CN112073102B - Intelligent reflecting surface assisted safe communication method and device - Google Patents

Intelligent reflecting surface assisted safe communication method and device Download PDF

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CN112073102B
CN112073102B CN202010931804.9A CN202010931804A CN112073102B CN 112073102 B CN112073102 B CN 112073102B CN 202010931804 A CN202010931804 A CN 202010931804A CN 112073102 B CN112073102 B CN 112073102B
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irs
base station
representing
jammer
ehr
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CN112073102A (en
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朱政宇
孙钢灿
徐金雷
林宇
郝万明
刘沛佳
李双志
郭亚博
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Zhengzhou 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
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H04B7/043—Power distribution using best eigenmode, e.g. beam forming or beam steering
    • 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
    • H04B7/04013—Intelligent reflective surfaces
    • 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
    • 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
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition

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  • Mobile Radio Communication Systems (AREA)

Abstract

The invention relates to a safe communication method and a safe communication device assisted by an intelligent reflecting surface, wherein the method comprises the following steps: establishing an intelligent reflector assistance-based SWIPT Internet of things system model; jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and intelligent reflecting surface phase shift to construct an optimization problem of maximizing energy acquisition; and converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iterative optimization algorithm to obtain a feasible solution of the original problem. The intelligent reflector and the jammer are combined, a secret communication link of the SWIPT internet of things system based on the assistance of the intelligent reflector is established, a base station transmitting beam forming matrix, a jammer covariance matrix and intelligent reflector phase shift are jointly optimized, communication safety is improved, and meanwhile system energy acquisition capacity is enhanced.

Description

Intelligent reflecting surface assisted safe communication method and device
Technical Field
The invention belongs to the technical field of communication, and particularly relates to an intelligent reflecting surface assisted safe communication method and device.
Background
Further research and development of the sixth generation communication technology (6G) can meet the requirement of the Internet of things (IoT) in the future, but the 6G & IoT architecture has a series of problems of resource allocation, sustainable communication, information security and the like among devices. As the rate of information transmission and the number of mobile terminals increase rapidly, security and reliability of information transmission are of particular importance.
Wireless energy-carrying communication transmission (SWIPT) is a radio frequency energy collection technology, that is, wireless information and energy are transmitted simultaneously, and different from wireless power transmission, information is transmitted while energy interaction is performed with a wireless device. The SWIPT technology can simultaneously realize continuous energy supply and effective communication of equipment in the wireless IoT network, and meets the basic requirements of new generation IoT green communication.
The emerging Intelligent Reflective Surface (IRS) technology is considered to be one of the foreground technologies of the B5G/6G communication system. IRS is a uniform array plane integrated by a large number of low cost, sub-wavelength structures and independently controllable passive electromagnetic reflective elements. The intelligent control system has the main function of randomly adjusting the reflection amplitude and the phase of electromagnetic waves by a controller connected with a transmitter in a software programming mode according to communication link information fed back by signal propagation so as to realize intelligent control on a wireless propagation environment. The reflected signal is constructively added with signals of other paths according to the channel parameters, so that the expected signal power of a receiving end can be enhanced, the communication quality is improved, and the purposes of enhancing capacity and expanding the coverage range are achieved. In addition, compared with a traditional active transceiver/relay, the IRS only reflects signals without amplification of transmission power, and the power consumption is small.
The active and passive reciprocal transmission technology based on the IRS is one of the physical layer solutions of the 6G & IoT system, and simultaneously brings new physical layer security. Most of the current work only considers the IRS assisted SWIPT system model or mainly focuses on the traditional secret transmission system, but the current work is not researched as an interference machine technology for effectively improving the secret speed and energy transmission. By using an external interference machine to transmit interference signals to resist eavesdropping, the communication safety is improved, and meanwhile, the energy acquisition capacity of the system is enhanced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an intelligent reflecting surface assisted safe communication method and device.
The purpose of the invention is realized as follows: an intelligent reflector assisted secure communication method comprises
S1: establishing an intelligent reflector assistance-based SWIPT Internet of things system model;
s2: an interference machine is deployed to transmit interference signals, so that eavesdropping is resisted, the system confidentiality is improved, and the system energy collection is enhanced;
s3: considering the secret rate, the transmitting power and the IRS reflection phase shift constraint, jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and intelligent reflecting surface phase shift, and constructing an optimization problem of maximizing energy acquisition;
s4: and converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iterative optimization algorithm to obtain a feasible solution of the original problem.
The step S1 specifically includes:
the method comprises the steps of establishing an IRS-assisted SWIPT (wireless local area network) system, wherein the system comprises a multi-antenna base station, a single-antenna legal IoT device and an interception device (Eve), deploying an energy collector (EHR) near the IRS to collect energy of radio frequency signals, and assuming that the base station is provided with M antennas, and the IRS is provided with N reflection units.
The step S2 specifically includes:
a configuration root antenna jammer is deployed in an IRS-assisted SWIPT internet of things system to transmit an interference signal, and the transmitted interference wave beam is optimized to resist eavesdropping, so that information leakage is prevented, the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
The step S3 specifically includes:
by jointly optimizing the secure transmit beamforming vector, the interference covariance matrix, and the IRS phase shifts, maximization of energy harvesting of EHR under the constraints of base station transmit power, interference transmit power, and IoT reachable secret rate is achieved, which may be expressed as
Figure GDA0003228800400000031
Figure GDA0003228800400000032
Figure GDA0003228800400000033
Rs≥Rth (1d)
Figure GDA0003228800400000034
Wherein,
Figure GDA0003228800400000035
and
Figure GDA0003228800400000036
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure GDA0003228800400000037
and
Figure GDA0003228800400000038
representing the jammer to IRS, EHR and reflected link to EHR channel gains, respectively, f1And f2Transmit beamforming vectors, P, for base station and jammer, respectivelyBAnd PJRepresenting the transmission power, R, of the base station and the jammer, respectivelysRepresenting the secret rate, RthRepresenting the privacy rate threshold, the diagonal phase shift matrix of the IRS is represented as
Figure GDA0003228800400000039
θnFor the elements on its major diagonal, (1b) represents the base station transmit power constraint, (1c) represents the jammer transmit power constraint, and (1d) represents the achievable secret rateConstraint, (1e) denotes the IRS reflective element phase shift constraint.
The step S4 specifically includes:
the obtained problem formula (1) is a non-convex quadratic programming problem with quadratic constraint and is difficult to directly solve,
Figure GDA00032288004000000310
and
Figure GDA00032288004000000311
representing the channel gains of the base station to IoT device and Eve respectively,
Figure GDA0003228800400000041
and
Figure GDA0003228800400000042
representing the jammer to IoT devices and Eve's channel gains respectively,
Figure GDA0003228800400000043
and
Figure GDA0003228800400000044
channel gains representing IRS reflection base station signals and jammer signals to IoT devices and Eve, respectively, of
Figure GDA0003228800400000045
Figure GDA0003228800400000046
Figure GDA0003228800400000047
Definition of
Figure GDA0003228800400000048
And
Figure GDA0003228800400000049
order to
Figure GDA00032288004000000410
v＝[uH,1]Auxiliary variable
Figure GDA00032288004000000411
Introducing a relaxation variable r1> 0 and r2> 0, using the idea of the SPCA technique, assuming f1、f2、r1And r2To a corresponding known point, σ2Represents the variance of the noise, and therefore, expresses the original non-convex problem as
Figure GDA00032288004000000412
Figure GDA00032288004000000413
Figure GDA00032288004000000414
Figure GDA00032288004000000415
Figure GDA00032288004000000416
Figure GDA00032288004000000417
V≥0 (2g)
rank(V)＝1 (2h)
Where (2c), (2d) and (2e) are privacy rate constraints and (2f), (2g) and (2h) are reflection phase shift constraints, due to the combination variable (f)1,f2) Coupling with V still exists, the objective function (2a) is still non-convex, a first-order Taylor expansion method and an SDR method are utilized, and an alternative iterative optimization algorithm is provided to obtain the solution of the original problem.
An intelligent reflector assisted safety communication device comprises
The model establishing module is used for establishing an intelligent reflector assistance-based SWIPT Internet of things system model;
the interference deployment module is used for resisting eavesdropping, improving the system confidentiality and enhancing the system energy acquisition;
the system comprises an equation construction module, a data acquisition module and a data acquisition module, wherein the equation construction module is used for jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and intelligent reflecting surface phase shift and constructing an optimization problem of maximum energy acquisition;
and the iteration solving module is used for converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iteration optimization algorithm to obtain a feasible solution of the original problem.
The model building module specifically comprises:
a system deploys an interference signal configured with M antenna jammers in an IRS-assisted SWIPT Internet of things, and prevents information leakage by optimizing an emitted interference wave beam to resist eavesdropping, so that the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
The interference deployment module specifically includes:
a configuration root antenna jammer is deployed in an IRS-assisted SWIPT internet of things system to transmit an interference signal, and the transmitted interference wave beam is optimized to resist eavesdropping, so that information leakage is prevented, the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
The equation constructing module specifically comprises:
the system comprises an equation construction module, a data acquisition module and a data acquisition module, wherein the equation construction module is used for jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and IRS phase shift and constructing an optimization problem of maximizing energy acquisition;
Figure GDA0003228800400000051
Figure GDA0003228800400000052
Figure GDA0003228800400000053
Rs≥Rth (3d)
Figure GDA0003228800400000054
wherein,
Figure GDA0003228800400000055
and
Figure GDA0003228800400000056
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure GDA0003228800400000057
and
Figure GDA0003228800400000058
respectively representing the channel gains, P, of jammers to IRS, EHR, and reflected link to EHRBAnd PJRepresenting the transmission power of the base station and the jammer, respectively, f1And f2Transmit beamforming vectors, R, for base station and jammer, respectivelysRepresenting the secret rate, RthRepresenting the privacy rate threshold, the diagonal phase shift matrix of the IRS is represented as
Figure GDA0003228800400000061
θnThe elements on its major diagonal, (3b) represent base station transmit power constraints, (3c) represent jammer transmit power constraints, (3d) represent achievable secret rate constraints, and (3e) represent IRS reflective element phase shift constraints.
The iterative solution module specifically includes:
an iterative solution module for utilizing a relaxation variable, semi-definite relaxation methodThe convex approximation method of the auxiliary variables and the sequence parameters converts the non-convex quadratic problem into an equivalent convex problem, provides a feasible solution for obtaining the original problem by an alternative iterative optimization algorithm, obtains a problem formula (3) which is a non-convex quadratic programming problem with quadratic constraint and is difficult to directly solve,
Figure GDA0003228800400000062
and
Figure GDA0003228800400000063
representing the channel gains of the base station to IoT device and Eve respectively,
Figure GDA0003228800400000064
and
Figure GDA0003228800400000065
representing the jammer to IoT devices and Eve's channel gains respectively,
Figure GDA0003228800400000066
and
Figure GDA0003228800400000067
channel gains representing IRS reflection base station signals and jammer signals to IoT devices and Eve, respectively, of
Figure GDA0003228800400000068
Figure GDA0003228800400000069
Figure GDA00032288004000000610
Definition of
Figure GDA00032288004000000611
And
Figure GDA00032288004000000612
order to
Figure GDA00032288004000000613
v＝[uH,1]Auxiliary variable
Figure GDA00032288004000000614
Introducing a relaxation variable r1> 0 and r2> 0, using the idea of the SPCA technique, assuming f1、f2、r1And r2To a corresponding known point, σ2Representing the variance of the noise, expressing the original non-convex problem as
Figure GDA00032288004000000615
Figure GDA00032288004000000616
Figure GDA00032288004000000617
Figure GDA00032288004000000618
Figure GDA00032288004000000619
Figure GDA00032288004000000620
V≥0 (4g)
rank(V)＝1 (4h)
Where (4c), (4d) and (4e) are privacy rate constraints and (4f), (4g) and (4h) are reflection phase shift constraints, due to the combination variable (f)1,f2) Coupling with V still exists, the objective function (4a) is still non-convex, a first-order Taylor expansion method and an SDR method are utilized, and an alternative iterative optimization algorithm is provided to obtain the solution of the original problem. Advantageous effects of the inventionAnd (4) fruit: according to the technical scheme, the intelligent reflecting surface assisted safe communication method and device provided by the invention have the advantages that under the restraint of secret rate, transmitting power and intelligent reflecting surface reflection phase shift, the aim of maximizing the energy collector acquisition power is taken, the base station transmitting beam forming matrix, the jammer covariance matrix and the IRS phase shift are jointly optimized, and the EHR energy acquisition is maximized.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent reflector-assisted secure communication method provided by the present invention.
Fig. 2 is a structural schematic diagram of an IRS-assisted SWIPT IoT system model.
FIG. 3 is a schematic diagram of a system deployment architecture;
FIG. 4 is a graph showing the variation of the energy collected by the EHR with the number of iterations in the present invention for different transmission powers of the base station;
FIG. 5 is a graph of the energy collected by an EHR versus privacy rate for a progressively higher privacy rate in accordance with the present invention;
FIG. 6 is a graph showing the relationship between the energy collected by the EHR and the number N of IRS reflective elements in the present invention when the number N of reflective elements is increased;
FIG. 7 shows that when the transmission power of the base station is gradually increased, the energy collected by the EHR and the transmission power P of the base station in the present inventionBA relationship diagram of (1);
FIG. 8 is a schematic structural diagram of an intelligent reflector assisted secure communication device provided by the present invention;
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an intelligent reflecting surface assisted safe communication method and device. Under the restraint of secret rate, transmission power and IRS reflection phase shift, the aim of maximizing the energy collector collected power is taken, the base station transmission beam forming matrix, the interference machine covariance matrix and the IRS phase shift are jointly optimized, and the EHR energy collection is maximized. As shown in fig. 1, the method comprises the steps of:
s1: establishing an intelligent reflector assistance-based SWIPT Internet of things system model;
s2: an interference machine is deployed to transmit interference signals, so that eavesdropping is resisted, the system confidentiality is improved, and the system energy collection is enhanced;
s3: considering the secret rate, the transmitting power and the IRS reflection phase shift constraint, jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and intelligent reflecting surface phase shift, and constructing an optimization problem of maximizing energy acquisition;
s4: and converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iterative optimization algorithm to obtain a feasible solution of the original problem.
As shown in fig. 2, the method described in this embodiment is applied to an IRS-assisted-based SWIPT internet of things system. Fig. 3 is a schematic diagram of the deployment structure of the system, assuming that the distances from the base station/jammer to the EHR, Eve, and IoT are 5m, 90m, and 100m, respectively, and the distance from the base station/jammer to the IRS channel is a line-of-sight link and is set to be 7 m. The path loss L per meter is 30dB, the path loss indexes between the base station/jammer and the IRS and between the IRS and the EHR/Eve/IoT device are both 2.4, and the path loss index between the base station/jammer EHR/Eve/IoT device is 3. Variance of noise σ2-105dBm, collection efficiency ξ 0.5, base station transmission power PBAnd jammer transmit power PJAre all 15W.
In this embodiment, the specific process of step S1 is as follows:
the method comprises the steps of establishing an IRS-assisted SWIPT (wireless local area network) system, wherein the system comprises a multi-antenna base station, a single-antenna legal IoT device and an interception device (Eve), deploying an energy collector (EHR) near the IRS to collect energy of radio frequency signals, and assuming that the base station is provided with M antennas, and the IRS is provided with N reflection units.
The transmission signal of the base station is
x1＝f1s1 (5)
The transmission signal of the jammer is
x2＝f2s2 (6)
The received signal of the IoT device is denoted as
Figure GDA0003228800400000091
Eve's received signal is
Figure GDA0003228800400000092
The SINR of an IoT device is expressed as
Figure GDA0003228800400000093
Eve SINR is expressed as
Figure GDA0003228800400000094
Wherein,
Figure GDA0003228800400000095
and
Figure GDA0003228800400000096
representing the channel gains of the base station to IRS, IoT devices and Eve respectively,
Figure GDA0003228800400000097
and
Figure GDA0003228800400000098
representing the channel gains of jammers to IRS, IoT devices and Eve respectively,
Figure GDA0003228800400000099
and
Figure GDA00032288004000000910
representing the channel gains of the IRS reflected base station signals and jammer signals to IoT devices and Eve, respectively.
Figure GDA00032288004000000911
A diagonal phase shift matrix representing IRS. Principal diagonal line thetanWhere (0, 2 pi) denotes the phase shift of the nth element of the combined incident signal, where N is 1,2, …, N.
The achievable privacy rate of an IoT device may be expressed as
Rs＝log2(1+ΥU)-log2(1+ΥE) (11)
The EHR is capable of collecting power of
Figure GDA0003228800400000101
Where ξ is the energy conversion efficiency.
Figure GDA0003228800400000102
And
Figure GDA0003228800400000103
respectively, the channel gains of the base station to EHR, the jammer to EHR, and the IRS reflected base station signals and jammer signals to EHR.
In this embodiment, the specific process of step S2 is as follows:
by jointly optimizing the secure transmit beamforming vector, the interference covariance matrix, and the IRS phase shift, the energy collection of the EHR is maximized under the constraints of the base station transmit power, the interference transmit power, and the IoT reachable secret rate. The energy harvesting maximization problem can be expressed as
Figure GDA0003228800400000104
Figure GDA0003228800400000105
Figure GDA0003228800400000106
Rs≥Rth (13d)
Figure GDA0003228800400000107
Wherein, (13b) represents a base station transmit power constraint; (13c) representing an interferer transmit power constraint; rthRepresents a privacy rate threshold, and thus, (13d) represents an achievable privacy rate constraint; (13e) the representation is the IRS reflective element phase shift constraint. Due to the non-convexity of the objective function and the constraint conditions, the optimization problem (13) is a non-convex quadratic programming problem with quadratic constraint, which is difficult to solve directly, but when f is1,f2And Θ is known, it can be solved efficiently using an alternating iterative algorithm.
In this embodiment, the specific process of step S3 is as follows:
order to
Figure GDA0003228800400000111
v＝[uH,1]，
Figure GDA0003228800400000112
Figure GDA0003228800400000113
Figure GDA0003228800400000114
Substituting optimization problem formula (13), simplifying to obtain optimization problem (14)
Figure GDA0003228800400000115
s.t.(13b)，(13c)，(13d)，(13e)
Convex approximation is carried out on a non-convex constraint condition (10d) by adopting a relaxation variable and SPCA method, and two relaxation variables r are introduced firstly1> 0 and r2> 0, (13d) can be converted equivalently
log2(r1r2)≥Rth (15a)
Figure GDA0003228800400000116
Figure GDA0003228800400000117
Further simplified (15) to obtain
Figure GDA0003228800400000118
Figure GDA0003228800400000119
Figure GDA00032288004000001110
Constraint (16a) is equivalent to
Figure GDA00032288004000001111
Further conversion to a quadratic function representation of a quadratic curve, e.g.
Figure GDA00032288004000001112
Definition of
Figure GDA00032288004000001113
(16b) And (16c) are respectively arranged as
Figure GDA00032288004000001114
Figure GDA00032288004000001115
The constraints (18b) and (18c) are still non-convex, but to the right are related to the variable f1And f2The quadratic form of (a) is divided by a linear convex function form, and the form of the quadratic form divided by a linear function can be equivalently converted into a first-order taylor expansion.
Introduction 1: defining a function f with respect to the variables (w, q)A,a(w,q)
Figure GDA0003228800400000121
Wherein A is greater than or equal to 0 and q is greater than or equal to a, function fA,a(w, q) is a first order Taylor expansion centered at (w, q)
Figure GDA0003228800400000122
Next, according to the conclusion of theorem 1, the following (f) is respectively used1,r1) And (f)2,r2) The right half of constraints (18b) and (18c) can be converted to the center point, respectively
Figure GDA0003228800400000123
Figure GDA0003228800400000124
In addition, the first and second substrates are,
Figure GDA0003228800400000125
is of a first order Taylor expansion of
2(2/r2r2/r2 2) (22)
In combination with the above equations (21b), (21c) and (22), the inequalities (18b) and (18c) are converted into the following convex constraints, respectively
Figure GDA0003228800400000126
Figure GDA0003228800400000127
Finally, define
Figure GDA0003228800400000128
And
Figure GDA0003228800400000129
according to (14) to (23), the optimization problem (13) is converted into (24)
Figure GDA00032288004000001210
Figure GDA00032288004000001211
Figure GDA00032288004000001212
V≥0 (24d)
rank(V)＝1 (24e)
(17)，(23b)，(23c)
Due to a combination of variables (f)1,f2) Still coupled with V, the objective function (24a) is still non-convex. The optimization problem (24) is transformed into two sub-problems by using an alternating iteration algorithm, and then SPCA and SDR are respectively utilizedThe method solves the sub-problem. Will be provided with
Figure GDA0003228800400000131
And
Figure GDA0003228800400000132
at point f1And point f2First order Taylor expansions, respectively denoted as
Figure GDA0003228800400000133
Figure GDA0003228800400000134
With (25) and (26), the objective function (21a) can be expressed as
Figure GDA0003228800400000135
Suppose that given a known vector V, a question (24) can be converted into a sub-question (28)
Figure GDA0003228800400000136
s.t.(17)，(23b)，(23c)，(24b)
The problem (28) is a second order cone programming problem that can be solved directly by the CVX tool.
Next, a combination variable (f) is given1,f2) And optimizing the vector V. Question (P3) can be converted into question (P5)
Figure GDA0003228800400000137
s.t.(17)，(23b)，(23c)，(24c)，(24d)，(24e)
The problem (29) is still not convex due to the rank-one constraint. Adopting SDR algorithm, neglecting the constraint condition of rank (V) 1, the problem (29) is converted into a problem (30)
Figure GDA0003228800400000138
s.t.(17)，(23b)，(23c)，(24c)，(24d)
Problem (30) is an SDP problem that can be solved using a convex optimization solver CVX. However, the relaxation problem (30) does not necessarily yield a rank-one solution, i.e., rank (v) ≠ 1, so the optimal objective function values of the problem (30) serve only the upper bound of the problem (29). Therefore, constructing a rank-one solution from the optimal higher-order solution of the problem (30) requires first passing through V ═ U Σ UHPerforming singular value decomposition, wherein U ═ e1,…,eN+1]Sum ═ diag (λ)1,…,λN+1) Respectively a unitary matrix and a diagonal matrix; then, a sub-optimal solution v of the problem (30) is obtained*＝UΣ1/2r, wherein,
Figure GDA0003228800400000139
is based on
Figure GDA00032288004000001310
The random vector is generated by the random vector generator,
Figure GDA00032288004000001311
representing a circularly symmetric complex Gaussian distribution with a mean of zero and a covariance matrix of IN+1Approximating the value of the objective function of (30) to the maximum value obtained by the optimal v in all r by using an independently generated Gaussian random vector r; finally, v can be represented by
Figure GDA0003228800400000141
And (4) reducing. The results show that the SDR method plus multiple executions of randomization ensures maximization of the target value of the problem (30).
According to the technical scheme, the intelligent reflecting surface assisted secure communication method provided by the invention has the advantages that under the constraints of secret rate, transmitting power and IRS reflection phase shift, the maximum EHR energy acquisition can be obtained by jointly optimizing the base station transmitting beam forming matrix, the interference machine covariance matrix and the IRS phase shift.
Fig. 4 shows the variation of the acquired energy of EHR with the number of iterations obtained by the proposed alternating iteration algorithm. As can be seen from the figure, the convergence rate of the submitted alternative iterative algorithm is high, and the algorithm is applied to different PBUnder the condition of (3), the maximum acquisition energy can be obtained only by 5 iterations to achieve convergence.
Figure 5 shows the energy collected by an EHR versus the privacy rate. When M is 8 and N is 40, it can be seen from the figure that as the privacy rate increases, the energy collected by the EHR gradually decreases; comparing the method provided by the embodiment of the invention with the three reference schemes, the energy acquired under the assistance of the IRS is about 2.88dB better than that of the non-IRS scheme, mainly because the IRS provides a new degree of freedom and diversity gain for the system, and the acquired energy of the EHR is improved by optimizing the phase shift of the IRS. The method provided by the embodiment of the invention is superior to the traditional IRS method and the random phase shifting method. This figure demonstrates the effectiveness of the method provided by the embodiments of the present invention, in comparison to a non-Jammer scheme.
FIG. 6 shows the EHR collected energy versus the number of IRS reflective elements, N. Obviously, the method provided by the embodiment of the invention is superior to other reference schemes. Let R bethWhen the number of IRS reflective elements is increased from 10 to 70 at 3bps/Hz, the energy collected by the EHR increases monotonically with the increase in the number of reflective elements N. The main reason is that as the number N of IRS reflection elements increases, the spatial degree of freedom and diversity gain acquired by the IRS will become larger. When N is 10, the energy collected by the non-Jammer scheme is slightly lower than that of the random phase-shift method because the total power of the non-Jammer scheme is lower than that of the random phase-shift scheme, and is better than that of the random phase-shift method at about N15. Compared with a non-IRS scheme, the random phase shift method only obtains a tiny performance gain, and the performance is improved slowly with the increase of N.
FIG. 7 shows the energy collected by the EHR versus the base station transmit power PBThe relationship of (1). It can be seen from the figure that as the base station transmit power increases, the energy harvested by the EHR is related to the base station transmissionThe power monotonically increases. Under the condition that the base station power is the same, the method provided by the embodiment of the invention is about 1.74dB better than the non-Jammer scheme. As can be seen from comparative analysis, the IRS-assisted system brings the gain of energy acquisition performance superior to that of a non-IRS scheme, and the scheme provided by the invention is remarkably superior to a random phase shift method. In addition, with PBAdditionally, the performance difference between the IRS and non-IRS schemes and the performance difference between the IRS phase shift optimization scheme and the random phase shift scheme are gradually increased because optimizing the IRS phase shift directionally enhances the desired reflected signal and thus increases the spatial freedom and diversity gain brought by the IRS.
FIG. 8 is a schematic structural diagram of an intelligent reflector assisted secure communication device provided by the present invention;
the model establishing module is used for establishing an SWIPT Internet of things system model based on IRS assistance;
the system comprises an equation construction module, a data acquisition module and a data acquisition module, wherein the equation construction module is used for jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and IRS phase shift and constructing an optimization problem of maximizing energy acquisition;
and the iteration solving module is used for converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iteration optimization algorithm to obtain a feasible solution of the original problem.
In this embodiment, the model building module specifically includes:
the model establishing module is used for establishing an SWIPT Internet of things system model based on IRS assistance; the wireless communication system comprises a multi-antenna base station, a single-antenna legal IoT device and an interception device (Eve), wherein an energy collector (EHR) is deployed near an IRS to collect energy of radio frequency signals, and the IRS is provided with N reflection units under the condition that the base station is provided with M antennas.
In this embodiment, the interference deployment module specifically includes:
a system deploys an interference signal configured with M antenna jammers in an IRS-assisted SWIPT Internet of things, and prevents information leakage by optimizing an emitted interference wave beam to resist eavesdropping, so that the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
In this embodiment, the equation constructing module specifically includes:
the system comprises an equation construction module, a data acquisition module and a data acquisition module, wherein the equation construction module is used for jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and IRS phase shift and constructing an optimization problem of maximizing energy acquisition;
Figure GDA0003228800400000161
Figure GDA0003228800400000162
Figure GDA0003228800400000163
Rs≥Rth (32d)
Figure GDA0003228800400000164
wherein,
Figure GDA0003228800400000165
and
Figure GDA0003228800400000166
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure GDA0003228800400000167
and
Figure GDA0003228800400000168
respectively representing the channel gains, P, of jammers to IRS, EHR, and reflected link to EHRBAnd PJRepresenting the transmission power of the base station and the jammer, respectively, f1And f2Transmit beamforming vectors, R, for base station and jammer, respectivelysRepresenting the secret rate, RthRepresentative securityThe diagonal phase shift matrix of IRS is represented as the secret rate threshold
Figure GDA0003228800400000169
θnThe elements on its major diagonal, (32b) represent base station transmit power constraints, (32c) represent jammer transmit power constraints, (32d) represent achievable secret rate constraints, and (32e) represent IRS reflective element phase shift constraints.
In this embodiment, the iterative solution module specifically includes:
an iterative solving module, which is used for converting the non-convex quadratic problem into an equivalent convex problem by utilizing a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iterative optimization algorithm to obtain a feasible solution of the original problem, wherein the obtained problem formula (3) is a non-convex quadratic programming problem with quadratic constraint and is difficult to directly solve,
Figure GDA00032288004000001610
and
Figure GDA00032288004000001611
representing the channel gains of the base station to IoT device and Eve respectively,
Figure GDA00032288004000001612
and
Figure GDA00032288004000001613
representing the jammer to IoT devices and Eve's channel gains respectively,
Figure GDA0003228800400000171
and
Figure GDA0003228800400000172
channel gains representing IRS reflection base station signals and jammer signals to IoT devices and Eve, respectively, of
Figure GDA0003228800400000173
Figure GDA0003228800400000174
Figure GDA0003228800400000175
Definition of
Figure GDA0003228800400000176
And
Figure GDA0003228800400000177
order to
Figure GDA0003228800400000178
v＝[uH,1]Auxiliary variable
Figure GDA0003228800400000179
Introducing a relaxation variable r1> 0 and r2> 0, using the idea of the SPCA technique, assuming f1、f2、r1And r2To a corresponding known point, σ2Representing the variance of the noise, expressing the original non-convex problem as
Figure GDA00032288004000001710
Figure GDA00032288004000001711
Figure GDA00032288004000001712
Figure GDA00032288004000001713
Figure GDA00032288004000001714
Figure GDA00032288004000001715
V≥0 (33g)
rank(V)＝1 (33h)
Wherein (33c), (33d) and (33e) are privacy rate constraints and (33f), (33g) and (33h) are reflection phase shift constraints due to a combination variable (f)1,f2) Coupling with V still exists, the objective function (4a) is still non-convex, a first-order Taylor expansion method and an SDR method are utilized, and an alternative iterative optimization algorithm is provided to obtain the solution of the original problem.

Claims (10)

1. An intelligent reflector assisted secure communication method, comprising:
s1: establishing an intelligent reflector assistance-based SWIPT Internet of things system model;
s2: an interference machine is deployed to transmit interference signals, so that eavesdropping is resisted, the system confidentiality is improved, and the system energy collection is enhanced;
s3: considering the secret rate, the transmitting power and the IRS reflection phase shift constraint, jointly optimizing a base station transmitting beam forming matrix, an interference machine covariance matrix and intelligent reflecting surface phase shift, and constructing an optimization problem of maximizing energy acquisition:
Figure FDA0003424202210000011
Figure FDA0003424202210000012
Figure FDA0003424202210000013
Rs≥Rth (1d)
Figure FDA0003424202210000014
wherein,
Figure FDA0003424202210000015
and
Figure FDA0003424202210000016
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure FDA0003424202210000017
and
Figure FDA0003424202210000018
representing the jammer to IRS, EHR and reflected link to EHR channel gains, respectively, f1And f2Transmit beamforming vectors, P, for base station and jammer, respectivelyBAnd PJRepresenting the transmission power, R, of the base station and the jammer, respectivelysRepresenting the secret rate, RthRepresenting the privacy rate threshold, the diagonal phase shift matrix of the IRS is represented as
Figure FDA0003424202210000019
θnFor elements on its major diagonal, (1b) represents a base station transmit power constraint, (1c) represents an interferer transmit power constraint, (1d) represents an achievable secret rate constraint, (1e) represents an IRS reflective element phase shift constraint;
s4: and converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iterative optimization algorithm to obtain a feasible solution of the original problem.
2. An intelligent reflective surface assisted secure communication method according to claim 1,
the step S1 specifically includes:
the method comprises the steps of establishing an IRS-assisted SWIPT (wireless local area network) system, wherein the system comprises a multi-antenna base station, a single-antenna legal IoT device and an interception device (Eve), deploying an energy collector (EHR) near the IRS to collect energy of radio frequency signals, and assuming that the base station is provided with M antennas, and the IRS is provided with N reflection units.
3. The intelligent reflector assisted secure communication method of claim 1, wherein the step S2 specifically includes:
a system deploys an interference signal configured with M antenna jammers in an IRS-assisted SWIPT Internet of things, and prevents information leakage by optimizing an emitted interference wave beam to resist eavesdropping, so that the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
4. The intelligent reflector assisted secure communication method of claim 1, wherein the step S3 specifically includes:
by jointly optimizing the secure transmit beamforming vector, the interference covariance matrix, and the IRS phase shift, the energy collection of the EHR is maximized under the constraints of the base station transmit power, the interference transmit power, and the IoT reachable secret rate, and the problem is expressed as formula (1 a).
5. The intelligent reflector assisted secure communication method of claim 1, wherein the step S4 specifically includes:
the problem formula (1a) is a non-convex quadratic programming problem with quadratic constraints, which is difficult to solve directly,
Figure FDA0003424202210000021
and
Figure FDA0003424202210000022
representing the channel gains of the base station to IoT device and Eve respectively,
Figure FDA0003424202210000023
and
Figure FDA0003424202210000024
representing the jammer to IoT devices and Eve's channel gains respectively,
Figure FDA0003424202210000025
and
Figure FDA0003424202210000026
channel gains representing IRS reflection base station signals and jammer signals to IoT devices and Eve, respectively, of
Figure FDA0003424202210000027
Figure FDA0003424202210000028
Figure FDA0003424202210000029
Definition of
Figure FDA00034242022100000210
And
Figure FDA00034242022100000211
order to
Figure FDA0003424202210000031
v＝[uH,1]Auxiliary variable
Figure FDA0003424202210000032
Introducing a relaxation variable r1>0 and r2>0, using the idea of the SPCA technique, assume
Figure FDA0003424202210000033
And
Figure FDA0003424202210000034
is a corresponding known point，σ2Representing the variance of the noise, expressing the original non-convex problem as
Figure FDA0003424202210000035
Figure FDA0003424202210000036
Figure FDA0003424202210000037
Figure FDA0003424202210000038
Figure FDA0003424202210000039
Figure FDA00034242022100000310
Figure FDA00034242022100000311
rank(V)＝1 (2h)
Where (2c), (2d) and (2e) are privacy rate constraints and (2f), (2g) and (2h) are reflection phase shift constraints, due to the combination variable (f)1,f2) Coupling with V still exists, the objective function (2a) is still non-convex, a first-order Taylor expansion method and an SDR method are utilized, and an alternative iterative optimization algorithm is provided to obtain the solution of the original problem.
6. An intelligent reflector assisted secure communications device, comprising:
the model establishing module is used for establishing an intelligent reflector assistance-based SWIPT Internet of things system model;
the interference deployment module is used for resisting eavesdropping, improving the system confidentiality and enhancing the system energy acquisition;
the equation constructing module is used for jointly optimizing the base station transmitting beam forming matrix, the interference machine covariance matrix and the intelligent reflecting surface phase shift, and constructing an optimization problem of maximizing energy acquisition:
Figure FDA00034242022100000312
Figure FDA00034242022100000313
Figure FDA00034242022100000314
Rs≥Rth (3d)
Figure FDA0003424202210000041
wherein,
Figure FDA0003424202210000042
and
Figure FDA0003424202210000043
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure FDA0003424202210000044
and
Figure FDA0003424202210000045
respectively representing the channel gains, P, of jammers to IRS, EHR, and reflected link to EHRBAnd PJRepresenting the transmission power of the base station and the jammer, respectively, f1And f2Transmit beamforming vectors, R, for base station and jammer, respectivelysRepresenting the secret rate, RthRepresenting the privacy rate threshold, the diagonal phase shift matrix of the IRS is represented as
Figure FDA0003424202210000046
θnAs elements on its major diagonal, (3b) represents a base station transmit power constraint, (3c) represents an interferer transmit power constraint, (3d) represents an achievable secret rate constraint, (3e) represents an IRS reflective element phase shift constraint;
and the iteration solving module is used for converting the non-convex quadratic problem into an equivalent convex problem by using a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing an alternative iteration optimization algorithm to obtain a feasible solution of the original problem.
7. The intelligent reflector-assisted secure communication apparatus of claim 6, wherein the model building module specifically comprises:
the model establishing module is used for establishing an SWIPT Internet of things system model based on IRS assistance; the wireless communication system comprises a multi-antenna base station, a single-antenna legal IoT device and an interception device (Eve), wherein an energy collector (EHR) is deployed near an IRS to collect energy of radio frequency signals, and the IRS is provided with N reflection units under the condition that the base station is provided with M antennas.
8. The intelligent reflector-assisted secure communication apparatus of claim 6, wherein the interference deployment module specifically comprises:
a system deploys an interference signal configured with M antenna jammers in an IRS-assisted SWIPT Internet of things, and prevents information leakage by optimizing an emitted interference wave beam to resist eavesdropping, so that the safe transmission of user information is ensured, and the energy acquisition of the system is enhanced.
9. The intelligent reflector-assisted secure communication apparatus of claim 6, wherein the equation construction module specifically comprises:
an equation construction module for jointly optimizing the base station transmit beamforming matrix and the jammer covariance matrix, as well as the IRS phase shift, to construct an optimization problem (3a) that maximizes energy harvesting, wherein,
Figure FDA0003424202210000051
and
Figure FDA0003424202210000052
and channel gains for base station to IRS, EHR and reflected link to EHR respectively,
Figure FDA0003424202210000053
and
Figure FDA0003424202210000054
representing the jammer to IRS, EHR and reflected link to EHR channel gains, respectively, f1And f2Transmit beamforming vectors, P, for base station and jammer, respectivelyBAnd PJRepresenting the transmission power, R, of the base station and the jammer, respectivelysRepresenting the secret rate, RthRepresenting the privacy rate threshold, the diagonal phase shift matrix of the IRS is represented as
Figure FDA0003424202210000055
θnThe elements on its major diagonal, (3b) represent base station transmit power constraints, (3c) represent jammer transmit power constraints, (3d) represent achievable secret rate constraints, and (3e) represent IRS reflective element phase shift constraints.
10. The intelligent reflector-assisted secure communication apparatus of claim 6, wherein the iterative solution module specifically comprises:
an iterative solving module, which is used for transforming the non-convex quadratic problem into an equivalent convex problem by utilizing a relaxation variable, a semi-definite relaxation method, an auxiliary variable and a sequence parameter convex approximation method, and providing a feasible solution for obtaining the original problem by an alternative iterative optimization algorithm, wherein a problem formula (3a) is a non-convex quadratic programming problem with quadratic constraint and is difficult to directly solve,
Figure FDA0003424202210000056
and
Figure FDA0003424202210000057
representing the channel gains of the base station to IoT device and Eve respectively,
Figure FDA0003424202210000058
and
Figure FDA0003424202210000059
representing the jammer to IoT devices and Eve's channel gains respectively,
Figure FDA00034242022100000510
and
Figure FDA00034242022100000511
channel gains representing IRS reflection base station signals and jammer signals to IoT devices and Eve, respectively, of
Figure FDA00034242022100000512
Figure FDA00034242022100000513
Figure FDA00034242022100000514
Definition of
Figure FDA00034242022100000515
And
Figure FDA00034242022100000516
order to
Figure FDA00034242022100000517
v＝[uH,1]Auxiliary variable
Figure FDA00034242022100000518
Introducing a relaxation variable r1>0 and r2>0, using the idea of the SPCA technique, assume
Figure FDA00034242022100000519
And
Figure FDA00034242022100000520
to a corresponding known point, σ2Representing the variance of the noise, expressing the original non-convex problem as
Figure FDA0003424202210000061
Figure FDA0003424202210000062
Figure FDA0003424202210000063
Figure FDA0003424202210000064
Figure FDA0003424202210000065
Figure FDA0003424202210000066
Figure FDA0003424202210000067
rank (v) ═ 1 (4h) where (4c), (4d), and (4e) are privacy rate constraints and (4f), (4g), and (4h) are reflection phase shift constraints due to the combining variable (f)1,f2) Coupling with V still exists, the objective function (4a) is still non-convex, a first-order Taylor expansion method and an SDR method are utilized, and an alternative iterative optimization algorithm is provided to obtain the solution of the original problem.
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