CN103607723A - Wireless communication link estimation method facing high-speed railway linear community - Google Patents

Abstract

The invention discloses a wireless communication link estimation method facing a high-speed railway linear community, and belongs to the technical field of wireless mobile communication. The method comprises the following steps: 1) a set of classification standard aiming at a high-speed railway characteristic spreading environment is put forward; 2) modeling is performed on large-scale path loss and shadow fading under various scenes, and a set of standardized spreading model library facing a high-speed railway is established; and 3) a coverage prediction method facing the railway linear community is put forward. The coverage range of the high-speed railway community is more accurately predicted under the premise of being without preliminary measurement so that a network arrangement scheme of the high-speed railway is optimized, base station spacing distance among communities is reasonably arranged and thus investment in high-speed railway wireless communication infrastructure is greatly reduced.

Description

A kind of wireless communication link method of estimation towards high-speed railway wire community

Technical field

The invention belongs to wireless mobile telecommunication technology field, particularly a kind of wireless communication link method of estimation towards high-speed railway wire community.

Background technology

In mobile Communication System for High Speed Railway, the setting of cell base station and planning mainly depend on the attenuation of wireless signal in railway characteristic environment.Along with the increase of distance, electromagnetic wave can be subject to blocking loss and being concerned with and the phenomenon that disappears mutually by the signal anti-, scattered wave causes of electrolytical absorption loss, ground obstacle in the process of free space transmission.These effects affect the intensity of receiver place wireless channel greatly.If the wireless signal strength of receiving terminal, lower than the threshold level of system, just there will be call drop phenomenon between train and base station, this,, for the such Safety-Critical System of high-speed railway, can cause huge potential safety hazard.

In order to guarantee the high-speed railway reliability of wireless coverage completely, must, in a large amount of base station of rail layout along the line, by setting up the distributed cell structure of chain, realize the good covering of wireless signal in train operation completely.Larger base station spacing cannot meet minimum covering level and the overall high standard requirement that covers probability under high-speed railway Safety-Critical System; And less base station spacing will cause huge fund waste, increase greatly subsequent network maintenance cost, reduce the antijamming capability of high-speed railway wireless communication system simultaneously.So, one towards high-speed railway radio communication rationally, link budget method, for promoting high-speed railway network performance, guarantees that high-speed railway security of operation is most important accurately.

For the method for high-speed railway community link budget, the past conventionally adopts beehive network Xia community in public network is covered to Probabilistic estimation, the way combining with the channel model (being Hata model) of traditional public network communication environment.Wherein Hata model only can be predicted city, suburb, rural three class scenes, cannot contain the scenes such as the overpass that often relates in high-speed railway radio communication, cutting, river, station.When using wireless link based on Hata model to estimate, its prediction effect often with railway characteristic environment under channel test there is larger error.And mostly traditional public network is based on honeycomb-like network structure, this class formation is many assumes a disc by cell coverage area, and railway wireless communication Zhong community is wire community, traditional community covering probability forecasting method can cause covering probability and owe to estimate phenomenon in Railway Environment, cannot reasonably predict the situation of change of railway wireless link.

In sum, a set of standardization propagation model storehouse of containing railway characteristic communication environments, join with the brand-new covering probability forecasting method towards railway wire community, can be good at solving a link budget difficult problem for high-speed railway wireless communication system.

Summary of the invention

The problem existing for above-mentioned prior art, the present invention proposes a kind of wireless communication link method of estimation towards high-speed railway wire community, it is characterized in that, and the method includes following steps:

1) a set of criteria for classification for high-speed railway characteristic communication environments is proposed;

2) the large scale path loss under all kinds of scenes and shadow fading are carried out to modeling, set up a set of standardization propagation model storehouse towards high-speed railway;

3) based on step (2), the coverage prediction method towards railway wire community is proposed.

Described in step 1), criteria for classification is: high-speed railway communication environments is divided into 7 classes: city, suburb, rural area, overpass, cutting, station, river.

Step 2) described large scale path loss is carried out to modeling, formula is as follows:

PL _Proposed(dB)=Δ ₁+74.52+26.16log ₁₀(f=930)

-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ²

+[44.9-6.55log ₁₀(h _b)+Δ ₂]log ₁₀(d)

Wherein, f is signal frequency (MHz), h _band h _mfor base station and the mobile portable antennas height (m) apart from rail level, d is the spacing (km) of base station and travelling carriage, Δ ₁and Δ ₂modifying factor for constant term and path loss index item.

Described two modifying factors are carried out to modeling, formula is as follows:

Δ _i=p·log ₁₀(h _b)+q

Wherein, i=1,2 refer to respectively two modifying factors, and p and q are the fitting parameters obtaining according to actual measurement, for describing Δ ₁and Δ ₂variation, in different environment, p and q equal respectively different values.

Step 2) described shadow fading is obeyed the Gaussian Profile of 0 average, and shadow fading is carried out to modeling, and formula is as follows:

${\mathrm{\σ}}_j\left(\mathrm{dB}\right)~N[{{\mathrm{\μ}}_{\mathrm{\σ}}}_j,{{\mathrm{\σ}}_{\mathrm{\σ}}}_j]$

Wherein, j=1,2,3,4,5,6,7 represent respectively 7 class high-speed railway communication environments.

Step 2) degree of fitting in the standardization propagation model storehouse of described high-speed railway judgement evaluation index is:

$\begin{array}{c}R-\mathrm{Square}=1-\frac{\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{w}_n{(y_n-{\hat{y}}_n)}^2}{\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{w}_n{(y_n-{\stackrel{\‾}{y}}_n)}^2}\\ \mathrm{RMSE}=\sqrt{\frac{1}{N-1}\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{(y_n-{\stackrel{\‾}{y}}_n)}^2}\end{array}$

Wherein, R-Square is the coefficient of determination, and RMSE is root-mean-square error, and N is number of samples, w _nfor weight factor, y _nfor test sample book,

for estimated value,

mean value for test value; The coefficient of determination more approaches 1 and shows that degree of fitting is better, and root-mean-square error is less shows that the error of model is less.

Described step 3) comprises the following steps:

31) determine that upper or down link is as the foundation of link budget;

32) determine ambient noise thresholding N, formula is as follows:

N=k·T _tem·BW

Wherein, BW is system bandwidth, and Tem is ambient temperature, and k is Boltzmann constant;

33) determine receiver sensitivity RS, formula is as follows:

RS=N+NF+SNR _min

Wherein, NF is receiver noise figure, and SNRmin is the required minimum signal to noise ratio of receiver, and k is Boltzmann constant;

34) determine incoming level thresholding T under Safety-Critical System, formula is as follows:

T=RS+ protection value

Wherein, protection value is multipath fading protection value, high-speed mobile protection value, aging protection value, phone noise protection value, interference protection value, row control protection value sum;

35) determine shadow fading nargin M, formula is as follows:

$O=\frac{1}{2}+\frac{1}{2}\·\mathrm{erf}\left(\frac{M}{\mathrm{\σ}\sqrt{2}}\right)$

Wherein, O is edge communications failure-free probability, and σ is the standard deviation of shadow fading in wire community;

36) determine that the overall situation covers probability U, formula is as follows:

$U=\frac{1}{2}-\frac{1}{2}\mathrm{erf}\left(a\right)-\frac{1}{2}\·\exp \left(\frac{1-4\mathrm{ab}}{{4b}^2}\right)\·[\mathrm{erf}(\frac{1}{2b}-a)-1]$

Wherein:, $a=-\frac{M}{\mathrm{\σ}\sqrt{2}},b=\frac{10n{\log }_{10}\left(e\right)}{\mathrm{\σ}\sqrt{2}},$ N is path loss index;

37) determine the average received level at maximum communication distance D place

formula is as follows:

$\stackrel{\‾}{P_{\mathrm{RX}}\left(D\right)}=M+T$

Wherein, T is incoming level thresholding;

38) determine maximum communication distance D, formula is as follows:

$D={10}^{\frac{P_{\mathrm{TX}}+G_{\mathrm{TX}}+G_{\mathrm{RX}}-L_{\mathrm{TX}}-L_{\mathrm{RX}}-{\mathrm{PL}}_0-\stackrel{\‾}{P_{\mathrm{RX}}\left(D\right)}}{10n}}$

Wherein, P _tXfor transmitting power, G _tX/ G _rXfor receiving/send out antenna gain, L _tX/ L _rXfor receiving/make a start overall loss, PL ₀for the constant term in large scale path loss model, that is:

Δ ₁+74.52+26.16log ₁₀(f=930)-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ²。

Described step 31) link budget according to for selecting the link of loss minimum.

Described step 31) to step 34) by the adjustment to real system parameter, can be generalized to non-Measurement of Railway Radio Communication System.

The beneficial effect of the invention: it is large at Railway Environment application error that the method has overcome conventional wireless propagation model storehouse, cover with planar community the limitation that probability Estimation cannot be applicable to wire community, well solved the wireless communication link estimation problem of characteristic wire community under high-speed railway typical environment, accuracy and the science of railway wire community wireless link budget have been promoted, and then the design of optimization Railroad Communication System, there is very strong applicability and practicality, for the design of high-speed railway cordless communication network provides important evidence.

Accompanying drawing explanation

Fig. 1 is a kind of wireless communication link method of estimation flow chart towards high-speed railway that the present invention proposes;

Fig. 2 verifies proposed path loss model storehouse on " Zhengzhou-Xi'an " high-speed railway circuit with the coefficient of determination (R-Square);

Fig. 3 verifies proposed path loss model storehouse on " Beijing-Shanghai " high-speed railway circuit with the coefficient of determination (R-Square);

Fig. 4 verifies proposed path loss model storehouse on " Zhengzhou-Xi'an " high-speed railway circuit by root-mean-square error (RMSE);

Fig. 5 verifies proposed path loss model storehouse on " Beijing-Shanghai " high-speed railway circuit by root-mean-square error (RMSE);

Fig. 6 is the affect situation of shadow fading nargin on cell edge outage probability;

Fig. 7 is channel quality and the impact of shadow fading nargin on the whole covering in railway wire community probability;

Fig. 8 is that channel quality is communicated by letter failure-free probability to the whole impact that covers probability in railway wire community with cell edge;

Fig. 9 is the flow chart of estimating that high-speed railway wire community maximum can communication distance;

Figure 10 is base station antenna height on maximum impact that can communication distance under urban settings;

Figure 11 is base station antenna height on maximum impact that can communication distance under the scene of suburb;

Figure 12 is base station antenna height on maximum impact that can communication distance under rural scene;

Figure 13 is base station antenna height on maximum impact that can communication distance under overpass scene;

Figure 14 is base station antenna height on maximum impact that can communication distance under cutting scene;

Figure 15 is base station antenna height on maximum impact that can communication distance under the scene of station;

Figure 16 is base station antenna height on maximum impact that can communication distance under river scene.

Embodiment

Below in conjunction with accompanying drawing and part railway system actual parameter, the method is elaborated.

Be illustrated in figure 1 a kind of wireless communication link method of estimation flow chart towards high-speed railway that the present invention proposes.First, based on China 4 high-speed railway circuits (Wuhan-Guangzhou, Zhengzhou-Xi'an, Shijiazhuang-Taiyuan, Beijing-Tianjin) and 8 high speed railway stations (Beijing South Station, station, Zhengzhou, Wuhan Railway Stations, Changsha Station, northern station, Xi'an, northern station, Shijiazhuang, station, Taiyuan, Tianjin station), on field test and the basis of investigation, a set of criteria for classification for high-speed railway characteristic communication environments is proposed.High-speed railway communication environments is divided into 7 classes:

1) city: this scene is refered in particular to typical large and medium-sized urban district, the area that population is comparatively dense, industry and commerce is comparatively flourishing.Rail level can be parallel to earth's surface, also can be positioned on the overpass of 5-20 rice.Rail level both sides radially effective coverage, longitudinally have the building of 5-20 layer (exceeding rail level 10-40 rice) in 80% community.High-rise building can cause the appearance in a large amount of strong reflections, loose footpath.This type of is anti-, scattering composition because of its Secondary Emission point high, less to the diffraction loss of any barrier, larger to receiving end signal intensity effect.

2) suburb: this scene is refered in particular to typical micropolis, township, town, village, and non-flat forms, non-open area is outside of the city.Rail level is parallel to earth's surface.Rail level both sides radially effective coverage, longitudinally have the vegetation of building and the similar height of 1-5 layer in the community of 60%-80%.In suburb, exist appropriate, equally distributed anti-, scattering object.Direct projection footpath, ground return footpath, environment are anti-, scattering footpath all occupies certain weight proportion.

3) rural area: this scene is refered in particular to region outside of the city open on typical Image of Flat Ground.Rail level is parallel to earth's surface.Rail level both sides radially effective coverage, longitudinal 80% do not have building in community, only have short (being less than 2 meters) crops and vegetation on a small quantity.In open ground, rural area instead, scattering object is less, direct wave and ground-reflected wave are occupied an leading position.Transmission matrix convergence sparse matrix structure.

4) overpass: this scene is refered in particular at area, ,Fei river, ,Fei mountain area, non-city rail level and is placed in the region on the overpass that 10-30 rice is high.Rail level both sides radially effective coverage, longitudinal 80% are short house in community, have part trees, shaft tower higher than bridge floor 0-10 rice.Overpass bridge floor can stop anti-, the scattered wave of most of earth's surface scattering object.And smooth bridge floor can produce stronger bridge floor reflected wave.The number, house that exceeds bridge floor can cause at receiving terminal that near-end is anti-, scattering, occurs multipath sub-clustering phenomenon.

5) cutting: this scene is refered in particular in uneven area as guaranteeing smooth the dug U-shaped groove region of rail level.Cutting both sides cliff mostly is symmetrical structure, 30 ° of gradients, degree of depth 2-20 rice, the many coverings in surface vegetation.The outer both sides of cutting are suburb, township environment, have a small amount of slight slope.Cutting mostly is suburb, rural environment outward.There is fragmentary little slight slope.The zanjon shape structure of cutting makes anti-, the scattered wave outside cutting be difficult to arrive receiving terminal.Cutting both sides cliff can cause at receiving terminal that a large amount of near-ends is anti-, scattered wave.

6) station: this scene is refered in particular to the large, medium and small type passenger station occurring in railway line.There are long 400-800 rice, wide 100-500 rice, the canopy of high 50-80 rice in top, station.Large and medium-sized station canopy is closed, and small station canopy mostly is the semi-enclosed canopy at platform place.The outer 100-500 rice of awning is stood in base station more.Station top can cause extra diffraction loss to the transmission of radio wave.The structure of its enclose inside formula can cause in subregion intensive reflection effect.

7) river: this scene is refered in particular in rail both sides radially has sheet (more than 5 square kilometres) lake waters in effective coverage, or have the wide river of 50-200 rice from below, to pass rail (now rail as many as is in overpass).Rail both sides mostly are typical suburb, rural environment.Level can cause the appearance of a large amount of mirror-reflections.Absorption loss due to the water surface is different from earth's surface simultaneously, and its reflection coefficient is larger, and it is larger that wireless loss is affected by it.

The division of above-mentioned scene is based on following criterion:

1) division of scene depends on served wireless system.

2) not only radio transmission mechanism is to propagate the foundation of scene partitioning, wireless communication system arrange net, configure and performance requirement should be all the reference factor of propagating scene partitioning.

3) scene classification is without containing all possibilities; But must change by response feature.

4) scene has exclusiveness each other.

5), except the scene of station, the characteristic feature in all the other scenes (as cutting, overpass) surpasses 80% of community track section.

6) based on rail, radially the topography and geomorphology in effective coverage and scattering object distribute in the classification of scene.Effective coverage radical length is for can be expressed as d _h=(D2) tan (θ), wherein θ is the angle on rail and radiation pattern main lobe border.

Secondly, in above-mentioned 7 class scenes, the method of testing that adopts GSM-R existing network BCCH signal to combine with vehicle-mounted field test instrument, in all kinds of high-speed railway environment, obtained and surpassed 2,300 ten thousand reception signal testing sample values, large scale path loss under all kinds of scenes and shadow fading are carried out to modeling, proposed a set of standardized high-speed railway propagation model storehouse.This model scope of application is as follows:

1) frequency: 930MHz;

2) mulching method: wire covers;

3) antenna form: omnidirectional, orientation all can;

4) effective base station antenna height (apart from rail level) 20-40m;

5) effective travelling carriage base station height 4m, only for car antenna;

6) Prediction distance scope 0.5-8km;

7) do not consider earth curvature;

8) do not consider the variation of track grade and radius of curvature.

This model comprises to large scale path loss is carried out modeling and shadow fading is carried out to modeling.

In to the modeling of large scale path loss, use classical Hata model as the basal expression formula of path loss PL, as follows:

PL _Hata(dB)=74.52+26.16log ₁₀(f)

-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ² （1）

+[44.9-6.55log ₁₀(h _b)]log ₁₀(d)

Wherein, f is signal frequency (MHz), h _band h _mfor base station and the mobile portable antennas height (m) apart from rail level, d is the spacing (km) of base station and travelling carriage.Classical Hata model cannot be applicable to railway wireless communication environments, so, the path loss prediction algorithm of a correction is proposed on the basis of above formula, as follows:

PL _Proposed(dB)=Δ ₁+74.52+26.16log ₁₀(f=930)

-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ² （2）

+[44.9-6.55log ₁₀(h _b)+Δ ₂]log ₁₀(d)

Wherein, Δ ₁and Δ ₂for the modifying factor of constant term and path loss index item, be respectively used to boosting algorithm accuracy and the impact of reaction high-speed railway characteristic environment on path loss index.Note, because this algorithm is for high-speed railway GSM-R communication system, therefore frequency limitation is at 930MHz.

In conjunction with a large amount of field tests, two modifying factors in above-mentioned correction term are carried out to modeling, modeling method adopts the linear regression theory based on least square method, probes into height of transmitting antenna to modifying factor Δ ₁and Δ ₂impact, formula is as follows:

Δ _i=plog ₁₀(h _b)+q (3) is i=1 wherein, and 2 refer to respectively two modifying factors.

Shadow fading (dB) for signal under high-speed railway environment, obey the Gaussian Profile of 0 average, joint test by a large amount of communities, the standard deviation of 0 average Gaussian Profile is carried out to quadratic fit modeling, find standard deviation also Gaussian distributed under j class environment, can portray with following formula:

${\mathrm{\σ}}_j\left(\mathrm{dB}\right)~N[{{\mathrm{\μ}}_{\mathrm{\σ}}}_j,{{\mathrm{\σ}}_{\mathrm{\σ}}}_j]---\left(4\right)$

On the basis of a large amount of tests, under all kinds of scenes, utilize equation (2) and (4) to obtain high-speed railway propagation model storehouse, conclude in Table 1:

Table one high-speed railway divides scene propagation model storehouse

In order to verify proposed high-speed railway propagation model storehouse, adopt " coefficient of determination (R-Square) " and " root-mean-square error (RMSE) " as degree of fitting judgement evaluation index, the method for estimation of the two is as follows:

$\begin{array}{c}R-\mathrm{Square}=1-\frac{\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{w}_n{(y_n-{\hat{y}}_n)}^2}{\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{w}_n{(y_n-{\stackrel{\‾}{y}}_n)}^2}\\ \mathrm{RMSE}=\sqrt{\frac{1}{N-1}\underset{n-1}{\overset{N}{\mathrm{\Σ}}}{(y_n-{\stackrel{\‾}{y}}_n)}^2}\end{array}---\left(5\right)$

Wherein, N is number of samples, w _nfor weight factor, y _nfor test sample book,

for estimated value,

mean value for test value.The coefficient of determination more approaches 1 and shows that degree of fitting is better, and root-mean-square error is less shows that the error of model is less.On " ”He“ Beijing-Shanghai, Zhengzhou-Xi'an " two rail tracks, proposed model is verified respectively, effect as shown in Figure 2-5.Can find out that proposed models and theory optimal solution (i.e. regression fit line in figure) performance is very approaching, and be much better than the Hata model that public network wireless link budget adopts.

Next, the method for estimation of shadow fading nargin in link budget under proposition high-speed railway characteristic environment.Shadow fading nargin is the pre-made allowance of protecting as shadow fading in link budget, for estimating that maximum can communication distance.If do not consider that shadow fading is with the variation of distance, only need be in cell edge propagation loss prediction, calculate maximum and consider shadow fading nargin can communication distance time.Cell edge outage probability has determined the shadow fading margin value that system should arrange.The outage probability of high-speed railway wire cell edge can be expressed as:

$\begin{array}{c}O\left(D\right)=P(P_r\left(D\right)<T)\\ =\underset{-\&infin;}{\overset{\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA0000416916610000022.png,HDA0000416916610000051.png"\; state="\{\{state\}\}">T</figure-callout>}}{\&Integral;}}\frac{1}{\sqrt{2\mathrm{\&pi;}}\mathrm{\&sigma;}}\exp \left(\frac{{(r-\stackrel{\&OverBar;}{P_r\left(D\right)})}^2}{2{\mathrm{\&sigma;}}^2}\right)\mathrm{dr}---\left(6\right)\\ =\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{T-\stackrel{\&OverBar;}{P_r\left(D\right)}}{\mathrm{\&sigma;}\sqrt{2}}\right)\end{array}$

Wherein, P (P _r(D) < Τ) for wire cell edge D place incoming level, be less than the probability of threshold level T, σ is the standard deviation of shadow fading in wire community.

In order to reduce (or control) edge outage probability, must in link budget, introduce shadow fading nargin M.The difference of the I received signal strength T of the local average of cell edge D place received signal strength and system, is exactly required compensation in link budget/reserved surplus, i.e. shadow fading nargin:

$M=\stackrel{\&OverBar;}{P_r\left(D\right)}-T---\left(7\right)$

Known from above-mentioned derivation, edge outage probability can be expressed as:

$\begin{array}{c}O=\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{T-\stackrel{\&OverBar;}{P_r\left(D\right)}}{\mathrm{\&sigma;}\sqrt{2}}\right)\\ =\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}(-\frac{M}{\mathrm{\&sigma;}\sqrt{2}})---\left(8\right)\\ =\frac{1}{2}-\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{M}{\mathrm{\&sigma;}\sqrt{2}}\right)\end{array}$

Accumulated probability density function (CDF) in conjunction with 0 average Gaussian Profile:

Can draw the relation of the edge outage probability of railway wire community and the accumulated probability density function of average Gaussian Profile:

O(x)=F(-x)（10）

On the basis of above-mentioned analysis, can draw, shadow fading possesses randomness, cannot measure between its absolute field, only can describe its feature by the mode of probability threshold, therefore due to the communication overlay Quality Down that shadow fading causes, also should adopt the mode of probability to measure.Fig. 6 has shown the impact of shadow fading nargin on cell edge outage probability, and it is 0.1,0.05 and the situation of 0.01 o'clock that three horizontal lines have marked out outage probability.This figure shows: under 4dB standard deviation, system shadow fading remaining when the 5dB outage probability of cell edge be 0.1, and shadow fading remaining during for 9dB the outage probability of cell edge be 0.01.Therefore,, in the link budget process of follow-up railway wire community, cell edge outage probability must be set according to system requirements in advance.The characteristic of considering the overcritical system of railway security, cell edge outage probability can not be too high.If between a typical railway scene Statistical Area, do not consider in the situation of multipath fading, require the outage probability of system to be less than a%, railway minute scene shadow fading nargin M (dB) design reference value is concluded in table two:

Table two high-speed railway divides scene shadow fading nargin design reference value

a%

City

Suburb

Rural area

Overpass

Cutting

Vehicle-mounted

River

10%

4.3dB

5.2dB

3.8dB

3.6dB

4.8dB

3.5dB

4.5dB

5%

5.5dB

6.6dB

4.8dB

4.7dB

6.2dB

4.5dB

5.8dB

1%

7.7dB

9.4dB

6.8dB

6.6dB

8.7dB

6.4dB

8.3dB

Finally, utilize above-mentioned conclusion, the covering probabilistic budgeting method of mover iron route shape community, and determine on this basis the largest coverage distance of railway community.For the ease of subsequent algorithm, understand, first part concept is defined.Local communication failure-free probability, in railway line, r place, distance base station receives signal P _rX(r) higher than the probability of threshold signal T.Edge communications failure-free probability, in railway line, D place, edge, base station receives signal P _rX(D) higher than the probability of threshold signal T, corresponding one by one with outage probability before.Railway line communication overlay probability, any position that railway base station covers in railway line receives signal higher than the probability of threshold signal T.Accumulated probability, the value of certain stochastic variable is lower than the probability of a threshold value.Conventional CDF represents.

The communication failure-free probability at local position r place can be expressed as

$\begin{array}{c}O\left(r\right)=P(P_{\mathrm{RX}}\left(r\right)>T)\\ =1-\underset{-\&infin;}{\overset{\mathrm{<figure-callout\; id="1"\; label="T"\; filenames="HDA0000416916610000022.png,HDA0000416916610000051.png"\; state="\{\{state\}\}">T</figure-callout>}}{\&Integral;}}\frac{1}{\sqrt{2\mathrm{\&pi;}}\mathrm{\&sigma;}}\exp \left(\frac{{(P_{\mathrm{RX}}\left(r\right)-\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(r\right)})}^2}{2{\mathrm{\&sigma;}}^2}\right)d\left(P_{\mathrm{RX}}\left(r\right)\right)---\left(11\right)\\ =\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{T-\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(r\right)}}{\mathrm{\&sigma;}\sqrt{2}}\right)\end{array}$

Make r=D, above formula becomes edge communications failure-free probability.If P[P _rx(r) > Τ] be illustrated in rail circuit and accept power P apart from r place _rx(r) be greater than the probability of system threshold level T, the railway wire circuit that length is D covers probability and can be expressed as

$\begin{array}{c}U=\frac{1}{D}\&Integral;P[P_{\mathrm{RX}}\left(r\right)>T]\mathrm{dr}\\ =\frac{1}{D}\underset{0}{\overset{D}{\&Integral;}}P[P_{\mathrm{RX}}\left(r\right)>T]\mathrm{dr}\end{array}---\left(12\right)$

Can further derive:

$\begin{array}{c}U=\frac{1}{D}\underset{0}{\overset{D}{\&Integral;}}P[P_{\mathrm{RX}}\left(r\right)>T]\mathrm{dr}\\ =\frac{1}{D}\underset{0}{\overset{D}{\&Integral;}}[\frac{1}{2}-\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{T-[P_{\mathrm{TX}}-({\mathrm{<figure-callout\; id="0"\; label="PL"\; filenames="HDA0000416916610000021.png,HDA0000416916610000022.png"\; state="\{\{state\}\}">PL</figure-callout>}}_0+10n{\log }_{10}(r/r_0))]}{\mathrm{\&sigma;}\sqrt{2}}\right)]\mathrm{dr}\\ =\frac{1}{D}\underset{0}{\overset{D}{\&Integral;}}[\frac{1}{2}-\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{T-P_{\mathrm{TX}}+{\mathrm{<figure-callout\; id="0"\; label="PL"\; filenames="HDA0000416916610000021.png,HDA0000416916610000022.png"\; state="\{\{state\}\}">PL</figure-callout>}}_0+10\mathrm{nlo}{g}_{10}(D/r_0)+10n{\log }_{10}(r/D)}{\mathrm{\&sigma;}\sqrt{2}}\right)]\mathrm{dr}\\ =\frac{1}{2}-\frac{1}{2D}\underset{0}{\overset{D}{\&Integral;}}\left[\mathrm{erf}(\frac{T-P_{\mathrm{TX}}+{\mathrm{<figure-callout\; id="0"\; label="PL"\; filenames="HDA0000416916610000021.png,HDA0000416916610000022.png"\; state="\{\{state\}\}">PL</figure-callout>}}_0+10n{\log }_{10}(D/r_0)}{\mathrm{\&sigma;}\sqrt{2}}+\frac{10n{\log }_{10}(r/D)}{\mathrm{\&sigma;}\sqrt{2}})\right]\mathrm{dr}\end{array}---\left(13\right)$

Wherein n is path loss index, for the ease of follow-up expression, and order:

$\begin{array}{c}a=\frac{T-P_{\mathrm{TX}}+{\mathrm{<figure-callout\; id="0"\; label="PL"\; filenames="HDA0000416916610000021.png,HDA0000416916610000022.png"\; state="\{\{state\}\}">PL</figure-callout>}}_0+10{n\log }_{10}(D/r_0)}{\mathrm{\&sigma;}\sqrt{2}}\\ b=\frac{10n{\log }_{10}\left(e\right)}{\mathrm{\&sigma;}\sqrt{2}}\end{array}---\left(14\right)$

Above formula can abbreviation be:

$U=\frac{1}{2}-\frac{1}{2D}\underset{0}{\overset{D}{\&Integral;}}\left[\mathrm{erf}(a+b\ln \left(\frac{r}{D}\right))\right]\mathrm{dr}---\left(15\right)$

Above formula is replaced: t=a+bln (r/D), above formula integration finally abbreviation be following closed solutions:

$\begin{array}{c}U=\frac{1}{2}-\frac{1}{2D}\underset{-\&infin;}{\overset{a}{\&Integral;}}\exp \left(\frac{t-a}{b}\right)\&CenterDot;\mathrm{erf}\left(t\right)\mathrm{dr}\\ =\frac{1}{2}-\frac{\exp (-a/b)}{2}\&CenterDot;[\exp \left(\frac{1}{4b^2}\right)\mathrm{erf}(\frac{1}{2b}-t)+\exp \left(\frac{t}{b}\right)\mathrm{erf}\left(t\right)={|}_{t=-\&infin;}^{t=a}\\ =\frac{1}{2}-\frac{1}{2}\mathrm{erf}\left(a\right)-\frac{1}{2}\&CenterDot;\exp \left(\frac{1-4\mathrm{ab}}{4b^2}\right)\&CenterDot;[\mathrm{erf}(\frac{1}{2b}-a)-1]\end{array}---\left(16\right)$

Wherein:

$\begin{array}{c}a=\frac{T-P_{\mathrm{TX}}+{\mathrm{<figure-callout\; id="0"\; label="PL"\; filenames="HDA0000416916610000021.png,HDA0000416916610000022.png"\; state="\{\{state\}\}">PL</figure-callout>}}_0+10{n\log }_{10}(D/r_0)}{\mathrm{\&sigma;}\sqrt{2}}\\ b=\frac{10n{\log }_{10}\left(e\right)}{\mathrm{\&sigma;}\sqrt{2}}\end{array}---\left(17\right)$

In conjunction with the derivation to shadow fading nargin above, can draw:

$a=-\frac{M}{\mathrm{\&sigma;}\sqrt{2}}---\left(18\right)$

Fig. 7 and Fig. 8 have shown respectively the impact on the whole covering in railway wire community probability in the lower shadow fading nargin of different channel quality (σ/n) and edge communications failure-free probability, simultaneously, for the ease of comparison, the relation curve of planar public network also draws in the drawings.As can be seen from the figure, there is larger difference in covering probability and the planar community of railway wire community, and traditional planar community coverage prediction method is not suitable for railway wire community and characteristic communication environments.In addition, can find, when σ/n is larger, wire cell edge covers probability can react overall situation covering probability preferably; But when σ/n is less, the very high overall situation covers probability can not guarantee good edges cover probability.This explanation, although railway wire line traffic covers probability higher than planar community:

1) under Railway Environment, less σ/n has restricted the accuracy of utilizing edge outage probability to estimate overall situation covering probability.

2) acceptance criteria based on overall situation covering probability is not suitable for Railway Environment.

3) examination of railway wireless network should be emphasized wire cell edge, checks and accepts the phenomenon of the covering probability " virtual height " being caused to reduce global measuring.

Demand for applicable railway characteristic environment and wire community, utilize said method, to system threshold level T, edge communications failure-free probability (otherwise or: the edge outage probability) reasonable definition of O, the overall situation that can obtain under present railway community covers probability, combining wireless propagation channel model library again, the anti-maximum communication distance that solves railway wire community.

Concrete grammar step is as follows:

Step 1: determine that upper or down link is as the foundation of link budget.

The core parameter of high-speed railway GSM-R system is as shown in Table 3:

Table three high-speed railway GSM-R system parameters

Parameter	Base station	Vehicle-mounted mobile platform
			Transmitting power (dBm)	43	39
Thermal noise (dBm)	-121	-121
			Noise pattern (dB)	5	7
Minimum SNR(dB)	6	10
			Receiver sensitivity (dBm)	-110	-104

Railway is because the loss uplink and downlink of the devices such as GSM-R link center tap, cable, coupler, circulator are identical, therefore the maximum link loss that GSM-R up link can bear is: 39-(110)=149dB; The maximum link loss that GSM-R down link can bear is: 43-(104)=147dB.Link budget is because selecting the link of loss minimum, i.e. down link.Meanwhile, uplink budget lacks feasibility: the test that down link can be based on BCCH signal, can meet the requirement of Li Shi sampling criterion; And up link only can be tested based on Abis interface, cannot provide test data accurately.Therefore suggestion: the link budget of GSM-R system is based on down link.Step 2: determine ambient noise thresholding N.

Known system bandwidth BW, ambient temperature Tem, Boltzmann constant k.GSM-R system bandwidth 200kHz wherein.Under typical environment, Tem is 290 Kelvins (approximately 16.9 degrees Celsius), and ambient noise thresholding N is:

N=k·T _tem·BW

=(1.38×10 ^-23)×290×(200×10 ³)

=8.004×10 ^-16W （19）

=-120.97dBm

Step 3: determine receiver sensitivity RS.

Known receiver noise figure NF, the required minimum signal to noise ratio snr min of receiver, Boltzmann constant k.Wherein GSM-R receiver noise figure is 7dB, and signal to noise ratio is 10dB, and receiver sensitivity RS is:

RS=N+NF+SNR _min=-121+7+10=-104dBm (20) step 4: determine incoming level thresholding T under Safety-Critical System.

Consider the requirement of the overcritical system of railway security, on the basis of receiver sensitivity, introduce protection.Consider multipath fading protection (3dB), high-speed mobile protection (3dB), aging protection (3dB), the protection of electrochemical noise (3dB), interference protection (3dB), row control protections (3dB).Therefore the incoming level thresholding T of railway GSM-R system is:

T=RS+(3+3+3+3+3+3)

=-104+18 （21）

=-86dBm

Step 5: determine shadow fading nargin M.

Known edge communications failure-free probability O, shadow fading nargin M can determine by the following method:

$O=\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{M}{\mathrm{\&sigma;}\sqrt{2}}\right)---\left(22\right)$

Step 6: determine that the overall situation covers probability U.

$U=\frac{1}{2}-\frac{1}{2}\mathrm{erf}\left(a\right)-\frac{1}{2}\&CenterDot;\exp \left(\frac{1-4\mathrm{ab}}{{4b}^2}\right)\&CenterDot;[\mathrm{erf}(\frac{1}{2b}-a)-1]---\left(23\right)$

Wherein:, $a=-\frac{M}{\mathrm{\&sigma;}\sqrt{2}},b=\frac{10n{\log }_{10}\left(e\right)}{\mathrm{\&sigma;}\sqrt{2}},$ N is path loss index.

Step 7: the average received level of determining maximum communication distance place

Known incoming level thresholding T and shadow fading nargin M.The average received level of Gu great Tong Xinjulichu

for:

$\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(D\right)}=M+T$

Step 8: determine maximum communication distance D.

Known transmit power P _tX, receive/send out antenna gain G _tX/ G _rX, receive/make a start overall loss L _tX/ L _rX, in large scale path loss model

Δ ₁+ 74.52+26.16log ₁₀(f=930)-13.82log ₁₀(h _b)-3.2 (log ₁₀(11.75h _m)) ²item PL ₀;

Therefore maximum communication distance is:

$D={10}^{\frac{P_{\mathrm{TX}}+G_{\mathrm{TX}}+G_{\mathrm{RX}}-L_{\mathrm{TX}}-L_{\mathrm{RX}}-{\mathrm{PL}}_0-\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(D\right)}}{10n}}$

This distance is the use value of base station spacing in wireless network.

In above-mentioned steps, front four steps, by the adjustment to real system parameter, also extend to non-Measurement of Railway Radio Communication System.To the calculation process of rear three steps, can summarize with Fig. 8 on this basis.

Embodiment 1

In order further clearly to set forth the using method of the link budget algorithm that proposes, introduce the more specifically railway system and do example.Wherein, the device loss parameter of railway down link is in Table four:

The device loss parameter of table four railway down link

All the other high-speed railway link budget parameters are concluded in table five:

Table five high-speed railway wire link budget parameter gathers

On the basis arranging in said system parameter, integrating step 1-8, can obtain under high-speed railway environment each and propagate maximum communication distance in scene and the graph of a relation of base station height, and result is as Figure 10-16.Wherein, in figure, three black lines represent respectively that railway wire cell edge communication failure-free probability is 90%, 95%, 99% situation from top to bottom.Therefrom can find out, the base station range of 90% edge communications failure-free probability Xia， community is maximum.In addition, the cell coverage area under all kinds of characteristic scenes of high-speed railway can reach 10km mostly, much larger than the 3km base station spacing in actual existing network, and is subject to antenna for base station larger apart from the effect of altitude of rail level.Existing network is badly in need of adopting rational link method of estimation to be optimized, and the network of follow-up high-speed railway circuit is set up and is also necessary to adopt link algorithm for estimating more accurately to design.

The above; be only preferably embodiment of this method, but the protection range of this method is not limited to this, is anyly familiar with those skilled in the art in the technical scope that this method is described; the variation that can expect easily or replacement, within all should being encompassed in the protection range of this method.Therefore, the protection range of this method should be as the criterion with the protection range of claim.

Claims (9)

1. towards a wireless communication link method of estimation for high-speed railway, it is characterized in that, the method includes following steps:

1) a set of criteria for classification for high-speed railway characteristic communication environments is proposed;

2) the large scale path loss under all kinds of scenes and shadow fading are carried out to modeling, set up a set of standardization propagation model storehouse towards high-speed railway;

3) based on step (2), the coverage prediction method towards railway wire community is proposed.

2. a kind of wireless communication link method of estimation towards high-speed railway according to claim 1, it is characterized in that, criteria for classification is described in step 1): high-speed railway communication environments is divided into 7 classes: city, suburb, rural area, overpass, cutting, station, river.

3. a kind of wireless communication link method of estimation towards high-speed railway according to claim 1, is characterized in that step 2) described large scale path loss is carried out to modeling, formula is as follows:

PL _Proposed(dB)=Δ ₁+74.52+26.16log ₁₀(f=930)

-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ²

+[44.9-6.55log ₁₀(h _b)+Δ ₂]log ₁₀(d)

Wherein, f is signal frequency (MHz), h _band h _mfor base station and the mobile portable antennas height (m) apart from rail level, d is the spacing (km) of base station and travelling carriage, Δ ₁and Δ ₂modifying factor for constant term and path loss index item.

4. a kind of wireless communication link method of estimation towards high-speed railway according to claim 3, is characterized in that, described two modifying factors is carried out to modeling, and formula is as follows:

Δ _i=p·log ₁₀(h _b)+q

I=1 wherein, 2 refer to respectively two modifying factors, and p and q are the fitting parameters obtaining according to actual measurement, for describing Δ ₁and Δ ₂variation, in different environment, p and q equal respectively different values.

5. a kind of wireless communication link method of estimation towards high-speed railway according to claim 1, is characterized in that step 2) described shadow fading obeys the Gaussian Profile of 0 average, and shadow fading is carried out to modeling, and formula is as follows:

${\mathrm{\&sigma;}}_j\left(\mathrm{dB}\right)~N[{{\mathrm{\&mu;}}_{\mathrm{\&sigma;}}}_j,{{\mathrm{\&sigma;}}_{\mathrm{\&sigma;}}}_j]$

Wherein, j=1,2,3,4,5,6,7 represent respectively 7 class high-speed railway communication environments.

6. a kind of wireless communication link method of estimation towards high-speed railway according to claim 1, is characterized in that step 2) the degree of fitting judgement evaluation index in the standardization propagation model storehouse of described high-speed railway is:

$\begin{array}{c}R-\mathrm{Square}=1-\frac{\underset{n-1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n{(y_n-{\hat{y}}_n)}^2}{\underset{n-1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_n{(y_n-{\stackrel{\&OverBar;}{y}}_n)}^2}\\ \mathrm{RMSE}=\sqrt{\frac{1}{N-1}\underset{n-1}{\overset{N}{\mathrm{\&Sigma;}}}{(y_n-{\stackrel{\&OverBar;}{y}}_n)}^2}\end{array}$

Wherein, R-Square is the coefficient of determination, and RMSE is root-mean-square error, and N is number of samples, w _nfor weight factor, y _nfor test sample book,

for estimated value,

mean value for test value; The coefficient of determination more approaches 1 and shows that degree of fitting is better, and root-mean-square error is less shows that the error of model is less.

7. a kind of wireless communication link method of estimation towards high-speed railway according to claim 1, is characterized in that, step 3) comprises the following steps:

31) determine that upper or down link is as the foundation of link budget;

Link budget is selected the link of loss minimum;

32) determine ambient noise thresholding N, formula is as follows:

N=k·T _tem·BW

Wherein, BW is system bandwidth, and Tem is ambient temperature, and k is Boltzmann constant;

33) determine receiver sensitivity RS, formula is as follows:

RS=N+NF+SNR _min

Wherein, NF is receiver noise figure, and SNRmin is the required minimum signal to noise ratio of receiver, and k is Boltzmann constant;

34) determine incoming level thresholding under Safety-Critical System, formula is as follows:

T=RS+ protection value

Wherein, protection value is multipath fading protection value, high-speed mobile protection value, aging protection value, phone noise protection value, interference protection value, row control protection value sum;

35) determine shadow fading nargin M, formula is as follows:

$O=\frac{1}{2}+\frac{1}{2}\&CenterDot;\mathrm{erf}\left(\frac{M}{\mathrm{\&sigma;}\sqrt{2}}\right)$

Wherein, O is edge communications failure-free probability, and σ is the standard deviation of shadow fading in wire community;

36) determine that the overall situation covers probability U, formula is as follows:

$U=\frac{1}{2}-\frac{1}{2}\mathrm{erf}\left(a\right)-\frac{1}{2}\&CenterDot;\exp \left(\frac{1-4\mathrm{ab}}{{4b}^2}\right)\&CenterDot;[\mathrm{erf}(\frac{1}{2b}-a)-1]$

Wherein: $a=-\frac{M}{\mathrm{\&sigma;}\sqrt{2}},b=\frac{10n{\log }_{10}\left(e\right)}{\mathrm{\&sigma;}\sqrt{2}},$ N is path loss index;

37) determine the average received level at maximum communication distance D place

formula is as follows:

$\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(D\right)}=M+T$

Wherein, T is incoming level thresholding;

38) determine maximum communication distance D, formula is as follows:

$D={10}^{\frac{P_{\mathrm{TX}}+G_{\mathrm{TX}}+G_{\mathrm{RX}}-L_{\mathrm{TX}}-L_{\mathrm{RX}}-{\mathrm{PL}}_0-\stackrel{\&OverBar;}{P_{\mathrm{RX}}\left(D\right)}}{10n}}$

Wherein, P _tXfor transmitting power, G _tX/ G _rXfor receiving/send out antenna gain, L _tX/ L _rXfor receiving/make a start overall loss, PL ₀for the constant term in large scale path loss model, that is:

Δ ₁+74.52+26.16log ₁₀(f=930)-13.82log ₁₀(h _b)-3.2(log ₁₀(11.75h _m)) ²。

8. a kind of wireless communication link method of estimation towards high-speed railway according to claim 7, is characterized in that described step 31) link budget according to for selecting the link of loss minimum.

9. a kind of wireless communication link method of estimation towards high-speed railway according to claim 7, is characterized in that described step 31) to step 34) by the adjustment to real system parameter, can be generalized to non-Measurement of Railway Radio Communication System.

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