A configuration method of a super surface network, and a super surface network

Abstract

The present application discloses a configuration method of a metasurface network and a metasurface network. In the configuration method of the metasurface network of an embodiment of the present application, the metasurface network includes multiple metasurfaces, which are respectively deployed at different preset positions on the signal transmission path between the signal transmitting end and the signal receiving end, for reflecting the wireless signal emitted by the signal transmitting end to the signal receiving end. Due to the deployment of multiple metasurfaces, the coverage range is increased, which can meet actual needs. In addition, the present application also configures the continuous compensation phase of each metasurface, specifically configuring each metasurface with the channel with the largest amplitude and the corresponding quantized value of the continuous compensation phase of each metasurface, ensuring that the metasurface network can meet the needs and realize the reflection of wireless signals.

Description

Technical Field

[0001] The present application belongs to the field of wireless communication technology, and in particular relates to a configuration method of a metasurface network and a metasurface network. Background Art

[0002] Current metasurface research has demonstrated many capabilities, such as beamforming for improving the coverage or capacity of wireless signals and channel randomization for security. Typically, only one metasurface is deployed in a real-world scenario because multiple metasurfaces cannot be coordinated.

[0003] However, the coverage of a single metasurface is limited. If the coverage of wireless signals transmitted by the metasurface needs to be expanded, the hardware deployment cost will be greatly increased. Summary of the Invention

[0004] The embodiments of the present application provide a configuration method of a metasurface network and a metasurface network, which can expand the coverage range of wireless signals transmitted by the metasurface.

[0005] In one aspect, an embodiment of the present application provides a method for configuring a metasurface network, wherein the metasurface network includes multiple metasurfaces, each metasurface being deployed at a different preset position on a signal transmission path between a signal transmitting end and a signal receiving end. The method includes:

[0006] Obtaining preset parameters of the signal transmission path; wherein the preset parameters include a channel from the signal transmitting end to the first metasurface of the corresponding path, a quantized value of the continuous compensation phase of each metasurface on the corresponding path, a channel between adjacent metasurfaces on the corresponding path, and a channel from the last metasurface on the corresponding path to the signal receiving end;

[0007] Establish a metasurface network channel model based on the preset parameters of the signal transmission path;

[0008] Determining, according to the metasurface network channel model, the channel sum of all signal transmission paths from a signal transmitting end to a signal receiving end for each metasurface under different quantized values ​​of the continuous compensation phase;

[0009] Determine a target channel sum with the largest channel sum amplitude from among multiple channel sums;

[0010] Determine the quantization value of the continuous compensation phase of the target channel and each corresponding metasurface according to a quantization formula;

[0011] Each metasurface is configured according to the determined quantized value of the continuous compensation phase.

[0012] On the other hand, the hypersurface network channel model includes:

[0013]

[0014] in,

[0015]

[0016] h l is the channel of the path l from the signal transmitter to the signal receiver, h is the channel sum; L path is the number of available paths; B is an array that specifically represents the S hypersurfaces contained in the l-th path, s is the index of the element in array B, B(s) represents the s-th hypersurface in path l, Φ B(s) is the quantized value of the continuous compensation phase of the s-th metasurface in path l;

[0017] h x,y is the channel between node x and node y, and the node includes the signal transmitter, each hypersurface, and the signal receiver; v0 represents the signal transmitter, v p+1 Characterizes the signal receiving end.

[0018] On the other hand, determining the target channel sum with the largest channel sum amplitude from the multiple channel sums includes:

[0019] For each metasurface in the metasurface network, the following operation is cyclically performed until the amplitude of the channel sum satisfies a preset convergence condition: for a target metasurface, while the phase of a non-target metasurface is fixed, the continuous compensation phase of the target metasurface is adjusted so that the current channel sum amplitude is maximized; the target metasurface is any metasurface in the metasurface network;

[0020] The channel sum that meets the preset convergence condition is determined as the target channel sum with the largest magnitude.

[0021] On the other hand, determining the quantized value of the continuous compensation phase includes:

[0022] Determine the corresponding quantization formula based on the phase shifting capability of the metasurface hardware;

[0023] The continuous compensation phase is quantized according to the quantization formula to obtain a corresponding quantization value.

[0024] On the other hand, the quantization formula includes:

[0025]

[0026] …

[0027]

[0028] in,

[0029]

[0030] Among them, MTS B(1) ...MTS B(S) Respectively represent all the metasurfaces, is the continuous compensation phase of the corresponding metasurface; M, N are the number of units of the corresponding metasurface.

[0031] On the other hand, after configuring each metasurface according to the determined quantized value of the continuous compensation phase, the method further includes:

[0032] Obtain the actual channel sum on each path from the signal sending end to the signal receiving end;

[0033] Obtaining a similarity between the actual channel sum and the target channel sum;

[0034] When the similarity does not meet the preset requirement, each metasurface is redeployed.

[0035] On the other hand, obtaining the similarity between the actual channel sum and the target channel sum includes:

[0036]

[0037] Wherein, CSR (dB) is the similarity, is the actual channel sum, and h1 is the target channel sum.

[0038] On the other hand, before obtaining the preset parameters of the signal transmission path, the method further includes:

[0039] When the position of the signal receiving end is unknown and there are multiple first metasurfaces, the signal receiving end is positioned by each of the first metasurfaces to obtain the channel sum;

[0040] The first metasurface is a metasurface on which wireless signals can reach a signal receiving end.

[0041] On the other hand, when the position of the signal receiving end is unknown and there is only one first metasurface, determining the channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end under different quantized values ​​of the continuous compensation phase for each metasurface according to the metasurface network channel model includes:

[0042] Using the first metasurface as a virtual signal receiving end, and calculating a virtual channel sum according to the metasurface network channel model;

[0043] calculating a first channel between the first metasurface and the signal receiving end;

[0044] The channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end is determined based on the first channel and the virtual channel sum.

[0045] On the other hand, an embodiment of the present application provides a metasurface network, including:

[0046] Multiple metasurfaces, each metasurface is deployed at a preset position on the path from the signal transmitting end to the signal receiving end; each metasurface is configured according to the above-mentioned metasurface network configuration method.

[0047] In the configuration method of the metasurface network of the embodiment of the present application, the metasurface network includes multiple metasurfaces, which are respectively deployed at different preset positions on the signal transmission path between the signal transmitting end and the signal receiving end, and are used to reflect the wireless signal transmitted by the signal transmitting end to the signal receiving end. Due to the deployment of multiple metasurfaces, the coverage range is increased, which can meet actual needs. In addition, the present application also configures the continuous compensation phase of each metasurface, specifically configuring each metasurface with the channel with the largest amplitude and the corresponding quantized value of the continuous compensation phase of each metasurface, ensuring that the metasurface network can meet the needs and realize the reflection of wireless signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 A schematic diagram showing a flow chart of a method for configuring a metasurface network provided by one embodiment of the present application is shown;

[0050] Figure 2 is the single metasurface beamforming graph;

[0051] Figure 3 is a schematic diagram of the metasurface network;

[0052] Figure 4 It is a schematic diagram of the relationship between Rice factor and beam pattern;

[0053] Figure 5 This is a schematic diagram of the scheme for locating the signal receiving end through two metasurfaces;

[0054] Figure 6 This is a schematic diagram of the channel and determination method when the location of the signal receiving end is unknown and only a single metasurface wireless signal can reach the signal receiving end;

[0055] Figure 7 A schematic diagram showing the hardware structure of a configuration device for a metasurface network provided in an embodiment of the present application is shown;

[0056] FIG8( a ) is a schematic diagram showing the verification results of the deployment offset and the corresponding channel similarity;

[0057] FIG8( b ) is a schematic diagram of the verification results of the azimuth offset and the corresponding channel similarity;

[0058] FIG8( c ) is a schematic diagram showing the verification results of the pitch angle offset and the corresponding channel similarity;

[0059] Figure 9(a) is a schematic diagram of the performance results of a verification system;

[0060] Figure 9(b) is another schematic diagram of the verification system performance results;

[0061] Figure 10(a) is a schematic diagram of the performance verification scenario for different IoT devices;

[0062] Figure 10(b) is a schematic diagram of the performance verification results for different IoT devices;

[0063] Figure 11(a) is a schematic diagram of the uplink and downlink performance verification results when the metasurface is turned off;

[0064] Figure 11(b) is a schematic diagram of the uplink and downlink performance verification results when the metasurface is turned on;

[0065] Figure 12(a) is a schematic diagram of a mobility verification scenario;

[0066] Figure 12(b) is a schematic diagram of the results of slow mobility verification;

[0067] Figure 12(c) is a schematic diagram of the results of normal speed mobility verification. DETAILED DESCRIPTION

[0068] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0069] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0070] The promise of ubiquitous wireless connectivity often falters in complex real-world environments, where communication links are hampered by the inherent volatility of RF propagation. For example, millimeter-wave signals suffer from unstable coverage and blockage due to their high directivity and small wavelength. Even in sub-6 GHz networks, wireless links are hampered by the vagaries of indoor environments. This problem becomes particularly acute in cluttered environments such as factory floors, concrete buildings, and underground mines, significantly impacting the range of wireless signals. For IoT systems based on small radio devices, limited transmit power, antenna gain, and receiver sensitivity further hinder the pursuit of coverage.

[0071] To alleviate these issues, metasurfaces can be used to reshape the RF environment and reprogram wireless signal propagation. Currently, the focus is on functional verification of standalone metasurfaces, which only capture a small portion of the electromagnetic field from the transmitter and are insufficient in large, dispersed environments. Deploying an entire building interior with a large metasurface would be costly and complex.

[0072] To address the problems of the prior art, embodiments of the present application provide a method for configuring a metasurface network and a metasurface network. The following first introduces the method for configuring a metasurface network provided by embodiments of the present application, wherein the metasurface network includes multiple metasurfaces, each of which is deployed at a different preset position on the signal transmission path between a signal transmitting end and a signal receiving end. Embodiments of the present application utilize a group of closely coordinated metasurfaces to jointly alter the propagation environment, enabling wireless signals to be forwarded to target areas where user experience is weak or unconnected. Figure 1 FIG1 shows a flow chart of a configuration method of a metasurface network provided by an embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0073] S101: Obtain preset parameters of a signal transmission path.

[0074] S102: Establishing a metasurface network channel model according to preset parameters of the signal transmission path.

[0075] S103: According to the metasurface network channel model, the channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end is determined for each metasurface under different quantized values ​​of the continuous compensation phase.

[0076] S104: Determine a target channel sum with the largest channel sum amplitude from the multiple channel sums.

[0077] S105: Determine the quantization value of the continuous compensation phase of the target channel and each corresponding metasurface according to the quantization formula.

[0078] S106: configuring each metasurface according to the determined quantized value of the continuous compensation phase.

[0079] For S101, the type and number of preset parameters are not limited. Generally, the preset parameters include the channel from the signal transmitter to the first metasurface in the corresponding path, the quantized value of the continuous compensation phase of each metasurface in the corresponding path, the channel between adjacent metasurfaces in the corresponding path, and the channel from the last metasurface in the corresponding path to the signal receiver. In actual practice, there is no requirement for how the preset parameters are obtained.

[0080] Regarding the process of establishing the metasurface network channel model according to the preset parameters of the signal transmission path in S102, for ease of understanding, the beamforming of a single metasurface is first described here.

[0081] Figure 2 is a single metasurface beamforming diagram; Figure 2 As shown in Figure 1, a square metasurface is composed of M atoms (units). Wireless signals propagate different distances before hitting the metasurface. The phase vector caused by the incident path can be expressed as:

[0082]

[0083] where λ is the wavelength. is the distance matrix between the signal transmitter Tx and the M units on the metasurface. Assume that the desired outgoing wave direction is (α, β), where α and β are the elevation angle and azimuth angle, respectively. Then, the ideal outgoing phase vector is:

[0084]

[0085] where u=sinαcosβ and v=sinαsinβ. y m and z mis the distance of the mth unit relative to the coordinate origin on the Y and Z axes. Beamforming requires that the phase of the signal reflected by all units must be the same. Therefore, in order to redirect the incident signal to (α, β), the metasurface should generate an ideal continuous compensation phase:

[0086]

[0087] Next, we will explain the beamforming between multiple metasurfaces. For ease of explanation, we focus on the interaction between two cascaded metasurfaces, which can be easily extended to multiple metasurface cascades. In this case, the incident signal of the next metasurface comes from the outgoing signal of the previous metasurface. For example, the electromagnetic wave emitted from the mth unit of metasurface 1 (MTS1) travels a propagation distance d before reaching the nth unit of metasurface 2 (MTS2). m,n , so the phase caused by the distance between the two units is: Then, the phase matrix between MTS1 and MTS2 can be obtained as:

[0088]

[0089] in,

[0090] Therefore, the incident phase of MTS2 can be written as:

[0091]

[0092] Similarly, the desired emission direction of MTS2 is expressed as (α, β), and the theoretical phase vector Given, and can be expressed by Formula 2. Therefore, the ideal phase compensation of MTS2 is:

[0093]

[0094] Subsequently, the electromagnetic wave emitted from MTS2 travels a distance and is received by the signal receiving end Rx. The phase of Rx can be expressed as:

[0095]

[0096] in,

[0097] Therefore, the end-to-end channel for the case of two metasurfaces cascaded is as follows:

[0098]

[0099] in, and denote the diagonal phase compensation matrices of MTS1 and MTS2, respectively. a(·) is the signal attenuation due to path loss.

[0100] Then, a channel model is established between the nodes (signal transmitter Tx, metasurface (MTS), and signal receiver Rx). When there is a line-of-sight path between the nodes, the channel between the two nodes is modeled as a Rice fading channel (including line-of-sight and non-line-of-sight paths); conversely, when the line-of-sight path between the nodes is blocked, the channel between the two nodes is modeled as a Rayleigh fading channel. Figure 3 is a schematic diagram of the metasurface network; Figure 3 In this paper, all the channels entering and exiting the metasurface are assumed to be Rician fading. The channel between Tx and Rx (i.e. h Tx,Rx is assumed to be Rayleigh fading since the Tx-Rx link is completely blocked). Note that if Rx falls within the line-of-sight region of Tx, the channel can be modeled by Rician fading. Therefore, node v x and node v y The channel between It can be expressed as:

[0101]

[0102] in, yes The Rice factor. as well as They are the line-of-sight and non-line-of-sight parts of the Ricean fading channel. Modeled as a Gaussian fading with mean 0 and variance 1, Metasurface i is the i-th metasurface.

[0103] Next, calculate the Rice factor Indicates the relative strength of line-of-sight compared to multipath, to approximate The inherent relationship between beam pattern and multipath effect can be seen. Figure 4 is a schematic diagram of the relationship between the Rice factor and the beam pattern; Figure 4 As shown, most of the signal energy reflected by the metasurface is concentrated in the main lobe, which is designed to point along the line of sight. The side lobes represent the energy scattered due to multipath effects. Therefore, This can be modeled using the amplitude ratio of the main lobe to the side lobe. Here, only strong side lobes with a gain difference of less than 15dB compared to the main lobe are considered. This value can also vary in different scenarios. Azimuth angle is the azimuth angle, and elevation angle is the elevation angle.

[0104] Based on the above description, here is how to characterize the overall metasurface network channel model. Figure 3 As shown, for simplicity, the embodiment of the present application defines a node set V = {v0, v1, v2, ..., v p+1}, where v0 represents Tx, v p+1 represents Rx, and the remaining p nodes are hypersurfaces. x and node v y The channel representation between is obtained from the previous content. Therefore, the end-to-end channel of the hypersurface network can be written as (i.e., the hypersurface network channel model):

[0105]

[0106]

[0107] h l is the channel of the available signal transmission path from Tx to Rx, h is the channel sum; L path is the number of available paths; B is an array that specifically represents the S hypersurfaces contained in the l-th path, S≤p, s is the index of the element in array B, B(s) represents the s-th hypersurface in path l, Φ B(s) is the quantized value of the continuous compensation phase of the s-th metasurface in path l. x,y It is a channel between node x and node y, and the node includes a signal sending end, each metasurface and a signal receiving end.

[0108] For S103 and S104, based on the metasurface network channel model established above, it is necessary to determine the channel sums of all signal transmission paths from the signal transmitter to the signal receiver for each metasurface under different quantized values ​​of the continuous compensation phase. Then, from these multiple channel sums, the target channel sum with the largest channel sum amplitude is determined.

[0109] Specifically, the optimization function can be written as:

[0110]

[0111] In S105 and S106, after determining the target channel and the corresponding continuous compensation phase of each metasurface, the quantization formula is used to determine the quantized value of the target channel and the corresponding continuous compensation phase of each metasurface. The specific content of the quantization formula is not limited and can be determined based on the phase shifting capability of the metasurface hardware. Finally, the metasurfaces are configured based on the obtained quantized values, so that the metasurface network meets the usage requirements.

[0112] This application uses a set of tightly coordinated metasurfaces to jointly create a more intelligent radio environment, which can forward signals to target areas with weak user experience or no connection, thereby improving the performance of wireless communications. Taking four metasurfaces as an example, through the technical solution proposed in this application, an average signal strength improvement of 13.31dB (up to 26.96dB) and an average throughput gain of 1.61 times can be achieved when four metasurfaces work together. This application can also work reliably and transparently in complex radio environments for different wireless standards (such as Bluetooth, Zigbee, and Wi-Fi) and communication modes (such as single-input single-output system SISO and multiple-input multiple-output system MIMO).

[0113] In the configuration method of the metasurface network of the embodiment of the present application, the metasurface network includes multiple metasurfaces, which are respectively deployed at different preset positions on the signal transmission path between the signal transmitting end and the signal receiving end, and are used to reflect the wireless signal transmitted by the signal transmitting end to the signal receiving end. Due to the deployment of multiple metasurfaces, the coverage range is increased, which can meet actual needs. In addition, the present application also configures the continuous compensation phase of each metasurface, specifically configuring each metasurface with the channel with the largest amplitude and the corresponding quantized value of the continuous compensation phase of each metasurface, ensuring that the metasurface network can meet the needs and realize the reflection of wireless signals.

[0114] The above embodiment mentioned that when each metasurface is configured with a different continuous compensation phase, the channel sum of all signal transmission paths from Tx to Rx will change accordingly. However, the embodiment of the present application needs to determine the target channel sum with the largest channel sum amplitude from multiple channel sums; specifically, the target channel sum can be obtained through the following scheme. For each metasurface in the metasurface network, the following operations are performed cyclically until the amplitude of the channel sum meets the preset convergence condition: for the target metasurface, while the phase of the non-target metasurface is fixed, the continuous compensation phase of the target metasurface is adjusted so that the current channel sum amplitude is maximized; the target metasurface is any metasurface in the metasurface network; the channel sum that meets the preset convergence condition is determined as the target channel sum with the largest amplitude.

[0115] This application specifically adopts the substitution optimization technology to iteratively update each single variable until the channel sum converges, that is, tends to the maximum value, and the continuous compensation phase configured by each metasurface at this time is used as the final configuration value, and each metasurface is configured with this continuous compensation phase. Taking two metasurfaces as an example, first randomly generate MTS1 and MTS2 and (Continuous compensation phase). Next, fix And the continuous compensation phase of MTS1 is optimized as The continuous compensation phase is then quantized and the discrete phase compensation is then updated. And the continuous compensation phase of MTS2 is optimized to Finally, the above steps are repeated cyclically until the amplitude of the channel sum converges. For each step of the iterative update, this application adopts semidefinite relaxation (SDR) to convert the non-convex problem of metasurface configuration optimization into a convex problem by relaxing the constraints.

[0116] Through the iterative update method provided in the embodiment of the present application, the target channel sum with the largest channel sum amplitude can be determined from multiple channel sums with high efficiency.

[0117] In practical applications, different metasurfaces have different hardware and different phase shifting capabilities. Therefore, when determining the quantization value of the continuous compensation phase, the corresponding quantization formula can be determined based on the phase shifting capability of the metasurface hardware. Then, the continuous compensation phase is quantized according to the quantization formula to obtain the corresponding quantization value. For example, for a 2-bit programmable metasurface, quantization can be performed using the following quantization formula:

[0118]

[0119] …

[0120]

[0121] in,

[0122]

[0123] Among them, MTS B(1) ...MTS B(S) Respectively represent all the metasurfaces, is the continuous compensation phase of the corresponding metasurface; M,…N is the number of units of the corresponding metasurface, which can be equal or unequal.

[0124] The corresponding quantization formula is determined according to the phase shifting capability of the metasurface hardware. After the continuous compensation phase is quantized by the quantization formula, the metasurface is configured to better adapt to the hardware phase shifting capability of the metasurface.

[0125] In addition, during the actual deployment process, the deployment position of the metasurface may not completely match the deployment position in the channel model. However, as long as the end-to-end channel does not change significantly under a given deployment offset, the metasurface configuration is usable. This is because based on the optimization method in this application, similar end-to-end channels require similar metasurface configurations. That is, after configuring each metasurface according to the determined quantized value of the continuous compensation phase, the method further includes: obtaining the actual channel sum on each path from the signal transmitting end to the signal receiving end; obtaining the similarity between the actual channel sum and the target channel sum; when the similarity does not meet the preset requirements, redeploying each metasurface to ensure that the final metasurface network can meet the actual usage needs.

[0126] Here, the channel similarity ratio (CSR) can be used to quantify the similarity between the real channel and the offset channel:

[0127]

[0128] Among them, CSR (dB) is the similarity, is the actual channel sum, and h1 is the target channel sum.

[0129] In practice, the location of the signal receiving end (Rx) may be unknown before obtaining the preset parameters of the signal transmission path, so a special method is required to locate Rx. When Rx falls at the intersection of multiple metasurface fields of view (FoV), that is, when there are multiple first metasurfaces (a first metasurface is a metasurface through which wireless signals can reach the signal receiving end), any two of these first metasurfaces can be used to locate Rx. Figure 5 This is a schematic diagram of a scheme for positioning the signal receiving end through two metasurfaces; Figure 5 As shown, each metasurface can use its beam scanning capability to search for the receiver. The beam direction with the maximum RSS reported from the receiver is then used to approximate the direction of the receiver relative to the metasurface. Since the position of the metasurface is known a priori, a triangulated model can be used to determine the receiver's position. The channel sum is then calculated based on the determined receiver's position. The solution provided in this embodiment enables positioning of the signal receiver even when its position is unknown.

[0130] However, when the location of the signal receiver is unknown and only one metasurface's wireless signal can reach the receiver (i.e., only one first metasurface exists), beam scanning can only help estimate the relative angle of the receiver. Due to the lack of distance information, direct modeling of the channel between the metasurface and the receiver is no longer feasible. To overcome this problem, this embodiment proposes a solution. Figure 6This is a schematic diagram of the channel and determination method when the location of the signal receiving end is unknown and only a single metasurface wireless signal can reach the signal receiving end; Figure 6 As shown, a single supporting metasurface can be configured to perform beamforming in the Rx direction. This supporting metasurface is regarded as a virtual signal receiving end, and the optimization algorithm is applied again to obtain the optimized configuration of all other metasurfaces. Specifically, the first metasurface is used as the virtual signal receiving end, and the virtual channel sum is calculated based on the metasurface network channel model; the first channel between the first metasurface and the signal receiving end is calculated; based on the first channel and the virtual channel sum, the channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end is determined. Through the solution proposed in this embodiment, the channel sum can be calculated when the position of the signal receiving end is unknown and its position cannot be determined by the metasurface.

[0131] In order to solve the above technical problems, an embodiment of the present application also provides a metasurface network, which includes multiple metasurfaces, each of which is deployed at a preset position on the path from the signal sending end to the signal receiving end; each metasurface is configured according to the configuration method of the metasurface network in any one of the above embodiments.

[0132] Figure 7 A schematic diagram of the hardware structure of a configuration device for a super-surface network provided in an embodiment of the present application is shown; the configuration device for the super-surface network may include a processor 701 and a memory 702 storing computer program instructions.

[0133] Specifically, the processor 701 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0134] The memory 702 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 702 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 702 may include removable or non-removable (or fixed) media. Where appropriate, the memory 702 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 702 is a non-volatile solid-state memory.

[0135] The memory 702 may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0136] The processor 701 reads and executes the computer program instructions stored in the memory 702 to implement any one of the methods for configuring the metasurface network in the above embodiments.

[0137] In one example, the configuration device of the metasurface network may further include a communication interface 703 and a bus 710. Figure 7 As shown, the processor 701, the memory 702, and the communication interface 703 are connected via a bus 710 and communicate with each other.

[0138] The communication interface 703 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0139] Bus 710 includes hardware, software or both, couples the parts of the configuration equipment of super surface network to each other.For example, and not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 710 may include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0140] In addition, in conjunction with the configuration method of the metasurface network in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the configuration methods of the metasurface network in the above embodiments is implemented.

[0141] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements a method for configuring a metasurface network in any one of the above embodiments.

[0142] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0143] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0144] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0145] Finally, the following aspects can be used to evaluate the deployed and configured metasurface network.

[0146] First, verify the similarity between the actual channel and the target channel. To verify the effectiveness of CSR, both simulations and real-world experiments can be conducted. The Tx metasurface distance is set to 1m, and the direction of the incident wave is perpendicular to the metasurface. The distance between the Rx and the metasurface is 3m. The outgoing wave direction is concentrated at (0 degrees, 30 degrees), and the Rx is located in the same direction. Figure 8(a) shows the verification results of the deployment offset and the corresponding channel similarity. As shown in Figure 8(a), the metasurface deployment offset can be changed from -20cm to 20cm, where the positive / negative sign indicates left / right movement. The corresponding relationship between the deployment offset and CSR is shown in the figure. Figure 8(b) shows the verification results of the azimuth angle offset and the corresponding channel similarity. As shown in Figure 8(b), the Y-axis rotation is changed from -6 degrees to 6 degrees, where the positive / negative sign indicates the rotation direction. The corresponding relationship between the azimuth angle offset and CSR is shown in the figure. Figure 8(c) illustrates the verification results of elevation angle offset and the corresponding channel similarity. As shown in Figure 8(c), the elevation angle offset and CSR are plotted by changing the Z-axis rotation from -6 degrees to 6 degrees, where the positive / negative sign indicates the rotation direction. When the offset or rotation reaches -6 cm to 6 cm or -3 degrees to 3 degrees, respectively, the system experiences only 3 dB of attenuation. These experiments not only confirm the effectiveness of CSR but also highlight the system's significant tolerance to deployment errors. This is because the beamforming of the metasurface involves the collaboration of many meta-atoms, meaning that not all meta-atoms on the metasurface fail simultaneously when there is a deployment offset. This spatial diversity provides adaptability, enabling the system to withstand the effects of metasurface offset. It should be noted that due to the effects of multipath, the simulation and experimental results differ slightly, but the profiles remain consistent.

[0147] Next is the overall system performance verification. To verify the system performance, multiple metasurfaces can be placed in an irregular fan-shaped conference room. Figure 9(a) is a schematic diagram of the system performance verification results. As shown in Figure 9(a), the Tx and four metasurfaces are fixed at different positions. The signal-to-noise ratio (SNR) is measured when the Rx is located at more than 20 random positions. The Tx and Rx are omnidirectional antennas. Figure 9(b) is another schematic diagram of the system performance verification results. As shown in Figure 9(b), when the metasurface is "ON" (off), the present invention shows a significant capacity gain. For example, when the metasurface is in the "OFF" (open) and "ON" (closed) states, the 80th percentile SNR is 18dB and 23dB, respectively, indicating that this solution achieves a 27% improvement in SNR.

[0148] Next, we conduct performance verification on different IoT devices. Figure 10(a) shows a schematic diagram of the performance verification scenario for different IoT devices. Following the scheme in Figure 10(a), the system performance of different IoT devices is demonstrated using three IoT radios: Zigbee 3.0 with a CC2530 radio, BLE 5.0 with a CSRBC417 radio, and 2.4 GHz Wi-Fi with an ESP32 radio. All IoT devices use the SISO communication mode. Figure 10(b) shows the performance verification results for different IoT devices. Figure 10(b) shows the throughput when the metasurface is turned on and off, with "A-C" representing the results for the three IoT devices. When the metasurface is turned on, all IoT devices experience a consistent and significant improvement in throughput (up to 33.69%).

[0149] In addition, this application evaluates the throughput performance in SISO and MIMO communication modes. Two laptops equipped with AR9580 802.11n wireless network cards are used as transmitters and receivers, each with three antennas. We vary the communication mode between 1x1 SISO, 2x2 MIMO, and 3x3 MIMO, and collect throughput measurements using the iperf toolbox. The results are shown in Figure 10(b), where "D-F" represents the throughput of different communication modes. First, for the SISO mode, communication between the transmitter and receiver is successfully achieved, as they cannot directly reach each other when the metasurface is off (i.e., throughput is N / A). Second, for the MIMO mode, average throughput improvements of 2.76Mbps and 5.18Mbps can be achieved in the 2x2 and 3x3 modes, respectively, representing an improvement of up to 60.74% compared to the baseline (i.e., when the metasurface is "OFF"). Overall, this scheme not only enhances the coverage and link capacity of different IoT devices, but is also transparent to their protocols and communication modes.

[0150] Next is the verification of uplink and downlink performance. Due to the reciprocity of electromagnetic wave propagation, the metasurface configuration optimized for the downlink (Tx-Rx) can be similarly applied to the uplink (Rx-Tx). In this experiment, three metasurface scenarios are used as examples to evaluate this bidirectional communication (Figures 11(a) and 11(b)). Specifically, MTS2 is deployed at a 30-degree angle relative to MTS2, with a spacing of 3m. Rx is close to MTS2, and there are 21 test positions. For each Rx test position, the SNR of the uplink (i.e., from Rx to Tx) and downlink (i.e., from Tx to Rx) are measured when the metasurface is "ON" and "OFF". Figure 11(a) is a schematic diagram of the uplink and downlink performance verification results when the metasurface is turned off; as shown in Figure 11(a), when the metasurface is turned off, the SNR of most test positions is low. Figure 11(b) illustrates the performance verification results for both uplink and downlink communications when the metasurface is enabled. As shown in Figure 11(b), the signal-to-noise ratio (SNR) at most locations significantly improves when the metasurface is activated. The average SNR improvements for the uplink and downlink are 13.31 dB and 13.09 dB, respectively. These results demonstrate that our scheme can seamlessly facilitate uplink communications, even though its optimization scheme assumes a downlink channel by default.

[0151] The following is a mobility verification scenario. Figure 12(a) illustrates the mobility verification scenario. As shown in Figure 12(a), the receiver (Rx) moves along a predefined 3m trajectory at two constant speeds: 0.5m / s (slow) and 1.0m / s (normal). In each case, two metasurfaces are configured in real time to accurately direct the reflected signal toward the receiver. Figure 12(b) illustrates the results of the slow mobility verification; the relationship between distance (Distance) and SNR for slow movement is shown in the figure. Figure 12(c) illustrates the results of the normal speed mobility verification; the relationship between distance (Distance) and SNR for normal speed movement is shown in the figure. Figures 12(b) and 12(c) show the real-time SNR measurements at the receiver. When the metasurface is "ON," our proposed scheme consistently achieves improved SNR at both speed settings compared to the baseline when the metasurface is "OFF." These results demonstrate that our proposed scheme is well-suited for indoor human mobility scenarios.

[0152] Finally, a specific embodiment is provided. The metasurface of this embodiment is a 2-bit programmable metasurface. A DC voltage regulator (MESTEK DP3005B) is used to provide a bias voltage for the metasurface. By providing different DC voltage levels (0V or 5V), a pair of PIN diodes in each unit switches states, thereby acting as a 2-bit phase shifter, introducing phase values ​​of 0, 2 / π, π, or 3π / 2. To independently control each unit, this embodiment uses a microcontroller (i.e., STMicroelectronics' STM32H743IIT6) and 64 SN74LV595 shift registers to provide different DC voltages (0V / 5V) to the PIN diodes. Specifically, this embodiment divides 256 meta-atoms into 16 groups in parallel, each group consisting of 4 shift registers, and serially controls 32 meta-atoms.

[0153] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0154] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A method for configuring a metasurface network, characterized in that: The metasurface network includes a plurality of metasurfaces, each of which is deployed at a different preset position on a signal transmission path between a signal transmitting end and a signal receiving end. The method includes: Obtaining preset parameters of the signal transmission path; wherein the preset parameters include a channel from the signal transmitting end to the first metasurface of the corresponding path, a quantized value of the continuous compensation phase of each metasurface on the corresponding path, a channel between adjacent metasurfaces on the corresponding path, and a channel from the last metasurface on the corresponding path to the signal receiving end; Establish a metasurface network channel model based on the preset parameters of the signal transmission path; Determining, according to the metasurface network channel model, the channel sum of all signal transmission paths from a signal transmitting end to a signal receiving end for each metasurface under different quantized values ​​of the continuous compensation phase; Determine a target channel sum with the largest channel sum amplitude from among multiple channel sums; Determine the quantization value of the continuous compensation phase of the target channel and each corresponding metasurface according to a quantization formula; Each metasurface is configured according to the determined quantized value of the continuous compensation phase.

2. The method for configuring a metasurface network according to claim 1, wherein: The hypersurface network channel model includes: in, h l is the channel of the path l from the signal transmitter to the signal receiver, h is the channel sum; L path is the number of available paths; B is an array that specifically represents the S hypersurfaces contained in the l-th path, s is the index of the element in array B, B(s) represents the s-th hypersurface in path l, Φ B(s) is the quantized value of the continuous compensation phase of the s-th metasurface in path l; h x,y is the channel between node x and node y, and the node includes the signal transmitter, each hypersurface, and the signal receiver; v0 represents the signal transmitter, v p+1 Characterizes the signal receiving end.

3. The method for configuring a metasurface network according to claim 2, wherein: Determining a target channel sum with the largest channel sum amplitude from the multiple channel sums includes: For each metasurface in the metasurface network, the following operation is cyclically performed until the amplitude of the channel sum satisfies a preset convergence condition: for a target metasurface, while the phase of a non-target metasurface is fixed, the continuous compensation phase of the target metasurface is adjusted so that the current channel sum amplitude is maximized; the target metasurface is any metasurface in the metasurface network; The channel sum that meets the preset convergence condition is determined as the target channel sum with the largest magnitude.

4. The method for configuring a metasurface network according to claim 3, wherein: Determine the quantized value of the continuous compensation phase, including: Determine the corresponding quantization formula based on the phase shifting capability of the metasurface hardware; The continuous compensation phase is quantized according to the quantization formula to obtain a corresponding quantization value.

5. The method for configuring a metasurface network according to claim 4, wherein: The quantification formula includes: …… in, Among them, MTS B(1) ...MTS B(S) Respectively represent all the metasurfaces, is the continuous compensation phase of the corresponding metasurface; M, N are the number of units of the corresponding metasurface.

6. The method for configuring a metasurface network according to claim 1, wherein: After configuring each metasurface according to the determined quantized value of the continuous compensation phase, the method further includes: Obtain the actual channel sum on each path from the signal sending end to the signal receiving end; Obtaining a similarity between the actual channel sum and the target channel sum; When the similarity does not meet the preset requirement, each metasurface is redeployed.

7. The method for configuring a metasurface network according to claim 6, wherein: The obtaining of the similarity between the actual channel sum and the target channel sum includes: Wherein, CSR (dB) is the similarity, is the actual channel sum, and h1 is the target channel sum.

8. The method for configuring a metasurface network according to claim 1, wherein: Before obtaining the preset parameters of the signal transmission path, the method further includes: When the position of the signal receiving end is unknown and there are multiple first metasurfaces, the signal receiving end is positioned by each of the first metasurfaces to obtain the channel sum; The first metasurface is a metasurface on which wireless signals can reach a signal receiving end.

9. The method for configuring a metasurface network according to claim 8, wherein: When the position of the signal receiving end is unknown and there is only one first metasurface, determining, according to the metasurface network channel model, the channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end under different quantized values ​​of the continuous compensation phase for each metasurface, includes: Using the first metasurface as a virtual signal receiving end, and calculating a virtual channel sum according to the metasurface network channel model; calculating a first channel between the first metasurface and the signal receiving end; The channel sum of all signal transmission paths from the signal transmitting end to the signal receiving end is determined based on the first channel and the virtual channel sum.

10. A metasurface network, characterized in that: include: Multiple metasurfaces, each metasurface is deployed at a preset position on the path from the signal transmitting end to the signal receiving end; Each metasurface is configured according to the metasurface network configuration method according to any one of claims 1 to 9.

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