CN113660051A - Energy efficiency maximization method and system of millimeter wave communication system - Google Patents

Abstract

The invention discloses a method and system for maximizing energy efficiency of a millimeter-wave communication system. The method includes the following steps: first, a plurality of intelligent reflection surfaces are set in the millimeter-wave communication system, and a multi-input single-output millimeter-wave communication system is constructed. Second, obtain multiple model parameters of the millimeter-wave communication system model, and establish the energy efficiency maximization model of the millimeter-wave communication system; then, decouple the energy efficiency maximization model of the millimeter-wave communication system into phase optimization, beamforming optimization, intelligent Three sub-problems of reflector switch optimization; finally, the three sub-problems of phase optimization, beamforming optimization, and intelligent reflector switch optimization are solved alternately and iteratively to obtain the convergence results that maximize the energy efficiency of the millimeter-wave communication system. The above method effectively improves the energy efficiency and communication quality of the system and improves the communication environment.

Description

Energy Efficiency Maximization Method and System for Millimeter Wave Communication Systems

technical field

The present invention relates to the field of communication technologies, and in particular, to a method and system for maximizing energy efficiency of a millimeter wave communication system.

Background technique

With the development of science and technology and the advancement of society, communication technology is also constantly developing, among which, the high data rate requirements of emerging and future wireless networks (5th generation (5G) and above) have caused people's energy consumption close attention. One of the key performance indicators of 5G communication networks is high throughput. As an emerging communication technology, millimeter wave communication is more and more widely used in communication systems because it meets huge throughput requirements.

At present, a single IRS (Intelligent Reflecting Surface) is mostly used in millimeter-wave communication systems to optimize the energy efficiency of the millimeter-wave communication system. In the blocking effect of the millimeter-wave communication system, the intelligent reflecting surface can adjust the phase shift of the planar array by adjusting the phase shift of the millimeter-wave communication system. To enhance the user's receiving gain, improve the overall energy efficiency of the system, and improve the communication quality. In addition, in the millimeter-wave communication system, when the millimeter-wave signal is transmitted, when the signal strength between the base station and the user is too large, the blocking effect of the millimeter-wave makes the communication quality of the entire millimeter-wave communication system low, resulting in low communication efficiency. However, the millimeter wave signal has problems such as small coverage, serious interference and high network construction cost.

Therefore, how to maximize the energy efficiency of the millimeter wave communication system has become an urgent technical problem to be solved.

SUMMARY OF THE INVENTION

Based on this, it is necessary to provide a method and system for maximizing the energy efficiency of a millimeter-wave communication system for the problem of low energy efficiency of a millimeter-wave communication system.

A method for maximizing energy efficiency of a millimeter wave communication system, comprising the following steps:

Set up multiple smart reflectors in the millimeter-wave communication system to build a multi-input single-output millimeter-wave communication system model;

Obtain multiple model parameters of the millimeter-wave communication system model, and establish an energy efficiency maximization model of the millimeter-wave communication system;

The energy efficiency maximization model of millimeter wave communication system is decoupled into three sub-problems: phase optimization, beamforming optimization, and intelligent reflector switch optimization;

Alternately and iteratively solve the three sub-problems of phase optimization, beamforming optimization, and intelligent reflector switch optimization to obtain a convergence result that maximizes the energy efficiency of the millimeter-wave communication system.

In one of the embodiments, the millimeter wave communication system model further includes a base station, a plurality of intelligent reflective surface control switches, and a plurality of users, wherein,

When any smart reflective surface control switch is closed, the base station can send the transmission signal to each of the multiple users respectively through the smart reflective surface controlled by the smart reflective surface control switch.

In one of the embodiments, the step of acquiring multiple model parameters of the millimeter-wave communication system model, and establishing an energy efficiency maximization model of the millimeter-wave communication system includes the following steps:

Determine the signal-to-interference-noise ratio of a single user, the sum rate of multiple users, and the power consumption of a mmWave communication system.

In one embodiment, the signal-to-interference-noise ratio of the single user is:

θ_ln∈[0,2π]，x_l为智能反射面开关矢量，当x_l＝0时，第l个智能反射面不参与信号传输；当x_l＝1时，表明第l个智能反射面处于工作状态，k表示多个用户中的第k个用户，l表示毫米波通信系统中多个智能反射面中的第l个智能反射面，N_l表示第l个智能反射面上反射元件的数量，ω_k是第k个用户的波束形成矢量，M为基站的天线数量，G_l表示基站到第l个IRS的信道，h_kl表示从第l个智能反射面到第k个用户的信道，其中，

h_kl ^H表示h_kl的共轭转置矩阵。Among them, n _k additive white Gaussian noise, n _k ～CN(0,σ ² ), the effective phase shift matrix applied by the smart reflector:

θ _ln ∈ [0,2π], x _l is the switch vector of the smart reflective surface, when x _l = 0, the l-th smart reflective surface does not participate in signal transmission; when x _l = 1, it indicates that the l-th smart reflective surface In the working state, k represents the kth user among the multiple users, l represents the lth smart reflector among the multiple smart reflectors in the millimeter wave communication system, and N _l represents the reflective element on the lth smart reflector. number, ω _k is the beamforming vector of the k-th user, M is the number of antennas of the base station, G _l represents the channel from the base station to the l-th IRS, h _kl represents the channel from the l-th smart reflector to the k-th user ,in,

h _kl ^H represents the conjugate transpose matrix of h _kl .

In one embodiment, determining the sum rate of multiple users includes the following steps:

Based on the signal-to-dry ratio of a single user, the sum rate of multiple users is determined by Shannon's theorem:

Among them, B is the bandwidth of the channel in the millimeter wave communication system.

In one embodiment, the power consumption of the millimeter wave communication system is:

where ω _k is the beamforming vector of the kth user, μ is the efficiency of the base station power amplifier, P _BS is the hardware power consumption of the base station, P _k is the hardware power consumption of the mobile user terminal, and P _IRS is the hardware power consumption of the intelligent reflector .

In one embodiment, the energy efficiency maximization model of the millimeter wave communication system is:

ω ^H ω≤P _max , (2.3)

θ _ln ∈ [0,2π], (2.4)

x _l ∈ {0,1}, (2.5)

ω＝[ω₁,...,ω_K]^T，x＝[x₁,...,x_L]^T，R_k是第k个用户的最小速率，P_max是基站处的最大发送功率。in

ω=[ω ₁ ,...,ω _K ] ^T , x=[x ₁ ,...,x _L ] ^T , R _k is the minimum rate of the kth user, P _max is the maximum transmit power at the base station .

In one embodiment, the phase optimization sub-problem is:

θ _ln ∈ [0,2π], (3.4)

where γ is the relaxation vector introduced, γ=[γ ₁ ,...,γ _K ] ^T , and γ _k is an element in γ;

The beamforming optimization sub-problem is:

ω ^H ω≤P _max , (12.3)

Among them, ζ is the slack variable introduced, ζ=[ζ ₁ ,...,ζ _K ] ^T , ζ _k is the element in ζ,

The intelligent reflective surface switching optimization sub-problem is a nonlinear integer optimization problem of the intelligent reflective surface switching vector x.

In one embodiment, the alternate iterative solution of the three sub-problems of phase optimization, beamforming optimization, and smart reflector switch optimization, and obtaining a convergence result that maximizes the energy efficiency of the millimeter-wave communication system includes:

Using continuous convex approximation and Dinkelbach method to solve the beamforming optimization sub-problem, the optimal beamforming is obtained;

The non-convex problem of the phase optimization sub-problem is transformed into a convex problem by semi-definite relaxation and continuous convex approximation method to solve the phase optimization sub-problem;

The greedy method is used to solve the optimization problem of smart reflector switching.

An energy efficiency maximization system for a millimeter wave communication system, comprising,

The building block is used to set up multiple smart reflectors in the millimeter-wave communication system, and build a multi-input single-output millimeter-wave communication system model;

A module is established to obtain multiple model parameters of the millimeter-wave communication system model, and to establish an energy efficiency maximization model of the millimeter-wave communication system;

The decoupling module is used to decouple the energy efficiency maximization model of the millimeter wave communication system into three sub-problems: phase optimization, beamforming optimization, and intelligent reflector switch optimization;

The solving module is used to alternately and iteratively solve the three sub-problems of phase optimization, beamforming optimization, and intelligent reflector switch optimization, so as to obtain a convergence result that maximizes the energy efficiency of the millimeter wave communication system.

The energy efficiency maximization method of the above-mentioned millimeter-wave communication system uses multiple smart reflective surfaces to assist, which can provide reliable data transmission, because different smart reflective surfaces can be deployed geometrically separately, and at the same time, multiple smart reflective surfaces can provide receiving signals In addition, setting up multiple intelligent reflecting surfaces can effectively improve the confidentiality and energy efficiency of the millimeter wave communication system, and realize green communication.

Further, the energy efficiency maximization of the millimeter wave communication system is decoupled into three sub-problems: phase optimization, beamforming optimization, and IRS switch optimization. The final convergence result of the alternate iteration algorithm proves that the energy efficiency maximization method of the millimeter wave communication system can be It can effectively improve the energy efficiency of the system, reduce the complexity of the algorithm, reduce the number of iterations, improve the communication environment, and improve the communication quality.

Description of drawings

Figure 1 is a flowchart of a method for maximizing energy efficiency of a millimeter-wave communication system;

Figure 2 is a structural diagram of a millimeter wave communication system;

Fig. 3 is a graph showing the convergence result of the energy efficiency maximization method of the millimeter wave communication system as the number of iterations increases;

FIG. 4 is a structural diagram of an energy efficiency maximizing system of a millimeter wave communication system.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Referring to FIG. 1, an embodiment of the present invention introduces a method for maximizing energy efficiency of a millimeter wave communication system, including the following steps:

In step S100, a plurality of intelligent reflecting surfaces are set in the millimeter wave communication system, and a model of the millimeter wave communication system with multiple input and single output is constructed.

s_k是归一化信息符号，s_k属于s，s＝[s₁,...,s_K]，且

表示发给第k个用户的信息。进一步满足，E(SS^H)＝I_K表示s满足分布规律，E表示期望。ω_k是第k个用户的波束形成矢量，其中，ω_k为ω中的元素，

进一步，G_l表示基站到第l个IRS的信道，h_kl表示从第l个IRS到第k个用户的信道，其中，

第l个IRS上有N_l个反射元件(反射元件即图2中的反射阵源)，进一步，所有IRS的反射元件个数是相等的，示例性的，l取值为1、2或10等整数时，N₁、N₂以及N₁₀的取值相等，优选地，在仿真时，可设置N_l＝256或64。本发明实施例中通过在毫米波通信系统中加入多个智能反射面(IRS)能够提供可靠的数据传输，因为系统中不同的智能反射面可以在几何上分开部署，同时，多个智能反射面可以提供接收信号的多条路径，增加了用户接收信号的强度，此外设置多个智能反射面能有效提高毫米波通信系统的保密性和能效，实现绿色通信。Specifically, the millimeter wave communication system model further includes a base station, multiple control switches, and multiple users. When any control switch is closed, the base station can separate the transmitted signals of the base station through the intelligent reflective surface controlled by the control switch. Sent to each of multiple users. Referring to FIG. 2 , there are a total of L multiple smart reflective surfaces in the millimeter wave communication system model, which are IRS1-IRSL, respectively, and the base station controls the corresponding smart reflective surfaces through corresponding control switches. There are K total of multiple users, k represents the kth user among the K users, k belongs to an integer, and k>0. More specifically, the base station is multi-antenna, the user is a single antenna, and the downlink is used for data transmission. The transmitted signal at the base station is:

_sk is the normalized information symbol, _sk belongs to s, s=[s ₁ ,...,s _K ], and

Indicates the information sent to the kth user. It is further satisfied that E( ^SSH )=I _K means that s satisfies the distribution law, and E means expectation. ω _k is the beamforming vector of the kth user, where ω _k is an element in ω,

Further, G1 represents the channel from the base station to the _lth IRS, and h _k1 represents the channel from the lth IRS to the kth user, wherein,

There are N _l reflective elements on the lth IRS (the reflective elements are the reflection array sources in FIG. 2 ). Further, the number of reflective elements of all IRSs is equal. For example, the value of l is 1, 2 or 10. When the integers are equal, the values of N ₁ , N ₂ and N ₁₀ are equal. Preferably, during simulation, N _l =256 or 64 can be set. In the embodiment of the present invention, reliable data transmission can be provided by adding multiple intelligent reflecting surfaces (IRS) to the millimeter wave communication system, because different intelligent reflecting surfaces in the system can be deployed geometrically separately, and at the same time, multiple intelligent reflecting surfaces It can provide multiple paths for receiving signals, which increases the strength of users' received signals. In addition, setting up multiple intelligent reflecting surfaces can effectively improve the confidentiality and energy efficiency of the millimeter-wave communication system, and realize green communication.

In step S200, a plurality of model parameters of the millimeter wave communication system model are acquired, and an energy efficiency maximization model of the millimeter wave communication system is established. The acquiring multiple model parameters of the millimeter-wave communication system model and establishing the energy efficiency maximization model of the millimeter-wave communication system includes determining the signal-to-interference-noise ratio of a single user, the sum rate of multiple users, and the power consumption of the millimeter-wave communication system . in,

The signal-to-interference-noise ratio of the single user is:

θ_ln∈[0,2π]，θ_ln为第l个IRS相移矩阵中第n个元素的相移角度，n∈[1,N_l]。x_l为IRS开关矢量，当x_l＝0时，第l个智能反射面不参与信号传输；当x_l＝1时，表明第l个智能反射面处于工作状态，K表示多个用户的总数量，k表示多个用户K中的第k个用户，l表示毫米波通信系统中多个智能反射面中的第l个智能反射面，N_l表示第l个智能反射面上反射元件的数量，M为基站的天线数量，G_l表示基站到第l个IRS的信道，h_kl表示从第l个IRS到第k个用户的信道，其中，

h_kl ^H表示h_kl的共轭转置矩阵。Among them, n _k additive white Gaussian noise, n _k ～CN(0,σ ² ) (n _k obeys Gaussian distribution), the effective phase shift matrix applied by IRS:

θ _ln ∈ [0,2π], θ _ln is the phase shift angle of the n-th element in the l-th IRS phase-shift matrix, n∈[1,N _l ]. x _l is the IRS switching vector, when x _l = 0, the l-th smart reflective surface does not participate in signal transmission; when x _l = 1, it indicates that the l-th smart reflective surface is in the working state, and K represents the total number of users Quantity, k represents the kth user among multiple users K, l represents the lth smart reflector among the multiple smart reflectors in the millimeter-wave communication system, N _l represents the number of reflective elements on the lth smart reflector , M is the number of antennas of the base station, G _l represents the channel from the base station to the lth IRS, h _kl represents the channel from the lth IRS to the kth user, where,

h _kl ^H represents the conjugate transpose matrix of h _kl .

In this embodiment, the transmission signal of the base station is a unit transmission signal.

Further, determining the sum rate of multiple users includes the following steps:

On the basis of obtaining the signal-to-interference-noise ratio of a single user, the sum rate of multiple users is determined by Shannon's theorem:

Among them, B is the bandwidth of all channels in the millimeter-wave communication system, that is, the bandwidths of G1 and h _k1 . In the embodiment of the present invention, the B is selected as a unit bandwidth and takes a value of ₁ , but is not limited to this, and B is taken as 4 and other other The value is also applicable in the embodiments of the present invention.

Further, the power consumption of the millimeter wave communication system is:

是ω_k的共轭转置矩阵，μ是基站功率放大器的效率，P_BS为基站硬件功耗，P_k为移动用户终端硬件功耗，P_IRS为智能反射面的硬件消耗功率。where ω _k is the beamforming vector of the kth user,

is the conjugate transpose matrix of ω _k , μ is the efficiency of the base station power amplifier, P _BS is the hardware power consumption of the base station, P _k is the hardware power consumption of the mobile user terminal, and P _IRS is the hardware power consumption of the intelligent reflector.

Therefore, based on the signal-to-interference-noise ratio of a single user, the sum rate of multiple users, and the power consumption of the millimeter-wave communication system, the energy efficiency maximization model of the millimeter-wave communication system is obtained as:

ω ^H ω≤P _max , (2.3)

θ _ln ∈[0,2π], (2.4)

x _l ∈{0,1}, (2.5)

波束形成矢量ω＝[ω₁,...,ω_K]，智能反射面开关矢量x＝[x₁,...,x_L]^T，其中，L指的是共有L个IRS，小写的l代表1～L中的某一个IRS，K代表的是有K个用户，R_k是第k个用户的最小速率，P_max是基站处的最大发送功率。where the phase shift vector

Beamforming vector ω=[ω ₁ ,...,ω _K ], intelligent reflective surface switch vector x=[x ₁ ,...,x _L ] ^T , where L refers to a total of L IRSs, in lowercase l represents an IRS from 1 to L, K represents that there are K users, R _k is the minimum rate of the k-th user, and P _max is the maximum transmit power at the base station.

Step S300, the energy efficiency maximization model of the millimeter wave communication system is decoupled into three sub-problems: phase optimization, beamforming optimization, and intelligent reflector switch optimization. Specifically, based on a given beamforming vector ω, intelligent reflector switch vector x and Two of the phase shift vectors θ decouple the energy efficiency maximization model of the millimeter-wave communication system into three sub-problems: phase optimization, beamforming optimization, and smart reflector switch optimization.

More specifically, the phase optimization sub-problem is specifically: given the beamforming vector ω and the IRS switching vector x, the total power consumption of the system is fixed, and maximizing the energy efficiency is equivalent to maximizing the sum rate. Therefore, given (ω,x), which decouples the energy efficiency maximization model of the mmWave communication system into a phase optimization sub-problem (that is, the sum rate maximization problem):

θ _ln ∈ [0,2π], (3.4)

Among them, γ is the relaxation vector introduced, γ=[γ ₁ ,...,γ _K ] ^T , that is, γ is a matrix composed of 1-k relaxation variables, γ _k is an element in γ; R _k is the kth The minimum rate of each user, ω _i is the beamforming vector of the interfering user i when the kth user communicates.

Given the phase shift vector θ and the IRS switch vector x, the beamforming optimization sub-problem is:

ω ^H ω≤P _max , (12.3)

Among them, ζ is the introduced slack variable, ζ=[ζ ₁ ,...,ζ _K ] ^T , that is, ζ is a matrix composed of 1-k slack variables, ζ _k is an element in ζ,

The intelligent reflective surface switching optimization sub-problem is a nonlinear integer optimization problem of the intelligent reflective surface switching vector x.

In this embodiment, the beamforming vector ω is the beamforming at the base station end, and the phase shift vector θ is the phase shift vector of all smart reflectors.

S400. Performing alternate iterative solutions on the three sub-problems of phase optimization, beamforming optimization, and intelligent reflector switch optimization, and obtaining a convergence result that maximizes the energy efficiency of the millimeter-wave communication system includes: using continuous convex approximation and Dinkelbach The method solves the beamforming optimization sub-problem and obtains the optimal beamforming. The non-convex problem of the phase optimization sub-problem is transformed into a convex problem by using the semi-definite relaxation and continuous convex approximation method to solve the phase optimization sub-problem, and the greedy method is used to solve the intelligent reflection. facet switch optimization problem.

In this embodiment, the non-convex problem of the phase optimization sub-problem is transformed into a convex problem by using the semi-definite relaxation and continuous convex approximation methods. Solving the phase optimization sub-problem includes the following steps:

其中，在

的辅助下，令

其中，

因此约束(3.2)可以表示为：make

Among them, in

with the help of

in,

So constraint (3.2) can be expressed as:

where t _ki =[t _kl1 ,...,t _klL ] ^T .

Based on constraint (4), the energy efficiency maximization model of mmWave communication system can be transformed into a phase optimization sub-problem and can be reformulated as:

To handle the non-convex constraint (5.2), using the penalty function method, the phase optimization subproblem can also be rewritten as:

Among them, C is a large positive constant. In order to solve the non-convex problem in the phase optimization sub-problem, using the SCA method (continuous convex approximation method), the objective function of (5.1) can be approximated as:

的一阶泰勒展开，上标(t-1)表示变量在第(t-1)次迭代时的值。为处理约束(4)的非凸性，引入松弛变量β_k，约束(4)等价于:Among them, the second part is

The first-order Taylor expansion of , where the superscript (t-1) represents the value of the variable at the (t-1)th iteration. To deal with the non-convexity of constraint (4), a slack variable β _k is introduced, and constraint (4) is equivalent to:

and

Where (9) is convex, and the non-convexity function of (8) still needs to be processed, the constraint (8) can be approximated by using the difference (DC) of two convex functions as:

在φ＝φ^(t-1)的一阶泰勒展开。where the left-hand side of the inequality is

First-order Taylor expansion at φ=φ ^(t-1) .

Using the above approximation, the nonconvex problem in (6.1)-(6.4) can be formulated as the following approximate convex problem:

_stβk ≥0, (11.2)

Wherein, in the same way, β=[β ₁ ,...,β _K ] ^T , and β _k is an element in the matrix.

Finally, continue to use the continuous convex approximation method to solve (11.1)-(11.5), that is, in the iterative process, the obtained value makes the energy efficiency problem converge, and the energy efficiency value tends to remain unchanged.

In this embodiment, the semidefinite relaxation refers to all methods for introducing relaxation variables.

In this embodiment, continuous convex approximation and Dinkelbach method are used to solve the beamforming optimization sub-problem, and obtaining the optimal beamforming includes the following steps:

A slack variable ρ _k > 0 is introduced, and constraint (12.2) is reformulated as:

都为实数，也就是

将

用泰勒一阶级数表示为：Suppose an arbitrary beamforming vector ω such that any

are real numbers, that is

Will

The Taylor first-order number is expressed as:

Using the above approximation, the nonconvex problem in (12.1))-(12.4) can be formulated as the following approximation problem:

stρ _k ≥0, (16.2)

ω ^H ω≤P _max , (16.5)

Finally, the Dinkelbach (0-1 bipartite programming better solution method) method is used to optimize and solve (16.1)-(16.6), and the optimal beamforming is obtained.

In this embodiment, the greedy method is used to solve the optimization problem of the intelligent reflective surface switch. Among them, the present invention adopts the greedy method to solve the IRS switch optimization problem, and the specific operation can be as follows: one IRS is turned off each time, and if the target value is improved, it proves that the new solution is feasible. Since the target value of the energy-efficiency maximization model for mmWave communication systems increases in each iteration, and the target value always has a finite upper bound, the algorithm must converge. Figure 3 shows the convergence of the algorithm as the number of iterative solutions increases.

In this embodiment, the parameter angle code in the formula is the conjugate transpose matrix of H representing the parameter itself.

Referring to FIG. 4 , an energy efficiency maximization system for a millimeter wave communication system that executes the above method is also introduced in an embodiment of the present invention, including a building module, a building module, a decoupling module, and a solving module, wherein the building module is used for Set up multiple smart reflectors in the millimeter-wave communication system to build a multi-input single-output millimeter-wave communication system model; build a module to obtain multiple model parameters of the millimeter-wave communication system model to maximize the energy efficiency of the millimeter-wave communication system model; the decoupling module is used to decouple the energy efficiency maximization model of the millimeter wave communication system into three sub-problems: phase optimization, beamforming optimization, and intelligent reflector switch optimization; the solving module is used for the phase optimization, beamforming optimization, The three sub-problems of intelligent reflector switch optimization are solved alternately and iteratively to obtain a convergence result that maximizes the energy efficiency of the millimeter-wave communication system.

The above-mentioned embodiments only represent several embodiments of the present invention, and the descriptions thereof are specific and detailed, but should not be construed as limiting the scope of the patent of the present invention. It should be pointed out that for those skilled in the art, without departing from the concept of the present invention, several modifications and improvements can be made, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

Claims (10)

1. A method for maximizing energy efficiency of a millimeter wave communication system is characterized by comprising the following steps:

setting a plurality of intelligent reflecting surfaces in a millimeter wave communication system, and constructing a multi-input single-output millimeter wave communication system model;

obtaining a plurality of model parameters of a millimeter wave communication system model, and establishing an energy efficiency maximization model of the millimeter wave communication system:

decoupling an energy efficiency maximization model of a millimeter wave communication system into three sub-problems of phase optimization, beam forming optimization and intelligent reflector switch optimization;

and performing alternate iterative solution on the three sub-problems of phase optimization, beam forming optimization and intelligent reflector switch optimization to obtain a convergence result which enables the energy efficiency of the millimeter wave communication system to be maximized.

2. The energy efficiency maximizing method of millimeter wave communication system according to claim 1, wherein the millimeter wave communication system model further comprises a base station, a plurality of intelligent reflector control switches, and a plurality of users, wherein,

and any intelligent reflecting surface control switch is closed, and the base station can respectively send the sending signal to each user in the plurality of users through the intelligent reflecting surface controlled by the intelligent reflecting surface control switch.

3. The energy efficiency maximizing method of the millimeter wave communication system according to claim 1, wherein the step of obtaining a plurality of model parameters of the millimeter wave communication system model and establishing the energy efficiency maximizing model of the millimeter wave communication system comprises the steps of:

the signal-to-interference-and-noise ratio of a single user, the sum rate of a plurality of users, and the power consumption of the millimeter wave communication system are determined.

4. The energy efficiency maximization method of a millimeter wave communication system according to claim 3, wherein the signal to interference and noise ratio of the single user is:

wherein n is_kAdditive white Gaussian noise, n_k～CN(0，σ²) The effective phase shift matrix applied by the intelligent reflecting surface:

θ_ln∈[0，2π]，x_lfor the intelligent reflector switching vector, when x_lWhen the number is 0, the first intelligent reflecting surface does not participate in signal transmission; when x is_lWhen the number is 1, the l intelligent reflecting surface is in an operating state, k represents the k user in the plurality of users, l represents the l intelligent reflecting surface in the plurality of intelligent reflecting surfaces in the millimeter wave communication system, and N_lIndicating the number of reflecting elements on the ith intelligent reflecting surface, ω_kIs the beamforming vector of the kth user, M is the number of antennas of the base station, G_lIndicating the channel from the base station to the first IRS, h_klRepresenting the channel from the ith intelligent reflecting surface to the kth user, wherein,

represents h_klThe conjugate transpose matrix of (2).

5. The energy efficiency maximizing method of the millimeter wave communication system according to claim 4, wherein the determining the sum rate of the plurality of users comprises the steps of:

the sum rate of multiple users is determined by shannon's theorem based on the signal-to-dryness ratio of a single user:

where B is the bandwidth of the channel in the millimeter wave communication system.

6. The energy efficiency maximizing method of the millimeter wave communication system according to claim 5, wherein the power consumption of the millimeter wave communication system is:

wherein, ω is_kIs the beamforming vector for the kth user, mu is the efficiency of the base station power amplifier, P_BSFor base station hardware power consumption, P_kFor mobile user terminal hardware power consumption, P_IRSPower is consumed for the hardware of the intelligent reflective surface.

7. The energy efficiency maximizing method of the millimeter wave communication system according to claim 6, wherein the energy efficiency maximizing model of the millimeter wave communication system is:

ω^Hω≤P_max， (2.3)

θ_ln∈[0，2π]， (2.4)

x_l∈{0，1}， (2.5)

wherein

ω＝[ω₁，...，ω_K]^T，x＝[x₁，...，x_L]^T，R_kIs the minimum rate, P, of the k-th user_maxIs the maximum transmit power at the base station.

8. The energy efficiency maximization method of a millimeter wave communication system according to claim 6, wherein the phase optimization sub-problem is:

θ_ln∈[0，2π]， (3.4)

where γ is the introduced relaxation vector, γ ═ γ₁，...，γ_K]^T，γ_kIs an element in γ;

the sub-problem of beam forming optimization is as follows:

ω^Hω≤P_max， (12.3)

where ζ is the relaxation variable introduced, and ζ ═ ζ₁，...，ζ_K]^T，ζ_kIs an element in the zeta-group,

the intelligent reflector switch optimization sub-problem is a nonlinear integer optimization problem of an intelligent reflector switch vector x.

9. The energy efficiency maximizing method of a millimeter wave communication system according to claim 1, wherein the performing alternate iterative solution on the three sub-problems of phase optimization, beam forming optimization and intelligent reflector switch optimization to obtain a convergence result that maximizes the energy efficiency of the millimeter wave communication system comprises:

solving a beam forming optimization sub-problem by adopting a continuous convex approximation method and a Dinkelbach method to obtain optimal beam forming;

converting the non-convex problem of the phase optimization sub-problem into a convex problem by adopting a semi-definite relaxation and continuous convex approximation method to solve the phase optimization sub-problem;

and solving the intelligent reflecting surface switch optimization problem by a greedy method.

10. An energy efficiency maximization system of a millimeter wave communication system, comprising,

the building module is used for setting a plurality of intelligent reflecting surfaces in the millimeter wave communication system and building a multi-input single-output millimeter wave communication system model;

the establishing module is used for acquiring a plurality of model parameters of the millimeter wave communication system model and establishing an energy efficiency maximization model of the millimeter wave communication system;

the decoupling module is used for decoupling the energy efficiency maximization model of the millimeter wave communication system into three sub-problems of phase optimization, beam forming optimization and intelligent reflector switch optimization; and

and the solving module is used for carrying out alternate iterative solution on the three subproblems of phase optimization, beam forming optimization and intelligent reflector switch optimization to obtain a convergence result which enables the energy efficiency of the millimeter wave communication system to be maximized.

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