CN106211320B - It is a kind of in heterogeneous network between macro base station and user distance passive type estimation method - Google Patents
It is a kind of in heterogeneous network between macro base station and user distance passive type estimation method Download PDFInfo
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
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Abstract
The present invention disclose it is a kind of in heterogeneous network between macro base station and user distance passive type estimation method, all Signal to Noise Ratio (SNR) that micro-base station SBS only needs to listen to itself are ranked up and take median that can estimate macrosystem base station to the distance d user0.In traditional estimation method, d0It can only estimate in macro base station and macro user.By the feedback link of macrosystem to SBS, macrosystem is by d0It is sent to SBS.Therefore with traditional d0Estimation method is compared, and the present invention does not need macrosystem to the feedback link of SBS.Also, the shadow fading in wireless channel makes the channel between transceiver generate acute variation.This makes SBS estimate d0Become abnormal difficult.The present invention considers influence of the shadow fading to wireless channel, proposes a kind of simple d0Estimator.Experiment simulation proves that the estimator has preferable estimation performance.
Description
Technical field
The invention belongs to the honeycomb heterogeneous networks of mobile communication field.Present invention seek to address that micro-base station is to macro in the network
Between base station and macro user the problem of distance estimations.
Background technique
In recent years, the research of heterogeneous network becomes the most popular of wireless communication field.In heterogeneous network, micro-base station is typically located at
In the coverage area of macro base station.In order to reach higher Microcell handling capacity, the frequency resource of macrosystem is can be used in micro-base station.
But in order to not influence macro user communication, micro-base station, which needs to control, interferes the downlink of macro user.
In order to control the downlink interference to macro user, micro-base station needs to obtain the location information of macro user.Particularly, such as
The macro user of fruit is in except the coverage area of micro-base station, then interference very little of the signal transmission of micro-base station to primary user.Therefore,
Micro-base station can maximize Microcell handling capacity using maximum allowable power transmission signal.Conversely, when macro user be in it is micro-
When within the coverage area of base station, micro-base station then needs strict control transmission power, to prevent from interfering macro user.?
In existing technology, in order to obtain the location information of primary user, micro-base station usually requires a feedback link from macrosystem
Road.But in actual scene, this feedback link may be not present.Therefore, how micro-base station obtains the position of primary user
Information becomes a big urgent problem to be solved.
Summary of the invention
The present invention in order to solve the above technical problems, propose it is a kind of in heterogeneous network between macro base station and user distance quilt
Dynamic formula estimation method, in the present invention, micro-base station can estimate macro base station and macro user under conditions of feedback link is not present
The distance between.
The technical solution adopted by the present invention is that: it is a kind of for the passive type of distance to be estimated between macro base station and user in heterogeneous network
Method, comprising:
In S1, downlink transmission, close-loop power control is used between macro base station and macro user, macro base station is according to macro user
The target signal to noise ratio at place carries out power adjustment；
S2, micro-base station obtain macro base station and macro use by the estimation criterion based on median according to the signal-to-noise ratio received
The distance between family.
Further, the step S1 specifically include it is following step by step:
S11, macro base station use adaptive modulation system, and macro base station emits the signal x of unit power0, it may be assumed that | x0|2=1,
Transmission power is p0, then macro user terminal receives signal are as follows:
Wherein, (i) be data block coefficient；(i, j) indicates j-th of sub-block of i-th of data block；n0(i, j) is
The mean value received at SBS is 0, variance σ2Additive white Gaussian noise；h0(i, j) is multipath fading coefficient, | h0(i,j)
| obey the rayleigh distributed that mean value is 1；gqExpression path loss, q=0,1；Expression shadow fading, q=0,1；
The signal-to-noise ratio that macro user terminal receives are as follows:
In order to meet the target signal to noise ratio γ of Hong YonghuchuT, the transmission power of macro base station meets the following conditions:
S12, in downlink transmission, micro-base station receives the signal of macro base station are as follows:
Wherein, n1(i, j) is that mean value is 0 at micro-base station, variance σ2Additive white Gaussian noise；
Therefore the signal-to-noise ratio at micro-base station are as follows:
It willWithBand
EnterIn, then the signal-to-noise ratio at micro-base station can indicate are as follows:
Further, the step S2 specifically include it is following step by step:
S21, to the signal-to-noise ratio at micro-base station:Index is carried out to handle, and
It is indicated using dB form are as follows:
Wherein, stochastic variableγ1,dBFor micro- base
The signal-to-noise ratio that the place of station receives, γT,dBFor the target signal to noise ratio of Hong Yonghuchu；
γ in S22, step S211,dBCumulative Distribution Function are as follows:
S23, the definition according to median are enabledObtain γc,dBMedian
S24, pass through solutionTo obtain the distance between macro base station and macro user d0Estimated value
Further, the step S22 specifically:
A1, due to | h0| and | h1| the rayleigh distributed that mean value is 1 is obeyed, therefore, φ=| h1|2/|h0|2Cumulative distribution
Function are as follows:
A2、Θr=10log10The Cumulative Distribution Function of (φ) are as follows:
A3, the result of step A1 is brought into step A2 and obtains that Θ can be obtained in resultrCumulative Distribution Function are as follows:
A4, by step A3 acquired results to θrIntegral can obtain ΘrCumulative Distribution Function:
A5, due toWithObeying variance isLogarithm normal distribution, therefore, ΘsObeying mean value is 0, and variance isNormal distribution, then ΘsCumulative Distribution Function are as follows:
A6, γ is obtained according to the result of step A4 and step A51,dBCumulative Distribution Function are as follows:
A7, orderThen A6 obtains γ1,dBCumulative Distribution Function can table
It is shown as:
Further, the step S24 specifically:
S241, independent data blocks a for I, micro-base station measure the signal-to-noise ratio of J sub-block in each independent data block,
It can detecte K=IJ independent signal-to-noise ratio in total,
γ1,dB(i,j)(1≤i≤I,1≤j≤J)；
S242, the γ for obtaining step S2411,dB(i, j) (1≤i≤I, 1≤j≤J) is expressed as
And carry out ascending order arrangement, it may be assumed that
S243, when K be odd number when, sample medianThen γ1,dBIt can be approximated to be:
S244, macro base station is obtained according to the definition to result, the result that step S243 is obtained and median of step S23
The distance between macro user d0Estimated value
S245, when K be even number when, sample medianIt is inWithBetween, then γ1,dBIt can be with
It is approximately:
S246, macro base station is obtained according to the definition to result, the result that step S245 is obtained and median of step S23
The distance between macro user d0Estimated value
Beneficial effects of the present invention: of the invention is a kind of for the passive type of distance to be estimated between macro base station and user in heterogeneous network
Meter method, all Signal to Noise Ratio (SNR) that micro-base station SBS only needs to listen to itself are ranked up and take median that can estimate
Macrosystem base station is to the distance d between user0.In traditional estimation method, d0It can only estimate in macro base station and macro user.By macro
System is to the feedback link of SBS, and macrosystem is by d0It is sent to SBS.Therefore with traditional d0Estimation method is compared, and the present invention is not required to
Want macrosystem to the feedback link of SBS.Also, it is violent that the shadow fading in wireless channel generates the channel between transceiver
Variation.This makes SBS estimate d0Become abnormal difficult.The present invention considers influence of the shadow fading to wireless channel, proposes
A kind of simple d0Estimator.Experiment simulation proves that the estimator has preferable estimation performance.
Detailed description of the invention
Fig. 1 is the system schematic that the present invention uses.
Fig. 2 is channel model provided by the invention.
Fig. 3 is the opposite evaluated error ε of the distance between MBS provided by the invention and MU and the pass of number of data blocks I (J)
System's figure.
Fig. 4 is the location diagram of the SNR and MU or SBS at SBS provided by the invention.
Fig. 5 is the positional relationship of opposite the evaluated error ε and MU or SBS of the distance between MBS provided by the invention and MU
Figure.
Specific embodiment
For convenient for those skilled in the art understand that technology contents of the invention, with reference to the accompanying drawing to the content of present invention into one
Step is illustrated.
Term used in the present invention and model are introduced first:
Define 1 macro base station (MBS, Macro Base Station): the signal transmitting terminal in macrosystem.
Define 2 macro users (MU, Macro User Equipment): the signal receiving end in macrosystem.
Define 3 micro-base stations (SBS, Small-cell Based Station): the signal transmitting terminal in micro-system.
Define 4 signal-to-noise ratio (SNR, Signal Noise Ratio): the ratio of signal power and noise power.
Define 5 close-loop power controls (CLPC, Closed Loop Power Control): transmitting terminal is believed according to receiving end
Make an uproar ratio variation to adjust the transmission power of itself, to guarantee the quality of reception of receiving end.
It defines 6 cumulative distribution function (CDF, Cumulative Distribution Function): indicating a certain random
Variable falls in the probability on a certain section.
It defines 7 probability-distribution functions (PDF, Probability Distribution Function): indicating instantaneous amplitude
Fall in the probability in certain specified range.
It defines 8 medians (Median): representing a sample, a numerical value in probability distribution, it can be by numerical value set
It is divided into equal two parts up and down.
Define 9 estimators (MB, Median Based) based on median: the estimation proposed using median feature
Device.
As shown in Figure 1, system of the invention is made of MBS, MU and SBS, MBS is communicated in some frequency range with MU, MBS
Fixation is set, coverage area is the circle that radius is R, and SBS is located within the coverage area of MBS.In order to use the frequency range of MBS, SBS
Need interference of the strict control to MU.Therefore, SBS attempts to estimate the distance between MBS and MU information d0MU is done to control
It disturbs.In system, the wireless channel between two transceivers is made of large-scale fading and multipath fading.Wherein, large scale declines
It falls including path loss gq(q=0,1) and shadow fadingMultipath fading is Rayleigh fading hq(q=0,1).Cause
This, the channel coefficients between MBS and MU areChannel coefficients between MBS and SBS areg0Indicate MBS
Path loss between MU, gs0Indicate the shadow fading between MBS and MU, g1Indicate the path loss between MBS and SBS,
gs1Indicate the shadow fading between MBS and SBS.
Particularly, gq(q=0,1) it is determined by the space loss model between transceiver.If using space loss model:
Pl(dq)=- 128-37.6log10(dq),for dq≥0.035km (1)
Then gqIt can indicate are as follows:
Wherein, dqIt (q=0,1) is the distance between two communication nodes；Wherein d0Indicate that the MBS to be estimated is arrived in this system
The distance between MU, d1Indicate the distance of MBS to SBS.
gq(q=0,1),And hqThe relationship of (q=0,1) is as shown in Fig. 2, gq(q=0,1) only by transceiver
The distance between determine, do not change over time.
For shadow fading coefficient, obeying variance isLogarithm normal distribution, and in each time block
(i) it remains unchanged in, changes in different time block independent random, the shelter between transceiver has relationship, is an obedience
The stochastic variable of logarithm normal distribution.In practice, building etc. can block the propagation of radio wave, change wireless channel decline
Intensity.If great variety can occur for the wireless channel coefficient between transceiver there are shelter between transceiver.In actual field
Jing Zhong, value variation are slower relative to multipath fading.
hq(q=0,1) is multipath fading coefficient, | hq| obedience mean value be 1 rayleigh distributed, and each time sub-block (i,
J) independent random changes in, has relationship with the environment around transceiver, and in actual scene, value variation is very fast.
The present invention considers that macrosystem uses CLPC in downlink (i.e. signal is transmitted to macro user by macro base station) transmission.?
While MBS emits signal to MU, the SNR from MBS end signal is monitored at the end SBS.By monitoring multiple independent SNR, this is utilized
The median and d of a little SNR0Mathematical relationship estimate d0。
Median and sampling median are defined as follows:
It defines 10, for a CDF function be FX(x), the stochastic variable X of x ∈ R, if there is following relationship exists:
SoIt is just the median of X.
It defines 11, have M sampled value x for onemThe stochastic variable X of (1≤m≤M), if:
ThenFor the median of X sampled value.
Due to using CLPC in macrosystem between MBS and MU, the transmission power of MBS contains the distance between MBS and MU
Information.Meanwhile the transmission power information of MBS is included in the SNR data that SBS is received.Therefore, SBS can be by measuring SNR
To estimate the distance between MBS and MU d in macrosystem0.At the same time, median can react the average value of multiple data.Benefit
With SNR average value and d0Relationship can estimate to obtain d0Value.
SBS carries out d by median criterion0The method of estimation, includes the following steps:
In S1, downlink transmission, CLPC, MBS is used to be believed between macro base station MBS and macro user MU according to the target at MU
It makes an uproar than carrying out power adjustment.Specific step is as follows:
S11, MBS use adaptive modulation system, and MBS emits the signal x of unit power0, it may be assumed that | x0|2=1, emit function
Rate is p0, then MU terminates the signal received and can indicate are as follows:
Wherein, (i) be data block coefficient, (i, j) indicate i-th of data block j-th of sub-block.n0(i, j) is
The mean value received at MU is 0, variance σ2Additive white Gaussian noise, h0(i, j) is multipath fading coefficient, | h0(i,j)|
Obey the rayleigh distributed that mean value is 1.Then, the SNR received at MU are as follows:
Due to using CLPC, MBS to be adaptively adjusted the transmission power of itself to reach the target at MU between MBS and MU
Signal-to-noise ratio γT, therefore, the transmission power at MBS should meet the following conditions:
S12, in downlink transmission, SBS receives the signal of MBS are as follows:
Wherein, n1(i, j) is that mean value is 0 at SBS, variance σ2Additive white Gaussian noise.
Then the SNR at SBS are as follows:
(2) and (5) are brought into (7), above-mentioned SNR can be indicated are as follows:
S2, as shown from the above formula: d0Estimation it is related with the SNR of all sub-blocks received at SBS, then SBS
All SNR estimate CG value d based on the received0。
It is succinct for formula, the index in (8) is removed, and is indicated with dB form:
Wherein, stochastic variableγ1,dBFor SBS
The SNR that place receives, γT,dBFor the target SNR at MU.Because of ΘrAnd ΘsFor stochastic variable, so γ1,dBIt also is corresponding
Stochastic variable will first acquire Θ respectively belowrAnd ΘsPDF, then acquire γ1,dBPDF form.
Firstly, since | h0| and | h1| the rayleigh distributed that mean value is 1 is obeyed, therefore, φ=| h1|2/|h0|2CDF shape
Formula are as follows:
Then, Θr=10log10The CDF form of (φ) are as follows:
(10), which are brought into, can obtain Θ in (11)rCDF form are as follows:
By above formula to θrIntegral can obtain ΘrPDF form it is as follows:
Secondly asWithObeying variance isLogarithm normal distribution, therefore, ΘsObeying mean value is 0, variance
ForNormal distribution.Its PDF form are as follows:
Then, γ1,dBCDF form can indicate are as follows:
It enablesThen (15) become:
Based on definition 10, Ke YilingTo obtain γc,dBMedian
Theorem 1: whenWhen,It sets up.
Detailed proof procedure is as follows:
In order to proveFormula (17) is set up, it is only necessary to prove that following formula is set up:
(12) are brought into (18) to obtain:
By (14) it is found thatFor even function, so thatAnd
Then, (19) can indicate are as follows:
Then theorem 1 must be demonstrate,proved.
It is available based on theorem 1 aboveWith d0Relationship it is as follows:
By (21) it is found thatFor d0Function, solution can be passed throughTo obtain d0Estimated valueBut SBS
And it is unaware ofValue, therefore first to estimateValue.
For I independent data blocks, SBS can measure the SNR of J sub-block in each independent data block, therefore,
SBS can detecte K=IJ independent SNR i.e. in total: γ1,dB(i, j) (1≤i≤I, 1≤j≤J), next, will be with adopting
Sample medianCome approximateFinally acquire MB estimator
Firstly, SNR γ will be sampled1,dB(i, j) (1≤i≤I, 1≤j≤J) is expressed asAnd to it
Carry out ascending order arrangement, it may be assumed that
Due to when number of samples K be odd and even number when, sample medianIt is different, so, the application will be respectively to K
It discusses for odd and even number.
1) when K is odd number, sample medianTherefore, γ1,dBIt can be approximated to be:
(22) are brought into (21), it can be deduced that MB estimator:
2) when K is even number, sample medianIt is inWithBetween, then, γ1,dBIt can be with
It is approximately:
(24) are brought into (21), MB estimator can indicate are as follows:
Synthesis can obtain, MB estimator brief summary are as follows:
Wherein, odd indicates that odd number, even indicate even number.From (26) as can be seen that MB estimatorValue depend on MU at
Target SNR γT,dB, the distance between MBS and SBS d1, the received SNR γ of SBS itself1,dB, since SBS can pass through research
The Modulation and Coding Scheme of macrosystem obtains γT,dB, by measuring itself at a distance from MBS obtain d1, measure and receive
SNR obtains γ1,dB, therefore, SBS can obtain MB estimator by solution (26)
Simulation result: in simulations, the coordinate position of transmitter is set as (0,0), the coverage area of MBS is 0.5Km, MU
It is in x-axis with SBS, the target signal to noise ratio at receiver is γT=10dB, the power of noise are -114dBm, Monte Carlo
Spreading points is 10000.
Fig. 3 is d0Opposite evaluated error ε and data block (sub-block) number I (J) relational graph, ε is defined as:
Wherein, the distance between MBS and SBS d1=0.1km, the distance between MBS and MU d0=0.25km.It can be with by figure
Find out, with the increase of (wherein I, J ∈ (1, ∞)) data block (sub-block) number I (J), the value of evaluated error ε is increasingly
It is small.This is because SBS can detect more SNR when I (J) becomes larger, it also can be more and more accurate to the estimation of SNR median,
And d0Estimation it is related to SNR medion estimator, therefore d0Estimation performance can improve.Meanwhile as seen from the figure, with the increasing of I
Greatly, evaluated error ε can be strongly reduced, and when J increases, and the decline of ε is not obvious, this can illustrate it is elected select biggish I and
When lesser J, preferably estimation performance can be obtained.
Fig. 4 is the location diagram of the SNR and MU or SBS at SBS.That is: work as d0Or d1SNR when taking different value, at SBS
Size variation.Wherein I=200, J=20.Figure, which illustrates, works as d0Increase or d1When reduction, the SNR at SBS can become larger therewith.This is
Cause are as follows: work as d0When becoming larger, MBS is in order to meet the γ at MUT, need to improve transmission power, then receive signal power at SBS
Become larger, while the corresponding SNR that receives also will increase；Meanwhile working as d1When reduction, the signal that SBS is received from MBS can enhance,
Then SNR is received to become larger.
Fig. 5 is d0Opposite evaluated error ε and MU or SBS location diagram.That is: work as d0Or d1When taking different value, relatively
The size variation of evaluated error ε.Wherein I=200, J=20.As seen from the figure, work as d0Increase or d1When reduction, d0It is opposite
Evaluated error ε can become smaller therewith.Work as d as can be drawn from Figure 40Increase or d1When reduction, the SNR at SBS becomes larger, therefore SNR estimates
Error can also reduce, and d0Estimation it is again related to SNR estimation, then d0Evaluated error also accordingly reduce.Upper figure also shows
Work as d0Increase or d1When reduction, evaluated error ε can converge to 4%, and this present MB estimators preferably to estimate performance.
In the art, considering influence of the shadow fading to channel, while without the feedback link of macrosystem to SBS
In the case where, SBS of the invention estimates d0Method, be not suggested also.
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.This field
Those of ordinary skill disclosed the technical disclosures can make according to the present invention and various not depart from the other each of essence of the invention
The specific variations and combinations of kind, these variations and combinations are still within the scope of the present invention.
Claims (4)
1. it is a kind of in heterogeneous network between macro base station and user distance passive type estimation method characterized by comprising
In S1, downlink transmission, close-loop power control is used between macro base station and macro user, macro base station is according to Hong Yonghuchu's
Target signal to noise ratio carries out power adjustment；
S2, micro-base station according to the signal-to-noise ratio received, by the estimation criterion based on median obtain macro base station and macro user it
Between distance；The step S2 specifically include it is following step by step:
S21, to the signal-to-noise ratio at micro-base station:It carries out index to handle, and uses dB
Form indicates are as follows:
Wherein, stochastic variableγ1,dBAt micro-base station
The signal-to-noise ratio received, γT,dBFor the target signal to noise ratio of Hong Yonghuchu, d0It indicates in this system between MBS to the MU to be estimated
Distance, d1Indicate the distance of MBS to SBS, h0The multipath fading coefficient of (i, j) between MBS to MU, h1(i, j) arrives for MBS
The multipath fading coefficient of SBS；
γ in S22, step S211,dBCumulative Distribution Function are as follows:
S23, the definition according to median are enabledObtain γc,dBMedian
S24, pass through solutionTo obtain the distance between macro base station and macro user d0Estimated value
2. it is according to claim 1 it is a kind of in heterogeneous network between macro base station and user distance passive type estimation method,
It is characterized in that, the step S1 specifically include it is following step by step:
S11, macro base station use adaptive modulation system, and macro base station emits the signal x of unit power0, it may be assumed that | x0|2=1, transmitting
Power is p0, then macro user terminal receives signal are as follows:
Wherein, (i) be data block coefficient；(i, j) indicates j-th of sub-block of i-th of data block；n0(i, j) is macro user
The mean value that place receives is 0, variance σ2Additive white Gaussian noise；h0(i, j) is multipath fading coefficient, | h0(i, j) | clothes
The rayleigh distributed for being 1 from mean value；gqExpression path loss, q=0,1；Expression shadow fading, q=0,1；
The signal-to-noise ratio that macro user terminal receives are as follows:
In order to meet the target signal to noise ratio γ of Hong YonghuchuT, the transmission power of macro base station meets the following conditions:
S12, in downlink transmission, micro-base station receives the signal of macro base station are as follows:
Wherein, n1(i, j) is that the mean value that micro-base station receives is 0, variance σ2Additive white Gaussian noise；
Therefore the signal-to-noise ratio at micro-base station are as follows:
It willWithIt brings intoIn, then the signal-to-noise ratio at micro-base station can indicate are as follows:
3. it is according to claim 1 it is a kind of in heterogeneous network between macro base station and user distance passive type estimation method,
It is characterized in that, the step S22 specifically:
A1, due to | h0| and | h1| the rayleigh distributed that mean value is 1 is obeyed, therefore, φ=| h1|2/|h0|2Cumulative Distribution Function
Are as follows:
A2、Θr=10log10The Cumulative Distribution Function of (φ) are as follows:
A3, the result of step A1 is brought into step A2 and obtains that Θ can be obtained in resultrCumulative Distribution Function are as follows:
A4, by step A3 acquired results to θrIntegral can obtain ΘrCumulative Distribution Function:
A5, due toWithObeying mean value is 0, and variance isLogarithm normal distribution, therefore, ΘsObeying mean value is 0, side
Difference isNormal distribution, then ΘsCumulative Distribution Function are as follows:
A6, γ is obtained according to the result of step A4 and step A51,dBCumulative Distribution Function are as follows:
A7, orderThen A6 obtains γ1,dBCumulative Distribution Function may be expressed as:
4. it is according to claim 1 it is a kind of in heterogeneous network between macro base station and user distance passive type estimation method,
It is characterized in that, the step S24 specifically:
S241, independent data blocks a for I, micro-base station measure the signal-to-noise ratio of J sub-block in each independent data block, in total
It can detecte K=IJ independent signal-to-noise ratio,
γ1,dB(i,j)(1≤i≤I,1≤j≤J)；
S242, the γ for obtaining step S2411,dB(i, j) (1≤i≤I, 1≤j≤J) is expressed asAnd it is right
It carries out ascending order arrangement, it may be assumed that
S243, when K be odd number when, sample medianThen γ1,dBIt can be approximated to be:
S244, obtained according to the definition to result, the result that step S243 is obtained and median of step S23 macro base station with it is macro
The distance between user d0Estimated value
S245, when K be even number when, sample medianIt is inWithBetween, then γ1,dBIt can be approximate
Are as follows:
S246, obtained according to the definition to result, the result that step S245 is obtained and median of step S23 macro base station with it is macro
The distance between user d0Estimated value
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| CN102006599A (en) * | 2010-11-05 | 2011-04-06 | 北京邮电大学 | Interference suppression method of hybrid network of macrocell and Femtocell |
| CN103763721A (en) * | 2014-01-07 | 2014-04-30 | 电子科技大学 | Passive receiver detection and spectrum access method for heterogenous network |
| CN103780316A (en) * | 2014-01-07 | 2014-05-07 | 电子科技大学 | Passive receiver detection method used for cognizing radio spectrum sharing |
| CN104010341A (en) * | 2014-06-06 | 2014-08-27 | 电子科技大学 | Relay selection and power control method for efficient collaboration multicasting communication |
| WO2016079656A1 (en) * | 2014-11-18 | 2016-05-26 | Egypt-Japan University Of Science And Technology | Zero-calibration accurate rf-based localization system for realistic environments |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102006599A (en) * | 2010-11-05 | 2011-04-06 | 北京邮电大学 | Interference suppression method of hybrid network of macrocell and Femtocell |
| CN103763721A (en) * | 2014-01-07 | 2014-04-30 | 电子科技大学 | Passive receiver detection and spectrum access method for heterogenous network |
| CN103780316A (en) * | 2014-01-07 | 2014-05-07 | 电子科技大学 | Passive receiver detection method used for cognizing radio spectrum sharing |
| CN104010341A (en) * | 2014-06-06 | 2014-08-27 | 电子科技大学 | Relay selection and power control method for efficient collaboration multicasting communication |
| WO2016079656A1 (en) * | 2014-11-18 | 2016-05-26 | Egypt-Japan University Of Science And Technology | Zero-calibration accurate rf-based localization system for realistic environments |
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