CN108494445B - Down channel estimation method based on uplink channel information auxiliary in extensive MIMO - Google Patents
Down channel estimation method based on uplink channel information auxiliary in extensive MIMO Download PDFInfo
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- CN108494445B CN108494445B CN201810042658.7A CN201810042658A CN108494445B CN 108494445 B CN108494445 B CN 108494445B CN 201810042658 A CN201810042658 A CN 201810042658A CN 108494445 B CN108494445 B CN 108494445B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
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- H—ELECTRICITY
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- H04L25/0224—Channel estimation using sounding signals
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- H—ELECTRICITY
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- 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
- H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
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Abstract
The invention discloses a kind of Downlink channel estimation methods of extensive MIMO communication system based on uplink traffic channel information auxiliary, comprising: step 1: base station uses the uniform linear array with N root antenna, and mobile subscriber uses single antenna.Mobile subscriber's pilot signal transmitted after base station receives signal, goes out uplink channel using classical Least Square Method, is denoted asStep 2: base station pilot signal transmitted matrix X within T moment, the then signal that mobile subscriber receives are denoted as y.Step 3: initialization correlated variables l, w,α andβ.Step 4: α is updated,γ and τ.Step 5: updating β.Step 6: judge whether iteration count variable l reaches whether the upper limit L or γ restrain, if be all unsatisfactory for, iteration count variable l=l+1, and return step 4.Step 7: setting thresholding η, and utilize the effective angle set omega of thresholding selection downlink channel.Step 8: utilizing effective angle set omega, estimate final downlink channel
Description
Technical field
The invention belongs to wireless communication field, be related to a kind of multiple-input and multiple-output (Multi-input Multi-output,
MIMO) the channel estimation methods of communication system, it is specifically a kind of based on the extensive of uplink traffic channel information auxiliary
The Downlink channel estimation method of MIMO communication system.
Background technique
Multiple-input and multiple-output (Multi-input Multi-output, MIMO) technology has become the core of future communication systems
One of heart technology, while also will be one of core technology used by WLAN standard.MIMO communication system is on a large scale
Tens of even hundreds of or more antennas are centrally placed in finger in base station coverage area in a manner of large scale array.Due to possessing
The spatial degrees of freedom of hundreds of antenna element, extensive mimo system is higher, can be by energy using beam-forming technology
Lesser region is concentrated on, transmission rate is greatly improved and improves energy efficiency.Extensive mimo system is expected to from root
The spectrum efficiency and energy efficiency that mobile communication is solved the problems, such as in sheet have become one of the important technology of 5G mobile communication.
Channel estimation is the basis of signal of communication detection and Adaptive Transmission, is played to the performance of communication system most important
Effect.Since the antenna number of base station is more, the Downlink channel estimation of extensive mimo system becomes abnormal difficult, people
The angle restored from sparse signal has been attempted, some sparse downlink link channel estimation sides based on Fourier transform are proposed
Method.Such as in document Rao X.and Lau V.K., Distributed compressive CSIT estimation and
feedback for FDD multi-user massive MIMO systems,IEEE Transactions on Signal
It is proposed in Processing, 62 (12) (2014) 3261-3271 a kind of based on l1The channel of the Fourier transform of-norm is estimated
Meter method.But the main bottleneck of existing method first is that: single observation sample is only utilized in corresponding rarefaction representation optimization problem
This.Therefore, additional observation sample information is made full use of, it will help improve the performance of Downlink channel estimation.
Summary of the invention
For the deficiency of existing method, the invention proposes a kind of based on the extensive of uplink traffic channel information auxiliary
The Downlink channel estimation method of MIMO communication system.
Include the following steps: for realizing technical solution of the invention
Step 1: base station uses the uniform linear array with N root antenna, and mobile subscriber uses single antenna.It is mobile
User's pilot signal transmitted after base station receives signal, goes out uplink channel using classical Least Square Method, is denoted as
Step 2: base station pilot signal transmitted matrix X within T moment, the then signal that mobile subscriber receives are y=Φ
(β)w+n。
Step 3: setting the number of iterations counting variable l=1 initializes the precision vector of wIn each element be
1, initializationPrecision vectorIn each element be 1, initialize noise precisionβ is initialized simultaneously
For full neutral element.
Step 4: α is updated,γ and τ.
Step 5: updating β.
Step 6: judge whether iteration count variable l reaches whether the upper limit L or γ restrain, if be all unsatisfactory for, iteration
Counting variable l=l+1, and return step 4.
Step 7: setting thresholding η, and utilize the effective angle set omega of thresholding selection downlink channel.
Step 8: utilizing effective angle set omega, estimate final downlink channel.
Beneficial effects of the present invention:
Uplink traffic channel information is fused in Downlink channel estimation by the present invention, using uplink channel under
The joint sparse characteristic of Downlink channels, so that the available observation sample quantity of corresponding rarefaction representation optimization problem improves
One times.Compared with the conventional method, the present invention can significantly improve the performance of channel estimation
Detailed description of the invention
Fig. 1 is implementation flow chart of the present invention.
Under the conditions of Fig. 2 is 200 Monte Carlo Experiments, when signal-to-noise ratio is 0dB, when pilot tone moment T is by 30 to 100 variation,
Compared with the present invention estimates the normalization root-mean-square error (NMSE) of channel with conventional Fourier Transform method respectively.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples.
As shown in Figure 1, the method for the present invention includes following steps:
(1) base station uses the uniform linear array with N root antenna, and mobile subscriber uses single antenna.It is mobile to use
Family pilot signal transmitted after base station receives signal, goes out uplink channel using classical Least Square Method, is denoted asAnd it is expressed as the form of sparse signal recovery:Wherein:
The referred to as calculation matrix of uplink,
Expression is evenly dividingN number of mesh point, i.e.,
dn, n=1,2 ..., N, the spacing of expression the n-th array element and the 1st array element,Indicate uplink electrical magnetic wave
Wavelength,
In element βiIndicate θiOn angular deviation,
It is channel in calculation matrixOn rarefaction representation vector,
E is that the mean value of a N-dimensional is 0, and precision isWhite Gaussian noise vector.
(2) base station pilot signal transmitted matrix X within T moment, the then signal that mobile subscriber receives are y=Φ (β)
W+n, wherein
Φ (β)=XA (β) is known as the calculation matrix of downlink,
A (β)=[a (θ1+β1),a(θ2+β2),...,a(θN+βN)],
λ indicates the wavelength of downlink electromagnetic wave,
W is rarefaction representation vector of the channel on calculation matrix Φ (β),
N is that the mean value of T dimension is 0, and precision is the white Gaussian noise vector of α.
(3) the number of iterations counting variable l=1 is set, the precision vector of w is initializedIn each element be 1, just
BeginningizationPrecision vectorIn each element be 1, initialize noise precisionIt is complete for initializing β simultaneously
Neutral element.
(4) α is updated,γ and τ, it may be assumed that
Wherein:
The mark of tr () representing matrix, | | | |22 norms of representing matrix, []iiI-th of representing matrix is diagonal
Line element, ()HExpression conjugate transposition, a=b=0.0001,
μ (α, γ, β)=α Σ (α, γ, β) ΦH(β) y, Σ (alpha, gamma, β)=(α ΦH(β)Φ(β)+diag(γ))-1
⊙ indicates Hadamard product,
Diag () indicates diagonal operation matrix, Ξ (alpha, gamma, β)=μ (alpha, gamma, β) μH(alpha, gamma, β)+Σ (alpha, gamma, β),
(5) β is updated, it may be assumed that
Wherein
Sign () expression takes sign operation,
Re () expression takes real part operation,
ci1=-α (χii+|μi|2),
μiIndicate i-th of element of μ (alpha, gamma, β), χjiIt indicates Σ (α, γ, β)
(j, i) a element,
(·)*Indicate conjugate operation, a'(θi+βi) indicate a (θi+βi) about βiDerivative,
It indicatesI-th of element,It indicates(j, i) a element,It indicatesAbout βiDerivative.
(6) judge whether iteration count variable l reaches upper limit L (such as L=100) or whether γ restrains (i.e. when secondary update
As a result whether equal result was updated with last time), if be all unsatisfactory for, iteration count variable l=l+1, and return to (4).
(7) thresholding is setWhereinIndicate the maximum element of i-th of value in μ (alpha, gamma, β), and
Using the thresholding choose downlink channel effective angle set omega=i | (μi)2>=η, i=1,2 ..., N }.
(8) effective angle set omega is utilized, estimates final downlink channel:Wherein
(·)ΩIndicate by the corresponding Column vector groups of set omega in matrix at submatrix,The generalized inverse of representing matrix.
Effect of the invention is described further below with reference to emulation experiment.
In order to assess the performance of this method, it is assumed that base station uses the homogenous linear battle array with N=150 root antenna
Column, the working frequency of downlink are 1980MHz, and the working frequency of downlink is 2170MHz, and wireless channel is by 3GPP
Spatial channel model (SCM) model is randomly generated, and each element of base station pilot signal transmitted matrix X obeys zero
The independent Gaussian of mean value unit variance is distributed, and ambient noise is assumed to be white Gaussian noise.
Experiment condition
Use the present invention in signal-to-noise ratio for 0dB, pilot tone moment T is estimated by carrying out 200 times to channel when 30 to 100 variation,
Simulation result is as shown in Figure 2.
Experimental analysis
Figure it is seen that the present invention can accurately estimate out the downlink channel of extensive MIMO communication system,
NMSE performance is substantially better than conventional method.
The series of detailed descriptions listed above only for feasible embodiment of the invention specifically
Protection scope bright, that they are not intended to limit the invention, it is all without departing from equivalent implementations made by technical spirit of the present invention
Or change should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of Downlink channel estimation method of the extensive MIMO communication system based on uplink traffic channel information auxiliary,
It is characterized by comprising the following steps:
Step 1: using a uniform linear array with N root antenna, mobile subscriber uses single antenna, mobile subscriber's hair for base station
After sending pilot signal, base station to receive signal, uplink channel is gone out using classical Least Square Method, is denoted asWherein,For the calculation matrix of uplink,It is channel in calculation matrixOn it is sparse
Indicate that vector, e are that the mean value of a N-dimensional is 0, precision isWhite Gaussian noise vector；
Step 2: base station pilot signal transmitted matrix X within T moment, the then signal that mobile subscriber receives are y=Φ (β) w+
n；Wherein, Φ (β) is known as the calculation matrix of downlink, and w is rarefaction representation vector of the channel on calculation matrix Φ (β), and n is
The mean value of one T dimension is 0, and precision is the white Gaussian noise vector of α；
Step 3: the initial value of setting the number of iterations counting variable l is l=1, initializes the precision vector of wIn it is each
Element is 1, initializationPrecision vectorIn each element be 1, initialize noise precisionJust simultaneously
Beginningization β is full neutral element；
Step 4: α is updated,γ and τ；
Step 5: updating β；
Step 6: judge whether iteration count variable l reaches whether the upper limit L or γ restrain, if be all unsatisfactory for, iteration count
Variable l=l+1, and return step 4；
Step 7: setting thresholding η, and utilize the effective angle set omega of thresholding selection downlink channel；
Step 8: utilizing effective angle set omega, estimate final downlink channel；
α is updated in the step 4,The method of γ and τ are as follows:
Wherein:
The mark of tr () representing matrix, | | | |22 norms of representing matrix, []iiI-th of diagonal entry of representing matrix,
(·)HExpression conjugate transposition, a=b=0.0001,
μ (α, γ, β)=α Σ (α, γ, β) ΦH(β) y, Σ (alpha, gamma, β)=(α ΦH(β)Φ(β)+diag(γ))-1
⊙ indicates Hadamard product,
Diag () indicates diagonal operation matrix, Ξ (alpha, gamma, β)=μ (alpha, gamma, β) μH(alpha, gamma, β)+Σ (alpha, gamma, β),
The method of β is updated in the step 5 are as follows:
Wherein:
Sign () expression takes sign operation,
Re () expression takes real part operation,
μiIndicate i-th of element of μ (alpha, gamma, β), χjiIndicate Σ (α, γ, β) the (j,
I) a element,
(·)*Indicate conjugate operation, a'(θi+βi) indicate a (θi+βi) about βiDerivative,
It indicatesI-th of element,It indicates?
(j, i) a element,It indicatesAbout βiDerivative；
The expression formula of the effective angle set omega are as follows: Ω=i | (μi)2>=η, i=1,2 ..., N }；
The final downlink channel estimated in the step 8Wherein ()ΩIt indicates by matrix
The corresponding Column vector groups of middle set omega at submatrix,The generalized inverse of representing matrix；
Wherein,In element βiIndicate θiOn angular deviation.
2. under a kind of extensive MIMO communication system based on uplink traffic channel information auxiliary according to claim 1
Downlink channels estimation method, which is characterized in that in the step 1Wherein
Expression is evenly dividingN number of mesh point, i.e.,
dn, n=1,2 ..., N, the spacing of expression the n-th array element and the 1st array element,Indicate the wavelength of uplink electrical magnetic wave,In element βiIndicate θiOn angular deviation.
3. under a kind of extensive MIMO communication system based on uplink traffic channel information auxiliary according to claim 2
Downlink channels estimation method, which is characterized in that Φ (β)=XA (β) in the step 2, in which:
A (β)=[a (θ1+β1),a(θ2+β2),...,a(θN+βN)]
λ indicates downlink chain
The wavelength of road electromagnetic wave.
4. under a kind of extensive MIMO communication system based on uplink traffic channel information auxiliary according to claim 1
Downlink channels estimation method, which is characterized in that the expression formula of the thresholding η in the step 7 are as follows:Its
InIndicate the maximum element of i-th of value in μ (α, γ, β).
5. a kind of extensive MIMO communication based on uplink traffic channel information auxiliary according to claim 1-4
The Downlink channel estimation method of system, which is characterized in that the L is set as 100, and the N is set as 150.
6. a kind of extensive MIMO communication based on uplink traffic channel information auxiliary according to claim 1-4
The Downlink channel estimation method of system, which is characterized in that pilot tone moment T is 30 to 100.
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Non-Patent Citations (2)
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| 《Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems》;Xiongbin Rao等;《IEEE TRANSACTIONS ON SIGNAL PROCESSING》;20140615;第62卷(第12期);3261-3271 * |
| 《Massive MIMO通信系统中信道估计技术研究》;谢建超;《中国知网》;20161118;44-47 * |
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