CN1728864A - Method for obtaining sector coverage by using tiled measured data - Google Patents
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Abstract
The method can reduce deviation for predicting field intensity of unknown point in sector. The sector includes steps: partitioning area covered by antenna into mXn grids; data of field intensity measured at geographical position of sector are as grid field intensities of grids; counting grid number, where there are grid field intensities, in each sector in m pieces of sector; defining the sector containing counted grid number larger than prearranged value as radial predictable sector, and the sector containing counted grid number smaller than prearranged value as radial unpredictable sector; using Okumura/Hata model, interpolation of least square method, and tiled measured data of field intensity predicts grid field intensities of grids in radial predictable sectors; using selected grid field intensities of grids from adjacent sector and grids adjacent to this grid etc. predicts grid field intensities of grids, where there are no measured grid field intensities, in radial unpredictable sectors.
Description
Technical field
The present invention relates to the mobile communication cells soverlay technique, relate to or rather obtain the method that the sub-district covers with sub-district measured data carvel built.
Background technology
Recent two decades comes, and the land wireless mobile communications has been obtained swift and violent development.
Communicate by letter between cellphone subscriber and the base station is that mode with electromagnetic wave propagation is carried out informational linkage.In order to guarantee that the user can both communicate with mobile phone anywhere, must guarantee that the field intensity of the every bit between cellphone subscriber and the base station is all greater than a lower limit.
In the real network optimizing process, drive test is indispensable, covers for effective sub-district by the field intensity data tiling of drive test with actual measurement, thereby substitutes the coverage condition that traditional prediction reflects network.But because factors such as ground, landform and costs, driver test system can not obtain the field intensity data of every bit in the sub-district, on the contrary, can only obtain the part centrifugal pump.For the field intensity of describing the sub-district covers, must carry out field intensity prediction to unknown point according to measured data.So the mobile radio communication wireless signal field prediction has become the focus of domestic and international research.
Mobile communication network planning is optimized the sub-district coverage condition of need of work reflection real network, promptly needs to utilize wireless signal propagation model to dope the coverage condition of sub-district wireless signal field in the mobile communications network.But because wireless signal propagation model is inaccurate, thereby cause the field intensity that dopes can not the actual coverage condition of fine reflection, or cause the invalid of each parameter factors in the forecasting process owing to obtaining effective geodata.
Both at home and abroad to the research of mobile radio communication wireless signal field prediction, i.e. the research that covers at the sub-district mainly contains following two class methods at present: the one, and the propagation model prediction sub-district that depends on three-dimensional or accurate three-dimensional digital map covers; The 2nd, utilize measured data and obtain the sub-district to cover by measured data is tiled.
The condition that traditional propagation model Forecasting Methodology needs is relatively harsher, not only require propagation model to meet the current network situation, and owing in forecasting process, need detailed geodata, comprise landform, landforms, building position etc., also need concrete landform tendency information, depth of building information etc., even the material information of each obstacle, particularly all changing all the time, so be difficult to obtain very realistic predicting the outcome owing to actual geographical environment.At present relatively more commonly used is the method for propagation model correction up, and its shortcoming is owing to require a large amount of measured datas is analyzed, fits, added up, thereby the data volume that needs is big, amount of calculation big, need supporting geodata, effectual time is little.
The sub-district covering method that at present also has some to utilize measured data to tile, common practices are directly to utilize the field intensity value of known point to estimate the field intensity value of the unknown point of closing on known point.Specifically comprise: at first measured data is deposited in the database, as the field intensity of known point; In database, find out the field intensity value of several the nearest known points of strong unknown point of leaving the theatre then; Obtain the field intensity of this unknown point again according to certain method.This certain method is normally carried out respective attenuation to the field intensity of known point, ask its mean value again, and carry out iteration according to the method, promptly utilize the data of the unknown point of this prediction to predict near the field intensity of unknown point it again, carry out so repeatedly, the field intensity that obtains the sub-district at last covers.The shortcoming of these class methods is comparison subjectivities, does not consider the characteristics of electromagnetic wave propagation, so bigger to the prediction deviation of unknown point field intensity.When the measured data skewness, then there is unpredictable area in the sub-district, promptly predicted value is extremely inaccurate.Because this method has adopted simple iterative method, promptly directly utilize the prediction data of unknown point to predict near unknown point field intensity once more, and cause deviation increasing simultaneously.
Summary of the invention
The objective of the invention is to design a kind of method of utilizing the measured data tiling to obtain the sub-district covering, to overcome the existing sub-district covering method of utilizing measured data the to tile shortcoming bigger to the prediction deviation of unknown point field intensity.
In order to realize the foregoing invention purpose, the present invention adopts following technical scheme.
A kind of method of utilizing the measured data tiling to obtain the sub-district covering is characterized in that comprising:
A. in antenna coverage areas, be the center of circle, be radius increment n the plane concentric circles that draw as step-length and with this step-length l the geographic accuracy l of actual measurement with the antenna position, the m bar radius of drawing from this center of circle and n plane concentric circles intersect, and are partitioned into m * n grid;
B. the field intensity data map that will survey on the geographical position, sub-district is to the grid field intensity of described grid as grid;
C. n plane concentric circles of two adjacent radius cuttings forms m sector in the steps A, add up the meshes number that has above-mentioned grid field intensity in each sector, the sector that number is surpassed preset value is decided to be radially measurable sector and D execution set by step, and the sector that number is lower than preset value is decided to be radially unpredictable sector and E execution set by step;
D. utilize the interpolation method of Okumura/Hata model and least square method,, predict in the radially measurable sector grid field intensity of the grid of the field intensity data that each is not mapped to actual measurement with the field intensity data tiling of actual measurement;
E. the grid field intensity of adjacent mesh and the grid field intensity of this sector adjacent mesh in utilization and the radially unpredictable sector adjacent sectors are predicted the grid field intensity that does not have the grid of grid field intensity in the radially unpredictable sector.
Among the described step B, the described field intensity data map that will survey on the geographical position, sub-district comprises to the grid field intensity of grid as grid:
When B1. an actual measurement field intensity is only arranged, this actual measurement field intensity is mapped to the grid field intensity of this grid as this grid in the geographical position corresponding with grid;
When B2. in the geographical position corresponding, not surveying field intensity, the grid field intensity of this grid is designated as minus infinity with grid;
When B3. more than one actual measurement field intensity is arranged in the geographical position corresponding with grid, these actual measurement field intensity are averaged, and this mean value is mapped to the grid field intensity of this grid as this grid;
B4. near one antenna actual measurement field intensity is mapped near the grid the antenna, the grid field intensity that equates as these grids.
Described step D further comprises:
D1. arbitrary grid is designated as Arcgrid
(i, j), 0≤i＜n, 0≤j＜m is with grid Arcgrid
(i, j)The center is independent variable to the described center of circle apart from i * l+ , this grid Arcgrid
(i, j)Grid field intensity E
A (i, j)Be dependent variable, according to landform characteristic use 0kumura/Hata model construction function curve;
D2. with the field intensity data of function curve that makes up and the grid that is shone upon and this grid element center to the described center of circle apart from match, carry out interpolation by least square method, prediction obtains in the described radially measurable sector grid field intensity of the grid of each field intensity data that are not mapped to actual measurement.
Before the described step e of execution, determine earlier in each radially unpredictable sector whether maximum the and unique sector of the meshes number that has the grid field intensity is arranged, be then direct execution in step E; Otherwise to there being the radially unpredictable sector that equates maximum number, further determine the meshes number sum that radially there is the grid field intensity in the direct neighbor sector of unpredictable sector in these respectively, to maximum and unique radially unpredictable sector execution in step E with number; Otherwise optional sector from have the radially unpredictable sector that equates maximum and number, execution in step E.
Described step e further comprises:
E1. find two sectors that have described grid field intensity adjacent and adjacent with grid to be predicted with radially unpredictable sector to be predicted;
E2. with the grid field intensity of two adjacent in above-mentioned two adjacent sectors grids with grid to be predicted respectively as this one of grid field intensity for the treatment of pre-predicted grid with it two;
E3. find and same sector, radially unpredictable sector to be predicted, adjacent with grid to be predicted and have two grids of grid field intensity;
E4. the grid field intensity of above-mentioned two adjacent mesh is taken advantage of respectively after the decay factor as three with it four of the grid field intensity of grid to be predicted;
E5. to one of above-mentioned grid field intensity, two, three, four ask average, with the grid field intensity of mean value as grid to be predicted in the radially unpredictable sector to be predicted.
In the described step e 1, when there is the grid field intensity in the grid the most adjacent and adjacent with grid to be predicted with radially unpredictable sector to be predicted, with this adjacent sectors as described two sectors; When there is not the grid field intensity in the grid adjacent with grid to be predicted in the sector the most adjacent with radially unpredictable sector to be predicted, inquire about the adjacent sector of this adjacent sectors in regular turn, until finding the grid adjacent to have the sector of grid field intensity, as described two sectors with grid to be predicted.
In the described step e 2, two grids that grid described and to be predicted is adjacent, the distance between its grid element center and the described center of circle equates with distance between the described center of circle with described grid to be predicted.
In the described step e 3, when there are the grid field intensity in and its grid the most adjacent with grid to be predicted, with the grid field intensity of two adjacent mesh respectively as one of described grid field intensity with it two; When there is not the grid field intensity in the grid the most adjacent with grid to be predicted, inquire about the adjacent grid of this adjacent mesh in regular turn, until finding the grid that has the grid field intensity, with its grid field intensity as the grid field intensity that participates in the step e 4 calculating.
In the described step e 4, two adjacent mesh are adjusted described decay factor according to the distance in their described centers of circle of distance.
Key technology of the present invention comprises: the division methods of grid in the cell coverage area, and will survey the rule of field intensity data map in the grid; The Forecasting Methodology of grid field intensity in the radially measurable sector; The Forecasting Methodology of grid field intensity in the radially unpredictable sector.
Method of the present invention, the zone radius and the concentric circles that utilize the sub-district to cover are divided into plurality of grids with microzonation, will survey the field intensity data and be mapped in the grid according to four kinds of rules; In radially measurable sector, utilize the grid field intensity of grid in the interpolation method prediction sector of Okumura/Hata model and least square method; In radially unpredictable sector, utilize the grid field intensity of grid adjacent, that have measured data or prediction data in the grid field intensity of grid adjacent, that have measured data or prediction data in the adjacent sector and the same sector that the grid field intensity of unknown grid is predicted.
Because the present invention is many-sided deviation accumulation of having considered the characteristics of electromagnetic wave propagation and having avoided iterative method to bring in the process of measured data tiling, division, the measured data that mainly shows the arc grid is mapped to the tiling of measured data and prediction data in the tiling of measured data in grid, the radially measurable sector and the radially unpredictable sector, overcome the inaccurate problem of existing measured data tiling method prediction data.Owing to utilize the measured data tiling to obtain the sub-district covering, the sub-district of having avoided causing because geodata is inaccurate or propagation model is inaccurate covers the big problem of deviation simultaneously.
Method described in the invention, will be very under the mass data situation near the sub-district coverage condition of real network.
Description of drawings
Fig. 1 is that arc grid of the present invention is divided schematic diagram;
Fig. 2 is the selection FB(flow block) of the present invention to field intensity tiling order in the radially unpredictable sets of sectors;
Fig. 3 is the FB(flow block) of step 204 among Fig. 2, predicts the radially grid field intensity of unpredictable sector by radially measurable sector.
Embodiment
The operating frequency of mobile communication system is generally all than higher, thereby the electromagnetic wave propagation wavelength is compared just much little with the size of most of barriers, this moment, electromagnetic wave propagation can be described with geometric optics, promptly think electromagnetic wave along straightline propagation, the electromagnetic wave in far-field region can be considered the part plan ripple.
So the present invention is according to this feature of electromagnetic wave propagation, based on existing Okumura/Hata forecast model, and provide a series of corrections according to suburb, open area, antenna height and landform etc., calculate propagation curve, thereby the field intensity of some unknown point in the sub-district is predicted.
Antenna is outside launching electromagnetic wave at a certain angle, and with the outer launching electromagnetic wave of 360 degree angles, directional antenna is outside launching electromagnetic wave at a certain angle then as omnidirectional antenna, an angle of 90 degrees for example, 120 degree angles or the like.Its radial propagation path is maximum to the contribution of the field intensity in the overlay area, in actual geographical environment, since landform, the influence of building, and cause measured data to be offset.So we are predicting field intensity in the radial direction, realize the radially tiling of field intensity data, and then utilize the field intensity of point of proximity to realize the field intensity data tiling of overlay area.
Referring to Fig. 1, be the division schematic diagram of arc grid.Directional antenna is with the outer launching electromagnetic wave of 120 degree angles.
With antenna position (as antenna tower or corresponding building) is center of circle O, is that radius r can make up a flat circle with its largest coverage distance.The electromagnetic wave path that antenna penetrates then is all radiuses of this circle.
The geographic accuracy of setting actual measurement simultaneously is l (unit is rice).Be the center of circle with O then, be the radius increment with step-length l, some concentric circless that draw, concentrically ringed number can be labeled as n, and m=rmodl+1 represents wherein any concentric circles with i.And, draw m bar radius r from center of circle O according to the size of measured data amount, and intersect with m concentric circles, the concentric circles of n in the antenna coverage areas is divided into m the sector Sect that deflection is different
j(0≤j＜m), represent wherein any sector with j, these sectors and concentric circles have constituted m * n arc grid, and we use symbol Arcgrid
(i, j)(0≤i＜n, 0≤j＜m) represent wherein any arc grid, as shown in Figure 1.
Then, measured data need be imported in the arc grid, be about to measured data and be mapped in the arc grid of being divided.Its longitude, latitude are generally used in the geographical position of measured data, and (L, M) expression is so can be E with actual measurement field intensity data markers
P (L, M), and with arc grid Arcgrid
(i, j)In the grid field intensity be labeled as E
A (i, j)To survey field intensity E
P (L, M)Be mapped to grid field intensity E
A (i, j)The time, being subjected to the influence of measured precision, following four kinds of mapping situations can appear:
1. at arc grid Arcgrid
(i, j)The geographical position in, have and only have an actual measurement field intensity E
P (L, M), then actual measurement field intensity data can be put in this grid grid field intensity, promptly as this grid
2. (i does not survey field intensity in geographical position j), then its grid field intensity is a minus infinity, E at arc grid Arcgrid
A (i, j)=-∞;
3. at arc grid Arcgrid
(i, j)The geographical position in k actual measurement field intensity data (generally appearing in antenna arc grid far away) are arranged, then with k mean value of surveying the field intensity data as this grid field intensity,
4. in the nearer grid of antenna, if the precision of actual measurement is not high, then an actual measurement field intensity may occur in the geographical position of a plurality of arc grids such as y arc grid, promptly equates to be an actual measurement field intensity E in the grid field intensity from y nearer arc grid of antenna
P (L, M),
Determine radially measurable sector and radially unpredictable sector then, carry out field intensity prediction more respectively.
At sector Sect
j(n the grid Arcgrid that 0≤j＜m) forms
(0, j), Arcgrid
(1, j)Arcgrid
(n-1, j)In, with grid field intensity E in n the grid
A (i, j)The arc grid number order of ≠-∞ is labeled as x
jIf, x
j〉=W (W is a lower limit of setting according to the size of measured data amount), then sector Sect
jIt is a radially measurable sector; If x
j＜W, then sector Sect
jIt is a radially unpredictable sector.
For radially measurable sector, (i, j) distance to center of circle o is an independent variable, this Arcgrid (i, grid field intensity E j) with arc grid Arcgrid
A (i, j)Be dependent variable, constructor curve y=f (x), the tiling of measured data is radially changed into the interpolation of curvilinear function or is referred to as approaching of curvilinear function, thereby the interpolation problem of two dimensional surface has been changed into the interpolation of one dimension function, thereby increased the accuracy of interpolation greatly.
In the function curve y=f (x) that makes up, the particularly key of determining to seem of the value of x and function f (x).Grid Arcgrid (i, j) can think this grid Arcgrid (i to the distance of center of circle o, j) center is to the distance of center of circle o, be Arcgrid (i, j) radius of arc grid is i * l+ , (n-1, j), grid element center can be approximately equal to radius of a circle r to the distance of center of circle o for grid Arcgrid.
For function f (x), adopt the classical Okumura/Hata model that is used for field intensity prediction.The Okumura/Hata model is when making field intensity prediction, and model changes according to the landform in the cell coverage area to be adjusted, with landform branch be as the criterion shape and irregular terrain profiles two big classes smoothly.Model needs to carry out following hypothesis in use: handle as the propagation loss between two omnidirectional antennas; Handle as level and smooth landform of standard rather than irregular terrain profiles; As standard, other areas adopt updating formulas that it is revised with the propagation loss formula of city proper.
When with the propagation loss formula of city proper as standard, when other areas adopted updating formulas to revise, then its propagation loss empirical equation was:
L
P＝A+BlogRdB (1)
(1) expression of A is in:
A＝69.55+26.16logf
c-13.82logh
b-α(h
m)+μ
In the following formula, f
cBe calculated rate (MHz of unit); h
bEffective depth (unit rice) for antenna for base station; A (h
m) be the mobile portable antennas height correction factor, wherein h
mBe in mobile portable antennas height (unit rice); μ is a correction factor.
(1) computing formula of B value is in:
B＝44.9-6.55logh
b+λ
H in the formula
bBe the effective depth (unit rice) of antenna for base station, λ is a correction factor.
(1) R is propagation distance (kilometer) in.
The correction propagation loss in suburb is: L
Ps=L
p-KmrdB (2)
L wherein
PResult of calculation for (1) formula; Kmr=2{log (f
c/ 28) }
2+ 5.4.
Open area is proofreaied and correct propagation loss: L
PQ=L
P-Q
0DB (3)
L wherein
PResult of calculation for (1) formula; Q
0=4.78 (logf
c)
2-18.33logf
c+ 40.94dB.
The present invention adopts the interpolation method of least square method, is about to function E=S (x) and the grid field intensity data of being shone upon and grid element center the distance { (l to center of circle o
(i, j), E
(i, j), i=0,1 ... m; J=0,1 ... the n} match is by asking the minimum value of error sum of squares, the unknown point field intensity that can obtain predicting.Here S (x) is the propagation loss empirical equation of Okumura/Hata model; l
(i, j)For grid Arcgrid (i, j) to the distance of center of circle o, E
(i, j)Be grid Arcgrid (i, grid field intensity j).Foregoing description illustrated in radially measurable sector, utilizes the grid field intensity of each arc grid in the interpolation method prediction sector of Okumura/Hata model and least square method, realizes the tiling of radially measurable sector field intensity measured data.
For the tiling of radially unpredictable sector field intensity measured data, promptly need from a plurality of radially unpredictable sectors, successively the tiling of field intensity measured data to be done in each radially unpredictable sector earlier by the order of selecting.The process of selecting sequence and the process that field intensity measured data tiling is done in selected radially unpredictable sector is shown in respectively in accompanying drawing 2 and the accompanying drawing 3.
Referring to Fig. 2, select to carry out the order of the radially unpredictable sector of field intensity measured data tiling, be not equal to infinitely-great number according to the grid field intensity of the arc grid that is comprised in the radially unpredictable sector and carry out (promptly having the meshes number of grid field intensity).
Step 202 is as x
c=x
d, according to E in this two sectors adjacent sectors separately
A (i, j)The number of ≠-∞ grid is judged (if adjacent sectors is radially measurable sector or the radially unpredictable sector of passing through the measured data tiling, then E
A (i, j)The number of ≠-∞ is maximum n), this step then will be obtained these two sectors x of adjacent sectors separately earlier
jSum is therefrom chosen maximum, promptly carries out H
2=max (x
C-1+ x
C+1, x
D-1+ x
D+1), if maximum and unique then this sector is designated as Sect is arranged
h Change step 204 and carry out, if, promptly have the maximum that equates, x though maximum is arranged is not unique
C-1+ x
C+1=x
D-1+ x
D+1=H
2, then transfer execution in step 203 to;
Step 203, optional sector is designated as Sect with this sector from these two sectors
h
Step 204 is to the radially unpredictable sector Sect that chooses in the above-mentioned steps
hCarry out the grid field intensity prediction, predict that specifically flow process as shown in Figure 3.
Above-mentioned steps is carried out continuously until the grid field intensity prediction has all been carried out in all radially unpredictable sectors.
Referring to Fig. 3, prediction sector Sect
hThe n that is comprised grid Arcgrid
(0, h), Arcgrid
(1, h)Arcgrid
(n-1, h)Middle E
A (i, j)The grid field intensity of=-∞ (grid that does not promptly have the grid field intensity).
As shown in fig. 1, with grid Arcgrid
(i, j)Eight adjacent grids are respectively: the adjacent grid Arcgrid of same sector
(i-1, j)And Arcgrid
(i+1, j), the adjacent grid Arcgrid of adjacent sectors
(i-1, j-1), Arcgrid
(i, j-1), Arcgrid
(i+1, j-1), Arcgrid
(i-1, j+1), Arcgrid
(i, j+1), Arcgrid
(i+1, j+1)
There are two big class situations in adjacent sectors:
A. adjacent sectors is radially measurable sector, and then the grid field intensity of all grids all exists in the sector, or the field intensity data for surveying, or is through the prediction data after radially tiling;
B. adjacent sectors also is radially unpredictable sector, and then the grid field intensity in the adjacent sectors (refers to Arcgrid
(i-1, j-1), Arcgrid
(i, j-1), Arcgrid
(i+1, j-1), Arcgrid
(i-1, j+1), Arcgrid
(i, j+1), Arcgrid
(i+1, j+1)(refer to Arcgrid with the grid field intensity that is in the adjacent mesh of same sector with grid to be predicted
(i-1, j), Arcgrid
(i+1, j)) may there be three kinds of situations again.With grid Arcgrid
(i-1, j)Be example: its grid field intensity E
A (i-1, j)Be measured data; E
A (i-1, j)It is a prediction field intensity; E
A (i-1, j)Promptly there is not measured data in=-∞, and not prediction.
So we adopt flow process prediction Arcgrid among the figure
(i, j)Field intensity.
Step 301 need to suppose predicted grid Arcgrid
(i, j)Field intensity, need determine at first whether the grid adjacent with grid to be measured in two direct adjacent sectors (adjacent sectors) of its sector, place exists actual measurement field intensity or prediction field intensity (having put into the grid field intensity in the grid), be execution in step 303 then, otherwise execution in step 302;
If step 302 is grid Arcgrid
(i, j)When the grid adjacent with grid to be measured do not exist actual measurement field intensity or prediction field intensity in the direct adjacent sector of sector, place (adjacent sectors), then inquire about adjacent sector (the grid Arcgrid of the direct adjacent sector of this sector again
(i, j)The adjacent sector of the adjacent sector of sector, place), there is when surveying field intensity or prediction field intensity execution in step 303 in the adjacent mesh of inquiring about successively in inquiring the sector;
Step 303 is by the grid field intensity in the radially unpredictable sector of adjacent grid prediction, adjacent sector.
As grid Arcgrid to be predicted
(i, j)Directly (perhaps claim adjacent sectors) adjacent sector Sect of sector, place
J-1In the grid Arcgrid adjacent with grid to be measured
(i, j-1)There are actual measurement field intensity or prediction field intensity, then get its grid Arcgrid
(i, j-1)Grid field intensity E
A (i, j-1)Be grid Arcgrid
(i, j)One of prediction field intensity E
A (i, j-1) (i, j)In like manner, if sector Sect
J+1In with grid Arcgrid to be predicted
(i, j)Adjacent grid Arcgrid
(i, j+1)When having actual measurement field intensity or prediction field intensity, then get its grid Arcgrid
(i, j+1)Grid field intensity E
A (i, j+1)Be grid Arcgrid
(i, j)Two E of prediction field intensity
A (i, j+1) (i, j)(when if the grid adjacent with grid to be predicted do not exist actual measurement field intensity or prediction field intensity in the adjacent sector, then get the adjacent sector of adjacent sector, when adjacent mesh in the sector exists actual measurement field intensity or prediction field intensity, again with the grid field intensity of corresponding grid as grid Arcgrid
(i, j)The prediction field intensity, i.e. E
A (i, j-1) (i, j)=E
A (i, j-s) (i, j), or E
A (i, j+1) (i, j)=E
A (i, j+s) (i, j), s represents this corresponding grid in the formula, value is 1 to m).These obtain one of prediction field intensity, two grid Arcgrid
(i, j-1), Arcgrid
(i, j+1)With predicted grid Arcgrid
(i, j)Between relation to be grid equate and exist the adjacent mesh of measured data or prediction data to the distance between the o of the center of circle.
If step 305 is grid Arcgrid
(i, j)The direct adjacent grid of sector, place (adjacent mesh) does not exist measured data or prediction data (two direct adjacent grid do not exist or one of them grid does not exist), then inquires about adjacent grid (the grid Arcgrid of this direct adjacent grid that does not have measured data or prediction data again
(i, j)The adjacent grid of the adjacent grid of sector, place), inquire about when inquiring the adjacent grid that has measured data or prediction data execution in step 306 successively;
Step 306 is by the grid field intensity with the grid field intensity prediction grid to be predicted of the adjacent grid in sector.Grid Arcgrid for example
(i-1, j), get its field intensity E
A (i-1, j)Multiply by attenuation factor
(i-1, j)(attenuation factor
(i-1, j)Be empirical value, can choose according to electromagnetic wave propagation frequency, certainty of measurement, landform etc.) be grid Arcgrid
(i, j)Three E of prediction field intensity
A (i-1, j) (i, j)In like manner desirable grid Arcgrid
(i+1, j)Field intensity E
A (i+1, j)Multiply by attenuation factor
(i+1, j)The back is grid Arcgrid
(i, j)Four E of prediction field intensity
A (i+1, j) (i, j)If (the field intensity value of direct adjacent grid is-∞, as adjacent grid Arcgrid
(i-1, j)Or Arcgrid
(i+1, j)The field intensity value be-∞, then get the adjacent grid of adjacent grid, have measured data or prediction data until adjacent grid, again with the field intensity of this neighbour's grid to grid Arcgrid
(i, j)Predict, i.e. E
A (i-1, j) (i, j)=α
(i-q, j)* E
A (i-q, j) (i, j), or E
A (i+1, j) (i, j)=α
(i+q, j)* E
A (i+q, j) (i, j), q represents this neighbour's grid in the formula, value is 1 to n).These obtain the prediction field intensity three, four grid Arcgrid
(i-1, j), Arcgrid
(i+1, j)With predicted grid Arcgrid
(i, j)Between relation be to be positioned at same sector and to have measured data or the adjacent grid of prediction data.
E
A (i，j)＝(E
A(i，j-1) (i，j)+E
A(i，j+1) (i，j)+E
A(i-1，j) (i，j)+E
A(i+1，j) (i，j))/4。
Fig. 2 and Fig. 3 flow process alternately and are continuously carried out, and will tile by measured data and prediction data to total-grid shown in Figure 1, have realized utilizing the measured data tiling to obtain the sub-district and have covered.The inventive method is in the process of utilizing measured data to tile, the characteristics of electromagnetic wave propagation have been taken into full account from many aspects, division, the measured data that mainly shows grid is mapped to the tiling of measured data and prediction data in the tiling of measured data in grid, the radially measurable sector and the radially unpredictable sector, avoided the inaccurate problem of data, also avoided the inaccurate or inaccurate sub-district covering Problem-Error that causes of propagation model simultaneously because of geodata.
Claims (11)
1. one kind is utilized the measured data tiling to obtain the method that the sub-district covers, and it is characterized in that comprising:
A. in antenna coverage areas, be the center of circle, be radius increment n the plane concentric circles that draw as step-length and with this step-length l the geographic accuracy l of actual measurement with the antenna position, the m bar radius of drawing from this center of circle and n plane concentric circles intersect, and are partitioned into m * n grid;
B. the field intensity data map that will survey on the geographical position, sub-district is to the grid field intensity of described grid as grid;
C. n plane concentric circles of two adjacent radius cuttings forms m sector in the steps A, add up the meshes number that has above-mentioned grid field intensity in each sector, the sector that number is surpassed preset value is decided to be radially measurable sector and D execution set by step, and the sector that number is lower than preset value is decided to be radially unpredictable sector and E execution set by step;
D. utilize the interpolation method of Okumura/Hata model and least square method,, predict in the radially measurable sector grid field intensity of the grid of the field intensity data that each is not mapped to actual measurement with the field intensity data tiling of actual measurement;
E. the grid field intensity of adjacent mesh and the grid field intensity of this sector adjacent mesh in utilization and the radially unpredictable sector adjacent sectors are predicted the grid field intensity that does not have the grid of grid field intensity in the radially unpredictable sector.
2. method according to claim 1 is characterized in that: among the described step B, the described field intensity data map that will survey on the geographical position, sub-district comprises to the grid field intensity of grid as grid:
When B1. an actual measurement field intensity is only arranged, this actual measurement field intensity is mapped to the grid field intensity of this grid as this grid in the geographical position corresponding with grid;
When B2. in the geographical position corresponding, not surveying field intensity, the grid field intensity of this grid is designated as minus infinity with grid;
When B3. more than one actual measurement field intensity is arranged in the geographical position corresponding with grid, these actual measurement field intensity are averaged, and this mean value is mapped to the grid field intensity of this grid as this grid.
3. method according to claim 2 is characterized in that also comprising:
B4. near one antenna actual measurement field intensity is mapped near the grid the antenna, the grid field intensity that equates as these grids.
4. method according to claim 1 is characterized in that: the preset value among the described step C is a lower limit of setting according to the size of actual measurement field intensity data volume.
5. method according to claim 1 is characterized in that described step D further comprises:
D1. arbitrary grid is designated as Arcgrid
(i, j), 0≤i＜n, 0≤j＜m is with grid Arcgrid
(i, j)The center is independent variable to the described center of circle apart from i * l+ , this grid Arcgrid
(i, J)Grid field intensity E
A (i, j)Be dependent variable, according to landform characteristic use Okumura/Hata model construction function curve;
D2. with the field intensity data of function curve that makes up and the grid that is shone upon and this grid element center to the described center of circle apart from match, carry out interpolation by least square method, prediction obtains in the described radially measurable sector grid field intensity of the grid of each field intensity data that are not mapped to actual measurement.
6. method according to claim 1 is characterized in that: before the described step e of execution, determining earlier in each radially unpredictable sector whether maximum the and unique sector of the meshes number that has the grid field intensity is arranged, is then direct execution in step E; Otherwise to there being the radially unpredictable sector that equates maximum number, further determine the meshes number sum that radially there is the grid field intensity in the direct neighbor sector of unpredictable sector in these respectively, to maximum and unique radially unpredictable sector execution in step E with number; Otherwise optional sector from have the radially unpredictable sector that equates maximum and number, execution in step E.
7. method according to claim 1 is characterized in that described step e further comprises:
E1. find two sectors that have described grid field intensity adjacent and adjacent with grid to be predicted with radially unpredictable sector to be predicted;
E2. with the grid field intensity of two adjacent in above-mentioned two adjacent sectors grids with grid to be predicted respectively as this one of grid field intensity for the treatment of pre-predicted grid with it two;
E3. find and same sector, radially unpredictable sector to be predicted, adjacent with grid to be predicted and have two grids of grid field intensity;
E4. the grid field intensity of above-mentioned two adjacent mesh is taken advantage of respectively after the decay factor as three with it four of the grid field intensity of grid to be predicted;
E5. to one of above-mentioned grid field intensity, two, three, four ask average, with the grid field intensity of mean value as grid to be predicted in the radially unpredictable sector to be predicted.
8. method according to claim 7 is characterized in that: in the described step e 1, when there is the grid field intensity in the grid the most adjacent and adjacent with grid to be predicted with radially unpredictable sector to be predicted, with this adjacent sectors as described two sectors; When there is not the grid field intensity in the grid adjacent with grid to be predicted in the sector the most adjacent with radially unpredictable sector to be predicted, inquire about the adjacent sector of this adjacent sectors in regular turn, until finding the grid adjacent to have the sector of grid field intensity, as described two sectors with grid to be predicted.
9. method according to claim 7 is characterized in that: in the described step e 2, and two grids that grid described and to be predicted is adjacent, the distance between its grid element center and the described center of circle equates with distance between the described center of circle with described grid to be predicted.
10. method according to claim 7 is characterized in that: in the described step e 3, when there are the grid field intensity in and its grid the most adjacent with grid to be predicted, with the grid field intensity of two adjacent mesh respectively as one of described grid field intensity with it two; When there is not the grid field intensity in the grid the most adjacent with grid to be predicted, inquire about the adjacent grid of this adjacent mesh in regular turn, until finding the grid that has the grid field intensity, with its grid field intensity as the grid field intensity that participates in the step e 4 calculating.
11. method according to claim 7 is characterized in that: in the described step e 4, two adjacent mesh are adjusted described decay factor according to the distance in their described centers of circle of distance.
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| KR100283081B1 (en) * | 1998-11-12 | 2001-03-02 | 이계철 | Transmission Loss Estimation Method Using Interpolation in Wireless Network Design System |
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