Intelligent metasurface assisted wireless multicast transmission method and system

Abstract

The embodiment of the invention provides an intelligent metasurface-assisted wireless multicast transmission method and system, and belongs to the technical field of mobile communication. The method comprises the following steps: acquiring user propagation demand information and user distribution information; determining a multicast transmission strategy according to the user propagation demand information and the user distribution information; determining a wireless transmission parameter according to the multicast transmission strategy; and obtaining intelligent metasurface-assisted wireless multicast transmission data according to the wireless transmission parameters. According to the method, the multicast transmission rate can be maximized, so that the spectrum efficiency and the multicast system capacity are improved, and the energy consumption is reduced.

Description

Technical Field

[0001] The present 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 Art

[0002] As a new type of wireless service, wireless multicast transmission utilizes the broadcast characteristics of wireless channels. During the transmission process, all users with the same demand for specific service content are treated as a multicast group, and the same information is delivered to all multicast users at the same time. 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 at different locations in 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 condition. If the transmission rate is too high, users with poor channel conditions cannot correctly decode the data. If the transmission rate satisfies the user with the worst channel condition, good fairness can be achieved, but the wireless resource efficiency is too low.

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

[0005] The main purpose of the embodiments of the present application is to provide a method and system for intelligent metasurface-assisted wireless multicast transmission.

[0006] The technical solution adopted by the present invention is:

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

[0008] Obtain user communication demand information and user distribution information;

[0009] Determining a multicast transmission strategy according to the user propagation demand information and the user distribution information;

[0010] Determining wireless transmission parameters according to the multicast transmission strategy;

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

[0012] Furthermore, the obtaining of user communication demand information and user distribution information comprises the following steps:

[0013] Obtaining the service request information of the communication user;

[0014] According to the service request information, the user 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 location information or the relative distance and orientation information between the communication user and the base station is used as the user distribution information;

[0016] According to the business request information, statistics are obtained to obtain user communication demand information;

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

[0018] Further, determining the multicast transmission strategy according to the user propagation demand information and the user distribution information comprises the following steps:

[0019] Setting non-orthogonal multiple access condition information;

[0020] Obtaining non-orthogonal multiple access condition determination information for multicast transmission according to the non-orthogonal multiple access condition information, the user propagation demand information and the user distribution information;

[0021] According to the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than a preset threshold, or the scheduled unicast user is not within the preset azimuth range of the multicast group user, the multicast transmission strategy is determined as only intelligent metasurface assisted transmission, otherwise the multicast transmission strategy is determined as 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] Furthermore, 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 user is within the preset azimuth range of the multicast group user, then according to the principle of closest azimuth, several potential unicast users are selected from the scheduled unicast users to participate in the intelligent metasurface assisted transmission based on non-orthogonal multiple access;

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

[0026] When the number of the potential unicast users is 1, the potential unicast user is regarded as the unicast user closest to the multicast user;

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

[0028]

[0029] Wherein, u* is the unicast user closest to the multicast user;

[0030] θ i is the position between the multicast user and the base station;

[0031] θ u is the position between the potential unicast user and the base station;

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

[0033] Ω u is the potential unicast user set.

[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 only the smart metasurface assists the transmission, the optimal wireless transmission parameters for only the smart metasurface assists the transmission are obtained by maximizing the rate of the worst multicast user;

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

[0037] Further, according to the multicast transmission strategy, if only the intelligent metasurface assists the transmission, the optimal wireless transmission parameters for only the intelligent metasurface assists the transmission are obtained by maximizing the rate of the worst multicast user, and the formula used includes:

[0038]

[0039] st‖ω‖ 2 ≤P max ;

[0040] |Φ n |=1,n=1,…,N;

[0041] Where k is a multicast user; D k is the channel coefficient vector from the base station antenna array to the multicast user; G k is a 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 cascade channel coefficient matrix from the base station to the multicast user through the smart metasurface;

[0044] n is the smart metasurface unit;

[0045] Φ n Represents a phase coefficient of the smart metasurface unit;

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

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

[0048] P max is the maximum transmit power of the base station;

[0049] σ 2 is the noise power;

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

[0051] (ω * ,Φ * ) is the optimal wireless transmission parameter for only smart metasurface-assisted transmission.

[0052] Furthermore, according to the multicast transmission strategy, if it is an intelligent metasurface assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters of the intelligent metasurface assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmitting antenna and the phase coefficient vector of the intelligent metasurface, and the formula used includes:

[0053]

[0054] st‖ω‖ 2 ≤P max

[0055] |Φ n |=1,n=1,…,N

[0056]

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

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

[0059] Furthermore, the intelligent metasurface assisted wireless multicast transmission data is obtained according to the wireless transmission parameters, and the formula used includes:

[0060]

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

[0062] S BS (t) is the smart metasurface-assisted wireless multicast data transmission.

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

[0064] Determining a candidate unicast user set;

[0065] Calculating the benefit of each unicast user in the candidate unicast user set participating in the collaborative transmission;

[0066] According to the benefits of the unicast users participating in the cooperative transmission, selecting the unicast users with the best cooperative transmission benefits;

[0067] Obtaining the wireless transmission parameter according to the unicast user with the best cooperative transmission benefit;

[0068] The unicast data and the multicast data are superimposed and encoded, and based on the wireless transmission parameters, the base station sends data.

[0069] On the other hand, an embodiment of the present invention further provides a system for intelligent metasurface-assisted wireless multicast transmission, the system comprising:

[0070] The first module is used to obtain user communication demand information and user distribution information;

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

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

[0073] The fourth module is used to obtain smart metasurface assisted wireless multicast transmission data according to the wireless transmission parameters;

[0074] The fifth module is used to control the intelligent metasurface to assist in transmitting wireless multicast data.

[0075] The embodiments of the present application include at least the following beneficial effects: The present application provides a method and system for intelligent metasurface-assisted wireless multicast transmission. The present invention obtains 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; obtains intelligent metasurface-assisted wireless multicast transmission data based on the wireless transmission parameters. The present invention can maximize the rate of multicast transmission, thereby improving spectrum efficiency and multicast system capacity, and saving energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

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

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

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

[0081] Figure 6 It is a schematic diagram of the signaling process of RIS-assisted wireless multicast transmission provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the 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 the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

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

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

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

[0086] The present invention proposes a wireless multicast transmission method assisted by a reconfigurable intelligent surface (RIS), which uses RIS to construct the channel environment of wireless multicast users, selects appropriate unicast users to participate in cooperative multicast transmission, and uses non-orthogonal multiple access (NOMA) to superimpose and encode the data of multicast users and unicast users. Users use successive interference cancellation (SIC) to eliminate mutual interference. By controlling the beamforming of the base station transmitting antenna and RIS, the multicast transmission rate is maximized, thereby improving the spectrum efficiency and multicast system capacity, and saving energy consumption.

[0087] The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0088] On the one hand, an embodiment of the present invention provides a method for intelligent metasurface assisted wireless multicast transmission, referring to Figure 1 , the method comprises the following steps:

[0089] S100, obtaining user communication demand information and user distribution information;

[0090] S200, determining a multicast transmission strategy according to user transmission demand information and user distribution information;

[0091] S300, determining wireless transmission parameters according to the multicast transmission strategy;

[0092] S400. Obtaining intelligent metasurface-assisted wireless multicast transmission data according to wireless transmission parameters.

[0093] The embodiment of the present invention discloses step S100 of acquiring user communication demand information and user distribution information, including the following steps:

[0094] S110, obtaining service request information of the communication user;

[0095] S120, obtaining user location information according to the service request information or obtaining relative distance and orientation information between the communication user and the base station through wireless sensing;

[0096] S130, using user location information or relative distance and orientation information between a communication user and a base station as user distribution information;

[0097] S140, obtaining user communication demand information based on the business request information;

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

[0099] The embodiment of the present invention discloses that step S200 determines a multicast transmission strategy according to user propagation demand information and user distribution information, including the following steps:

[0100] S210, setting non-orthogonal multiple access condition information;

[0101] S220, obtaining non-orthogonal multiple access condition determination information for multicast transmission according to the non-orthogonal multiple access condition information, the user propagation demand information, and the user distribution information;

[0102] S230, according to the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than a preset threshold, or the scheduled unicast user is not within the preset azimuth range of the multicast group user, the multicast transmission strategy is determined as only intelligent metasurface assisted transmission, otherwise the multicast transmission strategy is determined as 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 unicast users participating in the cooperative multicast transmission.

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

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

[0106] S242, forming 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 closest to the multicast user;

[0108] S244, the formula used to obtain the unicast user closest to the multicast user includes:

[0109]

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

[0111] θ i is the position between the multicast user and the base station;

[0112] θ u is the position between the potential unicast user and the base station;

[0113] Ω m is the set of multicast users;

[0114] Ω u A collection of potential unicast users.

[0115] The embodiment of the present invention discloses that step S300 determines wireless transmission parameters according to a multicast transmission strategy, including the following steps:

[0116] S310, according to the multicast transmission strategy, if only the intelligent metasurface assists the transmission, then by maximizing the rate of the worst multicast user, the optimal wireless transmission parameters for only the intelligent metasurface assists the transmission are obtained;

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

[0118] The embodiment of the present invention discloses that in step S310, according to the multicast transmission strategy, if only the intelligent metasurface assists the transmission, the optimal wireless transmission parameters for only the intelligent metasurface assists the transmission are obtained by maximizing the rate of the worst multicast user, and the formula used includes:

[0119]

[0120] st‖ω‖ 2 ≤P max ;

[0121] |Φ n |=1,n=1,…,N;

[0122] Where k is a multicast user; D k is the channel coefficient vector from the base station antenna array to the multicast user; G k is the channel coefficient vector from the smart metasurface array to the multicast users;

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

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

[0125] n is the smart metasurface unit;

[0126] Φ n represents the phase coefficient of the smart metasurface unit;

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

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

[0129] σ 2 is the noise power;

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

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

[0132] (ω * ,Φ * ) is the optimal wireless transmission parameter for only smart metasurface-assisted transmission.

[0133] The embodiment of the present invention discloses that in step S320, according to the multicast transmission strategy, if it is an intelligent metasurface assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters of the intelligent metasurface assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmitting antenna and the phase coefficient vector of the intelligent metasurface, and the formula used includes:

[0134]

[0135] st‖ω‖ 2 ≤P max

[0136] |Φ n |=1,n=1,…,N

[0137]

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

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

[0140] As an optional implementation, D k and G k are the channel coefficient vectors from the base station antenna array and the RIS array to the multicast user k, H is the channel coefficient matrix from the base station antenna array to the RIS array, G k H is the cascade channel coefficient matrix from the base station to multicast user k through RIS. Φ n represents the phase coefficient of RIS unit n, and ω is the beamforming vector of the base station transmitting antenna. max is the maximum transmission power of the base station, N is the number of elements in the RIS array, σ 2 is the noise power. l>u means that unicast user l is decoded after unicast user u.

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

[0142] The embodiment of the present invention discloses that step S400 obtains the intelligent metasurface assisted wireless multicast transmission data according to the wireless transmission parameters, and the formula used includes:

[0143]

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

[0145] S BS (t) is the smart metasurface-assisted wireless multicast data transmission.

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

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

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

[0149] S500, determining a candidate unicast user set;

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

[0151] S700, selecting a unicast user with the best cooperative transmission benefit according to the benefit of the unicast user participating in the cooperative transmission;

[0152] S800, obtaining wireless transmission parameters according to the unicast user with the best cooperative transmission benefit;

[0153] S900: Superimpose and encode unicast data and multicast data, and obtain base station send data based on wireless transmission parameters.

[0154] On the other hand, an embodiment of the present invention further provides a system for intelligent metasurface-assisted wireless multicast transmission, the system comprising:

[0155] The first module is used to obtain user communication demand information and user distribution information;

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

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

[0158] The fourth module is used to obtain smart metasurface assisted wireless multicast transmission data according to the wireless transmission parameters;

[0159] The fifth module is used to control the intelligent metasurface to assist in transmitting wireless multicast data.

[0160] As an optional implementation, the present invention solves the problem of improving the system capacity and spectrum efficiency of 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 appropriate ones to participate in multicast transmission from the scheduled unicast users to form a cooperative transmission group.

[0161] The base station adopts superposition coding for the multicast data and unicast data of the cooperative transmission group, and sends the coded data in the TTI, while controlling the phase shift of the RIS and cooperatively reflecting the superposition coded data signal.

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

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

[0164] 1) The base station counts the user's multicast service needs based on the communication user's service requests.

[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 the multicast services of user i and user k are the same.

[0168] 2) The base station determines the user distribution through wireless sensing.

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

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

[0171] Methods for determining multicast transmission strategies are as follows: Figure 4 Said:

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

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

[0174] Conditions for RIS-assisted transfer only:

[0175] |Ω m |>N thr

[0176] or

[0177]

[0178] Among them, θ i and θ u are the positions of multicast user i and unicast user u to the base station, Ω s is the set of unicast users scheduled in 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 scheduled this time thr According to the principle of closest position, M unicast users are selected to participate in NOMA transmission, forming a participating unicast user set Ω u , M is an integer greater than zero. 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 perform spatial multiplexing with multicast users, thereby improving the efficiency of spatial resources.

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

[0184] 1) Determine the radio 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 multicast user:

[0186]

[0187] st‖ω‖ 2 ≤P max

[0188] |Φ n |=1,n=1,…,N

[0189] Among them, D k and G k are the channel coefficient vectors from the base station antenna array and the RIS array to the multicast user k, H is the channel coefficient matrix from the base station antenna array to the RIS array, G k H is the cascade channel coefficient matrix from the base station to multicast user k through RIS. Φ nrepresents the phase coefficient of RIS unit n, and ω is the beamforming vector of the base station transmitting antenna. max is the maximum transmission power of the base station, σ 2 is the noise power, and N is the number of elements in the RIS array.

[0190] By using alternating iteration combined with other optimization algorithms, such as semi-definite relaxation, semi-definite programming, etc., to solve the above optimization problem, the optimal wireless transmission parameters (ω * ,Φ * ).

[0191] The base station is based on the optimal RIS reflection coefficient Φ * Control RIS and beamform based on the optimal transmit antenna ω * , send the data of the multicast group.

[0192] Multicast data signals are reflected in real time by RIS, and relay cooperative transmission is completed in one time slot, which improves the spectrum efficiency of multicast transmission.

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

[0194] For RIS-assisted multicast transmission based on NOMA, the beamforming ω of the base station's transmitting antenna and the phase coefficient Φ of RIS are jointly optimized to maximize the rate of the worst 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 are the channel coefficient vectors from the base station antenna array and the RIS array to the multicast user k, H is the channel coefficient matrix from the base station antenna array to the RIS array, G k H is the cascade channel coefficient matrix from the base station to multicast user k through RIS. Φ n represents the phase coefficient of RIS unit n, and ω is the beamforming vector of the base station transmitting antenna. max is the maximum transmission power of the base station, N is the number of elements in the RIS array, σ 2 is the noise power. l>u means that unicast user l is decoded after unicast user u.

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

[0201] For multicast data m (t) and unicast data s u (t) Perform superposition coding to obtain the data sent by the base station:

[0202]

[0203] The base station is based on the optimal RIS reflection coefficient Φ * Controlling the RIS to assist in transmitting the superimposed coded data.

[0204] Multicast data and unicast data are sent in the same time-frequency resources through superposition coding, which improves spectrum efficiency. On the other hand, the superposition coded data signal is reflected in real time by RIS, and relay cooperative transmission is completed in one time slot, which further improves spectrum efficiency and saves energy consumption of cooperative transmission.

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

[0206] Step 1: Determine the candidate unicast user set:

[0207] Determine the preset position range θ of the user in the multicast group where the TTI is scheduled thr The unicast users in the TTI form a candidate unicast user set. To reduce selection overhead, optionally, if the multicast user set scheduled in the TTI has an intersection with the candidate unicast user set, 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 cooperation benefit of each unicast user in the candidate unicast user set can be the maximum rate R of the worst multicast user. u,noma , by solving the following optimization problem:

[0210]

[0211] st‖ω‖ 2 ≤P max

[0212] |Φ n |=1,n=1,…,N

[0213]

[0214] The line transmission parameters (a) of 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 are the channel coefficient vectors from the base station antenna array and the RIS array to the multicast user k, H is the channel coefficient matrix from the base station antenna array to the RIS array, G k H is the cascade channel coefficient matrix from the base station to multicast user k through RIS. Φ n represents the phase coefficient of RIS unit n, and ω is the beamforming vector of the base station transmitting antenna. max is the maximum transmission power of the base station, N is the number of units in the RIS array, a is the power ratio allocated to multicast services, R min,u The rate requirement for unicast services.

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

[0218] The unicast user with the best cooperative transmission benefit is selected by the following formula:

[0219] u * = argmaxR u,noma

[0220] Unicast user u * Corresponding wireless transmission parameters are the required wireless transmission parameters.

[0221] Step 4: Superposition encode unicast and multicast data and send based on the selected wireless transmission parameters:

[0222] For multicast data m (t) and unicast data Perform superposition coding to obtain the data sent by the base station:

[0223]

[0224] The base station is based on the corresponding RIS reflection coefficient The RIS is controlled to assist in transmitting the superimposed encoded data.

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

[0226] 1) When a user has a service, a service request message is sent to the base station, which carries the service type, indicating unicast or multicast, and optionally, the user location information.

[0227] 2) The base station counts the user service requirements and distribution based on the service request message, and determines the 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 the service request response message, wherein the data transmission strategy includes a multicast transmission strategy indication and, optionally, a decoding order indication.

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

[0230] 5) The user processes the received data based on the user data transmission strategy. If it is 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 decoding is performed according to the decoding order indication. Otherwise, the multicast user decodes its own data. If it fails, serial interference cancellation decoding is performed to decode the unicast user data and eliminate the unicast user data before decoding its own data. The decoding of the unicast user is similar to that of the multicast user.

[0231] On the other hand, an embodiment of the present invention also provides a device 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, the method for intelligent metasurface-assisted wireless multicast transmission as described above is implemented.

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

[0233] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0234] The memory may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. Among them, ROM can store static data or instructions required by the processor or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory may 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 may also be used. In some embodiments, the memory may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0235] The memory stores executable codes, and when the executable codes are processed by the processor, the processor can execute part or all of the methods described above.

[0236] On the other hand, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above method.

[0237] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium 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 include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0238] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for intelligent metasurface assisted wireless multicast transmission, characterized in that: The method comprises the following steps: Obtain user communication demand information and user distribution information; Determining a multicast transmission strategy according to the user propagation demand information and the user distribution information; Determining wireless transmission parameters according to the multicast transmission strategy; According to the wireless transmission parameters, intelligent metasurface-assisted wireless multicast transmission data is obtained.

2. The method according to claim 1, characterized in that: The step of obtaining user communication demand information and user distribution information comprises the following steps: Obtaining the service request information of the communication user; According to the service request information, the user 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 location information or the relative distance and orientation information between the communication user and the base station is used as the user distribution information; According to the business request information, statistics are obtained to obtain user communication demand information; The user broadcast demand information includes user multicast service demand information.

3. The method according to claim 1, characterized in that Determining a multicast transmission strategy according to the user propagation demand information and the user distribution information comprises the following steps: Setting non-orthogonal multiple access condition information; Obtaining non-orthogonal multiple access condition determination information for multicast transmission according to the non-orthogonal multiple access condition information, the user propagation demand information and the user distribution information; According to the non-orthogonal multiple access condition judgment information, if the number of users in the multicast group is greater than a preset threshold, or the scheduled unicast user is not within the preset azimuth range of the multicast group user, the multicast transmission strategy is determined as only intelligent metasurface assisted transmission, otherwise the multicast transmission strategy is determined as 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.

4. The method according to claim 3, characterized in that 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: If the scheduled unicast user is within the preset azimuth range of the multicast group user, then according to the principle of closest azimuth, several potential unicast users are selected from the scheduled unicast users to participate in the intelligent metasurface assisted transmission based on non-orthogonal multiple access; The selected potential unicast users form a potential unicast user set; the number of the potential unicast users is an integer greater than zero; When the number of the potential unicast users is 1, the potential unicast user is regarded as the unicast user closest to the multicast user; The formula used to obtain the unicast user closest to the multicast user includes: Among them, u * The unicast user closest to the multicast user; θ i is the position between the multicast user and the base station; θ u is the position between the potential unicast user and the base station; Ω m is the set of multicast users; Ω u is the potential unicast user set.

5. The method according to claim 1, characterized in that: Determining the wireless transmission parameters according to the multicast transmission strategy comprises the following steps: According to the multicast transmission strategy, if only the smart metasurface assists the transmission, the optimal wireless transmission parameters for only the smart metasurface assists the transmission are obtained by maximizing the rate of the worst multicast user; According to the multicast transmission strategy, if it is an intelligent metasurface assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters of the intelligent metasurface assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmitting antenna and the phase coefficient vector of the intelligent metasurface.

6. The method according to claim 5, characterized in that According to the multicast transmission strategy, if only the intelligent metasurface assists the transmission, the optimal wireless transmission parameters for only the intelligent metasurface assists the transmission are obtained by maximizing the rate of the worst multicast user, and the formula used includes: st‖ω‖ 2 ≤P max ; |F n |=1,n=1,…,N; Where k is a multicast user; D k is the channel coefficient vector from the base station antenna array to the multicast user; G k is a channel coefficient vector from the smart metasurface array to the multicast user; H is the channel coefficient matrix from the base station antenna array to the smart metasurface array; G k H is the cascade channel coefficient matrix from the base station to the multicast user through the smart metasurface; n is the smart metasurface unit; Φ n represents a phase coefficient of the smart metasurface unit; ω is the beamforming vector of the base station transmitting antenna; Φ is the phase coefficient vector of the smart metasurface; P max is the maximum transmit power of the base station; σ 2 is the noise power; N is the number of units of the smart metasurface array; (ω * ,Φ * ) is the optimal wireless transmission parameter for only smart metasurface-assisted transmission.

7. The method according to claim 5, characterized in that According to the multicast transmission strategy, if it is an intelligent metasurface assisted transmission based on non-orthogonal multiple access, the optimal wireless transmission parameters of the intelligent metasurface assisted transmission based on non-orthogonal multiple access are obtained by jointly optimizing the beamforming vector of the base station transmitting antenna and the phase coefficient vector of the intelligent metasurface. The formula used includes: st‖ω‖ 2 ≤P max ; |F n |=1,n=1,…,N; α u is the power ratio allocated to unicast user u, R min,u is the rate requirement of unicast user u, l>u means that unicast user l decodes after unicast user u; (a * ,ω * ,Φ * ) is the optimal wireless transmission parameter for smart metasurface-assisted transmission based on non-orthogonal multiple access.

8. The method according to claim 1, characterized in that The formula used to obtain the intelligent metasurface assisted wireless multicast transmission data according to the wireless transmission parameters includes: Among them, s m (t) is multicast data; s u (t) is unicast data; S BS (t) is the smart metasurface-assisted wireless multicast data transmission.

9. The method according to claim 1, characterized in that: The method further comprises: Determining a candidate unicast user set; Calculating the benefit of each unicast user in the candidate unicast user set participating in the collaborative transmission; According to the benefits of the unicast users participating in the cooperative transmission, selecting the unicast users with the best cooperative transmission benefits; Obtaining the wireless transmission parameter according to the unicast user with the best cooperative transmission benefit; The unicast data and the multicast data are superimposed and encoded, and based on the wireless transmission parameters, the base station sends data.

10. A system for intelligent metasurface-assisted wireless multicast transmission, characterized in that: The system comprises: The first module is used to obtain user communication demand information and user distribution information; The second module is used to determine a multicast transmission strategy according to the user propagation demand information and the user distribution information; A third module is used to determine wireless transmission parameters according to the multicast transmission strategy; The fourth module is used to obtain smart metasurface assisted wireless multicast transmission data according to the wireless transmission parameters; The fifth module is used to control the intelligent metasurface to assist in transmitting wireless multicast data.

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