Channel optimization method and related apparatus

Abstract

The present application provides a channel optimization method and a related apparatus, capable of reducing interference signals in reconfigurable intelligent surface (RIS)-based wireless transmission channels and optimizing the channels. The method comprises: determining a plurality of user equipments, wherein transmission channels of the plurality of user equipments are parallel; adjusting a reflection coefficient of an element in the RIS, wherein the amplitude of the reflection coefficient of the element is unchanged; and adjusting a phase shifter corresponding to the element on the basis of the adjusted reflection coefficient of the element to reduce or eliminate interference signals in the transmission channels of the user equipments.

Description

A channel optimization method and related apparatus Technical Field

[0001] This application relates to the field of communication technology, and in particular to a channel optimization method and related apparatus. Background Technology

[0002] Reconfigurable Intelligent Surfaces (RIS) are generally used for non-line-of-sight transmission between base stations and user equipment. When line-of-sight transmission is not possible between the base station and user equipment, the RIS can reflect or refract the signal sent from the base station to the user equipment, allowing the transmitted signal to be received by the user equipment.

[0003] With the increase in communication frequency bands and the expansion of communication system capacity, the transmission signals of different user equipment may interfere with the transmission signals of other user equipment.

[0004] Summary of the Invention

[0005] This application provides a channel optimization method and related apparatus, which can reduce interference signals in RIS-based wireless transmission channels and optimize the channel.

[0006] In a first aspect, embodiments of this application provide a channel optimization method, the method comprising:

[0007] Multiple user equipments are identified, and the transmission channels of the multiple user equipments are parallel;

[0008] The reflection coefficient of the array in the reconfigurable metasurface RIS is adjusted, wherein the amplitude of the reflection coefficient of the array is constant. The amplitude of the reflection coefficient of the array can refer to the constant phase modulation amplitude corresponding to the array.

[0009] Based on the adjusted reflection coefficient of the array, the corresponding phase shifter of the array is adjusted to reduce or eliminate interference signals in the user equipment transmission channel.

[0010] In one possible implementation, this application provides a channel optimization method in which adjusting the reflection coefficient of the array in the RIS includes:

[0011] Determine the cascaded channel model for each user equipment and the interference model for each user equipment;

[0012] Based on the preset first interference constraint, and the cascaded channel model and interference model corresponding to each user equipment, the first reflection coefficient of the RIS is determined. The first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0013] In one possible implementation, the first interference constraint condition includes:

[0014] The cascaded channel model corresponding to each user equipment is a non-zero matrix;

[0015] The interference model corresponding to each user equipment is a zero matrix;

[0016] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0017] In one possible implementation, adjusting the reflection coefficient of the array in the RIS includes:

[0018] Determine the cascaded channel model and the interference model corresponding to each user equipment;

[0019] Based on the cascaded channel model corresponding to each user equipment, the channel degrees of freedom corresponding to each user equipment are determined;

[0020] Based on the preset second interference constraint, the channel degrees of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficient of the RIS is determined. The first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0021] In one possible implementation, the second interference constraint condition includes:

[0022] The difference between the channel degree of freedom corresponding to each user equipment and the maximum channel degree of freedom of the user equipment is less than or equal to a preset degree of freedom threshold.

[0023] The interference model corresponding to each user equipment is a zero matrix;

[0024] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0025] In one possible implementation, this application provides a channel optimization method in which determining the first reflection coefficient of the array element in the RIS includes:

[0026] Based on the alternating projection algorithm and preset interference constraints, the first reflection coefficient is determined, and the first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0027] In one possible implementation, this application provides a channel optimization method, which, after determining the first reflection coefficient, further includes:

[0028] A second reflection coefficient is determined for the array in the RIS, the second reflection coefficient being used to increase the overall system rate of the RIS.

[0029] In one possible implementation, this application provides a channel optimization method in which determining the second reflection coefficient of the array element in the RIS includes:

[0030] Based on the conjugate gradient algorithm, using the first reflection coefficient as the initial starting point, a second reflection coefficient is determined that maximizes the total system speed of the RIS.

[0031] In one possible implementation, this application provides a channel optimization method that, after determining the second reflection coefficient, further includes:

[0032] The third reflection coefficient of the array in the RIS is determined. The third reflection coefficient is used to increase the maximum channel transmission rate of the target user equipment, wherein the target user equipment is the user equipment corresponding to the minimum value of the maximum channel transmission rate among the plurality of user equipments.

[0033] Secondly, embodiments of this application provide a channel optimization apparatus, comprising:

[0034] The first processing module is used to identify multiple user equipments, wherein the transmission channels of the multiple user equipments are parallel;

[0035] The second processing module is used to adjust the reflection coefficient of the array in the reconfigurable metasurface RIS, wherein the amplitude of the reflection coefficient of the array is constant. The amplitude of the reflection coefficient of the array can refer to the constant phase modulation amplitude corresponding to the array.

[0036] An adjustment module is used to adjust the corresponding phase shifter of the array based on the adjusted reflection coefficient of the array, so as to reduce or eliminate interference signals in the transmission channel of the user equipment.

[0037] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is specifically used for:

[0038] Determine the cascaded channel model for each user equipment and the interference model for each user equipment;

[0039] Based on the preset first interference constraint, and the cascaded channel model and interference model corresponding to each user equipment, the first reflection coefficient of the array in the RIS is determined.

[0040] In one possible implementation, the first interference constraint condition includes:

[0041] The cascaded channel model corresponding to each user equipment is a non-zero matrix;

[0042] The interference model corresponding to each user equipment is a zero matrix;

[0043] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0044] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is specifically used for:

[0045] Determine the cascaded channel model and the interference model corresponding to each user equipment;

[0046] Based on the cascaded channel model corresponding to each user equipment, the channel degrees of freedom corresponding to each user equipment are determined;

[0047] Based on the preset second interference constraint, the channel degrees of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficient of the RIS is determined. The first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0048] In one possible implementation, the second interference constraint condition includes:

[0049] The difference between the channel degree of freedom corresponding to each user equipment and the maximum channel degree of freedom of the user equipment is less than or equal to a preset degree of freedom threshold.

[0050] The interference model corresponding to each user equipment is a zero matrix;

[0051] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0052] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is specifically used for:

[0053] Based on the alternating projection algorithm and preset interference constraints, the first reflection coefficient is determined, and the first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0054] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is further configured to:

[0055] After determining the first reflection coefficient, a second reflection coefficient of the array in the RIS is determined, the second reflection coefficient being used to increase the system summation rate of the RIS.

[0056] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is specifically used for:

[0057] Based on the conjugate gradient algorithm, using the first reflection coefficient as the initial starting point, a second reflection coefficient is determined that maximizes the total system speed of the RIS.

[0058] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module is further configured to:

[0059] After determining the second reflection coefficient, the third reflection coefficient of the RIS is determined. The third reflection coefficient is used to increase the maximum channel transmission rate of the target user equipment, wherein the target user equipment is the user equipment corresponding to the minimum value of the maximum channel transmission rate among the plurality of user equipments.

[0060] Thirdly, embodiments of this application also provide a control device capable of controlling the phase shifter of an array in a reconfigurable metasurface RIS;

[0061] The control device is used to perform the method as described in the first aspect and any of its embodiments.

[0062] Fourthly, embodiments of this application also provide a glass device including a reconfigurable metasurface RIS and a control device as described in the second aspect.

[0063] Fifthly, embodiments of this application also provide a communication system, which may include at least one base station, at least one user equipment, a reconfigurable metasurface RIS, and a control device as described in the second aspect.

[0064] In a sixth aspect, embodiments of this application also provide a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program that, when the computer program is run on a computer, causes the computer to perform the method as described in the first aspect and any of its embodiments. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 is a schematic diagram of an application scenario provided by an embodiment of this application;

[0067] Figure 2 is a flowchart illustrating a channel optimization method provided in an embodiment of this application;

[0068] Figure 3 is a schematic diagram of a test result provided in an embodiment of this application;

[0069] Figure 4 is a schematic diagram of a test result provided in an embodiment of this application;

[0070] Figure 5 is a flowchart illustrating a channel optimization method provided in an embodiment of this application;

[0071] Figure 6 is a schematic diagram of a channel optimization device provided in an embodiment of this application;

[0072] Figure 7 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0073] Figure 8 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0075] The application scenarios described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the emergence of new application scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0076] The embodiments of this application involve at least one, including one or more; wherein, multiple means two or more. Furthermore, it should be understood that in the description of this application, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance, nor as indicating or implying order. In the description of this application, "A and / or B" includes three options: including A; including B; and including both A and B.

[0077] Referring to Figure 1, the RIS (Radio Resonance Array) comprises multiple sub-units. These sub-units can be referred to as sub-units, cells, elements, etc. By adjusting the phase and amplitude of the sub-units in the RIS, highly precise beamforming of electromagnetic waves can be achieved, enabling signals to transmit with stronger directionality and improving network coverage and transmission efficiency. The arrangement of the multiple sub-units in the RIS can be arrayed or non-arrayed, allowing for flexible configuration based on specific application scenarios. The RIS can reflect signals transmitted by the base station, allowing the reflected signals to reach the user equipment. Similarly, as shown in Figure 1, the RIS can reflect signals transmitted by the user equipment, allowing the reflected signals to reach the base station.

[0078] In some scenarios, RIS can be used to compensate for path loss of signals during transmission, especially in high-frequency and millimeter-wave communications. It can be used to reduce energy loss and improve communication quality in wireless communication links by optimizing the signal propagation path.

[0079] With the increasing demand for larger communication system capacity, Massive Multiple-Input Multiple-Output (MIMO) technology is a key technology for improving the overall capacity of future wireless networks. A channel generally refers to the transmission medium or path of a signal from the transmitter to the receiver. In high-capacity communication systems, the presence of multiple user devices inevitably leads to signal interference on the same time-frequency resources between different user devices. Since the channel correlation between different user devices cannot be guaranteed to be completely orthogonal, there will inevitably be some interference signal leakage. Reconstruction of the wireless transmission channel (RIS) can achieve this. However, reducing interference signals in RIS-based wireless transmission channels to achieve channel optimization remains a challenge.

[0080] This application provides a channel optimization method and related apparatus, which can reduce interference signals in RIS-based wireless transmission channels and optimize the channel.

[0081] Figure 2 illustrates an exemplary channel optimization method, which can be executed by a control device. The control device can control the RIS (Reflection Array), under which the RIS changes the amplitude and / or phase of the reflection coefficient of the array. The control device can be referred to as a RIS controller. The channel optimization method may include the following steps:

[0082] S201, Identify multiple user equipments, wherein the transmission channels of the multiple user equipments are parallel.

[0083] Any device capable of data communication with a base station can be considered a user equipment (UE). UE is also called a terminal, terminal device, user equipment, mobile station, or mobile terminal. UE can be widely used in various scenarios. For example, UE can be: mobile phones, computers, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, stations (STA), robotic arms, cameras, robots, vehicles, drones, helicopters, airplanes, ships, or smart home devices (such as televisions, air conditioners, robot vacuums, speakers, set-top boxes), relays, customer premises equipment (CPE), or UE in Internet of Things (IoT) systems, such as water meters and electricity meters. This application does not impose further limitations on these.

[0084] The number of user equipments (UAEs) can be an integer greater than or equal to 2. Generally, a RIS can serve one or more base stations. The RIS can reflect (and sometimes refract) signals sent by each base station, allowing the reflected signals to reach the UAEs. Base stations and UAEs that interact with each other are called transceiver pairs. A RIS can simultaneously support multiple transceiver pairs' channels. A transceiver pair's channel can include two parts: the channel between the base station and the RIS, and the channel between the RIS and the UAE.

[0085] Optionally, the channel between the transmit and receive pairs can be implemented as the transmission channel of the user equipment in the transmit and receive pair. Alternatively, the channel between the user equipment and the RIS can be implemented as the transmission channel of the user equipment.

[0086] The control unit can determine the transmission channels of multiple user equipments operating in parallel. User transmission channels within the same time period, frequency band, and space are considered parallel. Generally, large-scale MIMO communication scenarios involve numerous parallel user equipment transmission channels. In some applications, the RIS (Radio Router Identifier) ​​can identify multiple parallel user equipments based on Channel State Information (CSI). Among the parallel transmission channels of multiple user equipments, the signal transmitted in one user equipment's transmission channel can interfere with the transmission channels of other user equipments.

[0087] The control device can perform the operations in steps S202 and S203 to reduce interference in the transmission channels of the multiple user equipments and optimize the transmission channels.

[0088] S202, Adjust the reflection coefficient of the array in the reconfigurable metasurface RIS, wherein the amplitude of the reflection coefficient of the array remains unchanged.

[0089] In implementation, the control device can adjust the reflection coefficient of the array in the RIS based on constraints. The reflection coefficient generally includes amplitude and phase. In step S202, the control device only adjusts the phase of the reflection coefficient. It does not adjust the amplitude of the reflection coefficient. Optionally, the amplitude of the reflection coefficient can be a default value. In some scenarios, the absolute value of the amplitude of the reflection coefficient can be 1.

[0090] Optionally, the elements whose reflection coefficient is adjusted in step S202 can be all the elements of the RIS. Alternatively, the elements whose reflection coefficient is adjusted can be a subset of the elements in the RIS. This application embodiment does not specifically limit the method of selecting a subset of elements from the RIS.

[0091] S203, based on adjusting the reflection coefficient of the array, adjust the corresponding phase shifter of the array to reduce or eliminate interference signals in the user equipment transmission channel.

[0092] In step S202, the control device can adjust the reflection coefficient of the elements in the RIS in various ways. For ease of explanation, assume that the number of the plurality of user equipments is P, and the number of elements in the RIS participating in the adjustment of the reflection coefficient is N. Optionally, in order to completely eliminate interference caused by signals from other user equipments in the transmission channel of a user equipment, the number N of elements in the RIS participating in the adjustment of the reflection coefficient is greater than or equal to 2P(P+1).

[0093] For any user equipment k, the signal received by user equipment k can be denoted as y. k .in, h r,k h represents the transmission channel between RIS and user equipment k. t,k h represents the transmission channel between user equipment k and the base station. t,j Characterized by the transmission channel between user equipment j and the base station, s k The original signal s represents the signal transmitted between the base station and the user equipment k. j The original signal transmitted between the base station and user equipment j, n k The noise of the transmission channel of user equipment k is represented by v, and the reflection coefficient matrix of the RIS array is represented by v. ω i Characterizes the phase value of the phase shifter corresponding to element i. Optional, n k It can be Gaussian noise.

[0094] In one possible implementation, in step S202, the control device may perform the following operations:

[0095] The cascaded channel model corresponding to each user equipment is determined, as well as the interference model corresponding to each user equipment; based on the preset first interference constraint, the cascaded channel model and the interference model corresponding to each user equipment, the first reflection coefficient of the array in the RIS is determined.

[0096] The signal received by user equipment k is It can also be expressed as in, a k,k The channel covariance matrix representing the differences between different users can also be called the equivalent concatenated channel between user equipment k and the base station (hereinafter referred to as the concatenated channel). k,j The interference of the transmitted signal of user equipment j's channel to user equipment k is characterized. In this embodiment, the cascaded channel model corresponding to user equipment k is denoted as... The interference model corresponding to user equipment k is denoted as

[0097] The control device can be based on a preset first interference constraint condition and the cascaded channel model corresponding to each user equipment. and interference model Determine the first reflection coefficient of the array element in the RIS. The first interference constraint can be a constraint on the cascaded channel model and a constraint on the interference model.

[0098] In some scenarios, the first disturbance constraint may include the following conditions:

[0099] Condition A1: The cascaded channel model corresponding to each user equipment is a non-zero matrix, that is...

[0100] Condition A2 states that the interference model for each user equipment is a zero matrix, that is...

[0101] Condition A3, the amplitude of the reflection coefficient of the array is equal to a preset first value, for example, |v i |=1,i=1,…,N。

[0102] Conditions A1 and A2 constrain the reflection coefficient values ​​of the RIS array to be greater than zero. In condition A1, the concatenated channel model is non-zero, constraining user equipment k to interact with the base station. In condition A2, the interference model is zero, constraining the interference from other user equipment to user equipment k to be zero, ensuring complete interference elimination. Condition 3, constraining the amplitude of the reflection coefficient, speeds up the solution to the reflection coefficient matrix v.

[0103] The control device can be based on the first interference constraint condition and the cascaded channel model corresponding to each user equipment. and interference model The first reflection coefficient of the RIS array is obtained by solving. Adjusting the phase shifter of the RIS array based on the first reflection coefficient can eliminate interference.

[0104] In one possible implementation, in step S202, the control device may perform the following operations:

[0105] Determine the cascaded channel model for each user equipment. And determine the interference model corresponding to each user equipment. Based on the cascaded channel model corresponding to each user equipment, the channel degree of freedom corresponding to each user equipment is determined; according to the preset second interference constraint, the channel degree of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficient of the array in the RIS is determined.

[0106] The control device can utilize the cascaded channel model corresponding to the user equipment. And determine the interference model corresponding to each user equipment. And noise determines the system throughput of user equipment k. Where p k Characterizing the fixed transmit power of user equipment k, This characterizes the noise signal received by user equipment k. If interference from other user equipments on the transmission channel of user equipment k is completely eliminated, the system throughput of user equipment k can be denoted as... At this time, the channel degrees of freedom of user equipment k are

[0107] The second interference constraint condition may include the following conditions:

[0108] Condition B1: The difference between the channel degree of freedom corresponding to each user equipment and the maximum channel degree of freedom of the user equipment is less than or equal to a preset degree of freedom threshold.

[0109] Condition B2 states that the interference model for each user equipment is a zero matrix, that is...

[0110] Condition B3, the amplitude of the reflection coefficient of the array is equal to a preset first value, for example, |v i |=1,i=1,…,N。

[0111] In condition B1, the preset degree-of-freedom threshold characterizes the difference between the channel degree of freedom corresponding to the user equipment and the maximum channel degree of freedom. Optionally, the preset degree-of-freedom threshold can be 0. The control device can adjust the reflection coefficient matrix v to make the channel degree of freedom of user equipment k equal to the difference between the maximum channel degree of freedom of user equipment k. This constraint ensures that the communication system where the RIS is located can maximize the transmission data flow.

[0112] The process by which the control device determines the first reflection coefficient of the array in the RIS based on the preset second interference constraint, the channel degrees of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment is equivalent to solving the following first objective problem:

[0113] find v

[0114] subject to

[0115] The matrix form of the first objective problem can be represented as: Π S1 (v)=vA * (A T A * ) -1 A T v

[0116] Here, S1 and S2 are two different constraint sets. The control device can be based on an alternating projection algorithm, alternately projecting the reflection coefficients onto the two different constraint sets. The corresponding projection process is Π. S1 (v) is obtained by mapping the feature vector v onto different feature spaces and iteratively optimizing the optimal solution to obtain the first reflection coefficient.

[0117] As can be seen, different constraints correspond to different constraint sets. By alternately projecting onto different constraint sets using an alternating projection algorithm, combined with an iterative approach, the first reflection coefficient can be obtained. In this embodiment, the control device can adjust the phase of the array in the RIS based on the first reflection coefficient, thereby eliminating interference signals in the transmission channel of each user equipment and achieving a channel optimization effect of zeroing interference.

[0118] Based on the channel optimization method provided in any of the above embodiments, the control device can also improve the overall communication rate of the RIS-served communication system by adjusting the reflection coefficient of the array in the RIS. The control device can perform the following operations:

[0119] A second reflection coefficient of the array in the RIS is determined, the second reflection coefficient being used to increase the system summation rate of the RIS.

[0120] The control device can obtain the second reflection coefficient by solving the following second objective problem: subject to|v i | = 1, i = 1, ..., N

[0121] Solving the second objective problem is also solving a nonconvex optimization problem. The main challenge of nonconvex optimization problems is that a local optimum is usually not guaranteed to be a global optimum, making finding the global optimum extremely difficult. Furthermore, the solution process for these problems may encounter multiple local optima, saddle points, or other complex local structures. Commonly used solutions include heuristics, branch and bound methods, and relaxation techniques. However, these optimization search methods generally have high computational complexity.

[0122] In some scenarios, the control device can use the conjugate gradient algorithm, with the first reflection coefficient as the initial starting point, to determine a second reflection coefficient that maximizes the total system speed of the RIS.

[0123] Since the second objective problem involves constraints on the non-convex objective function f1 and the magnitude modulus of the non-convex dome, the optimization problem is continuously differentiable and can therefore be solved using the gradient projection algorithm. To accelerate convergence, the conjugate gradient algorithm can be the Riemannian Conjugate Gradient (RCG). The control device can use the conjugate Riemann gradient to converge to optimization, speeding up the determination of the second reflection coefficient and avoiding local maxima.

[0124] The amplitude constraints of the phase form a Riemannian manifold. By projecting the Euclidean gradient onto the tangent space, the Riemann gradient of the objective function f1 for the complex unit circle is... in in This represents the Hadamard product. Given the Riemann gradient, the search direction is updated using the conjugate gradient algorithm. Here, λ1 represents the conjugate gradient update parameters. The control device uses the first reflection coefficient as the initial point and projects this initial point onto the Riemannian manifold to perform the update operation. Here, λ2 represents the Armijo step size.

[0125] Based on the channel optimization method provided in any of the above embodiments, the control device can perform user system fairness adjustments. Here, user system fairness is reflected in the fact that the difference in the maximum throughput achievable by different user devices should not be too large, thereby ensuring that each user device can obtain the wireless channel transmission resources allocated by the communication system to support its relevant services.

[0126] For the target user equipment with the lowest maximum throughput among the multiple user equipments, the control device can increase the maximum throughput of the target user equipment, enabling the worst-performing user equipment in the RIS system to meet the RIS system's Quality of Service (QoS) requirements, thus resolving the system fairness issue. The control device can increase the maximum throughput of the target user equipment by adjusting the reflection coefficient of the RIS array.

[0127] The control device can determine the third reflection coefficient by solving the following third objective problem, wherein the third reflection coefficient is used to increase the maximum channel transmission rate of the target user equipment: subject to|v i | = 1, i = 1, ..., N

[0128] {-R k} can represent the set of inverses of the maximum channel transmission rate of each of the multiple user equipments. It can reflect the maximum value in the set, that is, the opposite of the maximum channel transmission rate of the target user equipment.

[0129] The objective function f2 is not smooth in the gradient differentiation process. The control device can solve the third objective problem based on the subgradient projection method. Subgradient differential form: Where i = argmax x k {-R k Since the gradient is differentiable and finite in magnitude, there exists a corresponding constant that satisfies the following constraint: f2(v)≥R i (v)

[0130] To accelerate convergence learning, the size of the subgradient projection can be configured. Here, s represents different iteration steps, and c represents a fixed data point used to adjust the scaling of the subgradient projection.

[0131] In some test scenarios, to evaluate the channel optimization method, the RICIAN fading model is used for the wireless transmission channel model. The bandwidth of the communication system served by the RIS is assumed to be 10MHz, and the noise power spectral density within the bandwidth is -170dBm / Hz. Figure 3 shows a schematic diagram of the relationship between the number of elements participating in interference cancellation in the RIS and the probability of successful interference cancellation. It can be seen that as the scale of the transmission channels of parallel user equipment increases, that is, as the number of P increases, the parameters and the number of elements participating in interference cancellation in the RIS also increase to eliminate interference. Among them, when the number of elements participating in interference cancellation is equal to 2P(P+1), the interference between the transmission channels of parallel user equipment can be completely eliminated. Therefore, in some application scenarios, the number of elements participating in interference cancellation in the RIS can be no less than 2P(P+1).

[0132] In some test scenarios, it is assumed that the number of transmission channels for multiple user equipments operating in parallel is 6, and the transmit power is 35 dBm. Figure 4 shows the number of elements involved in interference cancellation in the RIS and the RIS system throughput in different interference cancellation schemes.

[0133] To maximize the exploration of the RIS's lateral spatial degrees of freedom, it is assumed that the number of vertical elements in the RIS is fixed at 10, while the number of horizontal elements increases from 4 onwards. Figure 4 shows the simulation results of several algorithms, including random initialization and adjustment of the reflection coefficient matrix, eig initialization and adjustment of the reflection coefficient matrix, random initialization combined with RCG algorithm, random initialization combined with interference elimination (ZF) and RCG, and eig initialization and adjustment of the reflection coefficient matrix combined with interference elimination (ZF) and RCG.

[0134] The interference elimination ZF can be described as the process by which the control device in the aforementioned embodiment determines the first reflection coefficient of the array in the RIS based on a preset second interference constraint, the channel degrees of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment. Because interference elimination makes the interference zero or close to zero, it can also be called the Zero Force (ZF) algorithm.

[0135] In this context, RCG can be the implementation process by which the control device in the aforementioned embodiment determines a second reflection coefficient that maximizes the total system speed of the RIS, based on the Riemann gradient descent method and using the first reflection coefficient as an initial starting point.

[0136] As shown in Figure 4, the control device determines the implementation process of the first reflection coefficient of the RIS based on the preset second interference constraint, the channel degree of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment. It also determines the implementation process of the second reflection coefficient based on the Riemann gradient descent method, using the first reflection coefficient as the initial starting point, to maximize the total system rate of the RIS. Combined with eig initialization or random initialization, it has good system throughput.

[0137] Furthermore, Figure 4 shows that the performance of the RIS system increases rapidly when N increases from 50 to 60. This is mainly because, with 6 parallel user equipment transmission channels, the number of elements participating in interference cancellation equals 60, which is the phase inflection point for the RIS.

[0138] Figure 5 illustrates an exemplary channel optimization method, which can be executed by a control device, and the method may include the following steps:

[0139] S501, Identify multiple user equipments, wherein the transmission channels of the multiple user equipments are parallel.

[0140] S502, based on the preset interference constraint conditions, determine the first reflection coefficient of the radius in the RIS, wherein the amplitude of the reflection coefficient of the radius is constant.

[0141] Optionally, the preset interference constraint can be the first interference constraint or the second interference constraint in the aforementioned embodiments.

[0142] S503, based on the first reflection coefficient, adjust the corresponding phase shifter of the array to reduce or eliminate interference signals in the user equipment transmission channel.

[0143] S504, based on the second objective problem, determine the second reflection coefficient.

[0144] S505, based on the second reflection coefficient, adjust the corresponding phase shifter of the array to increase the total system speed of the RIS.

[0145] S506, based on the third objective problem, determine the third reflection coefficient.

[0146] S507, based on the third reflection coefficient, adjust the corresponding phase shifter of the array to increase the maximum channel transmission rate of the target user equipment, wherein the target user equipment is the user equipment corresponding to the minimum value of the maximum channel transmission rate among the plurality of user equipments.

[0147] Based on the same inventive concept, as shown in Figure 6, this application also provides a channel optimization device, including:

[0148] The first processing module 601 is used to identify multiple user equipments, wherein the transmission channels of the multiple user equipments are in parallel;

[0149] The second processing module 602 is used to adjust the reflection coefficient of the array in the reconfigurable metasurface RIS, wherein the amplitude of the reflection coefficient of the array is constant. The amplitude of the reflection coefficient of the array can refer to the constant phase modulation amplitude corresponding to the array.

[0150] The adjustment module 603 is used to adjust the corresponding phase shifter of the array based on the adjusted reflection coefficient of the array, so as to reduce or eliminate interference signals in the transmission channel of the user equipment.

[0151] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is specifically used for:

[0152] Determine the cascaded channel model for each user equipment and the interference model for each user equipment;

[0153] Based on the preset first interference constraint, and the cascaded channel model and interference model corresponding to each user equipment, the first reflection coefficient of the RIS is determined. The first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0154] In one possible implementation, the first interference constraint condition includes:

[0155] The cascaded channel model corresponding to each user equipment is a non-zero matrix;

[0156] The interference model corresponding to each user equipment is a zero matrix;

[0157] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0158] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is specifically used for:

[0159] Determine the cascaded channel model and the interference model corresponding to each user equipment;

[0160] Based on the cascaded channel model corresponding to each user equipment, the channel degrees of freedom corresponding to each user equipment are determined;

[0161] Based on the preset second interference constraint, the channel degrees of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficient of the RIS is determined. The first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0162] In one possible implementation, the second interference constraint condition includes:

[0163] The difference between the channel degree of freedom corresponding to each user equipment and the maximum channel degree of freedom of the user equipment is less than or equal to a preset degree of freedom threshold.

[0164] The interference model corresponding to each user equipment is a zero matrix;

[0165] The amplitude of the reflection coefficient of the array is equal to a preset first value.

[0166] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is specifically used for:

[0167] Based on the alternating projection algorithm and preset interference constraints, the first reflection coefficient is determined, and the first reflection coefficient is used to eliminate interference signals in the transmission channel of the user equipment.

[0168] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is further configured to:

[0169] After determining the first reflection coefficient, a second reflection coefficient of the array in the RIS is determined, the second reflection coefficient being used to increase the system summation rate of the RIS.

[0170] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is specifically used for:

[0171] Based on the conjugate gradient algorithm, using the first reflection coefficient as the initial starting point, a second reflection coefficient is determined that maximizes the total system speed of the RIS.

[0172] In one possible implementation, this application provides a channel optimization apparatus in which the second processing module 602 is further configured to:

[0173] After determining the second reflection coefficient, the third reflection coefficient of the RIS is determined. The third reflection coefficient is used to increase the maximum channel transmission rate of the target user equipment, wherein the target user equipment is the user equipment corresponding to the minimum value of the maximum channel transmission rate among the plurality of user equipments.

[0174] Based on the same inventive concept, embodiments of this application also provide a control device capable of controlling the phase shifters corresponding to each element in the RIS. The control device can execute the operations performed by the control device in any of the foregoing embodiments. Alternatively, the control device can execute the channel optimization method provided in any of the foregoing embodiments.

[0175] In the embodiments provided above, the methods provided by the embodiments of this application are described from the perspective of the control device as the executing entity. To implement the functions of the methods provided in the embodiments of this application, the control device may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0176] On the other hand, this application also provides an electronic device, as shown in FIG7, which may include a RIS and a control device for the RIS. In some application scenarios, the electronic device may include a support structure, and the RIS may be disposed on the support structure. This application does not limit the specific material of the support structure. In other application scenarios, the electronic device may include glass. The RIS may be disposed on the surface of the glass, or the RIS may be located in a designated layer within the glass. The control device for the RIS may execute the channel optimization method provided in any of the foregoing embodiments.

[0177] On the other hand, embodiments of this application provide a glass device, as shown in FIG8. The glass device may include glass, a RIS (Radio Optimization System), and a control device for the RIS. In some application scenarios, the RIS may be disposed on the surface of the glass, or the RIS may be located in a designated layer within the glass. This application does not specifically limit this. The control device for the RIS can execute the channel optimization method provided in any of the foregoing embodiments.

[0178] On the other hand, embodiments of this application provide a communication system that may include at least one base station, at least one user equipment, a RIS, and a control device for the RIS, wherein the control device for the RIS may execute the channel optimization method provided in any of the foregoing embodiments.

[0179] In addition, embodiments of this application provide a computer-readable storage medium for storing a computer program that, when run on a computer, causes the computer to perform steps as described in any of the channel optimization methods above.

[0180] As used in the above embodiments, depending on the context, the terms "when..." or "after..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrases "when..." or "if (the stated condition or event) is detected" can be interpreted as meaning "if...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0181] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0182] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0183] This application also provides a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)). Where there is no conflict, the solutions of the above embodiments can be combined.

Claims

1. A method of channel optimization, wherein, The method comprises: determining a plurality of user equipment, transmission channels of the plurality of user equipment being parallel; adjusting reflection coefficients of an array in a reconfigurable metasurface (RIS), wherein amplitudes of the reflection coefficients of the array are invariant; based on the adjusted reflection coefficients of the array, adjusting phase shifters corresponding to the array to reduce or eliminate interference signals in the transmission channels of the user equipment.

2. The method of claim 1, wherein, The adjustment of the reflection coefficients of the array in the RIS comprises: determining a cascade channel model corresponding to each user equipment, and determining an interference model corresponding to each user equipment; determining first reflection coefficients of the array in the RIS according to a preset first interference constraint condition, the cascade channel model corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficients being used to eliminate interference signals in the transmission channels of the user equipment.

3. The method of claim 2, wherein, The first interference constraint condition comprises: the cascade channel model corresponding to each user equipment being a non-zero matrix; the interference model corresponding to each user equipment being a zero matrix; amplitudes of the reflection coefficients of the array being equal to a preset first value.

4. The method of claim 1, wherein, The adjustment of the reflection coefficients of the array in the RIS comprises: determining a cascade channel model corresponding to each user equipment, and determining an interference model corresponding to each user equipment; determining a channel degree of freedom corresponding to each user equipment based on the cascade channel model corresponding to each user equipment; determining first reflection coefficients of the array in the RIS according to a preset second interference constraint condition, the channel degree of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficients being used to reduce or eliminate interference signals in the transmission channels of the user equipment. The second interference constraint condition comprises:

5. The method of claim 4, wherein, a difference between the channel degree of freedom corresponding to each user equipment and a maximum channel degree of freedom of the user equipment being less than or equal to a preset degree of freedom threshold; the interference model corresponding to each user equipment being a zero matrix; amplitudes of the reflection coefficients of the array being equal to a preset first value. The determination of the first reflection coefficients of the array in the RIS comprises:

6. The method of claim 2 or 4, wherein, determining the first reflection coefficients based on an alternating projection algorithm and a preset interference constraint condition, the first reflection coefficients being used to eliminate interference signals in the transmission channels of the user equipment. After the determination of the first reflection coefficients, the method further comprises:

7. The method of claim 6, wherein, determining second reflection coefficients of the array in the RIS, the second reflection coefficients being used to increase a system sum rate of the RIS. The determination of the second reflection coefficients of the array in the RIS comprises:

8. The method of claim 7, wherein, determining the second reflection coefficients that maximize the system sum rate of the RIS based on a conjugate gradient algorithm, the first reflection coefficients being used as an initial starting point. After the determination of the second reflection coefficients, the method further comprises:

9. The method of claim 7, wherein, determining third reflection coefficients of the array in the RIS, the third reflection coefficients being used to increase a maximum channel transmission rate of a target user equipment, wherein the target user equipment is a user equipment corresponding to a minimum value in the maximum channel transmission rates of the plurality of user equipment. The method comprises:

10. A channel optimization apparatus, wherein, a first processing module configured to determine a plurality of user equipment, transmission channels of the plurality of user equipment being parallel; ​ The second processing module is configured to adjust reflection coefficients of the array elements in the reconfigurable metasurface (RIS). The amplitude of the reflection coefficients of the array elements is constant. The adjustment module is configured to adjust phase shifters corresponding to the array elements based on the adjusted reflection coefficients of the array elements, so as to reduce or eliminate interference signals in a transmission channel of the user equipment.

11. The apparatus of claim 10, wherein, The second processing module is specifically configured to: determine a cascade channel model corresponding to each user equipment and determine an interference model corresponding to each user equipment; determine first reflection coefficients of the array elements in the RIS based on a preset first interference constraint condition and the cascade channel model and the interference model corresponding to each user equipment, the first reflection coefficients being used to eliminate interference signals in the transmission channel of the user equipment.

12. The apparatus of claim 10, wherein, The second processing module is specifically configured to: determine a cascade channel model corresponding to each user equipment and determine an interference model corresponding to each user equipment; determine a channel degree of freedom corresponding to each user equipment based on the cascade channel model corresponding to each user equipment; determine first reflection coefficients of the array elements in the RIS based on a preset second interference constraint condition, the channel degree of freedom corresponding to each user equipment, and the interference model corresponding to each user equipment, the first reflection coefficients being used to eliminate interference signals in the transmission channel of the user equipment.

13. The apparatus of claim 11 or 12, wherein, The second processing module is further configured to: after the first reflection coefficients are determined, determine second reflection coefficients of the array elements in the RIS, the second reflection coefficients being used to increase a system sum rate of the RIS.

14. The apparatus of claim 13, wherein, The second processing module is further configured to: after the second reflection coefficients are determined, determine third reflection coefficients of the array elements in the RIS, the third reflection coefficients being used to increase a maximum channel transmission rate of a target user equipment, wherein the target user equipment is a user equipment corresponding to a minimum value in the maximum channel transmission rates of the plurality of user equipment.

15. A control device, wherein, The control device is capable of controlling phase shifters of array elements in a reconfigurable metasurface (RIS). The control device is configured to perform the method of any one of claims 1-9.

16. An electronic device, wherein, The control device is configured to perform the method of any one of claims 1-9.

17. A communication system, wherein, The control device is configured to perform the method of any one of claims 1-9.

18. A computer readable storage medium, wherein, The computer readable storage medium is configured to store a computer program, which, when executed on a computer, causes the computer to perform the method of any one of claims 1-9.

Images