# US 12,000,954 B2 · Transmit beamforming method for integrated multi-antenna system with joint near-field sensing and far-field communication

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- Number: US 12,000,954 B2
- Document ID: US12000954B2
- Status: Granted
- Kind: B2
- Application number: 18/451,148
- Filed: 2023-08-17
- Published: 2024-04-25
- Granted: 2024-06-04
- Earliest claimed: 2022-10-14
- Assignees: Shandong University
- Applicants: Shandong University
- Inventors: Shuaishuai Guo; Kaiqian Qu; Jia Ye
- Web page: https://patentgrep.com/patent/US12000954B2

## CPC

- G01S 7/4008: {of transmitters}
- G01S 13/42: Simultaneous measurement of distance and other co-ordinates (indirect measurement G01S13/46)
- G01S 7/006: {using shared front-end circuitry, e.g. antennas (G01S13/765, G01S13/825 take precedence)}
- G01S 7/03: Details of HF subsystems specially adapted therefor, e.g. common to transmitter and receiver
- H01Q 3/40: with phasing matrix
- Y02D 30/70: in wireless communication networks
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- H01Q: ANTENNAS, i.e. RADIO AERIALS (radiators or antennas for microwave heating H05B6/72)
- Y02D: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE

## Abstract

A transmit beamforming method for integrated multi-antenna systems with joint near-field sensing and far-field communication, which includes: (1) establishing a communication signal transmission model and a communication channel model, and analyzing an upper limit of communication spectrum efficiency; (2) acquiring an optimal communication beam matrix based on the communication channel model; (3) establishing a near-field sensing signal model; (4) generating an optimal radar beam matrix based on an antenna array response vector of a radar detection target; (5) introducing a compromise factor to construct an initial optimization problem of an integrated beamforming matrix in power constraint based on the established near-field sensing signal model; and (6) transforming and solving the constructed initial optimization problem to obtain the integrated beamforming matrix.

## Claims

### Claim 1

An emission beamforming method of a multi-antenna integrated system combining near-field sensing and far-field communication, comprising a computer readable medium operable on a computer with memory for the emission beamforming method of a multi-antenna integrated system combining near-field sensing and far-field communication, and comprising program instructions for executing the following steps:
(i) establishing a communication signal transmission model and a communication channel model, and analyzing an upper limit of communication spectrum efficiency;
(ii) acquiring an optimal communication beam matrix Fcom based on the communication channel model in step (i);
(iii) establishing a sensing near-field region signal model;
(iv) generating an optimal radar beam matrix Frad based on an antenna array response vector of a radar detection target;
(v) introducing a compromise factor to construct an initial optimization problem of an integrated beamforming matrix in power constraint based on the established sensing near-field region signal model;
(vi) transforming and solving the constructed initial optimization problem of an integrated beamforming matrix in step (v) to obtain the integrated beamforming matrix; and
(vii) improving performance for the near-field sensing and increasing capability of the far-field communication based on the integrated beamforming matrix;
wherein
in step (iii), the sensing near-field region signal model is represented as a directional pattern of a near-field region radar emission signal P(θ, r), as shown in formula (IX):
P(θ,r)=a(θ,r)RaH(θ,r) (IX);
in the formula (IX), R represents a covariance matrix of the emission signal;
in step (iv), the generating an optimal radar beam matrix Frad based on an antenna array response vector of a radar detection target specifically comprises:
a) making a design of a radar detection signal x equivalent to a design of an emission beamforming matrix F, wherein due to a covariance matrix of the emission signal R=E (xxH)=E(Fs(Fs)H)=FFH, formula (IX) is represented by formula (X):
P(θ,r)=atH(θ,r)Rat(θ,r)=∥FHat(θ,r)∥F2 (X), and
b) generating the optimal radar beam matrix Frad directly based on the antenna array response vector of the radar detection target, wherein an emission front end is a hybrid modulus fully-connected structure, the optimal radar beam matrix Frad is constructed as formula (XI):
Frad=[v1 v2 . . . vtar]∈□Nt×Ntar (XI);
in the formula (XI), vi is an element in an array steering vector:
v
i
=
1
N
t
⁢
a
⁡
(
θ
i
,
r
i
)
⁢
i
=
1
,
2
⁢
…
⁢
N
tar
,
N
tar
is the number of the detection targets, a(θi,ri) represents a steering vector at which an ith detection target is located, and θi and ri represent an angle and a distance of the ith target;
a radar performance measurement index is defined as an Euclidean distance between the emission beamforming matrix F and the optimal radar beam matrix Frad: ∥F−Frad∥F2;
in step (v), the introducing a compromise factor to construct an initial optimization problem of an integrated beamforming matrix in power constraint based on the established sensing near-field region signal model means that emission power is taken as constraint, an target function is to minimize a sum of Euclidean distances between an emission beamforming matrix F, the optimal radar beam matrix Frad and the optimal communication beam matrix Fcom with the compromise factor being introduced, and the optimization problem, namely, the initial optimization problem of an integrated beamforming matrix is established and represented by formula (XII):
{
min
F
η
⁢

F
-
F
c
⁢
o
⁢
m

F
2
+
(
1
-
η
)
⁢

F
-
F
r
⁢
a
⁢
d

F
2
s
.
t
.

F

F
2
=
P
T
;
(
XII
)
in the formula (XII), Fcom represents the optimal beam matrix for communication, Frad represents the optimal beam matrix of an radar, η represents the compromise factor within [0, 1], and PT represents total emission power; and
in step (vi), the transforming and solving the constructed initial optimization problem of an integrated beamforming matrix in step (5) to obtain the integrated beamforming matrix specifically comprises:
a) constructing auxiliary variables A=[√{square root over (η)}INtT, √{square root over (1−η)}INtT]T∈2Nt×Nt and B=[√{square root over (η)}FcomT,√{square root over (1−η)}FradT]T∈2Nt×Ns, and converting formula (XI) into a quadratic constrained and quadratic programming problem in an equivalent form, as shown in formula (XIII):
{
min
F

AF
-
B

F
2
s
.
t
.

F

F
2
=
P
T
,
(
XIII
)
b) introducing E=INs⊗A, f=vec(F), b=vec(B), t=±1, in which vec (□) represents an column vector stacking operation, ⊗ represents a Kronecker product, and the formula (XIII) is deformed to obtain formula (XIV):
{
min
f

Ef
-
tb

2
2
s
.
t
.
⁢

f

2
2
=
P
T
,
t
2
=
1
,
(
XIV
)
c) constructing
C
=
[
E
H
⁢
E
-
E
H
⁢
b
-
b
H
⁢
E
b
H
⁢
b
]
,
y
=
[
f
t
]
,
Y
=
yy
H
,
A
1
=
[
I
N
s
×
N
t
0
0
0
]
,
A
2
=
[
0
N
s
×
N
t
0
0
1
]
,
wherein the initial optimization problem of an integrated beamforming matrix is re-represented by formula (XV):
{
min
Y
∈
H
n
T
⁢
r
(
C
⁢
Y
)
s
.
t
.
Tr
⁡
(
A
1
⁢
Y
)
=
P
T
Tr
(
A
2
⁢
Y
)
=
1
rank
(
Y
)
=
1
,
Y
≥
0
,
(
XV
)
d) ignoring non-convex constraint of rank(Y)=1 by a semi-definite relaxation method, wherein in the formula (XV), only rank(Y)=1 is non-convex, the problem becomes a semi-definite programming problem and is represented by formula (XVI):
{
min
Y
∈
H
n
T
⁢
r
(
C
⁢
Y
)
s
.
t
.
Tr
⁡
(
A
1
⁢
Y
)
=
P
T
T
⁢
r
⁡
(
A
2
⁢
Y
)
=
1
Y
≥
0
,
(
XVI
)
and
the formula (XVI) is a convex optimization problem, and Y is solved by a CVX toolbox in MATLAB, and
e) solving formula (XVII) and separating y from Y based on the constructed
y
=
[
f
t
]
,
Y
=
yy
H
,
in the step b):
min∥Y−yyH∥F2 (XVII),
giving a root of a maximum eigenvector multiplied by a maximum eigenvalue of Y equal to an optimal solution y of the formula (XVII), eliminating a last element in the optimal solution y to obtain f=vec(F) in the step a), and recombining elements in f into a matrix F with a dimension being Nt×Ns to obtain the integrated beamforming matrix.

### Claim 2 (depends on 1)

The method according to claim 1, wherein the method is applied to a multi-input and multi-output communication and sense integration system; the system comprises a base station equipped with Nt antennas and multi-antenna user equipment equipped with Nr antennas; antennas of a receiving end and an emitting end use a uniform linear array, and an antenna array element spacing is half of a wavelength; and the number of emitted data flows is Ns, and the number of targets of interest to a radar is Ntar.

### Claim 3 (depends on 1)

The method according to claim 1, wherein the establishing a communication signal transmission model in step (i) means that when determining a symbol vector s transmitted by an emitting end, under the action of an emission beamforming matrix F, the communication signal transmission model is represented by formula (I):
Y=√{square root over (ρ)}WHHFs+WHn (I); and
in the formula (I), Y represents a signal received by a receiving end, p represents average receiving power of the receiving end, W∈Nr×Ns represents a receiving beamforming matrix, F−Nt×Ns represents the emission beamforming matrix, s∈Ns×1 represents the symbol vector, various data flows are mutually uncorrelated and satisfy (ssH)=INs, and H∈Nr×Nt represents a transmission channel matrix, namely, the communication channel model, n˜(0, N0IMt) represents a Gaussian noise vector, and N0 represents noise power.

### Claim 4 (depends on 3)

The method according to claim 3, wherein for a wireless communication channel, a multi-path channel model, namely, a Saleh-Valenzuela model, is used, and if an antenna spacing is half of a wavelength, the transmission channel matrix H is represented by formula (II):
H
=
N
t
×
N
r
L
⁢
∑
i
=
1
L
α
i
⁢
a
r
(
θ
i
)
⁢
a
t
H
(
φ
i
)
;
(
II
)
and
in formula (II), L represents the number of paths in the channel, αi represents a fading coefficient of an ith path following Gaussian distribution, Nt represents the number of antennas of an emitting end of a base station, Nr represents the number of antennas received by a user end, θi and φi represent an arrival angle and an emission angle of an ith path of beam, and ar(θi) and at(φi) represent steering vectors of the receiving end and the emitting end of the ith path and are represented by formula (III) and formula (IV), respectively:
ar(θi)=[1,e−jπ sin(θi), . . . ,e−jπ(N−1)sin(θi)] (III)
at(φi)=[1,e−jπ sin(φi), . . . ,e−jπ(N−1)sin(φi)] (IV).

### Claim 5 (depends on 1)

The method according to claim 1, wherein in step (i), the analyzing an upper limit of communication spectrum efficiency means that the upper limit of the communication spectrum efficiency R is represented by formula (V):
R=log2|I+Rn−1WHHFFHHHW| (V); and
in the formula
R
n
=
1
S
⁢
N
⁢
R
⁢
W
H
⁢
W
,
(
V
)
and SNR represents a signal noise ratio.

### Claim 6 (depends on 1)

The method according to claim 1, wherein in step (ii), the acquiring an optimal communication beam matrix Fcom based on the communication channel model in step (1) means that the optimal communication beam matrix Fcom is constructed based on a way of singular value decomposition of a channel matrix, and specifically means that
H=UΣVH represents singular value decomposition of a transmission channel matrix, and the optimal communication beam matrix Fcom is composed of right singular vectors of Ns maximum singular values of a right singular matrix obtained after singular value decomposition of H, as shown in formula (VI):
Fcom=V[:,1:Ns] (VI); and
a receiving beamforming matrix W is composed of left singular vectors of the Ns maximum singular values of the right singular matrix obtained after singular value decomposition of H, as shown in formula (VII):
W=U[:,1:Ns] (VII).

### Claim 7 (depends on 1)

The method according to claim 1, wherein step (iii) means that when the target is in an array near-field range
r
≤
2
⁢
D
2
λ
,
an array steering vector at the target (r, θ) is established, as shown in formula (VIII):
a
⁡
(
r
,
θ
)
=
[
1
r
d
1
⁢
exp
⁡
(
-
jk
⁡
(
d
1
-
r
)
)
r
d
2
⁢
exp
⁢
(
-
jk
⁢
(
d
2
-
r
)
)
⋮
r
d
N
t
-
1
⁢
exp
⁡
(
-
jk
⁡
(
d
N
t
-
1
-
r
)
)
]
,
r
≤
2
⁢
D
2
λ
;
(
VIII
)
and
in the formula (VIII), r represents a distance of the target, θ represents an angle at which the target is located, λ represents a wavelength, D represents an antenna array aperture, di represents a distance of the target from an ith antenna array element,
i
=
1
,
2
⁢
…
⁢
N
t
-
1
,
k
=
2
⁢
π
λ
represents a wave number, and j=√{square root over (−1)} represents an imaginary symbol.