WO2013075278A1

WO2013075278A1 - Frequency offset estimation and channel estimation method and system

Info

Publication number: WO2013075278A1
Application number: PCT/CN2011/082551
Authority: WO
Inventors: 萧少宁; 王竟宇
Original assignee: 中兴通讯股份有限公司
Priority date: 2011-11-21
Filing date: 2011-11-21
Publication date: 2013-05-30

Abstract

Disclosed are a frequency offset estimation and channel estimation method and system. A local demodulation signal and a frequency offset effect matrix can be used to reconstruct a signal received in the scenario of frequency offset; and the frequency offset effect matrix is applied to perform optimum algorithm frequency offset estimation on the reconstructed received signal, thereby obtaining a channel estimation value. The frequency offset estimation and channel estimation technology in the present invention can enable a communication system receiver to accurately perform frequency offset estimation and channel estimation for different users if the signal frequency offset is relatively large, so as to improve the performance of the receiver in the case of multi-user MIMO in the scenario of relatively large user frequency offset.

Description

Method and system for frequency offset estimation and channel estimation

The present invention relates to the field of communications, and in particular, to a method and system for frequency offset estimation and channel estimation. Background technique

When the crystals of the transmitter and receiver of the communication system are not aligned, the received signal is affected by the frequency offset. When the mobile terminal in the wireless communication system moves quickly, the Doppler effect also causes a frequency offset. When the above frequency offset is large, the performance of the receiver is degraded, so the receiver needs to perform frequency offset compensation, and the frequency offset needs to be estimated before performing frequency offset compensation.

Existing technology cannot estimate multi-user multiple input multiple output in orthogonal frequency division multiplexing communication system

Frequency offset in the case of (MIMO). Summary of the invention

In view of this, it is a primary object of the present invention to provide a method and system for frequency offset estimation and channel estimation to implement frequency offset estimation and channel estimation in the case of multi-user MIMO.

In order to achieve the above object, the technical solution of the present invention is achieved as follows:

A method for frequency offset estimation and channel estimation, including:

The local demodulation reference signal and the frequency offset influence matrix are used to reconstruct the received signal in the frequency offset scene. The frequency offset influence matrix is used to perform the optimization algorithm frequency offset estimation on the reconstructed received signal, and the channel estimation value is obtained accordingly.

The process of reconstructing the received signal includes:

In the case of multi-user multiple input multiple output MIMO, the received demodulation reference signal is utilized And the locally generated demodulation reference signal obtains a channel impulse response of the reference signal portion, and reconstructs the received signal in the frequency offset scene by constructing a frequency offset influence matrix ^M ) embodied in the form of a Toeplitz matrix to obtain correlation System equation.

The process of reconstructing the received signal includes:

When two users are involved, for a resource block at the demodulation reference signal, there is the following system equation:

Yv =M{f _l ) diag (Ρ, )ί _Λ +Μ (f ₂ ) diag(P ₂ ) ₂ + η _γ yi

Diag (P, ) h _2l +M(f ₂ ) diag(P ₂ ) h _2a + n ₂

y ₃ =M(f _l ) diag(P ₃ ) 1 &χρ(ί2π/ _ι ί) + M(f ₂ ) diag(P ₄ ) 1 ₂ exp( 2^" f ₂ t) + / _3⁄4 y ₄

among them

L ² ′′ is the demodulation reference signal received on the ith antenna, which is the channel impulse response of the jth user on the ith antenna; = 1 or 2, and '· = ³ or ' · = ⁴ The case of the second time slot; ^f , , are the frequency offsets of user 1 and user 2 respectively; the . and , are both unknowns that need to be estimated, and the remaining variables are known quantities;

The individual elements of M (/) = (3⁄4 ) are defined as follows:

f

Where ^ is the normalization, ie bandwidth

Demodulation reference signal "transmitted to the user on the resource block, wherein n-additive noise, the ^{M (/)} is the estimated inverse M (- /). The process of performing the frequency offset estimation of the optimization algorithm includes: after expressing in a matrix form, the formula (*) becomes ^Κ)^" ( ^Δ )

Φ( ,Λ) =

M {f, ) diag(P ₃ ) M (f ₂ ) diag(P ₄ )

M {f, ) diag(P ₃ )

M (f ₂ ) diag(P ₄ )

Where is the coefficient matrix of the formula (*); based on the formula (Δ), the number of variables is reduced by ^J ^^WII by substitution

₇ -φ( ₂ )φ corpse

The following formula is obtained:

According to this, the following equation is obtained:

Where ⁺ ( , / ² ) is the matrix;, / ² ) Moore-Penrose generalized inverse; use the Nelder-Mead simplex search algorithm or Powell algorithm in the optimization algorithm to estimate the frequency offset; after that, use the least squares Least Square algorithm Or the minimum mean square error MMSE algorithm obtains the channel estimate.

Wherein, after performing the frequency offset estimation, using the Least Square algorithm or the MMSE algorithm To the channel estimate.

Wherein, when the Least Square algorithm is applied, the process of obtaining the channel estimation value comprises: calculating ^Φ " according to the estimated frequency offset sum, and then using the Least Square algorithm on the formula ( ^Δ ) to obtain an estimated value of the channel estimation. +(/;, / ₂ ).3 A system for frequency offset estimation and channel estimation, comprising a received signal reconstruction unit and an estimation unit; wherein

The received signal reconstruction unit is configured to reconstruct a received signal in a frequency offset scene by using a local demodulation reference signal and a frequency offset influence matrix;

And the estimating unit is configured to apply the frequency offset influence matrix to perform an optimization algorithm frequency offset estimation on the reconstructed received signal, and obtain a channel estimation value according to the method.

The receiving signal reconstruction unit is configured to: when reconstructing the received signal:

In the case of multiple users, the channel impulse response of the reference signal portion is obtained by using the received demodulation reference signal and the locally generated demodulation reference signal, and the frequency offset influence matrix ^Μ ^· embodied in the form of a Toeplitz matrix is constructed. ^, Reconstruct the received signal in a frequency offset scene to obtain the relevant system equation.

Yv =M(f _l ) diag (Ρ, )ί _Λ +Μ (f ₂ ) diag{P ₂ ) ₂ + η _γ

Yi

^Dia § { ^p i ) i ⁺ ( ₂ ) iag(P ₂ ) h _2a + " ₂

y ₃ t) + n ₃

y ₄ + M(f ₂ ) diag [P ₄ ) h ₂₂ &χρ(ί2π f ₂ t) + n ₄ (*)

^l i,j,2

Where L ² ′′ is the demodulation reference signal received on the ith antenna, L “w ² ′′ is the channel impulse response of the jth user on the ith antenna; = 1 or 2, and, '· = ³ Or ' · = ⁴ is the case of the second time slot; ^f , , are the frequency offsets of user 1 and user 2 respectively; the /^, and are both unknowns to be estimated, and the remaining variables are known quantities;

The individual elements of ^M (/) = (3⁄4 ) are defined as follows:

'When = shot

Sin [πγ] lk ) f . N- ex ]πγ ~ _r 'when shot

N N

Nsin

N f

Where ^ is the normalization, ie bandwidth;

For the demodulation reference signal transmitted user on the resource block, "wherein additive noise, the ^{[mu] (/)} is the estimated inverse Μ (- /).

Wherein, when the estimating unit performs the frequency offset estimation of the optimization algorithm, it is used to: after expressing in a matrix form, the formula (*) becomes ^Κ)^" ( ^Δ )

M {f, ) diag(P ₃ ) M (f ₂ ) diag(P ₄ )

M {f, ) diag(P ₃ )

M (f ₂ ) diag(P ₄ ) where is the coefficient matrix of the formula (*); based on the formula (Δ), by simplification of the number of variables, the following formula is obtained:

^P Hf f2) ^y ; According to this, the following equation is obtained:

Where ⁺ ( , / ² ) is a matrix; , / ² ) Moore-Penrose generalized inverse;

The frequency offset is estimated using the Nelder-Mead simplex search algorithm or the Powell algorithm in the optimization algorithm; after that, the channel estimation value is obtained by using the Least Square algorithm or the MMSE algorithm.

The estimating unit obtains the channel estimation value by using a Least Square algorithm or an MMSE algorithm after performing the frequency offset estimation.

Wherein, when the Least Square algorithm is applied, the estimating unit is configured to: when obtaining the channel estimation value:

Calculate ^Φ " from the estimated frequency offset sum, and then use the Least Square algorithm for the formula ( ^Δ ) to obtain the estimated value of the channel estimate Φ + ( / ₂ ).3.

The receiving signal reconstruction unit and the estimating unit are disposed in the base station. And channel estimation, improve the performance of the receiver in the case of multi-user MIMO when the user frequency is large. DRAWINGS

1 is a schematic diagram of a frequency offset estimation and channel estimation process according to an embodiment of the present invention;

2 is a system diagram of a frequency offset estimation and channel estimation system according to an embodiment of the present invention. detailed description

In practical applications, the base station can first reconstruct the system equation of the receiver at the reference signal position by using the local demodulation reference signal and the frequency offset influence matrix. Specifically, in the case of multi-user MIMO, the channel impulse response of the reference signal portion can be obtained by using the received demodulation reference signal and the locally generated demodulation reference signal, by constructing in the form of a Topplitz Toeplitz matrix. The reflected ^Μ (·^, can reconstruct the received signal in the frequency offset scene to obtain the relevant system equation. The ^M (which can be called the frequency offset influence matrix) mainly describes the influence of the frequency offset on the system. .

For example, taking two users as an example, for a resource block at the demodulation reference signal, there may be the following system equation:

Yv =M(f _l ) diag (Ρ, )ί _Λ +Μ (f ₂ ) diag{P ₂ ) ₂ + η _γ

Yi

^Dia § { ^p i ) i ⁺ ( ₂ ) iag(P ₂ ) h _2a + " ₂

y ₃ t) + n ₃

y ₄ + M(f ₂ ) diag [P ₄ ) h ₂₂ &χρ(ί2π f ₂ t) + n ₄ (*)

Channel impulse response of the jth user on i antennas; = 1 or 2, and '· = ³ or ' · = ⁴ is the case of the second time slot; ^/2 is user 1 and user 2 respectively Frequency offset. It should be noted that , and are both unknowns that need to be estimated, and the remaining variables are known quantities.

The elements of Μ (/) = (3⁄4 ) are defined as follows:

f

Where ^ is the normalization, ie bandwidth

Demodulation reference signal transmitted by the user on the resource block, "for additive noise. Next, using the received signal on each antenna and the mathematical characteristics of the reconstructed portion in the formula (*), ie the inverse approximation is equal to M (-f) (Normally, the computational complexity of the matrix inversion will be large), and the unknown channel estimate /^ can be replaced by a known amount at a small cost to reduce the number of unknowns. Thereby reducing the corresponding amount of calculation. The specific process is as follows: After expressing in matrix form, the formula (*) can be written as ^φ , ² ) ^{Α +} " ( ^Δ )

Φ( ,Λ) = M {f,

M {f,

For the public

A coefficient matrix of equation (*). In practical applications, it is necessary to calculate the respective frequency offsets of the two users and satisfy the formula ( ^Δ ) so that the solution obtained by ■;, and A makes the condition r{f,h) ₌

The result is minimal.

2

Based on the formula (Δ), the number of variables can be changed by ' | _ ^φ , , Simplified, got the following formula:

The above formula transforms the complex maximum likelihood calculation problem similar to the maximum likelihood into a problem of solving the nonlinear least squares sum. Such a problem has a simplified method and can be solved in the optimization algorithm.

So there is the following equation:

= ^φ , , ,

Where ^φ+ , / ₂ ) is the molar-Penrose Moore-Penrose generalized inverse of the matrix ^φ , / ₂ ). Next, we will estimate the pair and A through the above series of problem simplifications.

Through the above simplification, the frequency offset can be estimated using an optimization algorithm, and then the channel estimation value is obtained using a mature estimation algorithm. Specifically, the frequency offset and ^/2 can be estimated first.

^{Φ Φ} ( ) ^Φ+ ( ₂ Ι ² minimum. For the nonlinear least square sum problem represented by condition II, ^/2 ) ^Φ+ ( ) Ι ² , the initial value of the frequency offset sum can be set, and then the optimization is used. In the algorithm, the Neder-Mead Nelder-Mead simplex search algorithm or the Powell Powell algorithm estimates the frequency offset ^^.

The channel estimate can then be obtained using the Least Square algorithm or the approximate minimum mean square error (MMSE) algorithm. For example, taking the Least Square algorithm as an example, calculate ^^) based on the estimated frequency offset sum, and then use the Least Square algorithm for the formula ( ^Δ ) to obtain the estimated value Φ+ ( / ₂ ) of the channel estimate h.

It can be seen from the above description that the operation of the present invention for performing frequency offset estimation and channel estimation can represent the flow shown in FIG. 1, and the process includes the following steps: Step 110: Reconstruct the received signal in the frequency offset scene by using the local demodulation reference signal and the frequency offset influence matrix, such as: reconstructing the system equation of the receiver at the reference signal position by using the local demodulation reference signal and the frequency offset influence matrix. .

Step 120: Apply the frequency offset influence matrix to perform optimization algorithm frequency offset estimation on the reconstructed received signal, and obtain a channel estimation value according to the received signal, and a mathematical part according to the received signal of the receiver and the reconstructed part of the system equation. Characteristic, applying the frequency offset influence matrix to perform unknown quantity substitution on the unknown channel estimate to reduce the number of unknowns; and using the optimization algorithm to estimate the frequency offset for the replaced result, and then using The estimation algorithm obtains channel estimates.

In order to ensure that the above description and operation ideas can be smoothly implemented, the settings shown in Figure 2 can be performed. Referring to FIG. 2, FIG. 2 is a system diagram of a frequency offset estimation and channel estimation system according to an embodiment of the present invention. The system includes a received signal reconstruction unit and an estimation unit, which can be connected to each other.

In practical applications, the received signal reconstruction unit can reconstruct the received signal in the frequency offset scene by using the local demodulation reference signal and the frequency offset influence matrix, such as: reconstructing the reception by using the local demodulation reference signal and the frequency offset influence matrix. The system equation of the machine at the reference signal position. The estimating unit can apply the frequency offset influence matrix to perform optimization algorithm frequency offset estimation on the reconstructed received signal, thereby obtaining channel estimation values, such as: according to the received signal of the receiver and the mathematical part of the reconstructed part of the system equation Characteristic, applying the frequency offset influence matrix to perform unknown quantity substitution on the unknown channel estimate to reduce the number of unknowns; and using the optimization algorithm to estimate the frequency offset for the replaced result, and then using the estimation algorithm The channel estimate is obtained.

In summary, the frequency offset estimation and channel estimation techniques of the present invention enable the communication system receiver to accurately perform frequency offset estimation and channel estimation for different users when the signal frequency offset is large, whether it is a method or a system. Improve the performance of the receiver in the case of multi-user MIMO in a scenario where the user frequency is large; in addition, by constructing a formula

^P A , which can be used for frequency offset estimation and channel estimation Complex operations are transformed into simple operations that solve nonlinear least squares sums, which in turn can be optimized

Claims

Claim

1. A method for frequency offset estimation and channel estimation, comprising:

2. The method of claim 1 wherein the process of reconstructing the received signal comprises: utilizing a received demodulation reference signal and a locally generated demodulation reference signal in the case of multi-user multiple input multiple output MIMO The channel impulse response of the reference signal portion is obtained. By constructing the frequency offset influence matrix ^M ) embodied in the form of a Toeplitz matrix, the received signal in the frequency offset scene is reconstructed to obtain the relevant system equation.

3. The method according to claim 2, wherein the process of reconstructing the received signal comprises: when two users are involved, for a resource block at the demodulation reference signal, the following system side

Yx =M{f _l ) diag (Ρ, )ί _Λ +Μ (f ₂ ) diag{P ₂ ) ₂ + η _γ

Yi

^Dia § { ^p i ) i ⁺ ( ₂ ) iag(P ₂ ) h _2a + " ₂

y ₃ t) + n ₃

y ₄ + M(f ₂ ) diag {P ₄ ) h ₂₂ οχρ(ί2π f ₂ t) + " ₄

Channel impulse response of the jth user on i antennas; = 1 or 2, and '· = ³ or ' · = ⁴ is the case of the second time slot; ^f , , respectively, for user 1 and user 2 Frequency offset; the /^, and are all unknowns that need to be estimated, and the remaining variables are known quantities; The individual elements of (/) = (3⁄4 ) are defined as follows:

f

Where ^ is the normalization, ie bandwidth

A demodulation reference signal transmitted by the user on the resource block, "is additive noise.

4. The method according to claim 3, wherein said inverse calculation is Μ(-/).

5. The method according to claim 4, wherein the process of performing the frequency offset estimation of the optimization algorithm comprises:

After expressing in matrix form, the formula (*) becomes ^Κ)^" ( ^δ )

For the public

a coefficient matrix of equation (*);

Based on the formula (Δ), the number of variables is reduced by substituting ^ Ι^Φί 'Λ^Ι ² , and the following formula is obtained: , / ₂ ) ⁼ Ι^ ^φ p

, / ₂ ) ^φ+ , / ₂ )· ; According to this, the following equation is obtained: 仏Λ )

, - l|2

₇ -Φ(/;, ₂ )Φ ⁺ (/;, ₂ )3

^P Hf f2) ^y where ⁺ ( , / ² ) is a matrix; , / ² ) Moore-Penrose generalized inverse;

The frequency offset is estimated using the Nelder-Mead simplex search algorithm or the Powell algorithm in the optimization algorithm; thereafter, the channel estimate is obtained using a least squares Least Square algorithm or a minimum mean square error MMSE algorithm.

6. The method according to claim 5, wherein, after performing the frequency offset estimation, the channel estimation value is obtained by using a Least Square algorithm or an MMSE algorithm.

7. The method according to claim 6, wherein, when the Least Square algorithm is applied, the process of obtaining the channel estimation value comprises:

Based on the estimated frequency offset sum, ^φ , / _{2 is} calculated and the Least Square algorithm is used for the formula ( ^Δ ) to obtain the estimated value of the channel estimate Φ + ( / ; , / ₂ ).

8. A system for frequency offset estimation and channel estimation, comprising a received signal reconstruction unit and an estimation unit; wherein

The system according to claim 8, wherein the received signal reconstruction unit is configured to: when reconstructing the received signal: The frequency offset in the form of the matrix affects the matrix ^M(/ ), reconstructing the received signal in a frequency-biased scene to obtain the relevant system equations.

10. The system according to claim 9, wherein the received signal reconstruction unit is configured to: when reconstructing the received signal:

Yv =M{f _l ) diag (Ρ, )ί _Λ +Μ (f ₂ ) diag(P ₂ ) ₂ + η _γ

Yi

^Dia § ( ^p i ) i ⁺ ( ₂ ) iag(P ₂ ) h _2a + " ₂

y ₃

y ₄

among them

L ² ′′ is the demodulation reference signal received on the ith antenna, which is the channel impulse response of the jth user on the ith antenna; = 1 or 2, and '· = ³ or ' · = ⁴ The case of the second time slot; ^f , , are the frequency offsets of user 1 and user 2 respectively; the /^, and are both unknown quantities to be estimated, and the remaining variables are known quantities;

The individual elements of M (/) = (3⁄4 ) are defined as follows:

f

Where ^ is the normalization, ie bandwidth P, =

P., "Demodulation reference signal transmitted by the user on the resource block, "is additive noise.

The system of claim 10, wherein the inverse of the ^^" ^ is calculated as M(-/).

12. The system according to claim 11, wherein the estimating unit performs the optimal frequency offset estimation, and is used to: after expressing in a matrix form, the formula (*) becomes ⁺ "( ^Δ )

Φ(.ί,Λ) = where

The coefficient matrix of the formula (*) is based on the formula (Δ), and the number of variables is reduced by substitution, and the following formula is obtained:

^P Hf f2) ^y ; According to this, the following equation is obtained:

= ^φ , , ,

= min

^P Hf f2) ^y where +( , / ₂ ) is the Moore-Penrose generalized inverse of the matrix (/;, / ₂ );

13. The system according to claim 12, wherein said estimating unit is performing said frequency After the partial estimation, the channel estimation value is obtained using a Least Square algorithm or an MMSE algorithm.

14. The system according to claim 13, wherein, when the Least Square algorithm is applied, the estimating unit is configured to: when obtaining the channel estimation value:

Calculate ^Φ " from the estimated frequency offset sum, and then use the Least Square algorithm for the formula ( ^Δ ) to obtain the estimated value of the channel estimate Φ + ( / ₂ ).y.

The system according to claim 8, wherein the received signal reconstruction unit and the estimation unit are disposed in a base station.