cell information table, generally includes: ENodeBId, CI, longitude, latitude, antenna hangup, azimuth, cell type, frequency point, PCI, etc.
2. Determining high overlapping coverage cells
(1) Cell overlap coverage analysis
Cell overlap coverage index definition: in the case of periodic measurement, a primary cell is setFor the serving cell s, the sum of the number of sample points of which all the neighbor cells of the main cell appear in the measurement report of the serving cell s and the RSRP received signal code power strength difference is greater than a preset threshold (the threshold is an adjustable parameter, such as-6 dB), and the total number X of neighbor cells of all the n neighbor cells measured by the measurement report MR of the serving cellallThe ratio of (a) to (b). RSRP (reference signal received power) is one of the key parameters that may represent the wireless signal strength in an LTE network and the physical layer measurement requirements.
Chinese name of related statistical data:
RSRP of a primary carrier of an LTE serving cell, the RSRP representing received signal code power
RSRP of main carrier of LTE defined adjacent region relation cell and cell without defined adjacent region relation, wherein RSRP represents received signal code power
Index to statistical data Chinese mapping algorithm:
wherein, Xsi(6dB)For the number of signal points, X, of the neighbor cell i appearing in the measurement report of the serving cell s and having an RSRP difference greater than a preset threshold (e.g., -6dB)allThe total number of sample points of all primary cells measured for the MR of the serving cell s.
In specific implementation, the sum of the number of sample points when all the neighboring cells of the main cell appear in the measurement report of the serving cell s and the RSRP received signal code power intensity difference is larger than the preset threshold (-6dB) can be obtained by adopting the following formula,
Σ i = 1 n Σ j = 1 m ( MR i * L T E N c R s r p * X j - MR i * L T E S c R s r p * Y i ) > ( - 6 d b m ) )
wherein (MR)i*LTENcRsrp*Xj-MRi*LTEScRsrp*Yi) > (-6dbm) represents the sample point of the main server, wherein the difference between the measured RSRP of the adjacent region j and the RSRP of the local region is larger than-6 dBiIndicating a primary serving cell, LTENcRsrp indicating a neighbor level, XjIndicating the sequence number of the adjacent sampling point measured by the main serviceiSample point sequence number, X, representing the main garmentjThe value is 0 to the number of actually measured adjacent regions, YiThe number of main service samples from 0 to the actual samples represents the affiliated relationship; n represents the number of sampling points of the main service, and m represents the number of sampling points of the adjacent region measured by the main service.
(2) High overlap coverage cell screening
And screening the overlapping coverage analysis results of the overlapping coverage cells of the whole network according to a corresponding preset threshold, and screening the cells with the too high overlapping coverage to prepare for subsequent analysis.
(3) Weight calculation for overlapping coverage cells
And (3) according to the screening result in the step (2), respectively forming overlapping covering adjacent cell pairs by the overlapping adjacent cells entering the envelope band and the main cell one by one, calculating the weight of the overlapping adjacent cell pairs according to the number of the signal points of the overlapping adjacent cells, and finally sequencing the overlapping covering adjacent cell pairs according to the weight, thereby determining the priority of the overlapping covering cells according to the sequencing result and screening according to a preset weight threshold value.
The weight calculation method is that for a single adjacent cell A, the weight is the number of the overlapping signals of the adjacent cell A/the number of the overlapping signals of all the adjacent cells.
The following case analysis was used:
the basic properties of the analyzed overlapping coverage cells are as follows:
name of cell eNodeB-ID CI Overlapping coverage Signal assembly Overlapping neighbors Grid assembly
Tong Yang countryside government 334446 5 66.72％ 119798 13 157
The information of the overlapping coverage adjacent cell pair is as follows:
neighborhood names eNodeB-ID CI Overlapping signals Valid signal Weight of Distance (rice)
Tong Yang Xiang government LF-2 334446 2 51702 54083 46.82％ 0.22
Tongyang industrial garden 880294 6 4760 16287 14.1％ 1515.71
Tongyang industrial park LF-3 880294 3 4093 7029 6.08％ 1515.71
Yinping DXLF-3 880251 3 7925 16780 14.52％ 473.1
Tong Yang goat LF-3 879740 3 394 733 0.63％ 2288.28
Xinhe Panhu LF-1 880366 1 790 1687 1.46％ 4491.07
Tongyang primary middle school 334445 2 411 1443 1.25％ 914.61
Tong yang Xuzhuang LF _6 880538 6 443 2841 2.46％ 3086.92
Tong yang Xuzhuang LF-3 880538 3 207 315 0.27％ 3086.92
Tongyang rear bin LF _6 880295 6 270 1501 1.3％ 3898.71
Yinping DXLF-2 880251 2 5297 8697 7.53％ 473.1
Tong yang exit north 898631 3 85 181 0.16％ 1818
Tongyanping LF-2 880622 2 2672 3933 3.4％ 2269.92
As shown in the above table, weight one is the weight calculation result, and CI represents CellID, i.e., cell identity. Through the weight analysis, the cells with the following weight of more than 10% are analyzed, and thus, the analysis range of the problem is further reduced.
(4) Coverage distance correlation analysis
And analyzing the coverage distance of the cell after weight screening, respectively calculating the distance between the main service cell and the overlapping region of the overlapping adjacent cell pair and the distance between the main service cell and the overlapping region of the adjacent cell, and the average level value of the main service cell in the problem region and the average level value of the adjacent cell in the problem region, and comparing the level values with the theoretical level value calculated by the propagation model, so as to judge whether the coverage from the main cell or the adjacent cell to the overlapping coverage region is normal, for example, if the average level of the signals of the overlapping adjacent cell is-92, the average level calculated by the propagation model is-91, and the difference between the two level values is within +/-5 dbm, the coverage of the adjacent cell is considered to be normal, otherwise, the coverage is. The average level values of the main serving cell in the problem area and the neighboring cells in the problem area refer to the average level of the neighboring cell overlapping signal and the average level of the overlapping point of the main server and the current neighboring cell.
As described in the above example, in the cell with the higher weight, the following cells are found to be far away from the primary serving cell:
neighborhood names eNodeB-ID CI Overlapping signals Valid signal Weight of Distance (rice)
Tongyang industrial garden 880294 6 4760 16287 14.1％ 1515.71
Is the object of emphasis optimization.
3. Multi-factor correlation analysis
(1) Weak coverage correlation analysis
Calculating the average level value of the main coverage cell (namely, the main service cell and the main cell) in the problem area, comparing the main coverage level value with the weak coverage threshold, and if the average level value is lower than the preset weak coverage threshold, considering that the cell has a weak coverage phenomenon in the overlapping coverage area and needs to strengthen the coverage.
As described in the previous example, the average total signal level of the main coverage cell is-92.28 dbm, and no weak coverage phenomenon exists.
Name of cell eNodeB-ID CI Overlapping coverage Signal assembly Average level value
Tong Yang countryside government 334446 5 66.72％ 119798 -92.28
(2) Ratio of useful signal analysis
The MR useful signal ratio analysis algorithm is as follows:
UsefUsigRate (a) ═ a cell MR total sampling point ÷ (a cell total sampling point + a cell as the total number of interference sampling points in the neighborhood)
Wherein, useful signal ratio analysis result of the cell a is UseUul SigRate (a).
Through the ratio analysis of the useful signals of the adjacent regions, whether the adjacent regions have more useful signals or more interference can be known, and if the adjacent regions have more interference, the adjacent regions are the objects of key optimization. In specific implementation, it may be determined whether the useful signal percentage is lower than the threshold preset value by 50%, and if so, the signal is an adjacent cell with more interference signals.
(3) User concentration correlation analysis
And respectively calculating the user concentration of each cell with high overlapping coverage, wherein the cells with higher user concentration are key guarantee objects and need to be optimized preferentially. The user concentration ratio reflects the total user number measured in the current cell, and can be obtained through MR data statistics in specific implementation. In specific implementation, it may be determined whether the sampling of the cell is greater than the average number of the whole network or a preset corresponding threshold, and if so, the cell with a higher user concentration is determined.
4. Output remediation scheme
The effective signal is the interference opposite to the interference signal, the overlapped signal is the interference signal considered by the invention, the overlapped signal is high, and the useful signal is low. Through the various correlation analyses, a cell which has problems and can be optimized is found out finally, optimization suggestions are proposed through the problems existing in the cell, the overlapping coverage is optimized through controlling the coverage, and under the conditions that the base station and the antenna feed system work normally and the parameter setting is reasonable, the following optimization measures can be output basically:
(1) and adjusting the downward inclination angle of the antenna.
In the coverage distance correlation analysis, the suggestion is given to the neighboring cell when the coverage distance of the cell is too far, which causes the overlapping signal of the neighboring cell to be too much.
(2) And adjusting the azimuth angle of the antenna.
This adjustment recommendation is typically used in weak coverage association analysis when the primary cell coverage area deviates from the intended coverage area.
(3) And adjusting the power of the RS.
In the weak coverage and coverage distance correlation analysis, the adjustment suggestion is usually given when the main service or the neighboring cell signal is too weak or too strong.
(4) Raise or lower the antenna hangheight.
In the weak coverage and coverage distance correlation analysis, the adjustment suggestion is usually given when the main service or the neighboring cell signal is too weak or too strong.
(5) And (5) station relocation.
In the weak coverage and coverage distance correlation analysis, the adjustment suggestion is usually given when the main service or the neighboring cell signal is too weak or too strong.
(6) And newly adding a station or an RRU.
The above embodiment flow descriptions are only for the purpose of clearly illustrating the basic method and apparatus of the present invention, but the present invention is not limited to the above embodiments; any simple modification, equivalent change and modification made according to the technical essence of the present invention are within the scope of the technical solution of the present invention.

Claims (3)

1. An LTE cell overlapping coverage analysis method based on MR data is characterized in that: comprises the following steps of (a) carrying out,
step 1, MR data acquisition is carried out, and an LTEMR data file and a cell information table are obtained;
step 2, determining a high-overlapping coverage cell to be optimized, comprising the following substeps,
step 2.1, analyzing the cell overlapping coverage;
2.2, screening according to the overlapping coverage analysis result of the overlapping coverage cells of the whole network and a corresponding preset threshold; step 2.3, overlapping covering adjacent cell pairs are formed by the screened overlapping adjacent cells and the master cell respectively, the weights of the overlapping adjacent cell pairs are calculated according to the number of the overlapping adjacent cell signals, and finally the overlapping covering adjacent cell pairs are sequenced according to the weights, the priority of the overlapping covering cells is determined, and screening is carried out according to a preset weight threshold value;
step 2.4, performing coverage distance analysis on the cells after weight screening to determine high-overlap coverage cells to be optimized;
step 3, multi-factor association analysis, including the following 3 analysis,
weak coverage correlation analysis, including calculating the average level value of the main cell in the problem area, comparing the main coverage level value with a weak coverage threshold, and if the average level value is lower than the preset weak coverage threshold, considering that the cell has weak coverage in the overlapping coverage area and needs to strengthen the coverage;
useful signal ratio analysis, including useful signal ratio analysis of each adjacent cell, if the adjacent cell with more interference is manufactured, the adjacent cell is regarded as a key optimization object;
and (4) performing user concentration correlation analysis, including calculating the user concentrations of all the cells with high overlapping coverage respectively, and regarding the cells with high user concentration as needing to be optimized preferentially.
2. The method of claim 1 for analyzing LTE cell overlap coverage based on MR data, wherein: determining a corresponding treatment scheme according to the multi-factor correlation analysis result.
3. The method for LTE cell overlap coverage analysis based on MR data according to claim 1 or 2, characterized by: the MR useful signal ratio is analyzed as follows,
useful SigRate (a) = a cell MR total sampling point ÷ (a cell total sampling point + a cell interference sampling point total when being adjacent)
Wherein,UsefulSigRate(a) And the result of the analysis of the ratio of the useful signals of the a cell.
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Application publication date: 20160803