CN108737299A - A kind of LMMSE channel estimation methods of low complex degree - Google Patents
A kind of LMMSE channel estimation methods of low complex degree Download PDFInfo
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- CN108737299A CN108737299A CN201810450594.4A CN201810450594A CN108737299A CN 108737299 A CN108737299 A CN 108737299A CN 201810450594 A CN201810450594 A CN 201810450594A CN 108737299 A CN108737299 A CN 108737299A
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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
- H04L25/0256—Channel estimation using minimum mean square error criteria
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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
- H04L25/022—Channel estimation of frequency 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
- H04L25/0224—Channel estimation using sounding signals
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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
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Abstract
The present invention relates to a kind of LMMSE channel estimation methods of low complex degree, belong to wireless communication field.This approach includes the following steps：S1：Using end pilot frequency sequence is sent and received, the time domain impulse response of pilot tone is obtainedS2：Using the channel estimation value at pilot sub-carrier, channel autocorrelation matrix and signal-to-noise ratio are quickly estimated；S3：Using the fast inversion method of circular matrix, LMMSE estimated matrix is obtainedS4：Using the property of toeplitz matrix vector product, the LMMSE channel estimation values of pilot tone are quickly calculatedThe present invention ensures system performance again in channel estimation while reducing complexity.
Description
Technical field
The invention belongs to wireless communication fields, are related to a kind of LMMSE channel estimation methods of low complex degree.
Background technology
In broadband wireless communications field, since orthogonal frequency division multiplexi can greatly alleviate intersymbol interference, thus obtain
Extensive use is arrived.It due to channel meeting occurrence frequency Selective intensity, and changes over time, it is therefore desirable to pass through channel estimation pair
Channel directly affects the performance of ofdm system in time and the enterprising line trace of frequency domain, the performance of channel estimation.Accurate channel is estimated
Meter is particularly significant for OFDM technology.
Many channel estimation techniques such as least square (Least Squares, LS) and linear minimum mean-squared error
(Linear Minimum Mean Squared Error, LMMSE) has been suggested, and the advantages of LS algorithms is that complexity is low, but its
The influence of noise is had ignored, channel estimating performance is poor.Traditional LMMSE channel estimation methods are based on the channel auto-correlation in frequency domain
Matrix needs the second-order statistics information that channel is known in advance, also relates to the inversion operation of matrix, keeps algorithm complexity higher.
Although LMMSE algorithms belong to optimal filter, it has two big disadvantages to limit its practical application.(1) algorithm is multiple
Miscellaneous degree is very high, and traditional LMMSE channel algorithms there are higher dimensional matrix due to inverting and product calculation, complexity are up to(2) the second-order statistics information of receiving terminal channel and noise is needed, but can not often be obtained in advance in practice.
Therefore, in order to solve problem above, a kind of LMMSE algorithms of low complex degree are needed, algorithm complexity is being reduced
Also ensure that system channel estimates performance simultaneously.
Invention content
In view of this, the purpose of the present invention is to provide one kind being based on FFT operations, cycle shift operation, and quickly support
The LMMSE channel estimation methods of Puli's hereby low complex degree of matrix-vector product, ensure that estimation while reducing complexity
Performance.
In order to achieve the above objectives, the present invention provides the following technical solutions：
A kind of LMMSE channel estimation methods of low complex degree, ensure system performance, this method while reducing complexity
Specifically include following steps：
S1：Using end pilot frequency sequence is sent and received, the time domain impulse response of pilot tone is obtained
S2：Using the channel estimation value at pilot sub-carrier, channel autocorrelation matrix and signal-to-noise ratio are quickly estimated；
S3：Using the fast inversion method of circular matrix, linear minimum mean-squared error (Linear Minimum are obtained
Mean Squared
Error, LMMSE) estimated matrix
S4：Using the property of toeplitz matrix vector product, the LMMSE channel estimation values of pilot tone are quickly calculated
Further, the step S1 includes the following steps：
S11：Pilot tone Y is extracted in all reception signalsP, calculated using least square (Least Squares, LS) algorithm
Domain channel response at pilot sub-carrier
Wherein, XPIndicate the local pilot frequency sequence of transmission antenna, NpRepresent total pilot number, H (Np) indicate NpA pilot tone
The domain channel response value at place；
S12：Carry out fast fourier inverse transformation (Inverse Fast Fourier Transform, IFFT) operation, meter
LS channel response of the calculation pilot sub-carrier in time domain
Wherein,Indicate NpTime domain channel response value at a pilot tone.
Further, the step S2 includes the following steps：
S21：Its energy P is found out according to the channel impulse response in time domain：
Wherein, P (Np) indicate NpEnergy at a pilot tone；
S22：It according to the multipath item number L of setting, finds the preceding L maximum in P and is worth to P1, and by its respective index information
It is put into set α, remaining then sets to 0, and is shown below：
Wherein, k=0,1 ..., NP-1；
S23：Noise variance energy PnoiseFor
Channel energy PchFor
Signal-to-noise ratio is
S24：Channel autocorrelation matrixIt is circular matrix, therefore need to only estimates its first row, channel auto-correlation is estimated
Count matrixThe first row be denoted as
Autocorrelation matrix to the first row cyclic shift by obtaining complete matrix.
Further, the step S3 includes：LMMSE matrixesIts estimated matrix is denoted asWhereinIt is channel autocorrelation matrix, β is the constellation factor of diagram depending on modulation system, and SNR is average signal-to-noise ratio,
It is NP×NPUnit matrix；
Due to autocorrelation matrixIt is circular matrix, due to the addition of circular matrix, to be multiplied and invert be Cyclic Moment
Battle array, thereforeWithIt is also circular matrix.Therefore
It can be inverted by the fast inversion method of circular matrix.Equally we only need to calculate the first row, and LMMSE is estimated square
Battle arrayThe first row be denoted asThen
Wherein, β is the constellation factor of diagram depending on modulation system；
The similarly step S3, LMMSE estimated matrixBy being obtained to its first row LMMSE estimated matrix cyclic shifts
Complete matrix.
Further, the step S3 includes：Estimate LMMSE estimated matrixAfterwards, the LMMSE channel estimation values of pilot toneFor：
Wherein,Indicate LS domain channel responses at pilot sub-carrier；
The computational complexity of traditional matrix and vector product isIt, will using the property of toeplitz matrixIt indicates toeplitz matrix vector product, quickly calculates, computation complexity is down to O (Nplog Np)；
First, toeplitz matrixBy extended below for 2NP×2NPMatrix：
Wherein wijIndicate toeplitz matrixElement；
NoteCircular matrixThe IFFT matrixes being normalizedDiagonalization：
WhereinExpression pairThe matrix obtained after complex conjugate transposition is carried out,Expression formula is：
Wherein
Therefore,Product representation be：
Operated by FFT, the complexity of product fromIt is down to O (NplogNp)。
The beneficial effects of the present invention are：
There are three advantages compared to tradition LMMSE algorithms by the present invention：1) present invention need not obtain in advance autocorrelation matrix and
Signal-to-noise ratio, but least mean-square error performance is sufficiently close to bit error rate performance and tradition LMMSE algorithms；2) present invention by using
The characteristics of channel autocorrelation matrix, based on FFT operations, cycle shift operation, and quickly toeplitz matrix vector product, and
Without carrying out inversion operation to higher dimensional matrix, since there are matrix inversion operation, the calculating of traditional LMMSE channel estimation methods is multiple
Miscellaneous degree is up to(wherein NpRepresent pilot number total in an OFDM symbol), computational complexity of the invention is reduced to O
(NPlogNP)；3) present invention can track channel variation, i.e. channel autocorrelation matrix and signal-to-noise ratio, and traditional LMMSE algorithms are not
Channel ratio can be tracked.Once channel parameter changes, parameter mismatch will cause LMMSE performances to decline.
Description of the drawings
In order to keep the purpose of the present invention, technical solution and advantageous effect clearer, the present invention provides following attached drawing and carries out
Explanation：
Fig. 1 is the flow diagram of the LMMSE channel estimation methods of low complex degree of the present invention；
Fig. 2 is LS channel estimation methods, ideal LMMSE algorithms, based on singular value decomposition under EVA70 channel conditions
The bit error rate of LMMSE algorithms and quick LMMSE proposed by the present invention compare analogous diagram；
Fig. 3 is LS channel estimation methods, ideal LMMSE algorithms, based on singular value decomposition under ETU100 channel conditions
The bit error rate of LMMSE algorithms and quick LMMSE proposed by the present invention compare analogous diagram.
Specific implementation mode
Below in conjunction with attached drawing, the preferred embodiment of the present invention is described in detail.
Attached drawing 1 is a kind of flow diagram of the LMMSE channel estimation methods of low complex degree of the present invention, by Fig. 1
It is found that a kind of LMMSE channel estimation methods of low complex degree include the following steps：
The first step obtains the time domain impulse response of pilot tone using end pilot frequency sequence is sent and received
(1) pilot tone Y is extracted in all reception signalsP, domain channel response at pilot sub-carrier is calculated using LS algorithms
Wherein XPIndicate the local pilot frequency sequence of transmission antenna；
(2) IFFT operations, LS channel response of the calculating pilot sub-carrier in time domain are carried out：
Second step carries out channel autocorrelation matrix and signal-to-noise ratio quick using the channel estimation value at pilot sub-carrier
Estimation.
(1) its energy P is found out according to the channel impulse response in time domain；
(2) it according to the multipath item number L of setting, finds the preceding L maximum in P and is worth to P1, and by its respective index information
It is put into set α, remaining then sets to 0, and is shown below：
Wherein, k=0,1 ..., NP-1；
(3) noise variance energy PnoiseFor
Channel energy PchFor
Signal-to-noise ratio is
(4) autocorrelation matrixIt is circular matrix, therefore need to only estimates its first row, by matrixThe first row
It is denoted as
Autocorrelation matrix can be by the first rowCyclic shift obtains complete matrix.
Third walks, and using the fast inversion method of circular matrix, obtains the estimation of LMMSE matrixes
Due to autocorrelation matrixIt is circular matrix, due to the addition of circular matrix, to be multiplied and invert be Cyclic Moment
Battle array, thereforeWithIt is also circular matrix.Therefore
It can be inverted by the fast inversion method of circular matrix.Equally we only need to calculate the first row, by LMMSE matrixes
The first row be denoted asThen
Similarly, LMMSE matrixesIt can be by shifting to obtain complete matrix to its first row LMMSE matrix circulars.
4th step quickly calculates the LMMSE channel estimation values of pilot tone using the property of toeplitz matrix vector product
After estimating LMMSE channel estimate matrixs, LMMSE channel estimation methods can be obtained by following formula：
The computational complexity of traditional matrix and vector product isIt, will using the property of toeplitz matrixIt indicates toeplitz matrix vector product, can quickly calculate, computation complexity can be down to O (Nplog Np)。
First, toeplitz matrixBy extended below for 2NP×2NPMatrix：
Wherein wijIndicate toeplitz matrixElement；
NoteCircular matrixThe IFFT matrixes being normalizedDiagonalization：
WhereinExpression pairThe matrix obtained after complex conjugate transposition is carried out,Expression formula is：
Wherein
Therefore,Product representation be：
Operated by FFT, the complexity of product fromIt is down to O (Nplog Np)。
Embodiment
Using the setting of the channel simulator parameter of table 1, emulation testing is carried out to the channel estimation methods of the present invention, verification is originally
The estimation performance of invention.
Table 1
Fig. 2,3 simulate LS channel estimation methods, ideal LMMSE algorithms, base under conditions of assuming that system is fully synchronized
In singular value decomposition (Singular Value Decomposition, SVD) LMMSE algorithms and it is proposed by the present invention quickly
LMMSE respectively under the channel condition of EVA70 and ETU100 under the bit error rate compare.It can be seen that from Fig. 2,3, it is proposed by the invention
Quick LMMSE be sufficiently close to ideal LMMSE performance curves, and be substantially better than LS channel estimation methods and SVD-LMMSE and calculate
Method.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (5)
1. a kind of LMMSE channel estimation methods of low complex degree, which is characterized in that ensure systematicness while reducing complexity
Can, this method specifically includes following steps：
S1：Using end pilot frequency sequence is sent and received, the time domain impulse response of pilot tone is obtained
S2：Using the channel estimation value at pilot sub-carrier, channel autocorrelation matrix and signal-to-noise ratio are quickly estimated；
S3：Using the fast inversion method of circular matrix, linear minimum mean-squared error (Linear Minimum Mean are obtained
Squared Error, LMMSE) estimated matrix
S4：Using the property of toeplitz matrix vector product, the LMMSE channel estimation values of pilot tone are quickly calculated
2. a kind of LMMSE channel estimation methods of low complex degree according to claim 1, which is characterized in that the step
S1 includes the following steps：
S11：Pilot tone Y is extracted in all reception signalsP, pilot tone is calculated using least square (Least Squares, LS) algorithm
Domain channel response at subcarrier
Wherein, XPIndicate the local pilot frequency sequence of transmission antenna, NpRepresent total pilot number, H (Np) indicate NpAt a pilot tone
Domain channel response value；
S12：Fast fourier inverse transformation (Inverse Fast Fourier Transform, IFFT) operation is carried out, calculating is led
LS channel response of the frequency subcarrier in time domain
Wherein,Indicate NpTime domain channel response value at a pilot tone.
3. a kind of LMMSE channel estimation methods of low complex degree according to claim 1, which is characterized in that the step
S2 includes the following steps：
S21：Its energy P is found out according to the channel impulse response in time domain：
Wherein, P (Np) indicate NpEnergy at a pilot tone；
S22：According to the multipath item number L of setting, finds the preceding L maximum in P and be worth to P1, and its respective index information is put into
Set α, remaining then sets to 0, and is shown below：
Wherein, k=0,1 ..., NP-1；
S23：Noise variance energy PnoiseFor
Channel energy PchFor
Signal-to-noise ratio is
S24：Channel autocorrelation matrixIt is circular matrix, therefore need to only estimates its first row, by channel autocorrelation estimation square
Battle arrayThe first row be denoted as
Autocorrelation matrix to the first row cyclic shift by obtaining complete matrix.
4. a kind of LMMSE channel estimation methods of low complex degree according to claim 1, which is characterized in that the step
S3 includes：By LMMSE estimated matrixThe first row be denoted asThen
Wherein, β is the constellation factor of diagram depending on modulation system；LMMSE estimated matrixBy estimating its first row LMMSE
Matrix circular shifts to obtain complete matrix.
5. a kind of LMMSE channel estimation methods of low complex degree according to claim 1, which is characterized in that the step
S3 includes：Estimate LMMSE estimated matrixAfterwards, the LMMSE channel estimation values of pilot toneFor：
Wherein,Indicate the LS domain channel responses at pilot sub-carrier；
The computational complexity of traditional matrix and vector product isIt, will using the property of toeplitz matrix
It indicates toeplitz matrix vector product, quickly calculates, computation complexity is down to O (NplogNp)；
First, toeplitz matrixBy extended below for 2NP×2NPMatrix：
Wherein wijIndicate toeplitz matrixElement；
NoteCircular matrixThe IFFT matrixes being normalizedDiagonalization：
WhereinExpression pairThe matrix obtained after complex conjugate transposition is carried out,Expression formula is：
Wherein
Therefore,Product representation be：
Operated by FFT, the complexity of product fromIt is down to O (NplogNp)。
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Cited By (4)
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| CN109743270A (en) * | 2019-03-25 | 2019-05-10 | 重庆邮电大学 | A kind of channel estimation methods of the multiuser multiplexing based on 5G |
| CN111404847A (en) * | 2020-03-20 | 2020-07-10 | 中山大学 | Channel estimation method of marine communication system |
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