IP Library › Granted Patent US 12,088,438
Granted Patent B2
US 12,088,438 · App. 17/679,911 · Granted Sep 10, 2024

Linear equalization method and device for OTFS systems

Inventors: Wenjun Xu (Beijing, CN); Tingting Zou (Beijing, CN); Hui Gao (Beijing, CN); Zhisong Bie (Beijing, CN); Ping Zhang (Beijing, CN); Fengyu Wang (Beijing, CN); Jiaru Lin (Beijing, CN)
Assignee: Beijing University of Posts and Telecommunications
H04L25/03878H04W24/02
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Quick Facts
Patent No.
US 12,088,438
App. No.
17/679,911
Granted
Sep 10, 2024
Kind
B2
Abstract

Disclosed is a low-complexity linear equalization method for an Orthogonal Time Frequency Space (OTFS) system. The method may include: receiving a time domain signal passing through a linear time-varying (LTV) channel; sampling the time domain signal to obtain a sampled signal; demodulating the sampled signal to obtain a demodulated signal; performing a Symplectic Finite Fourier Transform (SFFT) on the demodulated signal to obtain a sampled delay-Doppler domain signal; determining an effective channel matrix in a delay-Doppler domain under a restriction of a rectangular window according to a time domain channel matrix; determining a linear equalization matrix according to the effective channel matrix; and equalizing the sampled delay-Doppler domain signal in a low-complexity way according to the linear equalization matrix. The disclosure also discloses a linear equalization device of an OTFS system for realizing the linear equalization method and a computer-readable storage medium.

Claims (442)

1. A linear equalization method for an Orthogonal Time Frequency Space (OTFS) system implemented by an OTFS receiver, comprising:

receiving a time domain signal passing through a linear time-varying (LTV) channel;

sampling the time domain signal to obtain a sampled signal;

demodulating the sampled signal to obtain a demodulated signal;

performing a Symplectic Finite Fourier Transform (SFFT) on the demodulated signal to obtain a sampled delay-Doppler domain signal;

determining an effective channel matrix in a delay-Doppler domain under a restriction of a rectangular window according to a time domain channel matrix;

determining a linear equalization matrix according to the effective channel matrix; and

equalizing the sampled delay-Doppler domain signal according to the linear equalization matrix.

2. The linear equalization method of claim 1 , wherein, the effective channel matrix H eff is a block circulant matrix composed of N first circulant matrices A n .

3. The linear equalization method of claim 2 , wherein, determining an effective channel matrix in a delay-Doppler domain under a restriction of a rectangular window according to a time domain channel matrix comprises:

obtaining a time domain channel sub-matrix {tilde over (H)} p from the time domain channel matrix; wherein, {tilde over (H)} p represents the time domain channel sub-matrix of the time domain channel matrix {tilde over (H)}=diag[ , . . . , ] experienced by the p th symbol; {tilde over (H)}=diag[ , . . . , ] is a NM×NM block diagonal matrix, which represents the time domain channel matrix when a length of a cyclic prefix is greater than a maximum delay of the LTV channel;

determining each first circulant matrices A n based on the time domain channel sub-matrix {tilde over (H)} p ; and

determining the effective channel matrix H eff based on the first circulant matrices A n .

4. The linear equalization method of claim 3 , wherein, determining each first circulant matrices A n based on the time domain channel sub-matrix {tilde over (H)} p comprises:

determining the circulant matrices A n according to the following equation:

A n =FFT Mtx ( {tilde over (H)} p )

wherein, FFT Mtx ( ) represents a Fast Fourier Transform operation on a set of matrices.

5. The linear equalization method of claim 3 , wherein, determining the effective channel matrix H eff based on the circulant matrices A n comprises:

determining the effective channel matrix H eff according to the following equation:

H

eff

=

(

⁢

A

1

A

2

…

A

N

⁢

­

⁢

1

A

N

A

N

A

1

A

N

-

2

A

N

-

1

⋮

⋱

⋮

A

3

A

4

…

A

1

A

2

A

2

A

3

A

N

A

1

⁢

)

.

6. The linear equalization method of claim 2 , wherein, the linear equalization matrix is a zero-forcing equalization matrix W ZF ; wherein,

determining the linear equalization matrix according to the effective channel matrix comprises: determining the zero-forcing equalization matrix according to the following expression:

W ZF =H eff −1 .

7. The linear equalization method of claim 2 , wherein, the linear equalization matrix is a zero-forcing equalization matrix W ZF ; wherein,

determining the linear equalization matrix according to the effective channel matrix comprises:

for each first circulant matrices A n , performing an Inverse Fast Fourier Transform (IFFT) on the first circulant matrices A n to obtain a first intermediate matrix S t ; inverting the first intermediate matrix S t to obtain a first inversed intermediate matrix S t −1 ; performing a Fast Fourier Transform (FFT) on the first inversed intermediate matrix S t −1 to obtain a second circulant matrix B q ; and

determining the zero-forcing equalization matrix W ZF according to the second circulant matrices B q .

8. The linear equalization method of claim 7 , wherein, performing a Fast Fourier Transform (FFT) on the first inversed intermediate matrix S t −1 to obtain a second circulant matrix B q comprises:

determining the second circulant matrix B q according to the following equation:

B

q

=

1

N

⁢

F

⁢

F

⁢

T

Mtx

⁡

(

S

t

-

1

)

wherein, FFT Mtx ( ) represents a Fast Fourier Transform operation on a set of matrices.

9. The linear equalization method of claim 7 , wherein, inverting the first intermediate matrix S t to obtain a first inversed intermediate matrix S t −1 comprises:

initializing an L matrix as L=I M ;

initializing a U matrix as U=0 M ;

initializing an intermediate variable matrix as Y=0 M ;

initializing an auxiliary vector as d=[d chan ,M−D P ]; wherein, d chan =[D 1 , D 2 , D 3 , . . . , D P ] is a vector representing delays of the LTV channel; P represents a number of paths of the LTV channel; D 1 , D 2 , D 3 , . . . , D P represents a coordinate value of a delay of each path on a delay axis in the delay-Doppler domain;

determining a first M−D P columns of the L matrix according to L(i+D P ,i)=S t (i+D P ,i)/S t (i,i); where, L(i+D P , i) represents an element at a position of row i+D P and column i in the L matrix; and i is a first cyclic variable, where i=1: M−D P ;

determining a first M−D P rows of the U matrix according to U(ξ,:)=S t (ξ,:)−Σ k=2 n Σ j=1 M L(ξ,ξ−D k )U(ξ−D k ,j); where, U(ξ,:) represents row ξ of the U matrix; S t (ξ,:)) represents row ξ of the first intermediate matrix S t ; the vector ξ increases from D p +1 to D p+1 one by one; and p is a second cyclic variable, where p=1: P+1;

determining a last D P columns of the L matrix through an LU decomposition method;

determining a last D P rows of the U matrix through the LU decomposition method;

obtaining the first inversed intermediate matrix S t −1 according to the L matrix and the U matrix.

10. The linear equalization method of claim 9 , wherein, obtaining the first inversed intermediate matrix S t −1 according to the L matrix and the U matrix comprises:

setting a third cyclic variable n increasing from 1 to P one by one;

in loop n, setting a vector k increasing from d(n)+1 to d(n+1) one by one;

wherein, d(n) represents a n th element in the vector d(n); d(n+1) represents a n+1 th element in the vector d(n);

calculating the row k of the intermediate variable matrix Y according to the following expression Y(k,:)=I(k,:)−Σ i=1 n L(k,k−d(i)Y(k−d(i),:);

setting a fourth cyclic variable k increasing from D P +1 to M one by one;

in loop k, calculating row k of the intermediate variable matrix Y according to Y(k,:)=I(k,:)−L(k,1:k−1)Y(1:k−1,:);

setting a fifth cyclic variable t decreasing from N to 1 one by one;

in loop t, setting a variable f represents a bigger one between M−D P and k+1;

obtain row t of the inversed matrix S t −1 through

S

t

-

1

⁡

(

t

,

;

)

=

Y

⁡

(

t

,

:

)

-

U

⁡

(

t

,

f

:

M

)

⁢

X

⁡

(

f

:

M

,

:

)

U

⁡

(

t

,

t

)

.

11. The linear equalization method of claim 2 , wherein, the linear equalization matrix is a Minimum Mean Square Error (MMSE) equalization matrix W MMSE ; wherein,

determining the linear equalization matrix according to the effective channel matrix comprises:

determining a second intermediate matrix R according to the effective channel matrix and a transpose matrix of the effective channel matrix and a variance of channel noises;

inverting the second intermediate matrix R to obtain a second inverted intermediate matrix R −1 ; and

multiplying the second inverted intermediate matrix R −1 by the transpose matrix of the effective channel matrix to obtain the equalization matrix of the MMSE equalization W MMSE .

12. The linear equalization method of claim 11 , wherein, determining a second intermediate matrix R according to the effective channel matrix and a transpose matrix of the effective channel matrix and a variance of channel noises comprises:

determining the second intermediate matrix R according to the following expression:

R=H eff H H eff +σ 2 I

wherein, H eff H represents the conjugate transpose matrix of the effective channel matrix H eff ; σ 2 represents the variance of channel noises; and I represents an identity matrix with a same dimension with the effective channel matrix H eff .

13. The linear equalization method of claim 11 , wherein, determining a second intermediate matrix R according to the effective channel matrix and a transpose matrix of the effective channel matrix and a variance of channel noises comprises:

determining the second intermediate matrix R according to the following expression:

R

=

[

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

⁢

]

N

+

σ

2

⁢

I

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

1

⁢

]

N

…

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

N

-

1

⁢

]

N

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

N

-

1

⁢

]

N

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

⁢

]

N

+

σ

2

⁢

I

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

N

-

2

⁢

]

N

⋮

⋱

⋮

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

1

⁢

]

N

+

σ

2

⁢

I

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

+

2

⁢

]

N

+

σ

2

⁢

I

…

∑

n

=

1

N

⁢

A

n

H

⁢

A

[

n

⁢

]

N

+

σ

2

⁢

I

]

wherein, [⋅] N represent a modulo operation; [N] N =N.

14. The linear equalization method of claim 11 , wherein, inverting the second intermediate matrix R to obtain a second inverted intermediate matrix R −1 comprises:

initializing an L matrix as L=I M ;

initializing a U matrix as U=0 M ;

initializing an intermediate variable matrix as Y=0 M ;

initializing an auxiliary vector as d=[d chan ,M−D P ]; wherein, d chan =[D 1 , D 2 , D 3 , . . . , D P ] is a vector representing delays of the LTV channel; P represents a number of paths of the LTV channel; D 1 , D 2 , D 3 , . . . , D P represents a coordinate value of a delay of each path on a delay axis in the delay-Doppler domain;

determining a first M−D P columns of the L matrix according to L(i+D P ,i)=M(i+D P ,i)/M(i,i); where, L(i+D P , i) represents an element at a position of row i+D P and column i in the L matrix; and i is a first cyclic variable, where i=1: M−D P ;

determining a first M−D P rows of the U matrix according to U(ξ,:)=M(ξ:)−Σ k=2 n τ j=1 M L(ξ,ξ−D k )U(ξ−D k ,j); where, U(ξ,:) represents row of the U matrix; S t (ξ,:) represents row of the first intermediate matrix M; the vector increases from D p +1 to D p+1 one by one; and p is a second cyclic variable, where p=1: P+1;

determining a last D P columns of the L matrix through an LU decomposition method;

determining a last D P rows of the U matrix through the LU decomposition method;

obtaining the second inversed intermediate matrix R −1 according to the L matrix and the U matrix.

15. The linear equalization method of claim 14 , wherein, obtaining the second inversed intermediate matrix R −1 according to the L matrix and the U matrix comprises:

setting a third cyclic variable n increasing from 1 to P one by one;

in loop n, setting a vector k increasing from d(n)+1 to d(n+1) one by one;

wherein, d(n) represents a n th element in the vector d; d(n+1) represents a n+1 th element in the vector d;

calculating the row k of the intermediate variable matrix Y according to the following expression Y(k,:)=I(k,:)−L(k,k−d(i))Y(k−d(i),:);

setting a fourth cyclic variable k increasing from D p +1 to M one by one;

in loop k, calculating row k of the intermediate variable matrix Y according to Y(k,:)=I(k,:)−L(k,1:k−1)Y(1:k−1,:);

setting a fifth cyclic variable t decreasing from N to 1 one by one;

in loop t, setting a variable f represents a bigger one between M−D P and k+1;

obtain row t of the inversed matrix R −1 through

R

-

1

⁡

(

t

,

;

)

=

Y

⁡

(

t

,

:

)

-

U

⁡

(

t

,

f

:

M

)

⁢

X

⁡

(

f

:

M

,

:

)

U

⁡

(

t

,

t

)

.

16. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the linear equalization method of claim 1 .

17. A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions being used to make a computer execute the linear equalization method of claim 1 .

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 24, 2022
From: XU, WENJUN; ZOU, TINGTING; GAO, HUI; BIE, ZHISONG; ZHANG, PING; WANG, FENGYU; LIN, JIARU
To: BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS
Reel/Frame 059094/0416 →
Priority Claims (1)
CN 201910847083.0 · Sep 2, 2019 · national
Continuity (2)
Continuation PCTCN2019125475 · Dec 16, 2019
Related Publication 20220182265A1 · Jun 9, 2022