阅读说明：本技术 一种鲁棒无线携能中继协作安全通信方法 (Robust wireless energy-carrying relay cooperation safety communication method ) 是由 金勇� 郭睿杰 白可 李军伟 胡振涛 周林 魏倩 于 2021-06-24 设计创作，主要内容包括：本发明公开了一种鲁棒无线携能中继协作安全通信方法,包括构建无线携能中继协作的无线传感器网络系统模型,引入由合法接收端的信道容量减去最强窃听者的信道容量得到系统保密速率,对求解过程转化为最大化最坏情况下的保密速率问题,通过迭代优化算法对上述问题进行高效求解,获得矢量和中继功率分配因子。本发明将问题建模为一个最大最小问题,通过引入松弛变量,将问题转换为上下两层问题,针对上层问题的分式二次规划形式,通过变换将其转换为标准凸问题；并设计了一种迭代算法同时求解两个问题以获得中继处最优的波束形成矢量。然后使用一维搜索获得中继最优功率分配因子。本发明能显著提高中继无法获取窃听者完美信道状态信息时的保密速率。(The invention discloses a robust wireless energy-carrying relay cooperation safety communication method which comprises the steps of constructing a wireless sensor network system model of wireless energy-carrying relay cooperation, obtaining a system confidentiality rate by subtracting the channel capacity of a strongest eavesdropper from the channel capacity of a legal receiving end, converting a solving process into a problem of maximizing the confidentiality rate under the worst condition, and efficiently solving the problem through an iterative optimization algorithm to obtain a vector and relay power distribution factor. The problem is modeled into a maximum and minimum problem, the problem is converted into an upper layer problem and a lower layer problem by introducing a loose variable, and the upper layer problem is converted into a standard convex problem by a fractional quadratic programming form aiming at the upper layer problem; and an iterative algorithm is designed to solve the two problems simultaneously to obtain the optimal beam forming vector at the relay. And then obtaining the optimal power distribution factor of the relay by using one-dimensional search. The invention can obviously improve the secrecy rate when the relay can not obtain the perfect channel state information of the eavesdropper.)

1. A robust wireless energy-carrying relay cooperation safety communication method is characterized by comprising the following steps: the method comprises the following steps:

step 1: constructing a wireless sensor network system model of wireless energy-carrying relay cooperation, wherein the wireless sensor network system model comprises 1 transmitting terminal s, 1 legal receiving terminal d, N wireless energy-carrying relay nodes r using an amplification-forwarding technology, and K eavesdroppers e expecting to obtain relay forwarding information, and the equipment is respectively provided with a single antenna;

the method comprises the following steps that two stages, namely a source transmission stage and a relay cooperative transmission stage, are divided in a single information transmission period in the network;

is provided withIs a channel coefficient vector of s to N relays of the transmitting end [2]]^HRepresenting the conjugate transpose of the vector, C^N×1Represents a set of complex numbers of dimension Nx 1,for N channel coefficient vectors relaying r to the legitimate receiver d,for the N channel coefficient vectors relaying r to the k-th eavesdropper e, k, where channel disturbances exist,is the estimated channel coefficient of the nth relay to the kth eavesdropper e, k,is to satisfyIn which the channel is disturbed, whereinRepresenting vectorsThe square of the two norms of (1), delta is more than or equal to 0 and is the upper bound of channel disturbance;

step 2: the signal sent by the transmitting terminal is cooperatively forwarded to a legal receiving terminal d and an eavesdropper e through N wireless energy-carrying relays, which is specifically expressed as follows: in the source transmission stage, the transmitting end sends a secret signal x to determine the receiving signal of the ith relay

In the relay cooperation transmission phase, each relay collects the signalsIs divided into two parts, one partFor harvesting energy, another partFor collecting information, wherein_iIs the energy allocation factor;

determining the energy E required for relaying and amplifying the forwarding information_FThe circuit consumes energy E_CIRRelaying the collected energy E_H；

Determining that the transmission power of each relay, the energy collected by the relay and the circuit consumption energy meet the energy constraint, and determining the signal-to-noise ratio SINR of the signal received by the legal receiving end d_dChannel capacity r of legitimate receiver d_d(ii) a Signal to noise ratio SINR of signal received by eavesdropper e_eChannel capacity r of eavesdropper e_e；

And step 3: by the channel capacity r of the legitimate receiver d_dSubtracting the channel capacity r of the strongest eavesdropper e, k_e,kObtaining a system secret rate r_SThe solving process is converted into a privacy rate problem P1 under the worst case maximization, so that the system has good robustness;

and 4, step 4: based on maximizing the worst-case privacy rate problem P1 described in step 3,obtaining the best worst beamforming vector w by respectively optimizing the upper layer problem and the lower layer problem for joint solution according to an alternating iterative algorithm^*And a secret rate r^*；

And 5: after the iterative algorithm is solved through the step 4, the feasible range alpha of the power distribution factor alpha belongs to (0, 1)]Effectively solving the optimal energy distribution factor alpha through a one-dimensional search algorithm^*。

2. The robust wireless energy-carrying relay cooperative security communication method as claimed in claim 1, wherein: in step 3, the solving process is converted into a privacy rate problem P1 under the worst case maximization, which specifically includes: each relay transmitting power is constrained by taking maximization of the worst case secret rate as an optimization targetNot higher than the energy collected by the relayConstraining the channel error of the eavesdropper to be within an ellipsoid to obtain a non-convex maximum and minimum problem, namely a problem P1 of maximizing the security rate under the worst condition; then, fixing the energy distribution factor α, and introducing an intermediate variable τ to transform the problem P1 into an upper layer problem P2 and a lower layer problem P3; the lower-layer problem P3 is a fractional quadratic programming problem, the lower-layer problem is converted into a convex optimization problem capable of being efficiently solved through SDR, S-procedure and Charnes-Cooper transformation, and the upper-layer problem P2 is efficiently solved through a bisection algorithm after the lower-layer problem P3 is solved.

3. The robust wireless energy-carrying relay cooperative security communication method as claimed in claim 1, wherein:

the information received by the ith relay in step 2 is:wherein n is_srIs a received noise signal relayed;

the energy collected by the ith relay is:

wherein eta, 0 < eta < 1 is energy collection efficiency, P_sIn order for the transmitting end to transmit the signal power,received noise power for the relay;

represents a plurality of numbersSquare of the mode of (a);

the energy required for each relay to forward the signal is:

where trace () represents the trace of an internal element, w ∈ C^N×1For relay beamforming vectors, E_i＝diag(e_i)∈C^N×N，e_i∈C^N×1The column vector is that the ith element is 1, and other elements are 0;

due to the limited energy at the relay, the energy of the relay output amplified signal must be less than the energy collected by the relay, i.e. the following constraints are satisfied:

E_F+E_CIR≤E_H(ii) a Wherein E_CIRConsuming energy for the amplification circuit;

the signal-to-noise ratio of the signal received by the legal receiving end d is:

the channel capacity of the legal receiving end d is defined as:

whereinP_sDenotes the transmitting power of the transmitting terminal s, h_sr∈C^N×1Channel vector of source s to relay r, h_rd∈C^N×1Representing the channel vector relayed r to the legitimate receiver d,in order to amplify the noise power generated by the circuit,receiving the power of noise for the legitimate receiver D, D_βα＝diag(α₁β₁,...,α_Nβ_N)∈C^N×N，D_β＝diag(β₁,...,β_N)∈C^N×NBeta is the relay amplification signal multiple, [ h ]_sd]_iRepresents a column vector h_sdThe i-th element of (1), diag () denotes that a diagonal matrix is constructed with internal elements,to define a symbol;

the signal-to-noise ratio of the signal received by the kth eavesdropper e, k is:

the channel capacity of the kth eavesdropper e, k is defined as:

wherein The power of the noise is received for the eavesdropper.

4. The robust wireless energy-carrying relay cooperative security communication method according to claim 2, wherein: the system security rate in step 3 is defined as:

wherein the content of the first and second substances,represents the maximum and minimum criterion, (r)_d-r_e,k)⁺Is expressed as (r)_d-r_e,k) And 0, with the optimization goal of maximizing the worst-case privacy rate, the optimization problem P1 can be described as:

α∈(0,1]，representing all values of k, and carrying out one-dimensional search in the interval can inevitably obtain an optimal value, so that alpha is firstly fixed; introducing an intermediate variable tau to convert P1 into upper and lower two-layer sub-problems, wherein the lower layer problem P3 can be described as:

given τ, the lower layer problem P3 can be considered a non-convex quadratic programming problem;

then using SDR, let W be ww^H∈C^N×NRelaxing the rank-one constraint of W, the lower layer problem P3 translates into:

whereinRepresenting W semi-positive, in combination with (C5) and (C7), the problem described above can be rewritten as a fractal programming without non-convex constraints by introducing auxiliary variables μ ≧ 0, ψ ≧ 0, using the S-procedure technique:

wherein (C8) e C^(N+1)×(N+1)(ii) a Two auxiliary variables mu is more than or equal to 0 and psi is more than or equal to 0 are introduced by using Charnes-Cooper transformation, and the lower layer problem can be finally expressedIn a standard convex optimization form:

the upper layer problem can be described as:

s.t.(C13)τ_min≤τ≤1

where H (τ) ═ τ γ (τ), γ (τ) is the optimum value of the underlying problem P3; τ is an introduced intermediate variable, satisfying the (C13) constraint:

wherein, the formula is obtained according to Cauchy-Schwarz inequality, and the formula is shown as | w_i|²Is less than or equal to 1;

after the lower layer problem P3 obtains the optimal value gamma (tau), the upper layer problem P2 is a standard convex problem and is solved through a bisection algorithm; so far, two standard convex optimization problems of an upper layer problem P2 and a lower layer problem P3 are obtained and solved through a convex optimization algorithm.

5. The robust wireless energy-carrying relay cooperative security communication method as claimed in claim 1, wherein: the specific process of jointly solving the upper and lower layer problem algorithms by using the convex optimization technology in the step 4 can be described as an algorithm A:

A1. setting (P3) a problem parameter tau_min＝l,u＝τ_max1 and convergence precision epsilon;

A2. solving (P3) by using an interior point method to obtain an optimal solution H (τ) ═ τ γ (τ) and W;

A3. and solving (P2) to obtain the current secret rate r ═ 1/2 log₂(τ + H (τ)) and neighbor location privacy rateWhereinDelta tau is more than 0 and is a minimum value to judge the iteration direction of the algorithm;

A4. judging whether r is larger than r ', if l is larger than r', if u is larger than r, if not, u is larger than r;

A5. judging whether | r-r' | < epsilon or not, if yes, jumping to the step A6, and if not, returning to the step A2;

A6. output the optimum value W^*When W is satisfied, it is judged whether or not Rank (W) is satisfied^*) 1, if the worst best beamforming vector w obtained by eigenvalue decomposition is satisfied^*If not, the worst best beamforming vector w is obtained by the gaussian randomization technique^*Output w^*。

6. The robust wireless energy-carrying relay cooperative security communication method as claimed in claim 1, wherein: the algorithm for obtaining the optimal power distribution factor of the wireless energy-carrying relay in the step 5 specifically comprises the following steps:

a. in a regionIn the range of m [ alpha ] (0, 1)]Setting a search interval xi and an initial value alpha of a power distribution factor xi, r_max＝0,α_max＝α,w_max＝0；

b. Solving the problem P1 by the algorithm a of step 4 of claim 1, recording the optimal value r^*,w^*；

c. Judging whether r is satisfied^*>r_maxIf yes, update r_max＝r^*,w_max＝w^*If not, directly jumping to the step d;

d. if alpha is alpha + xi, judging whether alpha is more than or equal to 1, if so, skipping to the step e, otherwise, skipping to the step b;

e. output optimum value r_max,α_max,w_max。

Background

With the progress of wireless communication technology, Wireless Sensor Network (WSN) technology is fully developed, a large number of wireless sensors are put into use, and due to the size limitation of wireless sensors, only a single antenna is often equipped, and the Beamforming (Beamforming) in the Multiple Input Multiple Output (MIMO) technology cannot be used to obtain spatial gain to obtain better transmission performance. However, a large number of nodes often exist in the internet of things, and a feasible solution can be provided for the above problem through a relay cooperation technology by using the nodes, that is, other nodes existing in the internet of things are used as relays to transmit cooperation information, so that a good space diversity gain is obtained. However, the cooperative transmission needs to consume the energy of the sensor node, and as the wireless sensors are often widely distributed and cannot be continuously supplied with power by cables, the working life of the sensors is extremely dependent on the battery life. Using cooperative transmission will greatly reduce network lifetime and is difficult to achieve. In order to solve the above problems, energy harvesting using Radio Frequency (RF) technology has become a new concept. The method uses radio frequency energy collection technology to collect energy and information simultaneously for the received signals, thereby prolonging the service life of the equipment and providing effective information transmission.

However, due to the broadcasting characteristic of the wireless channel and the dynamic topological structure of the wireless network, the wireless energy-carrying relay network is more easily intercepted and intercepted by a third party in the information transmission process, so that information leakage is caused. Current security mechanisms for wireless communication systems are still based on multi-layer protocols outside the physical layer, and conventional methods for ensuring security are usually based on cryptographic encryption methods. However, the complicated encryption system can bring huge computational challenges to the signal transmitting end, and it is difficult to ensure the security of the channel for transmitting the key. In this context, physical layer security is proposed as a new method to enhance the overall security of wireless networks. Compared with the conventional encryption technology, the physical layer security is not subject to the condition that the computational capability of an eavesdropper is limited, which means that privacy can be realized even if an eavesdropper with unlimited computational capability exists, and thus, the physical layer security technology is gradually becoming a main means for improving the network security.

In order to improve the secure communication performance of the wireless energy-carrying network, a zero forcing algorithm is proposed in document [1] to place a secret signal transmitted by a transmitting end in a null space of an eavesdropper, so as to improve the system security, but the algorithm is extremely dependent on acquiring perfect channel state information of the eavesdropper and a legal receiving end. In order to reduce the dependence on channel state information, a cooperative noise method is proposed in document [2], which interferes with an eavesdropper by generating artificial noise at a relay, but is disadvantageous for the continuous use of low-power energy-limited devices because additional energy consumption is generated due to the generation of artificial noise. Meanwhile, the noise also interferes with a legal receiving end, and extra calculation pressure is brought to the legal receiving end. A probability constraint algorithm based on the bernstein inequality is proposed in the document [3], and the basic idea is as follows: if the legal receiving end service quality can be satisfied with a certain probability, the network is considered to reach the established performance requirement. This constraint places too stringent a lower probability limit, which tends to result in a lower privacy rate.

The design for the wireless energy-carrying network only focuses on enabling the user to obtain the best service quality, and the damage of an eavesdropper possibly existing in the network to the user service quality is not considered; or the eavesdropper is only inhibited by using the perfect channel state information, and the condition that the relay cannot acquire the perfect channel state information of the eavesdropper is not considered. In this case, the performance of the original transceiver algorithm design for the wireless portable communication network is greatly reduced, and even a positive secret rate cannot be achieved. Aiming at the problems existing in the previous method, a best optimization problem under the worst condition is established by introducing a widely used elliptical model to model possible channel errors. 2. The decoding noise in the receiver and the noise introduced by the amplifying circuit are considered, so that the decoding noise and the noise are more consistent with a real scene. 3. And the maximum and minimum balance of the worst condition is used for improving the comprehensive quality of network communication.

The above-mentioned references are as follows:

[1]Q.Shi,C.Peng,W.Xu,M.Hong and Y.Cai,"Energy Efficiency Optimization for MISO SWIPT Systems With Zero-Forcing Beamforming,"in IEEE Transactions on Signal Processing,vol. 64,no.4,pp.842-854,Feb.15,2016.

[2]M.R.A.Khandaker,C.Masouros,K.Wong and S.Timotheou,"Secure SWIPT by Exploiting Constructive Interference and Artificial Noise,"in IEEE Transactions on Communications,vol.67,no.2,pp.1326-1340,Feb.2019.

[3]Bin LI,Zesong FEI,"Probabilistic-constrained robust secure transmission for energy harvesting over MISO channels,"in Journal of SCIENCE CHINA Information Sciences,vol 61,no. 2,pp.022303-,Feb 2018.

disclosure of Invention

The invention aims to provide a robust wireless energy-carrying relay cooperation safety communication method, which describes imperfect channel state information of an eavesdropper by introducing a bounded channel disturbance model, and jointly optimizes a relay beam forming matrix and a receiver power distribution factor by using an algorithm based on S-procedure and SDR (standard definition link) so as to obtain the best transceiver parameter value under the worst condition and ensure that a legal receiving end can obtain stable confidentiality rate under the condition that a relay cannot obtain the perfect channel state information of the eavesdropper. The problem of serious decline of system performance caused by the fact that an eavesdropper is not considered and the relay to the eavesdropper perfect channel state information cannot be obtained in the prior art is solved.

In order to achieve the above object, the robust wireless energy-carrying relay cooperation secure communication method of the present invention includes:

step 1: constructing a wireless sensor network system model of wireless energy-carrying relay cooperation, which comprises a transmitting terminal s, a legal receiving terminal d, N wireless energy-carrying relay nodes r using an amplifying-forwarding technology,k eavesdroppers e, who desire to relay the forwarded information, all equipped with a single antenna. The K eavesdroppers e are uniformly and independently distributed around the legal receiving end d, and due to the obstruction of the geographic environment, the legal receiving end d and the eavesdroppers e cannot directly obtain the signal directly transmitted by the transmitting end, and only can obtain the signal forwarded by the relay r. A single information transmission period in the network is divided into two stages, namely a source transmission stage and a relay cooperative transmission stage. Is provided withFor the channel coefficient vector of the transmitting end s to N relays r,^Hrepresenting the conjugate transpose of the vector, C^N×1Represents a set of complex numbers of dimension Nx 1,for N channel coefficient vectors relaying r to the legitimate receiver d,for the N channel coefficient vectors relaying r to the k-th eavesdropper e, k, where channel disturbances exist,is the estimated channel coefficient of the nth relay to the kth eavesdropper e, k,is to satisfyIn which the channel is disturbed, whereinRepresenting vectorsThe square of the two norms of (1), delta is more than or equal to 0 and is the upper bound of channel disturbance;

step 2: signals sent by a transmitting terminal are cooperatively forwarded to a legal receiver through N wireless energy-carrying relays rThe receiving end d and the eavesdropper e can be specifically expressed as follows: in the source transmission stage, the transmitting end sends a secret signal x to determine the receiving signal of the ith relayIn the relay cooperation transmission phase, each relay collects the signalsIs divided into two parts, one partFor harvesting energy, another partFor collecting information, wherein_iIs the energy allocation factor. Determining the energy E required for relaying and amplifying the forwarding information_FThe circuit consumes energy E_CIRRelaying the collected energy E_H. Determining that the transmission power of each relay, the energy collected by the relay and the circuit consumption energy meet the energy constraint, and determining the signal-to-noise ratio SINR of the signal received by the legal receiving end d_dChannel capacity r of legitimate receiver d_d(ii) a Signal to noise ratio SINR of signal received by eavesdropper e_eChannel capacity r of eavesdropper_e；

And step 3: system secret rate r_SFor the channel capacity r of a legitimate receiver d_dSubtracting the channel capacity r of the strongest eavesdropper_e. For good system robustness, each relay transmit power is constrained with the goal of maximizing the worst case secret rateNot higher than the energy collected by the relayConstraining the eavesdropper's channel error to be within an ellipsoid yields a non-convex maximum-minimum problem (P1). The energy distribution factor alpha is fixed and,introducing an intermediate variable τ transforms the problem into an upper layer problem (P2) and a lower layer problem (P3). The lower layer problem (P3) is a fractional quadratic programming problem, the lower layer problem is converted into a convex optimization problem which can be efficiently solved through SDR, S-procedure and Charnes-Cooper transformation, and the upper layer problem (P2) can be efficiently solved through a bisection algorithm after the lower layer problem is solved;

and 4, step 4: based on the worst-case secret rate problem (P1) described in step 3, the worst-case best beamforming vector w can be obtained by jointly solving the upper-layer problem and the lower-layer problem by respectively optimizing them according to an alternating iterative algorithm^*And a secret rate r^*；

And 5: after the iterative algorithm is solved through the step 4, the feasible range alpha epsilon (0, 1) of the power distribution factor alpha is obtained]Effectively solving the optimal energy distribution factor alpha through a one-dimensional search algorithm^*。

Further, step 2 of the robust wireless energy-carrying relay cooperation secure communication method includes:

the information received by the ith relay is:wherein n is_srIs to relay the received noise signal(s),is a vector h_srThe ith coefficient,. The energy collected by the relay is as follows:

wherein eta (0 < eta < 1) is energy collection efficiency, P_sIn order for the transmitting end to transmit the signal power,to relay the received noise power. The energy required for each relay to forward the signal is:

where trace () represents the trace of an internal element,representing internal elementsSquare of the modulus of (d), w ∈ C^N×1For relay beamforming vectors, E_i＝diag(e_i)∈C^N×N，e_i∈C^N×1Is a column vector with the ith element being 1 and the other elements being 0. Due to the limited energy at the relay, the energy of the relay output amplified signal must be less than the energy collected by the relay, i.e. the following constraints are satisfied: e_F+E_CIR≤E_HIn which E_CIRIndicating that the amplification circuit consumes energy. The signal-to-noise ratio of the signal received by the legal receiving end d is:

the channel capacity of the legal receiving end d is:

whereinP_sDenotes the transmitting end transmit power, h_sr∈C^N×1Channel vector of source s to relay r, h_rd∈C^N×1Representing the channel vector relayed r to the legitimate receiver d,for the legitimate receiving end d to receive the power of the noise,for amplifying the noise power generated by the circuit, D_βα＝diag(α₁β₁,...,α_Nβ_N)∈C^N×N，D_β＝diag(β₁,...,β_N)∈C^N×NBeta is the relay amplification signal multiple, [ h ]_sd]_iRepresents a column vector h_sdThe i-th element of (1), diag () denotes that a diagonal matrix is constructed with internal elements,to define a symbol.

The signal-to-noise ratio of the signal received by the kth eavesdropper e, k is:

channel capacity of kth eavesdropper e, k:

wherein: power to receive noise for an eavesdropper;

further, the robust wireless energy-carrying relay cooperation safety communication method of the invention comprises the following steps of 3:

the system security rate is defined asWhereinRepresents the maximum and minimum criterion, (r)_d-r_e,k)⁺Is represented by (r)_d-r_e,k) And a maximum value of 0, and a maximum value of,with the optimization goal of maximizing the worst-case privacy rate, the optimization problem can be summarized (P1): (P1)

Wherein the content of the first and second substances,representing the values of all i. Fixing alpha, introducing an intermediate variable tau, and converting P1 into an upper and lower layer of subproblems, wherein the lower layer of subproblems can be described as:

given τ, the underlying problem can be viewed as a non-convex quadratic programming problem. Then using SDR, let W be ww^H∈C^N×NRelaxing the rank-one constraint of W, the underlying problem can translate into:

among the above problems (C4)Represents a positive half-definite value of W. Combining (C5) and (C7), by using S-procedure technique, introducing auxiliary variables μ ≧ 0, ψ ≧ 0, the problem (P3) can be rewritten in the form:

wherein (C8) e C^(N+1)×(N+1). Benefit toTwo auxiliary variables mu is more than or equal to 0 and psi is more than or equal to 0 are introduced by using Charnes-Cooper transformation, and the lower layer problem can be expressed as the following standard convex optimization form (P3):

the upper layer problem is as follows:

(P2)

s.t.(C13)τ_min≤τ≤1

where H (τ) ═ τ γ (τ), γ (τ) is the optimal value of the underlying problem (P3), τ is an introduced intermediate variable, and satisfies:

wherein, the formula is obtained according to Cauchy-Schwarz inequality, and the formula is shown as | w_i|²Is obtained with the mass ratio of less than or equal to 1. So far, two standard convex optimization problems are obtained, and the convex optimization can be used for solving;

further, the specific process of the iterative algorithm for solving the upper and lower layer problems by using the convex optimization technology, which is provided by the robust wireless energy-carrying relay cooperation secure communication method of the invention in step 4, can be summarized as an algorithm A:

A1. setting (P3) a problem parameter tau_min＝l,u＝τ_max1 and convergence precision epsilon;

A2. solving (P3) by using an interior point method to obtain an optimal solution H (τ) ═ τ γ (τ) and W;

A3. and solving (P2) to obtain the current secret rate r ═ 1/2 log₂(τ + H (τ)) and neighbor location privacy rateWhereinDelta tau is a minimum value used for judging the iteration direction of the algorithm;

A4. judging whether r is larger than r ', if l is larger than r', if u is larger than r, if not, u is larger than r;

A5. judging whether | r-r' | < epsilon or not, if yes, jumping to the step A6, and if not, returning to the step A2;

A6. output the optimum value W^*If W is satisfied, the Rank (W) is judged^*) The worst best beamforming vector w is obtained by eigenvalue decomposition as 1^*If not, the worst best beamforming vector w is obtained by the gaussian randomization technique^*. Output w^*。

Further, step 5 of the robust wireless energy-carrying relay cooperation safety communication method jointly obtains the best beam forming vector w under the worst condition^*And a power division factor alpha^*The algorithm of (a) may be described as:

a. in the interval alpha epsilon (0, 1)]Setting a search interval xi and an initial value alpha of a power distribution factor xi, r_max＝0,α_max＝α,w_max＝0；

b. Solving the problem (P1) by the algorithm A, and recording the optimal value r^*,w^*；

c. Judging whether r is satisfied^*>r_maxIf yes, update r_max＝r^*,w_max＝w^*If not, directly jumping to the step d;

d. updating alpha to alpha + xi, judging whether alpha is more than or equal to 1, if so, skipping to the step e, otherwise, skipping to the step b;

e. output optimum value r_max,α_max,w_max。

The invention has the beneficial effects that:

by the technical scheme, the robust wireless energy-carrying relay cooperation safety communication method is provided for solving the problems that an eavesdropper exists in a system and accurate channel state information of the eavesdropper cannot be obtained in the existing wireless sensor network transceiver design method.

The invention introduces a bounded channel disturbance model through the system privacy rate when an eavesdropper exists in a wireless energy-carrying relay network to describe the imperfect channel state of the eavesdropper, thereby establishing a non-convex optimization problem which takes a beam forming vector and a relay power distribution factor with the best privacy rate under the worst condition of the eavesdropper channel as targets, efficiently solving the problem through an iterative optimization algorithm based on S-procedure and SDR, and finally obtaining the relay beam forming vector and the relay power distribution factor which can enable the system to reach the optimal privacy rate under the worst condition. The invention improves the secrecy rate when the system can not obtain the accurate channel state information of the eavesdropper.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a diagram of a network model according to the present invention.

Fig. 2 is a block diagram of a transceiver employed by the wireless energy-carrying relay of the present invention.

FIG. 3 is a flow chart of the method of the present invention.

Fig. 4 is a graph comparing the secret rate obtained by the method of the present invention with the power of the transmitting end in comparison with the conventional method.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The robust wireless energy-carrying relay cooperation safety communication method comprises the following steps:

step 1: the physical model of the wireless energy-carrying relay secure communication network attached to the present invention is constructed, as shown in fig. 1, and includes a transmitting terminal s, a legal receiving terminal d, N wireless energy-carrying relay nodes r using an amplification-forwarding technique, K eavesdroppers e desiring to obtain relay forwarding information, and all the above devices are equipped with a single antenna. K eavesdroppers are randomly distributed around the legitimate users. Due to the obstruction of factors such as geography, the legal receiving end d and the eavesdropper e can only receive the transmitted information cooperatively forwarded by the relay, that is, the transmitting end s, the legal receiving end d and the eavesdropper e do not have direct links, which often occurs in the process of long-distance communication or satellite communication. In the network, single information transmission is divided into two stages, namely a source transmission stage and a relay cooperative transmission stage. Is provided withFor the channel coefficient vector of the transmitting end s to N relays r,^Hrepresenting the conjugate transpose of the vector, C^N×1Represents a set of complex numbers of dimension Nx 1,for the channel coefficient vector of the nth relay r to the legitimate receiver d,for the N channel coefficient vectors relaying r to the k-th eavesdropper e, k, where channel disturbances exist,is the estimated channel coefficient of the nth relay to the kth eavesdropper e, k,is to satisfyIn which the channel is disturbed, whereinRepresenting vectorsThe square of the two norms of (1), delta is more than or equal to 0 and is the upper bound of channel disturbance;

step 2: a signal sent by a transmitting terminal s is cooperatively forwarded to a legal receiving terminal d and an eavesdropper e through N wireless energy-carrying relays r, which can be specifically expressed as follows:

in the source transmission stage, the transmitting end sends a secret signal x, and the reception signal of the ith relay is:wherein n is_srTo relay the received noise signal. As shown in FIG. 2, during the relay cooperative transmission phase, the power divider in each relay will collect the signalIs divided into two parts, one partFor harvesting energy, another partFor collecting information, wherein_iIs the relay energy allocation factor.

The circuit consumes energy E_CIRThe energy collected by each relay is:

wherein eta (0 < eta < 1) is energy collection efficiency, P_sIn order for the transmitting end to transmit the signal power,to relay the received noise power. The energy required for each relay to linearly amplify the forwarded information is:

where trace () represents the trace of an internal element,represents a plurality of numbersSquare of the modulus of (d), w ∈ C^N×1For relay beamforming vectors, E_i＝diag(e_i)∈C^N×N，e_i∈C^N×1Is a column vector with the ith element being 1 and the other elements being 0. Due to the limited relay energy, to ensure cooperative forwarding does not consume relay energy, each relay must satisfy the following constraints:

the signal-to-noise ratio of the signal received by the legal receiving end d is:

the channel capacity of the legal receiving end d is:

whereinP_sWhich represents the transmit power of the transmitting end,for the legitimate receiving end d to receive the power of the noise,for amplifying the noise power generated by the circuit, D_βα＝diag(α₁β₁,...,α_Nβ_N)∈C^N×N，D_β＝diag(β₁,...,β_N)∈C^N×NBeta is the relay amplification signal multiple, [ h ]_sd]_iRepresents a vector h_sdThe ith element of (1), diag () represents a diagonal matrix with internal elements as diagonal elements,to define a symbol.

The signal-to-noise ratio of the signal received by the kth eavesdropper e, k is:

the channel capacity of the kth eavesdropper e, k is:

wherein: power to receive noise for an eavesdropper;

and step 3: after step 2 definition is completed, a system secret rate definition can be given:whereinIs the maximum minimum criterion, (r)_d-r_e,k)⁺Is represented by (r)_d-r_e,k) And a maximum value of 0. Considering that an eavesdropper can hide the eavesdropper and a relay cannot acquire the perfect channel state information of the eavesdropper, the traditional algorithm does not consider the problem, and therefore the performance of the traditional algorithm is sharply reduced when the perfect channel state information of the eavesdropper cannot be acquired. The invention is directed to maximizing the worst case secret rate, and additionally constrains each relay transmit powerNot higher than the energy collected by the relayAnd simultaneously, the channel error of the eavesdropper is restricted in an ellipsoid, and a non-convex maximum and minimum optimization problem is obtained (P1):

(P1)

whereinRepresents the values of all k

And 4, step 4: analyzing the maximum and minimum problems defined in the step 3, and giving an iterative algorithm, specifically:

since the energy distribution factor α has a fixed interval, an optimum value can be obtained by one-dimensional search. Therefore, fixing α first, introducing an intermediate variable τ decomposes the above problem into two layers of problems, where the lower layer of problems is:

as can be seen from the above equation, the underlying problem is a fractional quadratic programming problem with bounded channel disturbances. Using SDR, let W be ww^H∈C^N×NAnd relaxing the rank-one constraint, the above problem can be transformed into the following fractional programming problem:

whereinRepresents a positive half-definite value of W. The above formula still contains the coupling of bounded disturbance and beam forming vector, and cannot be directly solved, and the problem is converted into a fractional programming problem by using S-procedure and combining constraints (C5) and (C7):

wherein (C8) e C^(N+1)×(N+1). Finally, two auxiliary variables mu is larger than or equal to 0 and psi is larger than or equal to 0 are introduced by using Charnes-Cooper transformation, and the (P4) is rewritten into a standard convex optimization form (P3) capable of being solved efficiently.

(P3)

The upper layer problem (P2) can be described as:

(P2)

s.t.(C13)τ_min≤τ≤1

where H (τ) ═ τ γ (τ), γ (τ) is the optimal value for the underlying problem (P3), τ is the introduced intermediate variable that satisfies:

wherein, the formula is obtained according to Cauchy-Schwarz inequality, and the formula is shown as | w_i|²Is obtained with the mass ratio of less than or equal to 1. To this end, we have obtained two standard convex optimization problems, which can be solved efficiently by an iterative algorithm in a combined manner (P3) and (P2), and the specific steps can be described as algorithm a:

A1. setting (P3) a problem parameter tau_min＝l,u＝τ_max1, epsilon and convergence precision epsilon;

A2. solving (P3) by using an interior point method to obtain an optimal solution H (τ) ═ τ γ (τ) and W;

A3. and solving (P2) to obtain the current secret rate r ═ 1/2 log₂(τ + H (τ)) and neighboring positionSecret rateWhereinDelta tau is a minimum value used for judging the iteration direction of the algorithm;

A4. judging whether r is larger than r ', if l is larger than r', if u is larger than r, if not, u is larger than r;

A5. judging whether | r-r' | < epsilon or not, if yes, jumping to the step A6, and if not, returning to the step A2;

A6. output the optimum value W^*If W is satisfied, the Rank (W) is judged^*) The worst best beamforming vector w is obtained by eigenvalue decomposition as 1^*If not, the worst best beamforming vector w is obtained by the gaussian randomization technique^*. Output w^*；

And 5: after the problem (P1) is solved, the optimal power allocation factor α of the wireless energy-carrying relay can be obtained through a one-dimensional search algorithm, and the algorithm for jointly obtaining the best beamforming vector and power allocation factor under the worst condition can be specifically described as the following steps:

a. in the interval alpha epsilon (0, 1)]Setting a search interval xi and an initial value alpha of a power distribution factor xi, r_max＝0,α_max＝α,w_max＝0；

b. The problem is solved (P1) by the algorithm A, and the optimal value r is recorded^*,w^*；

c. Judging whether r is satisfied^*>r_maxIf yes, update r_max＝r^*,w_max＝w^*If not, directly jumping to the step d;

d. if alpha is alpha + xi, judging whether alpha is more than or equal to 1, if so, skipping to the step e, otherwise, skipping to the step b;

e. output optimum value r^*,α^*,w^*。

The experimental process comprises the following steps:

1. simulated environment setup

As shown in fig. 1, it is assumed that the entire simulation scene is in a circular area with a radius R, the transmitting end s is located at the edge of the circular area, and the legal receiving end d is located at a symmetric position of s on the circle. Relays r and eavesdroppers e are randomly distributed inside the circular area. Similar to the correlation work, the channel model is assumed to contain large-scale path loss and small-scale multipath fading. The path loss model is given by:

the meaning of the parameters in the above formula and the other parameter settings of the experiment are shown in the following table:

TABLE 1 Experimental parameters

2. The specific process of the experiment

Setting experimental parameters according to the table, setting three comparison algorithms as follows: 1, zero forcing algorithm, 2, probability constraint algorithm and 3, collaborative noise algorithm, and carrying out simulation experiment under the same parameter to obtain the following data:

TABLE 2 Experimental data

From the experimental data, it can be seen that the algorithm provided by the invention can obtain the highest privacy rate, and the algorithm has greater superiority than the algorithm.

By the technical scheme, the invention provides a robust wireless energy-carrying relay cooperation safety communication method aiming at the problems that the existing wireless sensor network transceiver design method does not consider the existence of an eavesdropper in a system and the accurate channel state information of the eavesdropper cannot be obtained, and the like:

firstly, the invention provides the system confidentiality rate when an eavesdropper exists in the wireless energy-carrying relay network; then, the invention introduces a bounded channel disturbance model to describe the imperfect channel state of an eavesdropper, and establishes a maximum and minimum optimization problem which takes a relay beam forming vector and a power distribution factor which obtain the best privacy rate of the eavesdropper channel under the worst condition as a target; converting the problem into an upper layer problem and a lower layer problem by introducing a Relaxation variable, and converting the problem into a standard convex problem by using Semi-fine Relay (SDR), S-procedure and Charnes-Cooper transformation aiming at a fractional quadratic programming form of the upper layer problem; the original problem is efficiently solved through an iterative optimization algorithm based on S-procedure and SDR, the lower layer problem is efficiently solved through a bisection algorithm, and a relay beam forming vector and a relay power distribution factor which can enable the system to achieve the optimal secret rate under the worst condition are obtained. The security rate when the system can not obtain the accurate channel state information of the eavesdropper is improved.

The invention designs an iterative algorithm to simultaneously solve two problems so as to obtain the optimal beam forming vector at the relay. And then obtaining the optimal power distribution factor of the relay by using one-dimensional search. The invention can obviously improve the secrecy rate when the relay can not obtain the perfect channel state information of the eavesdropper.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.