Information processing method, communication equipment and computer readable storage medium

Abstract

Provided is an information processing method, the method comprising: a first access point acquiring channel state information of a plurality of user equipments, the plurality of user equipments comprising reflective user equipments and transmissive user equipments, the reflective user equipments being devices that communicate by using reflective functions of a plurality of omnidirectional metasurfaces, and the transmissive user equipments being devices that communicate by using reflective functions of a plurality of omnidirectional metasurfaces; the transmission user equipment is equipment for performing communication by utilizing the transmission functions of the plurality of omnidirectional metasurfaces; optimizing the first precoding vectors of the plurality of pieces of user equipment to obtain second precoding vectors; and sending the channel state information and the second precoding vector to the network equipment. The invention further provides communication equipment and a computer readable storage medium. The technical problem of how to design the precoding vector, the transflective phase and the transflective amplitude in the scene of omnidirectional metasurface-assisted non-cell network communication is at least solved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to an information processing method, a communication device, and a computer-readable storage medium. Background Art

[0002] In the face of the needs of large-scale connectivity, high spectrum efficiency, and highly reliable and energy-saving communications in future communication networks, cell-free large-scale multiple-input multiple-output (MIMO) system networks and reconfigurable intelligent metasurfaces (RIS) are key candidate technologies. Intelligent metasurfaces include reflective intelligent metasurfaces and omnidirectional metasurfaces (IOS). Reflective intelligent metasurfaces have the function of controlling signals for reflection, and omnidirectional metasurfaces have the dual functions of controlling signals for reflection and transmission. Compared with reflective intelligent metasurfaces, omnidirectional metasurfaces have a wider coverage range and can greatly improve system capacity. In a typical application scenario, omnidirectional metasurfaces can be introduced into cell-free networks. Multiple access points (APs) in cell-free networks can work together with omnidirectional metasurfaces to interact with network devices (such as core network devices), thereby providing communication services for multiple user devices.

[0003] In the scenario of omnidirectional metasurface assisted cell-free network, it is usually necessary to design the precoding vector of the access point and the transmission and reflection phase information and transmission and reflection amplitude information of the omnidirectional metasurface. However, there is still a lack of an effective technical solution to achieve this goal. Summary of the invention

[0004] The present application provides an information processing method, a communication device and a computer-readable storage medium, which are used to solve the problem of how to design the precoding vector and the phase information and amplitude information of the omnidirectional metasurface in the scenario of omnidirectional metasurface-assisted cell-free network communication.

[0005] To solve the above technical problems, this application is implemented as follows:

[0006] In a first aspect, an information processing method is provided, which is applied to a first access point, and includes:

[0007] Acquire channel state information of multiple user devices, wherein the multiple user devices include reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate using the reflective functions of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive functions of the multiple omnidirectional metasurfaces;

[0008] Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector;

[0009] The channel state information and the second precoding vector are sent to a network device.

[0010] In a second aspect, an information processing method is provided, which is applied to a network device, comprising:

[0011] receiving channel state information and second precoding vectors of multiple user equipments sent by multiple access points, the multiple user equipments including reflective user equipments and transmissive user equipments, the reflective user equipments are equipments that communicate by using the reflective functions of multiple omnidirectional metasurfaces, the transmissive user equipments are equipments that communicate by using the transmissive functions of the multiple omnidirectional metasurfaces, and the second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user equipments by the multiple access points;

[0012] According to the channel state information and the second precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized.

[0013] In a third aspect, a communication device is provided, comprising:

[0014] processor;

[0015] a memory for storing instructions executable by the processor;

[0016] The processor is configured to execute the instructions to implement the method as described in the first aspect or the second aspect.

[0017] In a fourth aspect, a computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a communication device, the communication device is enabled to execute the method described in the first aspect or the second aspect.

[0018] Based on the technical solution provided in the embodiment of the present application, in the scenario of omnidirectional metasurface assisted cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be realized through the interaction between multiple access points in the cell-free network and the network equipment, wherein the multiple access points can optimize the precoding vector, and the network equipment can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in the scenario of omnidirectional metasurface assisted cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be realized. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly realized by the interactive collaboration between the network equipment and the multiple access points, the computational complexity of the network equipment can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0020] Figure 1 This is a schematic diagram of a scenario of an omnidirectional metasurface assisted cell-free network according to an embodiment of the present application;

[0021] Figure 2 It is a flowchart of an information processing method according to an embodiment of the present application;

[0022] Figure 3 It is a flowchart of an information processing method according to an embodiment of the present application;

[0023] Figure 4 This is a schematic diagram of interaction between network elements in an omnidirectional metasurface-assisted cell-free network according to an embodiment of the present application;

[0024] Figure 5 This is a schematic diagram of interaction between network elements in an omnidirectional metasurface-assisted cell-free network according to an embodiment of the present application;

[0025] Figure 6 It is a schematic diagram of the performance effect of an information processing method according to an embodiment of the present application under different AP transmit powers;

[0026] Figure 7 This is a schematic diagram of the performance effect of an information processing method according to an embodiment of the present application under different numbers of IOS units;

[0027] Figure 8is a schematic diagram of the structure of a communication device according to an embodiment of the present application;

[0028] Fig. 9 is a schematic diagram of the structure of an information processing device according to an embodiment of the present application;

[0029] Fig.10 It is a structural diagram of an information processing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] With the rapid development of wireless communication networks, the demand for data transmission is growing exponentially. Technologies such as large-scale multiple-input multiple-output (MIMO), millimeter wave communication, and ultra-dense networks under 5G have greatly improved network capacity. However, they also face problems of high energy consumption and high costs. In order to support the development of green and energy-saving networks in the future, reconfigurable intelligent metasurfaces (RIS) are currently receiving widespread attention and have become one of the key technologies for 6G. Through the assistance of intelligent metasurfaces in wireless communication networks, coverage enhancement and capacity improvement can be achieved. At the same time, another form of metasurface has also emerged, the omnidirectional metasurface (IOS), which has great potential to increase system capacity compared to traditional intelligent metasurfaces.

[0031] The omnidirectional metasurface can also be called a smart metasurface that realizes both transmission and reflection (Simultaneously transmitting and reflecting RIS, STAR-RIS). It has the dual functions of controlling signal reflection and transmission, so that the coverage range can be extended to the entire space. In addition, the omnidirectional metasurface can adjust the phase of the reflected or transmitted signal and the power ratio between the reflected and transmitted signals to produce appropriate beamforming. Therefore, compared with the smart metasurfaces that can only achieve half-space communication coverage by reflecting or transmitting alone, the omnidirectional metasurface provides new degrees of freedom for expanding communication coverage, enhancing received signal strength, and improving the service quality of communication links.

[0032] At present, there are related studies discussing several different working modes of omnidirectional metasurfaces. The first is that the omnidirectional metasurface unit can achieve energy splitting, that is, the unit array can reflect and transmit at the same time. The second is mode switching, that is, the unit array is divided into two groups: transmission mode and reflection mode. The third is time splitting, that is, switching between transmission and reflection in different time dimensions. Considering the limitations of time synchronization and the flexibility of hardware, most of the current related research is based on the energy splitting mode. However, related studies have proposed that according to electromagnetic theory, for completely passive and lossless omnidirectional metasurfaces, there is a constraint that the reflection phase is coupled with the transmission phase, and phase independent control cannot be fully achieved. However, most of the current system optimization work does not consider this constraint model. In addition, in the scenario of omnidirectional metasurface-assisted cell-free networks, in addition to the need to design the phase information of the omnidirectional metasurface, it is also necessary to design the amplitude information of the omnidirectional metasurface and the precoding vectors of multiple access points. However, there is currently a lack of an effective technical solution to achieve such a technical goal.

[0033] The embodiment of the present application provides an information processing method, an electronic device, and a computer-readable storage medium. In the scenario of omnidirectional metasurface assisted cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be realized by multiple access points in the cell-free network interacting with the network device, wherein the multiple access points can optimize the precoding vector, and the network device can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, the design of the precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information can be realized in the scenario of omnidirectional metasurface assisted cell-free network communication. In addition, since the design of the precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information can be jointly realized by the interactive collaboration between the network device and the multiple access points, the computational complexity of the network device can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed. Furthermore, when optimizing the phase information of the omnidirectional metasurface, the phase coupling constraint between the reflection phase and the transmission phase is also taken into account, so that independent control of the phase can be achieved.

[0034] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in this application will be described clearly and completely below in conjunction with the drawings in one or more embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0035] The terms "first", "second", etc. in the present application and claims are used to distinguish similar objects, and are not used to describe a particular order or precedence. It should be understood that the data used in this way can be interchanged where appropriate so that the present application can be implemented in an order other than those illustrated or described herein. In addition, "and / or" in the present application and claims means at least one of the connected objects, and the character " / " generally means that the objects associated with each other are in an "or" relationship.

[0036] The following is a detailed description of the technical solutions provided by the embodiments of the present application in conjunction with the accompanying drawings. It should be noted that in the embodiments of the present application, RIS and smart metasurface refer to smart metasurfaces with reflection or transmission functions, and IOS and omnidirectional metasurface refer to smart metasurfaces with both reflection and transmission functions.

[0037] Figure 1 This is a schematic diagram of a scenario of an omnidirectional metasurface assisted cell-free network according to an embodiment of the present application.

[0038] Figure 1 The network shown includes multiple user devices, multiple access points (APs), multiple omnidirectional metasurfaces (IOSs), and network devices. The multiple omnidirectional metasurfaces include multiple units with reflection and transmission functions, and each omnidirectional metasurface may correspond to a controller ( Figure 1 (not shown), each controller can adjust the reflection phase and reflection amplitude of the corresponding omnidirectional metasurface. Multiple user devices and multiple access points can each have multiple transceiver antennas. The network device can be a core network or a 5G centralized unit (CU), etc.

[0039] exist Figure 1 In the network shown, multiple omnidirectional metasurfaces can assist multiple access points to collaboratively serve multiple user devices. The multiple user devices include reflective user devices and transmissive user devices. The reflective user devices are user devices that communicate using the reflection function of the omnidirectional metasurface, that is, Figure 1 The user equipment in the system is served by the reflected signals of multiple omnidirectional metasurfaces and multiple access points. The transmission user equipment is the user equipment that communicates by using the transmission function of the omnidirectional metasurface, that is, Figure 1 A user device served by the transmission signals of multiple omnidirectional metasurfaces. Among them, the reflective user device can receive the direct connection signals of multiple access points and the reflected signals of multiple omnidirectional metasurfaces, and the transmissive user device can only receive the transmitted signals of multiple omnidirectional metasurfaces due to the occlusion of the direct connection link. In an embodiment of the present application, the network device can coordinate all access points and all omnidirectional metasurfaces to achieve signal enhancement through precoding design and transmission and reflection amplitude and phase design, so as to maximize the system capacity, thereby better providing communication services for multiple user devices.

[0040] Figure 2 It is a flowchart of an information processing method according to an embodiment of the present application. Figure 2 The information processing method shown can be applied to Figure 1 In other words, the information processing method can be performed by installing any access point Figure 1 The software or hardware in any of the access points shown may be executed, and for ease of distinction, may be represented by the first access point. Figure 2 The information processing method shown is as follows.

[0041] S202: Acquire channel state information of multiple user devices, where the multiple user devices include reflective user devices and transmissive user devices. The reflective user devices are devices that communicate using the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive function of multiple omnidirectional metasurfaces.

[0042] The multiple user devices here can be Figure 1 The multiple user devices shown include reflective user devices and transmissive user devices. The channel state information (CSI) of the multiple user devices may be the downlink channel state information of the multiple user devices when the first access point, with the assistance of multiple omnidirectional metasurfaces, performs downlink communication with the multiple user devices. The channel state information of the reflective user device includes the channel state information of the direct channel between the first access point and the reflective user device, and the channel state information of the cascade channel between the first access point, multiple omnidirectional metasurfaces and the reflective user device. The channel state information of the transmissive user device includes the channel state information of the cascade channel between the first access point, multiple omnidirectional metasurfaces and the reflective user device.

[0043] When acquiring channel state information of multiple user equipments, the same method may be used for each user equipment to acquire the channel state information. Optionally, as an embodiment, for each user equipment, the channel state information of the user equipment may be acquired by the following steps:

[0044] A pilot signal is sent to the user equipment.

[0045] Receive channel state information fed back by the user equipment according to the pilot signal.

[0046] Specifically, when it is necessary to obtain channel state information, the first access point can send a pilot signal to the user equipment. For the reflective user equipment, the pilot signal can be sent to the reflective user equipment through the first channel and the second channel, the first channel is the direct channel between the first access point and the reflective user equipment, and the second channel is the cascade channel between the first access point, multiple omnidirectional metasurfaces and the reflective user equipment (including the direct channel between the first access point and multiple omnidirectional metasurfaces, and the direct channel between multiple omnidirectional metasurfaces and the user equipment). For the transmissive user equipment, the pilot signal can be sent to the transmissive user equipment through the third channel, and the third channel is the cascade channel between the first access point, multiple omnidirectional metasurfaces and the transmissive user equipment.

[0047] After receiving the pilot signal, the user equipment can perform channel estimation on the first channel and the second channel for the reflection user equipment, and obtain the channel state information of the reflection user equipment according to the channel estimation result. For the transmission user equipment, channel estimation can be performed on the third channel, and obtain the channel state information of the transmission user equipment according to the channel estimation result. After obtaining the channel state information, the user equipment can send the channel state information to the first access point, so that the first access point can obtain the channel state information corresponding to a user equipment.

[0048] After the first access point obtains the channel state information corresponding to one user equipment through the above method, it can obtain the channel state information corresponding to other user equipment through the same method, thereby obtaining the channel state information corresponding to multiple user equipments.

[0049] S204: Optimize the first precoding vectors of the multiple user equipments to obtain a second precoding vector.

[0050] The first precoding vector is a downlink precoding vector used by the first access point when performing downlink communications with multiple user devices. In an embodiment of the present application, the first precoding vector can be obtained by the first access point through initialization, that is, the first precoding vector is a set of initial precoding vectors designed by the first access point for multiple user devices. The specific implementation method of the first access point initializing the first precoding vector can refer to the specific implementation in the related art, which will not be described in detail here. Alternatively, the first precoding vector can also be sent to the first access point by the network device. The method for obtaining the first precoding vector is not specifically limited here. Among them, the first precoding vector is not the optimal precoding vector, and it needs to be optimized to obtain the optimized second precoding vector.

[0051] It should be noted that in the embodiment of the present application, the optimization problem of the first precoding vector is a non-convex problem and is not easy to solve. Therefore, when optimizing the first precoding vector, the optimization problem can be converted into an easy-to-solve convex problem to achieve the optimization of the first precoding vector.

[0052] Optionally, as an embodiment, when optimizing first precoding vectors of multiple user equipments to obtain second precoding vectors, the following steps may be included:

[0053] Acquire first information, where the first information includes a receiving vector, a weight vector, precoding cross information between multiple access points, and transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces;

[0054] The first precoding vector is optimized according to the first information to obtain a second precoding vector.

[0055] The receiving vector and weight vector in the first information are auxiliary vectors introduced to optimize the precoding vector. The receiving vector may be a receiving vector of the user equipment when receiving a downlink signal. For example, the receiving vector may be a linear receiving filter vector on the user equipment side. The weight vector is also a vector for the user equipment, corresponding to the receiving vector, and can characterize the weight information of the user equipment receiving the downlink signal. The transmission and reflection phase information of multiple omnidirectional metasurfaces includes transmission phase information and reflection phase information, and the transmission and reflection amplitude information includes transmission amplitude information and reflection amplitude information. When acquiring the first information, optionally, the first access point may obtain the first information by initialization, or the first access point may obtain the first information from a network device, which is not specifically limited here. After acquiring the first information, the first precoding vector may be optimized according to the first information.

[0056] Optionally, as an embodiment, optimizing the first precoding vector according to the first information to obtain the second precoding vector may include the following steps:

[0057] Determine the objective function according to the reception vector, the weight vector, the precoding cross information, the transmission reflection phase information and the transmission reflection amplitude information in the first information;

[0058] The first precoding vector is optimized according to the objective function to obtain a second precoding vector.

[0059] The objective function refers to a function used to optimize the first precoding vector, and may also be referred to as an optimization objective expression of the precoding vector (or precoding matrix). The objective function is a convex problem and is easy to solve.

[0060] In one implementation, when determining the objective function according to the reception vector, the weight vector, the precoding cross information, the transmission reflection phase information, and the transmission reflection amplitude information, the following S2041 to S2043 may be included.

[0061] S2041: Under the transmission power constraint and the transmission constraint of the omnidirectional metasurface, a user sum rate maximization problem is constructed according to the first precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information to obtain a first function.

[0062] The transmission power constraint condition refers to the transmission power constraint condition of the first access point, and specifically, when the first access point sends downlink information to multiple user devices, the actual transmission power of the first access point needs to be less than or equal to the maximum transmission power of the first access point. The transmission constraint condition of the omnidirectional metasurface refers to the constraint condition that the units in the omnidirectional metasurface need to meet when multiple omnidirectional metasurfaces reflect and transmit received signals. Among them, the transmission constraints of multiple omnidirectional metasurfaces may be different under different scenario requirements. Optionally, in one implementation, the transmission constraint condition may include a phase coupling constraint condition and an amplitude constraint condition. In another implementation, the transmission constraint condition may include an amplitude phase constraint condition, but does not include a phase coupling constraint condition, that is, the phase coupling constraint is not considered.

[0063] Under the transmission power constraint condition and the transmission constraint condition of multiple omnidirectional metasurfaces, a maximum weighted sum rate optimization problem can be constructed according to the first precoding vector, the transmission reflection phase information and the transmission reflection amplitude information to obtain the first function. The first function is related to the first precoding vector, the weighting coefficients of multiple user equipments, the signal to interference noise ratio of the received signals of the multiple user equipments, the transmission reflection phase information and the transmission reflection amplitude information of the multiple omnidirectional metasurfaces, and is constrained by the transmission power constraint condition and the transmission constraint condition of the multiple omnidirectional metasurfaces.

[0064] It should be noted that the first function is a non-convex problem and is not easy to solve. Therefore, after obtaining the first function, it needs to be transformed through the following S2042 and S2043.

[0065] S2042: According to the receiving vector and the weight vector, the user sum rate maximization problem is equivalently converted into a mean square error minimization problem, and the first function is equivalently converted into a second function.

[0066] When transforming the first function, the relationship between the weighted rate sum of multiple user devices (i.e., the rate obtained by weighted summing the rate of each user device and the weighting coefficient) and the summed mean square error (i.e., the error obtained by weighted summing the mean square errors of the rate of each user device) can be explored, and then the first function can be equivalently transformed according to the receiving vector and the weight vector, that is, the problem of maximizing the weighted sum rate optimization is equivalently transformed into the problem of minimizing the mean square error. In this way, the first function can be transformed into the second function.

[0067] S2043: Simplify the second function according to the receiving vector, the weight vector, the precoding cross information, the transmission and reflection phase information, and the transmission and reflection amplitude information to obtain the target function.

[0068] After obtaining the second function, the second function can be further simplified to obtain the objective function, which is a convex problem.

[0069] Thus, through the above S2041 to S2043, the non-convex problem of precoding vector optimization can be transformed into a convex problem, and an easily solvable objective function can be obtained. After obtaining the objective function, the first precoding vector can be optimized according to the objective function to obtain an optimized second precoding vector.

[0070] Optionally, as an embodiment, optimizing the first precoding vector according to the objective function to obtain the second precoding vector may include the following S2044 to S2046.

[0071] S2044: Introduce the transmit power constraint into the objective function using the Lagrange multiplier method, and apply the first-order optimization condition to the objective function to obtain the optimal expression of the precoding vector.

[0072] Here, the Lagrange multiplier method can be used to process the transmit power constraint condition, and the objective function is applied to the first access point and multiple user equipments. The closed form of the active beamformer of the first access point can be derived, that is, the optimal expression of the precoding vector is obtained. The optimal expression of the precoding vector is related to the multiplier introduced by the transmit power constraint condition and the precoding cross information between multiple access points, wherein the multiplier introduced by the transmit power constraint condition can be obtained by the dichotomy method.

[0073] S2045: Determine a third precoding vector according to the optimal expression of the precoding vector.

[0074] After the optimal expression of the precoding vector is obtained, a group of precoding vectors may be calculated based on the optimal expression. Here, for the sake of distinction, a third precoding vector may be used for representation.

[0075] S2046: Optimize the first precoding vector according to the third precoding vector to obtain a second precoding vector.

[0076] After obtaining the third precoding vector, the first precoding vector may be optimized according to the third precoding vector, thereby obtaining the second precoding vector. When optimizing the first precoding vector according to the third precoding vector, the first precoding vector and the third precoding vector may be weighted summed (the sum of the weight coefficient of the first precoding vector and the weight coefficient of the third precoding vector is 1), and the weighted summation result is used as the second precoding vector. Of course, it may also be implemented in other ways, which are not specifically limited here.

[0077] At this point, the first precoding vector can be optimized according to the first information, and the optimized second precoding vector can be obtained.

[0078] S206: Send the channel state information and the second precoding vector to the network device.

[0079] After the first access point obtains the channel state information of multiple user devices and optimizes the first precoding vectors of the multiple user devices to obtain the second precoding vector, the channel state information and the optimized second precoding vector can be sent to the network device. In the embodiment of the present application, the channel state information and the second precoding vector of the multiple user devices are related to the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces, and can be used to optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces. After the first access point sends the channel state information and the second precoding vector of the multiple user devices to the network device, the network device can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces based on the received channel state information and the second precoding vector. For specific implementation methods, please refer to Figure 3 The illustrated embodiment will not be described in detail here.

[0080] The above-mentioned transmission and reflection phase information and transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are related to the channel state information and the second precoding vector of the multiple user devices, specifically: for the reflection user device, the channel state information of the reflection user device includes the channel state information of the cascade channel between the first access point, the multiple omnidirectional metasurfaces and the reflection user device, and the cascade channel utilizes the reflection function of the multiple omnidirectional metasurfaces, and is therefore related to the reflection phase and reflection amplitude of the multiple omnidirectional metasurfaces. The second precoding vector of the reflection user device is used for the first access point to perform downlink transmission with the reflection user device with the assistance of the reflection signals of the multiple omnidirectional metasurfaces, and the reflection signals of the multiple omnidirectional metasurfaces are related to the reflection phase and reflection amplitude of the multiple omnidirectional metasurfaces. Therefore, the second precoding vector of the reflection user device is also related to the reflection phase and reflection amplitude of the multiple omnidirectional metasurfaces. For the transmission user device, the channel state information of the transmission user device is the channel state information of the cascade channel between the first access point, the multiple omnidirectional metasurfaces and the transmission user device, and the cascade channel utilizes the transmission function of the multiple omnidirectional metasurfaces, and is therefore related to the transmission phase and transmission amplitude of the multiple omnidirectional metasurfaces. The second precoding vector of the transmission user equipment is used for the first access point to perform downlink transmission with the transmission user equipment with the assistance of the transmission signals of multiple omnidirectional metasurfaces, and the transmission signals of the multiple omnidirectional metasurfaces are related to the transmission phases and transmission amplitudes of the multiple omnidirectional metasurfaces. Therefore, the second precoding vector of the transmission user equipment is also related to the transmission phases and transmission amplitudes of the multiple omnidirectional metasurfaces.

[0081] In this way, in the scenario where the omnidirectional metasurface assists in cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be achieved through the interaction between multiple access points in the cell-free network and the network equipment, wherein the multiple access points can optimize the precoding vector, and the network equipment can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in the scenario where the omnidirectional metasurface assists in cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be achieved. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly achieved by the interactive collaboration between the network equipment and multiple access points, the computational complexity of the network equipment can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed.

[0082] Optionally, as an embodiment, after the first access point optimizes and obtains the second precoding vector, it can also determine whether the rate optimization condition is met. When determining whether the rate optimization condition is met, it can be determined whether the rate value of the user and rate maximization problem constructed above converges based on the second precoding vector. If so, it can be determined that the rate optimization condition is met. If not, it can be determined that the rate optimization condition is not met. When the rate optimization condition is met, it can be explained that the second precoding vector is the optimal precoding vector, and the first access point can perform downlink transmission with multiple user devices based on the second precoding vector. When the rate optimization condition is not met, it can be explained that the second precoding vector is not the optimal precoding vector, and the second precoding vector needs to be optimized.

[0083] When optimizing the second precoding vector, the first access point may interact with the network device and optimize the second precoding vector in a loop iteration manner based on the interacted information. Optionally, as an embodiment, when optimizing the second precoding vector, the following S208 to S212 may be executed in a loop until the loop ends when the rate optimization condition is met.

[0084] S208: Receive second information sent by the network device.

[0085] In the first cycle, the second information is obtained by the network device after optimizing and updating the first information, that is, the second information includes the updated receiving vector, the updated weight vector, the updated precoding cross information, the optimized transmission reflection phase information and the optimized transmission reflection amplitude information. The specific implementation method of the network device optimizing and updating the first information can be found in Figure 3 The corresponding contents in the illustrated embodiment are not described in detail here. In the Nth (an integer greater than or equal to 2)th cycle, the second information may be the third information obtained after the network device optimizes and updates the second information in the N-1th cycle. The specific implementation method of the network device updating the second information is the same as the specific implementation method of the network device optimizing and updating the first information.

[0086] S210: Optimize the second precoding vector according to the second information to obtain a fourth precoding vector.

[0087] The specific implementation manner in which the first access point optimizes the second precoding vector according to the second information is the same as the specific implementation manner in which the first access point optimizes the first precoding vector according to the first information, and is not repeated here. After optimizing the second precoding vector, a group of precoding vectors can be obtained, which can be represented by a fourth precoding vector for easy distinction.

[0088] It should be noted that in the first cycle, the second precoding vector is a precoding vector obtained by updating the above-mentioned first precoding vector, and in the Nth (an integer greater than or equal to 2) cycle, the second precoding vector is the fourth precoding vector obtained in the N-1th cycle.

[0089] S212: Send the fourth precoding vector to the network device.

[0090] After sending the fourth precoding vector to the network device, the network device may update the second information in the previous cycle according to the fourth precoding vector and the channel state information of the plurality of user devices received previously, and send the updated third information to the first access point. The specific implementation of the network device may refer to Figure 3 The illustrated embodiment will not be described in detail here.

[0091] In the above cycle process, when the rate optimization condition is met, the cycle can be ended.

[0092] After the cycle is finished, for the first access point, the fourth precoding vector obtained in the last cycle can be used as the optimal precoding vector.

[0093] Optionally, after obtaining the optimal precoding vector, the first access point may perform downlink transmission with multiple user devices based on the optimal precoding vector. In this way, since the precoding vector used for downlink transmission is the optimal precoding vector, the first access point can better provide communication services for multiple user devices when performing downlink transmission with multiple user devices based on the optimal precoding vector.

[0094] In an embodiment of the present application, in a scenario where an omnidirectional metasurface assists in cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be achieved by interacting with multiple access points in the cell-free network and network devices, wherein multiple access points can optimize the precoding vector, and the network device can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in a scenario where an omnidirectional metasurface assists in cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be achieved. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly achieved by the interactive collaboration between the network device and multiple access points, the computational complexity of the network device can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed.

[0095] Figure 3 It is a flowchart of an information processing method according to an embodiment of the present application. Figure 3 The information processing method shown can be applied to Figure 1The network device shown, in other words, the information processing method can be executed by software or hardware installed in the network device. Optionally, the information processing method can be specifically executed by a CPU in the network device. Figure 3 The information processing method shown is as follows.

[0096] S302: Receive channel state information and a second precoding vector of multiple user devices sent by multiple access points, where the multiple user devices include reflective user devices and transmissive user devices, the reflective user devices are devices that communicate by utilizing the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate by utilizing the transmissive function of multiple omnidirectional metasurfaces, and the second precoding vector is obtained by optimizing the first precoding vectors of the multiple user devices by the multiple access points.

[0097] For each of the plurality of access points, a Figure 2 The method described in the illustrated embodiment determines the channel state information of multiple user devices, optimizes the first precoding vectors of the multiple user devices, obtains the second precoding vector, and then sends the channel state information and the second precoding vector to the network device, and the network device can receive the channel state information and the second precoding vector sent from multiple access points. Among them, for each access point, the channel state information sent can be the downlink channel state information of the multiple user devices when the access point performs downlink communication with the multiple user devices with the assistance of multiple omnidirectional metasurfaces, and the first precoding vectors of the multiple user devices can be initialized by the access point.

[0098] S304: Optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces according to the channel state information and the second precoding vector.

[0099] The transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces can be initialized by a network device, that is, the initial transmission and reflection phase information and transmission and reflection amplitude information designed by the network device for multiple omnidirectional metasurfaces, or, can also be initialized by multiple access points and sent to the network device, which is not specifically limited here. Since the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces are not the optimal information, they need to be optimized. During the optimization, since the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces are related to the channel state information and the second precoding vector of multiple user devices, it is possible to optimize according to the channel state information and the second precoding vector of multiple user devices to obtain appropriate transmission and reflection phase information and transmission and reflection amplitude information, so as to realize the design of the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces.

[0100] Optionally, as an embodiment, when optimizing the transmission and reflection phase information and the transmission and reflection amplitude information of multiple omnidirectional metasurfaces according to the channel state information and the second precoding vector, the following S3041 to S3045 may be included.

[0101] S3041: Obtain the second function.

[0102] Here the second function is Figure 2 The second function in the illustrated embodiment is obtained by equivalently transforming the first function based on the receiving vector and the weight vector, and converting the user and rate maximization problem into the mean square error minimization problem. The first function is obtained by constructing the user and rate maximization problem based on the first precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information under the transmission power constraint condition and the transmission constraint condition of multiple omnidirectional metasurfaces. The specific implementation method of determining the first function and the specific implementation method of converting the first function to obtain the second function can be referred to. Figure 2 The corresponding contents in the illustrated embodiments will not be repeated here.

[0103] Optionally, in one implementation, the second function may be sent by the access point to the network device, or may be determined by the network device, or may be pre-input into the network device, etc. The method for obtaining the second function is not specifically limited here.

[0104] S3042: Apply a first-order optimization condition to the second function according to the channel state information and the second precoding vector, update the receiving vector, and obtain an updated receiving vector.

[0105] After obtaining the second function, a first-order optimization condition may be applied to the second function according to the channel state information and the second precoding vector received in S302, so that the receiving vector may be updated to obtain an updated receiving vector. The expression of the updated receiving vector may be determined according to the channel state information and the second precoding vector.

[0106] S3043: Update the weight vector according to the channel state information, the second precoding vector, and the updated receiving vector to obtain an updated weight vector.

[0107] After obtaining the updated receiving vector, the weight vector can be further updated in combination with the channel state information and the second precoding vector to obtain an updated weight vector. The expression of the updated weight vector can be determined according to the channel state information, the second precoding vector and the updated receiving vector.

[0108] S3044: Update the precoding cross information according to the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector to obtain updated precoding cross information.

[0109] After obtaining the updated receiving vector and weight vector, the precoding cross information can be further updated in combination with the channel state information and the second precoding vector to obtain updated precoding cross information. The expression of the updated precoding cross information can be determined based on the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector.

[0110] S3045: Optimize the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the second function to obtain optimized transmission reflection phase information and optimized transmission reflection amplitude information.

[0111] After obtaining the updated receiving vector and the updated weight vector, the transmission and reflection phase information and the transmission and reflection amplitude information of multiple omnidirectional metasurfaces can be further optimized in combination with the channel state information, the second precoding vector and the second function obtained in S3041 to obtain the optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information.

[0112] In an embodiment of the present application, when optimizing the transmission and reflection phase information and the transmission and reflection amplitude information of multiple omnidirectional metasurfaces, it is necessary to consider the transmission constraints of multiple omnidirectional metasurfaces. The transmission constraints of multiple omnidirectional metasurfaces refer to the constraints that the units in the omnidirectional metasurfaces need to satisfy when the multiple omnidirectional metasurfaces reflect and transmit the received signals. Among them, under different scenario requirements, the transmission constraints of multiple omnidirectional metasurfaces may be different. Optionally, in one implementation, the transmission constraints may include phase coupling constraints and amplitude constraints, and in another implementation, the transmission constraints may include amplitude phase constraints, but do not include phase coupling constraints, that is, phase coupling constraints are not considered. In this way, when optimizing the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces, different optimization methods can be adopted according to different transmission constraints.

[0113] Specifically, when the transmission constraint condition includes a phase coupling constraint condition and an amplitude constraint condition, when optimizing the transmission-reflection phase information and the transmission-reflection amplitude information of multiple omnidirectional metasurfaces, the following steps 1 to 4 may be included:

[0114] Step 1: Obtain auxiliary variables equivalent to the reflection coefficients and transmission coefficients of multiple omnidirectional metasurfaces.

[0115] For each omnidirectional metasurface, its reflection coefficient can be determined according to the reflection phase and reflection amplitude of multiple units in the omnidirectional metasurface, and the transmission coefficient can be determined according to the transmission phase and transmission amplitude of multiple units in the omnidirectional metasurface. Here, the reflection coefficient and transmission coefficient of multiple omnidirectional metasurfaces can be equivalent to auxiliary variables, so that the transmission phase and transmission amplitude can be optimized with the help of the auxiliary variables.

[0116] Step 2: The second function is transformed according to the auxiliary variables to obtain a third function under an equality constraint, where the equality constraint is a constraint obtained by equating the reflection coefficient and the transmission coefficient to auxiliary variables.

[0117] The second function here is the second function obtained in the above S3041. After obtaining the auxiliary variables, the second function can be transformed according to the auxiliary variables to obtain the third function. The third function is a function related to the phase and amplitude optimization problem. The third function includes an equality constraint, which is a constraint obtained by equating the reflection coefficient and transmission coefficient of multiple omnidirectional metasurfaces to auxiliary variables. It should be noted that the transformation of the second function into the third function here is to transfer the phase coupling constraint and amplitude constraint of the omnidirectional metasurface to the auxiliary variables, that is, to change the phase constraint and amplitude constraint of the omnidirectional metasurface into the phase constraint and amplitude constraint of the auxiliary variables. In this way, it is convenient to optimize the reflection phase and reflection amplitude.

[0118] Step 3: Introduce the equality constraint into the third function as a penalty term, and transform the third function according to the penalty factor of the equality constraint and the Lagrange dual variable to obtain the target expression.

[0119] After introducing the equality constraint as a penalty term into the third function, the optimization problem of the transmission and reflection phase and the transmission and reflection amplitude can be converted into the corresponding augmented Lagrangian problem. After that, the penalty factor of the equality constraint and the Lagrangian dual variable can be further introduced, and the third function can be transformed, and finally the optimal objective expression for phase and amplitude optimization can be obtained.

[0120] Step 4: According to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the target expression, the transmission reflection phase information and the transmission reflection amplitude information are optimized to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information.

[0121] When optimizing the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the target expression, the variables to be optimized can be divided into two groups, one group is the reflection coefficient and the transmission coefficient of multiple omnidirectional metasurfaces, and the other group is the auxiliary variables equivalent to the reflection coefficient and the transmission coefficient. By optimizing these two groups of variables, the optimized transmission reflection phase information and the optimized transmission reflection amplitude information can be obtained.

[0122] Optionally, as an embodiment, when optimizing the transmission and reflection phase information and the transmission and reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the target expression, the following steps 41 to 45 may be included.

[0123] Step 41: Introduce the channel state information, the second precoding vector, the updated receiving vector and the updated weight vector into the target expression to obtain a first expression.

[0124] After the channel state information, the second precoding vector, the updated receiving vector and the updated weight vector are introduced into the target expression, the diagonal phase matrix in the target expression can be vectorized to obtain the first expression for optimizing the reflection coefficient and the transmission coefficient.

[0125] Step 42: Optimize the reflection coefficient and the transmission coefficient according to the first expression to obtain an optimized reflection coefficient and an optimized transmission coefficient.

[0126] The first expression is a convex problem. When optimizing the reflection coefficient and the transmission coefficient according to the first expression, a convex optimization tool can be used to solve the first expression, so as to obtain an optimized reflection coefficient and an optimized transmission coefficient.

[0127] Step 43: Determine a second expression for optimizing the auxiliary variables according to the optimized reflection coefficient, the optimized transmission coefficient and the target expression.

[0128] Here, the target expression can be simplified according to the optimized reflection coefficient and the optimized transmission coefficient, so as to obtain a second expression. The second expression includes terms involving auxiliary variables.

[0129] Step 44: Decompose the auxiliary variable in the second expression into a transmission reflection phase variable and a transmission reflection amplitude variable, and convert the second expression into a third expression according to the transmission reflection phase variable and the transmission reflection amplitude variable.

[0130] Here, the second expression is further transformed, specifically, the auxiliary variable in the second expression is decomposed into a transmission reflection phase variable and a transmission reflection amplitude variable, and the second expression is transformed based on the transmission reflection phase variable and the transmission reflection amplitude variable obtained after the decomposition to obtain a third expression. The third expression includes the transmission reflection phase variable and the transmission reflection amplitude variable, and based on the third expression, the transmission reflection phase variable and the transmission reflection amplitude variable can be optimized, that is, the auxiliary variable can be optimized.

[0131] Step 45: Optimize the transmission reflection phase variable and the transmission reflection amplitude variable according to the third expression to obtain an optimized transmission reflection phase variable and an optimized transmission reflection amplitude variable.

[0132] When optimizing, the transmission reflection amplitude variable can be given, and then the transmission reflection phase variable can be optimized according to the third expression, so as to obtain the optimized transmission reflection phase variable. After that, the transmission reflection phase variable can be given, and then the transmission reflection amplitude variable can be optimized according to the third expression, so as to obtain the optimized transmission reflection amplitude variable.

[0133] Based on the above S41 to S45, two groups of optimized transmission-reflection phase information and transmission-reflection amplitude information can be obtained. The first group is the optimized reflection coefficient and the optimized transmission coefficient obtained in the above S42, and the second group is the optimized transmission-reflection phase variable and transmission-reflection amplitude variable obtained in the above S45.

[0134] It should be noted that in other possible implementations, the penalized dual decomposition method mentioned above can also use other methods to obtain the transmission and reflection phase design under the coupled phase. For example, the phase design can be performed through the unit-by-unit optimization method. Under the coupled constraint condition, one phase is first optimized, and then the best other phase is selected in the constraint set; or the transmission and reflection phases are optimized separately without considering the constraint condition, and finally the phase error is equally divided into two phases according to the principle of optimal performance based on the coupled constraint. Considering that these methods will lead to a large performance loss under the phase constraint condition, therefore, if there is no special requirement, the penalized dual decomposition method can be preferably used to solve the phase optimization problem.

[0135] Optionally, as an embodiment, if the transmission constraints of the multiple omnidirectional metasurfaces include amplitude constraints, optimizing the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the second function may include the following steps:

[0136] The channel state information, the second precoding vector, the updated receiving vector and the updated weight vector are introduced into the second function to obtain a fourth expression;

[0137] The transmission reflection phase information and the transmission reflection amplitude information are optimized according to the fourth expression to obtain optimized transmission reflection phase information and optimized transmission reflection amplitude information.

[0138] Since the transmission constraints of multiple omnidirectional metasurfaces only include amplitude constraints and phase coupling constraints are not considered, it is not necessary to introduce auxiliary variables when optimizing the transmission reflection phase information and the transmission reflection amplitude information. Without introducing auxiliary variables, when optimizing, the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector can be introduced into the second function to obtain a fourth expression for optimizing the transmission reflection phase and the transmission reflection amplitude. The fourth expression is a convex problem. After obtaining the fourth expression, the fourth expression is solved by using a convex tool to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information.

[0139] At this point, the transmission reflection phase information and the transmission reflection amplitude information can be optimized for different transmission constraints of multiple omnidirectional metasurfaces, and the optimized transmission reflection phase information and transmission reflection amplitude information can be obtained. The optimized transmission reflection phase information can be continuous phase information.

[0140] In this way, in the scenario where the omnidirectional metasurface assists in cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be achieved through the interaction between multiple access points in the cell-free network and the network equipment, wherein the multiple access points can optimize the precoding vector, and the network equipment can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in the scenario where the omnidirectional metasurface assists in cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be achieved. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly achieved by the interactive collaboration between the network equipment and multiple access points, the computational complexity of the network equipment can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed.

[0141] Optionally, as an embodiment, after obtaining the optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information, the network device can also determine whether the rate optimization condition is met. When judging whether the rate optimization condition is met, it can be judged whether the rate value of the user and rate maximization problem constructed above converges based on the optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information. If so, it can be determined that the rate optimization condition is met. If not, it can be determined that the rate optimization condition is not met. Among them, for the two groups of optimized transmission and reflection phase information and transmission and reflection amplitude information obtained in S41 to S45 above, when judging whether the rate optimization condition is met, it can be judged based on the first group, that is, the optimized reflection coefficient and the optimized transmission coefficient obtained in S42.

[0142] If the rate optimization condition is met, it can be said that the optimized transmission reflection phase information and transmission reflection amplitude information are the optimal transmission reflection phase and transmission reflection amplitude, and the network device can send it to the controllers of multiple omnidirectional metasurfaces, and the controllers of multiple omnidirectional metasurfaces perform phase control and amplitude control on multiple omnidirectional metasurfaces. If the rate optimization condition is not met, it can be said that the optimized transmission reflection phase information and transmission reflection amplitude information are not the optimal transmission reflection phase and transmission reflection amplitude, and they need to be further optimized.

[0143] When further optimizing the transmission reflection phase information and the transmission reflection amplitude information, the network device may exchange information with multiple access points, and optimize the transmission reflection phase information and the transmission reflection amplitude information in a loop iteration manner based on the interacted information. Optionally, as an embodiment, when optimizing the transmission reflection phase information and the transmission reflection amplitude information, the following S306 to S310 may be executed in a loop until the loop ends when the rate optimization condition is met.

[0144] S306: Send second information to multiple access points, where the second information includes an updated receiving vector, an updated weight vector, updated precoding cross information, optimized transmission and reflection phase information, and optimized transmission and reflection amplitude information.

[0145] In the first cycle, the updated receiving vector, the updated weight vector, and the updated precoding cross information are the updated receiving vector, weight vector, and precoding cross information obtained through the above S3041 to S3044. The optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information refer to the transmission and reflection phase information and the transmission and reflection amplitude information obtained through the above S3045 optimization. Among them, considering the phase coupling constraints and amplitude constraints of multiple omnidirectional metasurfaces, the optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information can be the optimized reflection coefficient and the optimized transmission coefficient obtained through the above S42.

[0146] In the Nth (an integer greater than or equal to 2) cycle, the second information may be third information obtained by updating the second information based on S310 in the N-1th cycle.

[0147] S308: Receive fourth precoding vectors sent by multiple access points.

[0148] In the first cycle, the fourth precoding vector is obtained by optimizing the second precoding vector by the multiple access points according to the second information sent by the network device. In the Nth (an integer greater than or equal to 2)th cycle, the fourth precoding vector is obtained by optimizing the fourth precoding vector in the N-1th cycle by the multiple access points according to the second information sent by the network device in the Nth cycle.

[0149] S310: Optimize and update the second information according to the channel state information and the fourth precoding vector to obtain third information.

[0150] When the second information is optimized and updated according to the channel state information and the fourth precoding vector, the specific implementation method may refer to the corresponding content in the above S304, which will not be described in detail here.

[0151] It should be noted that the above-mentioned cycle process from S306 to S310 is the same as Figure 2 The loop process from S208 to S212 in the illustrated embodiment is a whole, that is, in the first loop, the network device sends the second information (including the updated receiving vector, the updated weight vector, the updated precoding cross information, the optimized transmission and reflection phase information, and the optimized transmission and reflection amplitude information) to multiple access points. For each access point, after receiving the second information, it can optimize the second precoding vector based on the second information to obtain a fourth precoding vector, and then send the fourth precoding vector to the network device. The network device optimizes and updates the second information according to the fourth precoding vector and the previously received channel state information to obtain the third information. At this point, the first loop is completed. In the second cycle, the network device sends the third information as the second information to multiple access points. For each access point, after receiving the second information, the second precoding vector (the fourth precoding vector obtained in the previous cycle) can be optimized based on the second information to obtain a fourth precoding vector, and then the fourth precoding vector is sent to the network device. The network device optimizes and updates the second information (i.e., the third information obtained in the previous cycle) according to the fourth precoding vector and the previously received channel state information to obtain the third information, thus completing the second cycle. In this way, such a loop operation is repeated, and when the rate optimization condition is met, the network device and the multiple access points can end the loop.

[0152] After the cycle is completed, multiple access points can obtain precoding vectors that meet the rate optimization condition, and the network device can obtain transmission and reflection phase information and transmission and reflection amplitude information that meet the rate optimization condition.

[0153] In the embodiment of the present application, if the amplitude constraints of multiple omnidirectional metasurfaces are considered without considering the phase coupling constraints, the transmission and reflection phase information and the transmission and reflection amplitude information obtained after the above cycle is completed can be used as the optimal transmission and reflection phase information and transmission and reflection amplitude information, and sent to the controllers of the multiple omnidirectional metasurfaces, and the controllers of the multiple omnidirectional metasurfaces perform transmission and reflection phase regulation and transmission and reflection amplitude regulation on the multiple omnidirectional metasurfaces according to the received transmission and reflection phase information and transmission and reflection amplitude information. If the amplitude constraints of multiple omnidirectional metasurfaces are considered while also considering the phase coupling constraints of multiple omnidirectional metasurfaces, then, since auxiliary variables are introduced in the optimization process of phase and amplitude, it is necessary to further determine whether the transmission and reflection phase information and transmission and reflection amplitude information obtained at the end of the above cycle are the optimal phase and amplitude.

[0154] Optionally, as an embodiment, when judging whether the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above-mentioned cycle are the optimal phase and amplitude, it can be judged whether the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the cycle meet the transmission reflection coefficient optimization condition. The transmission reflection coefficient optimization condition here is an optimization condition related to the auxiliary variable introduced above. Optionally, the transmission reflection coefficient optimization condition can be whether the difference between the optimized transmission coefficient and reflection coefficient obtained in S42 and the optimized transmission reflection phase variable and transmission reflection amplitude variable obtained in S45 is less than or equal to a preset threshold value. If so, the transmission reflection coefficient optimization condition is met. If not, the transmission reflection coefficient optimization condition is not met. In the case of meeting the transmission reflection coefficient optimization condition, it can be determined that the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above-mentioned cycle are the optimal phase and amplitude, and it can be sent to the controllers of multiple omnidirectional metasurfaces for phase and amplitude regulation. In the case of not meeting the transmission reflection coefficient optimization condition, it can be determined that the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above-mentioned cycle are not the optimal phase and amplitude, and need to be further optimized.

[0155] When the transmission-reflection phase information and the transmission-reflection amplitude information obtained at the end of the above loop are further optimized, the following S312 to S314 may be executed cyclically until the transmission-reflection coefficient optimization condition is met and the loop is terminated.

[0156] S312: Update the first parameter in the target expression for optimizing the transmission-reflection phase information and the transmission-reflection amplitude information to obtain a second parameter.

[0157] The target expression here is the target expression obtained by transforming the second function twice in the above S304 under the phase coupling constraint and the amplitude constraint, when optimizing the transmission and reflection phase information and the transmission and reflection amplitude information, with the introduction of auxiliary variables.

[0158] The first parameter may be a parameter in the target expression that has an impact on the optimization of the transmission reflection phase and the transmission reflection amplitude. Alternatively, it may be a penalty factor and a Lagrange dual variable in the target expression.

[0159] S314: Bring the second parameter into the target expression, and execute the first operation in a loop based on the target expression until the rate optimization condition is met.

[0160] After the first parameter in the target representative expression is updated to obtain the second parameter, the second parameter can be brought into the target expression, and the transmission reflection phase information and the transmission reflection amplitude information obtained at the end of the above loop can be optimized based on the target expression. During the optimization, the first operation can be executed cyclically, and the first operation is the above S306 to S310, that is, the above S306 to S310 can be executed cyclically again until the execution of S306 to S310 ends when the rate optimization condition is met (when executing S306 to S310 cyclically, multiple access points can be connected through Figure 2 After the execution of S306 to S310 is completed, it can be further determined whether the transmission reflection phase information and the transmission reflection amplitude information obtained when the loop is terminated meet the transmission reflection coefficient optimization condition. If so, the loop of S312 and S314 is terminated. If not, it is necessary to execute S312 and S314 again to optimize the transmission reflection phase information and the transmission reflection amplitude information again, until the transmission reflection coefficient optimization condition is met, the loop operation of S312 and S314 is terminated, and the transmission reflection phase information and the transmission reflection amplitude information obtained at this time can be regarded as the optimal transmission reflection phase information and the transmission reflection amplitude information.

[0161] It should be noted that the above-mentioned S306 to S310 and S312 to S314 are two loop operations. Each time the operation of S312 to S314 is cycled once, it is necessary to cycle S306 to S310 multiple times. The condition for ending the cycle of S306 to S310 is to meet the rate optimization condition, and the condition for ending the cycle of S312 to S314 is to meet the reflection coefficient optimization condition. When the cycle of S312 to S314 meets the reflection coefficient optimization condition, the cycle operation of S312 to S314 can be ended, and there is no need to cycle S306 to S310.

[0162] After the above-mentioned loop operation of S312 and S314 is completed, the network device can send the transmission reflection phase information and transmission reflection amplitude information obtained when the loop is completed to the controllers of multiple omnidirectional metasurfaces, so that the controllers of multiple omnidirectional metasurfaces can respectively adjust the transmission reflection phase and transmission reflection amplitude of multiple omnidirectional metasurfaces according to the received transmission reflection phase information and transmission reflection amplitude information. For multiple omnidirectional metasurfaces, since the adjusted transmission reflection phase and transmission reflection amplitude are the optimal phase and amplitude, multiple omnidirectional metasurfaces can better provide communication services for multiple user devices when combined with multiple access points and multiple user devices for downlink transmission.

[0163] In an embodiment of the present application, in a scenario where an omnidirectional metasurface assists in cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be achieved by interacting with multiple access points in the cell-free network and network devices, wherein multiple access points can optimize the precoding vector, and the network device can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in a scenario where an omnidirectional metasurface assists in cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be achieved. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly achieved by the interactive collaboration between the network device and multiple access points, the computational complexity of the network device can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed.

[0164] In order to facilitate understanding of the technical solution provided in the embodiment of the present application, a more specific implementation method will be used as an example for explanation below. Figure 4 and Figure 5 . Figure 4 and Figure 5 The embodiments shown are all described by taking a cell-free network including B APs and L IOSs, which collaboratively serve K user equipments as an example. r reflective user equipment and K t The number of transmitting antennas at the AP end and receiving antennas at the user equipment end are M t and M r , the number of units included in each IOS is N, and the definition They represent the collection of AP, IOS, reflective user equipment, transparent user equipment, all user equipment, and IOS units respectively.

[0165] Figure 4 The illustrated embodiment takes into account phase coupling constraints and amplitude constraints of multiple omnidirectional metasurfaces. Figure 4 The illustrated embodiment may include the following steps.

[0166] S401: Multiple APs obtain channel state information of multiple user equipments.

[0167] Specifically, only the first-order reflection or transmission is considered, and represents the equivalent channel from the bth AP to the kth reflecting user equipment, represents the equivalent channel from the lth IOS to the kth reflection / transmission user equipment, represents the equivalent channel from the bth AP to the lth IOS. In addition, it is assumed here that due to occlusion, the transmitted user equipment has no direct channel to the AP.

[0168] The diagonal matrix of reflection and transmission of the lth IOS is expressed as Among them, the reflection coefficient φ of the nth IOS unit on the incident electromagnetic wave r,l,n and the transmission coefficient φ t,l,n Can be described as n=1,...,N, and Represent the reflection and transmission phase shifts, η r,l,n ∈[0,1] and η t,l,n ∈[0,1] represents the reflection and transmission amplitudes respectively, and satisfies (i.e. amplitude constraint), for a completely passive and lossless IOS, further considering the phase coupling constraint, the reflected and transmitted phase shifts must satisfy the constraint

[0169] With the assistance of multiple IOS, considering that the part of the transmission user equipment that has no direct connection channel due to occlusion, the bth AP to the a reflective user device and a The equivalent combined channels (i.e., equivalent channel models) of the transmitted user equipment can be expressed as:

[0170]

[0171]

[0172] Then the received signal of the kth reflection / transmission user equipment can be uniformly expressed as:

[0173]

[0174] Among them, s m represents the symbol sent by the target to user m, represents the beamforming matrix designed by AP b for the transmission signal of user m, and is defined as represents the Gaussian noise at user equipment k.

[0175] S402: Multiple APs optimize first precoding vectors of multiple user equipments to obtain second precoding vectors.

[0176] For each AP, when optimizing the first precoding vector, the first information can be obtained, and the first precoding vector is optimized according to the first information. The first information includes a receiving vector, a weight vector, precoding cross information between multiple access points, and transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces. The first information can be initialized by the AP or sent to the AP by a network device.

[0177] When optimizing the first precoding vector, the following steps 1 to 3 may be included.

[0178] Step 1: Construct the user and rate maximization problem (i.e., the weighted and rate optimization problem) under the scenario and model constraints (including AP transmit power constraints, IOS phase coupling constraints, and amplitude constraints, a total of three constraints). Jointly optimize the transmit beamforming matrix W, the transmission and reflection phase shift vector And IOS reflection amplitude vector η r , η t , calculate the kth The SINR value of the received signal of a user equipment is:

[0179]

[0180] Then the optimization problem of maximizing the weighted sum rate can be described as the following formula (i.e. Figure 2 The first function in the embodiment shown):

[0181]

[0182]

[0183]

[0184]

[0185] Among them, P max ,ω k Respectively represent the maximum transmit power of each AP and the user weighting coefficient.

[0186] Step 2: By introducing the receiving vector and weight vector u k ,f k , The user sum rate maximization problem is equivalently transformed into the mean square error minimization problem, and the first function above is transformed to obtain the following formula (i.e. Figure 2 The second function in the illustrated embodiment):

[0187] Among them, c is an irrelevant constant term, mse k is the mean square error of the received signal at the user equipment k side, which can be expressed as:

[0188]

[0189] Among them, the received signal on the user equipment side After calculation and simplification, the active beamforming optimization problem can be re-expressed as the following formula (i.e. Figure 2 Objective function in the embodiment shown):

[0190]

[0191] Among them, the coefficient of the quadratic term about W is Its elements are represented by The coefficient of the first-order term is Its elements are represented by

[0192] Step 3: The Lagrange multiplier method is further used to process the transmit power constraint, and the first-order optimization condition is applied to the above objective function to obtain the closed-form distributed optimal solution of the active beamformer of the AP (i.e. Figure 2 The optimal expression of the precoding vector in the embodiment shown is:

[0193] w b,k =(Ξ bb +λ b I) -1 (z b,k -ξ b,k ).

[0194] in, is the introduced multiplier term of the transmit power constraint, which can be updated by bisection method, ξ b,k Represents precoding cross information.

[0195] After obtaining the optimal expression, the first precoding vector can be optimized based on the optimal expression. For user equipment k, in each iterative optimization, based on the fixed ξ b,k Each AP b and other APs simultaneously calculate w locally according to the above formula b,k . In order to ensure the convergence of each update and the convergence speed and accuracy, the step size α∈(0,1] can be fixed, and the precoding vector can be updated by the following expression:

[0196]

[0197] in, represents the precoding vector updated at the tth iteration, represents the precoding vector updated at the t-1th iteration, that is, the precoding vector to be optimized at the tth iteration, w b,k Indicates that at the tth iteration, The calculated precoding vector.

[0198] S403: The multiple APs send channel state information and the second precoding vector to the network device.

[0199] S404: The network device optimizes the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple IOSs according to the channel state information and the second precoding vector sent by the multiple APs.

[0200] When optimizing, the following steps 1 to 4 may be included.

[0201] Step 1: Based on the channel state information obtained from the AP and the second precoding vector of each AP, By optimizing the first-order optimization conditions of the variables respectively, the access vector is updated, and the updated receiving vector can be expressed as:

[0202]

[0203] Based on the updated receiving vector, combined with the channel state information and the second precoding vector, the weight vector is updated. The updated weight vector can be expressed as:

[0204]

[0205] Afterwards, the AP precoding cross information may be updated based on the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector. The updated AP precoding cross information may be expressed as:

[0206]

[0207] Step 2: Based on the updated receiving vector, the updated weight vector and the second precoding vector, the PDD-based method is used to deal with the non-convex constraints introduced by multi-IOS (i.e., the phase coupling constraints and amplitude constraints of multi-IOS). First, auxiliary variables equivalent to the reflection coefficient and the transmission coefficient are defined. The above formula, Transformation is performed to express the optimization problem of phase and amplitude as follows (i.e. Figure 3 The third function in the illustrated embodiment):

[0208]

[0209] Afterwards, the optimization problem of phase and amplitude can be transformed into the corresponding augmented Lagrangian problem by moving the equality constraints in the formula as penalty terms, introducing a penalty factor ρ>0 for violating the first constraint in the above formula, and a Lagrangian dual variable λ x , The above problem can be transformed into the following formula (i.e. Figure 3 Target expression in the embodiment shown):

[0210]

[0211] It can be observed that when ρ→0, the penalty term will be forced to zero, that is, the equality constraint is enforced. The embodiment of the present application solves the above phase and amplitude optimization problem by adopting the block coordinate descent method. When optimizing the phase and amplitude, the variables to be optimized can be divided into two groups, namely {φ r ,φ t}and Then the two groups of variables to be optimized are optimized separately.

[0212] Step 3: For {φ r ,φ t Specifically, the channel state information can be substituted into the target expression in step 2 above, and the diagonal phase matrix can be vectorized to φ x,l =[φ x,l,1 ,...,φ x,l,n ,...,φ x,l,N ] T , Ignoring the constant terms that are irrelevant to the phase matrix, performing vector combination and simplification, we can get r ,φ t The optimization problem of} can be reformulated as follows (i.e. Figure 3 The first expression in the embodiment shown):

[0213]

[0214] The above formula is a convex problem and can be easily solved using convex optimization tools. The coefficient of the quadratic term with respect to the phase vector is Each matrix element

[0215]

[0216] Combination Vector Since the reflective user equipment has both the direct link of the AP and the reflective link of the IOS, the coefficient p r,l Contains C l,k and Dl,k , Among them C l,k Derived from the direct link term, D l,k Derived from the IOS cascade link item, Since there is no direct link to the transmitted user equipment, item C is not included. l,k , coefficient p t,l Expressed as

[0217] Step 4: Right Based on the optimization result {φ r ,φ t}, then optimize the auxiliary variables Ignoring other irrelevant items, the optimization problem of auxiliary variables can be expressed as the following formula:

[0218]

[0219] Among them, the variable θ is introduced x =-φ x +ρλ x , Expand the above formula, because Then the above formula can be transformed into the following formula (i.e. Figure 3 The second expression in the embodiment shown):

[0220]

[0221] In the above formula, only the term involves the optimization variable, while the other terms are constants. Therefore, Decomposition into magnitude vectors and the phase vector Right now Ignoring irrelevant terms, the optimization problem of auxiliary variables can be expressed as the following formula (i.e. Figure 3 The third expression in the embodiment shown):

[0222]

[0223] Here, the constraint is reintroduced is used to ensure that during the following optimization process, all phase shifts are collected in and Definition Given The optimal phase shift for each unit can be solved as

[0224]

[0225] The constraint set is expressed as definition Given Then the amplitude coefficient of the optimal auxiliary variable can be obtained, that is Among them, the definition if belong Within the range, if belong Within the range, Otherwise in other cases, Right now

[0226] Through the above steps, two sets of optimized reflection phase information and reflection amplitude information can be obtained. The first set is for {φ r ,φ t The second group is the information of the phase and amplitude of the reflection obtained after optimization. The transmission and reflection phase information and transmission and reflection amplitude information obtained after optimization.

[0227] S405: The network device sends the optimized transmission and reflection phase information and transmission and reflection amplitude information to multiple APs.

[0228] The transmission and reflection phase information and the transmission and reflection amplitude information sent by the network device to the multiple APs may be the information of {φ r ,φ t} The transmission and reflection phase information and transmission and reflection amplitude information are obtained after optimization. When sending the transmission and reflection phase information and transmission and reflection amplitude information to multiple APs, the receiving vector, weight vector and precoding cross information updated in S404 can also be sent to multiple APs. After multiple APs receive the receiving vector, weight vector, precoding cross information, transmission and reflection phase information and transmission and reflection amplitude information, they can execute the above S402. Thus, multiple loop iterations can be performed between multiple APs and network devices. During the loop iteration process, each AP optimizes the precoding vector according to the receiving vector, weight vector, AP precoding cross information, transmission and reflection phase information and transmission and reflection amplitude information sent by the network device. The network device optimizes the transmission and reflection phase information and transmission and reflection amplitude information according to the channel state information sent by each AP and the updated precoding vector, and updates the receiving vector, weight vector and AP precoding cross information at the same time.

[0229] S406: When the convergence rate value is obtained, the loop ends.

[0230] S407: The network device determines whether the transmission and reflection phase information and the transmission and reflection amplitude information meet the transmission and reflection coefficient optimization condition.

[0231] After the loop ends, it can be determined whether the transmission reflection phase information and the transmission reflection amplitude information at the end of the loop meet the transmission reflection coefficient optimization conditions. Here, it can be determined whether φ x and is less than or equal to a preset threshold, if so, S410 can be executed. If not, S408 can be executed.

[0232] S408: The network device updates the first parameter in the target expression for optimizing the transmission-reflection phase information and the transmission-reflection amplitude information to obtain a second parameter.

[0233] The target expression here is the following formula in S404:

[0234]

[0235] The first parameter can be the penalty factor ρ and the Lagrangian dual variable λ in the formula x , in the case of ρ and λ x When updating, we can set ρ = 0.1ρ,

[0236] S409: The network device brings the second parameter into the target expression, and further optimizes the transmission and reflection phase information and the transmission and reflection amplitude information based on the target expression.

[0237] When further optimizing the transmission and reflection phase information and the transmission and reflection amplitude information, the above S402 to S405 can be executed in a loop until the loop ends when the rate optimization condition is met, and then S407 and S408 are executed again. In this way, S402 to S405 can constitute an inner loop, and S407 and S408 can constitute an outer loop. Each time the outer loop is looped once, the inner loop loops multiple times. The end condition of the inner loop is to meet the rate optimization condition, that is, to obtain the convergence rate value, and the end condition of the outer loop is to meet the transmission and reflection coefficient optimization condition. When the outer loop ends, the inner loop also ends accordingly. Among them, when the outer loop ends, the precoding vector, transmission and reflection phase information, and transmission and reflection amplitude information obtained in the last loop can be used as the optimal precoding vector, transmission and reflection phase information, and transmission and reflection amplitude information.

[0238] S410: Multiple APs perform downlink transmission with multiple user equipments based on the precoding vectors obtained in the last cycle.

[0239] S411: The network device sends the transmission and reflection phase information and the transmission and reflection amplitude information obtained in the last cycle to multiple IOS controllers.

[0240] S412: The multiple IOS controllers perform phase control and amplitude control on the multiple IOSs according to the transmission reflection phase information and the transmission reflection amplitude information.

[0241] Figure 5 The illustrated embodiment considers the amplitude constraints of multiple omnidirectional metasurfaces and does not consider the phase coupling constraints, that is, considers a phase-independent model. Figure 5 The illustrated embodiment includes the following steps.

[0242] S501: Multiple APs obtain channel state information of multiple user equipments.

[0243] S502: Multiple APs optimize first precoding vectors of multiple user equipments to obtain second precoding vectors.

[0244] The specific implementation of S501 and S502 can refer to the above S401 and S402, and will not be repeated here.

[0245] S503: The multiple APs send channel state information and the second precoding vector to the network device.

[0246] S504: The network device optimizes the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple IOSs according to the channel state information and the second precoding vector sent by the multiple APs.

[0247] When optimizing, the following steps 1 and 2 may be included.

[0248] Step 1: Based on the channel state information obtained from the AP and the second precoding vector of each AP, By optimizing the first-order optimization conditions of the variables respectively, the access vector is updated, and the updated receiving vector can be expressed as:

[0249]

[0250] Based on the updated receiving vector, combined with the channel state information and the second precoding vector, the weight vector is updated. The updated weight vector can be expressed as:

[0251]

[0252] Afterwards, the AP precoding cross information may be updated based on the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector. The updated AP precoding cross information may be expressed as:

[0253]

[0254] Step 2: Based on the updated receiving vector, the updated weight vector and the second precoding vector, the channel state information is substituted into And vectorize the diagonal phase matrix φ x,l =[φ x,l,1 ,...,φx,l,n ,...,φ x,l,N ] T , Ignoring the constant terms that are irrelevant to the phase matrix, performing vector combination and simplification, we can get r ,φ t The phase optimization problem can be reformulated as follows (i.e. Figure 3 The fourth expression in the embodiment shown):

[0255]

[0256] The above formula is a convex problem and can be solved using convex optimization tools. The coefficient of the quadratic term with respect to the phase vector is Each matrix element Combination Vector Since the reflective user equipment has both the direct link of the base station and the reflected link of the IOS, the coefficient p r,l Contains C l,k and D l,k , Among them C l,k Derived from the direct link term, D l,k Derived from the IOS cascade link item, Since the transmission user equipment has no direct link, item C is not included. l,k , coefficient p t,l Expressed as

[0257] Through the above steps, optimized transmission-reflection phase information and transmission-reflection amplitude information can be obtained.

[0258] S505: The network device sends the optimized transmission and reflection phase information and transmission and reflection amplitude information to multiple APs.

[0259] When the network device sends the transmission reflection phase information and the transmission reflection amplitude information to multiple APs, the receiving vector, weight vector and precoding cross information updated in S504 can also be sent to the multiple APs. After the multiple APs receive the receiving vector, weight vector, precoding cross information, transmission reflection phase information and transmission reflection amplitude information, they can execute the above S502. Thus, multiple loop iterations can be performed between the multiple APs and the network device. During the loop iteration process, each AP optimizes the precoding vector according to the receiving vector, weight vector, AP precoding cross information, transmission reflection phase information and transmission reflection amplitude information sent by the network device. The network device optimizes the transmission reflection phase information and transmission reflection amplitude information according to the channel state information sent by each AP and the updated precoding vector, and updates the receiving vector, weight vector and AP precoding cross information at the same time.

[0260] S506: When the convergence rate value is obtained, the loop ends.

[0261] S507: The multiple APs perform downlink transmission with the multiple user equipments based on the precoding vectors obtained in the last cycle.

[0262] S508: The network device sends the transmission and reflection phase information and the transmission and reflection amplitude information obtained in the last cycle to multiple IOS controllers.

[0263] S509: The multiple IOS controllers perform phase control and amplitude control on the multiple IOSs according to the transmission and reflection phase information and the transmission and reflection amplitude information.

[0264] In a cell-free network scenario, the performance can be verified based on the method designed in the embodiment of the present application, the performance of the phase-independent model can be compared to analyze the impact of the phase-coupled model on the overall performance, and the performance gain of IOS over traditional RIS can be analyzed under different parameter configurations.

[0265] Specifically, the optimized unit phase is output to verify that the optimization result satisfies the constraint of the transmission and reflection phase coupling. In the embodiment of the present application, consider that 4 APs are combined with 2 IOSs to serve 8 user devices, and the number of transmitting and receiving antennas is M. t =2,M r =2, assume that AP i is located at (20(i-1)m, 60m), and the two IOSs are located at (20m, 0) and (40m, 0) respectively, and the user devices are evenly distributed on both sides of the IOS. Set the heights of AP, IOS and user devices to be 3m, 3m and 1.5m respectively. Use the InH path loss model commonly used in indoor environments to establish the distance-dependent channel path loss, and set the center frequency to f c =5.8GHz, and the user weight coefficients are all set to The precoding vector update step size is set to α = 0.5, the initial ρ = 1, and the AP maximum transmit power P max =10dBm, noise power σ 2 =-80dBm. For specific comparison results, please refer to Figure 6 and Figure 7 .

[0266] Figure 6The relationship between the weighted sum rate performance and the AP transmit power is given. With N=100 fixed, as the AP transmit power increases, the weighted sum rate rises rapidly in all cases. It is found that the performance gain brought by RISs and IOSs is significant only when the AP transmit power is medium, while the performance gain is negligible when the AP transmit power is too low or too high. When the AP transmit power is too low, the signal reflected / transmitted by RIS / IOS is very weak, and the contribution of RIS / IOS to performance improvement is small. When the AP transmit power is too large, APs tend to allocate most of the power to the beam of the AP user link, making the role of RISs / IOSs less obvious. In addition, with the increase of transmit power, it can be observed that the impact of transmission and reflection phase coupling on system performance gradually increases, while when the transmit power is small, it is almost the same as the phase-independent system architecture.

[0267] Figure 7 The relationship between the weighted sum rate performance and the number of units of different IOS optimization schemes is given. For phase-coupled IOS, the PDD-based optimization method proposed in the embodiment of the present application can achieve almost the same performance as the independent phase model, with a loss of about 2.9% when N=100. It can be seen that the method proposed in the embodiment of the present application achieves significant performance gain compared to traditional RIS. IOS can bring greater diversity gain and expand coverage compared to RIS. The proposed method can achieve 2 times or more of the rate performance compared to traditional cell-free networks.

[0268] Based on the technical solution provided in the embodiment of the present application, in the scenario of omnidirectional metasurface assisted cell-free network communication, when designing the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface, it can be realized through the interaction between multiple access points in the cell-free network and the network equipment, wherein the multiple access points can optimize the precoding vector, and the network equipment can optimize the transmission and reflection phase information and the transmission and reflection amplitude information of the omnidirectional metasurface. Thus, in the scenario of omnidirectional metasurface assisted cell-free network communication, the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be realized. In addition, since the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information can be jointly realized by the interactive collaboration between the network equipment and the multiple access points, the computational complexity of the network equipment can be effectively reduced, the processing time is shorter, the efficiency is higher, and the system performance can be effectively guaranteed.

[0269] The technical solution provided in the embodiments of the present application can be applied to network scenarios of 6G configurable smart surfaces in the future, especially network scenarios assisted by omnidirectional metasurfaces with transmission and reflection functions. Compared with the RIS-assisted solution, the IOS-assisted solution is more suitable for scenarios with severe wall obstruction and the need to expand coverage. It is more suitable for deployment on walls or building surfaces to enhance the flexibility of assisted indoor and outdoor communication scenarios.

[0270] The above describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0271] Figure 8 This is a schematic diagram of the structure of a communication device according to an embodiment of the present application. Figure 8 At the hardware level, the communication device includes a processor, and optionally an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Of course, the communication device may also include hardware required for other services.

[0272] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0273] The memory is used to store the program. Specifically, the program may include a program code, and the program code includes a computer operation instruction. The memory may include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0274] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming an information processing device at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0275] Acquire channel state information of multiple user devices, wherein the multiple user devices include reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate using the reflective functions of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive functions of the multiple omnidirectional metasurfaces;

[0276] Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector;

[0277] The channel state information and the second precoding vector are sent to a network device.

[0278] Or to do the following:

[0279] receiving channel state information and second precoding vectors of multiple user equipments sent by multiple access points, the multiple user equipments including reflective user equipments and transmissive user equipments, the reflective user equipments are equipments that communicate by using the reflective functions of multiple omnidirectional metasurfaces, the transmissive user equipments are equipments that communicate by using the transmissive functions of the multiple omnidirectional metasurfaces, and the second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user equipments by the multiple access points;

[0280] According to the channel state information and the second precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized.

[0281] The above application Figure 8The method performed by the information processing device disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in this application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in this application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0282] The communication device can also perform Figure 2 and Figure 3 The method and the information processing device are implemented in Figure 2 and Figure 3 The functions in the illustrated embodiments will not be described in detail in this application.

[0283] Of course, in addition to software implementation, the communication device of the present application does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc. That is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0284] The present application also proposes a computer-readable storage medium, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by a portable communication device including a plurality of application programs, enable the portable communication device to execute Figure 2 and Figure 3 The method of the embodiment shown is specifically used to perform the following operations:

[0285] Acquire channel state information of multiple user devices, wherein the multiple user devices include reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate using the reflective functions of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive functions of the multiple omnidirectional metasurfaces;

[0286] Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector;

[0287] The channel state information and the second precoding vector are sent to a network device.

[0288] Or to do the following:

[0289] receiving channel state information and second precoding vectors of multiple user equipments sent by multiple access points, the multiple user equipments including reflective user equipments and transmissive user equipments, the reflective user equipments are equipments that communicate by using the reflective functions of multiple omnidirectional metasurfaces, the transmissive user equipments are equipments that communicate by using the transmissive functions of the multiple omnidirectional metasurfaces, and the second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user equipments by the multiple access points;

[0290] According to the channel state information and the second precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized.

[0291] Fig. 9 This is a schematic diagram of the structure of an information processing device 90 according to an embodiment of the present application. Fig. 9 In a software implementation, the information processing device 90 may include: an acquisition module 91, an optimization module 92 and a sending module 93, wherein:

[0292] An acquisition module 91 is configured to acquire channel state information of a plurality of user devices, wherein the plurality of user devices include a reflective user device and a transmissive user device, wherein the reflective user device is a device that communicates by using the reflective function of a plurality of omnidirectional metasurfaces, and the transmissive user device is a device that communicates by using the transmissive function of the plurality of omnidirectional metasurfaces;

[0293] An optimization module 92 optimizes the first precoding vectors of the plurality of user equipments to obtain a second precoding vector;

[0294] The sending module 93 sends the channel state information and the second precoding vector to a network device.

[0295] The information processing device 90 provided in the embodiment of the present application can also execute Figure 2 The method is implemented by the information processing device 90 in Figure 2 The functions of the illustrated embodiments will not be described in detail in this application.

[0296] Fig.10 This is a schematic diagram of the structure of an information processing device 100 according to an embodiment of the present application. Fig.10 In a software implementation, the information processing device 100 may include: a receiving module 101 and an optimization module 102, wherein:

[0297] A receiving module 101 receives channel state information and a second precoding vector of multiple user equipments sent by multiple access points, wherein the multiple user equipments include reflective user equipments and transmissive user equipments, wherein the reflective user equipments are equipments that communicate by using the reflective functions of multiple omnidirectional metasurfaces, and the transmissive user equipments are equipments that communicate by using the transmissive functions of the multiple omnidirectional metasurfaces, and the second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user equipments by the multiple access points;

[0298] The optimization module 102 optimizes the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces according to the channel state information and the second precoding vector.

[0299] The information processing device 100 provided in the embodiment of the present application can also execute Figure 3 The method is implemented by the information processing device 100 Figure 3 The functions of the illustrated embodiments will not be described in detail in this application.

[0300] The embodiment of the present application further provides an information processing system, the information processing system comprising a plurality of access points, a plurality of omnidirectional metasurfaces and a network device, the plurality of access points and the plurality of omnidirectional metasurfaces providing communication services for a plurality of user devices by collaboratively interacting with the network device, wherein:

[0301] The multiple access points acquire channel state information of the multiple user devices, the multiple user devices include reflective user devices and transmissive user devices, the reflective user devices are devices that communicate using the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive function of the multiple omnidirectional metasurfaces; optimize the first precoding vectors of the multiple user devices to obtain a second precoding vector; and send the channel state information and the second precoding vector to the network device;

[0302] The network device optimizes the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces according to the channel state information and the second precoding vector.

[0303] In the information processing system provided in the embodiment of the present application, each access point can implement Figures 1 to 5 The functions of the access point (or first access point) in the embodiment shown are that the network device can implement Figures 1 to 5 The functions of the network devices in the illustrated embodiment will not be described in detail here.

[0304] In short, the above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0305] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0306] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0307] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0308] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

Claims

1. An information processing method, characterized in that: Applied to the first access point, including: Acquire channel state information of multiple user devices, wherein the multiple user devices include reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate using the reflective functions of multiple omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive functions of the multiple omnidirectional metasurfaces; Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector; The channel state information and the second precoding vector are sent to a network device.

2. The method according to claim 1, characterized in that The acquiring channel state information of multiple user equipments includes: For each user equipment, sending a pilot signal to the user equipment; receiving channel state information fed back by the user equipment according to the pilot signal; Wherein, in the case where the user equipment is the reflective user equipment, the channel state information is obtained by performing channel estimation on a first channel and a second channel, the first channel being a direct channel between the user equipment and the first access point, and the second channel being a cascade channel between the first access point, the multiple omnidirectional metasurfaces, and the user equipment; in the case where the user equipment is the transmissive user equipment, the channel state information is obtained by performing channel estimation on a third channel, and the third channel is a cascade channel between the first access point, the multiple omnidirectional metasurfaces, and the user equipment.

3. The method according to claim 1, characterized in that The optimizing the first precoding vectors of the plurality of user equipments to obtain a second precoding vector includes: Acquire first information, where the first information includes a receiving vector, a weight vector, precoding cross information between the multiple access points, and transmission and reflection phase information and transmission and reflection amplitude information of the multiple omnidirectional metasurfaces; The first precoding vector is optimized according to the first information to obtain a second precoding vector.

4. The method according to claim 3, characterized in that The optimizing the first precoding vector according to the first information to obtain a second precoding vector includes: Determine an objective function according to the receiving vector, the weight vector, the precoding cross information, the transmission reflection phase information and the transmission reflection amplitude information in the first information; The first precoding vector is optimized according to the objective function to obtain a second precoding vector.

5. The method according to claim 4, characterized in that The determining of the objective function according to the receiving vector, the weight vector, the precoding cross information, the transmission reflection phase information and the transmission reflection amplitude information in the first information includes: Under the transmission power constraint condition and the transmission constraint condition of the omnidirectional metasurface, a user sum rate maximization problem is constructed according to the first precoding vector, the transmission reflection phase information, and the transmission reflection amplitude information to obtain a first function; According to the receiving vector and the weight vector, the user sum rate maximization problem is equivalently converted into a mean square error minimization problem, and the first function is equivalently converted into a second function; The second function is simplified according to the receiving vector, the weight vector, the precoding cross information, the transmission and reflection phase information, and the transmission and reflection amplitude information to obtain the objective function.

6. The method according to claim 5, characterized in that The transmission constraint condition includes a phase coupling constraint condition and an amplitude constraint condition; or, the transmission constraint condition includes an amplitude constraint condition.

7. The method according to claim 4, characterized in that The optimizing the first precoding vector according to the objective function to obtain a second precoding vector includes: Introducing the transmit power constraint condition into the objective function using a Lagrange multiplier method, and applying a first-order optimization condition to the objective function to obtain an optimal expression of a precoding vector; Determine a third precoding vector according to the optimal expression of the precoding vector; The first precoding vector is optimized according to the third precoding vector to obtain the second precoding vector.

8. The method according to any one of claims 3 to 7, characterized in that After sending the channel state information and the second precoding vector to the network device, the method further includes: Determine whether the rate optimization conditions are met; When the rate optimization condition is not met, the following operations are performed in a loop until the loop ends when the rate optimization condition is met; receiving second information sent by the network device; Optimize the second precoding vector according to the second information to obtain a fourth precoding vector; Sending the fourth precoding vector to the network device; In which, in the first cycle, the second information is obtained by the network device after optimizing and updating the first information; in the Nth cycle, the second information is the third information obtained by the network device after optimizing and updating the second information in the N-1th cycle, and the second precoding vector is the fourth precoding vector obtained in the N-1th cycle.

9. The method according to claim 8, characterized in that The method further comprises: After the cycle is finished, downlink transmission is performed with the multiple user equipments according to the precoding vector obtained in the last cycle.

10. The method according to claim 1, characterized in that The first access point is any one of a plurality of access points, and the plurality of access points and the plurality of omnidirectional hypersurfaces provide communication services for the plurality of user devices by collaboratively interacting with the network device.

11. An information processing method, characterized in that: Applied to network equipment, including: receiving channel state information and second precoding vectors of multiple user equipments sent by multiple access points, the multiple user equipments including reflective user equipments and transmissive user equipments, the reflective user equipments are equipments that communicate by using the reflective functions of multiple omnidirectional metasurfaces, the transmissive user equipments are equipments that communicate by using the transmissive functions of the multiple omnidirectional metasurfaces, and the second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user equipments by the multiple access points; According to the channel state information and the second precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized.

12. The method according to claim 11, characterized in that The optimizing the transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces according to the channel state information and the second precoding vector includes: Obtain a second function, where the second function is obtained by equivalently transforming the first function when the user sum rate maximization problem is equivalently transformed into a mean square error minimization problem according to the receiving vector and the weight vector, and the first function is obtained when the user sum rate maximization problem is constructed according to the first precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information under the transmission power constraint condition and the transmission constraint condition of the multiple omnidirectional metasurfaces; Applying a first-order optimization condition to the second function according to the channel state information and the second precoding vector, updating the receiving vector, and obtaining an updated receiving vector; Updating the weight vector according to the channel state information, the second precoding vector and the updated receiving vector to obtain an updated weight vector; Updating the precoding cross information according to the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector to obtain updated precoding cross information; The transmission reflection phase information and the transmission reflection amplitude information are optimized according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the second function to obtain optimized transmission reflection phase information and optimized transmission reflection amplitude information.

13. The method according to claim 12, characterized in that In a case where the transmission constraint condition includes a phase coupling constraint condition and an amplitude constraint condition, optimizing the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector, and the second function to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information, including: Acquire auxiliary variables equivalent to the reflection coefficients and transmission coefficients of the plurality of omnidirectional metasurfaces; Transforming the second function according to the auxiliary variable to obtain a third function under an equality constraint, wherein the equality constraint is a constraint obtained by equating the reflection coefficient and the transmission coefficient to the auxiliary variable; Introducing the equality constraint into the third function as a penalty term, and transforming the third function according to the penalty factor of the equality constraint and the Lagrange dual variable to obtain a target expression; According to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the target expression, the transmission reflection phase information and the transmission reflection amplitude information are optimized to obtain optimized transmission reflection phase information and optimized transmission reflection amplitude information.

14. The method according to claim 13, characterized in that The optimizing the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector and the target expression to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information includes: Introducing the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector into the target expression to obtain a first expression; Optimizing the reflection coefficient and the transmission coefficient according to the first expression to obtain an optimized reflection coefficient and an optimized transmission coefficient; Determining a second expression for optimizing the auxiliary variable according to the optimized reflection coefficient, the optimized transmission coefficient and the target expression; Decomposing the auxiliary variable in the second expression into a transmission reflection phase variable and a transmission reflection amplitude variable, and converting the second expression into a third expression according to the transmission reflection phase variable and the transmission reflection amplitude variable; The transmission reflection phase variable and the transmission reflection amplitude variable are optimized according to the third expression to obtain an optimized transmission reflection phase variable and an optimized transmission reflection amplitude variable.

15. The method according to claim 12, characterized in that In a case where the transmission constraint condition includes an amplitude constraint condition, optimizing the transmission reflection phase information and the transmission reflection amplitude information according to the channel state information, the second precoding vector, the updated receiving vector, the updated weight vector, and the second function to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information, comprises: Introducing the channel state information, the second precoding vector, the updated receiving vector, and the updated weight vector into the second function to obtain a fourth expression; The transmission reflection phase information and the transmission reflection amplitude information are optimized according to the fourth expression to obtain optimized transmission reflection phase information and optimized transmission reflection amplitude information.

16. The method according to claim 12, characterized in that After obtaining the optimized transmission-reflection phase information and the optimized transmission-reflection amplitude information, the method further includes: Determine whether the rate optimization conditions are met; When the rate optimization condition is not met, the following first operation is executed in a loop until the loop ends when the rate optimization condition is met: Sending second information to the multiple access points, the second information including an updated receiving vector, an updated weight vector, updated precoding cross information, optimized transmission and reflection phase information, and optimized transmission and reflection amplitude information; receiving fourth precoding vectors sent by the multiple access points; Updating the second information according to the channel state information and the fourth precoding vector to obtain third information; In which, in the first cycle, the fourth precoding vector is obtained by the multiple access points after optimizing the second precoding vector according to the second information; in the Nth cycle, the second information is the third information obtained in the N-1th cycle, and the fourth precoding vector is obtained by the multiple access points after optimizing the fourth precoding vector obtained in the N-1th cycle according to the second information sent by the network device in the Nth cycle.

17. The method according to claim 16, characterized in that In the case where the transmission constraints of the multiple omnidirectional metasurfaces include phase coupling constraints, after the loop ends, the method further includes: Determine whether the transmission reflection phase information and the transmission reflection amplitude information obtained at the end of the cycle meet the transmission reflection coefficient optimization condition; When the transmission coefficient optimization condition is not met, the following second operation is executed in a loop until the transmission coefficient optimization condition is met and the loop ends: Updating a first parameter in a target expression for optimizing the transmission-reflection phase information and the transmission-reflection amplitude information to obtain a second parameter; The second parameter is brought into the target expression, and the first operation is executed in a loop based on the target expression until the rate optimization condition is met.

18. The method according to claim 16 or 17, characterized in that The method further comprises: When the cycle ends, the transmission and reflection phase information and the transmission and reflection amplitude information obtained in the last cycle are sent as target information to the controller of the multiple omnidirectional metasurfaces, and the target information is used by the controller to perform transmission and reflection phase regulation and transmission and reflection amplitude regulation on the multiple omnidirectional metasurfaces.

19. A communication device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 18.

20. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of a communication device, the communication device is enabled to execute the method according to any one of claims 1 to 18.

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