WO2023165183A1 - Method and apparatus for designing multiple-input multiple-output transceiver - Google Patents

Abstract

The present application provides a method and apparatus for designing a multiple-input multiple-output transceiver, comprising: on the basis of a security rate model of a user signal in a signal transmission system, constructing a target optimization model; solving the target optimization model, and determining an optimization design parameter of a transceiver in the signal transmission system; the optimization design parameter comprising at least one of: a downlink precoding vector, a downlink artificial noise vector, an uplink transmission power, and a mode selection vector; and the security rate model being determined on the basis of signal security rates associating all users with eavesdropping devices. In the method and apparatus for designing a multiple-input multiple-output transceiver provided by the present application, by constructing a target optimization model, solving the target optimization model, and further obtaining optimization design parameters for a transceiver, it is possible to effectively prevent the interception of a signal by an eavesdropping device, thus ensuring the communication security of a signal transmission system.

Description

Design method and device for a multi-input multi-output transceiver

Cross References to Related Applications

This application claims the priority of the Chinese patent application with the application number 202210200224.1 filed on March 2, 2022, and the title of the invention is "a multi-input multi-output transceiver design method and device", which is incorporated herein by reference in its entirety .

technical field

The present application relates to the technical field of communications, and in particular to a design method and device for a multiple-input multiple-output transceiver.

Background technique

In order to improve the spectral efficiency of the signal transmission system, the existing network-assisted full-duplex system combined with the non-cellular large-scale MIMO technology can integrate the existing simultaneous and same-frequency full-duplex, flexible duplex and hybrid duplex All access points are connected to the central processing unit through the backhaul, and cooperate to provide services for users.

The access point can work at the same frequency full-duplex or half-duplex at the same time, but because the interference between the transceiver antennas of the same access point can be eliminated by analog means, the access point of the same frequency full-duplex at the same time can also be regarded as Two half-duplex access points.

However, in the signal transmission system, the possible eavesdropping equipment will extract or intercept the private information of uplink and downlink users from the wireless communication network, causing security risks.

Contents of the invention

In view of the problems existing in the prior art, the embodiments of the present application provide a design method and device for a multiple-input multiple-output transceiver.

This application provides a method for designing a multiple-input multiple-output transceiver, including:

Based on the safe rate model of user signals in the signal transmission system, the target optimization model is constructed;

Solving the target optimization model to determine optimal design parameters of the transceiver in the signal transmission system;

The optimal design parameters include at least one of a downlink precoding vector, a downlink artificial noise vector, an uplink transmit power, and a mode selection vector;

The security rate model is determined based on signal security rates associated with all users with the bugging device.

According to a method for designing a multiple-input multiple-output transceiver provided in the present application, the solving of the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system includes:

determining the working mode of the signal transmission system;

According to described mode of work, carry out approximate optimization to the objective function of described objective optimization model and constraint condition, construct solution optimization model;

Determining the optimal design parameters based on the solution optimization model;

The objective function is to optimize the maximum signal security rate of all users;

The constraints are based on the total power of the sending access point and the total power consumption of the uplink users.

According to a method for designing a multiple-input multiple-output transceiver provided by the present application, the objective function and constraint conditions of the objective optimization model are approximately optimized according to the working mode, and the solution optimization model is constructed, including:

According to the working mode, an approximate convex optimization solution is performed on the objective function to determine a new optimization function;

In the case that the optimization function does not converge, performing an approximate convex optimization solution to the new optimization function until the obtained optimization function converges, and then determining the convergence optimization function;

The solution optimization model is constructed according to the convergent optimization function.

According to a design method of a multiple-input multiple-output transceiver provided by the present application, the determination of the working mode of the signal transmission system includes:

Constructing a quantum system of the signal transmission system according to the state of the access point in the signal transmission system;

Measuring the quantum system by using a random matrix to determine a feasible solution matrix;

Using the feasible solution matrix to optimize and solve, determine the working mode of the signal transmission system.

According to a method for designing a multiple-input multiple-output transceiver provided by the present application, all users include all downlink users and all uplink users, and before the target optimization model is constructed based on the safe rate model of user signals in the signal transmission system, Also includes:

Determine the signal security rate function of any downlink user according to the signal-to-interference-noise ratio at any downlink user and the signal-to-interference-noise ratio of any downlink user at all eavesdropping device positions;

And according to the signal-to-interference-noise ratio of any uplink user's received signal and the signal-to-interference-noise ratio of any uplink user's leaked signal at all eavesdropping device positions, determine the signal security rate function of any uplink user;

The security rate model is constructed according to the signal security rate functions of all uplink users and the signal security rate functions of all downlink users.

According to a method for designing a multiple-input multiple-output transceiver provided by the present application, the signal-to-interference-noise ratio at the downlink user is obtained based on the following method:

Determine the transmission signal of the downlink access point in the signal transmission system based on the mode selection vector function, the downlink precoding vector function and the downlink artificial noise vector function of each access point;

determining a received signal received by each downlink user from the downlink access point according to the signal sent by the downlink access point;

Determine the signal-to-interference-noise ratio at each downlink user according to the interference covariance of the signals received by each user.

According to a kind of multi-input multi-output transceiver design method provided by the present application, the signal-to-interference-noise ratio of the received signal of the uplink user is obtained based on the following method:

According to the received signal of each uplink access point, the received signal of the cascaded central processing unit is obtained;

Performing interference elimination on the received signal of the cascaded central processing unit, and obtaining the received signal of the central processing unit;

According to the interference signal of each uplink user and the received signal of the central processing unit, the signal-to-interference ratio of the received signal of each uplink user is obtained.

According to a design method of a multiple-input multiple-output transceiver provided by the present application, the signal-to-interference-noise ratio of the leaked signal of the downlink user at all eavesdropping device locations is obtained based on the following method:

Obtain the leaked signal of the location of each eavesdropping device in the downlink;

According to the leaked signal of each eavesdropping device position in the downlink, and the interference covariance of each downlink user at each eavesdropping device, determine the signal interference noise of the leaked signal of each downlink user at all eavesdropping device positions Compare.

According to a design method for a multiple-input multiple-output transceiver provided by the present application, the signal-to-interference-noise ratio of the leakage signal of the uplink user at all eavesdropping device locations is obtained based on the following method:

According to the signal transmission power of each uplink user and the interference covariance of each uplink user at each eavesdropping device, determine the signal-to-interference-noise ratio of each uplink user leaking signals at all eavesdropping device locations.

The present application also provides a device for designing a multiple-input multiple-output transceiver, including:

The building block is based on the safe rate model of the user signal in the signal transmission system, and constructs the target optimization model;

A solving module, solving the target optimization model, and determining the optimal design parameters of the transceiver in the signal transmission system;

The optimal design parameters include at least one of a downlink precoding vector, a downlink artificial noise vector, an uplink transmit power, and a mode selection vector;

The security rate model is determined based on signal security rates associated with all users with the bugging device.

The present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the program, the multi-input, multi-input Output transceiver design methodology.

The present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the design method for the multiple-input multiple-output transceiver as described in any one of the above is implemented.

The present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the design method for the multiple-input multiple-output transceiver described in any one of the above is implemented.

The multi-input multi-output transceiver design method and device provided by this application, by constructing the target optimization model, and solving the target optimization model, and then obtaining the optimal design parameters of the transceiver, can effectively prevent interception of signals by eavesdropping devices, and ensure Communication security for signal transmission systems.

Description of drawings

In order to more clearly illustrate the technical solutions in this application or the prior art, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are the present For some embodiments of the application, those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 is one of the flow diagrams of the MIMO design method provided by the present application;

Fig. 2 is a schematic structural diagram of the signal transmission system provided by the present application;

Fig. 3 is the second schematic flow diagram of the design method of the multi-input multi-output transceiver provided by the present application;

Figure 4 is one of the security spectrum performance comparison diagrams provided by the present application;

Figure 5 is the second comparison chart of safety spectrum performance provided by this application;

FIG. 6 is a schematic structural diagram of a design device for a multiple-input multiple-output transceiver provided by the present application;

FIG. 7 is a schematic structural diagram of an electronic device provided by the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in this application. Obviously, the described embodiments are part of the embodiments of this application , but not all examples. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

Compared with the previous half-duplex mode of time division multiplexing or frequency division multiplexing, the flexible duplex mode supported by the fifth generation mobile communication technology (5th generation mobile networks, 5G) can further improve the utilization efficiency of communication resources.

Simultaneous same-frequency full-duplex is a full-duplex mode that allows simultaneous uplink and downlink communication on the same frequency. Since the interference between the transmitting and receiving antennas of the same base station can be eliminated well, the main problem faced by the signal transmission system becomes the interference elimination between uplink and downlink access points and users, that is, cross-link interference elimination. Technologies such as airspace duplex communication for cross-link interference cancellation fail to solve this cross-interference problem.

In addition, the security issue of communication is also very important. For the signal transmission in the signal transmission system, the grouping partial time model arranges the users in different time-frequency slots to maximize the minimum safe rate, and there are also schemes such as hybrid time switch and power division to improve system security, but it does not It involves the security of the physical layer of the network-assisted full-duplex system. The flexible selection of the duplex mode according to the channel conditions can effectively reduce cross-link interference and prevent the access of eavesdropping devices.

Compared with the traditional fixed duplex mode, the non-cellular network-assisted full-duplex system will have a greater degree of freedom, and can obtain the optimal uplink and downlink direction selection during the optimization process.

Aiming at the problem of secure transmission in a network-assisted full-duplex non-cellular large-scale MIMO network, this application proposes to maximize the uplink and downlink security spectrum efficiency in the signal transmission system as the optimization goal, and the downlink precoding vector, downlink manual The noise vector, the uplink transmission power and the mode selection vector are the optimization models, and the corresponding mode selection and security transceiver design schemes are given.

The design method and device for the MIMO transceiver provided by the embodiment of the present application will be described below with reference to FIG. 1 to FIG. 7 .

Fig. 1 is one of the flow diagrams of the multi-input multi-output transceiver design method provided in this application, as shown in Fig. 1, including but not limited to the following steps:

First, in step S1, based on the safe rate model of user signals in the signal transmission system, a target optimization model is constructed.

Users in the signal transmission system include uplink users and downlink users.

Fig. 2 is a schematic structural diagram of the signal transmission system provided by the present application. As shown in Fig. 2, the duplex modes in the signal transmission system may include: working modes such as flexible duplex, hybrid duplex and full duplex; network-assisted full duplex In the working mode, each access point is connected to the central processing unit through the fronthaul network.

In the same access point, the transmitting antenna will form self-interference to the receiving antenna; the uplink user will form uplink to downlink interference to the downlink user; in the same working mode, the receiving antenna will form downlink to uplink interference; eavesdropping The device can eavesdrop on leaked signals to uplink users and transmit antennas.

In the signal transmission system provided by the present application, each wiretapping device can wiretap all user equipments. By setting the spectrum detection device, it is possible to determine the detected wiretapping device in the signal transmission system and the location of the wiretapping device.

The mode selection vector is a duplex mode selection vector.

The security rate model includes an uplink user security rate function and a downlink user security rate function.

The objective optimization model includes an objective function and constraints.

Specifically, according to the safe rate model of user signals in the signal transmission system, the objective function and constraints are constructed.

Further, in step S2, the target optimization model is solved to determine the optimal design parameters of the transceiver in the signal transmission system; the optimal design parameters include downlink precoding vector, downlink artificial noise vector, uplink At least one item of link transmission power and mode selection vector; the security rate model is determined based on signal security rates associated with all users and eavesdropping devices.

The working modes in the signal transmission system may include: flexible duplex mode, hybrid duplex mode and full duplex mode.

For each user, among the signals leaked by all the eavesdropping devices, the SINR of the most leaked signal is determined, and then the signal security rate associated with each user and the eavesdropping device is determined through the SINR.

Since the objective optimization model itself has integer variables and multi-variables are coupled with each other, it belongs to non-smooth and non-convex optimization. Input multiple output transceiver design.

Specifically, the outer loop is based on the quantum tabu algorithm to solve the optimal duplex mode selection of the signal transmission system in a single loop. Through the inner loop, a series of non-convex-to-convex approximations, such as equivalent conversion or concave-convex process, will be used on the basis of the best working mode to solve the target optimization model, and finally the signal can be calculated The optimized design parameters of the transceivers in the transmission system can also determine the eavesdropping devices with the strongest interference to each user respectively.

The multi-input multi-output transceiver design method provided by this application, by constructing the target optimization model and solving the target optimization model, and then obtaining the optimal design parameters of the transceiver, can effectively prevent interception of signals by eavesdropping devices and ensure signal transmission System communication security.

Optionally, the all users include all downlink users and all uplink users, and before constructing the target optimization model based on the safe rate model of user signals in the signal transmission system, it further includes:

Determine the signal security rate function of any downlink user according to the signal-to-interference-noise ratio at any downlink user and the signal-to-interference-noise ratio of any downlink user at all eavesdropping device positions;

And according to the signal-to-interference-noise ratio of any uplink user's received signal and the signal-to-interference-noise ratio of any uplink user's leaked signal at all eavesdropping device positions, determine the signal security rate function of any uplink user;

The security rate model is constructed according to the signal security rate functions of all uplink users and the signal security rate functions of all downlink users.

Optionally, the SINR at the downlink user is obtained based on the following method:

Determine the transmission signal of the downlink access point in the signal transmission system based on the mode selection vector function, the downlink precoding vector function and the downlink artificial noise vector function of each access point;

determining a received signal received by each downlink user from the downlink access point according to the signal sent by the downlink access point;

Determine the signal-to-interference-noise ratio at each downlink user according to the interference covariance of the signals received by each user.

Optionally, the signal-to-interference-noise ratio of the received signal of the uplink user is obtained based on the following method:

According to the received signal of each uplink access point, the received signal of the cascaded central processing unit is obtained;

Performing interference elimination on the received signal of the cascaded central processing unit, and obtaining the received signal of the central processing unit;

According to the interference signal of each uplink user and the received signal of the central processing unit, the signal-to-interference ratio of the received signal of each uplink user is acquired.

Optionally, the signal-to-interference-noise ratio of the leakage signal of the downlink user at all eavesdropping device positions is obtained based on the following method:

Obtain the leaked signal of the location of each eavesdropping device in the downlink;

According to the leaked signal of each eavesdropping device position in the downlink, and the interference covariance of each downlink user at each eavesdropping device, determine the signal interference noise of each downlink user leaking signal at all eavesdropping device positions Compare.

Optionally, the signal-to-interference-noise ratio of the leakage signal of the uplink user at all eavesdropping device locations is obtained based on the following method:

According to the signal transmission power of each uplink user and the interference covariance of each uplink user at each eavesdropping device, determine the signal-to-interference-noise ratio of each uplink user's leaked signal at all eavesdropping device locations.

In the network-assisted full-duplex mode, the access point is connected to the central processing unit through the fronthaul network, and can work in half-duplex, same-frequency duplex, hybrid duplex and flexible duplex modes. Consider the uplink and downlink antennas of the same-frequency duplex base station and the antenna interference between uplink and downlink access points, as well as the inter-user interference between uplink users and downlink users. Each access point can work in uplink or downlink mode, which is obtained by solving the optimization result.

The signal transmission system has X access points, K downlink users, J uplink users and L eavesdropping devices. Each access point is equipped with M antennas, and each user and eavesdropping device is a single antenna. The access point metrics set is

The downlink user indicator set is

The uplink user indicator set is

and the eavesdropping device indicator set is

It can be understood that in the formula below, x' is the access point index set

in which is not an access point of x; k' is the downlink user index set

The downlink user in is not k; j' is the uplink user index set

Uplink users other than j in .

Define variables q _D,x ,q _U,x′ ∈ {0,1} to represent the uplink and downlink mode selection of the access point respectively, and q _D,x (q _U,x′ ) takes 1 or 0 to correspond to the access point Click to select downlink or uplink.

Let q _D ＝[q _D,1 ,q _D,2 ,…,q _D,X ]∈{0,1} ^X×1 , q _U ＝[q _U,1 ,q _U,2 ,…,q _{U ,X} ]∈{0,1} ^X×1 , the corresponding diagonal distribution matrix is:

From this, it can be concluded that the transmission signal x _D of the downlink access point is:

in,

is the downlink precoding vector for user k,

is a vector whose dimension is MX×1; s _D,k is the data signal sent to user k,

is the artificial noise superimposed in the transmitted signal by the downlink access point,

Anti-eavesdropping equipment interception by superimposing artificial noise on the transmitted signal.

Further, according to the transmission signal x _D of the downlink access point, it can be obtained that the received signal y _D, k of user k from the downlink access point is:

in,

Indicates the channel vector from all access points to user k; h _IUI,j,k indicates the channel vector between uplink user j and downlink user k; p _U,j is the signal transmission power of uplink user j;

Indicates the data signal from uplink user j;

Indicates the additive white Gaussian noise at the downlink user k.

According to the received signal y _D, k at the downlink user k, the signal-to-interference-noise ratio r _D,k at the downlink user k can be listed, the expression is:

where γ _D,k is the interference covariance at downlink user k:

Among them, g _U,j,k represents the channel state information from uplink transmitting user j to downlink receiving user k; σ _D,k represents Gaussian white noise at user k.

For the uplink, first list the received signal y _U,x′ at any access point x′, the specific formula is as follows:

in,

Indicates the channel vector from uplink user j to access point x′;

Indicates the channel vector between access point x and access point x′; x _{D, x} is the transmitted signal of downlink access point x; n _{U, x′} is the additive white Gaussian noise vector at access point x′ ,

Thus, it can be concluded that the received signal y _U cascaded in the central processing unit is:

in,

Due to the existence of channel estimation errors, the central processing unit often cannot completely remove the interference between the uplink and downlink antennas of the base station based only on its known downlink baseband signals and estimated channel information. For practical considerations, it is assumed that the estimation error of the channel between base station antennas is

And also assume that it obeys a Gaussian distribution:

Indicates the residual inter-antenna interference power not canceled in the digital or analog domain.

After proper interference cancellation, the received signal of the central processing unit becomes

The specific calculation is as follows:

Thus, the signal-to-interference-noise ratio r _U,j of the received signal of the uplink user j at the central processing unit can be obtained, and the expression is:

in,

is the receiver precoding vector; γ _U,j is the interference and noise when processing the signal of uplink user j, the expression is as follows:

Among them, u _U,j,x' represents the receiver precoding vector at the receiving access point x'; Q _U,x' represents the duplex working mode assignment matrix at the receiving access point x'; Q _D,x represents The duplex working mode allocation matrix at the transmitting access point x; w _D,x,k represents the downlink precoding vector of the transmitting access point x for user k; v _AN,x represents the artificial noise superimposed at the access point x; σ _U,x' represents the Gaussian white noise at the access point x'; δ _IAI,x,x' represents the residual interference power between the access point x and the access point x' after interference cancellation.

Assuming that the eavesdropping device can also obtain downlink information, the expression of the leaked signal y _{EV,l at the eavesdropping device l} can be listed as follows:

in,

Represent the eavesdropping channel vectors from all access points to eavesdropping device l;

is the additive white Gaussian noise to the eavesdropping device l; h _UE,j,l represents the channel parameter from the uplink user j to the eavesdropping device l; n _DE,l represents the Gaussian white noise at the eavesdropping device l.

Thus, the signal-to-interference-noise ratio r _DE,k,l of the downlink user k signal leaked at the eavesdropping device l, and the SINR r _{UE,j,l of the uplink user j signal leaked at the eavesdropping device l} , The specific expression is:

Among them, γDE _,k,l and γUE _,j,l are the interference covariance of downlink user k and uplink user j at the eavesdropping device l respectively, and the expressions are written as:

Among them, σ _DE,l represents the white noise power when the eavesdropping device l eavesdrops on the downlink user k; σ _UE,l represents the white noise power when the eavesdropping device l eavesdrops on the uplink user j.

Therefore, the signal security rate functions of each downlink user k and uplink user j in the signaling system can be written as R _Ds,k and R _Us,j respectively, and the specific calculation is as follows:

According to the signal security rate function of all uplink users and the signal security rate function of downlink users, the security rate model of the whole signal transmission system is constructed.

The entire signal transmission system aims at maximizing the safe rate of the uplink and downlink signals of the system, and takes the total transmission power of the access point and the total transmission power of the uplink users as constraints to realize the downlink precoding vector, downlink artificial noise vector, uplink The joint optimal design of channel transmit power and mode selection vector.

First build the target optimization model:

stC1:

C2:

C3:

C4:

Among them, q _{D, x} is the duplex working mode allocation vector at the sending access point x; q _{U, x} is the duplex working mode allocation vector at the receiving access point x; _{PD, x} is the preset xth The total transmit power of access points is taken as the maximum transmit power consumption of access points; P _U,j is the total transmit power of uplink user j, which is taken as the maximum transmit power of uplink user j.

Since there are two binary variables {q _D,x ,q _U,x′ }, the non-convex optimization problem is a non-deterministic polynomial hard (NP-hard) mixed integer problem. When the number of access points and users is limited, the global optimal solution can be obtained by exhaustive method. However, in a non-cellular large-scale MIMO network, the number of access points is very large, and the calculation complexity of using the exhaustive method is greatly increased, and O(2 ^X ) sub-problems need to be calculated. Therefore, the exhaustive method is not applicable in actual situations.

The outer loop uses a duplex mode selection algorithm based on quantum tabu search to determine the working direction of each access point;

The inner loop optimizes the downlink precoding vector w _{D, k} , the downlink artificial noise vector v _AN , the value of the uplink transmit power p _U,j, and the mode selection vector based on the duplex direction determined by the outer loop Q _D and Q _U .

Optionally, the solving the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system includes:

determining the working mode of the signal transmission system;

According to the working mode, approximate optimization is performed on the objective function and constraint conditions of the objective optimization model, and a solution optimization model is constructed;

Determining the optimal design parameters based on the solution optimization model;

The objective function is to optimize the maximum signal security rate of all users;

The constraints are based on the total power of the sending access point and the total power consumption of the uplink users.

Optionally, the determining the working mode of the signal transmission system includes:

Constructing a quantum system of the signal transmission system according to the state of the access point in the signal transmission system;

Measuring the quantum system by using a random matrix to determine a feasible solution matrix;

Using the feasible solution matrix to optimize and solve, determine the working mode of the signal transmission system.

The quantum tabu search algorithm combines the two basic concepts of tabu search and quantum computing, so the quantum tabu search algorithm can not only use the quantum algorithm to fully reflect the change of the system information state, but also use the tabu search algorithm to improve the search efficiency. According to the proposed quantum taboo search method, the duplex mode of each access point can be optimized, and the specific calculation method is as follows:

First, according to the number of access points in the signal transmission system, initialize

and the value of μ,

Represents a quantum system with X qubits, μ is used to record the optimal solution obtained, and the initial value is set to 0.

Among them, α _x and β _x represent the probability that the qubit is in the 0 state and the 1 state, respectively,

Indicates that being in the 0 state is equally likely to be in the 1 state.

Further, randomly generate a random matrix

The random matrix V generates feasible solutions and adjacent solutions, where C represents the number of feasible solutions; the elements in the matrix V are between 0 and 1, and each row of the matrix V represents a possible duplex mode;

Represents a matrix of dimension C×X.

Furthermore, by measuring

Times, the obtained feasible solution is stored in the matrix

, specifically as follows:

Among them, by comparing

middle

And the value of the corresponding column element in the matrix V, each bit can be obtained

value.

Further, in order to satisfy the feasible region, a new variable ρ representing the feasible solution is introduced, so that

And solve the optimization problem and evaluate the suitable solution. in

Further, update the optimal solution μ. If the current loop fitness value is better than μ, then μ is replaced by the current loop fitness value.

Furthermore, in the process of looping, two kinds of solutions can be obtained from domain solutions. One is the best solution, which is stored in ρ ^b ; the other is the worst solution, which is stored in ρ ^w .

Further, Table 1 is a lookup table for a revolving door provided in the present application, wherein Δθ represents the angle of rotation.

Table 1 Revolving door lookup table

Based on Table 1, update

value. U(θ) represents the quantum gate, according to the quantum gate and

The calculation of the next cycle state of each access point in the signal transmission system can be obtained

At this time, the working mode of the transceiver in the signal transmission system can be determined.

Optionally, according to the working mode, performing approximate optimization on the objective function and constraint conditions of the objective optimization model, and constructing a solution optimization model, including:

According to the working mode, an approximate convex optimization solution is performed on the objective function to determine a new optimization function;

In the case that the optimization function does not converge, performing an approximate convex optimization solution to the new optimization function until the obtained optimization function converges, and then determining the convergence optimization function;

The solution optimization model is constructed according to the convergent optimization function.

The inner loop adopts an optimization algorithm based on Successive Convex Approximation (SCA), fixes the duplex mode, and optimizes the design of the transceiver. First consider the objective function in the optimization problem. By introducing two variables λ _D,k and λ _U,j , which respectively represent the lower bounds of the downlink security rate and uplink security rate, the optimization problem can be transformed into:

stC5:

C6:

Then, a series of new variables {ψ _D,k } and {ψ _U,j } are introduced, respectively representing the upper bounds of the rate at which the eavesdropping device eavesdrops on the downlink user and the rate at which the eavesdropping device eavesdrops on the uplink user, and the optimization problem can be approximated as :

stC7: ln(1+r _DE,k,l )≤ψ _D,k

C8: ln(1+r _D,k )-ψ _D,k ≥λ _D,k

C9: ln(1+r _UE,j,l )≤ψ _U,j

C10: ln(1+r _U,j )-ψ _U,j ≥λ _U,j ;

Although the original problem can be approximated by a new optimization problem to solve, but because w _D,k ,p _U,j ,u _U,j are tightly coupled together in constraints, the optimal solution of the new optimization problem is still difficult to find untie. According to the duplex mode determined by the outer loop, the values of Q _D,x and Q _U,x′ can be fixed first, and the optimization problem can be written as:

s.t. C1, C2, C7, C8, C9, C10;

in,

Due to the constraints C7 to C10, the optimization problem is non-convex and needs further variation processing.

First, for the constraint C7, by introducing a new variable τ _DE,k,l , which represents the optimized upper bound of the SNR of the eavesdropping device to the downlink user, the inequality C7 and the function r _DE,k,l can be approximated as:

C11: ln(1+τ _DE,k,l )≤ψ _D,k

C12:

D1:

D2:

Among them, a represents the optimization variable; w represents the vector variable; A represents the matrix constant. Using inequalities D1 and D2 to carry out first-order Taylor expansion on constraint condition C11 and constraint condition C12, respectively obtain constraint condition C13 and constraint condition C14:

C13:

C14:

in,

Next, for constraint C8, a variable {t _D,k } is introduced, representing the expression

The optimal lower bound of r _D,k can be approximated as:

C15:

in,

C16:

C17: t _D,k ≥ 0;

Using the inequality D2, the first-order Taylor expansion of the constraint C16 can be approximated as:

C18:

D3:

Among them, a and b are variables, a>0, b>0,

Since the constraint condition C15 is non-convex, finally use the D3 inequality to approximate C15, and get:

C19:

After completing the processing and approximation of the two downlink constraints C7 and C8, the constraints C9 and C10 are processed next.

For constraint C9, first consider the function r _UE,j,l . The upper bound of r _UE,j,l can be expressed as:

C20:

Among them, t _UE,j,l represents the upper bound of p _U,j |h _UE,j,l | ² ; τ _UE,j,l represents the lower bound of γ _UE,j,l .

C21:

C22: γ _UE,j,l ≥τ _UE,j,l ;

Constraint C9 can be written as:

C23:

given

in,

Indicates the output constant result of the optimization variable {τ _UE,l,k ,t _UE,j,l ,v _AN ,w _D,k′ } in the nth iteration, when n=0 represents the initial value of the input, using the inequality D1 and D2, constraints C21 and C22 can be approximated as:

C24:

C25:

Using inequality D1, constraint C23 is approximated as:

C26:

Constraint C10 is finally dealt with. Constraint C10 is the most intractable due to the coupling of variables p _U,j ,v _AN ,w _D,k and u _U,j in r _U,j . And introduce a new variable, get the lower bound of r _{U, j} , the constraint condition C27, specifically:

C27:

in,

are the new variables introduced, representing the expressions

The upper bound of , and the following constraints can be obtained:

C28:

C29:

C30:

C31:

Constraints C28 to C30 can be further approximated as:

C32:

C33:

C34:

Finally, constraint C10 can be transformed into:

C35:

in,

The target optimization model is finally transformed into a solution optimization model, as follows:

s.t. C1, C2, C13, C14, C17, C19, C24, C25, C26, C31, C32, C33, C34, C35;

At this time, according to the optimization model, the optimal design parameters of the transceiver in the signal transmission system can be obtained, including: downlink precoding vector

Downstream Artifact Vector

Uplink transmit power

and the mode selection vector

Can also include receiver precoding vector

In practical applications, any one or multiple items of optimal design parameters can be obtained according to specific requirements.

The multi-input multi-output transceiver design method provided by this application uses a double-loop strategy to solve the non-convex subproblem of the inner loop. The outer loop uses the quantum taboo algorithm to find the optimal mode selection for a single iteration, and then through the inner loop, Using continuous concave-convex process, equivalent transformation, etc. to solve non-convex to convex, and then determine the design of transceiver and uplink transmission power, and realize the communication security of signal transmission system.

Fig. 3 is the second schematic flow diagram of the multi-input multi-output transceiver design method provided by the present application, as shown in Fig. 3, including:

First, initialize

Further, generate a random matrix V, for

Make corrections.

Further, in the fixed

Solve the approximate convex optimization problem below, and update the parameters in the next convex optimization iteration with the optimal solution obtained

Further, it is judged whether the approximate convex optimization problem is converged, and if it is not converged, the problem is further approximated; in the case of convergence, the optimal solution of the approximate convex optimization is returned

Further, update fitness μ and

Find the optimal solution ρ ^b and the worst solution ρ ^w .

Further, it is judged whether the quantum tabu search algorithm converges, and if it does not converge, the random matrix pair is generated again

Make corrections; in the case of convergence, end and return the optimal solution

The multi-input multi-output transceiver design method provided by this application is constrained by the total power of the transmission access point and the total power of the uplink, so as to maximize the total rate of the uplink and downlink of the system under the limitation of power consumption, and realize the signal transmission system The uplink security transmission rate and the downlink security transmission rate maximization problem.

Fig. 4 is one of the security spectrum performance comparison diagrams provided by the present application. As shown in Fig. 4, the horizontal axis is the self-interference intensity △, and the unit is decibel (dB); the vertical axis is the spectral efficiency, and the unit is bit rate/Hz (bps /Hz). Under different self-interference suppression conditions, according to the safety spectrum efficiency performance curve in Figure 4, as the strength of self-interference changes, compared with the greedy algorithm, network-assisted full-duplex and time-division duplex in fixed duplex mode, based on The system security spectral efficiency and performance gain of the quantum tabu search algorithm are higher.

And the spectral efficiency performance of the quantum tabu search algorithm is also closer to the spectral efficiency of the exhaustive algorithm. When the self-interference is less than or equal to 0dB, the security spectral efficiency performance of the greedy algorithm, fixed duplex mode network-assisted full-duplex, time-division duplex, exhaustive algorithm and the proposed quantum tabu search algorithm changes relatively smoothly. When the self-interference is greater than 0dB, the performance of these five algorithms decreases sharply with the increase of self-interference. But on the whole, when the self-interference is in a low range, the energy efficiency improvement of this solution is very effective. Moreover, it can be found that when the self-interference is greater than 20dB, the gap between the performance of the quantum taboo search algorithm and the greedy algorithm and the network-assisted full-duplex performance of the fixed duplex mode further widens. Because when the self-interference is too large, the system needs a more flexible access point scheduling mechanism to overcome the negative impact of excessive self-interference. Therefore, compared with the greedy algorithm and the network-assisted full-duplex and time-division duplex mechanisms of the fixed duplex mode, the design based on the quantum taboo search algorithm has higher security spectrum efficiency and can provide a higher degree of freedom to overcome the influence of self-interference.

FIG. 5 is the second security spectrum performance comparison diagram provided by the present application. As shown in FIG. 5 , the horizontal axis is the number of access points, and the vertical axis is the spectrum efficiency, and the unit is bit rate/hertz (bps/Hz). Figure 5 shows the impact of different access point settings on the system security spectrum. Security algorithms include quantum tabu search algorithm, greedy algorithm, network-assisted full-duplex and time-division duplex. When the fixed self-interference is set to -5dB and the number of antennas is 2, the security spectral efficiency of all algorithms increases with the access point As the number increases, as the number of access points increases from 6 to 20, the security spectral efficiency range increases from 23.63bps/Hz to 50.76bps/Hz to 37.52bps/Hz to 74.34bps/Hz. And under the same parameter settings, the performance of the algorithm proposed in this application is better than other algorithms to achieve higher security spectrum efficiency, followed by greedy algorithm and fixed uplink and downlink network assisted full-duplex network, and the system security under time-division duplex mode Spectral effects came last.

The MIMO transceiver design device provided by this application is described below, and the MIMO transceiver design device described below and the MIMO transceiver design method described above can be referred to in correspondence.

Fig. 6 is a structural schematic diagram of the multi-input multi-output transceiver design device provided by the present application, as shown in Fig. 6, including:

A construction module 601, configured to construct a target optimization model based on a security rate model of user signals in the signal transmission system;

A solving module 602, configured to solve the target optimization model based on the working mode, and determine optimal design parameters of the transceiver in the signal transmission system; the optimal design parameters include downlink precoding vectors, downlink manual At least one of a noise vector, an uplink transmission power, and a mode selection vector; the security rate model is determined based on signal security rates associated with all users and eavesdropping devices.

First, the construction module 601 constructs a target optimization model based on a safe rate model of user signals in the signal transmission system.

Users in the signal transmission system include uplink users and downlink users.

As shown in Figure 2, the duplex mode in the signal transmission system may include: flexible duplex, hybrid duplex, and full duplex; in network-assisted full-duplex mode, each access point into the central processing unit.

In the same access point, the transmitting antenna will form self-interference to the receiving antenna; the uplink user will form uplink to downlink interference to the downlink user; in the same working mode, the receiving antenna will form downlink to uplink interference; eavesdropping The device can eavesdrop on leaked signals to uplink users and transmit antennas.

In the signal transmission system provided by the present application, each wiretapping device can wiretap all user equipments. By setting the spectrum detection device, it is possible to determine the detected wiretapping device in the signal transmission system and the location of the wiretapping device.

The mode selection vector is a duplex mode selection vector.

The security rate model includes an uplink user security rate function and a downlink user security rate function.

The objective optimization model includes an objective function and constraints.

Specifically, according to the safe rate model of user signals in the signal transmission system, the objective function and constraints are constructed.

Further, the solving module 602 solves the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system; the optimal design parameters include downlink precoding vector, downlink artificial noise vector, uplink At least one item of transmission power and mode selection vector; the safe rate model is determined based on the signal safe rates associated with all users and eavesdropping devices.

The working modes in the signal transmission system may include: flexible duplex mode, hybrid duplex mode and full duplex mode.

For each user, among the signals leaked by all the eavesdropping devices, the SINR of the most leaked signal is determined, and then the signal security rate associated with each user and the eavesdropping device is determined through the SINR.

Since the objective optimization model itself has integer variables and multi-variables are coupled with each other, it belongs to non-smooth and non-convex optimization. Input multiple output transceiver design.

Specifically, the outer loop is based on the quantum tabu algorithm to solve the optimal duplex mode selection of the signal transmission system in a single loop. Through the inner loop, a series of non-convex-to-convex approximations, such as equivalent conversion or concave-convex process, will be used on the basis of the best working mode to solve the target optimization model, and finally the signal can be calculated The optimized design parameters of the transceivers in the transmission system can also determine the eavesdropping devices with the strongest interference to each user respectively.

The multi-input multi-output transceiver design device provided by this application, by constructing the target optimization model and solving the target optimization model, and then obtaining the optimal design parameters of the transceiver, can effectively prevent interception of signals by eavesdropping devices and ensure signal transmission System communication security.

FIG. 7 is a schematic structural diagram of an electronic device provided by the present application. As shown in FIG. 7, the electronic device may include: a processor (processor) 710, a communication interface (Communications Interface) 720, a memory (memory) 730 and a communication bus 740, Wherein, the processor 710 , the communication interface 720 , and the memory 730 communicate with each other through the communication bus 740 . The processor 710 can call the logic instructions in the memory 730 to execute the design method of the multiple-input multiple-output transceiver. The method includes: building a target optimization model based on the safe rate model of the user signal in the signal transmission system; determining the signal transmission system Based on the working mode, the target optimization model is solved to determine the optimal design parameters of the transceiver in the signal transmission system; the optimal design parameters include downlink precoding vectors, downlink artificial noise vectors At least one of , uplink transmission power, and mode selection vector; the security rate model is determined based on signal security rates associated with all users and eavesdropping devices.

In addition, the above-mentioned logic instructions in the memory 730 may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disc and other media that can store program codes. .

On the other hand, the present application also provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer During execution, the computer can execute the multiple-input multiple-output transceiver design method provided by the above-mentioned methods, the method includes: building a target optimization model based on the safe rate model of the user signal in the signal transmission system; determining the working mode of the signal transmission system mode; based on the working mode, solve the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system; the optimal design parameters include downlink precoding vector, downlink artificial noise vector, uplink At least one item of link transmission power and mode selection vector; the security rate model is determined based on signal security rates associated with all users and eavesdropping devices.

In yet another aspect, the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to implement the design of the MIMO transceiver provided by the above-mentioned embodiments. The method includes: constructing a target optimization model based on a safe rate model of user signals in a signal transmission system; determining the working mode of the signal transmission system; solving the target optimization model based on the working mode, and determining the The optimized design parameters of the transceiver in the signal transmission system; the optimized design parameters include at least one of a downlink precoding vector, a downlink artificial noise vector, an uplink transmission power, and a mode selection vector; the safe rate model is determined based on the signal security rate associated with the listening device for all users.

The device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative effort.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims (13)

1. A method for designing a multiple-input multiple-output transceiver, comprising:

   Based on the safe rate model of user signals in the signal transmission system, the target optimization model is constructed;

   Solving the target optimization model to determine optimal design parameters of the transceiver in the signal transmission system;

   The optimal design parameters include at least one of a downlink precoding vector, a downlink artificial noise vector, an uplink transmit power, and a mode selection vector;

   The security rate model is determined based on signal security rates associated with all users with the bugging device.
2. The multi-input multi-output transceiver design method according to claim 1, wherein said solving the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system includes:

   determining the working mode of the signal transmission system;

   According to the working mode, approximate optimization is performed on the objective function and constraint conditions of the objective optimization model, and a solution optimization model is constructed;

   Determining the optimal design parameters based on the solution optimization model;

   The objective function is to optimize the maximum signal security rate of all users;

   The constraints are based on the total power of the sending access point and the total power consumption of the uplink users.
3. The method for designing a multiple-input multiple-output transceiver according to claim 2, wherein, according to the operating mode, performing approximate optimization on the objective function and constraint conditions of the objective optimization model, and constructing a solution optimization model, comprising:

   According to the working mode, an approximate convex optimization solution is performed on the objective function to determine a new optimization function;

   In the case that the optimization function does not converge, performing an approximate convex optimization solution to the new optimization function until the obtained optimization function converges, and then determining the convergence optimization function;

   The solution optimization model is constructed according to the convergent optimization function.
4. The method for designing a multiple-input multiple-output transceiver according to claim 2, wherein said determining the working mode of said signal transmission system comprises:

   Constructing a quantum system of the signal transmission system according to the state of the access point in the signal transmission system;

   Measuring the quantum system by using a random matrix to determine a feasible solution matrix;

   Using the feasible solution matrix to optimize and solve, determine the working mode of the signal transmission system.
5. The multiple-input multiple-output transceiver design method according to claim 1, wherein said all users include all downlink users and all uplink users, and in said signal transmission system based on the safe rate model of user signals, an objective optimization model is constructed Previously, also included:

   Determine the signal security rate function of any downlink user according to the signal-to-interference-noise ratio at any downlink user and the signal-to-interference-noise ratio of any downlink user at all eavesdropping device positions;

   And according to the signal-to-interference-noise ratio of any uplink user's received signal and the signal-to-interference-noise ratio of any uplink user's leaked signal at all eavesdropping device positions, determine the signal security rate function of any uplink user;

   The security rate model is constructed according to the signal security rate functions of all uplink users and the signal security rate functions of all downlink users.
6. The method for designing a multiple-input multiple-output transceiver according to claim 5, wherein the SINR at the downlink user is obtained based on the following method:

   Determine the transmission signal of the downlink access point in the signal transmission system based on the mode selection vector function, the downlink precoding vector function and the downlink artificial noise vector function of each access point;

   determining a received signal received by each downlink user from the downlink access point according to the signal sent by the downlink access point;

   The SINR at each downlink user is determined according to the interference covariance of the signals received by each user.
7. The method for designing a multiple-input multiple-output transceiver according to claim 5, wherein the signal-to-interference-noise ratio of the received signal of the uplink user is obtained based on the following method:

   According to the received signal of each uplink access point, the received signal of the cascaded central processing unit is obtained;

   Performing interference elimination on the received signal of the cascaded central processing unit, and obtaining the received signal of the central processing unit;

   According to the interference signal of each uplink user and the received signal of the central processing unit, the signal-to-interference ratio of the received signal of each uplink user is obtained.
8. The method for designing a multiple-input multiple-output transceiver according to claim 5, wherein the signal-to-interference-noise ratio of the leakage signal of the downlink user at all eavesdropping device positions is obtained based on the following method:

   Obtain the leaked signal of the location of each eavesdropping device in the downlink;

   According to the leaked signal of each eavesdropping device position in the downlink, and the interference covariance of each downlink user at each eavesdropping device, determine the signal interference noise of the leaked signal of each downlink user at all eavesdropping device positions Compare.
9. The method for designing a multiple-input multiple-output transceiver according to claim 5, wherein the signal-to-interference-noise ratio of the leakage signal of the uplink user at all eavesdropping device positions is obtained based on the following method:

   According to the signal transmission power of each uplink user and the interference covariance of each uplink user at each eavesdropping device, determine the signal-to-interference-noise ratio of each uplink user leaking signals at all eavesdropping device locations.
10. A design device for a multiple-input multiple-output transceiver, comprising:

    The building block is based on the safe rate model of the user signal in the signal transmission system, and constructs the target optimization model;

    A solution module solves the target optimization model to determine the optimal design parameters of the transceiver in the signal transmission system;

    The optimal design parameters include at least one of a downlink precoding vector, a downlink artificial noise vector, an uplink transmit power, and a mode selection vector;

    The security rate model is determined based on signal security rates associated with all users with the bugging device.
11. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein, when the processor executes the program, the computer program according to any one of claims 1 to 9 is realized. Design method of multiple-input multiple-output transceiver described in item.
12. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the design method for a multiple-input multiple-output transceiver according to any one of claims 1 to 9 is realized.
13. A computer program product, including a computer program, wherein, when the computer program is executed by a processor, the design method for a multiple-input multiple-output transceiver according to any one of claims 1 to 9 is implemented.

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