CN105791181B - A kind of channel estimation and equalization method for rail traffic high-speed mobile scene - Google Patents
A kind of channel estimation and equalization method for rail traffic high-speed mobile scene Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/391—Modelling the propagation channel
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/0212—Channel estimation of impulse response
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/024—Channel estimation channel estimation algorithms
- H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L2025/03592—Adaptation methods
- H04L2025/03598—Algorithms
- H04L2025/03611—Iterative algorithms
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Abstract
The invention discloses a kind of channel estimation and equalization methods for rail traffic high-speed mobile scene, the step of this method includes: to obtain train current location S1, the channel model S2 for constructing train predicted position, the current location based on train, it determines the foundational shock response S3 of train predicted position channel, the variable quantity of predicted position channel response is tracked, and quickly estimate the actual channel impulse response S4 of predicted position and responded according to the real impact of the step S4 predicted position determined, carry out channel equalization S5.Technical solution combination rail traffic scene and Channel Modeling of the present invention, by carrying out channel estimation to the known channel model at train shift position, the time delay of channel estimation is very short, and estimated accuracy is high, be suitable for precise channel estimation under high-speed mobile, complex scene with it is balanced.
Description
Technical field
The present invention relates to wireless mobile telecommunication technology fields, are used for rail traffic high-speed mobile scene more particularly to one kind
Channel estimation and equalization method.
Background technique
It is train with the fast development of the Rail Transit Systems such as railway, subway, inter-city passenger rail, especially high-speed railway
Passenger provides reliable, real-time, efficient broadband wireless network service, it has also become the hot spot of domestic and international wide-band mobile communication research.
However, due to high-speed mobile and rail traffic complex scene (overpass, cutting, tunnel, marshalling yard, railway terminal etc.) bring
The quick time-varying of channel can cause to distort to the Train Control signal of transmission.If not carrying out balanced or compensation to the channel distortions
The signal that receiving end can be seriously affected restores, and influences traffic safety.Therefore, channel estimation technique is for being used for transmission Train Control
Information and ensure that the Rail Transit System of train safe operation is significant.
The method of channel estimation is broadly divided into three classes: non-blind Channel Estimation, blind Channel Estimation and semi-blind channel estimation.It is non-blind
Channel estimation methods are divided into again based on training sequence and based on the method for pilot tone.According to the difference of pilot tone inserted mode, can will lead
Frequency division is Block-type pilot, Comb Pilot, trellis pilot tone etc..The criterion of channel estimation substantially has 3 kinds: least square (LS) algorithm,
Least mean-square error (MMSE) algorithm and maximum likelihood (ML) algorithm.Blind Channel Estimation be based on transmission information symbol characteristic and
Statistical nature is estimated, potential in terms of the capacity and reliability for improving communication system, but convergence rate is slower.And half-blindness
Channel estimation is that a compromise is done between data transmission efficiency and convergence rate, i.e., obtains letter using less training sequence
The information in road.
Based on the above method, the moving velocity of terminal in conventional mobile communications scene is lower, have enough time obtain and with
Track channel synchronization realizes channel estimation in turn.But under high-speed mobile condition, it is desirable that realize that Fast synchronization is caught in a very short period of time
It obtains and accurate channel estimation.Traditional channel estimation technique for being suitable for middle low speed mobile context is not suitable for high-speed mobile
Scene.And the existing channel estimation and equalization technology for being suitable for high-speed mobile scene, accurately obtaining based on channel state information
Take or based on pilot tone frequency domain carry out estimation and interpolation, channel state information can be out-of-date quickly under high-speed moving state；Largely
The pilot tone of insertion can be such that estimation time delay greatly increases.These methods still have carry out channel estimation complexity is higher, channel
Delay time of estimation is long, can not be difficult in a very short period of time under track channel change, complex scene in time under high-speed moving state
With obtain precise channel estimation with it is balanced the problems such as.These methods are generally required in estimated accuracy and are rolled on the estimation time
In.
Accordingly, it is desirable to provide a kind of precise channel estimation that can be suitable under high-speed mobile, complex scene with it is balanced
Channel estimation methods.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of channel estimation for rail traffic high-speed mobile scene with
Equalization methods, in conjunction with rail traffic scene and Channel Modeling, by carrying out letter to the known channel model at train shift position
Road estimation, reduces the time delay of channel estimation, improves estimated accuracy, meanwhile, the accurate letter being suitable under high-speed mobile, complex scene
Road estimation with it is balanced.
In order to solve the above technical problems, the present invention adopts the following technical solutions:
A kind of the step of channel estimation and equalization method for rail traffic high-speed mobile scene, this method includes:
S1, train current location is obtained；
S2, the channel model for constructing train predicted position；
S3, the current location based on train determine the foundational shock response of train predicted position channel；
S4, the variable quantity of predicted position channel response is tracked, and quickly estimates the actual channel of predicted position
Shock response；
S5, it is responded according to the real impact of the step S4 predicted position determined, carries out channel equalization.
Preferably, the step S1 includes:
The ID of oneself is sent to train by S11, the transponder that ground base station is arranged in；
S12, the relative position for measuring train and the ground base station；
S13, train current location P is determined1: P1The relative position of=transponder india D+ train and the ground base station.
Preferably, the relative position of the wheel track stadia surveying train and the ground base station using setting ON TRAINS.
Preferably, the step S3 includes:
It in advance will be in the corresponding underlying parameter deposit channel database in each running position of train；
The current location of channel model and train based on train predicted position, reads corresponding from channel database
Underlying parameter estimates the actual channel impulse response of predicted position.
Preferably, the underlying parameter include: the corresponding channel in each running position of train multipath number and each diameter
Time delay and mean energy data.
Preferably, the step S2 includes:
S21, determine electromagnetic wave signal by propagation roads all between the obtained train current location step S1 and ground base station
Diameter；
S22, the transmission loss that each propagation path is calculated using the path loss formula of electromagnetic transmission:
PL (dB)=△1+74.52+26.16log10(f)-13.82log10(hb)-3.2log10(11.75hm)2+[44.9-
6.55log10(hb)+△2]log10(D)
Wherein, f indicates working frequency range, hbAnd hmRespectively indicate antenna for base station effective height and train antenna effective height, D
Indicate train current location between ground base station at a distance from transmission path, △1And △2It is constant relevant to transmission environment；
S23, the transmission delay for calculating each propagation path；
S24, energy loss and propagation delay time based on every transmission paths, construct the channel model of current location.
Preferably, the step S4 includes:
S41, the reception sequence based on the pilot signal propagated in the channel, using minimum mean square error criterion to arrive frequency point
Place's channel response is estimated；
S42, the response that all the points in channel are obtained using interpolation algorithm, the i.e. variable quantity of predicted position channel response；
S43, the actual channel impulse response of predicted position: the actual channel impulse response=prediction of predicted position is estimated
Foundational shock response+predicted position channel response variable quantity of position channel.
Preferably, the step S5 includes
By in train travelling process, all subchannels are denoted as: yi=Hixi+wi；
Equilibrium is carried out to channel using minimum mean square error criterion, i.e.,
minE{(giyi-xi)H(giyi-xi),
Then have,
Wherein, giFor equalizing coefficient, σn 2For noise variance,For equilibrium output.
Beneficial effects of the present invention are as follows:
Technical solution combination rail traffic scene and Channel Modeling of the present invention, by train shift position
Know that channel model carries out channel estimation, the time delay of channel estimation is very short, and estimated accuracy is high, is suitable for high-speed mobile, complexity
Under scene precise channel estimation with it is balanced.
Detailed description of the invention
Specific embodiments of the present invention will be described in further detail with reference to the accompanying drawing；
Fig. 1 shows the schematic diagram of rail traffic Private Mobile Communication Network network chain covering；
Fig. 2 shows the schematic diagrames of pilot tone of the present invention insertion；
Fig. 3 shows the flow chart of channel estimation and equalization of the present invention.
Specific embodiment
In order to illustrate more clearly of the present invention, the present invention is done further below with reference to preferred embodiments and drawings
It is bright.Similar component is indicated in attached drawing with identical appended drawing reference.It will be appreciated by those skilled in the art that institute is specific below
The content of description is illustrative and be not restrictive, and should not be limited the scope of the invention with this.
There are two main classes for existing channel estimation technique: one kind is for middle low speed mobile context, and one kind is for high speed
Mobile context.The channel estimation for being suitable for middle low speed mobile context is not suitable for high speed due to estimating complexity, postponing the factors such as big
Mobile context.Method in face of high-speed mobile scene or the acquisition based on channel state information come carry out channel estimation or
The channel estimation at pilot tone, which is carried out, in frequency domain based on pilot tone then carries out interpolation again；This method utilizes the known letter at certain position
Road model carries out channel estimation, and the time delay of channel estimation is very short, and estimated accuracy is high, is suitable for high-speed mobile complex scene.
As shown in Figure 1, basic ideas of the invention are: by based on wheel track rangefinder and transponder realization to train position
Set positioning (assuming that are as follows: P1), utilize P in the position1The scene information and channel model at place calculate position P1The letter at place
Road situation accurately obtains corresponding channel impulse response, so that being able to achieve fast, accurately under high-speed mobile complex scene
Channel estimation.Wherein scene information and basic channel model can obtain in data statistics measurement through a large number of experiments.
The present invention specifically discloses a kind of channel estimation and equalization method for rail traffic high-speed mobile scene, should
The step of method includes:
Step S1, train current location is obtained
Step S2, the channel model of train predicted position is constructed；
Step S3, based on the current location of train, the foundational shock response of train predicted position channel is determined；
Step S4, the variable quantity of predicted position channel response is tracked, and it is actual quickly to estimate predicted position
Channel impulse response；
Step S5, it is responded according to the real impact of the step S4 predicted position determined, carries out channel equalization.
For this programme, the step S1 specifically: the ID of oneself is sent to column by the transponder that ground base station is arranged in
Vehicle, meanwhile, utilize the relative position of setting wheel track stadia surveying train ON TRAINS and the ground base station.According to response
The ID of device and the relative position determine train current location P1: P1=transponder india D+ train is opposite with the ground base station
Position.As shown in Figure 1, distance D is a fixed value, because rail transit train driving trace is fixed, communication network
Base station space D be also fixed.
For this programme, the step S3 specifically: in advance by the multipath of the corresponding channel in each running position of train
The time delay and mean energy data of several and each diameter are stored in channel database；Channel model based on train predicted position and
Corresponding underlying parameter is read in the current location of train from channel database, estimates the actual channel punching of predicted position
Hit response.
For this programme, the step S2 specifically: determine the train current location that electromagnetic wave signal is obtained by step S1
All possible propagation path, including direct path, reflection path etc. between ground base station.Utilize the path of electromagnetic transmission
Formula is lost and calculates the transmission loss of each propagation path, while calculating the transmission delay of each propagation path, by above-mentioned
The energy loss and propagation delay time of the every transmission paths being calculated can construct the channel model of predicted position.
For this programme, the step S4 is specifically included:
S41, the reception sequence based on the pilot signal propagated in the channel, using minimum mean square error criterion to arrive frequency point
Place's channel response is estimated；
S42, the response that all the points in channel are obtained using interpolation algorithm, the i.e. variable quantity of predicted position channel response；
S43, the actual channel impulse response of predicted position: the actual channel impulse response=prediction of predicted position is estimated
Foundational shock response+predicted position channel response variable quantity of position channel.
The step S5 specifically: by train travelling process, all subchannels are denoted as: yi=Hixi+wi；Utilize minimum
Mean-square error criteria carries out equilibrium to channel, i.e.,
minE{(giyi-xi)H(giyi-xi),
Then have,
Wherein, giFor equalizing coefficient, σn 2For noise variance,For equilibrium output.
Below by one group of embodiment, the present invention will be further described:
The core concept of this programme is: the fast, accurately channel estimation and equalization based on channel model at certain position
Method, complexity is low, caused by avoiding due to the insertion using the channel state information or a large amount of pilot tone/training sequences of feedback
Efficiency of transmission reduces and big estimation delay.
In this example, as shown in figure 3, a kind of channel estimation and equalization method for rail traffic high-speed mobile scene,
Specifically:
Step 1: as shown in Figure 1, the ID of oneself is issued train, the position of train by the transponder being arranged in ground base station
Set P1The relative position of ground base station and train that=transponder india D+ is obtained using train wheel track rangefinder by wheel rotation.
Because rail transit train driving trace be it is fixed, the base station space D of communication network be also it is fixed, D1 is train operation
The distance of positional distance ground base station.
Step 2: the large-scale fading channel model of the correspondence predicted position of train-installed receiving platform storage are as follows:
PL (dB)=△1+74.52+26.16log10(f)-13.82log10(hb)-3.2log10(11.75hm)2+[44.9-
6.55log10(hb)+△2]log10(D)
Wherein, f indicates working frequency range, hbAnd hmRespectively indicate antenna for base station effective height and train antenna effective height, D
Indicate train current location between ground base station at a distance from transmission path, △1And △2It is constant relevant to transmission environment.
Channel model under 1 rail traffic different scenes of table
Table 1 gives under rail transit elevated bridge, cutting, station, tunnel, city, suburb, rural area and river scene
Large scale channel model.Wherein, parameter A, B indicate two fixed values.F indicates working frequency range, hbAnd hmRespectively indicate base station day
Line effective height and train antenna effective height, D2Indicate the train predicted position positioned to next to be switched cell base station
Distance.
Step 3: obtaining the basic channel impulse response with train operation environmental correclation.
Basic channel response section and channel details changing unit can be divided into for the estimation of channel impulse response.?
The large-scale fading predicted value of channel has been obtained in we in two steps.Due to rail transit train driving trace be it is fixed,
For each running position, it is relevant to channel fixed background that we can obtain the position by enough DATA REASONINGs in advance
Channel basis response, for example, channel multipath number and each diameter the parameters such as time delay, average energy, these ginsengs relevant to position
Number can store in channel database, the train specific location according to obtained in the first step, and quick predict reads the base of channel
Plinth parameter, this part impulse response is determined by the specific location of future position substantially, is denoted as h1。
Step 4: quickly estimating and tracking the variations in detail of channel.
Since variations in detail can occur train for channel during the motion, even if passing through same position, letter in different moments
Channel shock response will not be identical, can be superimposed variable quantity in the channel response basic value that third step obtains, be denoted as h2。h2
It can be obtained by auxiliary datas such as traditional pilot tone/training sequences, but in statistical significance, h2Relative to h1It is typically small,
It is only variable quantity of the channel response relative to basic value, we, which can be inserted, estimates all channel relative to conventional transmission systems
Less pilot tone/training sequence is responded quickly to be tracked.And the channel estimation under traditional quick time-variant multipath channel
In algorithm, relatively good channel estimation effect can be obtained by generally requiring to be inserted into a large amount of pilot tone/training sequence, when Doppler expands
When opening up larger, pilot tone/training sequence insertion even will reach the 50% of transmitted data amount, seriously reduce valid data
Efficiency of transmission.After channel estimation is divided into base response and variations in detail two parts by the method for the invention, pilot tone/training sequence
Insertion be intended merely to tracking channel variations in detail amount, particularly, when channel response substantially can be by train current location institute
When corresponding channel circumstance is determined namely h2Relative to h1It can ignore, pilot tone/training sequence insertion can be zero.Cause
This, this method improves the complexity of conventional channel estimation method, greatly reduces due to the insertion of pilot tone/training sequence and leads
The efficiency of transmission of cause reduces and biggish estimation delay.Final channel estimation results are denoted as h=h1+h2。h2Specifically tracked
Journey is as follows:
It is illustrated for being inserted into pilot tone, is one of ofdm system scattered pilot insertion pattern as shown in Figure 2.It is logical
Chang Di, it would be desirable to estimate the channel response of pilot point first, complete channel response result is then obtained by interpolation.
If the pilot signal sent is X=diag (X1,X2,…,XP), the reception sequence after channel is equal to
Y=XH+N
Wherein, H is the channel matrix of P × 1, and N is that P × 1 ties up noise vector.We are using minimum mean square error criterion to pilot tone
Channel response is estimated at point:
Wherein,
RHY=E (HYH)
RYY=E (YYH)=XRHHXH+σn 2IP
E () expression takes mean value, σn 2Indicate noise power.
In practical applications, in order to reduce computational complexity, the amplitude that we can choose pilot tone makes XXH=σs 2IP,
Wherein, σs 2It is signal power.At this point, above-mentioned channel estimation results can simplify are as follows:
After obtaining the channel response at pilot point, the channel response of remaining each point can be obtained by interpolation, most simply
First-order linear interpolation be
Wherein,WithFor two pilot point channel responses.
Step 5: carrying out channel equalization.
By it is above-mentioned obtain fast and accurately channel estimation results after, we can be using the method pair of time domain or frequency domain
Data carry out equilibrium, obtain solution adjusting data.Similarly, by taking ofdm system as an example, it is above-mentioned obtain channel frequency impulse response after,
Remember that the mode in i-th of subchannel is
yi=Hixi+wi
Wherein, xiFor the transmission symbol in i-th of subchannel, yiFor the symbol received, wiFor Gaussian noise.Still it adopts
Equilibrium is carried out with minimum mean square error criterion, if equalizing coefficient is gi, it meets:
minE{(giyi-xi)H(giyi-xi)}
Then have,
In formula, σn 2It is noise variance,As balanced output.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention may be used also on the basis of the above description for those of ordinary skill in the art
To make other variations or changes in different ways, all embodiments can not be exhaustive here, it is all to belong to this hair
The obvious changes or variations that bright technical solution is extended out are still in the scope of protection of the present invention.
Claims (5)
1. a kind of channel estimation and equalization method for rail traffic high-speed mobile scene, which is characterized in that the step of this method
Suddenly include:
S1, train current location is obtained；
S2, the channel model for constructing train predicted position,
Wherein, the step S2 includes: S21, determines electromagnetic wave signal by the obtained train current location step S1 and ground base
All propagation paths between standing；S22, it is damaged using the transmission that the path loss formula of electromagnetic transmission calculates each propagation path
Consumption: PL (dB)=△1+74.52+26.16log10(f)-13.82log10(hb)-3.2log10(11.75hm)2+[44.9-
6.55log10(hb)+△2]log10(D), wherein f indicates working frequency range, hbAnd hmRespectively indicate antenna for base station effective height and column
Vehicle mounted antenna effective height, D indicate train current location between ground base station at a distance from transmission path, △1And △2It is and transmission
The constant of environmental correclation；S23, the transmission delay for calculating each propagation path；S24, the energy damage based on every transmission paths
Consumption and propagation delay time, construct the channel model of predicted position；
S3, the current location based on train determine the foundational shock response of train predicted position channel,
Wherein, the step S3 includes: that the corresponding underlying parameter in each running position of train is stored in channel database in advance
In；The current location of channel model and train based on train predicted position, reads corresponding basis from channel database
Parameter estimates the foundational shock response of train predicted position channel；
S4, the variable quantity of predicted position channel response is tracked, and quickly estimates the actual Channel Impulse of predicted position
Response,
Wherein, the step S4 includes: S41, the reception sequence based on the pilot signal propagated in the channel, utilizes lowest mean square
Error criterion estimates channel response at pilot point；S42, the response that all the points in channel are obtained using interpolation algorithm, i.e.,
The variable quantity of predicted position channel response；S43, estimate the actual channel impulse response of predicted position: predicted position is actual
Channel impulse response=predicted position channel foundational shock response+predicted position channel response variable quantity；
S5, it is responded according to the real impact of the step S4 predicted position determined, carries out channel equalization.
2. channel estimation and equalization method according to claim 1, which is characterized in that the step S1 includes:
The ID of oneself is sent to train by S11, the transponder that ground base station is arranged in；
S12, the relative position for measuring train and the ground base station；
S13, train current location P is determined1: P1The relative position of=transponder india D+ train and the ground base station.
3. channel estimation and equalization method according to claim 2, which is characterized in that utilize the wheel track of setting ON TRAINS
The relative position of stadia surveying train and the ground base station.
4. channel estimation and equalization method according to claim 1, which is characterized in that the underlying parameter includes: train
The multipath number of each corresponding channel in running position and the time delay and mean energy data of each diameter.
5. channel estimation and equalization method according to claim 1, which is characterized in that the step S5 includes
By in train travelling process, all subchannels are denoted as: yi=Hixi+wi；
Equilibrium is carried out to channel using minimum mean square error criterion, i.e.,
minE{(giyi-xi)H(giyi-xi),
Then have,
Wherein, giFor equalizing coefficient, σn 2For noise variance,For equilibrium output, i indicates subchannel serial number, HiIndicate i-th of son
The channel matrix of channel, xiIndicate the information symbol of i-th of subchannel transmission, yiWhat expression was received in i-th of receiving end subchannel
Information symbol, wiIndicate the Gaussian noise received in i-th of receiving end subchannel, σs 2Indicate signal power.
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| CN106850087B (en) * | 2017-03-31 | 2021-05-18 | 北京润科通用技术有限公司 | Open-land environment channel modeling method and device |
| CN111049768B (en) * | 2019-12-25 | 2021-04-27 | 中山大学 | Position information assisted visible light channel estimation method based on deep learning |
| CN111586635B (en) * | 2020-05-18 | 2022-08-19 | 西南交通大学 | High-speed railway radio-over-fiber communication system and method based on precise channel parameters |
| CN113067613B (en) * | 2021-02-02 | 2022-11-08 | 上海大学 | Direction modulation method based on antenna selection for rail transit physical layer security |
| CN113225711B (en) * | 2021-05-11 | 2022-06-14 | 合肥工业大学 | Tunnel scene vehicle-to-vehicle MIMO wireless channel capacity estimation method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101478776A (en) * | 2009-01-23 | 2009-07-08 | 北京交通大学 | Method of railway wireless environment path loss index estimation |
| CN102014084A (en) * | 2010-11-12 | 2011-04-13 | 西南交通大学 | Channel estimation and diversity method based on train speed and position in train-ground communication |
| CN103227760A (en) * | 2013-04-28 | 2013-07-31 | 中国铁路通信信号股份有限公司 | Channel estimation method under high-speed mobile environment |
| CN103607723A (en) * | 2013-11-18 | 2014-02-26 | 北京交通大学 | Wireless communication link estimation method facing high-speed railway linear community |
| US9219629B1 (en) * | 2014-08-27 | 2015-12-22 | Zenith Electronics L.L.C. | Adaptive low complexity channel estimation for mobile OFDM systems |
-
2016
- 2016-02-26 CN CN201610108138.2A patent/CN105791181B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101478776A (en) * | 2009-01-23 | 2009-07-08 | 北京交通大学 | Method of railway wireless environment path loss index estimation |
| CN102014084A (en) * | 2010-11-12 | 2011-04-13 | 西南交通大学 | Channel estimation and diversity method based on train speed and position in train-ground communication |
| CN103227760A (en) * | 2013-04-28 | 2013-07-31 | 中国铁路通信信号股份有限公司 | Channel estimation method under high-speed mobile environment |
| CN103607723A (en) * | 2013-11-18 | 2014-02-26 | 北京交通大学 | Wireless communication link estimation method facing high-speed railway linear community |
| US9219629B1 (en) * | 2014-08-27 | 2015-12-22 | Zenith Electronics L.L.C. | Adaptive low complexity channel estimation for mobile OFDM systems |
Non-Patent Citations (1)
| Title |
|---|
| 适用于高速移动场景的信道估计方法;韩宜君等;《太赫兹科学与电子信息学报》;20131225;全文 |
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