Information processing method, communication device, and computer readable storage medium

Abstract

The present application provides an information processing method. The method comprises: a first access point acquiring channel state information of a plurality of user equipments, the plurality of user equipments including a reflective user equipment and a transmissive user equipment, the reflective user equipment being a device that uses reflection functions of a plurality of omnidirectional metasurfaces for communication, and the transmissive user equipment being a device that uses transmission functions of the plurality of omnidirectional metasurfaces for communication; optimizing first pre-coding vectors of the plurality of user equipments to obtain second pre-coding vectors; and sending the channel state information and the second pre-coding vectors to a network device. The present application further provides a communication device and a computer readable storage medium.

Description

Information processing method, communication device and computer-readable storage medium

[0001] Cross-references

[0002] This application claims priority to the Chinese patent application filed with the China Patent Office on September 5, 2023, with application number 202311140990.4 and titled “Information Processing Method, Communication Equipment and Computer-Readable Storage Medium”. The entire contents of that application are incorporated herein by reference. Technical Field

[0003] The present application relates to the field of communication technology, and in particular to an information processing method, communication equipment, and computer-readable storage medium. Background Art

[0004] In response to the demand for 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 Intelligence Surface (RIS) are key candidate technologies. Intelligent metasurfaces include reflective intelligent metasurfaces and omnidirectional metasurfaces (IOS). Reflective intelligent metasurfaces have the function of controlling signal reflection, while omnidirectional metasurfaces have the dual function of controlling signal 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 the cell-free network can work together with omnidirectional metasurfaces to interact with network devices (such as core network devices), thereby providing communication services for multiple user devices.

[0005] In the case of omnidirectional metasurface-assisted cell-free networks, it is usually necessary to design the precoding vector of the access point and the transmission and reflection phase information and amplitude information of the omnidirectional metasurface. However, there is currently a lack of an effective technical solution to achieve this goal.

[0006] Summary of the Invention

[0007] The present application provides an information processing method, a communication device, and a computer-readable storage medium.

[0008] In a first aspect, an information processing method is provided, applied to a first access point, comprising: obtaining channel state information of multiple user devices, the multiple user devices including reflective user devices and transmissive user devices, the reflective user devices being devices that communicate using the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices being devices that communicate using the transmissive function of the multiple omnidirectional metasurfaces; optimizing first precoding vectors of the multiple user devices to obtain second precoding vectors; and sending the channel state information and the second precoding vector to a network device.

[0009] In a second aspect, an information processing method is provided, which is applied to a network device, including: receiving channel state information and a second precoding vector of multiple user devices sent by multiple access points, the multiple user devices including 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 transmission function of the multiple omnidirectional metasurfaces, and the second precoding vector is obtained by the multiple access points after optimizing the first precoding vectors of the multiple user devices; and optimizing the transmission and reflection phase information and transmission and reflection amplitude information of the multiple omnidirectional metasurfaces based on the channel state information and the second precoding vector.

[0010] In a third aspect, a communication device is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the method described in the first aspect or the second aspect.

[0011] In a fourth aspect, a computer-readable storage medium is provided. 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 described in the first aspect or the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] FIG1 is a schematic diagram of a scenario of an omnidirectional metasurface-assisted cell-free network according to an embodiment of the present application;

[0014] FIG2 is a flow chart of an information processing method according to an embodiment of the present application;

[0015] FIG3 is a flow chart of an information processing method according to an embodiment of the present application;

[0016] FIG4 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;

[0017] FIG5 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;

[0018] FIG6 is a schematic diagram showing the performance effect of an information processing method according to an embodiment of the present application under different AP transmit powers;

[0019] FIG7 is a schematic diagram showing the performance effect of an information processing method according to an embodiment of the present application under different numbers of IOS units;

[0020] FIG8 is a schematic structural diagram of a communication device according to an embodiment of the present application;

[0021] FIG9 is a schematic structural diagram of an information processing device according to an embodiment of the present application;

[0022] FIG10 is a schematic structural diagram of an information processing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] With the rapid development of wireless communication networks, the demand for data transmission is growing exponentially. 5G technologies such as massive multiple-input multiple-output (MIMO), millimeter-wave communications, and ultra-dense networks have significantly increased network capacity. However, these technologies also face challenges with high energy consumption and costs. To support the development of future green and energy-efficient networks, reconfigurable intelligence surfaces (RIS) are currently attracting widespread attention and becoming a key technology for 6G. Using intelligent metasurfaces to assist wireless communication networks can enhance coverage and increase capacity. Meanwhile, another type of metasurface, the omnidirectional metasurface (IOS), has emerged, offering significant potential to increase system capacity compared to traditional intelligent metasurfaces.

[0024] Omnidirectional metasurfaces, also known as simultaneously transmitting and reflecting RIS (STAR-RIS), have the dual function of controlling signal reflection and transmission, extending coverage to the entire space. Furthermore, omnidirectional metasurfaces 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 to solely reflecting or transmitting smart metasurfaces, which can only achieve half-space communication coverage, omnidirectional metasurfaces provide new degrees of freedom for expanding communication coverage, enhancing received signal strength, and improving the quality of service of communication links.

[0025] At present, relevant research has discussed several different working modes of omnidirectional metasurfaces. The first is that the omnidirectional metasurface units 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 research is based on the energy splitting mode. However, relevant research has proposed that according to electromagnetic theory, for completely passive and lossless omnidirectional metasurfaces, there is a constraint that the reflection phase and the transmission phase are coupled, and it is impossible to fully achieve phase independent control. Most of the current system optimization work does not take this constraint model into consideration. In addition, in the scenario of omnidirectional metasurface-assisted cell-free networks, in addition to designing 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.

[0026] The embodiments of the present application provide an information processing method, a communication 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 achieved through interaction between multiple access points in the cell-free network and 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 achieved 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 achieved through 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 shortened, 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.

[0027] In order to help those skilled in the art better understand the technical solutions of this application, the following will clearly and completely describe the technical solutions of this application in conjunction with the drawings of one or more embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0028] The terms "first," "second," and the like in this application and the claims are used to distinguish similar objects and are not used to describe a particular order or precedence. It should be understood that such terms are interchangeable where appropriate so that this application can be implemented in sequences other than those illustrated or described herein. In addition, the term "and / or" in this application and the claims refers to at least one of the connected objects, and the character " / " generally indicates that the connected objects are in an "or" relationship.

[0029] The following, in conjunction with the accompanying drawings, details the technical solutions provided by various embodiments of the present application. It should be noted that in the various embodiments of the present application, RIS and smart metasurface refer to smart metasurfaces with either reflective or transmissive functions, while IOS and omnidirectional metasurface refer to smart metasurfaces with both reflective and transmissive functions.

[0030] FIG1 is a schematic diagram of a scenario of an omnidirectional metasurface-assisted cell-free network according to an embodiment of the present application.

[0031] The network shown in Figure 1 includes multiple user devices, multiple access points (APs), multiple omnidirectional metasurfaces (IOSs), and network devices. Among them, the multiple omnidirectional metasurfaces include multiple units with reflection and transmission functions, and each omnidirectional metasurface can correspond to a controller (not shown in Figure 1), and each controller can regulate the transmission and reflection phase and transmission 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.

[0032] In the network shown in Figure 1, multiple omnidirectional metasurfaces can assist multiple access points in collaboratively serving multiple user devices. Multiple user devices include reflective user devices and transmissive user devices. The reflective user device is a user device that communicates using the reflection function of the omnidirectional metasurface, that is, the user device served by the reflected signals of multiple omnidirectional metasurfaces and multiple access points in Figure 1. The transmissive user device is a user device that communicates using the transmission function of the omnidirectional metasurface, that is, the user device served by the transmitted signals of multiple omnidirectional metasurfaces in Figure 1. Among them, the reflective user device can receive direct connection signals from multiple access points and reflected signals from multiple omnidirectional metasurfaces. Due to the obstruction of the direct connection link, the transmissive user device can only receive the transmitted signals from multiple omnidirectional metasurfaces. 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 reflection amplitude and phase design, so as to maximize the system capacity, thereby better providing communication services for multiple user devices.

[0033] Figure 2 is a flowchart illustrating an information processing method according to an embodiment of the present application. The information processing method illustrated in Figure 2 can be applied to any access point illustrated in Figure 1. In other words, the information processing method can be executed by software or hardware installed in any access point illustrated in Figure 1. For ease of distinction, the first access point may be used to represent the information processing method. The information processing method illustrated in Figure 2 is described as follows.

[0034] 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.

[0035] The multiple user devices here can be the multiple user devices shown in Figure 1, including reflective user devices and transmissive user devices. The channel state information (CSI) of the multiple user devices can 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, the 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, the multiple omnidirectional metasurfaces and the reflective user device.

[0036] When acquiring channel state information of multiple user equipments, the same method can be used for each user equipment to acquire the channel state information. As an embodiment, the channel state information of each user equipment can be acquired by the following steps:

[0037] Sending a pilot signal to the user equipment.

[0038] Receive channel state information fed back by the user equipment based on the pilot signal.

[0039] In one embodiment, when channel state information needs to be obtained, the first access point may send a pilot signal to the user equipment. For a reflective user equipment, the pilot signal may be sent to the reflective user equipment via a first channel and a second channel, where the first channel is a direct channel between the first access point and the reflective user equipment, and the second channel is a cascade channel between the first access point, multiple omnidirectional metasurfaces, and the reflective user equipment (including a direct channel between the first access point and multiple omnidirectional metasurfaces, and a direct channel between multiple omnidirectional metasurfaces and the user equipment). For a transmissive user equipment, the pilot signal may be sent to the transmissive user equipment via a third channel, where the third channel is a cascade channel between the first access point, multiple omnidirectional metasurfaces, and the transmissive user equipment.

[0040] After receiving the pilot signal, the user equipment can perform channel estimation on the first and second channels for the reflection user equipment and obtain channel state information of the reflection user equipment based on the channel estimation results. For the transmission user equipment, channel estimation can be performed on the third channel and obtain channel state information of the transmission user equipment based on the channel estimation results. 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 the user equipment.

[0041] 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 equipment.

[0042] S204: Optimize the first precoding vectors of the multiple user equipments to obtain a second precoding vector.

[0043] The first precoding vector is a downlink precoding vector used by the first access point when performing downlink communications with multiple user devices. In the 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 implementation method of the first access point initializing the first precoding vector can refer to the implementation in the relevant technology and 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. There is no limitation on the method for obtaining the first precoding vector here. Among them, the first precoding vector is not the optimal precoding vector and needs to be optimized to obtain the optimized second precoding vector.

[0044] 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.

[0045] As an embodiment, when optimizing first precoding vectors of multiple user equipments to obtain second precoding vectors, the following steps may be included:

[0046] 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;

[0047] The first precoding vector is optimized according to the first information to obtain a second precoding vector.

[0048] The receiving vector and weight vector in the first information are auxiliary vectors introduced for optimizing the precoding vector. The receiving vector can be the receiving vector of the user equipment when receiving the downlink signal. For example, the receiving vector can be the 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 obtaining the first information, in one embodiment, the first access point can obtain the first information by initialization, or the first access point can obtain the first information from the network device, which is not limited here. After obtaining the first information, the first precoding vector can be optimized based on the first information.

[0049] As an embodiment, optimizing the first precoding vector according to the first information to obtain the second precoding vector may include the following steps:

[0050] Determine an objective function based on the reception vector, weight vector, precoding cross information, transmission reflection phase information, and transmission reflection amplitude information in the first information;

[0051] The first precoding vector is optimized according to the objective function to obtain a second precoding vector.

[0052] The objective function is a function used to optimize the first precoding vector, and may also be referred to as an optimization target expression of the precoding vector (or precoding matrix). The objective function is a convex problem and is easy to solve.

[0053] In one implementation, when determining the objective function according to the reception vector, the weight vector, the precoding cross information, the transmission and reflection phase information, and the transmission and reflection amplitude information, the following S2041 to S2043 may be included.

[0054] 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.

[0055] The transmission power constraint refers to the transmission power constraint of the first access point. In one embodiment, 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 of the omnidirectional metasurface refers to the constraint that the units in the omnidirectional metasurface need to meet when multiple omnidirectional metasurfaces reflect and transmit received signals. Specifically, the transmission constraints of multiple omnidirectional metasurfaces may be different under different scenario requirements. In one implementation, the transmission constraint may include a phase coupling constraint and an amplitude constraint. In another implementation, the transmission constraint may include an amplitude phase constraint, but not a phase coupling constraint, i.e., the phase coupling constraint is not considered.

[0056] Under the transmit power constraint and the transmission constraint of the multiple omnidirectional metasurfaces, a weighted sum rate optimization problem can be constructed based on the first precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information to obtain a first function. The first function is related to the first precoding vector, the weighting coefficients of the multiple user devices, the signal-to-interference-and-noise ratio of the signals received by the multiple user devices, the transmission and reflection phase information, and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces, and is subject to the transmit power constraint and the transmission constraint of the multiple omnidirectional metasurfaces.

[0057] 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.

[0058] 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.

[0059] When transforming the first function, the relationship between the weighted sum of the rates 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 rates 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 maximization weighted sum rate optimization problem is equivalently transformed into a mean square error minimization problem. In this way, the first function can be transformed into the second function.

[0060] 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.

[0061] After obtaining the second function, the second function can be further simplified to obtain the objective function, which is a convex problem.

[0062] Thus, through the above steps S2041 to S2043, the non-convex problem of precoding vector optimization can be transformed into a convex problem, thereby obtaining an easily solvable objective function. After obtaining the objective function, the first precoding vector can be optimized according to the objective function to obtain an optimized second precoding vector.

[0063] 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.

[0064] S2044: Using the Lagrange multiplier method, the transmit power constraint condition is introduced into the objective function, and the first-order optimization condition is applied to the objective function to obtain the optimal expression of the precoding vector.

[0065] Here, the Lagrange multiplier method can be used to address the transmit power constraint. By applying first-order optimization conditions to the objective function for the first access point and multiple user devices, a closed-form form of the active beamformer for the first access point can be derived, yielding the optimal expression for the precoding vector. This optimal expression for the precoding vector is related to the multiplier introduced by the transmit power constraint and the precoding cross-information between multiple access points. The multiplier introduced by the transmit power constraint can be obtained using a bisection method.

[0066] S2045: Determine a third precoding vector according to the optimal expression of the precoding vector.

[0067] After obtaining the optimal expression of the precoding vector, a group of precoding vectors may be calculated based on the optimal expression. For ease of distinction, a third precoding vector may be used for representation.

[0068] S2046: Optimize the first precoding vector according to the third precoding vector to obtain a second precoding vector.

[0069] After obtaining the third precoding vector, the first precoding vector can be optimized based on the third precoding vector to obtain a second precoding vector. When optimizing the first precoding vector based on the third precoding vector, the first precoding vector and the third precoding vector can be weightedly summed (the sum of the weight coefficients of the first precoding vector and the third precoding vector is 1), and the weighted summation result is used as the second precoding vector. This can also be achieved through other methods, which are not limited here.

[0070] At this point, the first precoding vector can be optimized according to the first information, and the optimized second precoding vector can be obtained.

[0071] S206: Send the channel state information and the second precoding vector to the network device.

[0072] 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. The implementation method can refer to the embodiment shown in Figure 3 and will not be described in detail here.

[0073] The transmission and reflection phase information and transmission and reflection amplitude information of the above-mentioned multiple omnidirectional metasurfaces are related to the channel state information and second precoding vectors of multiple user devices. In one embodiment: for a reflective user device, the channel state information of the reflective user device includes the channel state information of the cascaded channel between the first access point, the multiple omnidirectional metasurfaces, and the reflective user device. The cascaded 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 reflective user device is used for the first access point to perform downlink transmission with the reflective user device with the assistance of the reflected signals of the multiple omnidirectional metasurfaces. The reflected 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 reflective user device is also related to the reflection phase and reflection amplitude of the multiple omnidirectional metasurfaces. For a transmissive user device, the channel state information of the transmissive user device is the channel state information of the cascaded channel between the first access point, the multiple omnidirectional metasurfaces, and the transmissive user device. The cascaded 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 device is used for the first access point to perform downlink transmission with the transmission user device 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 device is also related to the transmission phases and transmission amplitudes of the multiple omnidirectional metasurfaces.

[0074] 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, it is possible to achieve the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information in the scenario where the omnidirectional metasurface assists in 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 achieved by the interactive collaboration between the network equipment and multiple access points, it is also possible to effectively reduce the computational complexity of the network equipment, shorten the processing time, and increase the efficiency, which can effectively guarantee the system performance.

[0075] 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 based on the second precoding vector whether the rate value of the user and rate maximization problem constructed above converges. 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. If the rate optimization condition is met, it can be determined 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. If the rate optimization condition is not met, it can be determined that the second precoding vector is not the optimal precoding vector and needs to be optimized.

[0076] When optimizing the second precoding vector, the first access point may exchange information with the network device and optimize the second precoding vector in an iterative loop based on the exchanged information. As an embodiment, when optimizing the second precoding vector, steps S208 to S212 may be executed in a loop until a rate optimization condition is met.

[0077] S208: Receive second information sent by the network device.

[0078] In the first cycle, the second information is obtained by the network device after optimizing and updating the above-mentioned first information, that is, the second information includes 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. Among them, the implementation method of the network device optimizing and updating the first information can refer to the corresponding content in the embodiment shown in Figure 3, and will not be described in detail here. In the Nth (an integer greater than or equal to 2) cycle, the second information can be the third information obtained by the network device after optimizing and updating the second information in the N-1th cycle. Among them, the implementation method of the network device updating the second information is the same as the implementation method of the network device optimizing and updating the first information.

[0079] S210: Optimize the second precoding vector according to the second information to obtain a fourth precoding vector.

[0080] The implementation method for the first access point to optimize the second precoding vector based on the second information is the same as the implementation method for the first access point to optimize the first precoding vector based on the first information described above, and is not repeated here. After optimizing the second precoding vector, a set of precoding vectors can be obtained, which can be represented by a fourth precoding vector for ease of distinction.

[0081] It should be noted that in the first loop, 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)th loop, the second precoding vector is the fourth precoding vector obtained in the N-1th loop.

[0082] S212: Send the fourth precoding vector to the network device.

[0083] After sending the fourth precoding vector to the network device, the network device may update the second information in the previous cycle based on the fourth precoding vector and the channel state information of multiple user devices previously received, and send the updated third information to the first access point. The implementation method of the network device can refer to the embodiment shown in Figure 3 and will not be described in detail here.

[0084] In the above loop process, when the rate optimization condition is met, the loop can be ended.

[0085] After the cycle ends, for the first access point, the fourth precoding vector obtained in the last cycle can be used as the optimal precoding vector.

[0086] In one embodiment, after obtaining the optimal precoding vector, the first access point may perform downlink transmission with multiple user devices based on the optimal precoding vector. Thus, because the precoding vector used for downlink transmission is the optimal precoding vector, the first access point can better provide communication services for the multiple user devices when performing downlink transmission with the multiple user devices based on the optimal precoding vector.

[0087] 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 through interaction between multiple access points in the cell-free network and 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, it is possible to achieve the design of the precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information in a scenario where the omnidirectional metasurface assists in 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 achieved through the interactive collaboration between the network device and the multiple access points, it is also possible to effectively reduce the computational complexity of the network device, shorten the processing time, and increase the efficiency, thereby effectively ensuring the system performance.

[0088] Figure 3 is a flow chart of an information processing method according to an embodiment of the present application. The information processing method shown in Figure 3 can be applied to the network device shown in Figure 1. In other words, the information processing method can be executed by software or hardware installed in the network device. In one embodiment, the information processing method can be executed by a CPU in the network device. The information processing method shown in Figure 3 is described as follows.

[0089] S302: Receive channel state information and second precoding vectors 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 transmission function of multiple omnidirectional metasurfaces. The second precoding vector is obtained by optimizing the first precoding vectors of the multiple user devices by the multiple access points.

[0090] For each of the multiple access points, channel state information of multiple user devices can be determined based on the method described in the embodiment shown in FIG. 2 , and the first precoding vectors of the multiple user devices can be optimized to obtain a second precoding vector. The channel state information and the second precoding vector are then transmitted to a network device, which can receive the channel state information and the second precoding vector transmitted from the multiple access points. The channel state information transmitted by each access point can be downlink channel state information of each of the multiple user devices when the access point, with the assistance of multiple omnidirectional metasurfaces, conducts downlink communications with the multiple user devices. The first precoding vectors of the multiple user devices can be initialized by the access point.

[0091] 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.

[0092] 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 limited here. Since the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces are not 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, thereby realizing the design of the transmission and reflection phase information and transmission and reflection amplitude information of multiple omnidirectional metasurfaces.

[0093] 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.

[0094] S3041: Get the second function.

[0095] The second function here and the second function in the embodiment shown in FIG2 are obtained by using a single function. In one embodiment, the first function is equivalently transformed based on the received vector and the weight vector, converting the user sum rate maximization problem into a mean square error minimization problem. The first function is obtained by constructing the user sum 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 and the transmission constraint of multiple omnidirectional metasurfaces. The implementation method for determining the first function and the implementation method for converting the first function into the second function can be referred to the corresponding content in the embodiment shown in FIG2, and will not be repeated here.

[0096] 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 limited here.

[0097] 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.

[0098] After obtaining the second function, a first-order optimization condition may be applied to the second function based on the channel state information and the second precoding vector received in S302, thereby updating the received vector to obtain an updated received vector. The expression of the updated received vector may be determined based on the channel state information and the second precoding vector.

[0099] 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.

[0100] After obtaining the updated receive vector, the weight vector may 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 may be determined based on the channel state information, the second precoding vector, and the updated receive vector.

[0101] 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.

[0102] After obtaining the updated receive 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 for the updated precoding cross information can be determined based on the channel state information, the second precoding vector, the updated receive vector, and the updated weight vector.

[0103] S3045: Optimize 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 second function to obtain optimized transmission and reflection phase information and optimized transmission and reflection amplitude information.

[0104] 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.

[0105] 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 the multiple omnidirectional metasurfaces. The transmission constraints of multiple omnidirectional metasurfaces refer to the constraints that the units in the omnidirectional metasurfaces need to meet 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. In one implementation, the transmission constraints may include phase coupling constraints and amplitude constraints. In another implementation, the transmission constraints may include amplitude-phase constraints, but not 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.

[0106] In one embodiment, when the transmission constraints include phase coupling constraints and amplitude constraints, 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:

[0107] Step 1: Obtain auxiliary variables equivalent to the reflection coefficients and transmission coefficients of multiple omnidirectional metasurfaces.

[0108] For each omnidirectional metasurface, its reflection coefficient can be determined based on the reflection phase and reflection amplitude of multiple units in the omnidirectional metasurface, and its transmission coefficient can be determined based on the transmission phase and transmission amplitude of multiple units in the omnidirectional metasurface. Here, the reflection coefficients and transmission coefficients of multiple omnidirectional metasurfaces can be equivalent to auxiliary variables, so that the transmission and reflection phase and transmission and reflection amplitude can be optimized with the help of these auxiliary variables.

[0109] Step 2: Transform the second function according to the auxiliary variables to obtain a third function under the equality constraint. The equality constraint is the constraint obtained by equating the reflection coefficient and the transmission coefficient to auxiliary variables.

[0110] 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 transmission and reflection phase and transmission and reflection amplitude.

[0111] Step 3: Introduce the equality constraint as a penalty term into the third function, and transform the third function according to the penalty factor of the equality constraint and the Lagrange dual variable to obtain the target expression.

[0112] After introducing the equality constraint as a penalty term into the third function, the optimization problem of the transmission and reflection phase and 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. Finally, the optimal objective expression for phase and amplitude optimization can be obtained.

[0113] Step 4: 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 target expression to obtain the optimized transmission reflection phase information and the optimized transmission reflection amplitude information.

[0114] When optimizing the transmission-reflection phase and amplitude information based on the channel state information, the second precoding vector, the updated receive vector, the updated weight vector, and the target expression, the variables to be optimized can be divided into two groups: one group consisting of the reflection coefficients and transmission coefficients of multiple omnidirectional metasurfaces, and the other group consisting of auxiliary variables equivalent to these reflection coefficients and transmission coefficients. By optimizing these two groups of variables, the optimized transmission-reflection phase and amplitude information can be obtained.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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, thereby obtaining the optimized reflection coefficient and the optimized transmission coefficient.

[0120] Step 43: Determine a second expression for optimizing the auxiliary variables based on the optimized reflection coefficient, the optimized transmission coefficient, and the target expression.

[0121] Here, the target expression can be simplified according to the optimized reflection coefficient and the optimized transmission coefficient, thereby obtaining a second expression. The second expression includes terms involving auxiliary variables.

[0122] Step 44: Decompose the auxiliary variables 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.

[0123] The second expression is further transformed. In one embodiment, the auxiliary variables in the second expression are decomposed into a transmission reflection phase variable and a transmission reflection amplitude variable. Based on the decomposed transmission reflection phase variable and transmission reflection amplitude variable, the second expression is transformed to obtain a third expression. The third expression includes the transmission reflection phase variable and the transmission reflection amplitude variable. Based on the third expression, the transmission reflection phase variable and the transmission reflection amplitude variable can be optimized, that is, the auxiliary variables can be optimized.

[0124] 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.

[0125] During optimization, the transmission reflection amplitude variable can be given, and then the transmission reflection phase variable can be optimized according to the third expression, thereby obtaining the optimized transmission reflection phase variable. Thereafter, the transmission reflection phase variable can be given, and then the transmission reflection amplitude variable can be optimized according to the third expression, thereby obtaining the optimized transmission reflection amplitude variable.

[0126] Based on the above S41 to S45, two sets of optimized transmission-reflection phase information and transmission-reflection amplitude information can be obtained. The first set is the optimized reflection coefficient and the optimized transmission coefficient obtained in the above S42, and the second set is the optimized transmission-reflection phase variable and transmission-reflection amplitude variable obtained in the above S45.

[0127] It should be noted that in other possible implementations, the penalized dual decomposition method mentioned above can also be used to obtain the transmission and reflection phase design under the coupled phase. For example, the phase design can be performed through a unit-by-unit optimization method. Under the coupled constraint conditions, one phase is first optimized, and then the optimal other phase is selected from the constraint set; or the transmission and reflection phases are optimized separately without considering the constraints, and finally the phase error is divided equally between the two phases based on the principle of optimal performance according to the coupled constraints. Considering that these methods will result in a large performance loss under the phase constraint conditions, if there are no special requirements, the penalized dual decomposition method can be used to solve the phase optimization problem.

[0128] As an embodiment, if the transmission constraints of multiple omnidirectional metasurfaces include amplitude constraints, 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 second function may include the following steps:

[0129] 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;

[0130] 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.

[0131] Because the transmission constraints of multiple omnidirectional metasurfaces only include amplitude constraints and do not consider phase coupling constraints, there is no need to introduce auxiliary variables when optimizing the transmission and reflection phase information and the transmission and reflection amplitude information. Without the need for auxiliary variables, during optimization, the channel state information, the second precoding vector, the updated receive vector, and the updated weight vector can be introduced into the second function to obtain a fourth expression for optimizing the transmission and reflection phase and the transmission and reflection amplitude. The fourth expression is a convex problem. After obtaining the fourth expression, the optimized transmission and reflection phase information and the optimized transmission and reflection amplitude information can be obtained by solving the fourth expression using a convex tool.

[0132] Thus, the transmission and reflection phase information and the transmission and reflection amplitude information can be optimized for different transmission constraints of multiple omnidirectional metasurfaces, and the optimized transmission and reflection phase information and transmission and reflection amplitude information can be obtained. The optimized transmission and reflection phase information can be continuous phase information.

[0133] 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, it is possible to achieve the design of the precoding vector, the transmission and reflection phase information and the transmission and reflection amplitude information in the scenario where the omnidirectional metasurface assists in 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 achieved by the interactive collaboration between the network equipment and multiple access points, it is also possible to effectively reduce the computational complexity of the network equipment, shorten the processing time, and increase the efficiency, which can effectively guarantee the system performance.

[0134] As an embodiment, after obtaining the optimized transmission-reflection phase information and optimized transmission-reflection amplitude information, the network device may further determine whether the rate optimization condition is met. When determining whether the rate optimization condition is met, the rate values ​​of the user and rate maximization problem constructed above may be determined to have converged based on the optimized transmission-reflection phase information and the optimized transmission-reflection amplitude information. If so, it may be determined that the rate optimization condition is met; if not, it may be determined that the rate optimization condition is not met. Specifically, for the two sets of optimized transmission-reflection phase information and transmission-reflection amplitude information obtained in S41 to S45, when determining whether the rate optimization condition is met, the determination may be made based on the first set, i.e., the optimized reflection coefficient and optimized transmission coefficient obtained in S42.

[0135] If the rate optimization conditions are met, the optimized transmission and reflection phase information and transmission and reflection amplitude information are the optimal transmission and reflection phase and amplitude information. The network device can then send them to the controllers of multiple omnidirectional metasurfaces, which then perform phase and amplitude control on the multiple omnidirectional metasurfaces. If the rate optimization conditions are not met, the optimized transmission and reflection phase information and transmission and reflection amplitude information are not optimal and require further optimization.

[0136] 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 an iterative loop based on the exchanged information. As an embodiment, when optimizing the transmission reflection phase information and the transmission reflection amplitude information, the following steps S306 to S310 may be executed in a loop until the rate optimization condition is met and the loop ends.

[0137] 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.

[0138] In the first loop, the updated receive vector, updated weight vector, and updated precoding cross information are the updated receive vector, weight vector, and precoding cross information obtained through S3041 to S3044. The optimized transmission-reflection phase information and optimized transmission-reflection amplitude information refer to the transmission-reflection phase information and transmission-reflection amplitude information obtained through the optimization in S3045. In particular, considering the phase coupling constraints and amplitude constraints of multiple omnidirectional metasurfaces, the optimized transmission-reflection phase information and optimized transmission-reflection amplitude information may be the optimized reflection coefficient and optimized transmission coefficient obtained through S42.

[0139] 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.

[0140] S308: Receive fourth precoding vectors sent by multiple access points.

[0141] In the first cycle, the fourth precoding vector is obtained by the multiple access points optimizing the second precoding vector based on 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 the multiple access points optimizing the fourth precoding vector in the N-1th cycle based on the second information sent by the network device in the Nth cycle.

[0142] S310: Optimize and update the second information according to the channel state information and the fourth precoding vector to obtain third information.

[0143] When optimizing and updating the second information according to the channel state information and the fourth precoding vector, the implementation method may refer to the corresponding content in the above S304 and will not be described in detail here.

[0144] It should be noted that the above-mentioned loop process from S306 to S310 is integrated with the loop process from S208 to S212 in the embodiment shown in Figure 2. 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 based on 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 loop, the network device sends the third information as the second information to multiple access points. After receiving the second information, each access point can optimize the second precoding vector (the fourth precoding vector obtained in the previous loop) based on the second information to obtain a fourth precoding vector. The fourth precoding vector is then sent to the network device. The network device optimizes and updates the second information (i.e., the third information obtained in the previous loop) based on the fourth precoding vector and the previously received channel state information to obtain the third information, thus completing the second loop. This loop operation is repeated in this way. When the rate optimization condition is met, the network device and the multiple access points can end the loop.

[0145] After the cycle is completed, multiple access points can obtain precoding vectors that meet the rate optimization condition, and the network equipment can obtain transmission and reflection phase information and transmission and reflection amplitude information that meet the rate optimization condition.

[0146] In an embodiment of the present application, if the amplitude constraints of multiple omnidirectional metasurfaces are considered without considering the phase coupling constraints, the transmission-reflection phase information and transmission-reflection amplitude information obtained after the above cycle is completed can be used as the optimal transmission-reflection phase information and transmission-reflection amplitude information, and sent to the controllers of the multiple omnidirectional metasurfaces. The controllers of the multiple omnidirectional metasurfaces then perform transmission-reflection phase and transmission-reflection amplitude control on the multiple omnidirectional metasurfaces based on the received transmission-reflection phase information and transmission-reflection amplitude information. If both the amplitude constraints of the multiple omnidirectional metasurfaces and the phase coupling constraints of the multiple omnidirectional metasurfaces are considered, then, since auxiliary variables are introduced in the phase and amplitude optimization process, it is necessary to further determine whether the transmission-reflection phase information and transmission-reflection amplitude information obtained at the end of the above cycle are the optimal phase and amplitude.

[0147] As an embodiment, when determining whether the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above loop are the optimal phase and amplitude, it can be determined whether the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the loop meet the transmission reflection coefficient optimization condition. The transmission reflection coefficient optimization condition here is an optimization condition related to the auxiliary variables introduced above. In one embodiment, 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. If so, the transmission reflection coefficient optimization condition is met; if not, the transmission reflection coefficient optimization condition is not met. If the transmission reflection coefficient optimization condition is met, it can be determined that the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above loop are the optimal phase and amplitude, and can be sent to the controllers of multiple omnidirectional metasurfaces for phase and amplitude control. If the transmission reflection coefficient optimization condition is not met, it can be determined that the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the above loop are not the optimal phase and amplitude, and need to be further optimized.

[0148] When further optimizing the transmission-reflection phase information and the transmission-reflection amplitude information obtained at the end of the above loop, the following S312 to S314 may be executed cyclically until the transmission-reflection coefficient optimization condition is met and the loop is terminated.

[0149] 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.

[0150] 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 and introducing auxiliary variables.

[0151] The first parameter may be a parameter in the objective expression that affects the optimization of the transmission reflection phase and the transmission reflection amplitude. In one embodiment, the first parameter may be a penalty factor and a Lagrange dual variable in the objective expression.

[0152] 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.

[0153] After updating the first parameter in the target representation to obtain the second parameter, the second parameter can be substituted into the target expression, and the transmission and reflection phase information and the transmission and reflection amplitude information obtained at the end of the above loop can be optimized based on the target expression. During optimization, the first operation can be executed repeatedly, which is S306 to S310 described above. In other words, S306 to S310 can be executed repeatedly until the rate optimization condition is met and S306 to S310 is terminated (while executing S306 to S310 repeatedly, multiple access points can interact with the network device through S208 to S212 shown in Figure 2). After completing execution of S306 to S310, it is possible to continue to determine whether the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the loop 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 transmission reflection amplitude information again. The loop operation of S312 and S314 is terminated until the transmission reflection coefficient optimization condition is met. The transmission reflection phase information and transmission reflection amplitude information obtained at this time can be regarded as the optimal transmission reflection phase information and transmission reflection amplitude information.

[0154] 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, S306 to S310 needs to be cycled multiple times. The condition for ending the cycle of S306 to S310 is that the rate optimization condition is met, and the condition for ending the cycle of S312 to S314 is that the transmission and reflection coefficient optimization condition is met. When the cycle of S312 to S314 meets the transmission and reflection coefficient optimization condition, the loop operation of S312 to S314 can be ended, and there is no need to cycle S306 to S310.

[0155] After completing the above-mentioned loop operations of S312 and S314, the network device can send the transmission reflection phase information and transmission reflection amplitude information obtained at the end of the loop to the controllers of the multiple omnidirectional metasurfaces, so that the controllers of the multiple omnidirectional metasurfaces can respectively adjust the transmission reflection phase and transmission reflection amplitude of the 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, the 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.

[0156] 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 through interaction between multiple access points in the cell-free network and 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, it is possible to achieve the design of the precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information in a scenario where the omnidirectional metasurface assists in 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 achieved through the interactive collaboration between the network device and the multiple access points, it is also possible to effectively reduce the computational complexity of the network device, shorten the processing time, and increase the efficiency, thereby effectively ensuring the system performance.

[0157] In order to facilitate understanding of the technical solution provided by the embodiment of the present application, a more specific implementation method will be used as an example for explanation. Please refer to Figures 4 and 5. The embodiments shown in Figures 4 and 5 are both described as an example of a cell-free network including B APs and L IOSs, which collaboratively serve K user devices. Among them, the K user devices include K 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.

[0158] The embodiment shown in Figure 4 takes into account the phase coupling constraints and amplitude constraints of multiple omnidirectional metasurfaces. The embodiment shown in Figure 4 may include the following steps.

[0159] S401: Multiple APs obtain channel state information of multiple user equipments.

[0160] In one embodiment, only the first-order reflection or transmission is considered, and represents the equivalent channel from the bth AP to the kth reflective 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 obstruction, the transmitted user device has no direct connection channel to the AP.

[0161] 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 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 reflection and transmission phase shifts must satisfy the constraint

[0162] With the assistance of multiple IOS, considering that the transmission user equipment has no direct connection channel due to the obstruction, the bth AP to the A reflective user device and The equivalent combined channels (i.e., equivalent channel models) of the transmitted user equipment can be expressed as:

[0163] Then the received signal of the kth reflection / transmission user equipment can be uniformly expressed as:

[0164] Among them, s m represents the symbol sent by the target to user m, represents the beamforming matrix designed by AP b for user m’s transmission signal, and defines represents the Gaussian noise at user equipment k.

[0165] S402: Multiple APs optimize first precoding vectors of multiple user equipments to obtain second precoding vectors.

[0166] When optimizing a first precoding vector, each AP can obtain first information and optimize the first precoding vector based on the first information. The first information includes a receive 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.

[0167] When optimizing the first precoding vector, the following steps 1 to 3 may be included.

[0168] Step 1: Construct the user sum rate maximization problem (also known as the weighted sum 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:

[0169] The problem of maximizing the weighted sum rate optimization can be described as the following formula (i.e., the first function in the embodiment shown in FIG2 ):

[0170] Among them, P max ,ω k Represents the maximum transmit power of each AP and the user weighting coefficient respectively.

[0171] Step 2: By introducing the receiving vector and weight vector u k ,f k , The user sum rate maximization problem is equivalently converted into a mean square error minimization problem, and the above first function is transformed to obtain the following formula (i.e., the second function in the embodiment shown in FIG2 ):

[0172] Among them, c is an irrelevant constant term, mse k is the mean square error of the received signal at user equipment k, which can be expressed as:

[0173] 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., the objective function in the embodiment shown in FIG2 ):

[0174] Among them, the coefficient of the quadratic term with respect to W is Its elements are represented as The coefficient of the first-order term is Its elements are represented as

[0175] Step 3: Further use the Lagrange multiplier method to process the transmit power constraint and apply the first-order optimization condition to the above objective function to obtain the closed-form distributed optimal solution of the AP's active beamformer (i.e., the optimal expression of the precoding vector in the embodiment shown in Figure 2): b,k =(Ξ bb+ +λ b I) -1 (z b,k -ξ b,k ).

[0176] 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.

[0177] After obtaining the optimal expression, the first precoding vector can be optimized based on the optimal expression. b,k Each AP b and other APs calculate w locally according to the above formula at the same time 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:

[0178] 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 the tth iteration is based on The calculated precoding vector.

[0179] S403: The multiple APs send the channel state information and the second precoding vector to the network device.

[0180] 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.

[0181] During optimization, the following steps 1 to 4 may be included.

[0182] Step 1: Based on the channel state information obtained from the AP and the second precoding vector of each AP, for the above formula By optimizing the first-order optimization conditions of the variables, the access vector is updated. The updated receiving vector can be expressed as:

[0183] 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:

[0184] Afterwards, the AP's 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:

[0185] Step 2: Based on the updated receiving vector, the updated weight vector and the second precoding vector, a PDD-based method is used to handle the non-convex constraints introduced by multi-IOS (i.e., the phase coupling constraint and amplitude constraint of multi-IOS). First, auxiliary variables equivalent to the reflection coefficient and transmission coefficient are defined. The above formula, By performing the transformation, the phase and amplitude optimization problem can be expressed as the following formula (i.e., the third function in the embodiment shown in FIG3 ):

[0186] 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 to indicate violation of the first constraint in the above formula, and the Lagrangian dual variable λ x , The above problem can be converted into the following formula (i.e., the target expression in the embodiment shown in FIG3 ):

[0187] 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.

[0188] Step 3: For {φ r ,φ t In one embodiment, 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 =[φx,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, then {φ r ,φ t The optimization problem of} can be re-expressed as the following formula (i.e., the first expression in the embodiment shown in FIG3 ):

[0189] The above formula is a convex problem and can be easily solved using convex optimization tools. Among them, the quadratic term coefficient of the phase vector is Each matrix element Combination Vector Since the reflecting user equipment has both the direct link of the AP 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 there is no direct link to the transmitted user equipment, item C is not included. l,k , coefficient p t,l Expressed as

[0190] Step 4: Optimize. Based on the optimized {φ r ,φ t}, then optimize the auxiliary variables Ignoring other irrelevant terms, the optimization problem of auxiliary variables can be expressed as the following formula:

[0191] Among them, the variable θ is introduced x =-φ x +ρλ x , Expand the above formula, because The above formula can be transformed into the following formula (i.e., the second expression in the embodiment shown in FIG3 ):

[0192] In the above formula, only the term involves optimization variables, while the other terms are constants. Therefore, we can Decomposition into magnitude vectors and phase vector Right now Ignoring irrelevant terms, the optimization problem of the auxiliary variables can be expressed as the following formula (i.e., the third expression in the embodiment shown in FIG3 ):

[0193] Here, the constraint is reintroduced It is used to ensure that all phase shifts are collected in the following optimization process. and Definition Given The optimal phase shift for each unit can be solved as

[0194] 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

[0195] Through the above steps, two sets of optimized transmission and reflection phase information and transmission and reflection amplitude information can be obtained. The first set is {φ r ,φ t The second group is the transmission reflection phase information and transmission reflection amplitude information obtained after optimization. The transmission and reflection phase information and transmission and reflection amplitude information obtained after optimization.

[0196] S405: The network device sends the optimized transmission and reflection phase information and transmission and reflection amplitude information to multiple APs.

[0197] The transmission and reflection phase information and the transmission and reflection amplitude information sent by the network device to 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 together. 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. In this way, 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.

[0198] S406: When the convergence rate value is obtained, the loop ends.

[0199] 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.

[0200] After the cycle ends, it can be determined whether the transmission reflection phase information and transmission reflection amplitude information at the end of the cycle meet the transmission reflection coefficient optimization conditions. Here, it can be determined whether φ x and Is the difference between is less than or equal to a preset threshold? If so, S410 can be executed. If not, S408 can be executed.

[0201] S408: The network device updates the first parameter in the target expression for optimizing the transmission and reflection phase information and the transmission and reflection amplitude information to obtain a second parameter.

[0202] The target expression here is the following formula in S404:

[0203] The first parameter can be the penalty factor ρ and the Lagrange dual variable λ in the formula x , in the case of ρ and λ x When updating, we can set ρ = 0.1ρ,

[0204] 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.

[0205] 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, at the end of the outer loop, 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.

[0206] S410: Multiple APs perform downlink transmission with multiple user equipments based on the precoding vectors obtained in the last cycle.

[0207] 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.

[0208] S412: 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.

[0209] The embodiment shown in Figure 5 considers the amplitude constraints of multiple omnidirectional metasurfaces and does not consider the phase coupling constraints, that is, considers a phase-independent model. The embodiment shown in Figure 5 includes the following steps.

[0210] S501: Multiple APs obtain channel state information of multiple user equipments.

[0211] S502: Multiple APs optimize first precoding vectors of multiple user equipments to obtain second precoding vectors.

[0212] The implementation of S501 and S502 can refer to the above S401 and S402, and will not be repeated here.

[0213] S503: The multiple APs send the channel state information and the second precoding vector to the network device.

[0214] 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.

[0215] When optimizing, the following steps 1 and 2 may be included.

[0216] Step 1: Based on the channel state information obtained from the AP and the second precoding vector of each AP, for the above formula By optimizing the first-order optimization conditions of the variables, the access vector is updated. The updated receiving vector can be expressed as:

[0217] 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:

[0218] Afterwards, the AP's 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:

[0219] 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 ,...,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, then {φ r ,φ t The phase optimization problem can be re-expressed as the following formula (ie, the fourth expression in the embodiment shown in FIG3 ):

[0220] The above formula is a convex problem and can be solved using convex optimization tools. Among them, the quadratic term coefficient about the phase vector is Each matrix element Combination Vector Since the reflecting user equipment has both direct link of the base station and reflected link of 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 transmitted user equipment has no direct link, item C is not included. l,k , coefficient p t,l Expressed as

[0221] Through the above steps, the optimized transmission-reflection phase information and transmission-reflection amplitude information can be obtained.

[0222] S505: The network device sends the optimized transmission and reflection phase information and transmission and reflection amplitude information to multiple APs.

[0223] When the network device sends the transmission and reflection phase information and transmission and reflection amplitude information to multiple APs, it may also send the received vector, weight vector, and precoding cross information updated in S504 to the multiple APs. After the multiple APs receive the received vector, weight vector, precoding cross information, transmission and reflection phase information, and transmission and reflection amplitude information, they may execute S502. Thus, multiple loop iterations may be performed between the multiple APs and the network device. During the loop iterations, each AP optimizes the precoding vector based on the received 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 based on the channel state information sent by each AP and the updated precoding vector, while simultaneously updating the received vector, weight vector, and AP precoding cross information.

[0224] S506: When the convergence rate value is obtained, the loop ends.

[0225] S507: The multiple APs perform downlink transmission with the multiple user equipments based on the precoding vectors obtained in the last cycle.

[0226] 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.

[0227] 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.

[0228] In a cell-free network scenario, the performance can be verified based on the method designed in the embodiment of the present application, and the performance of the phase-independent model can be compared to analyze the impact of the phase-coupled model on the overall performance. The performance gain of IOS compared to traditional RIS can also be analyzed under different parameter configurations.

[0229] In one embodiment, the optimized unit phase is output to verify that the optimization result satisfies the constraints of the transmission and reflection phase coupling. In the embodiment of the present application, consider 4 APs 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), the two IOSs are located at (20m, 0) and (40m, 0), and the user devices are evenly distributed on both sides of the IOS. Set the heights of the AP, IOS, and user devices to 3m, 3m, and 1.5m, respectively. Apply 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. The comparison results can be seen in Figures 6 and 7.

[0230] Figure 6 shows the relationship between weighted sum rate performance and AP transmit power. With N fixed at 100, the weighted sum rate increases rapidly in all cases as AP transmit power increases. It is found that the performance gains from RISs and IOSs are significant only when AP transmit power is moderate, while the performance gains are negligible when AP transmit power is too low or too high. When AP transmit power is too low, the signals reflected / transmitted by the RIS / IOS are very weak, and the contribution of the RIS / IOS to performance improvement is minimal. When AP transmit power is too high, APs tend to allocate most of their power to the beams of the AP user link, making the contribution of the RISs / IOSs less significant. Furthermore, as transmit power increases, the impact of transmission-reflection phase coupling on system performance gradually increases. At low transmit power, the performance is comparable to that of a phase-independent system architecture.

[0231] Figure 7 shows the relationship between the weighted sum rate performance and the number of cells for different IOS optimization schemes. 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 approximately 2.9% when N = 100. It can be seen that the method proposed in the embodiment of the present application achieves significant performance gains compared to traditional RIS. IOS can bring greater diversity gain and extend coverage compared to RIS. The proposed method can achieve twice or more rate performance compared to traditional cell-free networks.

[0232] Based on the technical solution provided by the embodiments 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 achieved through the interaction between multiple access points in the cell-free network and 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. In this way, the design of the precoding vector, the transmission and reflection phase information, and the transmission and reflection amplitude information can be achieved 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 achieved 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.

[0233] The technical solution provided in the embodiments of this 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 for expanded coverage. It is more suitable for deployment on walls or building surfaces to enhance the flexibility of assisted indoor and outdoor communication scenarios.

[0234] The foregoing description describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0235] FIG8 is a schematic diagram of the structure of a communication device 800 according to an embodiment of the present application. Referring to FIG8 , at the hardware level, the communication device 800 includes a processor, 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, such as at least one disk storage device. Of course, the communication device may also include hardware required for other services.

[0236] The processor, network interface, and memory can be interconnected via an internal bus, such as an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. These buses can be classified as address buses, data buses, and control buses. For ease of illustration, FIG8 shows only one bidirectional arrow, but this does not imply that there is only one bus or only one type of bus.

[0237] The memory is used to store programs. The programs may include program code, which includes computer operating instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0238] The processor reads the corresponding computer program from the non-volatile memory into the internal 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 used to perform the following operations:

[0239] Acquiring channel state information of a plurality of user devices, the plurality of user devices including reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate by utilizing the reflective function of a plurality of omnidirectional metasurfaces, and the transmissive user devices are devices that communicate by utilizing the transmissive function of the plurality of omnidirectional metasurfaces;

[0240] Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector;

[0241] The channel state information and the second precoding vector are sent to a network device.

[0242] Or to do the following:

[0243] receiving channel state information and second precoding vectors of multiple user devices sent by multiple access points, the multiple user devices including reflective user devices and transmissive user devices, the reflective user devices being devices that communicate using the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices being devices that communicate using the transmissive function of the multiple omnidirectional metasurfaces, the second precoding vectors being obtained by optimizing the first precoding vectors of the multiple user devices by the multiple access points;

[0244] The transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized according to the channel state information and the second precoding vector.

[0245] The method performed by the information processing device disclosed in the embodiment shown in FIG8 of the present application can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor or software instructions. 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 gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in this application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this application can be directly implemented as a hardware decoding processor or performed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0246] The communication device can also execute the methods of Figures 2 and 3 and realize the functions of the information processing device in the embodiments shown in Figures 2 and 3, which will not be described in detail in this application.

[0247] Of course, in addition to software implementation, the communication device of this 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.

[0248] The present application also provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions. When executed by a portable communication device including multiple application programs, the instructions enable the portable communication device to execute the method of the embodiments shown in FIG. 2 and FIG. 3 , and to perform the following operations:

[0249] Acquiring channel state information of a plurality of user devices, the plurality of user devices including reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate by utilizing the reflective function of a plurality of omnidirectional metasurfaces, and the transmissive user devices are devices that communicate by utilizing the transmissive function of the plurality of omnidirectional metasurfaces;

[0250] Optimizing the first precoding vectors of the multiple user equipments to obtain a second precoding vector;

[0251] The channel state information and the second precoding vector are sent to a network device.

[0252] Or to do the following:

[0253] receiving channel state information and second precoding vectors of multiple user devices sent by multiple access points, the multiple user devices including reflective user devices and transmissive user devices, the reflective user devices being devices that communicate using the reflective function of multiple omnidirectional metasurfaces, and the transmissive user devices being devices that communicate using the transmissive function of the multiple omnidirectional metasurfaces, the second precoding vectors being obtained by optimizing the first precoding vectors of the multiple user devices by the multiple access points;

[0254] The transmission and reflection phase information and the transmission and reflection amplitude information of the multiple omnidirectional metasurfaces are optimized according to the channel state information and the second precoding vector.

[0255] FIG9 is a schematic diagram of the structure of an information processing device 90 according to an embodiment of the present application. Referring to FIG9 , 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:

[0256] An acquisition module 91 is configured to acquire channel state information of a plurality of user devices, wherein the plurality of user devices include reflective user devices and transmissive user devices, wherein the reflective user devices are devices that communicate using the reflective function of a plurality of omnidirectional metasurfaces, and the transmissive user devices are devices that communicate using the transmissive function of the plurality of omnidirectional metasurfaces;

[0257] An optimization module 92 optimizes the first precoding vectors of the plurality of user equipments to obtain a second precoding vector;

[0258] The sending module 93 sends the channel state information and the second precoding vector to a network device.

[0259] The information processing device 90 provided in the embodiment of the present application can also execute the method of Figure 2 and realize the functions of the information processing device 90 in the embodiment shown in Figure 2, which will not be repeated in this application.

[0260] FIG10 is a schematic diagram of the structure of an information processing device 100 according to an embodiment of the present application. Referring to FIG10 , in a software implementation, the information processing device 100 may include: a receiving module 101 and an optimization module 102, wherein:

[0261] A receiving module 101 receives channel state information and second precoding vectors 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 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. The second precoding vectors are obtained by optimizing the first precoding vectors of the multiple user devices by the multiple access points.

[0262] 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.

[0263] The information processing device 100 provided in the embodiment of the present application can also execute the method of Figure 3 and realize the functions of the information processing device 100 in the embodiment shown in Figure 3, which will not be repeated in this application.

[0264] An embodiment of the present application further provides an information processing system, comprising multiple access points, multiple omnidirectional metasurfaces, and a network device. The multiple access points and multiple omnidirectional metasurfaces provide communication services for multiple user devices by collaboratively interacting with the network device, wherein:

[0265] The multiple access points acquire channel state information of the multiple user devices, where the multiple user devices include reflective user devices and transmissive user devices, wherein 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 first precoding vectors of the multiple user devices to obtain second precoding vectors; and send the channel state information and the second precoding vector to the network device;

[0266] 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.

[0267] In the information processing system provided in the embodiments of the present application, each access point can implement the functions of the access point (or first access point) in the embodiments shown in Figures 1 to 5, and the network device can implement the functions of the network device in the embodiments shown in Figures 1 to 5, which will not be described in detail here.

[0268] In short, the above description is only a preferred embodiment of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0269] The systems, devices, modules, or units described in the above embodiments may be implemented by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer. The computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, 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.

[0270] Computer-readable media includes 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 RAM (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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (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 transitory computer-readable media such as modulated data signals and carrier waves.

[0271] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0272] The various embodiments in this application are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiment is generally similar to the method embodiment, so the description is relatively simple. For relevant parts, refer to the partial description of the method embodiment.

Claims

1. An information processing method, applied to a first access point, comprising: 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 of claim 1, wherein: 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 of claim 1, wherein: 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 of claim 3, wherein: 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 of claim 4, wherein: 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 of claim 5, wherein: 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 of claim 4, wherein: The optimizing the first precoding vector according to the objective function to obtain a second precoding vector includes: Introducing a 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, wherein: 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 of claim 8, wherein: 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 of claim 1, wherein: 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, applied to a network device, comprising: 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 of claim 11, wherein: 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 of claim 12, wherein: 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 of claim 13, wherein: 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 of claim 12, wherein: 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 of claim 12, wherein: 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 of claim 16, wherein: 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, wherein: 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 comprising: 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, wherein: 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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