Methods and systems for intelligent metasurface-assisted wireless multicast transmission

Abstract

This application provides a method and system for intelligent metasurface-assisted wireless multicast transmission, belonging to the field of mobile communication technology. The invention acquires user propagation demand information and user distribution information; determines a multicast transmission strategy based on the user propagation demand information and user distribution information; determines wireless transmission parameters based on the multicast transmission strategy; and obtains intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters. This invention can maximize the multicast transmission rate, thereby improving spectral efficiency and multicast system capacity, and saving energy consumption.

Description

Technical Field

[0001] This application relates to the field of mobile communication technology, and in particular to a method and system for intelligent metasurface-assisted wireless multicast transmission. Background Technology

[0002] As a new type of wireless service, wireless multicast transmission utilizes the broadcast characteristics of wireless channels to form a multicast group of all users with the same demand for specific service content during transmission, and delivers the same information to all multicast users simultaneously. It is a high spectrum-efficiency wireless service that can be widely used in communication scenarios such as video-on-demand, video conferencing, and multimedia education.

[0003] Since users in a multicast group are distributed in different locations within the cell and experience different large-scale and small-scale fading, the channel conditions of different users vary greatly. The capacity of a multicast group is limited by the user with the worst channel conditions. If the transmission rate is too high, users with poor channel conditions cannot decode data correctly. If the transmission rate is sufficient for the user with the worst channel conditions, good fairness can be achieved, but the efficiency of radio resources is too low.

[0004] In wireless multicast transmission, cooperative relay technology can effectively combat channel fading and improve the transmission performance of multicast systems. Existing cooperative multicast technologies are basically unicast-assisted multicast or multicast-assisted unicast. Regardless of whether the participating nodes are unicast or multicast users, two time slots are required for transmission, leading to a decrease in multicast system capacity and an increase in energy consumption. Summary of the Invention

[0005] The main objective of this application is to provide a method and system for intelligent metasurface-assisted wireless multicast transmission.

[0006] The technical solution adopted in this invention is:

[0007] On one hand, embodiments of the present invention provide a method for intelligent metasurface-assisted wireless multicast transmission, the method comprising the following steps:

[0008] Obtain information on user dissemination needs and user distribution;

[0009] Based on the user propagation demand information and the user distribution information, a multicast transmission strategy is determined;

[0010] Based on the multicast transmission strategy, determine the wireless transmission parameters;

[0011] Based on the wireless transmission parameters, intelligent metasurface-assisted wireless multicast transmission data is obtained.

[0012] Furthermore, obtaining user dissemination demand information and user distribution information includes the following steps:

[0013] Obtain service request information from communication users;

[0014] Based on the service request information, the user's location information is obtained, or the relative distance and orientation information between the communication user and the base station is obtained through wireless sensing.

[0015] The user distribution information is based on the user location information or the relative distance and orientation information between the communication user and the base station.

[0016] Based on the business request information, user dissemination demand information is statistically obtained;

[0017] The user communication demand information includes user multicast service demand information.

[0018] Furthermore, determining the multicast transmission strategy based on the user propagation demand information and the user distribution information includes the following steps:

[0019] Configure non-orthogonal multiple access conditions;

[0020] Based on the non-orthogonal multiple access condition information, the user propagation requirement information, and the user distribution information, non-orthogonal multiple access condition judgment information for multicast transmission is obtained;

[0021] According to the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than the preset threshold, or the unicast users scheduled are not within the preset location range of the multicast group users, then the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission only; otherwise, the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0022] If the multicast transmission strategy is the intelligent metasurface-assisted transmission based on non-orthogonal multiple access, determine the unicast users participating in the cooperative multicast transmission.

[0023] Further, if the multicast transmission strategy is the intelligent metasurface-assisted transmission based on non-orthogonal multiple access, determining the unicast users participating in the cooperative multicast transmission includes:

[0024] If the scheduled unicast users are within the preset location range of the multicast group users, then according to the principle of closest location, several potential unicast users are selected from the scheduled unicast users to participate in intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0025] The selected potential unicast users are formed into a potential unicast user set; the number of potential unicast users is an integer greater than zero.

[0026] When the number of potential unicast users is 1, the potential unicast user is the unicast user whose location is closest to the multicast user.

[0027] The formula used to obtain the unicast user whose location is closest to the multicast user includes:

[0028]

[0029] Where u* is the unicast user whose location is closest to the multicast user;

[0030] θ i The location between the multicast user and the base station;

[0031] θ u The location between the potential unicast user and the base station;

[0032] Ω m The set of the multicast users;

[0033] Ω u The set of potential unicast users.

[0034] Further, determining the wireless transmission parameters according to the multicast transmission strategy includes the following steps:

[0035] According to the multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, the optimal wireless transmission parameters for intelligent metasurface-assisted transmission are obtained by maximizing the rate of the worst multicast user.

[0036] According to the multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface.

[0037] Furthermore, according to the multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, the optimal wireless transmission parameters for intelligent metasurface-assisted transmission only are obtained by maximizing the rate of the worst multicast user. The formula used includes:

[0038]

[0039] st‖ω‖ 2 ≤P max ;

[0040] |Φ n |=1,n=1,…,N;

[0041] Where k represents the multicast user; D k G is the channel coefficient vector from the base station antenna array to the multicast user; k The channel coefficient vector from the smart metasurface array to the multicast user;

[0042] H is the channel coefficient matrix from the base station antenna array to the smart metasurface array;

[0043] G k H is the cascaded channel coefficient matrix from the base station to the multicast user via the smart metasurface;

[0044] n represents a smart metasurface unit;

[0045] Φ n This represents the phase coefficient of the intelligent metasurface unit;

[0046] ω is the beamforming vector of the base station's transmitting antenna;

[0047] Φ is the phase coefficient vector of the smart metasurface;

[0048] P max This refers to the maximum transmit power of the base station;

[0049] σ 2 Noise power;

[0050] N is the number of units in the intelligent metasurface array;

[0051] (ω * ,Φ * ) represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission only.

[0052] Furthermore, according to the multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface. The formulas used include:

[0053]

[0054] st‖ω‖ 2 ≤P max

[0055] |Φ n |=1,n=1,…,N

[0056]

[0057] α u R is the proportion of power allocated to unicast user u. min,u For the rate requirement of unicast user u, l>u means that unicast user l decodes after unicast user u;

[0058] (a * ,ω *,Φ * ) represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0059] Furthermore, the formula used to obtain intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters includes:

[0060]

[0061] Among them, s m (t) represents multicast data; s u (t) represents unicast data;

[0062] S BS (t) represents the data transmitted via wireless multicast assisted by the intelligent metasurface.

[0063] Furthermore, the method for intelligent metasurface-assisted wireless multicast transmission also includes:

[0064] Determine the set of candidate unicast users;

[0065] Calculate the benefit of each unicast user in the candidate unicast user set participating in cooperative transmission;

[0066] Based on the benefits of unicast users participating in cooperative transmission, select the unicast user with the best cooperative transmission benefits;

[0067] The wireless transmission parameters are obtained based on the unicast user with the best cooperative transmission efficiency.

[0068] The base station transmits data by superimposing encoded unicast and multicast data and based on the wireless transmission parameters.

[0069] On the other hand, embodiments of the present invention also provide a system for intelligent metasurface-assisted wireless multicast transmission, the system comprising:

[0070] The first module is used to obtain information on user dissemination needs and user distribution;

[0071] The second module is used to determine a multicast transmission strategy based on the user propagation demand information and the user distribution information.

[0072] The third module is used to determine the wireless transmission parameters according to the multicast transmission strategy;

[0073] The fourth module is used to obtain intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters.

[0074] The fifth module is used to control the wireless multicast transmission of data assisted by the intelligent metasurface.

[0075] The embodiments of this application include at least the following beneficial effects: This application provides a method and system for intelligent metasurface-assisted wireless multicast transmission. The invention acquires user propagation demand information and user distribution information; determines a multicast transmission strategy based on the user propagation demand information and user distribution information; determines wireless transmission parameters based on the multicast transmission strategy; and obtains intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters. This invention can maximize the multicast transmission rate, thereby improving spectral efficiency and multicast system capacity, and saving energy consumption. Attached Figure Description

[0076] Figure 1 This is a flowchart of the method for intelligent metasurface-assisted wireless multicast transmission provided in an embodiment of the present invention;

[0077] Figure 2 This is a schematic diagram of the RIS-assisted wireless multicast transmission architecture provided in an embodiment of the present invention;

[0078] Figure 3 This is a schematic diagram of the RIS-assisted wireless multicast transmission method provided in an embodiment of the present invention;

[0079] Figure 4 This is a schematic diagram of the method for determining the multicast transmission strategy provided in an embodiment of the present invention;

[0080] Figure 5 This is a schematic diagram of a NOMA-based wireless multicast transmission method provided in an embodiment of the present invention;

[0081] Figure 6 This is a schematic diagram of the signaling flow for RIS-assisted wireless multicast transmission provided in an embodiment of the present invention. Detailed Implementation

[0082] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0083] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0084] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0085] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0086] This invention proposes a wireless multicast transmission method assisted by a Reconfigurable Intelligent Surface (RIS). The RIS is used to construct the channel environment for wireless multicast users, and suitable unicast users are selected to participate in cooperative multicast transmission. Multicast and unicast user data are superimposed and encoded based on Non-Orthogonal Multiple Access (NOMA). Users utilize Successive Interference Cancellation (SIC) to eliminate mutual interference. By controlling the base station's transmit antenna and the beamforming of the RIS, the multicast transmission rate is maximized, thereby improving spectral efficiency and multicast system capacity while saving energy.

[0087] The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0088] On one hand, embodiments of the present invention provide a method for intelligent metasurface-assisted wireless multicast transmission, with reference to Figure 1 The method includes the following steps:

[0089] S100, Obtain user dissemination needs information and user distribution information;

[0090] S200. Determine the multicast transmission strategy based on user propagation needs information and user distribution information;

[0091] S300: Determine wireless transmission parameters according to the multicast transmission strategy;

[0092] S400: Based on the wireless transmission parameters, obtain intelligent metasurface-assisted wireless multicast transmission data.

[0093] This invention discloses step S100 for obtaining user propagation demand information and user distribution information, including the following steps:

[0094] S110. Obtain service request information from communication users;

[0095] S120. Based on the service request information, obtain the user's location information or, through wireless sensing, acquire the relative distance and orientation information between the communication user and the base station.

[0096] S130. User distribution information is based on user location information or the relative distance and orientation information between the communication user and the base station.

[0097] S140. Based on the business request information, the user dissemination demand information is obtained;

[0098] S150, User communication needs information includes user multicast service needs information.

[0099] This invention discloses step S200, which determines a multicast transmission strategy based on user propagation demand information and user distribution information, including the following steps:

[0100] S210. Configure non-orthogonal multiple access conditions;

[0101] S220. Based on the non-orthogonal multiple access condition information, user propagation demand information, and user distribution information, obtain the non-orthogonal multiple access condition judgment information for multicast transmission;

[0102] S230. Based on the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than the preset threshold, or the unicast users scheduled are not within the preset location range of the multicast group users, then the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission only; otherwise, the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0103] S240. If the multicast transmission strategy is intelligent metasurface-assisted transmission based on non-orthogonal multiple access, determine the unicast users participating in the cooperative multicast transmission.

[0104] This invention discloses step S240, which, if the multicast transmission strategy is intelligent metasurface-assisted transmission based on non-orthogonal multiple access, determines the unicast users participating in cooperative multicast transmission, including:

[0105] S241. If the unicast users scheduled are within the preset location range of the multicast group users, then according to the principle of closest location, select several potential unicast users from the scheduled unicast users to participate in intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0106] S242. Form a potential unicast user set from the selected potential unicast users; the number of potential unicast users is an integer greater than zero;

[0107] S243. When the number of potential unicast users is 1, the potential unicast user is the unicast user whose location is closest to the multicast user.

[0108] S244. The formula used to obtain the unicast user whose location is closest to the multicast user includes:

[0109]

[0110] Among them, u * The unicast user whose location is closest to the multicast user;

[0111] θ i The location between the multicast user and the base station;

[0112] θ u The location between potential unicast users and the base station;

[0113] Ω m A collection of multicast users;

[0114] Ω u For a set of potential unicast users.

[0115] This invention discloses step S300, which determines wireless transmission parameters according to a multicast transmission strategy, including the following steps:

[0116] S310. According to the multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, the optimal wireless transmission parameters for intelligent metasurface-assisted transmission are obtained by maximizing the rate of the worst multicast user.

[0117] S320. According to the multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface.

[0118] This invention discloses step S310, which, according to a multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, obtains the optimal wireless transmission parameters for intelligent metasurface-assisted transmission only by maximizing the rate of the worst multicast user. The formula used includes:

[0119]

[0120] st‖ω‖ 2 ≤P max ;

[0121] |Φ n |=1,n=1,…,N;

[0122] Where k represents the multicast user; D k G is the channel coefficient vector from the base station antenna array to the multicast user; k This represents the channel coefficient vector from the intelligent metasurface array to the multicast user;

[0123] H is the channel coefficient matrix from the base station antenna array to the smart metasurface array;

[0124] G k H is the cascaded channel coefficient matrix from the base station to the multicast user via the smart metasurface;

[0125] n represents a smart metasurface unit;

[0126] Φ n Represents the phase coefficient of the intelligent metasurface unit;

[0127] ω is the beamforming vector of the base station's transmitting antenna;

[0128] Φ is the phase coefficient vector of the smart metasurface;

[0129] σ 2 Noise power;

[0130] P max This is the maximum transmit power of the base station;

[0131] N is the number of cells in the smart metasurface array;

[0132] (ω * ,Φ * ) represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission only.

[0133] This invention discloses step S320, which, according to a multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, obtains the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface. The formula used includes:

[0134]

[0135] st‖ω‖ 2 ≤P max

[0136] |Φ n |=1,n=1,…,N

[0137]

[0138] α u R is the proportion of power allocated to unicast user u. min,u For the rate requirement of unicast user u, l>u means that unicast user l decodes after unicast user u;

[0139] (a * ,ω * ,Φ * ) represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission based on non-orthogonal multiple access.

[0140] As an optional implementation, D k and G k Let G be the channel coefficient vector from the base station antenna array and the RIS array to the multicast user k, respectively, and H be the channel coefficient matrix from the base station antenna array to the RIS array. k H is the concatenated channel coefficient matrix from the base station to multicast user k via RIS. Φ n P represents the phase coefficient of the RIS element n, and ω is the beamforming vector of the base station transmit antenna. max Where σ is the maximum transmit power of the base station, N is the number of elements in the RIS array, and σ is the maximum transmit power of the base station. 2 This represents the noise power. `l>u` indicates that unicast user l decodes after unicast user u.

[0141] As an optional implementation, the optimal wireless transmission parameters (a) can be obtained by solving the above optimization problem. * ,ω * ,Φ * ).

[0142] This invention discloses step S400, which obtains intelligent metasurface-assisted wireless multicast transmission data based on wireless transmission parameters. The formula used includes:

[0143]

[0144] Among them, s m (t) represents multicast data; s u (t) represents unicast data;

[0145] S BS (t) represents the data transmitted via wireless multicast assisted by the intelligent metasurface.

[0146] As an optional implementation, for multicast data s m (t) and unicast data su (t) is overlaid and encoded to obtain the data sent by the base station:

[0147] As an optional implementation, the base station is based on the optimal RIS reflection coefficient Φ * Control RIS to assist in the transmission of the superimposed encoded data S BS (t).

[0148] The method for intelligent metasurface-assisted wireless multicast transmission disclosed in this invention embodiment further includes:

[0149] S500, Determine the set of candidate unicast users;

[0150] S600, Calculate the benefit of each unicast user in the candidate unicast user set participating in cooperative transmission;

[0151] S700: Based on the benefits of unicast users participating in cooperative transmission, select the unicast user with the best cooperative transmission benefits;

[0152] S800 obtains wireless transmission parameters based on the unicast user with the best cooperative transmission efficiency;

[0153] The S900 superimposes and encodes unicast and multicast data, and obtains the base station's transmitted data based on wireless transmission parameters.

[0154] On the other hand, embodiments of the present invention also provide a system for intelligent metasurface-assisted wireless multicast transmission, the system comprising:

[0155] The first module is used to obtain information on user dissemination needs and user distribution;

[0156] The second module is used to determine the multicast transmission strategy based on user propagation needs and user distribution information;

[0157] The third module is used to determine the wireless transmission parameters based on the multicast transmission strategy;

[0158] The fourth module is used to obtain intelligent metasurface-assisted wireless multicast transmission data based on wireless transmission parameters;

[0159] The fifth module is used to control the wireless multicast transmission of data assisted by the intelligent metasurface.

[0160] As an optional implementation, the present invention addresses the problem of improving system capacity and spectral efficiency in wireless multicast transmission, such as... Figure 2 As shown, in each transmission time interval (TTI), the base station schedules multicast users and unicast users, and selects suitable unicast users from the scheduled unicast users to participate in multicast transmission, forming a cooperative transmission group.

[0161] The base station uses superposition coding for multicast and unicast data of the cooperative transmission group, and transmits the coded data in the TTI. At the same time, it controls the phase shift of RIS and cooperatively reflects the superposition coded data signal.

[0162] The RIS-assisted wireless multicast transmission method of the present invention is as follows: Figure 3 As shown.

[0163] Step 1: Determine user transmission needs and distribution:

[0164] 1) Based on the service requests of communication users, the base station counts the multicast service needs of users.

[0165] Users of the same multicast service join a multicast group Ω m :

[0166] Ω m ={i,k;s i,k =1}

[0167] s i,k =1 indicates that user i and user k have the same multicast service.

[0168] 2) Base stations determine user distribution through wireless sensing.

[0169] If a user initiates a service request message that carries the user's location, then the location is used to represent the user's distribution. Otherwise, the relative distance and orientation between the user and the base station are used to represent the user's distribution. This information can be obtained through wireless sensing.

[0170] Step 2: Determine the multicast transmission strategy based on user transmission needs and distribution:

[0171] Methods for determining multicast transmission strategies include Figure 4 The following is stated:

[0172] 1) The base station determines whether the current multicast transmission meets the NOMA condition based on the user's transmission service requirements and distribution.

[0173] If multicast group Ω m The number of users is greater than the preset threshold N thr Or, the unicast user dispatched this time is not within the preset location range θ of the multicast group users. thr If the multicast transmission strategy is determined to be RIS-assisted transmission only, otherwise it is RIS-assisted transmission based on NOMA.

[0174] Conditions for RIS-assisted transmission only:

[0175] |Ω m |>N thr

[0176] or

[0177]

[0178] Where, θ i and θ u Ω represents the azimuth between multicast user i and unicast user u and the base station, respectively. s For the set of unicast users scheduled to this TTI.

[0179] 2) If the NOMA condition is met, the multicast transmission strategy is determined to be RIS-assisted transmission based on NOMA, and the unicast users participating in the cooperative multicast transmission are determined.

[0180] For the preset location range θ of the users in this multicast group that were dispatched this time thr Among the unicast users within the network, M unicast users are selected according to the nearest location principle to participate in NOMA transmission, forming the set Ω of participating unicast users. u M is a positive integer. When M = 1, the unicast user participating in NOMA transmission is the unicast user u closest to the multicast user. * :

[0181]

[0182] In this way, unicast users participating in multicast transmission can better reuse space with multicast users, improving the efficiency of space resources.

[0183] Step 3: Determine wireless transmission parameters and send data based on the multicast transmission strategy:

[0184] 1) Determine the wireless parameters for RIS-assisted transmission only and send data.

[0185] For multicast transmission assisted only by RIS, the beamforming ω of the base station's transmit antenna and the phase coefficient vector Φ of RIS are jointly optimized to maximize the rate of the worst-case multicast user:

[0186]

[0187] st‖ω‖ 2 ≤P max

[0188] |Φ n |=1,n=1,…,N

[0189] Among them, D k and G k Let G be the channel coefficient vector from the base station antenna array and the RIS array to the multicast user k, respectively, and H be the channel coefficient matrix from the base station antenna array to the RIS array. k H is the concatenated channel coefficient matrix from the base station to multicast user k via RIS. Φ nP represents the phase coefficient of the RIS element n, and ω is the beamforming vector of the base station transmit antenna. max σ is the maximum transmit power of the base station. 2 Where is the noise power, and N is the number of cells in the RIS array.

[0190] By employing alternating iterations combined with other optimization algorithms, such as positive semidefinite relaxation and positive semidefinite programming, the above optimization problem can be solved to obtain the optimal wireless transmission parameters (ω). * ,Φ * ).

[0191] The base station is based on the optimal RIS reflection coefficient Φ * Control the RIS and perform beamforming ω based on the optimal transmit antenna. * Send the data for the multicast group.

[0192] Multicast data signals are transmitted in real time via RIS, completing relay cooperative transmission in one time slot, thus improving the spectral efficiency of multicast transmission.

[0193] 2) Determine the wireless parameters for NOMA-based RIS-assisted transmission and send data.

[0194] For NOMA-based RIS-assisted multicast transmission, the beamforming ω of the base station's transmit antenna and the phase coefficient Φ of the RIS are jointly optimized to maximize the rate for the worst-case multicast user:

[0195]

[0196] st‖ω‖ 2 ≤P max

[0197] |Φ n |=1,n=1,…,N

[0198]

[0199] Among them, D k and G k Let G be the channel coefficient vector from the base station antenna array and the RIS array to the multicast user k, respectively, and H be the channel coefficient matrix from the base station antenna array to the RIS array. k H is the concatenated channel coefficient matrix from the base station to multicast user k via RIS. Φ n P represents the phase coefficient of the RIS element n, and ω is the beamforming vector of the base station transmit antenna. max Where σ is the maximum transmit power of the base station, N is the number of elements in the RIS array, and σ is the maximum transmit power of the base station. 2 This represents the noise power. `l>u` indicates that unicast user l decodes after unicast user u.

[0200] αu R is the proportion of power allocated to unicast user u. min,u Let u be the rate requirement of unicast user. By solving the above optimization problem, the optimal wireless transmission parameters (a) can be obtained. * ,ω * ,μ * ).

[0201] For multicast data s m (t) and unicast data s u (t) is overlaid and encoded to obtain the data sent by the base station:

[0202]

[0203] The base station is based on the optimal RIS reflection coefficient Φ * The RIS is controlled to assist in the transmission of the superimposed encoded data.

[0204] Multicast and unicast data are transmitted on the same time-frequency resource through superimposed coding, which improves spectral efficiency. On the other hand, the superimposed coded data signal is relayed in one time slot through real-time reflection of RIS, which further improves spectral efficiency and saves energy consumption for cooperative transmission.

[0205] For NOMA-based RIS-assisted transmission, another implementation of selecting one unicast user and determining radio transmission parameters is as follows: Figure 5 As shown:

[0206] Step 1: Determine the set of candidate unicast users:

[0207] Determine the preset location range θ of the TTI to be scheduled within the multicast group user. thr The unicast users within the TTI form a candidate unicast user set. To reduce selection overhead, optionally, if the multicast user set scheduled for this TTI intersects with the candidate unicast user set, then the intersection is determined as the candidate unicast user set.

[0208] Step 2: Calculate the benefit of each unicast user in the candidate unicast user set participating in cooperative transmission:

[0209] The collaborative benefit of each unicast user in the candidate unicast user set can be expressed as the maximum rate R of the worst multicast user. u,noma The following optimization problem is solved:

[0210]

[0211] st‖ω‖ 2 ≤P max

[0212] |Φ n |=1,n=1,…,N

[0213]

[0214] The line transmission parameters (a) for each unicast user u participating in multicast transmission can be obtained. * ,ω * ,Φ * ) and collaborative benefits.

[0215]

[0216] Among them, D k and G k Let G be the channel coefficient vector from the base station antenna array and the RIS array to the multicast user k, respectively, and H be the channel coefficient matrix from the base station antenna array to the RIS array. k H is the concatenated channel coefficient matrix from the base station to multicast user k via RIS. Φ n P represents the phase coefficient of the RIS element n, and ω is the beamforming vector of the base station transmit antenna. max R is the maximum transmit power of the base station, N is the number of elements in the RIS array, a is the power proportion allocated to multicast services, and R min,u This is to meet the rate requirements of unicast services.

[0217] Step 3: Select the unicast users and wireless transmission parameters that offer the best cooperative transmission benefits:

[0218] The following formula is used to select the unicast user with the best cooperative transmission efficiency:

[0219] u * =argmaxR u,noma

[0220] unicast user u * Corresponding wireless transmission parameters The required wireless transmission parameters.

[0221] Step 4: Overlay encoded unicast and multicast data and transmit them based on the selected wireless transmission parameters:

[0222] For multicast data s m (t) and unicast data By performing overlay encoding, the data transmitted by the base station can be obtained:

[0223]

[0224] The base station is based on the corresponding RIS reflection coefficient The RIS controls the transmission of the superimposed encoded data.

[0225] The signaling flow of the RIS-assisted wireless multicast transmission method of the present invention is as follows: Figure 6 As shown.

[0226] 1) When a user needs a service, they send a service request message to the base station, which carries the service type, indicating whether it is unicast or multicast. Optionally, the user's location information may also be carried.

[0227] 2) Based on service request messages, the base station statistically analyzes user service needs and distribution, and determines a multicast transmission strategy accordingly. The multicast transmission strategy indicates whether to use NOMA transmission.

[0228] 3) The base station notifies the user of the data transmission strategy through a service request response message. The data transmission strategy includes a multicast transmission strategy indication, and optionally, a decoding order indication.

[0229] 4) If it is RIS-assisted transmission based on NOMA, the base station performs superimposed encoding on multicast and unicast user data and controls RIS and data transmission.

[0230] 5) The user processes the received data according to the user data transmission strategy. If it is a RIS-assisted transmission based on NOMA, serial interference cancellation is used to decode the data. If the data transmission strategy includes a decoding order indication, the data is decoded according to the decoding order indication; otherwise, the multicast user decodes its own data. If the decoding fails, serial interference cancellation is performed to decode the unicast user data, cancel the unicast user data, and then decode its own data. The decoding of unicast users is similar to that of multicast users.

[0231] On the other hand, embodiments of the present invention also provide an apparatus for intelligent metasurface-assisted wireless multicast transmission, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method of intelligent metasurface-assisted wireless multicast transmission as described above.

[0232] The device for intelligent metasurface-assisted wireless multicast transmission according to embodiments of the present invention includes a memory and a processor.

[0233] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0234] Memory can include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. ROM can store static data or instructions required by the processor or other modules of the computer. Permanent storage devices can be read-write storage devices. Permanent storage devices can be non-volatile storage devices that retain stored instructions and data even when the computer is powered off. In some embodiments, permanent storage devices use high-capacity storage devices (e.g., magnetic or optical disks, flash memory) as permanent storage devices. In other embodiments, permanent storage devices can be removable storage devices (e.g., floppy disks, optical drives). System memory can be a read-write storage device or a volatile read-write storage device, such as dynamic random access memory. System memory can store some or all of the instructions and data required by the processor during operation. Furthermore, memory can include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks can also be used. In some implementations, the memory may include removable storage devices that are readable and / or writable, such as laser discs (CDs), read-only digital versatile optical discs (e.g., DVD-ROMs, dual-layer DVD-ROMs), read-only Blu-ray discs, ultra-high density optical discs, flash memory cards (e.g., SD cards, mini SD cards, Micro-SD cards, etc.), magnetic floppy disks, etc. Computer-readable storage media do not contain carrier waves or transient electronic signals transmitted wirelessly or via wired connections.

[0235] The memory stores executable code, which, when processed by the processor, can cause the processor to execute some or all of the methods described above.

[0236] On the other hand, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the methods described above.

[0237] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0238] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for intelligent metasurface-assisted wireless multicast transmission, characterized in that, The method includes the following steps: Obtain information on user dissemination needs and user distribution; Based on the user propagation demand information and the user distribution information, a multicast transmission strategy is determined; Based on the multicast transmission strategy, determine the wireless transmission parameters; Based on the wireless transmission parameters, intelligent metasurface-assisted wireless multicast transmission data is obtained; The step of determining the multicast transmission strategy based on the user propagation demand information and the user distribution information includes the following steps: Configure non-orthogonal multiple access conditions; Based on the non-orthogonal multiple access condition information, the user propagation requirement information, and the user distribution information, non-orthogonal multiple access condition judgment information for multicast transmission is obtained; According to the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than the preset threshold, or the unicast users scheduled are not within the preset location range of the multicast group users, then the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission only; otherwise, the multicast transmission strategy is determined to be intelligent metasurface-assisted transmission based on non-orthogonal multiple access. If the multicast transmission strategy is the intelligent metasurface-assisted transmission based on non-orthogonal multiple access, determine the unicast users participating in the cooperative multicast transmission; The step of determining the wireless transmission parameters according to the multicast transmission strategy includes the following steps: According to the multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, the optimal wireless transmission parameters for intelligent metasurface-assisted transmission are obtained by maximizing the rate of the worst multicast user. According to the multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface.

2. The method according to claim 1, characterized in that, The process of obtaining user dissemination demand information and user distribution information includes the following steps: Obtain service request information from communication users; Based on the service request information, the user's location information is obtained, or the relative distance and orientation information between the communication user and the base station is obtained through wireless sensing. The user distribution information is based on the user location information or the relative distance and orientation information between the communication user and the base station. Based on the business request information, user dissemination demand information is statistically obtained; The user communication demand information includes user multicast service demand information.

3. The method according to claim 1, characterized in that, If the multicast transmission strategy is the intelligent metasurface-assisted transmission based on non-orthogonal multiple access, the unicast users participating in the cooperative multicast transmission are determined, including: If the scheduled unicast users are within the preset location range of the multicast group users, then according to the principle of closest location, several potential unicast users are selected from the scheduled unicast users to participate in intelligent metasurface-assisted transmission based on non-orthogonal multiple access. The selected potential unicast users are formed into a potential unicast user set; the number of potential unicast users is an integer greater than zero. When the number of potential unicast users is 1, the potential unicast user is the unicast user whose location is closest to the multicast user. The formula used to obtain the unicast user whose location is closest to the multicast user includes: ； in, The unicast user whose location is closest to the multicast user; The location between the multicast user and the base station; The location between the potential unicast user and the base station; The set of the multicast users; The set of potential unicast users.

4. The method according to claim 1, characterized in that, According to the multicast transmission strategy, if it is intelligent metasurface-assisted transmission only, the optimal wireless transmission parameters for intelligent metasurface-assisted transmission are obtained by maximizing the rate of the worst multicast user. The formulas used include: ； ； ； in, For multicast users; This is the channel coefficient vector from the base station antenna array to the multicast user; The channel coefficient vector from the smart metasurface array to the multicast user; This is the channel coefficient matrix from the base station antenna array to the smart metasurface array; The cascaded channel coefficient matrix from the base station through the smart metasurface to the multicast user; For intelligent metasurface units; This represents the phase coefficient of the intelligent metasurface unit; Beamforming vectors for the base station's transmitting antenna; Let be the phase coefficient vector of the intelligent metasurface; This is the maximum transmit power of the base station; Noise power; The number of cells in the intelligent metasurface array; ( ) represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission only; The set of multicast users.

5. The method according to claim 1, characterized in that, According to the multicast transmission strategy, if it is a smart metasurface-assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters for smart metasurface-assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmit antenna and the phase coefficient vector of the smart metasurface. The formulas used include: ； ； ； ； To be allocated to unicast users The power ratio, For unicast users The speed requirement, Indicates unicast user In unicast users Decoding follows; ( () represents the optimal wireless transmission parameters for intelligent metasurface-assisted transmission based on non-orthogonal multiple access; The set of the multicast users; For a collection of potential unicast users; For the intelligent metasurface array to the unicast user The channel coefficient vector; For base station antenna array to the unicast user The conjugate transpose of the channel coefficient vector; To be allocated to the unicast user The power ratio; For the intelligent metasurface array to the unicast user The channel coefficient vector; For base station antenna array to the unicast user The conjugate transpose of the channel coefficient vector.

6. The method according to claim 1, characterized in that, The formula used to obtain intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters includes: ； in, For multicast data; This is unicast data; To assist in the wireless multicast transmission of data on intelligent metasurfaces; For unicast users; For a collection of potential unicast users; To optimally allocate to the unicast users The power ratio; This is the beamforming vector for the optimal base station transmit antenna.

7. The method according to claim 1, characterized in that, The method further includes: Determine the set of candidate unicast users; Calculate the benefit of each unicast user in the candidate unicast user set participating in cooperative transmission; Based on the benefits of unicast users participating in cooperative transmission, select the unicast user with the best cooperative transmission benefits; The wireless transmission parameters are obtained based on the unicast user with the best cooperative transmission efficiency. The base station transmits data by superimposing encoded unicast and multicast data and based on the wireless transmission parameters.

8. A system for intelligent metasurface-assisted wireless multicast transmission, used to implement the method as described in any one of claims 1 to 7, characterized in that, The system includes: The first module is used to obtain information on user dissemination needs and user distribution; The second module is used to determine a multicast transmission strategy based on the user propagation demand information and the user distribution information. The third module is used to determine the wireless transmission parameters according to the multicast transmission strategy; The fourth module is used to obtain intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters. The fifth module is used to control the wireless multicast transmission of data assisted by the intelligent metasurface.

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