WO2023020080A1

WO2023020080A1 - Wireless communication system assisted by intelligent reflecting surface

Info

Publication number: WO2023020080A1
Application number: PCT/CN2022/097839
Authority: WO
Inventors: 伍楷舜; 罗胜; 车越岭; 王晓桐; 山岩
Original assignee: 深圳大学
Priority date: 2021-08-18
Filing date: 2022-06-09
Publication date: 2023-02-23
Also published as: CN113726383A; CN113726383B

Abstract

Disclosed is a wireless communication system assisted by an intelligent reflecting surface. The system comprises an intelligent reflecting surface IRS, a hybrid access point H-AP and a user terminal, wherein the hybrid access point is provided with a plurality of antennas used for transmitting signals to a user, the intelligent reflecting surface is equipped with a plurality of reflective units, the reflective units are used to reflect and transmit the signals from the hybrid access point H-AP to the user, and the user terminal is provided with a plurality of wireless devices equipped with a single antenna so as to receive the signals transmitted from the hybrid access point H-AP or the intelligent reflecting surface. By means of constructing energy beamforming of the hybrid access point H-AP in a downlink phase, information receiving beamforming of the hybrid access point H-AP in an uplink phase, and a joint optimization problem of phase shift and time allocation of the intelligent reflecting surface during energy and information transmission, the uplink information transfer rate is maximized. The use of the present invention improves the throughput of a communication system, and the convergence speed of an algorithm optimization process is fast.

Description

A wireless communication system assisted by an intelligent reflective surface

technical field

The present invention relates to the technical field of wireless communication, and more particularly, to a wireless communication system assisted by an intelligent reflecting surface.

Background technique

In contemporary mobile communication technology, a large number of Internet devices are connected to wireless networks, so network design with high transmission rate and low delay has become one of the demands of the information age. At present, large-scale antenna technology such as multiple access multiple output or beamforming technology has been applied to the network to meet this requirement. However, these technologies cannot effectively deal with certain blocking or high path loss in the signal transmission path. However, the traditional repeater method increases the loss of the entire communication system due to the large demand for computing power.

With the development of metamaterials and hyperplanes, intelligent reflective surfaces (IRS) that configure wireless channels and can reflect signals in a controlled manner have become one of the better solutions to this problem. The smart reflective surface is a low-cost plane composed of multiple passive passive reflective elements, which can simultaneously reflect uplink and downlink signals. And because the smart reflective surface is lightweight, it can be easily integrated into the surface of a building or a moving object. At the same time, only the phase or amplitude of the smart reflector needs to be modulated to enable the receiving end to receive signals better and improve the communication quality.

In the prior art, the document "Optimized energy and information relaying in self-sustainable irs-empowered wpcn" (DOI: 10.1109/TCOMM.2020.3028875) proposes a H-AP (hybrid access point) containing a single antenna and multiple A wireless communication system for wireless devices with a single antenna. This paper proposes a scheme of time switching and power distribution, where the IRS can harvest energy from the signal of the H-AP by switching between energy harvesting and signal reflection in the TS scheme or adjusting its reflection amplitude in the PS.

The document "Intelligent reflecting surface assisted wireless powered communication networks" (DOI: 10.1109/WCNCW48565.2020.9124775) proposes a wireless communication system including a multi-antenna H-AP and multiple single-antenna wireless devices. Provide additional links by constructing beamforming between H-AP and wireless devices, and then maximize the transmission rate by optimizing the phase matrix of energy harvesting and information transmission.

In the current 5G era, thanks to many key technologies such as ultra-dense network (UDN), massive multiple-input multiple-output (MIMO), millimeter wave (mmWave), etc., the wireless connection of ultra-multiple devices has been realized, but in this In this network environment, problems such as high energy consumption and high complexity have not been fully resolved. In addition, due to the randomness and uncontrollability of signal propagation itself, in some cases, there may be certain blocking between the access point and the device. Based on the above reasons, an intelligent reflective surface (IRS) is used. By adjusting the phase and amplitude of the IRS components, the signal transmission can be actively adjusted, thereby opening up a new low-loss path for signal transmission to improve the performance of the wireless link. Existing methods of using source relay or backscatter communication to reduce wireless links have certain limitations compared with IRS. First of all, source relay usually works in half-duplex mode, while IRS does not use any transmitting module and can work in full-duplex mode, so source relay is not as good as IRS in terms of spectrum efficiency or technical cost. Secondly, compared with backscatter communication, IRS itself does not send any information of itself, and backscatter communication needs to eliminate interference at the receiving end to decode tags, so in the IRS-assisted communication environment, the direct path signal or reflection All path signals can carry the same useful information, which can coherently enhance the decoding signal strength at the receiving end. However, in the case of high loss or blockage in the path between the H-AP and the wireless device, the performance of the wireless communication network assisted by the smart reflector still needs to be improved.

Contents of the invention

The purpose of the present invention is to overcome the defects of the above-mentioned prior art, and provide a wireless communication system assisted by an intelligent reflective surface, which includes an intelligent reflective surface IRS, a hybrid access point H-AP and a user terminal, wherein the hybrid access point is set N _T antennas are used to transmit signals to users. The intelligent reflector is equipped with M reflection units, and the reflection units are used to reflect and transmit the signal from the hybrid access point H-AP to the user. The user end is set to K with a single antenna. Wireless devices to receive signals transmitted from hybrid access points H-AP or smart reflectors;

Among them, the energy beamforming of the hybrid access point H-AP in the downlink phase, the information receiving beamforming of the hybrid access point H-AP in the uplink phase, and the phase shift and time allocation of the energy and information transmission of the intelligent reflector are constructed. Joint optimization problem P1 to maximize the uplink information transmission rate, the joint optimization problem is expressed as:

Among them, τ ₀ is the downlink time for energy transmission, τ ₁ = T-τ ₀ is the uplink time for information transmission, T is the sum of the time lengths, Θ ^D and Θ ^U respectively represent the smart reflective surface in Diagonal reflection coefficient matrices for downlink and uplink, for '#'∈[D,U],m∈{1,M},

Indicates the reflection angle and phase shift of the mth reflection unit of the smart reflection surface,

Represents the energy beamforming vector, the hybrid access point H-AP uses receive beamforming W=[w ₁ ,…,w _K ] ^H ,

‖w _i ‖=1 to receive information, γ _i represents the signal-to-interference-plus-noise ratio when the i-th wireless device at the user end transmits information to the hybrid access point H-AP during the uplink period, U represents uplink, and D represents downlink , (1) in the constraints represents the formula τ ₀ +τ ₁ =T.

Compared with the prior art, the present invention has the advantage that, in view of the relatively high loss or blockage in the path between the H-AP and the wireless device, by constructing a joint optimization problem, an intelligent reflective surface with a relatively small path loss is selected to be used To transmit signals or information to maximize the transmission rate of information, thereby improving the performance of the communication system.

Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention.

Fig. 1 is a schematic diagram of a wireless communication system model assisted by an intelligent reflector according to an embodiment of the present invention;

Fig. 2 is a schematic diagram of the throughput performance of multi-wireless devices as the transmission power changes according to an embodiment of the present invention;

Fig. 3 is a schematic diagram of the throughput performance of multiple wireless devices as the number of smart reflective surface elements changes according to an embodiment of the present invention;

Fig. 4 is a schematic diagram of the throughput performance of multi-wireless devices as the distance from the smart reflective surface to the H-AP changes according to an embodiment of the present invention;

Fig. 5 is a schematic diagram of an optional communication system according to an embodiment of the present invention;

In the attached figure, Transmit Power-transmission power; Throughput-throughput; Wireless Link-wireless link; Wired Link-wired link; IRS Controller-IRS controller; WET-wireless energy transmission; WIT-wireless information transmission; Propose Scheme -the present invention scheme; Benchmark scheme I-baseline scheme 1; Benchmark scheme II-baseline scheme 2; Benchmark scheme III-baseline scheme 3; effective link-effective channel; Number of IRS elements-IRS component quantity; Distance of IRS from H- Distance between AP-IRS and H-AP.

Detailed ways

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangements of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and in no way taken as limiting the invention, its application or uses.

Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.

In all examples shown and discussed herein, any specific values should be construed as exemplary only, and not as limitations. Therefore, other instances of the exemplary embodiment may have different values.

It should be noted that like numerals and letters denote like items in the following figures, therefore, once an item is defined in one figure, it does not require further discussion in subsequent figures.

The scenario of the present invention is a wireless communication network with an intelligent reflector that contains multiple single-antenna wireless devices and a multi-antenna hybrid access point (H-AP, Hybrid access point), where the wireless devices will Harvesting energy from the H-AP via wireless signals, and then using the received energy to send information to the H-AP in the uplink phase. In the following description, first define the matrix or vector between the receiving end and the transmitting end according to the system model, and use mathematical formulas to describe the signal and energy; then increase the information transmission rate and system throughput in the entire system as the optimization goal , define the joint optimization problem; and then determine the parameters that meet the optimization goal by solving the joint optimization problem.

1), system model

Referring to Fig. 1, the provided wireless communication system based on the intelligent reflector includes a hybrid access point (H-AP), an intelligent reflector (IRS) and a user terminal, wherein the H-AP is equipped with _NT antennas to utilize The antenna transmits the signal to the user; the smart reflector is equipped with M reflection units to use the reflection unit to reflect and transmit the signal from the H-AP to the user; the user end contains K wireless devices equipped with a single antenna to receive the signal from the H-AP Or the signal transmitted by the smart reflective surface, wherein _NT , M and K are all integers greater than or equal to 2.

In one embodiment, for the provided wireless communication system, consider a time frame whose length sum is 1 (or uniformly denoted as T), wherein the downlink time for energy transmission is set as τ ₀ , The uplink time for information transmission is set as τ ₁ =T−τ ₀ , which can be expressed as τ ₀ +τ ₁ =T=1.

For the wireless communication system in Figure 1, P is the transmission power of the signal,

Indicates the channel vector from the H-AP directly to the i-th user,

represents the channel vector from the smart reflector directly to the i-th user,

Represents the channel matrix from the H-AP to the smart reflector, relative

Indicates the channel vector from the i-th user to the H-AP,

Indicates the channel vector from the i-th user to the smart reflector,

Indicates the channel matrix from the smart reflector to the H-AP. At the same time, the channel is considered to be reciprocal, so there is

Z=Z ^D ＝Z ^U , the diagonal reflection coefficient matrices of the smart reflector in the downlink and uplink are Θ ^D and Θ ^U respectively, that is to say, for ′#′∈[D,U],m∈{ 1,M},

in

Indicates the reflection coefficient of the mth reflection unit,

Represents the reflection angle and phase shift of the mth reflection unit, so it can be obtained

The superscript H represents the conjugate transpose, the superscript T represents the transpose, the scalar x ^b represents the energy signal sent by the H-AP to the user,

Represents the energy beamforming vector and satisfies ‖f‖=1, so the size of the signal received by the i-th user is:

in

is complex Gaussian noise, σ is the variance of Gaussian noise,

is the effective channel acquisition amount between the H-AP and the smart reflector.

Let q _i denote the energy harvested by the i-th user during the downlink, which can be expressed as:

where η≤1 represents the efficiency of energy harvesting.

During the uplink phase, the i-th device sends an information scalar

to the H-AP, the H-AP uses receive beamforming W=[w ₁ ,…,w _K ] ^H ,

‖w _i ‖=1 to receive information, the signal size received by H-AP is:

in,

is the additive white Gaussian noise at the H-AP,

is the effective channel acquisition amount between the H-AP and the i-th wireless device, n _AP is the additive white Gaussian noise at the H-AP, and obeys the distribution

The signal-to-interference plus noise ratio when the i-th wireless device transmits information to the H-AP during the uplink is:

2), define the optimization problem

In the embodiment of the present invention, aiming at maximizing the achievable uplink information transmission rate, through the H-AP energy beamforming in the downlink phase, the H-AP information receiving beamforming in the uplink phase, and the smart reflector combining energy and information The joint optimization of the problem is carried out on the four parameters of transmission phase shift and time allocation. Express the joint optimization problem as:

Wherein, (1) in the constraint condition represents the formula τ ₀ +τ ₁ =T. Due to the coupling of variables in the problem, it is difficult to solve the problem, and the problem itself is non-convex, so in the following embodiments, it is preferable to consider the individual optimization of the optimization variables, and then use alternative optimization to obtain a joint solution.

3) Obtain optimized parameters with the goal of maximizing throughput

① First optimize the energy and information transmission time distribution of the intelligent reflective surface.

Assuming that the other three of the four parameters are known, assume

The optimal time distribution τ ₁ can be obtained by solving the following relaxation problem.

Because problem P1.1 is a convex optimization problem for {τ ₀ ,τ ₁ }, it can be solved using a standard convex optimization solution, such as CVX, using the Lagrange function form of problem P1.1 and KKT as condition, you can get:

Equation (7) proves that the optimal τ ₀ exists.

② Optimize the beamforming of the received information of H-AP.

At this point, considering that the other three parameters are known, it is also assumed that

so

Therefore, the optimal W value can be obtained by solving the following relaxation problem:

For problem P1.2, the optimal information receiving beamforming at the H-AP end can be obtained through Proposition 3.1, and the maximum eigenvalue of the Rayleigh quotient γ _i (w _i ) can be proved at the same time. According to Theorem 3.2, in problem P1.2 The largest eigenvalue of γ _i (w _i ) is a convex function of w _i for the pair of symmetric matrices {C _i , D _i }.

Proposition 3.1: The optimal information receiving beamforming at the optimal H-AP side is

i∈[1,K], where φ _i represents the corresponding eigenvector of the largest eigenvalue λ _i of the Rayleigh quotient γ _i (w _i ).

Proof: Take the gradient of problem P1.2 about w _i and make it 0, get:

Simplify the above formula to get the result:

For any matrix C, let Φ _C ＝[φ ₁ ,…,φ _K ], Λ _C ＝diag[λ ₁ ,…,λ _K ] are eigenvectors and eigenmatrices, so there are:

CΦ _C ＝Φ _C Λ _C or Λ _C ＝Φ _C ^T CΦ _C (11)

Similarly, for matrix D, there are Φ _D , Λ _D is the eigenvector and eigenmatrix, so:

DΦ _D ＝Φ _D Λ _D or Λ _D ＝Φ _D ^T DΦ _D (12)

Assume that for matrix C, Φ _D , Λ _D are eigenvectors and eigenvalues, which means that Φ _D , Λ _D are generalized eigenvectors and eigenvalues of the matrix set {C, D}, so the following equations must be satisfied:

CΦ _D ＝Φ _D Λ _D or Λ _D ＝Φ _D ^T CΦ _D (13)

Multiply the left and right sides of Λ _D in the above formula by Λ _D ^-1/2 , there is:

Λ _D ^-1/2 Φ _D ^T CΦ _D Λ _D ^-1/2 = Λ _D ^-1/2 Λ _D Λ _D ^-1/2 = I (14)

It can be noticed that C′=Λ _D ^-1/2 Φ _D ^T CΦ _D Λ _D ^-1/2 is a symmetric matrix, and then according to the definition of eigenvalues and eigenvectors, there are:

C′Φ _C ＝Φ _C Λ _C orΛ _C ＝Φ _C ^T C′Φ _C (15)

Substitute C' in Λ _C into:

Λ _C ＝Φ _C ^T Λ _D ^-1/2 Φ _D ^T CΦ _D Λ _D ^-1/2 Φ _C ＝Φ ^T CΦ, where Φ＝Φ _D Λ _D ^-1/2 Φ _C (16)

Check the diagonalization ability of D using Φ as the result:

Φ ^-1 DΦ＝Φ ^T DΦ＝Φ _C ^T Λ _D ^-1/2 Φ _D ^T DΦ _D Λ _D ^-1/2 Φ _C (17)

The above formula can be rewritten as:

Φ ^T DΦ＝Φ _C ^T Λ _D ^-1/2 Λ _D Λ _D ^-1/2 Φ _C (18)

Simplify the above formula to Φ ^T DΦ=I, multiply the right side of the above formula by Λ _C , then it is equivalent to

ΛC＝Φ _C ^T Λ _D ^-1/2 Φ _D ^T CΦ _D Λ _D ^-1/2 ＝Φ ^T CΦ, where Φ＝Φ _D Λ _D ^-1/2 Φ _C

get:

CΦ＝ _DΦΛC (19)

The vector form equation of the above formula is:

C _i φ _i ＝ D _i φ _i λ _i (20)

Compare the previous formula

and C _i φ _i ＝ D _i φ _i λ _i , get

As the eigenvector φ _i , γ _i (w _i ) acts as the eigenvalue λ _i corresponding to the eigenvector φ _i , so, for problem P1.2, the optimal w _i ,i∈{1,K} is

Theorem 3.2: The largest eigenvalue of γ _i (w _i ) in problem P1.2 is a convex function about w _i for the symmetric matrix pair {C _i , D _i }.

Proof: order

is the eigenvalue of (N _T ×N _T ×K) matrix C _i , so C _i w _i =w _i λ _i . In addition,

this means

An equation similar to the above can also be written for the matrix D _i .

Now for the order N _T ×N _T ×K and 0≤α≤1, we can get:

Therefore the largest eigenvalue of the symmetric matrix pair {C _i ,D _i }

is a convex function for w _i .

③Optimize the transmit beamforming of H-AP.

Considering that the other three parameters are known at this time, the optimal transmit beamforming f can be obtained by solving the following relaxation problem:

Let us suppose

So now problem P1.3 is modified as follows:

In P1.3.1, the Rayleigh quotient has k product terms, and for the symmetric matrices E and G _i in P1.3.1, if ψ _i (w _i ,Θ ^# ,τ _i ) is corresponding to the largest eigenvalue ζ _i (w _i ,Θ ^# ,τ _i ), so according to the previous inference, when f(w _i ,Θ ^# ,τ _i )=ψ _i (w _i ,Θ ^# ,τ _i ), the The i Rayleigh quotients γ _i (f) are maximized to ζ _i (w _i ,Θ ^# ,τ _i ). Doing some calculations from the above formulas, we can know that the largest eigenvalue of the symmetric matrix pair {E, G _i } is a convex function about f. In order to know the optimal transmit beamformer f, the solution of k Rayleigh quotient needs to be optimized together, we assume cosδ _i =f ^H ψ _i (w _i ,Θ ^# ,τ _i ),

Then f of the i-th term is given by ζ _i (w _i ,Θ ^# ,τ _i )cosδ _i , problem P1.3.1 is now rewritten as problem P1.3.2, and the problem can be solved using Proposition 3.2.

Proposition 3.2: When δ ₁ =...δ _K ,

The maximum value appears. then the best

Here, the vector a=[1,…,1,0,…,0] ^T ,

Vector a contains K 1s and N _T -K 0s. ψ _i ,i∈[1,K] represents the solution of the i-th Rayleigh quotient,

Represents the basis vectors that are spatially orthogonal to the K vectors ψ _i .

Proof: Refer to the proof of Theorem 1 in "Throughput maximization for multiuser mimo wireless powered communication networks" (DOI: 10.1109/TVT.2015.2453206).

④Optimize the phase shift of the smart reflector.

At this time, it is considered that f, W and τ _i are known variables, and then the optimal Θ ^# can be obtained by solving the following equation.

For simplicity, assume

Then

So the effective channel

in

If there is no direct link connection between the H-AP and the wireless device (that is, when there is only a smart reflector),

When optimizing the phase shift of the uplink smart reflector, it is considered that the parameters involved in the phase shift conversion of the uplink smart reflector are constant, and vice versa. Therefore, when problem P1.4 optimizes the phase shift of the smart reflector in the uplink and downlink, the signal-to-interference-plus-noise ratio becomes as follows:

assumptions:

Now for the new problem P1.4.1, the objective function of problem P1.4 is modified as:

For problem P1.4.1, namely

For the symmetric matrices H and L _i in , if

is corresponding to the largest eigenvalue

eigenvectors of . According to Proposition 3.1, when

, the i-th Rayleigh quotient

is maximized as

According to Theorem 3.2, it can be known that the symmetric matrix pair {H ^# , L _i ^# } is about

Convex function of , so in solving about

In the case of problem P1.4.1, because there are k Rayleigh quotient items, k

solution. First, set the

normalized to

Thus [x] _(2:M+1) means a vector of M elements in x excluding the first element. in the right

After normalization, k solutions need to be optimized together to obtain the only optimal

When there is only a smart reflector between the H-AP and the wireless device, that is

then there is no need to

Perform normalization, then use k solutions to optimize together to obtain the only optimal

In order to obtain the only optimal

suppose

in

So the i item's

for

At this point problem P1.4.1 is rewritten as follows:

This problem can be solved using Corollary Proposition 3.2, assuming the optimal

Here vector a=[1,…,1,0,…,0] ^T ,

Vector a includes k 1s and MK 0s, i∈[1,K], representing the solution of the i-th Rayleigh quotient,

Represents and k vectors

Space-orthogonal basis vectors can be obtained by

Obtain the optimal Θ ^# ,

4) Joint solution using alternative optimization

In the above embodiments, the main problem is decomposed into multiple sub-problems, and then a solution is provided for the sub-problems. Now provide a joint solution to the main problem. The optimization order of the parameters is τ _i → W → f → Θ ^D → Θ ^U . After optimizing the sub-problems, it is found that the objective function of the main problem P1 is finite and non-decreasing. The following Algorithm 1 gives the steps. At the same time, it is also found that because Algorithm 1 has the characteristics of low complexity, the problem P1 will reach the optimal solution within several convergences (such as 2-3 times).

5) For the case of configuring ZFRB and MRT for H-AP

First assume that ZFRB (zero-forcing receive beamforming) is configured at the H-AP.

In this section, a suboptimal solution to the proposed system has been obtained due to the above. Therefore, W is known, and f, _τi , and Θ ^# are optimized as above, but when using ZFRB, the equations are simplified as described below.

When using ZFRB, the interference is 0, so

at the same time

So problem P1 is reduced to:

So the optimal _τ1 in problem P1.1 is simplified to the following formula:

The optimization problem of parameter τ ₁ is a convex optimization problem, so the existence of the optimal value of parameter τ ₁ can be easily proved by using the Lagrangian form of the problem and KKT conditions.

When optimizing transmit beamforming, it is assumed that

So problem P1.3.1 is reduced to:

In the optimization problem P1.4.1 the

hour,

Problem P1.4.1 is simplified to:

So now an alternative optimization of the parameters can be used to obtain the joint solution.

Next, assume that MRT ((maximum-ratio-transmission, maximum ratio transmission) is configured on the H-AP.

Since a suboptimal solution has been obtained above, f is known, and W, τ _i , Θ ^# are optimized according to the above method. Based on the link of the smart reflector and the effective link between the H-AP and the wireless device, two different MRTs are assumed. In the MRT of the smart reflector, the search direction of the H-AP is

In the MRT of the active link, the search direction of the H-AP is

The transmit beamforming f of each MRT becomes that of the previous search direction

times. Problem P1.3.1 is thus simplified, and then an optimal solution can be obtained by Proposition 3.2 by substituting ψ _i for the corresponding transmit beamformer.

In order to further verify the effect of the present invention, experiments are carried out, and MATLAB platform or other computing platforms can be used for simulation to verify the throughput of the system. Specifically, it is assumed that the H-AP located at (0m, 0m) has 5 antennas. The H-AP serves 3 wireless devices with a single antenna, and the wireless devices are randomly distributed in a circle with a radius of 10m at a distance of (200m, 10m) from the H-AP. The smart reflector with 100 elements is at a distance of H-AP(200m, 0m). In practical applications, it is found that the amplitude of the reflected signal of the smart reflector is related to the phase shift. For simplicity, this application does not consider the phase shift of the elements, and considers the reflection coefficients of the smart reflective surfaces to be the same. In addition, unless otherwise specified, it is assumed that the transmit power of the H-AP is P=25dBm.

In the experiment, the following benchmark schemes were compared:

Solution 1: A smart reflector is configured in the system, and the components of the smart reflector have random phase shifts, and a direct link between the H-AP and the wireless device is also available.

Scenario 2: The system is not equipped with a smart reflector, so it can only use the direct link connection between the H-AP and the wireless device to transmit the signal.

Solution 3: There is no direct link connection between the H-AP of the system and the wireless device, so the intelligent reflective surface can only be used to transmit signals.

FIG. 2 is a schematic diagram of the relationship between the transmission power variation and the throughput of a multi-radio device. It can be seen that as the transmit power at the H-AP increases, the signal received at the wireless device gradually increases, which allows the wireless device to obtain more energy to send information, so for all solutions, the system throughput The amount increases as the transmit power of the H-AP increases. But the throughput of solution 2 is relatively low, because the signal transmission is completed through the direct link with high path loss. For solution 1, although the components of the smart reflector adopt random phase shifts, since both the smart reflector and the direct link between the H-AP and the wireless device can be used for signal transmission, the throughput of solution 1 Performance is better than option 2. For solution 3, because the smart reflector element of solution 3 adopts the best phase shift, the throughput performance of solution 3 is better than that of

solutions

1 and 2. Furthermore, Fig. 2 also shows that when applying MRT and ZFRB at the H-AP, two suboptimal solutions with low complexity are obtained for the proposed system. It can be noticed that the MRT based on the effective channel has a slightly better throughput performance than the MRT based on the smart reflector. As the transmit power increases, the ZFRB performance degrades due to the simpler direction design of the receive beamforming.

Figure 3 is a schematic diagram of the relationship between the number of smart reflector components and the throughput of multiple wireless devices. The throughput during the period when the wireless device sends information to the H-AP in the wireless energy transmission network with the smart reflector is analyzed. It can be seen that with the increase of smart reflector elements, the throughput of the three schemes has a certain increase, because increasing the number of smart reflector elements can increase the received power of the wireless device within a given time. Therefore, the spectrum efficiency and energy collection efficiency of the system can be improved by increasing the components of the smart reflector.

Figure 4 analyzes the impact of the distance between the smart reflector and the H-AP on the system performance, reflecting the change in system performance when the distance between the smart reflector and the H-AP changes from 50m to 200m. It can be seen that the performance of all schemes improves when the smart reflective surface is brought closer to the wireless device.

From Figures 2 to 4, it can be seen that under various circumstances such as changes in H-AP transmission power, changes in the number of smart reflector components, and changes in the distance between the smart reflector and the H-AP, the solution provided by the present invention is relatively The existing technologies all improve the system throughput.

It should be understood that those skilled in the art can make appropriate changes or modifications to the above-mentioned embodiments without departing from the spirit and scope of the present invention. For example, the system model can be optimized, such as changing the hybrid access point H-AP in the system to separate and independent energy sending station and information receiving station, as shown in Figure 5, when using this communication model, the wireless device transmits from the energy The station receives energy and then sends information to the information receiving station. At this time, because the radio energy sent by the energy sending station may be lost on the path, multiple energy sending stations can be set to increase the energy received by the wireless device. As another example, other solution methods may be used to obtain the solution of the constructed joint optimization problem.

To sum up, the wireless communication system with IRS in the prior art is based on TDMA, which means that the wireless device will be allocated time slots to transmit information during the uplink phase, but in the communication system of this application, the wireless device simultaneously Sending information, so the information transmission rate and throughput are better than the existing schemes. At the same time, the present invention uses multi-antenna H-AP, so the signal strength received by the wireless device is higher than that of the single-antenna H-AP. In the optimization process, because the present invention sets the receiving beamformer at the H-AP, the received signal strength at the H-AP of the present invention is also relatively high. Furthermore, because the invention optimizes the phase shift, the signal-to-interference-plus-noise ratio can be kept relatively low. As far as the optimization algorithm is concerned, since the main problem of the present invention can use the proposed algorithm to complete convergence within a few steps, it has the advantage of fast convergence speed and can maximize system throughput.

The present invention can be a system, method and/or computer program product. A computer program product may include a computer readable storage medium having computer readable program instructions thereon for causing a processor to implement various aspects of the present invention.

A computer readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory), static random access memory (SRAM), compact disc read only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded device, such as a printer with instructions stored thereon A hole card or a raised structure in a groove, and any suitable combination of the above. As used herein, computer-readable storage media are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., pulses of light through fiber optic cables), or transmitted electrical signals.

Computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or downloaded to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or a network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .

Computer program instructions for carrying out operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or Source or object code written in any combination, including object-oriented programming languages—such as Smalltalk, C++, Python, etc., and conventional procedural programming languages—such as the “C” language or similar programming languages. Computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server implement. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as via the Internet using an Internet service provider). connect). In some embodiments, an electronic circuit, such as a programmable logic circuit, field programmable gate array (FPGA), or programmable logic array (PLA), can be customized by utilizing state information of computer-readable program instructions, which can Various aspects of the invention are implemented by executing computer readable program instructions.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It should be understood that each block of the flowcharts and/or block diagrams, and combinations of blocks in the flowcharts and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that when executed by the processor of the computer or other programmable data processing apparatus , producing an apparatus for realizing the functions/actions specified in one or more blocks in the flowchart and/or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause computers, programmable data processing devices and/or other devices to work in a specific way, so that the computer-readable medium storing instructions includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks in flowcharts and/or block diagrams.

It is also possible to load computer-readable program instructions into a computer, other programmable data processing device, or other equipment, so that a series of operational steps are performed on the computer, other programmable data processing device, or other equipment to produce a computer-implemented process , so that instructions executed on computers, other programmable data processing devices, or other devices implement the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, a portion of a program segment, or an instruction that includes one or more Executable instructions. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified function or action , or may be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by means of hardware, implementation by means of software, and implementation by a combination of software and hardware are all equivalent.

Having described various embodiments of the present invention, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principle of each embodiment, practical application or technical improvement in the market, or to enable other ordinary skilled in the art to understand each embodiment disclosed herein. The scope of the invention is defined by the appended claims.

Claims

A wireless communication system assisted by an intelligent reflective surface, including an intelligent reflective surface IRS, a hybrid access point H-AP, and a user terminal, wherein the hybrid access point is provided with NT root antennas for transmitting signals to users, and the intelligent reflective surface is equipped with M reflection units, using the reflection unit to reflect and transmit the signal from the hybrid access point H-AP to the user, the user end is set to K wireless devices equipped with a single antenna to receive signals from the hybrid access point H-AP or intelligent reflection The signal transmitted by the surface;

Among them, the energy beamforming of the hybrid access point H-AP in the downlink phase, the information receiving beamforming of the hybrid access point H-AP in the uplink phase, and the phase shift and time allocation of the energy and information transmission of the intelligent reflector are constructed. Joint optimization problem P1 to maximize the uplink information transmission rate, the joint optimization problem is expressed as:

st(1), ||f||=1,

||w i ||=1, and

Among them, τ 0 is the downlink time for energy transmission, τ 1 = T-τ 0 is the uplink time for information transmission, T is the sum of the time lengths, Θ D and Θ U respectively represent the smart reflective surface in Diagonal reflection coefficient matrices for downlink and uplink, for '#'∈[D,U],m∈{1,M},

κ m ∈ (0,1],
Indicates the reflection angle and phase shift of the mth reflection unit of the smart reflection surface,
Represents the energy beamforming vector, the hybrid access point H-AP uses receive beamforming W=[w 1 ,…,w K ] H ,
‖w i ‖=1 to receive information, γ i represents the signal-to-interference-plus-noise ratio when the i-th wireless device at the user end transmits information to the hybrid access point H-AP during the uplink period, U represents uplink, and D represents downlink , (1) in the constraints means τ 0 +τ 1 =T.
The wireless communication system according to claim 1, wherein the joint optimization problem is solved according to the following steps:

Solve the following relaxation problem P1.1 to obtain the optimal time allocation τ 1 for the energy and information transmission of the smart reflector:

s.t.(1).

Solve the following relaxation problem P1.2 to obtain the optimal W value of the beamforming of the received information of the hybrid access point H-AP:

st||w i ||＝1.

The optimal f for the transmit beamforming of the hybrid access point H-AP is obtained by solving the following relaxation problem P1.3:

s.t.||f||＝1

The optimal transformation of the phase shift parameter Θ # of the smart reflector is:

in

is the effective channel acquisition amount between the hybrid access point H-AP and the smart reflector,
Indicates the channel vector from the hybrid access point H-AP directly to the i-th user,
represents the channel vector from the smart reflector directly to the i-th user,
Indicates the channel matrix from the hybrid access point H-AP to the smart reflector,
Indicates the channel vector from the i-th user to the hybrid access point H-AP,
Indicates the channel vector from the i-th user to the smart reflector,
Indicates the channel matrix from the smart reflector to the H-AP, and has

Z = Z D = Z U .
The wireless communication system according to claim 3, wherein the problem P1.3 is further expressed as a problem P1.3.1:

s.t.||f||＝1.

in,

P represents the transmission power of the hybrid access point H-AP, the Rayleigh quotient has k product terms, and for the symmetric matrix E and G i , if ψ i (w i ,Θ # ,τ i ) is corresponding to the largest eigenvalue ζ i (w i ,Θ # ,τ i ), we know that when f(w i ,Θ # ,τ i )=ψ i (w i ,Θ # ,τ i ), the i-th Rayleigh quotient γ i (f) is maximized to ζ i (w i ,Θ # ,τ i ).
The wireless communication system according to claim 3, characterized in that the problem P1.3.1 is transformed into a problem P1.3.2 expressed as:

Solve according to the following proposition:

When δ 1 =…=δ K ,
The maximum value appears, then the optimal
where the vector a=[1,…,1,0,…,0] T ,
Vector a contains K 1s and N T -K 0s, ψ i , i∈[1,K] represents the solution of the i-th Rayleigh quotient,
Represents the basis vectors that are spatially orthogonal to the K vectors ψ i .
The wireless communication system according to claim 4, characterized in that problem P1.4 is transformed into:

Among them, assuming the optimal
vector a[1,…,1,0,…,0] T ,
Vector a includes k 1s and MK 0s, i∈[1,K], representing the solution of the i-th Rayleigh quotient,
Represents and k vectors
Space-orthogonal basis vectors, via
To obtain the optimal θ # ,
The wireless communication system according to claim 2, wherein, in the case where ZFRB is configured at the hybrid access point H-AP, problem P1.1 is simplified as:

s.t.(1), ||f||=1, and
The wireless communication system according to claim 3, wherein, when the MRT is configured at the hybrid access point H-AP, in the MRT of the intelligent reflector, the search direction of the hybrid access point H-AP is
In the MRT of the active link, the search direction of the hybrid access point H-AP is
The wireless communication system according to claim 2, wherein the signal-to-interference plus noise ratio when the i-th wireless device transmits information to the hybrid access point H-AP during the uplink period is expressed as:
A computer-readable storage medium, on which a computer program is stored, wherein, when the program is executed by a processor, the following steps are implemented:

For the intelligent reflector-assisted wireless communication system according to any one of claims 1 to 8, by constructing the energy beamforming of the hybrid access point H-AP in the downlink phase, the energy beamforming of the hybrid access point H-AP in the uplink phase The joint optimization problem P1 of information receiving beamforming, phase shift and time allocation of energy and information transmission of intelligent reflectors to maximize the uplink information transmission rate, the joint optimization problem is expressed as:

st(1), ||f||=1,

||w i ||=1, and

Among them, τ 0 is the downlink time for energy transmission, τ 1 = T-τ 0 is the uplink time for information transmission, T is the sum of the time lengths, Θ D and Θ U respectively represent the smart reflective surface in Diagonal reflection coefficient matrices for downlink and uplink, for '#'∈[D,U],m∈{1,M},

κ m ∈ (0,1],
Indicates the reflection angle and phase shift of the mth reflection unit of the smart reflection surface,
Represents the energy beamforming vector, the hybrid access point H-AP uses receive beamforming W=[w 1 ,…,w K ] H ,
‖w i ‖=1 to receive information, γ i represents the signal-to-interference-plus-noise ratio when the i-th wireless device at the user end transmits information to the hybrid access point H-AP during the uplink period, U represents uplink, and D represents downlink .