A method and device for determining RIS phase shift vector

Abstract

The present application relates to a method and device for determining a RIS phase shift vector. The method includes: obtaining first distance information from each target antenna of a base station to the RIS, and second distance information from the RIS to each target location point in the target area, a first channel from each target antenna to the RIS, and a second channel from the RIS to each target location point; determining the average channel link strength from each target antenna to each target location point, and taking the function corresponding to the minimum value of the average link strength as the objective function; based on the objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit, and obtaining the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving a signal sent by each target antenna, and reflect the reflection signal to the target area. The disclosed embodiment can improve the signal channel link strength of the target location in the target area.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for determining a RIS phase shift vector. Background Art

[0002] Ensuring wireless network coverage has always been a difficult problem. Although new network architectures and communication technologies have been proposed to meet data needs, new challenges have also been brought about. In particular, in discrete and irregularly distributed coverage blind spots (especially in urban areas), traditional coverage enhancement methods, such as network densification, distributed antennas, drones, and heterogeneous network architectures, may have shortcomings or limitations. For example, for small and discretely distributed coverage blind spots, it is costly to add base stations (BS) or dispatch drones. On the other hand, the recent development of reconfigurable intelligent surfaces (RIS) provides a new and promising method for enhancing coverage. It consists of numerous passive reflective elements and can achieve passive beamforming by controlling the phase offset of each element. Improving communication performance using RIS has been widely studied in various systems.

[0003] In the related art, the joint design of transmission precoding (at the BS) and passive beamforming (at the RIS) has been used to enhance performance, but this design brings more signaling overhead and makes the transmission protocol more complicated, which hinders the convenient use of RIS to enhance the performance of existing communication systems and improve coverage. Therefore, how to effectively improve communication performance and coverage without affecting the original transmission scheme of the main communication system is still a problem to be solved. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product that can determine the RIS phase shift vector of the signal channel link strength in order to solve the above technical problems.

[0005] In a first aspect, the present application provides a method for determining a RIS phase shift vector. The method comprises:

[0006] A method for determining a RIS phase shift vector, characterized in that it is applied to a RIS controller in a communication system, wherein the communication system includes a base station, a RIS, and a client, and the method includes:

[0007] Acquire the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point; wherein the target area is the area where the signal transmitted from the base station reaches after being passively reflected by the RIS;

[0008] Based on the first distance information, the second distance information, the first channel, and the second channel, determine the average channel link strength from each target antenna to each target position point, and take the function corresponding to the minimum value of the average link strength as the objective function;

[0009] Based on the objective function, a feasible solution set of the phase shift vector of the RIS phase shift unit is searched to obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving a signal sent by each target antenna, and reflect the reflection signal to the target area.

[0010] In one of the embodiments, based on the objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit to obtain the RIS phase shift vector corresponding to the maximum objective function value includes:

[0011] Acquire an initial sample set consisting of coordinate information of each target position point in the target area;

[0012] Performing spatial downsampling processing on the initial sample set to obtain an optimized sample set;

[0013] The objective function is updated based on the optimized sample set to obtain an updated objective function, and based on the updated objective function, a feasible solution set of the phase shift vector of the RIS phase shift unit is searched to obtain the RIS phase shift vector corresponding to the maximum objective function value.

[0014] In one embodiment, obtaining an initial sample set consisting of coordinate information of each target position point in the target area includes:

[0015] Get the position range of the target area on the coordinate axis;

[0016] Based on the position range, a rectangular area is generated so that the rectangular area completely covers the target area;

[0017] The rectangular area is divided into a plurality of grids, and it is determined whether the center of each grid is located within the target area. If the center of the grid is located within the target area, the position information corresponding to the center of the grid is added to the initial sample set.

[0018] In one embodiment, performing spatial downsampling processing on the initial sample set to obtain an optimized sample set includes:

[0019] Obtaining an initial target position point from an initial sample set;

[0020] Determine whether the initial target location point is in a vicinity of any target location point in the optimized sample set;

[0021] In the case where the initial target location point is located in the adjacent area, not adding the initial target location point to the optimized sample set;

[0022] When the initial target position point is outside the adjacent area, the initial target position point is added to the optimized sample set until all the initial target position points in the initial sample set are traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

[0023] In one embodiment, searching for a feasible solution set of a phase shift vector of a RIS phase shift unit based on the updated objective function to obtain a RIS phase shift vector corresponding to a maximum objective function value comprises:

[0024] Initialize auxiliary variables, as well as the lower and upper limits of the values ​​of the auxiliary variables;

[0025] When the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable;

[0026] The initial auxiliary variable is updated to obtain an updated initial auxiliary variable, and when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable, until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range;

[0027] When the iteration of the auxiliary variable is terminated, the final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, the current RIS phase shift vector is output.

[0028] In one embodiment, obtaining first distance information from each target antenna of the base station to the RIS, second distance information from the RIS to each target location point in the target area, first channels from each target antenna to the RIS, and second channels from the RIS to each target location point includes:

[0029] Based on the deployment parameter data and long-term service quality statistics of the communication operator, the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point are obtained.

[0030] In a second aspect, the present application provides a RIS phase shift vector determination device, which is applied to a RIS controller in a communication system, wherein the communication system includes a base station, a RIS, and a client, and the device includes:

[0031] An acquisition module is used to acquire first distance information from each target antenna of the base station to the RIS, and second distance information from the RIS to each target location point in the target area, a first channel from each target antenna to the RIS, and a second channel from the RIS to each target location point; wherein the target area is the area where the signal transmitted from the base station reaches after being passively reflected by the RIS;

[0032] A first determination module is used to determine the average channel link strength from each target antenna to each target position point based on the first distance information, the second distance information, the first channel and the second channel, and take the function corresponding to the minimum value of the average link strength as the objective function;

[0033] The second determination module is used to search for a feasible solution set of the phase shift vector of the RIS phase shift unit based on the objective function, and obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving the signal sent by each target antenna, and reflect the reflection signal to the target area.

[0034] In one embodiment, the second determining module is further configured to:

[0035] Acquire an initial sample set consisting of coordinate information of each target position point in the target area;

[0036] Performing spatial downsampling processing on the initial sample set to obtain an optimized sample set;

[0037] The objective function is updated based on the optimized sample set to obtain an updated objective function, and based on the updated objective function, a feasible solution set of the phase shift vector of the RIS phase shift unit is searched to obtain the RIS phase shift vector corresponding to the maximum objective function value.

[0038] In one embodiment, the second determining module is further configured to:

[0039] Get the position range of the target area on the coordinate axis;

[0040] Based on the position range, a rectangular area is generated so that the rectangular area completely covers the target area;

[0041] The rectangular area is divided into a plurality of grids, and it is determined whether the center of each grid is located within the target area. If the center of the grid is located within the target area, the position information corresponding to the center of the grid is added to the initial sample set.

[0042] In one embodiment, the second determining module is further configured to:

[0043] Obtaining an initial target position point from an initial sample set;

[0044] Determine whether the initial target location point is in a vicinity of any target location point in the optimized sample set;

[0045] In the case where the initial target location point is located in the adjacent area, not adding the initial target location point to the optimized sample set;

[0046] When the initial target position point is outside the adjacent area, the initial target position point is added to the optimized sample set until all the initial target position points in the initial sample set are traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

[0047] In one embodiment, the second determining module is further configured to:

[0048] Initialize auxiliary variables, as well as the lower and upper limits of the values ​​of the auxiliary variables;

[0049] When the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable;

[0050] The initial auxiliary variable is updated to obtain an updated initial auxiliary variable, and when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable, until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range;

[0051] When the iteration of the auxiliary variable is terminated, the final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, the current RIS phase shift vector is output.

[0052] In one embodiment, the acquisition module is further used for:

[0053] Based on the deployment parameter data and long-term service quality statistics of the communication operator, the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point are obtained.

[0054] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any one of the embodiments of the present disclosure is implemented.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method described in any one of the embodiments of the present disclosure is implemented.

[0056] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the method described in any one of the embodiments of the present disclosure is implemented.

[0057] The above-mentioned RIS signal determination method, device, computer equipment, storage medium and computer program product, since the target phase shift vector can uniquely determine the RIS signal, by constructing the target function of the channel link strength from the target antenna to the target position point, the minimum target function is selected from the target functions of the channel link strength corresponding to all antennas on the base station side and all target positions in the target area, and then the phase shift vector on the RIS side is adjusted so that the above-mentioned minimum target function takes the maximum value, the channel link strength in the target area can be optimized as a whole, the minimum channel link strength of all base station antennas at any target position point in the target area can be improved, and the service quality of the communication system in the target area can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 FIG. 1 is an application environment diagram of a method for determining a RIS signal in an embodiment;

[0059] Figure 2 is a flow chart of a method for determining a RIS signal in one embodiment;

[0060] Figure 3 is a flow chart of a method for determining a RIS signal in one embodiment;

[0061] Figure 4 is a flow chart of a method for determining a RIS signal in one embodiment;

[0062] Figure 5 is a flow chart of a method for determining a RIS signal in one embodiment;

[0063] Figure 6 is a flow chart of a method for determining a RIS signal in one embodiment;

[0064] Figure 7 is a flow chart of a method for determining a RIS signal in one embodiment;

[0065] Figure 8 is a first effect diagram of a method for determining a RIS signal in one embodiment;

[0066] Fig. 9 is a second effect diagram of a method for determining a RIS signal in one embodiment;

[0067] Fig.10 is a structural block diagram of a device for determining a RIS signal in one embodiment;

[0068] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0070] The RIS signal determination method provided in the embodiment of the present application can be applied to Figure 1 In the communication system shown.

[0071] In the embodiment of the present disclosure, the communication system includes a RIS (Reconfigurable Intelligent Surface), a RIS controller, a base station, and a client. In the above communication system, the base station is equipped with a certain number of antennas n. The RIS is equipped with a certain number of phase shift units, for example, M = M y ×M z The signal transmitted by each antenna on the base station is forwarded by the RIS and reaches the target location point in the target area, such as the target location point s.

[0072] In one embodiment, Figure 2 As shown, a method for determining a RIS phase shift vector is provided, and the method is applied to Figure 1 The following steps are used as an example to illustrate the RIS in the example:

[0073] Step S201, obtaining first distance information from each target antenna of the base station to the RIS, second distance information from the RIS to each target location point in the target area, first channels from each target antenna to the RIS, and second channels from the RIS to each target location point.

[0074] The target area is an area reached by the signal transmitted from the base station after being passively reflected by the RIS.

[0075] Specifically, the first distance information from the target antenna n to the RIS can be expressed as d n , the second distance information from RIS to the target location s can be expressed as d s , the first channel from target antenna n to RIS is denoted as h n The second channel from RIS to the target location s is represented by h s The above data can be obtained from the deployment parameter data or long-term service quality statistics of communication operators in various countries.

[0076] Step S203, based on the first distance information, the second distance information, the first channel and the second channel, determine the average channel link strength from each target antenna to each target position point, and take the function corresponding to the minimum value of the average link strength as the objective function.

[0077] In one embodiment, based on the first distance information and the second distance information, the cascade loss is determined. For example, the i-th cascade loss can be expressed as, optionally,

[0078] Based on the first channel, the first channel expectation is determined. For example, the first channel is represented by h n , the first channel expectation is denoted as R n ,

[0079]

[0080] Among them, K1 represents the Rice factor from the base station to RIS, I represents the unit matrix of size M×M, represents the Hermitian transpose of the first channel,

[0081] Based on the second channel, the second channel expectation is determined. For example, the second channel is represented by h s , the second channel expectation is expressed as R s .

[0082]

[0083] in, represents the conjugate of the second channel, represents the transpose of the second channel, K2 represents the Rice factor from RIS to the target area, It also represents the identity matrix of size M×M.

[0084] In one embodiment, based on the first channel expectation and the second channel expectation, a matrix product is determined, for example, M i represents matrix product, then Where ⊙ represents the Hadamard product operation.

[0085] In one embodiment, assuming that the total number of base station antennas is N, the number of target location points in the target area is S, s represents the target location point, and the total number of average channel link strength objective functions of the signal transmitted by the target antenna to the target location point is I=N×S. Taking the i=(S-1)N+nth objective function as an example, the corresponding average channel link strength objective function can be expressed as:

[0086] g i (u) = α i u H M i u (3)

[0087] Where, u represents the phase shift vector of the phase shift unit of RIS, M i , α i The definitions are the same as those in the above embodiments and will not be repeated herein.

[0088] Step S205: Based on the objective function, search for a feasible solution set of the phase shift vector of the RIS phase shift unit to obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving a signal sent by each target antenna, and reflect the reflection signal to the target area.

[0089] Step 1.1: Based on the obtained large-scale parameters, the large-scale parameters may include the parameters on the right side of the equal sign in formula (4). Given a sample location point The channel link strength from the nth antenna of the base station can be expressed as γ n,s , the formula is as follows:

[0090]

[0091] Wherein, R represents the target area. represents the path loss factor, d n represents the distance from the nth antenna to the RIS, d s represents the distance from RIS to the sample location s. Optionally, the channel may include a Rice channel. The path loss factor is related to the distance between the base station and the sample location s, the distance between the base station and the RIS, and the distance between the RIS and the target area.s is the channel from RIS to the sample location, h n It is the channel from the nth antenna at the base station to RIS. Optionally, the channel may include a Ricean channel. represents the phase shift matrix of RIS, which is a diagonal matrix. The phase shift of the mth unit can be expressed as Among them, the phase shift unit is a tiny element on the surface of RIS, which is used to adjust the phase of the signal. The phase shift unit can adjust the phase of the signal as needed, thereby realizing operations such as focusing, scattering, and diffraction of the signal. By reasonably adjusting the phase of the phase shift unit, the transmission characteristics of the signal can be optimized.

[0092] The area-oriented coverage enhancement problem can be expressed as:

[0093]

[0094] Among them, reference Figure 1 As shown, θ n ,φ n , d n Respectively represent the azimuth, elevation and distance from the nth antenna to the RIS, d s They represent the azimuth, elevation and distance from RIS to the target area point s, R represents the real number domain, The triplet θ describing the location of the base station antenna n ,φ n , d n The discrete feasible set of Represents a triple d s A continuous feasible set describing the locations in the target region.

[0095] Step 1.2 Solving the exact analytical expression, it can be expressed as:

[0096]

[0097] Where ⊙ represents the Hadamard product operation, For R n and R s It is expressed as,

[0098]

[0099] Where, I in formula (7) and formula (8) represents the unit matrix of size M×M, K1 represents the Rice factor from the base station to RIS, K2 represents the Rice factor from RIS to the target area, and h n represents the channel from the nth antenna to the RIS, represents the Hermitian transpose of the channel from the nth antenna to the RIS, represents the conjugate of the channel from RIS to the sample position s, * represents the conjugate processing, represents the transposition of the channel from RIS to the sample position s, T represents the transposition process,

[0100] Among them, h n The expression is: It includes Los part and NLos part. NLos conforms to Rayleigh distribution. The expression of Los part is: It consists of the classic millimeter wave model, namely:

[0101] They represent the array response vectors in the vertical and horizontal array directions respectively, that is, they represent the phase difference caused by the path difference.

[0102] Substituting equation (7) and equation (8) into equation (6), can be re-expressed as follows:

[0103]

[0104] Since only the first term changes with n and s, and Therefore, for The maximization of can be regarded as the maximization of the following formula:

[0105]

[0106] Among them, f n，s (u) represents the given sample location point The channel link strength γ from the nth antenna of the base station (n，s) Expectations, d n ,d s 、u、 ⊙, has the same meaning as that in the above embodiment, and will not be repeated in this application. n，s The expression of (u) does not need to know the fast fading part of the channel, only the historical data of RIS deployment and geometric parameters such as θ n ,φ n , d n It can be confirmed.

[0107] Step 1.3: For any given u and n, where u represents the phase shift vector of the RIS and n represents the nth antenna, (10) is continuous with respect to s. Specifically, for any two sample locations s1 and s2, and The upper limit of the difference between

[0108]

[0109] in, represents the distance from RIS to the sample location s1, represents the distance from RIS to the sample location s2, d n represents the distance from the nth antenna to the RIS, u represents the phase shift vector of the RIS, and It is expressed as follows,

[0110]

[0111] in, Indicates the elevation angle of the signal beam received by the sample position point s1, Indicates the elevation angle of the signal beam received by the sample position point s2, represents the azimuth of the signal beam received by the sample position point s1, Indicates the azimuth of the signal beam received by the sample position point s2. and In channel modeling, since millimeter wave channels are used, the phase inconsistency caused by the differences in pitch angles and azimuth angles will be taken into consideration. These two parameters are set to simplify the expression.

[0112] Specifically, step 2.1: For fixed n and s, maximizing (10) is independent of K1 and K2. When calculating the expectation, the fast fading part of the channel can be canceled out and become a fixed value. Therefore, only the LoS part of the channel is uncertain, because the LoS part will change with the change of RIS and region. Therefore, for the regional coverage enhancement design, regardless of the strength of the channel signal in the original target line of sight (LoS) direction, RIS should concentrate all its controllable power in the target line of sight (LoS) direction. and When both are rank 1 matrices, The rank of is also 1. So maximizing The optimum phase shift of RIS should be The eigen direction is consistent. The eigen direction is consistent with the direction of the eigenvector, which can be understood as pointing to the same position as the eigenvector; a rank 1 matrix has only one eigenvector, and the vector that can get the maximum value by multiplying it should be consistent with its eigenvector direction. The eigen direction is the direction of the matrix eigenvector. According to the Rice channel considered and The definition of and It can be expressed as

[0113]

[0114] in, represents the conjugate of the channel from the nth antenna to the RIS, represents the conjugate of the channel from RIS to the sample location s, represents the transpose of the channel from the nth antenna to the RIS, represents the transpose of the channel from RIS to the sample location s. It should be noted that the embodiments of the present disclosure are not limited to Ricean channels, but can also be used for LoS channels, that is, when the Ricean factor is very large; and can also be used for Rayleigh channels, that is, when the Ricean factor is very small. The “—” at the top of each symbol represents the LoS part of the channel, that is, the line-of-sight channel, for example: It is known that it remains stable when the RIS and the target area remain unchanged.

[0115] Then in this case, the optimal u that maximizes the average channel link strength from the nth antenna at position s is given by:

[0116]

[0117] Formula (14) can reflect the optimal u in the case of a single antenna.

[0118] Step 2.2: Problem (2) is extremely difficult to solve when considering all antennas at all base stations and all possible locations in R. However, with the help of (7), the original problem (2) is simplified to,

[0119]

[0120] Among them, θ n ,φ n , d n Respectively represent the azimuth, elevation and distance from the nth antenna to the RIS, d s They represent the azimuth, elevation and distance from RIS to the target area point s respectively. represents the real number domain, and m represents the mth phase shift unit. represents a triple describing the BS antenna position (θ n , φn, dn) is a discrete feasible set. Represents a three-tuple describing a position in the target region ( φs, ds) is a continuous feasible set.

[0121] Therefore, in one embodiment, the optimization objective of the objective function can be expressed as:

[0122]

[0123] The accuracy of formula (16) increases as the number of target position points in the target area increases. That is, the more samples there are in the target area, the better formula (16) can describe the optimization objective. However, increasing S will increase the complexity. The optimization objective of the objective function is to obtain the optimal value from all I(N×S) g i (u), choose the smallest g i (u), by solving u to maximize this minimum g i (u).

[0124] In one embodiment, reference Figure 3 As shown, based on the objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit, and obtaining the RIS phase shift vector corresponding to the maximum objective function value, includes:

[0125] Step S301: obtaining an initial sample set consisting of coordinate information of each target position point in the target area.

[0126] In one embodiment, step S301 includes: step S401, step S403 and step S405. Among them:

[0127] Step S401, obtaining the position range of the target area on the coordinate axis.

[0128] For example: Target area The coordinate range in the x and y dimensions is [x min , x max ] and [y min ,y max ].

[0129] Step S403: generating a rectangular area based on the position range, so that the rectangular area completely covers the target area.

[0130] In one embodiment, based on the coordinate range [x min , x max ] and [y min ,y max ], determine the rectangular area as L x ×L y , the rectangular area completely covers the target area.

[0131] Step S405, dividing the rectangular area into a plurality of grids, determining whether the center of each grid is located within the target area, and if the center of the grid is located within the target area, adding the position information corresponding to the center of the grid to the initial sample set.

[0132] Take the first x , l y) grid as an example, its center point can actually be obtained by the following formula: For each grid center, check whether it falls within R; if so, include the center point in the sample set middle.

[0133] Step S303: perform spatial downsampling processing on the initial sample set to obtain an optimized sample set.

[0134] In one embodiment, step S303 includes: step S501, step S503, step S505 and step S507. Among them:

[0135] Step S501, obtaining an initial target position point from an initial sample set. Step S503, determining whether the initial target position point is in a neighboring area of ​​any target position point in an optimized sample set. Step S505, when the initial target position point is in the neighboring area, not adding the initial target position point to the optimized sample set. Step S507, when the initial target position point is outside the neighboring area, adding the initial target position point to the optimized sample set, until all initial target position points in the initial sample set have been traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

[0136] Specifically, in one embodiment, under a given sample set S, in addition to uniform grid or random selection, how to more effectively select position samples, so it is necessary to explore a more efficient method for selecting sample positions, and the specific exploration process is as follows:

[0137] We first show the area coverage performance achieved using step 2 (obtaining feasible RIS phase shifts and different spatial grid densities for a given sample set). Two metrics are involved:

[0138] 1) t returned from step 2 * value, which describes the worst-case channel link strength guaranteed by the spatial samples used in the optimization;

[0139] 2) Coverage feasibility probability (with a ratio of t * The probability of a larger channel link strength) is defined as,

[0140]

[0141] Among them, Pr represents the probability operation, which is the target area Random positions in The channel link strength is greater than t *It reflects the effectiveness of applying step 2 on a specific sample set. It is shown that the worst-case area coverage performance can be guaranteed with high probability.

[0142] For a specific location point, the locations in its adjacent areas will have similar coverage performance. The location samples used for coverage optimization should be selected outside the adjacent areas to improve sampling efficiency. The adjacent area of ​​location s (in terms of coverage performance) is called the coverage similarity area, denoted by For the sample location It covers similar areas describes the worst-case channel link strength difference (compared to location s and measured from all BS antennas) less than σ th The union of all possible positions of

[0143]

[0144] Among them, f n，s (u) represents the expected channel link strength from the nth antenna of the base station at a given sample location s∈R. n，r (u) represents the given sample location point The expected channel link strength from the nth antenna of the base station at σ th Indicates the minimum power received difference, for any location point The following inequality holds,

[0145]

[0146] The proof process of formula 22 is as in step 1.3, and the present disclosure will not repeat it here. From the above formula, we can see that when the right hand side (RHS) of (22) is negative, the inequality holds for any point Therefore, in order to improve In the wireless coverage area, the best phase shift of RIS is to any point Beamforming, if the following requirements are met,

[0147]

[0148] Among them, σ th Indicates the minimum power receiving difference, In this case, ensure The difference in channel link strength between any two locations is less than σ th .d min，BS d min，RRepresent the minimum distances from the antenna to the RIS and from the RIS to the target location, respectively, and M represents the number of RIS phase shift units. When the RIS is small and the target area is far away from the RIS, the beam width formed by the RIS will be wider than the area size. Therefore, there is no need to formulate the regional coverage enhancement problem in the form of (15), and simply forming a beam in the direction of the area can meet the requirements. However, in practice, the number of RIS units is usually large and may be deployed in the vicinity of the target area. In this case, step 2 needs to be applied to achieve robust coverage of the entire area.

[0149] pass By definition, spatial sampling can actually be viewed as an exploration problem. That is, Coverage Area in is the set of selected spatial samples. But it should be noted that The shape and size of the The geometry may be discontinuous and irregular, usually depending on the M x , M z and a specific value of Δ, where M z is the number of phase shift units along the z-axis in the RIS, M x It is the number of RIS phase shift units along the x-axis, indicating the spacing between phase shift units, which is generally half a wavelength.

[0150] Step S305, updating the objective function based on the optimized sample set to obtain an updated objective function, searching for a feasible solution set of phase shift vectors of the RIS phase shift unit based on the updated objective function, and obtaining a RIS phase shift vector corresponding to a maximum objective function value.

[0151] Specifically, in an exemplary embodiment, the objective function is updated according to the optimized sample set to obtain an updated objective function. The updating method may include replacing the original sample set in the objective function. Based on the updated objective function, the feasible solution set of the phase shift vector of the RIS phase shift unit is searched to obtain the RIS phase shift vector corresponding to the maximum objective function value. The specific implementation may be the same as step S205, and the embodiments of the present disclosure will not be repeated here.

[0152] In another exemplary embodiment, step S305 further includes: step S601, step S603, step S605 and step S607. Among them:

[0153] In step S601, the auxiliary variables are initialized, and the lower limit and upper limit of the auxiliary variables are initialized. The optimized sample set and the auxiliary variables are obtained; wherein the sample set includes a set consisting of target position points s. For a fixed I (same meaning as in the above embodiment) and a fixed sample set (a set consisting of target position points s), by introducing the auxiliary variable positive integer t, (16) can be restated as:

[0154]

[0155] Furthermore, by performing a line search on t, we can find its maximum feasible value t* that satisfies all the constraints in (17). By solving the corresponding feasibility problem, we can get the solution to problem (14).

[0156] In one embodiment, a binary search method may be used to search for the maximum feasible value t*. Specifically, the binary search method includes:

[0157] Initialize the auxiliary variable t and the lower limit T of the value of the auxiliary variable t l And the upper limit T u .

[0158] For example, T l =0, Among them, α i , M i Same as the above embodiment, M represents the number of all units in RIS, M=M x ×M z , M x represents the number of phase shift units along the x-axis in RIS, M z represents the number of phase shift units along the z-axis in RIS, λ max (M i ) represents the maximum eigenvalue of M, which can be obtained by matrix decomposition.

[0159] For example, initialize the auxiliary variable to half of its lower and upper limits, and get the initial auxiliary variable, for example,

[0160] Step S603: when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the initial auxiliary variable is replaced by the initial auxiliary variable.

[0161] For example: Setting the initial And check whether the constraints in (15) are feasible under the current t. If so, update T l ←t, otherwise update T u ←t.

[0162] Step S605: Update the initial auxiliary variable to obtain an updated initial auxiliary variable. When the initial auxiliary variable is less than or equal to the updated objective function value, replace the lower limit of the initial auxiliary variable with the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, replace the upper limit of the initial auxiliary variable with the initial auxiliary variable, until the difference between the lower limit of the initial auxiliary variable and the lower limit of the initial auxiliary variable is within a preset range.

[0163] Step S607: when the iteration of the auxiliary variable is terminated, a final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, a current RIS phase shift vector is output.

[0164] For example: Update the initial auxiliary variable to obtain the updated initial auxiliary variable. When the initial auxiliary variable is less than or equal to g i (u), the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than g i (u), the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range.

[0165] For example: When T u -T l The iteration terminates when <ε, where ε is a predefined small value, and then returns the maximum feasible t*.

[0166] In the above embodiment, by searching the middle term of the auxiliary variable, it is determined whether the middle term is before or after the average power to be searched. If it is after, then you only need to continue searching in the first half; if it is before, then search in the second half. In this way, you can exclude half of the search range each time, thereby improving the query efficiency.

[0167] In another embodiment, the following method can be used to search for the maximum feasible value t*. For example, for a given t∈[T l , T u ], the feasibility problem mentioned above can be expressed as:

[0168] find u

[0169] st|u(m)|=1

[0170]

[0171] The semidefinite relaxation (SDR) technique is used to transform (18) into (19), where (19) is a convex feasibility problem that can be easily solved using existing optimization toolboxes, such as cvX.

[0172] find U

[0173]

[0174] U≥0 (19)

[0175] Among them, U=uu H , which satisfies the rank 1 constraint. Once the feasible U * , using Gaussian randomization, find U * The corresponding feasible solution U * .

[0176] It should be noted that because SDR needs to remove the rank 1 constraint of U, when finding a feasible U*, the rank 1 constraint may not be satisfied, and matrix decomposition is needed, but matrix decomposition obviously has a high error, which brings inevitable losses. There, a random matrix needs to be multiplied to expand the "field of view", similar to the gradient descent method, using multiple sets of random initial points, and then selecting the best performance as the solution, in order to solve the problem that the initial solution is not the optimal solution.

[0177] In the above embodiment, by constructing the objective function of the channel link strength from the target antenna to the target location point, the minimum objective function is selected from the objective functions of the channel link strength corresponding to all antennas on the base station side and all target locations in the target area, and then the phase shift vector on the RIS side is adjusted so that the minimum objective function takes the maximum value, the channel link strength in the target area can be optimized as a whole, and the minimum channel link strength of all base station antennas at any target location point in the target area can be improved, thereby improving the service quality of the communication system in the target area. .

[0178] In one embodiment, reference Figure 7 As shown, the method includes:

[0179] Step 1: Obtain large-scale parameters such as BS relative position;

[0180] Step 2: Determine the given sampling method. If it is given, obtain the sample set according to the given sampling method and go to step 4.

[0181] Step 3: Optimize the sample set by using spatial downsampling based on the coverage similarity area to cover the target area with the minimum number of samples. The specific steps include:

[0182] 3a, S0 can be constructed by fixed grid or random sampling or any other feasible method. It should be a dense sample set in R0, that is, it contains more samples than expected. The expected sample set S is initialized to an empty set;

[0183] 3b. A sample r can be taken from S0 (without replacement). If S0 is an empty set, go to step 4.

[0184] 3c, by simply checking whether the sample r falls within If it falls within If yes, go to step 3b;

[0185] 3d. Add sample r to sample set S and go to step 3b.

[0186] Step 4: Maximize the minimum channel link strength of all BS antennas at any point in the target area through the sample set obtained by spatial sampling. The specific steps include:

[0187] 4a. Set the iterative convergence value ε and construct the lower bound T of the channel link strength based on the channel information. l and upper bound T u ;

[0188] 4b. Set current target Check whether the constraints in (16) are solvable under this objective; if so, update T l = t, if unsolvable, update T u =t;

[0189] 4c. Calculate whether the difference between the current upper and lower bounds is less than the termination value. If it is greater than the termination value, go to step 4b. If it is satisfied, output t at this time and the solution u obtained by Gaussian randomization.

[0190] In one embodiment, reference Fig. 9 and Fig.10 As shown in the figure, it can be seen that the optimization scheme for enhancing regional coverage proposed in the present invention is significantly better than the existing scheme, and effectively improves the lower limit of the worst channel link strength and transmission rate in the area.

[0191] Based on the same inventive concept, the embodiment of the present application also provides a RIS-based signal determination method device for implementing the RIS-based signal determination method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more RIS-based signal determination method device embodiments provided below can refer to the above limitations on the RIS-based signal determination method, and will not be repeated here.

[0192] In one embodiment, Fig.10 As shown, a RIS signal determination device 1000 is provided, comprising:

[0193] The acquisition module 1001 is used to acquire first distance information from each target antenna of the base station to the RIS, and second distance information from the RIS to each target location point in the target area, a first channel from each target antenna to the RIS, and a second channel from the RIS to each target location point; wherein the target area is the area where the signal transmitted from the base station reaches after being passively reflected by the RIS;

[0194] A first determination module 1003 is used to determine the average channel link strength from each target antenna to each target position point based on the first distance information, the second distance information, the first channel and the second channel, and take the function corresponding to the minimum value of the average link strength as the objective function;

[0195] The second determination module 1005 is used to search for a feasible solution set of the phase shift vector of the RIS phase shift unit based on the objective function, and obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving the signal sent by each target antenna, and reflect the reflection signal to the target area.

[0196] In one embodiment, the second determining module is further configured to:

[0197] Acquire an initial sample set consisting of coordinate information of each target position point in the target area;

[0198] Performing spatial downsampling processing on the initial sample set to obtain an optimized sample set;

[0199] The objective function is updated based on the optimized sample set to obtain an updated objective function, and based on the updated objective function, a feasible solution set of the phase shift vector of the RIS phase shift unit is searched to obtain the RIS phase shift vector corresponding to the maximum objective function value.

[0200] In one embodiment, the second determining module is further configured to:

[0201] Get the position range of the target area on the coordinate axis;

[0202] Based on the position range, a rectangular area is generated so that the rectangular area completely covers the target area;

[0203] The rectangular area is divided into a plurality of grids, and it is determined whether the center of each grid is located within the target area. If the center of the grid is located within the target area, the position information corresponding to the center of the grid is added to the initial sample set.

[0204] In one embodiment, the second determining module is further configured to:

[0205] Obtaining an initial target position point from an initial sample set;

[0206] Determine whether the initial target location point is in a vicinity of any target location point in the optimized sample set;

[0207] In the case where the initial target location point is located in the adjacent area, not adding the initial target location point to the optimized sample set;

[0208] When the initial target position point is outside the adjacent area, the initial target position point is added to the optimized sample set until all the initial target position points in the initial sample set are traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

[0209] In one embodiment, the second determining module is further configured to:

[0210] Initialize auxiliary variables, as well as the lower and upper limits of the values ​​of the auxiliary variables;

[0211] When the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable;

[0212] The initial auxiliary variable is updated to obtain an updated initial auxiliary variable, and when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable, until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range;

[0213] When the iteration of the auxiliary variable is terminated, the final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, the current RIS phase shift vector is output.

[0214] In one embodiment, the acquisition module is further used for:

[0215] Based on the deployment parameter data and long-term service quality statistics of the communication operator, the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point are obtained.

[0216] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store RIS-based signal determination data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a signal determination method based on RIS is implemented.

[0217] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0218] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0219] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0220] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining a RIS phase shift vector, characterized in that: A RIS controller applied to a communication system, wherein the communication system includes a base station, a RIS and a client, and the method includes: Acquire the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point; wherein the target area is the area where the signal transmitted from the base station reaches after being passively reflected by the RIS; Based on the first distance information, the second distance information, the first channel and the second channel, the average channel link strength from each target antenna to each target position point is determined, and the function corresponding to the minimum value of the average link strength is taken as the objective function; wherein the total number of objective functions of the average channel link strength from the signal transmitted by the target antenna to the target position point is , the i=(S-1)N+nth objective function is expressed as: ; Where N represents the total number of base station antennas, and the number of target location points in the target area is S; in, represents the phase shift vector of the phase shift unit of RIS, represents matrix product, ; Denotes the i-th cascade loss: , represents the first distance information, represents the second distance information; in, represents the Hadamard product operation, Indicates the first channel expectation corresponding to the first channel: ;in, represents the Rice factor from the base station to the RIS, Indicates size The identity matrix of represents the Hermitian transpose of the first channel, ;in, Indicates the number of RIS phase shift units, Indicates Antennas; Indicates the second channel expectation corresponding to the second channel: ,in, represents the conjugate of the second channel, represents the transpose of the second channel, represents the Rice factor from RIS to the target area, ; Based on the objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit to obtain the RIS phase shift vector corresponding to the maximum objective function value; Based on the objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit to obtain the RIS phase shift vector corresponding to the maximum objective function value, including: obtaining an initial sample set consisting of coordinate information of each target position point in the target area; performing spatial downsampling processing on the initial sample set to obtain an optimized sample set; updating the objective function based on the optimized sample set to obtain an updated objective function, searching for a feasible solution set of the phase shift vector of the RIS phase shift unit based on the updated objective function to obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving a signal sent by each target antenna, and reflect the reflection signal to the target area.

2. The method according to claim 1, characterized in that Acquiring an initial sample set consisting of coordinate information of each target position point in the target area, including: Get the position range of the target area on the coordinate axis; Based on the position range, a rectangular area is generated so that the rectangular area completely covers the target area; The rectangular area is divided into a plurality of grids, and it is determined whether the center of each grid is located within the target area. If the center of the grid is located within the target area, the position information corresponding to the center of the grid is added to the initial sample set.

3. The method according to claim 1, characterized in that The performing spatial downsampling processing on the initial sample set to obtain an optimized sample set includes: Obtaining an initial target position point from an initial sample set; Determine whether the initial target location point is in a vicinity of any target location point in the optimized sample set; In the case where the initial target location point is located in the adjacent area, not adding the initial target location point to the optimized sample set; When the initial target position point is outside the adjacent area, the initial target position point is added to the optimized sample set until all the initial target position points in the initial sample set are traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

4. The method according to claim 1, characterized in that The step of searching a feasible solution set of a phase shift vector of the RIS phase shift unit based on the updated objective function to obtain a RIS phase shift vector corresponding to a maximum objective function value includes: Initialize auxiliary variables, as well as the lower and upper limits of the values ​​of the auxiliary variables; When the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; The initial auxiliary variable is updated to obtain an updated initial auxiliary variable, and when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable, until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range; When the iteration of the auxiliary variable is terminated, the final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, the current RIS phase shift vector is output.

5. The method according to claim 1, characterized in that Acquiring first distance information from each target antenna of the base station to the RIS, second distance information from the RIS to each target location point in the target area, first channels from each target antenna to the RIS, and second channels from the RIS to each target location point, including: Based on the deployment parameter data and long-term service quality statistics of the communication operator, the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point are obtained.

6. A RIS phase shift vector determination device, characterized in that: A RIS controller applied to a communication system, wherein the communication system includes a base station, a RIS and a client, and the device includes: An acquisition module is used to acquire first distance information from each target antenna of the base station to the RIS, and second distance information from the RIS to each target location point in the target area, a first channel from each target antenna to the RIS, and a second channel from the RIS to each target location point; wherein the target area is the area where the signal transmitted from the base station reaches after being passively reflected by the RIS; The first determination module is used to determine the average channel link strength from each target antenna to each target position point based on the first distance information, the second distance information, the first channel and the second channel, and take the function corresponding to the minimum value of the average link strength as the objective function; wherein the total number of objective functions of the average channel link strength from the signal transmitted by the target antenna to the target position point is , the i=(S-1)N+nth objective function is expressed as: ; Where N represents the total number of base station antennas, and the number of target location points in the target area is S; in, represents the phase shift vector of the phase shift unit of RIS, represents matrix product, ; Denotes the i-th cascade loss: , represents the first distance information, represents the second distance information; represents the Hadamard product operation, in, Indicates the first channel expectation corresponding to the first channel: ;in, represents the Rice factor from the base station to the RIS, Indicates size The identity matrix of represents the Hermitian transpose of the first channel, ;in, Indicates the number of RIS phase shift units, Indicates Antennas; Indicates the second channel expectation corresponding to the second channel: ,in, represents the conjugate of the second channel, represents the transpose of the second channel, represents the Rice factor from RIS to the target area, ; The second determination module is used to search for a feasible solution set of the phase shift vector of the RIS phase shift unit based on the objective function, and obtain the RIS phase shift vector corresponding to the maximum objective function value; the RIS phase shift vector is used to generate a reflection signal when receiving the signal sent by each target antenna, and reflect the reflection signal to the target area; the second determination module is also used to: obtain an initial sample set composed of coordinate information of each target position point in the target area; perform spatial downsampling processing on the initial sample set to obtain an optimized sample set; update the objective function based on the optimized sample set to obtain an updated objective function, and search for a feasible solution set of the phase shift vector of the RIS phase shift unit based on the updated objective function to obtain the RIS phase shift vector corresponding to the maximum objective function value.

7. The device according to claim 6, characterized in that The second determining module is further used for: Get the position range of the target area on the coordinate axis; Based on the position range, a rectangular area is generated so that the rectangular area completely covers the target area; The rectangular area is divided into a plurality of grids, and it is determined whether the center of each grid is located within the target area. If the center of the grid is located within the target area, the position information corresponding to the center of the grid is added to the initial sample set.

8. The device according to claim 6, characterized in that The second determining module is further used for: Obtaining an initial target position point from an initial sample set; Determine whether the initial target location point is in a vicinity of any target location point in the optimized sample set; In the case where the initial target location point is located in the adjacent area, not adding the initial target location point to the optimized sample set; When the initial target position point is outside the adjacent area, the initial target position point is added to the optimized sample set until all the initial target position points in the initial sample set are traversed or the number of target position points in the optimized sample set reaches a preset threshold, thereby obtaining an optimized sample set.

9. The device according to claim 6, characterized in that The second determining module is further used for: Initialize auxiliary variables, as well as the lower and upper limits of the values ​​of the auxiliary variables; When the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; The initial auxiliary variable is updated to obtain an updated initial auxiliary variable, and when the initial auxiliary variable is less than or equal to the updated objective function value, the lower limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable; when the initial auxiliary variable is greater than the updated objective function value, the upper limit of the value of the initial auxiliary variable is replaced by the initial auxiliary variable, until the difference between the lower limit of the value of the initial auxiliary variable and the lower limit of the value of the initial auxiliary variable is within a preset range; When the iteration of the auxiliary variable is terminated, the final objective function corresponding to the final auxiliary variable is determined, and based on the final objective function, the current RIS phase shift vector is output.

10. The device according to claim 6, characterized in that The acquisition module is also used for: Based on the deployment parameter data and long-term service quality statistics of the communication operator, the first distance information from each target antenna of the base station to the RIS, the second distance information from the RIS to each target location point in the target area, the first channel from each target antenna to the RIS, and the second channel from the RIS to each target location point are obtained.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

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

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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