Intelligent metasurface communication performance evaluation system and evaluation method

Abstract

The invention discloses an intelligent metasurface communication performance evaluation system and evaluation method, and belongs to the technical field of testing. The evaluation system is simple in composition and easy to deploy in a real scene, the characteristics of low cost, low complexity and easy deployment of the RIS are met, the deployment cost is reduced, and engineering and industrialization popularization of the RIS technology is facilitated; according to the method, the communication performance of the RIS is directly evaluated from an electromagnetic environment channel, the capacity of the RIS for intelligently controlling space electromagnetic wave signals can be essentially measured, and meanwhile, for a complex and changeable electromagnetic environment, the method can evaluate the influence of the electromagnetic environment on the capacity of the RIS for regulating and controlling the electromagnetic signals and locate reasons of RIS capacity sudden change under accidental conditions.

Description

Technical Field

[0001] The present invention belongs to the field of testing technology, and in particular relates to an intelligent metasurface communication performance evaluation system and evaluation method. Background Art

[0002] Reconfigurable Intelligent Surface (RIS) is a two-dimensional electromagnetic metamaterial composed of a large number of reconfigurable passive devices. Through programming, RIS can intelligently control the amplitude, phase and polarization of electromagnetic wave signals in space to achieve the reconstruction of the wireless electromagnetic environment. RIS has the characteristics of low cost, low power consumption, low complexity and easy deployment. It provides a new network paradigm for future wireless communication, perception and positioning, and has become one of the research focuses of 6G key technologies.

[0003] The performance evaluation of existing RIS communications mainly tests signal power, RSRP (reference signal received power), etc. The main process includes:

[0004] (1) Figure 1 As shown, the signal generator generates an unmodulated continuous wave signal or a modulated signal to simulate a signal transmitting device. The signal generator is connected to the excitation antenna, and the millimeter wave signal is converted into an electromagnetic wave through the transmitting antenna and transmitted.

[0005] (2) Through programming, RIS regulates the amplitude, phase, polarization, and frequency of the electromagnetic wave signal in space, adjusts the receiving probe antenna, aligns the antenna with the receiving angle, and uses a spectrum analyzer to measure the power, RSRP, and other indicators of the received signal. Then, the antenna is moved to different angles, and the spectrum analyzer is used to measure the power, RSRP, and other indicators of the received signal. The changes in signal power at different angles are compared.

[0006] The existing performance evaluation methods of RIS communication have the following disadvantages: First, the performance evaluation of existing RIS communication mainly tests signal power, RSRP (reference signal received power), etc., and does not directly evaluate the performance of RIS communication from the electromagnetic environment channel itself. It is impossible to directly analyze the reasons why the signal quality changes after the signal is intelligently controlled by RIS in theory; second, in the actual engineering deployment of RIS, the reflection angle of RIS needs to be repeatedly adjusted in different electromagnetic environments, which is not conducive to the engineering industrialization and promotion of RIS technology. Summary of the invention

[0007] In view of the above-mentioned technical problems existing in the prior art, the present invention proposes an intelligent metasurface communication performance evaluation system and evaluation method, which are reasonably designed, overcome the shortcomings of the prior art, and have good effects.

[0008] In order to achieve the above object, the present invention adopts the following technical solution:

[0009] An intelligent metasurface communication performance evaluation system, comprising a signal generation module, a low noise amplifier, an excitation antenna, a switch matrix, a signal shielding device, a RIS, a probe antenna, a signal receiving and collecting module, and a signal analysis software;

[0010] A signal generating module is configured to generate a broadband modulated signal;

[0011] a low noise amplifier configured to reduce noise and amplify a modulated signal;

[0012] An excitation antenna is configured to convert a millimeter wave signal into an electromagnetic wave and transmit it;

[0013] a switch matrix configured to switch links in different directions;

[0014] A signal shielding device, configured to shield the signal emitted by the excitation antenna;

[0015] RIS, configured to control the amplitude, phase and polarization of the signal;

[0016] a probe antenna configured to receive a signal reflected from the RIS;

[0017] A signal receiving and collecting module is configured to receive and collect electromagnetic signals;

[0018] The signal analysis software is configured to calculate a channel estimation matrix and output channel indicators including EVM, frequency error, and power.

[0019] In addition, the present invention also mentions a method for evaluating the communication performance of an intelligent metasurface, which adopts an intelligent metasurface communication performance evaluation system as described above, and the evaluation method includes an evaluation method for RIS communication performance in RIS application scenarios of spatial blind spot filling, edge coverage enhancement and improved system throughput; wherein

[0020] The evaluation method of RIS communication performance in the space blind spot filling scenario specifically includes the following steps:

[0021] Step S01: The signal generation module generates a broadband modulated signal x(t), the switch matrix is ​​switched to switch 0, the signal receiving and acquisition module is used to collect IQ data, the signal analysis software demodulates the broadband modulated signal y0(t), and calculates the channel estimation matrix H0(a0, θ0, φ0) and the EVM result EVM0(a0, θ0, φ0).

[0022] y0(t)=H0(a0, θ0, φ0)x(t)+w(t) (1);

[0023] Where a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal under line-of-sight conditions, respectively, and w(t) represents noise; if the influence of the signal receiving and acquisition module is ignored, H0(a0, θ0, φ0) is the optimal channel estimation matrix; EVM0(a0, θ0, φ0) is the optimal EVM;

[0024] Step S02: the switch matrix is ​​switched to the second switch, and the angle of the second excitation antenna is adjusted so that no matter how the probe antenna is adjusted, the signal analysis module cannot receive the signal, and only the spectrum of the background noise of the signal analysis module is displayed, and the angle θ2 of the second excitation antenna at this time is recorded;

[0025] Step S03: Switch the switch matrix to the first switch, activate RIS, adjust the amplitude, angle and phase of the signal, adjust the receiving probe antenna, align the antenna with the receiving angle to receive the signal y1(t) adjusted by RIS, and calculate the EVM result from RIS to the receiving end with the signal analysis software, and record the result that satisfies

[0026] |EVM0(a0, θ0, φ0)-EVM2(a, θ1, φ)|≤ε EVM (2);

[0027] The amplitude a={a i ∈[0, 1], 1≤i≤M}, angle θ1 and phase φ={φ i ∈[0, 2π), 1≤i≤M}, where v EVM represents the allowable EVM error, M represents the number of RIS reflection units, a i represents the amplitude after RIS reflection unit i is regulated, φi represents the phase after RIS reflection unit i is regulated, and the signal analysis software outputs the channel estimation matrix H2(a, θ1, φ) from RIS to the receiving end;

[0028] Step S04: remove RIS or turn off RIS, adjust the angle θ3 of the probe antenna, directly receive the broadband modulated signal x(t) emitted by the first excitation antenna, and use the signal analysis software to calculate the channel estimation matrix H1(a0, θ3, φ0) and the EVM result EVM1(a0, θ3, φ0) from the transmitter to the receiver;

[0029] Step S05: The signal after RIS regulation is expressed as shown in formula (3):

[0030] y1(t)=H2(a,θ1,φ)ΛH1(a0,θ3,φ0)x(t)+w(t)=H′0(a,θ 1，3 ,φ)x(t)+w(t) (3);

[0032] Among them, the diagonal matrix Indicates the regulation of signal by RIS, θ 1，3 represents the phase after RIS regulation;

[0033] Step S06: Calculate H0(a0, θ0, φ0) and H′0(a, θ 1，3， The matrix p-norm (Minkowski distance) of φ) is shown in formula (4):

[0034] d p (H0, H′0) = (∑ m＝0 ∑ n＝0 |(H0) mn -(H′0) mn | p ) 1 / p (4);

[0035] Or use the RV coefficient of the matrix to measure the similarity between matrices H0 and H′0, as shown in formula (5):

[0036]

[0037] Among them, T represents the transpose operation, tr represents the trace of the matrix, and the value range of RV(H0, H′0) is [0,1]. The closer it is to 1, the closer the distance between the matrices H0 and H′0 is. That is, the state of RIS at this time has achieved the same communication capability as the line-of-sight signal, realizing the function of spatial blindness filling.

[0038] Preferably, the method for evaluating RIS communication performance in an edge coverage enhancement scenario specifically comprises the following steps:

[0039] Step S11: The signal generation module generates a broadband modulated signal x(t), and moves the signal receiving and collecting module according to a fixed step length Δl to collect the IQ data signal y l (t), signal analysis software for y l (t) Demodulate the broadband modulated signal and calculate the signal power P at this time l (a l ,θ l ,φ l , l), frequency error f l (a l ,θ l ,φ l , l) and EVM results EVM l (a l ,θ l ,φ l , l), where a l ,θ l, φl respectively represent the signal amplitude, angle and phase of the signal with a distance l between the signal generating module and the signal receiving and collecting module, and set the signal power lower limit P Thre and EVM lower limit EVM Thre , the tag signal receiving and collecting module meets the requirements of

[0040]

[0041] and

[0042]

[0043] The distance at which P , ε EVM Respectively represent the power error and EVM error allowed by the system, They represent the signal amplitude, angle and phase when the distance between the signal generating module and the signal receiving and collecting module is l0, respectively. represents the signal power when the distance is l0, EVM results when the distance is l0; if there are multiple l0 that satisfy inequalities (6) and (7) at the same time, the distance with the largest value is recorded as l0; if the influence of the signal receiving and acquisition module is ignored, then is the power limit corresponding to the edge of signal coverage without RIS assistance, The EVM upper limit of the signal that can be demodulated by the signal analysis software. The frequency error at this time is It is the upper limit of the frequency error of the signal that the signal analysis software can lock;

[0044] Step S12: Activate RIS, adjust the amplitude, angle and phase of the signal, the signal receiving and collecting module at position l0 collects IQ data, adjust the receiving end probe antenna, align the probe antenna with the receiving angle to receive the signal adjusted by RIS Signal analysis software calculates the EVM results from RIS to the receiving end If this is satisfied

[0045]

[0046] Then continue to move the signal receiving and collecting module in a fixed step length Δl in a direction away from the signal generating module;

[0047] Step S13: Adjust the amplitude, angle and phase of the signal, the signal receiving and collecting module at the position of l0+nΔl collects IQ data, adjusts the receiving end probe antenna, and aligns the probe antenna with the receiving angle to receive the signal after RIS adjustment. Signal analysis software calculates the EVM results from RIS to the receiving end Records that satisfy both

[0048]

[0049] and

[0050]

[0051] The amplitude of Angle θ1 and phase and frequency error in, represents the amplitude after adjustment of RIS reflection unit i, represents the phase after adjustment of RIS reflection unit i, and M represents the number of RIS reflection units;

[0052] Step S14: Since the distance between the signal generating module and the signal receiving and collecting module has changed, the channel estimation matrix is ​​affected. and The Mahalanobis distance is as shown in formula (11):

[0053]

[0054] Excluded and The interference between the correlations, The smaller, the and The closer the distance between them is, that is, the communication distance between the signal generating module and the signal receiving and collecting module increases by nΔl, but with the assistance of RIS, normal communication can be achieved, realizing the function of edge coverage enhancement.

[0055] Preferably, the evaluation method of RIS communication performance in the scenario of improving system throughput specifically comprises the following steps:

[0056] Step S21: The signal generation module generates a broadband modulated signal x(t), the signal receiving and acquisition module acquires the IQ data signal, the signal analysis software demodulates the broadband modulated signal of the IQ data, adjusts the probe antenna to maximize the throughput TPUT0(a0, θ0, φ0), and calculates the channel estimation matrix H0(a0, θ0, φ0) and the EVM result EVM0(a0, θ0, φ0) at this time.

[0057] y0(t)=H0(a0, θ0, φ0)x(t)+w(t) (12);

[0058] Where a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal without RIS-assisted communication, respectively, and w(t) represents noise; if the influence of the signal receiving and acquisition module is ignored, under the premise of maintaining the maximum throughput TPUT0(a0, θ0, φ0), H0(a0, θ0, φ0) is the optimal channel estimation matrix, and EVM0(a0, θ0, φ0) is the optimal EVM;

[0059] Step S22: Activate multiple RISs at the same time, adjust the amplitude, angle and phase of the signal respectively, the signal receiving and collecting module collects the IQ data signal, and the signal analysis software demodulates the broadband modulated signal of the IQ data; the system at this time is an (N+1)×(N+1) MIMO system composed of N+1 transmitting units and N+1 receiving units, where N represents the number of RISs; adjust the receiving end probe antenna so that the throughput is greater than TPUT0(a0, θ0, φ0), continue to adjust the receiving end probe antenna, and when the throughput no longer changes, calculate the channel estimation matrix H1(a, θ1, φ) and EVM result EVM1(a, θ1, φ) at this time, and record the amplitude at this time Angle θ1 and phase in, It represents the amplitude received by the kth receiving unit after the RIS reflector unit i is regulated. represents the phase received by the kth receiving unit after the RIS reflection unit i is regulated, and M represents the number of RIS reflection units;

[0060] Step S23: The signal after RIS regulation is expressed as shown in formula (13):

[0061]

[0062] in, Diagonal Matrix Indicates the regulation of signal by RIS;

[0063] Step S24: By decomposing the matrix H1, Λ is the regulation of the signal amplitude and phase by RIS, and H2 is the remaining part; calculate the matrix p-norm of H2(a, θ1, φ) and the unit matrix I, as shown in formula (14):

[0064] d p (H2, I) = (∑ m＝0 ∑ n＝0 |(H2) mn -(I) mn | p ) 1 / p (14);

[0065] d pThe smaller (H2, I), the closer it is to the unit matrix. At this time, H1(a, θ1, φ)≈ΛH0(a0, θ0, φ0), that is, RIS enhances the signal, improves the channel environment, and increases the throughput.

[0066] Beneficial technical effects brought by the present invention:

[0067] The evaluation system of the present invention is simple in composition and easy to deploy in real scenarios, which meets the characteristics of RIS, such as low cost, low complexity and easy deployment, reduces the deployment cost, and is conducive to the engineering industrialization and promotion of RIS technology. The present invention directly evaluates the performance of RIS communication from the electromagnetic environment channel itself, and can essentially measure the ability of RIS to intelligently control electromagnetic wave signals in space. At the same time, for complex and changeable electromagnetic environments, the method can evaluate the influence of the electromagnetic environment on the ability of RIS to regulate electromagnetic signals, and locate the cause of the sudden change of RIS ability under occasional conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is the RIS communication performance test block diagram;

[0069] Figure 2 This is a schematic diagram of the composition of the space blind spot communication system;

[0070] Figure 3 A schematic diagram of the edge coverage enhancement communication system;

[0071] Figure 4 Schematic diagram of the communication system composition to improve system throughput. DETAILED DESCRIPTION

[0072] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0073] The present invention mainly builds a RIS communication performance evaluation system and designs a method for evaluating RIS communication performance in a typical application scenario, which is described in detail below.

[0074] The performance evaluation system of RIS communication consists of a signal generation module, a low noise amplifier, an excitation antenna, a switch matrix, a signal shielding device, a RIS, a probe antenna, a signal receiving and collecting module, and a signal analysis software. The signal generation module (simulating signal generation equipment such as base stations) generates broadband modulated signals such as 5G NR and LTE. Compared with unmodulated continuous wave signals, the larger the bandwidth of the modulated signal, the larger the background noise, and the smaller the communication link budget. Therefore, the measurement of modulated signals usually uses a low noise amplifier to amplify the signal with low noise. The excitation antenna converts the millimeter wave signal into an electromagnetic wave and transmits it. The switch matrix is ​​used to switch links in different directions. The signal shielding device (simulating obstacles such as buildings) blocks and shields the signal emitted by the excitation antenna. RIS regulates the amplitude, phase and polarization of the signal. The probe antenna receives the signal reflected by the RIS. The signal receiving and collecting equipment (simulating mobile phone terminals, etc.) is used to receive and collect signals. The signal analysis software is used to calculate the channel estimation matrix and output channel indicators such as EVM, frequency error, and power.

[0075] (1) RIS communication in space blind spot scenarios

[0076] (1.1) The signal generation module generates a wideband modulated signal x(t) such as 5G NR and LTE. The switch matrix is ​​switched to switch 0. The signal receiving and acquisition module is used to collect IQ data. The signal analysis software demodulates the wideband modulated signal of the IQ data y0(t). The channel estimation matrix H0(a0, θ0, φ0) and the EVM result EVM0(a0, θ0, φ0) are calculated.

[0077] y0(t)=H0(a0, θ0, φ0)x(t)+w(t)

[0078] Among them, a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal under line-of-sight conditions (i.e. when there are no obstacles), and w(t) represents noise. If the influence of the signal receiving and acquisition module is ignored, H0(a0, θ0, φ0) can be considered as the optimal channel estimation matrix, and EVM0(a0, θ0, φ0) is the optimal EVM.

[0079] (1.2) The switch matrix is ​​switched to the second switch, and the angle of the second excitation antenna is adjusted so that no matter how the probe antenna is adjusted, the signal receiving and acquisition module cannot receive the signal, and only displays the spectrum of the background noise of the signal, and records the angle θ2 of the second excitation antenna at this time.

[0080] (1.3) Switch the switch matrix to the first switch. Activate RIS, adjust the amplitude, angle and phase of the signal, adjust the receiving probe antenna, align the antenna with the receiving angle to receive the signal y1(t) adjusted by RIS, and use the signal analysis software to calculate the EVM result from RIS to the receiving end, and record the result that satisfies

[0081] |EVM0(a0, θ0, φ0)-EVM2(a, θ1, φ)|≤ε EVM

[0082] The amplitude a={a i ∈[0, 1], 1≤i≤M}, angle θ1 and phase φ={φ i ∈[0, 2π), 1≤i≤M}, where ε EVM represents the allowable EVM error, M represents the number of RIS reflection units, a i represents the amplitude after RIS reflection unit i is regulated, and φi represents the phase after RIS reflection unit i is regulated. The signal analysis software outputs the channel estimation matrix H2(a, θ1, φ) from RIS to the receiving end.

[0083] (1.4) Remove RIS or turn off RIS. Adjust the angle θ3 of the probe antenna to directly receive the broadband modulated signal x(t) emitted by the first excitation antenna. The signal analysis software calculates the channel estimation matrix H1(a0, θ3, φ0) and the EVM result EVM1(a0, θ3, φ0) from the transmitter to the receiver.

[0084] (1.5) The signal after RIS regulation can be expressed as

[0085] y1(t)=H2(a, θ1, φ)ΛH1(a0, θ3, φ0)x(t)+w(t)

[0086] =H′0(a, θ 1,3 ,φ)x(t)+w(t)

[0087] Among them, the diagonal matrix Indicates the regulation of signal by RIS, θ 1，3 Indicates the phase after RIS regulation.

[0088] (1.6) Calculate H0(a0, θ0, φ0) and H′0(a, θ 1，3 , φ) of the matrix p-norm (Minkowski distance), that is

[0089]

[0090] Or use the RV coefficient of the matrix, a value that measures the similarity between matrices H0 and H′0, that is,

[0091]

[0092] Where T represents the transpose operation, and tr represents the trace of the matrix. The value range of RV(H0, H′0) is [0,1]. The closer it is to 1, the closer the distance between matrices H0 and H′0 is. That is, the state of RIS at this time has achieved the same communication capability as the line-of-sight signal, realizing the function of spatial blindness filling.

[0093] (2) RIS communication in edge coverage enhancement scenario

[0094] (2.1) The signal generation module generates broadband modulation signals x(t) such as 5G NR and LTE, and moves the signal receiving and acquisition module to collect IQ data receiving signals y according to a fixed step size Δl. l (t), signal analysis software for y l (t) Demodulate the broadband modulated signal and calculate the signal power P at this time l (a l ,θ l ,φ ( , l), frequency error f l (a l ,θ l ,φ l , l) and EVM results EVM l (a l ,θ l ,φ l , l), where a l ,θ l ,φ l Respectively represent the signal amplitude, angle and phase when the distance between the signal generating module and the signal receiving and collecting module is l. Set the signal power lower limit P Thre and EVM lower limit EVM Thre The tag signal receiving and collecting module meets the following requirements during the movement process:

[0095]

[0096] and

[0097]

[0098] The distance at which P , ε EVM Respectively represent the power error and EVM error allowed by the system, They represent the signal amplitude, angle and phase when the distance between the signal generating module and the signal receiving and collecting module is l0, respectively. represents the signal power when the distance is l0, EVM result when the distance is l0. If there is a l0 that satisfies both of the above inequalities, the distance with the largest value is recorded as l0. If the influence of the signal receiving and acquisition module is ignored, it can be considered that is the power limit corresponding to the edge of signal coverage without RIS assistance, The EVM upper limit of the signal that can be demodulated by the signal analysis software. The frequency error at this time is It is the upper limit of the frequency error of the signal that the signal analysis software can lock.

[0099] (2.2) Activate RIS, adjust the amplitude, angle and phase of the signal, and the signal receiving and collecting module at position l0 collects IQ data. Adjust the receiving probe antenna and align the antenna with the receiving angle to receive the signal adjusted by RIS. Signal analysis software calculates the EVM results from RIS to the receiving end If this is satisfied

[0100]

[0101] Continue to move the signal receiving and collecting module in a fixed step length Δl in a direction away from the signal generating module.

[0102] (2.3) Adjust the amplitude, angle and phase of the signal. The signal receiving and collecting module at the position of l0+nΔl collects IQ data. Adjust the receiving probe antenna and align the antenna with the receiving angle to receive the signal after RIS adjustment. Signal analysis software calculates the EVM results from RIS to the receiving end Records that satisfy both

[0103]

[0104] and

[0105]

[0106] The amplitude of Angle θ1 and phase and frequency error in, represents the amplitude after adjustment of RIS reflection unit i, represents the phase after adjustment by RIS reflection unit i, and M represents the number of RIS reflection units.

[0107] (2.4) Since the distance between the signal generation module and the signal receiving and acquisition module has changed, the channel estimation matrix has been affected. Considering that there may be correlation between frequency errors, the calculation and The Mahalanobis distance is

[0108]

[0109] Excluded and The interference between the correlations, The smaller, the and The closer the distance between them is, that is, although the communication distance between the signal generating module and the signal receiving and collecting module increases by hΔl, normal communication can be achieved with the assistance of RIS, realizing the function of edge coverage enhancement.

[0110] (3) RIS communication in scenarios that improve system throughput

[0111] (3.1) The signal generation module generates wideband modulated signals x(t) such as 5G NR and LTE. The signal receiving and acquisition module acquires IQ data signals. The signal analysis software demodulates the wideband modulated signals on the IQ data and adjusts the probe antenna to maximize the throughput TPUT0(a0, θ0, φ0). The channel estimation matrix H0(a0, θ0, φ0) and the EVM result EVM0(a0, θ0, φ0) are calculated.

[0112] y0(t)=H0(a0, θ0, φ0)x(t)+w(t)

[0113] Among them, a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal without RIS-assisted communication, respectively, and w(t) represents noise. If the influence of the signal receiving and acquisition module is ignored, it can be considered that under the premise of maintaining the maximum throughput, H0(a0, θ0, φ0) is the optimal channel estimation matrix and EVM0(a0, θ0, φ0) is the optimal EVM.

[0114] (3.2) Activate multiple RIS at the same time, and adjust the amplitude, angle and phase of the signal respectively. The signal receiving and acquisition module collects the IQ data signal, and the signal analysis software demodulates the broadband modulated signal of the I0 data. At this time, the system is an (N+1)×(N+1) MIMO system consisting of N+1 transmitting units and N+1 receiving units, where N represents the number of RIS. Adjust the receiving probe antenna so that the throughput is greater than TPUT0(a0, θ0, φ0), and continue to adjust the receiving probe antenna. When the throughput no longer changes, calculate the channel estimation matrix H1(a, θ1, φ) and EVM result EVM1(a, θ1, φ) at this time, and record the amplitude at this time. Angle θ1 and phase in, It represents the amplitude received by the kth receiving unit after the RIS reflector unit i is regulated. It represents the phase received by the kth receiving unit after the RIS reflection unit i is adjusted, and M represents the number of RIS reflection units.

[0115] (3.3) The signal after RIS regulation can be expressed as

[0116] y1(t)=H1(a, θ1, φ)x(t)+w(t)

[0117] =H2(a, θ1, φ)ΛH0(a0, θ0, φ0)x(t)+w(t)

[0118] in, Diagonal Matrix Indicates the regulation of signal by RIS.

[0119] (3.4) By decomposing the matrix H1, Λ is the regulation of the signal amplitude and phase by RIS, and H2 is the remaining part. Calculate the matrix p-norm (Minkowski distance) between H2(a, θ1, φ) and the identity matrix I, that is,

[0120]

[0121] d p The smaller (H2, I), the closer it is to the unit matrix. At this time, H1(a, θ1, φ)≈ΛH0(a0, θ0, φ0), that is, RIS enhances the signal, improves the channel environment, and increases the throughput.

[0122] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A smart metasurface communication performance evaluation system, characterized in that: It includes signal generation module, low noise amplifier, excitation antenna, switch matrix, signal shielding device, RIS, probe antenna, signal receiving and acquisition module, and signal analysis software; A signal generating module is configured to generate a broadband modulated signal; a low noise amplifier configured to reduce noise and amplify a modulated signal; An excitation antenna is configured to convert a millimeter wave signal into an electromagnetic wave and transmit it; a switch matrix configured to switch links in different directions; A signal shielding device, configured to shield the signal emitted by the excitation antenna; RIS, configured to control the amplitude, phase and polarization of the signal; a probe antenna configured to receive a signal reflected from the RIS; A signal receiving and collecting module is configured to receive and collect electromagnetic signals; The signal analysis software is configured to calculate a channel estimation matrix and output channel indicators including EVM, frequency error, and power.

2. A method for evaluating the communication performance of an intelligent metasurface, characterized in that: An intelligent metasurface communication performance evaluation system as described in claim 1 is adopted, and the evaluation method includes an evaluation method for RIS communication performance in RIS application scenarios of spatial blind spot filling, edge coverage enhancement and system throughput improvement; wherein The evaluation method of RIS communication performance in the space blind spot filling scenario specifically includes the following steps: Step S01: The signal generation module generates a broadband modulated signal x(t), the switch matrix switches to switch 0, the signal receiving and acquisition module is used to collect IQ data y0(t), the signal analysis software demodulates y0(t) to perform broadband modulated signal demodulation, and calculates the channel estimation matrix H0(a0,θ0,φ0) and the EVM result EVM0(a0,θ0,φ0) at this time. y0(t)=H0(a0,θ0,φ0)x(t)+w(t) (1); Where a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal under line-of-sight conditions, respectively, and w(t) represents the noise; if the influence of the signal receiving and acquisition module is ignored, H0(a0, θ0, φ0) is the optimal channel estimation matrix; EVM0(a0,θ0,φ0) is the optimal EVM; Step S02: the switch matrix is ​​switched to the second switch, and the angle of the second excitation antenna is adjusted so that no matter how the probe antenna is adjusted, the signal receiving and collecting module cannot receive the signal, and only displays the spectrum of the background noise of the signal, and records the angle γ2 of the second excitation antenna at this time; Step S03: Switch the switch matrix to the first switch, activate RIS, adjust the amplitude, angle and phase of the signal, adjust the receiving probe antenna, align the antenna with the receiving angle to receive the signal y1(t) adjusted by RIS, and calculate the EVM result from RIS to the receiving end with the signal analysis software, and record the result that satisfies |EVM0(a0,θ0,φ0)-EVM2(a,θ1,φ)|≤ε EVM (2); The amplitude a corresponding to EVM2(a,θ1,φ) when i ∈[0,1],1≤i≤M}, angle θ1 and phase φ={φ i ∈[0,2π),1≤i≤M}, where ε EVM represents the allowable EVM error, M represents the number of RIS reflection units, a i represents the amplitude after adjustment of RIS reflection unit i, φ i represents the phase after adjustment of RIS reflection unit i, and the signal analysis software outputs the channel estimation matrix H2(a,θ1,φ) from RIS to the receiving end; Step S04: Remove RIS or turn off RIS, adjust the angle θ3 of the probe antenna, directly receive the broadband modulated signal x(t) emitted by the first excitation antenna, and use the signal analysis software to calculate the channel estimation matrix H1(a0,θ3,φ0) and the EVM result EVM1(a0,θ3,φ0) from the transmitter to the receiver. Step S05: The signal after RIS regulation is expressed as shown in formula (3): y1(t)=H2(a,θ1,φ)ΛH1(a0,θ3,φ0)x(t)+w(t)=H′0(a,θ 1,3 ,φ)x(t)+w(t) (3); Among them, the diagonal matrix Indicates the regulation of signal by RIS, θ 1,3 represents the phase after RIS regulation; Step S06: Calculate H0(a0,θ0,φ0) and H′0(a,θ 1,3 ,φ), as shown in formula (4): <h2 style=";text-align:left;direction:ltr">d<h2 style=";text-align:left;direction:ltr"> p <h2 style=";text-align:left;direction:ltr"> (H0,H′0)=(∑<h2 style=";text-align:left;direction:ltr"> m＝0 <h2 style=";text-align:left;direction:ltr"> ∑<h2 style=";text-align:left;direction:ltr"> n＝0 <h2 style=";text-align:left;direction:ltr"> |(H0)<h2 style=";text-align:left;direction:ltr"> mn <h2 style=";text-align:left;direction:ltr"> -(H′0)<h2 style=";text-align:left;direction:ltr"> mn <h2 style=";text-align:left;direction:ltr"> |<h2 style=";text-align:left;direction:ltr"> p <h2 style=";text-align:left;direction:ltr"> )<h2 style=";text-align:left;direction:ltr"> 1 / p <h2 style=";text-align:left;direction:ltr"> (4); Or use the RV coefficient of the matrix to measure the similarity between matrices H0 and H′0, as shown in formula (5): Among them, T represents the transpose operation, tr represents the trace of the matrix, and the value range of RV(H0,H′0) is [0,1]. The closer it is to 1, the closer the distance between the matrices H0 and H′0 is. That is, the state of RIS at this time has achieved the same communication capability as the line-of-sight signal, realizing the function of spatial blindness filling.

3. The method for evaluating the communication performance of an intelligent metasurface according to claim 2, characterized in that: The evaluation method of RIS communication performance in the edge coverage enhancement scenario specifically includes the following steps: Step S11: The signal generation module generates a broadband modulated signal x(t), and moves the signal receiving and collecting module according to a fixed step length Δl to collect the IQ data signal y l (t), signal analysis software for y l (t) Demodulate the broadband modulated signal and calculate the signal power P at this time l (a l ,θ l ,φ l ,l), frequency error f l (a l ,θ l ,φ l ,l) and EVM results EVM l (a l ,θ l ,φ l ,l), where a l ,θ l ,φ l Respectively represent the signal amplitude, angle and phase of the signal with a distance of l between the signal generating module and the signal receiving and collecting module, and set the signal power lower limit P Thre and EVM lower limit EVM Thre , the tag signal receiving and collecting module meets the requirements of and The distance at which P ,ε EVM Respectively represent the power error and EVM error allowed by the system, They represent the signal amplitude, angle and phase when the distance between the signal generating module and the signal receiving and collecting module is l0 respectively. represents the signal power when the distance is l0, EVM results when the distance is l0; if there are multiple l0 that satisfy inequalities (6) and (7) at the same time, the distance with the largest value is recorded as l0; if the influence of the signal receiving and acquisition module is ignored, then is the power limit corresponding to the edge of signal coverage without RIS assistance, The EVM upper limit of the signal that can be demodulated by the signal analysis software. The frequency error at this time is It is the upper limit of the frequency error of the signal that the signal analysis software can lock; Step S12: Activate RIS, adjust the amplitude, angle and phase of the signal, the signal receiving and collecting module at position l0 collects IQ data, adjust the receiving end probe antenna, align the probe antenna with the receiving angle to receive the signal adjusted by RIS Signal analysis software calculates the EVM results from RIS to the receiving end If this is satisfied Then continue to move the signal receiving and collecting module in a fixed step length Δl in a direction away from the signal generating module; Step S13: Adjust the amplitude, angle and phase of the signal, the signal receiving and collecting module at the position of l0+nΔl collects IQ data, adjusts the receiving end probe antenna, and aligns the probe antenna with the receiving angle to receive the signal after RIS adjustment. Signal analysis software calculates the EVM results from RIS to the receiving end Records that satisfy both and The amplitude of Angle θ1 and phase and frequency error in, represents the amplitude after adjustment of RIS reflection unit i, represents the phase after adjustment of RIS reflection unit i, and M represents the number of RIS reflection units; Step S14: Since the distance between the signal generating module and the signal receiving and collecting module has changed, the channel estimation matrix is ​​affected. and The Mahalanobis distance is as shown in formula (11): Excluded and The interference between the correlations, The smaller, the and The closer the distance between them is, that is, although the communication distance between the signal generating module and the signal receiving and collecting module increases by nΔl, normal communication can be achieved with the assistance of RIS, realizing the function of edge coverage enhancement.

4. The method for evaluating the communication performance of an intelligent metasurface according to claim 2, characterized in that: The evaluation method of RIS communication performance in the scenario of improving system throughput specifically includes the following steps: Step S21: The signal generation module generates a broadband modulated signal x(t), the signal receiving and acquisition module acquires the IQ data signal, the signal analysis software demodulates the broadband modulated signal of the IQ data, and adjusts the probe antenna so that the throughput TPUT0(a0,θ0,φ0) is the largest, and the channel estimation matrix H0(a0,θ0,φ0) and EVM result are calculated at this time EVM0(a0,θ0,φ0), then y0(t)=H0(a0,θ0,φ0)x(t)+w(t)(12); Where a0, θ0, φ0 represent the initial amplitude, angle and phase of the signal without RIS-assisted communication, respectively, and w(t) represents the noise. If the influence of the signal receiving and acquisition module is ignored, under the premise of maintaining the maximum throughput TPURT0(a0,θ0,φ0), H0(a0,θ0,φ0) is the optimal channel estimation matrix, EVM0(a0,θ0,φ0) is the optimal EVM; Step S22: Activate multiple RISs at the same time, adjust the amplitude, angle and phase of the signal respectively, the signal receiving and acquisition module collects the IQ data signal, and the signal analysis software demodulates the broadband modulated signal of the IQ data; the system at this time is an (N+1)×(N+1) MIMO system composed of N+1 transmitting units and N+1 receiving units, where N represents the number of RISs; adjust the receiving end probe antenna so that the throughput is greater than TPUT0(a0,θ0,φ0), continue to adjust the receiving end probe antenna, and when the throughput no longer changes, calculate the channel estimation matrix H1(a,θ1,φ) and EVM result at this time EVM1(a,θ1,φ), record the amplitude at this time Angle θ1 and phase in, It represents the amplitude received by the kth receiving unit after the RIS reflector unit i is regulated. represents the phase received by the kth receiving unit after the RIS reflection unit i is regulated, and M represents the number of RIS reflection units; Step S23: The signal after RIS regulation is expressed as shown in formula (13): in, Diagonal Matrix Indicates the regulation of signal by RIS; Step S24: By decomposing the matrix H1, Λ is the regulation of the signal amplitude and phase by RIS, and H2 is the remaining part; Calculate the matrix p-norm of H2(a,θ1,φ) and the identity matrix I, as shown in formula (14): d p (H2,I)=(∑ m＝0 ∑ n＝0 |(H2) mn -(I) mn | p ) 1 / p (14); d p The smaller (H2,I), the closer it is to the unit matrix, then H1(a,θ1,φ)≈ΛH0(a0,θ0,φ0).

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