A dual-RIS deployment position optimization method for multi-user communication, a terminal and a medium

Abstract

The application aims to provide a dual-RIS arrangement position optimization method, terminal and medium for multi-user communication, belonging to the technical field of wireless communication, according to the channel state information among a base station, a reconfigurable intelligent surface (RIS) and each user, a RIS cascaded channel from the base station B to each user is constructed, and a closed-form expression of the equivalent channel gain mean from the base station to each user is derived; so that the optimization target is to maximize the equivalent channel gain mean from the base station B to the worst user, and the arrangement position optimization problem of the dual-RIS is established with the feasible arrangement area range of the dual-RIS and the ordered reflection of the RIS as the constraint conditions; a two-layer search method is adopted to solve the optimization problem, and the optimal arrangement position of each RIS is obtained. The application maximizes the equivalent channel gain mean of the worst user by optimizing the position configuration of the dual-RIS in the multi-user communication system, significantly improves the wireless communication quality, and obtains the optimal arrangement scheme based on the two-layer search algorithm of the actual scene constraint, and simulation verification shows that the application is superior to the traditional arrangement method.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a dual RIS deployment location optimization method, terminal, and medium for multi-user communication. Background Technology

[0002] In recent years, Reconfigurable Intelligence Surfaces (RIS), as a new technology in wireless communication, have attracted widespread attention from academia and industry due to their advantages such as low power consumption and low cost. Because of their excellent performance, they are considered one of the key technologies for future 6G communication. RIS, also known as Intelligent Reflecting Surface (IRS), is an electromagnetic surface composed of a large number of low-cost passive reflective elements. Each reflective unit on the surface can independently change the phase shift or amplitude of the incident signal, thereby achieving intelligent reconfiguration of the wireless channel and improving wireless communication performance. Current applications of RIS mainly consider using single-hop RIS to assist and improve the performance of direct links. Research shows that, with the same number of reflective elements, using dual RIS can further improve the performance of wireless communication systems compared to a single RIS. This is because the collaborative work of two RIS can further improve the quality of transmitted signals and signal coverage. In practical scenarios, it can be used to improve the signal coverage of base station B and the quality of signals received by users, solving the problem of poor user communication quality in environments with dense obstructions. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a dual RIS deployment location optimization method, terminal and medium for multi-user communication. It aims to deploy RIS in the top area of ​​high-rise buildings in complex urban building complexes with many obstacles in real-world environments. By deploying two RIS, a dual RIS cascade link is established between base station B and the user. The optimal location is selected within the RIS deployment area to maximize the average channel gain from base station B to the worst user.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] In a first aspect, the present invention provides a dual RIS deployment location optimization method for multi-user communication, comprising: based on the distance from base station B to R1, from R1 to R2, and from R2 to each user U... k Channel state information is used to construct the connection between base station B and each user U. k The cascaded RIS channel is used to derive the connection from base station B to each user U. kThe closed-form expression for the mean equivalent channel gain is obtained. With maximizing the mean equivalent channel gain from base station B to the worst user as the optimization objective, and with the feasible deployment range of the first and second RIS and the ordered reflection of the RIS as constraints, a two-hop RIS deployment location optimization problem is constructed. A two-layer optimization algorithm is designed to solve the two-hop RIS deployment location optimization problem, obtain the optimal deployment location of the two RIS, and improve the mean channel gain from base station B to the worst user.

[0006] Considering B to R1, R1 to R2, and R2 to user U k All channels are Ricean channels, consisting of Los and NLos components, which can be specifically represented as follows:

[0007]

[0008] The Los component is modeled as the product of the array responses of devices p and q at both ends of the beam direction. The NLos component is defined as a vector or matrix following a Gaussian distribution with mean 0 and variance 1. Where N is the number of elements in the corresponding array. Let the phase difference between two adjacent elements be the array response of the RIS.

[0009]

[0010] Where υ a υ e Indicates the azimuth and elevation angles of the directional beam at RIS, where λ represents the wavelength. T Indicates transpose. It represents the Kronecker product.

[0011] The azimuth and elevation angles of the beam from base station B to R1 are expressed as follows: The azimuth and elevation angles of the beam from R1 to R2 are expressed as follows: The azimuth and elevation angles of arrival for the beams from R1 to R2 are expressed as follows: R2 to user U k The departure azimuth and departure elevation angles are Then, the connection from base station B to R1, from R1 to R2, and from R2 to user U... k The Los components can be represented as follows:

[0012] Will Substituting into equation (1), we get the connection from base station B to R1, from R1 to R2, and from R2 to user U. k The channels can be represented as follows:

[0013]

[0014]

[0015]

[0016] Where h NLos S NLos g NLos These represent the connections from base station B to R1, R1 to R2, and R2 to user U, respectively. k The NLos component. The reflection phase shift matrices of R1 and R2 are expressed as... Then, with the assistance of R1 and R2, the signal travels from base station B to user U. k The cascaded RIS channel can be represented as

[0017]

[0018] Substituting equations (3), (4), and (5) into the above equation, we get

[0019]

[0020] Equation (1) is the result of expansion and rearrangement without NLos component terms, Equation (2) is the result of expansion and rearrangement of three terms including one NLos component term, Equation (3) is the result of expansion and rearrangement of three terms including two NLos component terms, and Equation (4) is the result of expansion and rearrangement of NLos component terms.

[0021] Since the RIS should be deployed in a fixed location to enhance the wireless communication channel quality from the base station to each user over a long period, the statistical average channel gain from the base station to each user is derived. Considering that the communication system model of this invention adopts time division multiple access and each channel is independent of the others, based on the formulas E[h1h2]=E[h1]E[h2] and E[h1+h2]=E[h1]+E[h2], the channel gain h is calculated. B,k 2 Taking the average yields

[0022]

[0023] In the formula, terms (1)-(4) correspond to the derivation results with no NLos component terms, with one NLos component term, with two NLos component terms, and with three NLos component terms, respectively. This represents the number of combinations of randomly selecting 2 units from M reflective units.

[0024] With the vertical direction of base station B as the positive z-axis and the horizontal direction from B to R1 as the positive x-axis, the deployment areas of R1 and R2 are parallel to the xoz plane. The signal originates from the base station and is reflected by R1 and R2 to reach user U. kThe deployable areas of R1 and R2 are represented as follows: The coordinates of the deployment location are represented as follows: Considering the principle of fairness, and taking maximizing the average channel gain from base station B to the worst-performing user as the optimization objective, this paper constructs a dual RIS deployment location optimization problem, with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints.

[0025]

[0026]

[0027]

[0028]

[0029] Where C1 and C2 represent In two different deployable areas C3 represents the distance between base station B and point R1. Less than the distance between base station B and R2 This constitutes an ordered reflection. Substituting equation (9) into the above optimization problem yields...

[0030]

[0031]

[0032]

[0033]

[0034] Consider the case where M is large, since M is large in this case... 4 The order of magnitude is much higher than M 2 With M, the optimization problem (10) can be further simplified to

[0035]

[0036]

[0037]

[0038]

[0039] Furthermore, for the transformed path selection problem model, an ergonomic method is used to select the optimal deployment locations of R1 and R2. Since the channels from base station B to R1 and from R1 to R2 are the same for all users, regardless of the deployment locations of R1 and R2, once their locations are fixed, the user with the minimum average channel gain is the user furthest from R2. Therefore, a two-layer search algorithm is designed to solve the above optimization problem. The detailed algorithm is as follows.

[0040] Deployable areas Divide the area into two equal regions, J1 and J2, and use the center point of each region as the coordinate point for deployment. Discretize into The placement positions of R1 and R2 are denoted as P1 and P2:

[0041]

[0042]

[0043] In a second aspect, the present invention provides an electronic terminal, including a processor and a storage medium;

[0044] The storage medium is used to store instructions; the processor is used to operate according to the instructions to perform the steps of the method described in any of the first aspects.

[0045] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0047] (1) This invention proposes a dual RIS deployment location optimization method for multi-user communication. By constructing and analyzing cascaded RIS channels containing Los and NLos components, the average equivalent channel gain from the base station to each user is accurately calculated. Using time division multiple access technology, under the premise of ensuring the independence of each channel, joint optimization is performed on the links from base station B to the two RIS and from multiple RIS to different users kU.

[0048] (2) In view of the complexity and fairness requirements of the actual wireless environment, the present invention designs and adopts a two-layer search algorithm to determine the optimal deployment location of the dual RIS. Under the condition that the dual RIS are located in their respective preset areas, the average channel gain from the base station to the user with the worst channel quality is maximized. The deployable area is discretized and the optimal RIS configuration is found through iterative solution, thereby effectively improving the coverage of the entire network, overcoming non-line-of-sight propagation loss and enhancing signal stability, and significantly improving the performance and efficiency of the multi-user communication system. Attached Figure Description

[0049] The accompanying drawings, which form part of this specification, illustrate embodiments of the invention and, together with the specification, serve to explain the principles of the invention.

[0050] The invention will be more clearly understood with reference to the accompanying drawings and the following detailed description, wherein:

[0051] Figure 1 A flowchart illustrating the method provided in an embodiment of the present invention;

[0052] Figure 2 System model diagram of a dual RIS deployment location optimization method for multi-user communication;

[0053] Figure 3 This is a schematic diagram comparing the simulated channel gain results and the equivalent channel gain results from base station B to the worst user under the optimal RIS deployment location selection in the embodiment of the present invention.

[0054] Figure 4 This is a schematic diagram comparing the channel gain simulation results from base station B to the worst user when the optimal RIS deployment location obtained by the traversal search algorithm is used in the RIS deployment location selection of the present invention, the RIS deployment location is placed at the center point, and the RIS deployment location is randomly placed. Detailed Implementation

[0055] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, and not limitations thereof. Where there is no conflict, the embodiments and technical features in the embodiments can be combined with each other. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0056] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0057] Example 1

[0058] Figure 1 This is a flowchart of a dual RIS deployment location optimization method for multi-user communication according to Embodiment 1 of the present invention. This flowchart only illustrates the logical sequence of the method described in this embodiment. In other possible embodiments of the present invention, different methods may be used, provided there are no conflicts. Figure 1 Complete the steps shown or described in the order indicated.

[0059] This embodiment is a typical implementation of the present invention, providing a dual RIS deployment location optimization method for multi-user communication. This method can be applied to terminals and can be executed by electronic terminals. The electronic terminals can be implemented by software and / or hardware and can be integrated into terminals, such as any smartphone, tablet computer or computer device with communication functions.

[0060] As a novel wireless communication technology, a Reflective Surface (RIS) is an electromagnetic surface composed of numerous low-cost passive reflective elements. Each reflective element on the surface can independently alter the phase shift or amplitude of the incident signal, thereby achieving intelligent reconstruction of the wireless channel and improving wireless communication performance. Deploying two RISs in a dual-hop cascade can significantly improve the signal coverage of base station B. Furthermore, a reliable link can be established between the two RISs, enabling them to work collaboratively and further improve the quality of transmitted signals and signal coverage. In practical scenarios, it can be used to improve the signal coverage of base station B and the quality of signals received by users, addressing the problem of poor user communication quality due to complex environmental conditions.

[0061] Figure 1 The diagram shows a system simulation of a dual-RIS deployment location optimization method for multi-user communication. The system includes a single-antenna base station B and K users U. k k = (1, 2, ..., K), two reconfigurable smart surfaces R1 and R2. This invention aims to achieve [something] between base station B and each user U by using two RIS-assisted reflections. k A two-hop RIS cascaded link is established between base stations B and the worst-case user. The optimization objective is to maximize the mean equivalent channel gain from base station B to the worst-case user. The feasible deployment areas of the first and second RISs, and the ordered reflections of the RISs are used as constraints to construct a two-hop RIS deployment location optimization problem. Finally, a two-layer search algorithm is used to optimize the deployment locations of the two RISs within the feasible deployment areas of reflector surfaces R1 and R2. The optimal location is selected within the space.

[0062] This invention provides a dual RIS deployment location optimization method for multi-user communication, solving the problem of user U in urban areas. k The problem is that it is difficult to receive high-quality signals transmitted by base station B. That is, in the communication between base station B and each user U... k Two RIS are deployed between them to build a connection from base station B to each user U. k The system employs a dual-hop cascaded channel and ultimately uses a two-layer search algorithm to select the optimal placement of R1 and R2, thereby maximizing the average equivalent channel gain from base station B to the worst-performing user.

[0063] like Figure 1As shown, the method in this embodiment specifically includes the following steps:

[0064] Obtain the distance from base station B to reflector R1, from reflector R1 to reflector R2, and from reflector R2 to each user U. k Channel state information;

[0065] Based on the channel state information, a connection is constructed from base station B to each user U. k Cascaded RIS channels;

[0066] Based on the cascaded RIS channel, the connection from base station B to each user U is derived. k The closed-form expression for the mean of the equivalent channel gain;

[0067] With the goal of maximizing the mean of the equivalent channel gain from base station B to the worst user, and with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints, a dual RIS deployment location optimization problem is constructed.

[0068] Analysis of base station B to each user U k The closed-form expression and constraints of the equivalent channel gain mean are used to solve the optimization problem of the placement of the two-hop RIS using a two-layer optimization algorithm, so as to obtain the optimal placement of reflectors R1 and R2.

[0069] Specifically, a dual-RIS deployment location optimization method for multi-user communication, such as... Figure 2 As shown, this includes: obtaining data from base station B to R1, from R1 to R2, and from R2 to each user U. k The channel state information is used to construct the connection from base station B to each user U via R1 and R2. k Cascaded RIS channels; derivation of the connection from base station B to each user U k The closed-form expression for the mean of the equivalent channel gain is obtained. Taking the maximization of the mean of the equivalent channel gain from base station B to the worst user as the optimization objective, and taking the feasible deployment area range of the first RIS and the second RIS and the ordered reflection of the RIS as constraints, the deployment location optimization problem of the two-hop RIS is constructed. A two-layer optimization algorithm is designed to solve the deployment location optimization problem of the two-hop RIS and obtain the optimal deployment locations of the reflector surfaces R1 and R2.

[0070] Considering B to R1, R1 to R2, and R2 to user U k All channels are Ricean channels, consisting of Los and NLos components, and can be represented as follows:

[0071]

[0072] Where h Los The Los component can be represented as the product of the array responses of devices p and q at both ends of the beam direction, h NLosThe NLos components follow a Gaussian distribution with mean 0 and variance 1, where K is the Rice factor, β is the path loss factor when d0 = 1, and d I This represents the distance between the devices at both ends of the beam direction.

[0073] definition Where N is the number of elements in the corresponding array. Let the phase difference between two adjacent elements be the array response of the RIS.

[0074]

[0075] Where υ a υ e Indicates the azimuth and elevation angles of the directional beam at RIS, where λ represents the wavelength. T Indicates transpose. It represents the Kronecker product.

[0076] The azimuth and elevation angles of the beam from base station B to R1 are expressed as follows: The azimuth and elevation angles of the beam from R1 to R2 are expressed as follows: The azimuth and elevation angles of arrival for the beams from R1 to R2 are expressed as follows: R2 to user U k The departure azimuth and departure elevation angles are Then, the connection from base station B to R1, from R1 to R2, and from R2 to user U... k The Los components can be represented as follows: in Indicates the distance d between devices I The resulting phase shift, (·) H This indicates the conjugate transpose.

[0077] Will Substituting into equation (1), we get the connection from base station B to R1, from R1 to R2, and from R2 to user U. k The channels can be represented as follows:

[0078]

[0079]

[0080]

[0081] Where h NLos S NLos g NLos These represent the connections from base station B to R1, R1 to R2, and R2 to user U, respectively. k The NLos component. The reflection phase shift matrices of R1 and R2 are expressed as... Then, with the assistance of R1 and R2, the signal travels from base station B to user U. k The cascaded RIS channel can be represented as

[0082]

[0083] Substituting equations (3), (4), and (5) into the above equation, we get

[0084]

[0085] Equation (1) is the result of expansion and rearrangement without NLos component terms, Equation (2) is the result of expansion and rearrangement of three terms including one NLos component term, Equation (3) is the result of expansion and rearrangement of three terms including two NLos component terms, and Equation (4) is the result of expansion and rearrangement of NLos component terms.

[0086] Consider a scenario where the base station uses time-division multiple access (TDMA) to transmit signals to each user. Given that the RIS (Radio Router Array) should be fixed in a suitable location to enhance the wireless communication channel quality from the base station to each user over a long period, derive the signal transmission path from base station B to U. k The mean of the equivalent channel gain is

[0087]

[0088] Because of the connection between base station B and R1, R1 to R2, and R2 to user U k Each channel is independent of the others. Based on the formulas E[h1h2]=E[h1]E[h2] and E[h1+h2]=E[h1]+E[h2], we can obtain

[0089]

[0090] Among them, terms (1)-(4) correspond to the derivation results with no NLos component terms, with one NLos component term, with two NLos component terms, and with three NLos component terms, respectively. This represents the number of combinations of randomly selecting 2 units from M reflective units.

[0091] With the vertical direction of base station B as the positive z-axis and the horizontal direction from B to R1 as the positive x-axis, the deployment areas of R1 and R2 are parallel to the xoz plane. The signal originates from the base station antenna and is reflected by R1 and R2 to reach user U. k .

[0092] The deployable areas of R1 and R2 are represented as follows: The coordinates of the deployment location are represented as follows: Considering the principle of fairness, and taking maximizing the average channel gain from base station B to the worst-performing user as the optimization objective, this paper constructs a dual RIS deployment location optimization problem, with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints.

[0093]

[0094]

[0095]

[0096]

[0097] Where C1 and C2 represent In two different deployable areas C3 represents the distance between base station B and point R1. Less than the distance between base station B and R2 This constitutes an ordered reflection. Substituting equation (9) into the above optimization problem yields...

[0098]

[0099]

[0100]

[0101]

[0102] Consider the case where M is large, since M is large in this case... 4 The order of magnitude is much higher than M 2 With M, the optimization problem (11) can be further simplified to

[0103]

[0104]

[0105]

[0106]

[0107] in express Distance between the coordinates of base station B and the coordinates of base station B express and Distance between coordinate points express With user U k The distance between coordinate points.

[0108] For the transformed optimization problem model, the optimal deployment locations of R1 and R2 are selected using a traversal method. Since the channels from base station B to R1 and from R1 to R2 are the same for all users regardless of their deployment locations, once the deployment locations of R1 and R2 are fixed, equation (9) shows that the user with the smallest average channel gain is the user furthest from R2. Therefore, a two-layer search algorithm is designed to solve the above optimization problem. The detailed algorithm is as follows:

[0109] Deployable areas Divide the area into two equal regions, J1 and J2, and use the center point of each region as the coordinate point for deployment. Discretize into The placement positions of R1 and R2 are denoted as P1 and P2:

[0110]

[0111] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

[0112] Example 2

[0113] The technical solution of the present invention will be further described below with reference to specific embodiments:

[0114] This embodiment is implemented through Matlab simulation. In the simulation, the wireless channels are set to be independent of each other, and the channels follow Ricean fading. The system channel model is constructed in three-dimensional space, where the three-dimensional coordinates of base station B are [0,0,10]m. Considering 9 receiving users, the user coordinates are [85,45,30]m, [85,50,30]m, [85,55,30]m, [90,45,30]m, [90,50,30]m, [90,55,30]m, [95,45,30]m, [95,50,30]m, [95,55,30]m, [95,55,30]m. The deployable areas of reflectors R1 and R2 are also considered. At base station B and user U respectively k The center coordinates of the two deployable zones on the top of the two tall buildings are [50,0,50] and [80,40,50], respectively. The two deployable zones are spaced 5 meters apart. Each area is divided into 9 square regions, and the coordinates of the center of each square region are used as the potential deployment coordinates of R1 and R2. That is, the coordinates of the nine potential deployment locations of R1 are [45,0,45]m, [50,0,45]m, [55,0,45]m, [45,0,50]m, [50,0,50]m, [55,0,50]m, [45,0,55]m, [50,0,55]m, [55,0,55]m; and the coordinates of the nine potential deployment locations of R2 are [75,40,45]m, [80,40,45]m, [85,40,45]m, [75,40,50]m, [80,40,50]m, [85,40,50]m, [75,40,55]m, [80,40,55]m, [85,40,55]m. The path loss factor β was set to 0.0046, and the Rice factor K was set to 2. For the experimental simulation, 100 time slots were set for the channel, and a Monte Carlo simulation was performed. The average value was then taken as the simulation result.

[0115] Corresponding to the dual RIS deployment location optimization method for multi-user communication provided in the above embodiments, this invention also provides a dual RIS deployment location optimization system for multi-user communication, including: a channel state information acquisition module, an optimization model establishment module, and an optimization model solving module;

[0116] The channel state information acquisition module is used to acquire information from base station B to R1, from R1 to R2, and from R2 to each user U. k Channel state information;

[0117] The optimization model establishment module is used to establish the connection between base station B and each user U based on the acquired channel state information. k The two-hop RIS cascaded link determines the distance from base station B to each user U. k The mean of the equivalent channel gain; with the goal of maximizing the mean of the equivalent channel gain from base station B to the worst user, and with the feasible deployment area of ​​the first RIS and the second RIS and the ordered reflection of the RIS as constraints, a deployment location optimization problem of two-hop RIS is constructed.

[0118] The optimization model solving module is used to solve for the optimal deployment location of the double-hop RIS, so that the distance from base station B to each user U is optimal. k The equivalent channel gain has the largest mean.

[0119] Figure 3 A comparative experiment was conducted to show the simulation results and theoretical results when the RIS was deployed in the optimal position. Figure 3It can be seen that, under the optimal deployment position of RIS, the curves of the average actual channel gain and the average equivalent channel gain of the worst user almost coincide with the curves of the number of RIS reflection units increasing. The average equivalent channel gain is always slightly higher than the average actual channel gain, with a difference of less than 0.2dB.

[0120] In addition, two sets of comparative experiments were set up. In the first set, R1 and R2 were respectively set at... The center point, the second group randomly places R1 and R2 respectively at the center point. Within the region. By Figure 4 It can be seen that, under the optimal RIS deployment location, the average channel gain of the worst-performing user is consistently higher than that of the user with the RIS deployed at [location missing]. The location of the center point and the random placement in The location represents the average channel gain of the worst-performing user. This demonstrates the effectiveness of the RIS optimal location deployment method proposed in this invention.

[0121] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of each module of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0122] Those skilled in the art will understand that embodiments of this application can be provided as methods or computer program products. Therefore, this application can take the form of embodiments combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0124] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0125] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

[0126] Example 3

[0127] This invention also provides an electronic terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the following method:

[0128] Obtain the distance from base station B to reflector R1, from reflector R1 to reflector R2, and from reflector R2 to each user U. k Channel state information;

[0129] Based on the channel state information, a connection is constructed from base station B to each user U. k Cascaded RIS channels;

[0130] Based on the cascaded RIS channel, the connection from base station B to each user U is derived. k The closed-form expression for the mean of the equivalent channel gain;

[0131] With the goal of maximizing the mean of the equivalent channel gain from base station B to the worst user, and with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints, a dual RIS deployment location optimization problem is constructed.

[0132] Analysis of base station B to each user U k The closed-form expression and constraints of the equivalent channel gain mean are used to solve the optimization problem of the placement of the two-hop RIS using a two-layer optimization algorithm, so as to obtain the optimal placement of reflectors R1 and R2.

[0133] The electronic terminal provided in the embodiments of the present invention can execute a dual RIS deployment location optimization method for multi-user communication provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0134] Example 3

[0135] This invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the following method:

[0136] Obtain the distance from base station B to reflector R1, from reflector R1 to reflector R2, and from reflector R2 to each user U. k Channel state information;

[0137] Based on the channel state information, a connection is constructed from base station B to each user U. k Cascaded RIS channels;

[0138] Based on the cascaded RIS channel, the connection from base station B to each user U is derived. k The closed-form expression for the mean of the equivalent channel gain;

[0139] With the goal of maximizing the mean of the equivalent channel gain from base station B to the worst user, and with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints, a dual RIS deployment location optimization problem is constructed.

[0140] Analysis of base station B to each user U k The closed-form expression and constraints of the equivalent channel gain mean are used to solve the optimization problem of the placement of the two-hop RIS using a two-layer optimization algorithm, so as to obtain the optimal placement of reflectors R1 and R2.

[0141] The present invention provides a computer-readable storage medium storing a computer program that can execute a dual RIS deployment location optimization method for multi-user communication provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0142] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0143] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0144] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A dual RIS deployment location optimization method for multi-user communication, characterized in that, Includes the following steps: Obtain the image from base station B to the reflector. Reflective surface To the reflecting surface and reflective surface To each user Channel state information; Based on channel state information, a connection is constructed from base station B to each user. Cascaded RIS channels; Based on the cascaded RIS channel, the connection from base station B to each user is derived. The closed-form expression for the mean of the equivalent channel gain; With the goal of maximizing the mean of the equivalent channel gain from base station B to the worst user, and with the feasible deployment area of ​​dual RIS and the ordered reflection of RIS as constraints, a dual RIS deployment location optimization problem is constructed. Analysis of base station B to each user The closed-form expression and constraints of the equivalent channel gain mean are used to solve the dual RIS deployment location optimization problem using a two-layer optimization algorithm to obtain the reflector surface. Reflective surface The optimal deployment location; With the vertical direction of base station B as the positive z-axis, the distance from base station B to the reflecting surface... The horizontal direction is the positive x-axis, and the reflecting surface is... Reflective surface The deployment area is parallel to The plane, the signal is emitted from the base station antenna, and passes through the reflector. Reflective surface Reflection reaches the user ; reflective surface The feasible deployment area is represented as Reflective surface The feasible deployment area is represented as , reflective surface The deployment location coordinates are represented as Reflective surface The deployment location coordinates are represented as The optimization objective is to maximize the mean channel gain from base station B to the worst-case user, with the reflector surface as the target. Feasible deployment area Reflective surface Feasible deployment area And with the ordered reflection of RIS as a constraint, construct the optimization problem of the placement of dual RIS: in , express , In two different deployable areas , , Indicates base station B to Distance between two points Less than base station B to Distance between two points This constitutes an ordered reflection. This indicates that among each user Find the worst user among them, and select the one that best serves the worst user. Reflecting surface that achieves maximum value Deployment location coordinates Reflective surface Deployment location coordinates , Representing the constraints; substituting equation (9) into the optimization problem of the placement of the dual RIS, we get: consider In larger cases, due to the fact that at this time The order of magnitude is much higher than and The optimization problem of the placement of the dual RIS (11) is further simplified as follows: in Represents the reflecting surface The deployable area Represents the reflecting surface Location coordinates, Represents the reflecting surface The deployable area Represents the reflecting surface Location coordinates, Indicates the first The worst user is the individual user. express Distance between the coordinates of base station B and the coordinates of base station B express and Distance between coordinate points express With users Distance between coordinate points Indicates the number of reflecting elements in the reflecting surface. This indicates that among each user Find the worst user among them, and select the one that best serves the worst user. Reflecting surface that achieves maximum value Deployment location coordinates Reflective surface Deployment location coordinates , This indicates a constraint.

2. The dual RIS deployment location optimization method for multi-user communication according to claim 1, characterized in that, Base station B, reflector Reflective surface as well as individual users equipment With equipment express Then the distance from base station B to the reflecting surface Channel state information is Reflective surface To the reflecting surface Channel state information is and reflective surface To each user Channel state information is ; The device With equipment The channels between them are all Ricean channels, specifically represented as follows: in The Los component represents the devices at both ends of the beam direction. and equipment The product of array responses, The NLos components follow a Gaussian distribution with mean 0 and variance 1. Rice factor, for Path loss factor at time The distance between the devices at both ends of the beam direction; Reflective surface Reflective surface Depend on Composed of a reflective element, This indicates the number of reflecting elements in the horizontal direction of the reflecting surface. This indicates the number of reflecting elements in the vertical direction of the reflecting surface; Define the first intermediate parameter function ,in The number of elements in the corresponding array. The phase difference between two adjacent elements. Represents the field of complex numbers. Indicates size is complex vectors, For imaginary number labels, If the matrix or vector is transposed, then the RIS array response is: in , This indicates the departure (arrival) azimuth and departure (arrival) elevation angles of the directional beam at RIS. Indicates wavelength. Indicates the Kronecker product. The distance between the devices at both ends of the beam direction; The device With equipment The Rice channel between devices is defined as a device With equipment The product of the array responses between them will transfer the distance from base station B to the reflector. The azimuth angle of arrival of the directional beam is expressed as: The elevation angle is expressed as Reflective surface To the reflecting surface The azimuth angle of the directional beam departure is expressed as The angle of departure is represented as Reflective surface To the reflecting surface The azimuth angle of arrival of the directional beam is expressed as: The elevation angle is expressed as Reflective surface To users The departure azimuth is expressed as The angle of departure is Substituting the above parameters into equation (2) yields the distance from base station B to the reflecting surface. Los component Reflective surface To the reflecting surface Los component Reflective surface To users Los component ,in Indicates the distance between devices The resulting phase shift, This indicates the conjugate transpose of a matrix or vector. The , , Substituting into equation (1), the distance from base station B to the reflector can be obtained. Channel state information, reflector To the reflecting surface Channel state information, reflector To users Channel state information , , Specifically, it is expressed as: in Indicates the distance from base station B to the reflector. NLos components, Represents the reflecting surface To the reflecting surface NLos components, Represents the reflecting surface To users NLos components, Indicates the distance between devices The resulting phase shift, For equipment With equipment The distance between them Rice factor, for Path loss factor at time Indicates wavelength; reflective surface The reflection phase shift matrix is ​​expressed as , Indicates size is Complex matrix, Belongs to the complex field, reflecting surface The reflection phase shift matrix is ​​expressed as , It belongs to the complex field.

3. The dual RIS deployment location optimization method for multi-user communication according to claim 1, characterized in that, Based on the parameters in the obtained channel state information , , , as well as Base station B will be transmitted via a reflective surface Reflective surface Assistance to all users The cascaded RIS channel is represented as: in This indicates that the matrix or vector is being transposed using its conjugate. Substituting equations (3), (4), and (5) into equation (6) yields: In the formula, Representing the distance from base station B to the reflector surface NLos components, Represents the reflecting surface To the reflecting surface NLos components, Represents the reflecting surface To users NLos components, Indicates the distance between devices The resulting phase shift, For equipment With equipment The distance between them Rice factor, for Path loss factor at time The wavelength is represented; in equation (7), term (1) is the result of expansion and rearrangement without NLos component terms, term (2) is the result of expansion and rearrangement with three terms including one NLos component term, term (3) is the result of expansion and rearrangement with three terms including two NLos component terms, and term (4) is the result of expansion and rearrangement with NLos component terms.

4. The dual RIS deployment location optimization method for multi-user communication according to claim 1, characterized in that, Based on the cascaded RIS channel of equation (6), the connection from base station B to user is derived. The mean of the equivalent channel gain is: In the formula, Represents the square of the scalar modulus. This represents the mean; due to the distance from base station B to the reflecting surface Reflective surface To the reflecting surface Reflective surface To users Each channel is independent of the others, and the distance from base station B to each user is derived. The closed-form expression for the mean of the equivalent channel gain is: In the formula, terms (1), (2), (3), and (4) correspond to the derivation results with no NLos component, with one NLos component, with two NLos component, and with three NLos component, respectively; where, The number of reflecting elements in the reflecting surface. For equipment With equipment The distance between them Rice factor, for Path loss factor at time This represents the number of combinations of choosing any 2 elements from M reflective elements.

5. The dual RIS deployment location optimization method for multi-user communication according to claim 4, characterized in that, A two-layer optimization algorithm is designed and employed to solve the optimization problem. The detailed algorithm steps are as follows: Deployable areas equalized points Each region is used as a coordinate point for deployment, with its center point serving as the location coordinate point. Discretize into Deployable areas equalized points Each region is used as a coordinate point for deployment, with its center point serving as the location coordinate point. Discretize into , reflective surface The deployment location is denoted as Reflective surface The deployment location is denoted as : First, the outer algorithm of the two-layer optimization algorithm is performed to obtain the reflecting surface. Each deployable area The worst-performing user; reflective surface Each deployable area The corresponding worst user is ,in Indicates to make Minimum The possible values ​​of ; Secondly, the inner algorithm operation of the two-layer optimization algorithm is performed, targeting the worst user. For the reflecting surface Deployable area Perform a search to obtain Reflecting surface that achieves maximum average channel gain Optimal deployment location ; capable of Obtain the mean of maximum channel gain Deployment location is ,in Indicates when When fixed, make Maximum The possible values ​​of ; Finally, define the set of position coordinate points. , It includes the reflective surface obtained after calculation by the two-layer optimization algorithm. Reflective surface The coordinates of the candidate positions, for By comparing all candidate locations, the reflective surface can be obtained. Reflective surface Optimal deployment location ,in Representing variables belong , Indicates when When fixed, make Maximum The value of .

6. An electronic terminal, characterized in that, Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1 to 5.

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