CN112954690A - Anti-interference method and system based on space-based reconfigurable intelligent surface - Google Patents

Anti-interference method and system based on space-based reconfigurable intelligent surface Download PDF

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CN112954690A
CN112954690A CN202110093366.8A CN202110093366A CN112954690A CN 112954690 A CN112954690 A CN 112954690A CN 202110093366 A CN202110093366 A CN 202110093366A CN 112954690 A CN112954690 A CN 112954690A
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aris
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transmission rate
beam forming
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CN112954690B (en
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唐晓
江天奇
王大伟
张若南
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Northwestern Polytechnical University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • 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
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention belongs to the technical field of wireless communication, and discloses an anti-interference method and system based on a space-based reconfigurable intelligent surface. Aiming at the instantaneous channel state information of a legal channel and an eavesdropping channel, a joint optimization problem of deploying an aerial reconfigurable intelligent surface and passive beamforming is constructed. The method comprises the steps of solving through an alternate optimization framework, determining the optimal position of the air reconfigurable intelligent surface through a continuous convex approximation method, and obtaining the optimal reflection beam forming through a manifold optimization method. Compared with the traditional method, the method can effectively inhibit interference attack from an eavesdropper while enhancing legal transmission, thereby improving the anti-interference communication performance of the system.

Description

Anti-interference method and system based on space-based reconfigurable intelligent surface
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an anti-interference method and system based on a space-based reconfigurable intelligent surface.
Background
In the current military and civil wireless communication, anti-interference transmission is a key to solve the problem of information security. Interference attack of malicious nodes or unintentional interference of some transmitters always exists in the communication process, so that legal transmission is seriously damaged, the performance is reduced, and the security of wireless information is threatened. Therefore, the interference-free communication has attracted research in academic and industrial circles, and various strategies such as spread spectrum, frequency hopping, power control, cooperative transmission, and design based on machine learning have been proposed for the interference-free communication.
The anti-interference method of the traditional wireless network generally adopts modern cryptography, and utilizes an encryption algorithm and a secret key therein to encrypt information in the communication process, so as to protect the information from eavesdropping and attack, thereby achieving the purpose of safe communication. However, with the rapid development of computer technology, the computing power is greatly improved compared with the prior art, and the traditional secret method is easy to crack. Therefore, people are beginning to move the research direction to physical layer security, and Channel State Information (CSI) of a wireless network Channel is utilized to realize Information security transmission.
In recent years, Reconfigurable Intelligent Surface (RIS) has raised a wave in the field of wireless communication as an emerging wireless technology. The RIS is typically composed of small-sized, low-cost, nearly passive components that can be controlled by software to make the wireless environment programmable. The RIS can change the electromagnetic characteristics of an incident signal as needed to improve the reception of the signal, and thus has various applications in the wireless field. For example, RIS has been used to improve system throughput, energy efficiency, information security, network coverage, etc. of wireless transmissions. Since RIS can influence wireless propagation, it also paves a new way to combat interference attacks, where interfering signals can be mitigated after reflection, while legitimate signals can be enhanced by appropriate adjustment of the reflection.
Most of the existing research on the RIS enhanced communication security is devoted to the strategy design of the transmitting end. In contrast, the security problem at the receiving end is rarely solved. In practice, it is also important to enhance the security of the receiving end during the uplink transmission, because the transmitting end is usually some user equipment with lower power in the uplink transmission, the communication security of the transmitting end is more threatened, and the communication security of the receiving end cannot be effectively guaranteed. Furthermore, for the optimization for RIS, most studies tend to focus on the beamforming problem of the RIS itself, and neglecting that the deployment of the RIS has a great influence on the safety of the communication system.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an anti-interference method and system based on a space-based reconfigurable intelligent surface, which resists interference by deploying an AIRS (advanced interference detection System), enhances legal reception of a receiving end, and greatly improves the anti-interference performance of wireless communication compared with the traditional scheme.
The invention is realized by the following technical scheme:
an anti-interference method based on a space-based reconfigurable intelligent surface comprises the following steps:
s101, constructing a secure communication system model by using a plurality of legal transceiving nodes working on the ground, ARIS deployed in the air and a wiretapping node on the bottom surface, and determining the instantaneous signal-to-noise ratio and the secure transmission rate of the secure communication system model;
s102, constructing an optimization problem with the aim of maximizing the safe transmission rate according to the instantaneous signal-to-noise ratio and the safe transmission rate;
s103, solving an optimization problem with the maximum safe transmission rate as a target by fixing the deployment of the ARIS and adopting manifold optimization to obtain an ARIS beam forming local optimal strategy;
s104, obtaining an ARIS deployed local optimal strategy by a continuous convex approximation optimization method based on the ARIS beam forming local optimal strategy obtained in the step S103;
and S105, repeatedly executing the steps S103-S104 through an alternative optimization framework based on the ARIS beam forming optimization strategy of the step S103 and the ARIS deployed local optimal strategy of the step S104, and iteratively updating until variables of the ARIS beam forming optimization strategy and the ARIS deployed local optimal strategy and the system security transmission rate are converged to obtain the optimal security transmission strategy of the communication network model.
Preferably, in step S101, a channel gain model between nodes is first analyzed through the secure communication system model, an instantaneous signal-to-noise ratio of the secure communication system model is determined according to the channel gain model, and a secure transmission rate is determined according to the instantaneous signal-to-noise ratio.
Preferably, the expression of the instantaneous signal-to-noise ratio is as follows:
Figure RE-GDA0002999360850000031
wherein, PSIs the transmission power, PJIs the interference power, hSD,hJD,hRD,hSR,hJRA corresponding channel state matrix is represented and,
Figure RE-GDA0002999360850000032
is the background noise power, Θ is the reflection coefficient matrix of ARIS;
the expression of the secure transmission rate is as follows:
C＝log(1+η)
preferably, the expression of the optimization problem aimed at maximizing the safe transmission rate in step S102 is as follows:
Figure RE-GDA0002999360850000033
Figure RE-GDA0002999360850000034
Figure RE-GDA0002999360850000035
where C is the safe transmission rate, θ is the phase shift of the reflective element, w is the horizontal position of the ARIS deployment, and all nodes are located at
Figure RE-GDA0002999360850000036
Within the area of the definition, the area of the display screen,
Figure RE-GDA0002999360850000037
and
Figure RE-GDA0002999360850000038
scale on the x-axis and y-axis.
Preferably, the method for obtaining the local optimal strategy of the ARIS passive beamforming in step S103 is as follows:
and replacing the optimization problem with the goal of maximizing the safe transmission rate by adopting the optimization problem of minimizing the inverse of the instantaneous signal-to-noise ratio, and solving the optimization problem of minimizing the inverse of the instantaneous signal-to-noise ratio by adopting manifold optimization to obtain a local optimal strategy of ARIS passive beam forming.
Preferably, the obtaining of the local optimal strategy for ARIS passive beamforming in step S103 includes the following steps:
step S1031, replacing the optimization problem with the goal of maximizing the safe transmission rate by the optimization problem with the minimum inverse of the instantaneous signal-to-noise ratio, and rewriting the optimization problem with the goal of maximizing the safe transmission rate into the following expression:
Figure RE-GDA0002999360850000041
Figure RE-GDA0002999360850000042
step S1032, finding out a local optimal solution by using manifold optimization, and expressing the manifold as
Figure RE-GDA0002999360850000043
For the
Figure RE-GDA0002999360850000044
At any point in
Figure RE-GDA0002999360850000045
The tangent space is defined as the set of all tangent vectors, expressed as
Figure RE-GDA0002999360850000046
Step S1033 for
Figure RE-GDA0002999360850000047
Iterative process of contraction, initialized first
Figure RE-GDA0002999360850000048
χi，ρi，
Figure RE-GDA0002999360850000049
Wherein, χi+1Is the Polak-Ribiere parameter, rhoiAnd ζiIs that
Figure RE-GDA00029993608500000410
Direction and step size of the shrink, ξ, in the iterative processiRepresenting the search direction in euclidean space,
Figure RE-GDA00029993608500000411
is the euclidean space gradient;
shaping passive beams
Figure RE-GDA00029993608500000412
Is updated to
Figure RE-GDA00029993608500000413
The update is performed by the following formula:
Figure RE-GDA00029993608500000414
wherein the content of the first and second substances,
Figure RE-GDA0002999360850000051
representing the normalization process, step size piCan be obtained by Armijo backtracking line search;
step S1034, then
Figure RE-GDA0002999360850000052
New Riemann gradient, Polak-Ribiere parameter,
Figure RE-GDA0002999360850000053
To
Figure RE-GDA0002999360850000054
The tangential space transformation process, and the conjugate search direction;
the updated formula of the riemann gradient is as follows:
Figure RE-GDA0002999360850000055
Polak-Ribiere is updated as follows:
Figure RE-GDA0002999360850000056
Figure RE-GDA0002999360850000057
to
Figure RE-GDA0002999360850000058
The tangential space transformation process of (a) is as follows:
Figure RE-GDA0002999360850000059
the conjugate search direction update formula is as follows:
Figure RE-GDA00029993608500000510
step S1035 of obtainingTo after update
Figure RE-GDA00029993608500000511
χi，ρi，
Figure RE-GDA00029993608500000512
Repeating the steps S1032-S1034 for iteration after the parameters until the Riemann gradient is less than the predetermined threshold
Figure RE-GDA00029993608500000513
Thus, the ARIS passive beam forming local optimal strategy can be obtained when the ARIS is deployed fixedly.
Preferably, the method for obtaining the locally optimal strategy for the ARIS deployment in step S104 is as follows:
according to the obtained ARIS wave beam forming local optimal strategy, an objective function of a maximized system instantaneous signal-to-noise ratio problem is expressed as an ARIS deployment explicit function, a variable is introduced to convert the objective function into a quasi-convex function, the original constraint and the non-convex constraint in the introduced constraint are continuously convex, an optimization problem with the quasi-convex objective function and the convex constraint is obtained, the optimization problem with the quasi-convex objective function and the convex constraint is solved, and the ARIS deployment local optimal strategy is obtained.
Preferably, the expression of the optimization problem with the quasi-convex objective function and the convex constraint is as follows:
Figure RE-GDA0002999360850000061
Figure RE-GDA0002999360850000062
φ≥0
u≥0，v≥0
Figure RE-GDA0002999360850000063
Figure RE-GDA0002999360850000064
Figure RE-GDA0002999360850000065
defining:
Figure RE-GDA0002999360850000066
Figure RE-GDA0002999360850000067
Figure RE-GDA0002999360850000068
Figure RE-GDA0002999360850000069
Figure RE-GDA00029993608500000610
Figure RE-GDA00029993608500000611
where the variables u, v and φ are the parameters introduced, L0For reference the path loss at a distance of 1m,
Figure RE-GDA00029993608500000612
is the path loss exponent of the terrestrial radio transmission,
Figure RE-GDA00029993608500000613
is an air-to-ground channelThe path loss exponent of (a) is,
Figure RE-GDA00029993608500000614
representing small scale fading therein, d is the spacing between reflective elements, λ is the wavelength, φZRDenotes the cosine of the angle of arrival, phiRDRepresenting the cosine of the angle of arrival.
Preferably, the method for obtaining the optimal secure transmission policy of the communication network model in step S105 is as follows:
firstly, an ARIS beam forming optimization strategy and the deployment thereof are updated in an iterative mode by utilizing an alternative optimization framework, and firstly, the ARIS beam forming optimization strategy which meets constraint conditions is randomly selected
Figure RE-GDA00029993608500000615
And wiUpdating i ← i +1, according to step S103 when ARIS is deployed at wi-1In case of location, the passive beamforming is updated to
Figure RE-GDA0002999360850000071
Then passively beamformed in the AIRS to
Figure RE-GDA0002999360850000072
In case of updating the deployment location of the ARIS to wiAccording to
Figure RE-GDA0002999360850000073
And wiObtaining an updated objective function deltai(ii) a Repeating the steps S103-S104 to continuously and iteratively update the target function until convergence
Figure RE-GDA0002999360850000074
Thereby obtaining the maximum safe transmission rate of the communication network model.
A system based on an anti-interference method of a space-based reconfigurable intelligent surface comprises,
the safety communication system module is used for determining the instantaneous signal-to-noise ratio and the safety transmission rate of the safety communication system model according to the constructed safety communication system model;
the safe transmission rate optimization module is used for constructing an optimization problem which takes the maximized safe transmission rate as a target according to the instantaneous signal-to-noise ratio and the safe transmission rate;
the ARIS wave beam forming local optimal strategy module is used for solving an optimization problem with the maximum safe transmission rate as a target by fixing the deployment of the ARIS and adopting manifold optimization to obtain an ARIS wave beam forming local optimal strategy;
the ARIS deployed local optimal strategy module is used for obtaining an ARIS deployed local optimal strategy through a continuous convex approximation optimization method according to an ARIS beam forming local optimal strategy;
and the optimal safe transmission strategy module is used for iteratively solving the ARIS wave beam forming optimization strategy and the ARIS deployed local optimal strategy by adopting an alternate optimization framework to obtain the optimal safe transmission strategy of the communication network model.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention provides an anti-interference method based on a space-based reconfigurable intelligent surface, which is characterized in that when legal transmission is carried out on the ground between a transmitting node and a receiving node with a single antenna, an eavesdropping node is also arranged on the ground for attack, and the reconfigurable intelligent surface in the air is flexibly deployed to reduce interference attack and enhance legal transmission. Aiming at the instantaneous channel state information of a legal channel and an interception channel, the aerial reconfigurable intelligent surface is deployed in a communication network, the interference from the interception node is relieved at a receiving end by optimizing the passive beam forming of the AIRS and the deployment of the AIRS, and the joint optimization problem of deploying the aerial reconfigurable intelligent surface and the passive beam forming is constructed. And solving through an alternate optimization framework, determining the optimal position of the air reconfigurable intelligent surface by utilizing a continuous convex approximation method, and obtaining the optimal reflection beam forming by utilizing a manifold optimization method. Compared with the traditional method, the method can effectively inhibit interference attack from an eavesdropper while enhancing legal transmission, thereby improving the anti-interference communication performance of the system.
Drawings
Fig. 1 is a diagram of a wireless communication system model constructed by the present invention.
FIG. 2 is a flow chart of an anti-interference method based on a space-based reconfigurable intelligent surface.
Fig. 3 is a comparison graph of safe transmission performance of the space-based reconfigurable intelligent surface-based anti-interference method provided by the embodiment of the invention and a traditional method (no ARIS is deployed) under different transmission power and interference power conditions;
fig. 4 is a comparison graph of the safety transmission performance of the space-based reconfigurable intelligent surface-based anti-interference method provided by the embodiment of the present invention and a conventional method (no ARIS is deployed) in the case that the receiving end is located at different positions and the aires is located at different heights;
fig. 5 is a comparison graph of safe transmission performance of the space-based reconfigurable intelligent surface-based anti-interference method provided by the embodiment of the invention and a traditional method (no ARIS is deployed) under the conditions of different numbers of reflecting elements and different space-ground path loss indexes;
Detailed Description
The present invention will now be described in further detail with reference to the attached drawings, which are illustrative, but not limiting, of the present invention.
Referring to fig. 1 to 5, fig. 1 is a block diagram of a wireless communication system constructed according to the present invention, wherein a source node and a destination node in a legal wireless transmission are denoted as S and D, respectively. At the same time there is a malicious interferer, denoted J, intended to interrupt legitimate transmissions.
Node S, D, J is located on the ground with a two-dimensional horizontal coordinate wZ＝[xZ,yz]Z belongs to { S, D, J }, and each node is located in the group
Figure RE-GDA0002999360850000091
Within a defined area, wherein,
Figure RE-GDA0002999360850000092
and
Figure RE-GDA0002999360850000093
scale on the x-axis and y-axis. To counter interference attackIn an effort to deploy ARIS, for example, by dispatching a UAV or balloon to carry the RIS to a predetermined location to enhance legitimate signals while mitigating interfering signals. The deployment height of the ARIS is H, with w ═ x, y on the abscissa]And is represented by R. Geometrically, the distances between the ground nodes are dZD＝||wZ-wDI, Z belongs to { S, J }, and the distances between the ground nodes and the ARIS are respectively
Figure RE-GDA0002999360850000094
Referring to fig. 2, an anti-interference method based on a space-based reconfigurable intelligent surface includes the following steps:
s101: modeling a communication system, carrying out legal transmission by two legal transceiving nodes working on the ground, inhibiting interference attack from a ground eavesdropping node while enhancing the legal transmission by an ARIS deployed in the air, and forming a safe communication system as a system model;
analyzing a channel gain model among all nodes according to a network model, specifically:
Figure RE-GDA0002999360850000095
Figure RE-GDA0002999360850000096
Figure RE-GDA0002999360850000097
wherein L is0For reference the path loss at a distance of 1m,
Figure RE-GDA0002999360850000098
is the path loss exponent of the terrestrial radio transmission,
Figure RE-GDA0002999360850000099
is the path loss exponent of the air-to-ground channel,
Figure RE-GDA00029993608500000910
representing small scale fading therein, d is the spacing between reflective elements, λ is the wavelength, φZRDenotes the cosine of the angle of arrival, phiRDDenotes the cosine of the angle of arrival, while the ARIS consists of N reflection elements.
The expression for the instantaneous signal-to-noise ratio of system model wireless communication is as follows:
Figure RE-GDA0002999360850000101
wherein, PSIs the transmission power, PJIs the power of the interference(s),
Figure RE-GDA0002999360850000102
is the background noise power. Θ is the reflection coefficient matrix of ARIS, which is defined as
Figure RE-GDA0002999360850000103
θ＝[θ1,θ2,…,θN]T，
Figure RE-GDA0002999360850000104
Where θ represents the phase shift of the reflective element.
S102: obtaining the instantaneous signal-to-noise ratio and the safe transmission rate of the system according to the communication network model, and constructing an optimization problem with the maximized safe transmission rate as a target;
specifically, according to the system instantaneous signal-to-noise ratio obtained in S102, the safe transmission rate of the wireless communication is:
C＝log(1+η)
without loss of generality here, the present invention contemplates unit width. Further constructing an optimization problem with the aim of maximizing the safe transmission rate, specifically comprising the following steps:
Figure RE-GDA0002999360850000105
Figure RE-GDA0002999360850000106
Figure RE-GDA0002999360850000107
where w is the horizontal position of the ARIS deployment. In addition, all nodes are located by
Figure RE-GDA0002999360850000108
Within a defined area, wherein
Figure RE-GDA0002999360850000109
And
Figure RE-GDA00029993608500001010
scale on x-axis and y-axis, and each ground node position is wZ＝[xZ,yZ]And Z belongs to { S, D, J }. To avoid loss of generality, the present invention considers unit bandwidth.
Namely a joint optimization ARIS deployment w, ARIS beamforming
Figure RE-GDA00029993608500001011
To maximize the safe transmission rate of the wireless communication system. By decomposing the secure transport optimization model into w and w respectively
Figure RE-GDA00029993608500001012
In order to optimize the two sub-optimization models of the variables, the safe transmission scheme of the original model can be obtained by performing alternate optimization through an AO framework.
S103: the method comprises the following steps of fixing the ARIS deployment, obtaining a local optimal strategy of ARIS passive beam forming through manifold optimization, and specifically comprising the following steps:
step S1031, considering monotonicity between the safe transmission rate and the instantaneous signal-to-noise ratio, may replace the original optimization problem with an optimization problem that minimizes the reciprocal of the instantaneous signal-to-noise ratio, and first introduce δ:
Figure RE-GDA0002999360850000111
wherein the definition:
Figure RE-GDA0002999360850000112
Figure RE-GDA0002999360850000113
bJ＝PJhJDhJRD,bS＝PShSDhSRD
Figure RE-GDA0002999360850000114
therefore, the optimization problem of ARIS passive beamforming can be rewritten as:
Figure RE-GDA0002999360850000115
Figure RE-GDA0002999360850000116
step S1032, neither the rewritten optimization problem objective function nor the feasible domain is convex, but the unit modulus constraints in the optimization problem constitute the riemann manifold. Therefore, the invention utilizes manifold optimization to efficiently find a locally optimal solution, and expresses the manifold as
Figure RE-GDA0002999360850000117
For the
Figure RE-GDA0002999360850000118
At any point in
Figure RE-GDA0002999360850000119
The tangent space is defined as the set of all tangent vectors, expressed as
Figure RE-GDA00029993608500001110
Step S1032, for
Figure RE-GDA00029993608500001111
Iterative process of contraction, initialized first
Figure RE-GDA00029993608500001112
χi，ρi，
Figure RE-GDA00029993608500001113
Wherein xi+1Is the Polak-Ribiere parameter, rhoiAnd ζiIs that
Figure RE-GDA00029993608500001114
Direction and step size of the shrink, ξ, in the iterative processiRepresenting the search direction in euclidean space,
Figure RE-GDA00029993608500001115
is the euclidean space gradient.
Shaping passive beams
Figure RE-GDA0002999360850000121
Is updated to
Figure RE-GDA0002999360850000122
The update is performed by the following formula:
Figure RE-GDA0002999360850000123
wherein the content of the first and second substances,
Figure RE-GDA0002999360850000124
representing the normalization process, step size piCan be obtained by the search of the Armijo backtracking line, which is expressed as
Figure RE-GDA0002999360850000125
ξiIs an iterative process of
Figure RE-GDA0002999360850000126
Step S1034, then
Figure RE-GDA0002999360850000127
New Riemann gradient, Polak-Ribiere parameter,
Figure RE-GDA0002999360850000128
To
Figure RE-GDA0002999360850000129
The tangential space transformation process, and the conjugate search direction;
the updated formula of the riemann gradient is as follows:
Figure RE-GDA00029993608500001210
Polak-Ribiere is updated as follows:
Figure RE-GDA00029993608500001211
Figure RE-GDA00029993608500001212
to
Figure RE-GDA00029993608500001213
The tangential space transformation process of (a) is as follows:
Figure RE-GDA00029993608500001214
finally, the conjugate search direction is updated
Figure RE-GDA00029993608500001215
And updates i ← i + 1.
Step S1035, after obtaining the update
Figure RE-GDA00029993608500001216
χi，ρi，
Figure RE-GDA00029993608500001217
Repeating the above steps for iteration after the parameters are equal until the Riemann gradient is less than the predetermined threshold value
Figure RE-GDA00029993608500001218
Thus, the ARIS passive beam forming local optimal strategy can be obtained when the ARIS is deployed fixedly.
S104: based on the ARIS passive beam forming local optimal strategy obtained in the step S103, obtaining an ARIS deployed local optimal strategy by a continuous convex approximation optimization method;
specifically, according to the obtained ARIS passive beamforming local optimum strategy, the system instantaneous signal-to-noise ratio is rewritten into an explicit function related to ARIS deployment, and the function is expressed as:
Figure RE-GDA0002999360850000131
wherein
Figure RE-GDA0002999360850000132
Defining:
Figure RE-GDA0002999360850000133
Figure RE-GDA0002999360850000134
Figure RE-GDA0002999360850000135
for the deployment optimization problem, the original problem can be rewritten as:
Figure RE-GDA0002999360850000136
Figure RE-GDA0002999360850000137
further considering the optimization problem of ARIS deployment solved by using a continuous convex approximation method, the method specifically comprises the following steps:
firstly, introducing variables u and v, and rewriting an objective function into
Figure RE-GDA0002999360850000138
Meanwhile, the constraint u is more than or equal to 0, the constraint v is more than or equal to 0,
Figure RE-GDA0002999360850000139
the objective function of the quadratic fraction is rewritten to the minimized equivalent form by introducing a variable phi, which is expressed as:
Figure RE-GDA0002999360850000141
Figure RE-GDA0002999360850000142
φ≥0
αSu2+βSu+γS≥φ
u≥0，v≥0
Figure RE-GDA0002999360850000143
Figure RE-GDA0002999360850000144
then, a quasi-convex objective function is obtained, and then, a first-order approximation is carried out on the non-convex constraint in the optimization problem to carry out convex processing, so that:
Figure RE-GDA0002999360850000145
Figure RE-GDA0002999360850000146
Figure RE-GDA0002999360850000147
thus approximating the original deployment problem as being (w)0，u0) The optimization problem with pseudo-convex objective function and convex constraint is expressed as:
Figure RE-GDA0002999360850000148
Figure RE-GDA0002999360850000149
φ≥0
u≥0，v≥0
Figure RE-GDA00029993608500001410
Figure RE-GDA00029993608500001411
Figure RE-GDA00029993608500001412
the ARIS deployment optimization problem can thus be easily solved:
first randomly selecting the ones satisfying constraints
Figure RE-GDA0002999360850000151
Updating
Figure RE-GDA0002999360850000152
Updating i ← i + 1;
will w0And u0Bringing into the reconstructed optimization problem by minimizing the objective function
Figure RE-GDA0002999360850000153
Solve out the optimized variable
Figure RE-GDA0002999360850000154
And
Figure RE-GDA0002999360850000155
further repeating the steps, and continuously and iteratively updating the parameters of the ARIS deployment optimization problem until the parameters are updated to the parameters
Figure RE-GDA0002999360850000156
And converging to obtain the local optimal strategy for ARIS deployment.
S105: based on the ARIS passive beam forming optimization strategy of step S103 and the ARIS deployment optimization strategy of step S104, steps S103-S104 are repeatedly executed through an alternating optimization framework, and iterative updating is performed until the ARIS passive beam forming strategy, the variables of the ARIS deployment strategy, and the system secure transmission rate converge, so as to obtain the optimal secure transmission strategy of the communication network model.
Specifically, the AIRS passive beamforming and its deployment are updated iteratively through an alternating optimization framework, first randomly choosing those satisfying constraints
Figure RE-GDA0002999360850000157
And wiUpdating i ← i + 1; according to step S103, at ARIS deployment at wi-1In case of location, the passive beamforming is updated to
Figure RE-GDA0002999360850000158
Then according to step S104, in AIRS passive beam forming
Figure RE-GDA0002999360850000159
In case of updating the deployment location of the ARIS to wi(ii) a According to
Figure RE-GDA00029993608500001510
And wiObtaining an updated objective function deltai(ii) a Repeating the steps S103-S104 to continuously and iteratively update the target function until convergence
Figure RE-GDA00029993608500001511
Therefore, the maximum safe transmission rate of the communication network model is obtained, and anti-interference communication is realized.
The anti-interference method based on the space-based reconfigurable intelligent surface can provide reliable safe transmission guarantee for network legal users when an eavesdropping node interferes and attacks legal transmission in a wireless communication network. Aiming at the problems in the prior art, the aerial reconfigurable intelligent surface is deployed in the communication network, the interference from the eavesdropping node is relieved at the receiving end by optimizing the passive beam forming of the AIRS and the deployment of the AIRS, the legal transmission is improved, the safe transmission rate of the network can be effectively improved, and compared with the traditional safe transmission method, the method has the advantage that the transmission safety of the network is effectively improved.
The technical effects of the present invention will be described in detail with reference to simulations.
The invention simulates the anti-interference method based on the space-based reconfigurable intelligent surface and verifies the superiority of the method. The method comprises the following specific steps: the present invention sets a 400 x 400(m) area in which the horizontal positions of the legitimate transmitting end, receiving end and eavesdropper on the ground are (0, 400), (200, 0) and (400, 200), respectively, assuming that they all have a single antenna. The ARIS is deployed at a height of 200 meters and consists of 50 reflective elements. The ratio of the ARIS reflective element spacing to the wavelength is 0.5. The path loss at the reference distance of 1m is 20 dB. The path loss exponent for the terrestrial channel is 4.0 and the air-ground channel is 2.3. The background noise power is-140 dBW. Both the legal transmit power and the interference power are 1W.
In fig. 3-5, the performance of the system in suppressing interference is shown when various factors are considered. Overall, from all results, the case with ARIS is clearly superior to the case without AIRS. In particular, fig. 3 depicts system safe transmission rates with different transmit and interference power. It can clearly be seen that the safe transmission rate of the system increases with increasing transmit power and decreases with increasing interference power. It can also be seen that the ARIS will result in a higher anti-interference performance gain at higher interference power than at relatively lower interference power. Thus, the anti-jamming approach proposed by the present invention is clear to the benefit of the wireless system by a combination of interference mitigation and enhancement of legitimate transmissions. In fig. 4, the safe transmission rates at different positions at the receiving end and ARIS deployment at different altitudes are shown. As shown, the legal transmission of the system can be significantly improved when the receiving end is closer to the transmitting end, or the ARIS is deployed lower and thus closer to the legal transmission node. Furthermore, when the receiver is located further away or the ARIS rises higher, the reflected link is more sensitive to changes in other parameters, which cause drastic changes in the transmission rate when they exceed a certain threshold. Figure 5 shows the performance when considering different air-to-ground path loss indices and the number of reflective elements. Wherein the path loss of the reflective link can significantly affect the security performance of the system. In addition, when the large-scale path loss is high, increasing the number of reflecting elements can be effectively compensated. In addition, the improvement of the transmission rate brought by increasing the number of ARIS reflecting elements is more obvious under the condition of smaller path loss.
As existing tamper resistant mechanisms rely on encryption techniques, distribution and management of keys becomes increasingly difficult as the number of devices grows. And with the improvement of the computing power of the equipment, the risk of encryption cracking is increased, secondly, the existing physical layer security strategy mainly depends on artificial noise or a beam forming technology, the utilization of the transmission environment is poor, the technology meets the bottleneck, in addition, the existing reconfigurable intelligent surface-based enhanced receiving end communication security technology is less, and the communication security of the receiving end in an uplink communication link cannot be effectively guaranteed.
The existing physical layer security technology is mainly based on the research of transmission beam forming, and the introduction of reconfigurable intelligent surface enhanced communication security in the physical layer security is a novel solution; in the considered scene of the invention, the transmitting end antenna and the receiving end only have a single antenna, so that the transmitting end lacks enough spatial freedom, and the transmitting end transmission beam forming technology has little effect. Therefore, there is a need to introduce ARIS-assisted signal transmission, provide additional transmission beam forming, and enhance the legal reception at the receiving end. In addition, the ARIS can also suppress interference attacks by eavesdroppers, thereby maximizing interference immunity of the communication system.
The invention adopts a physical layer security scheme, which does not need a secret key and has lower complexity; the ARIS auxiliary signal transmission is introduced, so that legal reception of a receiving end is enhanced, meanwhile, interference attack of an eavesdropper is inhibited, the anti-interference method based on the space-based reconfigurable intelligent surface is realized, and the anti-interference performance of wireless communication is greatly improved compared with the traditional scheme.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.

Claims (10)

1. An anti-interference method based on a space-based reconfigurable intelligent surface is characterized by comprising the following steps:
s101, constructing a secure communication system model by using a plurality of legal transceiving nodes working on the ground, ARIS deployed in the air and a wiretapping node on the bottom surface, and determining the instantaneous signal-to-noise ratio and the secure transmission rate of the secure communication system model;
s102, constructing an optimization problem with the aim of maximizing the safe transmission rate according to the instantaneous signal-to-noise ratio and the safe transmission rate;
s103, solving an optimization problem with the maximum safe transmission rate as a target by fixing the deployment of the ARIS and adopting manifold optimization to obtain an ARIS beam forming local optimal strategy;
s104, obtaining an ARIS deployed local optimal strategy by a continuous convex approximation optimization method based on the ARIS beam forming local optimal strategy obtained in the step S103;
and S105, repeatedly executing the steps S103-S104 through an alternative optimization framework based on the ARIS beam forming optimization strategy of the step S103 and the ARIS deployed local optimal strategy of the step S104, and iteratively updating until variables of the ARIS beam forming optimization strategy and the ARIS deployed local optimal strategy and the system security transmission rate are converged to obtain the optimal security transmission strategy of the communication network model.
2. The anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 1, wherein in step S101, a channel gain model between nodes is first analyzed through a secure communication system model, an instantaneous signal-to-noise ratio of the secure communication system model is determined according to the channel gain model, and a secure transmission rate is determined according to the instantaneous signal-to-noise ratio.
3. The anti-jamming method based on the space-based reconfigurable intelligent surface of claim 2, wherein the expression of the instantaneous signal-to-noise ratio is as follows:
Figure RE-FDA0002999360840000011
wherein, PSIs the transmission power, PJIs the interference power, hSD,hJD,hRD,hSR,hJRA corresponding channel state matrix is represented and,
Figure RE-FDA0002999360840000021
is the background noise power, Θ is the reflection coefficient matrix of ARIS;
the expression of the secure transmission rate is as follows:
C＝log(1+η)
4. the anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 3, wherein the expression of the optimization problem aiming at maximizing the safe transmission rate in step S102 is as follows:
Figure RE-FDA0002999360840000022
Figure RE-FDA0002999360840000023
Figure RE-FDA0002999360840000024
where C is the safe transmission rate, θ is the phase shift of the reflective element, w is the horizontal position of the ARIS deployment, and all nodes are located at
Figure RE-FDA0002999360840000025
Within the area of the definition, the area of the display screen,
Figure RE-FDA0002999360840000026
and
Figure RE-FDA0002999360840000027
scale on the x-axis and y-axis.
5. The anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 1 or 4, wherein the method for obtaining the local optimal strategy of ARIS passive beam forming in step S103 is as follows:
and replacing the optimization problem with the goal of maximizing the safe transmission rate by adopting the optimization problem of minimizing the inverse of the instantaneous signal-to-noise ratio, and solving the optimization problem of minimizing the inverse of the instantaneous signal-to-noise ratio by adopting manifold optimization to obtain a local optimal strategy of ARIS passive beam forming.
6. The anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 5, wherein the step S103 of obtaining the local optimal strategy of ARIS passive beam forming comprises the following steps:
step S1031, replacing the optimization problem with the goal of maximizing the safe transmission rate by the optimization problem with the minimum inverse of the instantaneous signal-to-noise ratio, and rewriting the optimization problem with the goal of maximizing the safe transmission rate into the following expression:
Figure RE-FDA0002999360840000031
Figure RE-FDA0002999360840000032
step S1032, finding out a local optimal solution by using manifold optimization, and expressing the manifold as
Figure RE-FDA0002999360840000033
For the
Figure RE-FDA0002999360840000034
At any point in
Figure RE-FDA0002999360840000035
The tangent space is defined as the set of all tangent vectors, expressed as
Figure RE-FDA0002999360840000036
Step S1033 for
Figure RE-FDA0002999360840000037
Iterative process of contraction, initialized first
Figure RE-FDA0002999360840000038
χi，ρi，
Figure RE-FDA0002999360840000039
Wherein, χi+1Is the Polak-Ribiere parameter, rhoiAnd ζiIs that
Figure RE-FDA00029993608400000310
Direction and step size of the shrink, ξ, in the iterative processiRepresenting the search direction in euclidean space,
Figure RE-FDA00029993608400000311
is the euclidean space gradient;
shaping passive beams
Figure RE-FDA00029993608400000312
Is updated to
Figure RE-FDA00029993608400000313
The update is performed by the following formula:
Figure RE-FDA00029993608400000314
wherein the content of the first and second substances,
Figure RE-FDA00029993608400000315
representing the normalization process, step size piCan be obtained by Armijo backtracking line search;
step S1034, then
Figure RE-FDA00029993608400000316
New Riemann gradient, Polak-Ribiere parameter,
Figure RE-FDA00029993608400000317
To
Figure RE-FDA00029993608400000318
The tangential space transformation process, and the conjugate search direction;
the updated formula of the riemann gradient is as follows:
Figure RE-FDA00029993608400000319
Polak-Ribiere is updated as follows:
Figure RE-FDA00029993608400000320
Figure RE-FDA00029993608400000321
to
Figure RE-FDA00029993608400000322
The tangential space transformation process of (a) is as follows:
Figure RE-FDA0002999360840000041
Figure RE-FDA0002999360840000042
the conjugate search direction update formula is as follows:
Figure RE-FDA0002999360840000043
step S1035, after obtaining the update
Figure RE-FDA0002999360840000044
χi，ρi，
Figure RE-FDA0002999360840000045
Repeating the steps S1032-S1034 for iteration after the parameters until the Riemann gradient is less than the predetermined threshold
Figure RE-FDA0002999360840000046
Thus, the ARIS passive beam forming local optimal strategy can be obtained when the ARIS is deployed fixedly.
7. The anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 1 or 6, wherein the method for obtaining the ARIS deployment local optimal strategy in step S104 is as follows:
according to the obtained ARIS wave beam forming local optimal strategy, an objective function of a maximized system instantaneous signal-to-noise ratio problem is expressed as an ARIS deployment explicit function, a variable is introduced to convert the objective function into a quasi-convex function, the original constraint and the non-convex constraint in the introduced constraint are continuously convex, an optimization problem with the quasi-convex objective function and the convex constraint is obtained, the optimization problem with the quasi-convex objective function and the convex constraint is solved, and the ARIS deployment local optimal strategy is obtained.
8. The anti-interference method based on the space-based reconfigurable intelligent surface as claimed in claim 7, wherein the expression of the optimization problem with the quasi-convex objective function and the convex constraint is as follows:
Figure RE-FDA0002999360840000047
Figure RE-FDA0002999360840000048
φ≥0
u≥0，v≥0
Figure RE-FDA0002999360840000049
Figure RE-FDA00029993608400000410
Figure RE-FDA00029993608400000411
defining:
Figure RE-FDA0002999360840000051
Figure RE-FDA0002999360840000052
Figure RE-FDA0002999360840000053
Figure RE-FDA0002999360840000054
Figure RE-FDA0002999360840000055
Figure RE-FDA0002999360840000056
where the variables u, v and φ are the parameters introduced, L0For reference the path loss at a distance of 1m,
Figure RE-FDA0002999360840000057
is the path loss exponent of the terrestrial radio transmission,
Figure RE-FDA0002999360840000058
is the path loss exponent of the air-to-ground channel,
Figure RE-FDA0002999360840000059
representing small scale fading therein, d is the spacing between reflective elements, λ is the wavelength, φZRDenotes the cosine of the angle of arrival, phiRDRepresenting the cosine of the angle of arrival.
9. The anti-interference method based on the space-based reconfigurable intelligent surface of claim 8, wherein the method for obtaining the optimal security transmission strategy of the communication network model in step S105 is as follows:
firstly, an ARIS beam forming optimization strategy and the deployment thereof are updated in an iterative mode by utilizing an alternative optimization framework, and firstly, the ARIS beam forming optimization strategy which meets constraint conditions is randomly selected
Figure RE-FDA00029993608400000510
And wiUpdating i ← i +1, according to step S103 when ARIS is deployed at wi-1In case of location, the passive beamforming is updated to
Figure RE-FDA00029993608400000511
Then passively beamformed in the AIRS to
Figure RE-FDA00029993608400000512
In case of updating the deployment location of the ARIS to wiAccording to
Figure RE-FDA00029993608400000513
And wiObtaining an updated objective function deltai(ii) a Repeating the steps S103-S104 to continuously and iteratively update the target function until convergence
Figure RE-FDA00029993608400000514
Thereby obtaining the maximum safe transmission rate of the communication network model.
10. A system based on the anti-interference method based on the space-based reconfigurable intelligent surface of any one of claims 1 to 9, comprising,
the safety communication system module is used for determining the instantaneous signal-to-noise ratio and the safety transmission rate of the safety communication system model according to the constructed safety communication system model;
the safe transmission rate optimization module is used for constructing an optimization problem which takes the maximized safe transmission rate as a target according to the instantaneous signal-to-noise ratio and the safe transmission rate;
the ARIS wave beam forming local optimal strategy module is used for solving an optimization problem with the maximum safe transmission rate as a target by fixing the deployment of the ARIS and adopting manifold optimization to obtain an ARIS wave beam forming local optimal strategy;
the ARIS deployed local optimal strategy module is used for obtaining an ARIS deployed local optimal strategy through a continuous convex approximation optimization method according to an ARIS beam forming local optimal strategy;
and the optimal safe transmission strategy module is used for iteratively solving the ARIS wave beam forming optimization strategy and the ARIS deployed local optimal strategy by adopting an alternate optimization framework to obtain the optimal safe transmission strategy of the communication network model.
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