CN116017465A - RIS-based auxiliary wireless communication secret rate maximization model and method - Google Patents

RIS-based auxiliary wireless communication secret rate maximization model and method Download PDF

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CN116017465A
CN116017465A CN202211680905.9A CN202211680905A CN116017465A CN 116017465 A CN116017465 A CN 116017465A CN 202211680905 A CN202211680905 A CN 202211680905A CN 116017465 A CN116017465 A CN 116017465A
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杨柳
赵磊
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Shanghai Dianji University
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Abstract

The invention provides a security rate maximization model and a security rate maximization method based on RIS auxiliary wireless communication, wherein the method comprises the following steps: calculating the received power of legal users and eavesdroppers, and calculating the signal-to-interference-and-noise ratio of the legal users and the eavesdroppers by utilizing the obtained received power and combining distortion noise caused by hardware damage; obtaining the reachable rates of legal users and eavesdroppers according to the signal-to-interference-and-noise ratio, and establishing a wireless communication secret rate maximization model; fixing RIS passive beam forming vector to optimize active beam forming vector of base station; the fixed base station active beamforming vector optimizes the RIS passive beamforming vector; and (3) introducing the optimized base station active beam forming vector and the RIS passive beam forming vector into a system security rate maximization model, and calculating to obtain a maximum security rate value. The RIS-assisted wireless communication secret rate maximization model and the RIS-assisted wireless communication secret rate maximization method can reduce hardware implementation difficulty and improve secret rate of a system.

Description

RIS-based auxiliary wireless communication secret rate maximization model and method
Technical Field
The invention relates to the technical field of wireless communication physical layer security, in particular to a RIS-assisted wireless communication secret rate maximization model and a method.
Background
The intelligent super surface (Reconfigurable Intelligence Surface, RIS) is an artificial electromagnetic surface structure with programmable electromagnetic characteristics, and is formed by arranging a large number of carefully designed electromagnetic units, the electromagnetic properties of the electromagnetic units can be dynamically regulated and controlled through a control circuit, the intelligent reconstruction of the wireless signal propagation characteristics in a three-dimensional space is realized, and the limitation of passive adaptation of the traditional wireless environment is further broken through. The intelligent super-surface is used as a basic innovation technology, has the advantages of low cost, low power consumption and easy deployment, and the application scene comprises deterministic wireless transmission, wireless coverage blind supplement, wireless coverage expansion, wireless system capacity enhancement, special scene coverage of indoor carriages and the like.
The dominant aspect of RIS-assisted wireless communication at present, especially in terms of suppressing the eavesdropper rate by taking noise into account, is to suppress the eavesdropper rate of an eavesdropper by introducing artificial noise at the base station side. However, the conventional RIS-assisted wireless communication system is still in a start-up phase in consideration of hardware damage, and the current RIS-assisted wireless communication system is still in a start-up phase, and a situation of large-scale implementation does not occur, even though a large number of conventional methods have been applied to the wireless communication system to improve the privacy rate, a satisfactory result has not been obtained yet.
In recent years, in the article of expert, the rate of an eavesdropper is basically restrained by a method of introducing artificial noise into a base station side, so that the confidentiality rate of the whole wireless communication system is improved, and the complexity of hardware implementation is increased due to the introduction of the artificial noise, so that the energy consumption of the system is increased. Meanwhile, the established optimization problem constraint is increased, and the complexity of solving the optimization problem is increased.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a RIS-based auxiliary wireless communication security rate maximization model and a RIS-based auxiliary wireless communication security rate maximization method which can reduce hardware implementation difficulty and improve security rate of a system.
In order to solve the problems, the technical scheme of the invention is as follows:
a security rate maximization model based on RIS auxiliary wireless communication, which is applied to a RIS auxiliary wireless communication system, the system comprises a base station provided with M antennas, an RIS comprising N reflecting units, one legal user and K eavesdroppers, wherein the base station transmits a reflected signal to the legal user through the RIS to prevent eavesdroppers from eavesdropping,base station to RIS channel matrix
Figure BDA0004019317770000021
The channels from the base station to the legal user and the kth eavesdropper are +.>
Figure BDA0004019317770000022
And
Figure BDA0004019317770000023
the RIS channel to legal user and kth eavesdropper is +.>
Figure BDA0004019317770000024
and />
Figure BDA0004019317770000025
The transmission signals of the base station are: x=fs+m t Where s represents a secret independent Gaussian signal and satisfies E [ |s| | ] 2 ]＝1，/>
Figure BDA0004019317770000026
For the beamforming vector of the base station,>
Figure BDA0004019317770000027
for independent gaussian emission distortion noise, the signal received by a legitimate user is expressed as: />
Figure BDA0004019317770000028
wherein ,/>
Figure BDA0004019317770000029
Figure BDA00040193177700000210
Representing a complex additive white gaussian noise at a legitimate user, m U For independent zero-mean gaussian distortion noise at legitimate users, the signal received by an eavesdropper is represented as: />
Figure BDA00040193177700000211
wherein ,/>
Figure BDA00040193177700000212
Representing Additive White Gaussian Noise (AWGN) at the eavesdropper, the signal-to-interference-and-noise ratios at the legitimate user and the kth eavesdropper are expressed as:
Figure BDA00040193177700000213
Figure BDA00040193177700000214
preferably, the achievable rates of the legitimate user and the kth eavesdropper are expressed as: r is R U ＝log 2 (1+γ U) and
Figure BDA00040193177700000216
preferably, under the condition of maximum transmitting power constraint of the base station and RIS phase shift unit mode constraint, the active beam forming vector at the base station and the passive beam forming vector at the RIS are jointly optimized, so that the confidentiality rate is maximized, and the optimization expression formula is as follows:
Figure BDA00040193177700000215
wherein ,Pmax Is the maximum transmit power at the base station.
Further, the invention also provides a security rate maximizing method based on RIS auxiliary wireless communication, which comprises the following steps:
calculating the received power of legal users and eavesdroppers, calculating the signal-to-interference-plus-noise ratio of the legal users and the eavesdroppers and the reachable rate of the eavesdroppers by utilizing the obtained received power and combining the distortion noise caused by hardware damage, and establishing a wireless communication confidentiality rate maximization model;
fixing RIS passive beam forming vector to optimize active beam forming vector of base station;
the fixed base station active beamforming vector optimizes the RIS passive beamforming vector;
and (3) introducing the optimized base station active beam forming vector and the RIS passive beam forming vector into a system security rate maximization model, and calculating to obtain a maximum security rate value.
Preferably, the signal-to-interference-and-noise ratio at the legitimate user and the kth eavesdropper is expressed as:
Figure BDA0004019317770000031
Figure BDA0004019317770000032
preferably, the achievable rates at the legitimate user and the kth eavesdropper can be expressed as: r is R U ＝log 2 (1+γ U) and
Figure BDA0004019317770000033
establishing a secret rate maximization model by using the obtained rate, the total transmission power of the base station and the constraint of the RIS phase shift unit mode: />
Figure BDA0004019317770000034
wherein ,Pmax Is the maximum transmit power at the base station.
Preferably, the step of optimizing the base station active beamforming vector by the fixed RIS passive beamforming vector specifically includes: optimizing the base station active beamforming vector for any given RIS passive beamforming vector can be translated into:
Figure BDA0004019317770000035
s.t.f H f≤P max
the problem is simplified into by applying a semi-definite relaxation method:
Figure BDA0004019317770000036
s.t. Tr(F)≤P max ,F±0
obtaining optimal F:
Figure BDA0004019317770000041
s.t.Tr(F)≤P max f+/-0, and effectively solving by introducing a relaxation variable and adopting a convex optimization solver CVX.
Preferably, the step of optimizing the RIS passive beamforming vector by the fixed base station active beamforming vector specifically includes: optimizing the RIS passive beamforming vector for any given base station active beamforming vector can be translated into:
Figure BDA0004019317770000042
s.t. |v n |＝1,n＝1,...,N
the problem is simplified into by applying a semi-definite relaxation method:
Figure BDA0004019317770000043
s.t. V±0,V n,n ＝1,n＝1,…,N+1
obtain the optimal
Figure BDA0004019317770000044
By introducing a relaxation variable and adopting a convex optimization solver CVX, effective solving is carried out.
Preferably, the step of introducing the optimized active beamforming vector of the base station and the RIS passive beamforming vector into a system security rate maximization model to calculate a maximum security rate value specifically includes: and (3) bringing the optimized base station active beam forming vector f and the RIS passive beam forming vector v into a system security rate maximization model, calculating to obtain a maximum security rate value, and analyzing the complexity of the overall algorithm.
Preferably, the complexity of the overall algorithm is: o (L) 3 (L 1 max{M,K} 4 M 1/2 +L 2 max{N,K} 4 N 1/2 ) And), wherein L 1 Representing the number of iterations to solve the active beamforming problem of the base station, L 2 Representing the number of iterations to solve the RIS passive beamforming problem, L 3 Representing the number of iterations of the overall algorithm.
Compared with the prior art, the invention provides a novel RIS-assisted wireless communication security rate maximization model and method based on distortion noise caused by RIS and hardware damage, and the maximum security rate is obtained by adopting an alternate optimization method to jointly optimize the active beamforming vector of the base station and the passive beamforming vector of the RIS, so that the hardware implementation difficulty is reduced, and the security rate of the system is improved.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a RIS assisted wireless communication system according to an embodiment of the present invention;
fig. 2 is a flowchart of a security rate maximizing method based on RIS-assisted wireless communication according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, and will make the technical solution of the present invention and its advantageous effects obvious.
Specifically, fig. 1 is a schematic diagram of an RIS-assisted wireless communication system according to an embodiment of the present invention, where the system includes a base station equipped with M antennas, an RIS including N reflection units, a legal user, and K eavesdroppers, as shown in fig. 1. The base station equipped with M antennas transmits the reflected signals to legal users through RIS, preventing eavesdroppers from eavesdropping. Base station to RIS channel matrix
Figure BDA0004019317770000051
The channels from the base station to the legal user and the kth eavesdropper are +.>
Figure BDA0004019317770000052
and />
Figure BDA0004019317770000053
The RIS channel to legal user and kth eavesdropper is +.>
Figure BDA0004019317770000054
and />
Figure BDA0004019317770000055
Considering hardware impairments at the base station and at the legitimate user, the signal received by the legitimate user can be expressed as:
Figure BDA0004019317770000056
wherein ,/>
Figure BDA0004019317770000057
Figure BDA0004019317770000058
Representing a complex additive Gaussian white noise at the legal user, the variance of the noise being +.>
Figure BDA0004019317770000059
m U Representing independent zero-mean gaussian distortion noise at the legitimate user.
Φ=diag (v) is the phase shift matrix of RIS. By variable substitution of
Figure BDA00040193177700000510
wherein ,
Figure BDA00040193177700000511
the signal received by the kth eavesdropper can be expressed as:
Figure BDA00040193177700000512
wherein ,
Figure BDA00040193177700000513
representing Additive White Gaussian Noise (AWGN) at an eavesdropper with a noise variance of +.>
Figure BDA00040193177700000514
The signal-to-interference-and-noise ratio (SINR) at the legitimate user and the kth eavesdropper can be expressed as:
Figure BDA0004019317770000061
/>
Figure BDA0004019317770000062
then the achievable rates at the legitimate user and the kth eavesdropper can be expressed as: r is R U ＝log 2 (1+γ U) and
Figure BDA0004019317770000063
and establishing a confidentiality rate maximization model by using the obtained rate, the total transmission power of the base station and the constraint of the RIS phase shift unit mode.
The optimization problem can be expressed specifically as:
Figure BDA0004019317770000064
wherein ,Pmax Is the maximum transmit power at the base station.
Fig. 2 is a flowchart of a security rate maximizing method based on RIS-assisted wireless communication according to an embodiment of the present invention, as shown in fig. 2, where the method includes the following steps:
s1: calculating the received power of legal users and eavesdroppers, and calculating the signal-to-interference-and-noise ratio of the legal users and the eavesdroppers by utilizing the obtained received power and combining distortion noise caused by hardware damage;
specifically, the receiving power of the legal user is calculated according to the transmitting power of the base station, the channel matrix from the base station to the RIS and the channel matrix from the RIS to the legal user, the receiving power of the eavesdropper is calculated according to the transmitting power of the base station, the channel matrix from the base station to the RIS and the channel matrix from the RIS to the eavesdropper, and the signal-to-interference-and-noise ratio of the legal user and the eavesdropper is calculated by utilizing the obtained receiving power and combining distortion noise caused by hardware damage.
The signal-to-interference-and-noise ratio (SINR) at the legitimate user and the kth eavesdropper can be expressed as:
Figure BDA0004019317770000065
Figure BDA0004019317770000066
s2: obtaining the reachable rates of legal users and eavesdroppers according to the signal-to-interference-and-noise ratio, and establishing a wireless communication secret rate maximization model;
in particular, the achievable rates at the legitimate user and the kth eavesdropper can be expressed as: r is R U ＝log 2 (1+γ U) and
Figure BDA0004019317770000071
and establishing a confidentiality rate maximization model by using the obtained rate, the total transmission power of the base station and the constraint of the RIS phase shift unit mode.
The optimization problem can be expressed specifically as:
Figure BDA0004019317770000072
wherein ,Pmax Is the maximum transmit power at the base station. />
S3: fixing RIS passive beam forming vector to optimize active beam forming vector of base station;
specifically, optimizing the base station active beamforming vector f for any given RIS passive beamforming vector v, the problem can be expressed as:
Figure BDA0004019317770000073
s.t.f H f≤P max
by applying the semi-definite relaxation method, the problem can be reduced to:
Figure BDA0004019317770000074
s.t.Tr(F)≤P max ,F±0
wherein f=ff H . According to solving equations
Figure BDA0004019317770000075
Obtained->
Figure BDA0004019317770000076
The maximum and Sion's minimum max theorem converts the optimization problem described above into: />
Figure BDA0004019317770000077
For a given F, the optimal closed-loop solution can be expressed as:
Figure BDA0004019317770000078
Figure BDA0004019317770000079
for solving the above problems
Figure BDA0004019317770000081
The following problems are brought in, an optimal F can be obtained,
Figure BDA0004019317770000082
by introducing relaxation variables and using a convex optimization solver CVX, an efficient solution can be made. F can be recovered by eigenvalue decomposition if the rank of F is 1, otherwise F is recovered by gaussian randomization.
S4: the fixed base station active beamforming vector optimizes the RIS passive beamforming vector;
specifically, optimizing the RIS passive beamforming vector v for any given base station active beamforming vector f, the problem can be expressed as:
Figure BDA0004019317770000083
s.t. |v n |＝1,n＝1,...,N
wherein ,
Figure BDA0004019317770000084
Figure BDA0004019317770000085
indicating any phase rotation. By applying the semi-definite relaxation method, the problem can be reduced to:
Figure BDA0004019317770000086
s.t. V±0,V n,n ＝1,n＝1,…,N+1
wherein v=vv. According to solving equations
Figure BDA0004019317770000087
Obtained->
Figure BDA0004019317770000088
The maximum and Sion's minimum max theorem converts the optimization problem described above into: />
Figure BDA0004019317770000089
For a given V, the optimal closed-loop solution can be expressed as:
Figure BDA00040193177700000810
Figure BDA00040193177700000811
for solving the above problems
Figure BDA0004019317770000091
The following problems are brought in, and an optimum V can be obtained.
Figure BDA0004019317770000092
By introducing relaxation variables and using a convex optimization solver CVX, an efficient solution can be made. V can be recovered by eigenvalue decomposition if the rank of V is 1, otherwise V is recovered by gaussian randomization.
S5: and (3) introducing the optimized base station active beam forming vector and the RIS passive beam forming vector into a system security rate maximization model, and calculating to obtain a maximum security rate value.
Specifically, the optimized base station active beam forming vector f and RIS passive beam forming vector v are brought into a system security rate maximization model, so that a maximum security rate value can be calculated, and finally, complexity analysis of an overall algorithm is carried out.
The complexity of the overall algorithm is: o (L) 3 (L 1 max{M,K} 4 M 1/2 +L 2 max{N,K} 4 N 1/2 ) And), wherein L 1 Representing the number of iterations to solve the active beamforming problem of the base station, L 2 Representing the number of iterations to solve the RIS passive beamforming problem, L 3 Representing the number of iterations of the overall algorithm.
In summary, the invention provides a new security rate maximization model and method based on RIS auxiliary wireless communication based on distortion noise caused by RIS and hardware damage, and the maximum security rate is obtained by adopting an alternate optimization method to jointly optimize the active beamforming vector of the base station and the passive beamforming vector of the RIS, thereby reducing hardware realization difficulty and improving security rate of the system.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the invention. The embodiments of the present application and features in the embodiments may be combined with each other arbitrarily without conflict.

Claims (10)

1. A security rate maximization model based on RIS auxiliary wireless communication is applied to a RIS auxiliary wireless communication system, the system comprises a base station provided with M antennas, RIS containing N reflecting units, one legal user and K eavesdroppers, and is characterized in that the base station transmits reflected signals to the legal users through the RIS to prevent eavesdroppers from eavesdropping, and a channel matrix from the base station to the RIS is that
Figure FDA0004019317760000011
The channels from the base station to the legal user and the kth eavesdropper are +.>
Figure FDA0004019317760000012
And
Figure FDA0004019317760000013
the RIS channel to legal user and kth eavesdropper is +.>
Figure FDA0004019317760000014
and />
Figure FDA0004019317760000015
The transmission signals of the base station are: x=fs+m t Where s represents a secret independent Gaussian signal and satisfies E [ |s| | ] 2 ]＝1，/>
Figure FDA0004019317760000016
For the beamforming vector of the base station,>
Figure FDA0004019317760000017
is independent ofGaussian emission distortion noise, and a signal received by a legal user is expressed as: />
Figure FDA0004019317760000018
wherein ,
Figure FDA0004019317760000019
Figure FDA00040193177600000110
representing a complex additive white gaussian noise at a legitimate user, m U For independent zero-mean gaussian distortion noise at legitimate users, the signal received by an eavesdropper is represented as: />
Figure FDA00040193177600000111
wherein ,/>
Figure FDA00040193177600000112
Representing Additive White Gaussian Noise (AWGN) at the eavesdropper, the signal-to-interference-and-noise ratios at the legitimate user and the kth eavesdropper are expressed as:
Figure FDA00040193177600000113
Figure FDA00040193177600000114
2. the RIS-based assisted wireless communication privacy rate maximization model of claim 1, wherein the achievable rates of the legitimate user and the kth eavesdropper are expressed as: r is R U ＝log 2 (1+γ U) and
Figure FDA00040193177600000115
3. the RIS-assisted wireless communication privacy rate maximization model of claim 2, wherein the active beamforming vector at the base station and the passive beamforming vector at the RIS are jointly optimized under the conditions of the maximum transmit power constraint and the RIS phase shift unit mode constraint of the base station to maximize the privacy rate, and the optimization expression is:
Figure FDA0004019317760000021
wherein ,Pmax Is the maximum transmit power at the base station.
4. A method for maximizing security rate of a wireless communication based on RIS assistance, the method comprising the steps of:
calculating the received power of legal users and eavesdroppers, and calculating the signal-to-interference-and-noise ratio of the legal users and the eavesdroppers by utilizing the obtained received power and combining distortion noise caused by hardware damage;
obtaining the reachable rates of legal users and eavesdroppers according to the signal-to-interference-and-noise ratio, and establishing a wireless communication secret rate maximization model;
fixing RIS passive beam forming vector to optimize active beam forming vector of base station;
the fixed base station active beamforming vector optimizes the RIS passive beamforming vector;
and (3) introducing the optimized base station active beam forming vector and the RIS passive beam forming vector into a system security rate maximization model, and calculating to obtain a maximum security rate value.
5. The RIS-based assisted wireless communication privacy rate maximization method of claim 4, wherein the signal-to-interference-and-noise ratio at the legitimate user and the kth eavesdropper is expressed as:
Figure FDA0004019317760000022
Figure FDA0004019317760000023
6. the RIS-based assisted wireless communication privacy rate maximization method of claim 4, wherein the achievable rates at the legitimate user and the kth eavesdropper can be expressed as: r is R U ＝log 2 (1+γ U) and
Figure FDA0004019317760000024
establishing a secret rate maximization model by using the obtained rate, the total transmission power of the base station and the constraint of the RIS phase shift unit mode:
Figure FDA0004019317760000025
wherein ,Pmax Is the maximum transmit power at the base station.
7. The RIS-assisted wireless communication privacy rate maximization method of claim 4, wherein the step of optimizing the base station active beamforming vector with the fixed RIS passive beamforming vector specifically comprises: optimizing the base station active beamforming vector for any given RIS passive beamforming vector can be translated into:
Figure FDA0004019317760000031
s.t.f H f≤P max
the problem is simplified into by applying a semi-definite relaxation method:
Figure FDA0004019317760000032
s.t.Tr(F)≤P max ,F±0
obtaining optimal F:
Figure FDA0004019317760000033
s.t.Tr(F)≤P max f+/-0, and effectively solving by introducing a relaxation variable and adopting a convex optimization solver CVX.
8. The RIS-assisted wireless communication privacy rate maximization method of claim 4, wherein the step of optimizing the RIS passive beamforming vector by the fixed base station active beamforming vector specifically comprises: optimizing the RIS passive beamforming vector for any given base station active beamforming vector can be translated into:
Figure FDA0004019317760000034
s.t.|v n |＝1,n＝1,…,N
the problem is simplified into by applying a semi-definite relaxation method:
Figure FDA0004019317760000035
s.t.V±0,V n,n ＝1,n＝1,…,N+1
obtain the optimal
Figure FDA0004019317760000036
By introducing a relaxation variable and adopting a convex optimization solver CVX, effective solving is carried out.
9. The method for maximizing security rate of wireless communication based on RIS assistance according to claim 4, wherein the step of introducing the optimized base station active beamforming vector and the RIS passive beamforming vector into the system security rate maximizing model to calculate the maximum security rate value specifically comprises: and (3) bringing the optimized base station active beam forming vector f and the RIS passive beam forming vector v into a system security rate maximization model, calculating to obtain a maximum security rate value, and analyzing the complexity of the overall algorithm.
10. The RIS-based assisted wireless communication privacy rate maximization method of claim 9, wherein the overall algorithm is of complexity: o (L) 3 (L 1 max{M,K} 4 M 1/2 +L 2 max{N,K} 4 N 1/2 ) And), wherein L 1 Representing the number of iterations to solve the active beamforming problem of the base station, L 2 Representing the number of iterations to solve the RIS passive beamforming problem, L 3 Representing the number of iterations of the overall algorithm.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116489654A (en) * 2023-05-18 2023-07-25 北京航空航天大学 Intelligent super-surface-assisted physical layer secure communication method for resisting pilot spoofing attack
CN117639945A (en) * 2023-11-23 2024-03-01 天津师范大学 Offshore area direction modulation method based on intelligent reflection surface assistance
CN117978230A (en) * 2024-02-22 2024-05-03 盐城工学院 Double IRS-assisted MISO channel beam forming method and system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116489654A (en) * 2023-05-18 2023-07-25 北京航空航天大学 Intelligent super-surface-assisted physical layer secure communication method for resisting pilot spoofing attack
CN117639945A (en) * 2023-11-23 2024-03-01 天津师范大学 Offshore area direction modulation method based on intelligent reflection surface assistance
CN117978230A (en) * 2024-02-22 2024-05-03 盐城工学院 Double IRS-assisted MISO channel beam forming method and system

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