Dynamic non-stationary space-time channel reconstruction method, system and device

Abstract

The application discloses a dynamic non-stationary space-time channel reconstruction method, system and device, and the dynamic non-stationary space-time channel reconstruction method comprises the following steps: a target non-stationary channel model to be reconstructed is established; the target channel is reconstructed in a continuous time window; probe antenna weights and channel reconstruction precision errors in different time and different measured device antenna directions are calculated according to different channel reconstruction criteria; and the antenna direction of the measured device and the probe antenna weight are jointly optimized, so that the dynamic non-stationary space-time channel is reconstructed. The application solves the problem that the existing channel reconstruction method is difficult to improve the overall channel reconstruction precision in the continuous time window under the condition that the number of probe antennas is limited and relatively sparse. Through the joint optimization of the probe antenna weight and the measured device antenna direction, the precision and efficiency of the dynamic non-stationary space-time channel reconstruction are improved.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication technology, specifically relating to a dynamic non-stationary space-time channel reconstruction method, system, and device. Background Technology

[0002] In the development of wireless communication equipment, advanced testing methods are crucial for verifying new technologies and evaluating the performance of new devices, supporting the evolution of each generation of mobile communication technology. Due to the constantly changing external environment, field testing struggles to guarantee the reliability and repeatability of equipment verification, and it is also costly. In previous studies, RF test signals were typically transmitted directly to the antenna port of the device under test (DUT) via an antenna connector, a method known as conducted testing. Due to its simplicity and low cost, conducted testing has been dominant in the industry for single-antenna systems. However, conducted testing ignores the impact of the antenna on the overall performance of the communication system, and highly integrated antennas no longer reserve RF ports, making conducted testing unsuitable for multi-antenna systems.

[0003] To address the aforementioned issues, Over-the-Air (OTA) testing technology, which provides a repetitive and controllable real-world channel environment and accurately reflects the test results of the entire system, has emerged and gained favor from academia, industry, and standardization organizations. OTA performance testing aims to utilize a microwave anechoic chamber environment, employing absorbing materials to eliminate electromagnetic wave reflections within the anechoic chamber and shield against electromagnetic interference from the outside. By precisely reconstructing the channel, it achieves end-to-end performance evaluation of the device under test. The multi-probe anechoic chamber method, by controlling the transmission time, signal carrier frequency, and the combination of activated probe antennas, can flexibly and accurately reproduce the real wireless channel environment from multiple dimensions of "time-frequency-space." It has become an OTA performance testing method for next-generation wireless communication equipment recognized by several authoritative international standardization organizations, including the 3rd Generation Partnership Project (3GPP), the Cellular Telecommunications Industry Association (CTIA), and the International Telecommunication Union (ITU).

[0004] The multi-probe anechoic chamber method is currently the mainstream method for air interface performance testing. This method convolves the transmission signal generated by the base station simulator with the simulated channel impulse response generated by the channel simulator. Then, appropriate weights are assigned to the probe antennas and sent to the device under test, thereby realizing the reconstruction of the fading signal that has experienced the real field channel in the anechoic chamber. Considering the development trend of highly integrated antennas and the research and deployment of higher frequency band and larger scale antenna array technologies, the multi-probe anechoic chamber method will become the only feasible air interface performance testing method for next-generation wireless communication equipment.

[0005] Currently, channel reconstruction based on the multi-probe anechoic chamber method typically employs Plane Wave Synthesis (PWS) and Pre-Faded Signal Synthesis (PFS) techniques. PWS aims to reproduce each sub-path within each cluster by assigning complex weights to antenna probes to synthesize single plane waves with specific angles of arrival, Doppler shifts, and amplitudes. In contrast, PFS, due to its lower complexity and higher robustness, has become a more widely used channel reconstruction scheme in OTA performance testing. Unlike PWS, PFS uses clusters as the smallest unit, focusing on reconstructing the spatial characteristics of each cluster. Specifically, it accurately simulates the statistical characteristics of the channel using parameters such as spatial correlation, time-delay power spectrum, Doppler spectrum, and cross-polarization ratio.

[0006] Next-generation wireless communication systems will use higher frequency bands. Due to their shorter wavelengths, there are relatively fewer diffraction components in the channel, exhibiting propagation characteristics similar to optical propagation. Therefore, the number of clusters in higher frequency communication will be greatly reduced. Furthermore, with the improvement of spatiotemporal resolution, the high-speed movement of the transceiver and scatterer makes the power change of the cluster more rapid in the time and space domains, thus exhibiting spatiotemporal non-stationary characteristics. This leads to higher requirements for the dynamic characterization accuracy of channel reconstruction methods in air interface performance testing. However, traditional channel reconstruction methods based on multi-probe anechoic chambers are all time-slice-based and cannot reflect the spatiotemporal non-stationary characteristics of the channel. Moreover, there is a lack of high-precision continuous-time dynamic non-stationary spatiotemporal channel reconstruction methods within continuous time windows.

[0007] Due to cost and hardware limitations, multi-probe anechoic chambers employ a fan-shaped probe wall structure, and only a small number of probe antennas can be activated simultaneously. During channel reconstruction, existing methods independently optimize probe antenna weight parameters for each discrete time slice within the reconstruction time window, and typically do not consider adjusting the antenna pointing of the device under test (DUT) during air interface performance testing. This results in an inability to improve the overall channel reconstruction accuracy within a continuous time window under conditions of limited and relatively sparse probe antenna numbers. A few studies on dynamic channel reconstruction methods use a turntable structure to align the antenna pointing of the DUT with the line-of-sight (LoS) path in real time. However, these methods do not fully utilize the degrees of freedom provided by the DUT's antenna pointing, and when the LoS path angle of arrival (AoA) changes significantly, the turntable's physical rotation speed limitation prevents rapid alignment, leading to significant shortcomings in engineering implementation.

[0008] Based on the aforementioned technical problems in the existing technology, this invention proposes a dynamic non-stationary space-time channel reconstruction method, system, and device. Summary of the Invention

[0009] The purpose of this invention is to address the shortcomings of existing technologies by providing a dynamic non-stationary space-time channel reconstruction method, system, and device.

[0010] On the one hand, this invention provides a dynamic non-stationary space-time channel reconstruction method for air interface performance testing, comprising:

[0011] Establish a model of the target non-stationary channel to be reconstructed;

[0012] The target channel is reconstructed within a continuous time window. Based on different channel reconstruction criteria, the probe antenna weight and channel reconstruction accuracy error under different antenna pointing directions of the device under test at different times are calculated.

[0013] By jointly optimizing the antenna pointing of the device under test and the antenna weight of the probe, a reconstruction scheme with the lowest cumulative reconstruction error within a continuous time window is obtained. Thus, the reconstruction of the dynamic non-stationary space-time channel is achieved by adjusting the antenna pointing of the device under test and the antenna weight of the probe in real time.

[0014] Furthermore, establishing the target non-stationary channel model to be reconstructed includes:

[0015] Based on the test scenario, generate a virtual movement trajectory of the device under test relative to the base station;

[0016] Based on the virtual movement trajectory of the device under test, large-scale fading parameters of path loss, molecular absorption effect and shadow fading are generated.

[0017] Based on the changing dynamic characteristics of sub-paths or clusters in the virtual moving trajectory, the changes in the number of sub-paths and clusters, as well as the changes in small-scale fading parameters including cluster delay, Doppler shift, and angle spread, are modeled using the stochastic process method to obtain the dynamic non-stationary space-time channel model of the target to be reconstructed.

[0018] Furthermore, the target non-stationary channel model to be reconstructed comprises multiple paths or clusters of paths, and the impulse response h(t,φ,τ) is expressed as:

[0019]

[0020] Where t is time, φ is AoA, τ is cluster delay, and h LoS (t) represents the channel impulse response of the LoS path. The impulse response of the non-line-of-sight (NLoS) path channel is given by: K is the Rice factor; n is the cluster index, with N(t) clusters at time t; m(n) is the sub-path index in the nth cluster, with M(n) sub-path indices; δ is the reconstruction accuracy; and τ is the sub-path index. LoS (t), τ n (t), τ n,m(n) (t) represents the time delay of the LoS path, the nth cluster, and its m(n)th sub-path, respectively;

[0021] For different channel characteristics, different reconstruction target parameters are selected, and the reconstruction accuracy δ of the channel is measured by the Euclidean distance between the target and the reconstruction channel statistical parameters. To maximize the reconstruction accuracy, the optimization problem of the reconstruction accuracy δ at a single time step is expressed as:

[0022]

[0023] Where ε(t) represents the time-varying parameters or statistical characteristics of the target channel selected according to different channel reconstruction criteria, indicating the spatial, temporal, and frequency correlations and electric field strength of the channel. In a multi-probe anechoic chamber, by adding a time-varying weight vector w(t) to the probe antenna, the corresponding parameters or statistical characteristics of the reconstructed channel are synthesized within the quiet zone, over a continuous time window T = [t0, t...]. n ]Inside, Represented as:

[0024]

[0025] Where d is the antenna spacing of the device under test, Ω a (t) represents the spatial pointing angle of the antenna of the device under test, Ω p (t) represents the spatial angle between the probe antenna and the device under test. By controlling the probe antenna weight vector w(t), the desired reconstructed beam can be obtained, a(d,Ω) a(t) is the transfer matrix of the probe antenna in the quiet zone, expressed as:

[0026] a(d,Ω a (t))=[a1(d,Ω a (t)),...,a N (d,Ω a (t))] T ……(4);

[0027]

[0028] Where λ is the wavelength. and The antenna of the device under test points to Ω. a (t) and the pointing θ of the nth reference antenna n The direction vector in the global coordinate system, ω d This is the Doppler frequency shift.

[0029] Furthermore, in establishing the target non-stationary channel model to be reconstructed, the antenna pointing Ω of the device under test is adjusted in real time. a (t) and the antenna is pointed to Ω a (t) is jointly optimized with the probe antenna weight w(t).

[0030] Furthermore, a controllable turntable capable of rotating at different adjustable angular velocities in the horizontal and vertical directions is used. The device under test is fixed on the controllable turntable in the anechoic chamber, enabling real-time adjustment of the antenna pointing of the device under test. When the spatial angular velocity is ω... Ω At that time, within a time interval [t] i ,t i+1 Within [the specified range], the antenna pointing of the device under test changes only from its initial position. After adjusting the turntable to align a portion of the probe antenna positions, the set of coordinates of the positions that can be achieved can be obtained. Represented as:

[0031]

[0032] In an arc length of Δtω Ω Within the sphere of L, where Δt = t i+1 -t i This indicates the position of the probe antenna that the antenna of the device under test can reach in the next moment, which is determined by the position of the probe antenna that was aligned in the previous moment.

[0033] Among them, the spatial angle Ω pointed to by the antenna of the device under test a It can be determined by the horizontal angle. and the vertical angle is Confirm that the antenna pointing spatial angle Ω of the device under test is... aThe direction vector at time t Represented as:

[0034]

[0035] In a continuous time window T∈[t0,t n Within this framework, the optimization problem for dynamic non-stationary space-time channel reconstruction is expressed as:

[0036]

[0037]

[0038]

[0039]

[0040] According to equation (8) above, we obtain that in the time window t∈[t0,t... n The time-varying antenna pointing adjustment vector Φ of the device under test when reconstructing a dynamic non-stationary space-time channel h(t,τ,φ) is described. a (t)={Ω a The time-varying probe antenna weight vector w(t) = {w(t)}.

[0041] Furthermore, the virtual motion trajectory includes the obstacle location, the orientation of the device under test, the direction of movement, and the speed of movement. Based on the obstacle location, the orientation of the device under test, the direction of movement, and the speed of movement, the large-scale fading parameters and small-scale fading parameters of the channel required for reconstruction are extracted.

[0042] Furthermore, when adjusting the antenna pointing of the device under test in real time, the device under test is positioned so that it faces the center of the fan-shaped probe wall, wherein the fan-shaped probe wall is equipped with N... v Line N h N columns v ×N h =N probe antennas, with equal spacing in the x and y directions, covering 180° horizontally and [missing information] vertically. The distance between the probe wall and the device under test is L.

[0043] On the other hand, this invention discloses a dynamic non-stationary space-time channel reconstruction system for air interface performance testing, comprising:

[0044] The joint optimization module calculates the channel reconstruction error through the central processing unit based on different channel reconstruction criteria, and performs joint optimization of probe weighting and antenna pointing of the device under test.

[0045] The global control module is used to control the base station simulator to generate the required source data, provide the channel simulator with the required channel files and probe weights, and control the controllable turntable to adjust the antenna pointing of the device under test.

[0046] A controllable turntable is used for real-time adjustment of the antenna pointing of the device under test;

[0047] Fan-shaped probe wall, used to deploy probe antennas.

[0048] In another aspect, the present invention discloses a dynamic non-stationary space-time channel reconstruction device for air interface performance testing, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the reconstruction method when executing the computer program.

[0049] The beneficial effects of this invention are:

[0050] The technical solution of this invention solves the drawback that existing channel reconstruction methods are difficult to improve the overall channel reconstruction accuracy within a continuous time window under the condition that the number of probe antennas is limited and relatively sparse. By jointly optimizing the probe antenna weights and the antenna pointing of the device under test, the accuracy and efficiency of dynamic non-stationary space-time channel reconstruction are improved.

[0051] The method of generating dynamic feature parameters based on the spatiotemporal variation law of the non-stationary channel to be reconstructed can effectively reflect the spatiotemporal non-stationary characteristics of the channel and provide the target channel to be reconstructed for air interface performance testing.

[0052] A multi-probe anechoic chamber with a controllable turntable is used for air interface performance testing. Based on the original anechoic chamber structure, a master control device is used to realize the global control of the test system, enabling real-time control of the antenna aperture pointing spatial angle of the device under test. The structure is simple, easy to deploy and apply, and has high control accuracy. Attached Figure Description

[0053] Figure 1 This is a flowchart of the dynamic non-stationary space-time channel reconstruction method in an embodiment of the present invention;

[0054] Figure 2 This is a flowchart of the method for generating dynamic feature parameters of a non-stationary channel to be reconstructed in an embodiment of the present invention;

[0055] Figure 3 This is a schematic diagram of a dynamic non-stationary space-time channel reconstruction system for air interface performance testing in an embodiment of the present invention;

[0056] Figure 4 This is a schematic diagram of the main control device in an embodiment of the present invention;

[0057] Figure 5This is a flowchart of an air interface performance test based on the system in an embodiment of the present invention. Detailed Implementation

[0058] To better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0059] Example

[0060] like Figure 1 As shown, the dynamic non-stationary space-time channel reconstruction method for air interface performance testing includes:

[0061] Dynamic non-stationary space-time channel reconstruction methods include:

[0062] Establish a model of the target non-stationary channel to be reconstructed;

[0063] The target channel is reconstructed within a continuous time window. Based on different channel reconstruction criteria, the probe antenna weight and channel reconstruction accuracy error under different antenna pointing directions of the device under test at different times are calculated.

[0064] Since the channel reconstruction accuracy error varies depending on the antenna pointing of different devices under test, the reconstruction scheme with the lowest cumulative reconstruction error within a continuous time window is obtained by jointly optimizing the antenna pointing of the device under test and the antenna weight of the probe. Thus, the reconstruction of the dynamic non-stationary space-time channel is achieved by adjusting the antenna pointing of the device under test and the antenna weight of the probe in real time.

[0065] The dynamic space-time non-stationary channel to be reconstructed consists of multiple paths or clusters of paths, and its impulse response h(t,φ,τ) is expressed as:

[0066]

[0067] Where t is time, φ is AoA, τ is cluster delay, and h LoS (t) represents the channel impulse response of the LoS path. The impulse response of the non-line-of-sight (NLoS) path channel is given by K; the Rice factor is given by n; there are N(t) cluster indices at time t; and m(n) are the sub-path indices in the nth cluster, with M(n) in total.

[0068] For different channel characteristics, different reconstruction target parameters are selected, and the reconstruction accuracy δ of the channel is measured by the Euclidean distance between the target and the reconstruction channel statistical parameters. To maximize the reconstruction accuracy, the optimization problem of the reconstruction accuracy δ at a single time step is expressed as:

[0069]

[0070] Wherein, ε(t) represents the time-varying parameters or statistical characteristics of the target channel selected according to different channel reconstruction criteria, which can represent the spatial, temporal, and frequency correlations and electric field strength of the channel. The parameters or statistical characteristics of the reconstructed channel synthesized in the quiet zone by adding a time-varying weight vector w(t) to the probe antenna in a multi-probe anechoic chamber are as follows:

[0071]

[0072] In the above formula, d is the antenna spacing of the device under test, Ω a (t) represents the spatial pointing angle of the antenna of the device under test. By controlling the probe antenna weight vector w(t), the desired beam pointing, i.e., the angle of arrival Ω of the device under test, can be obtained. p (t), a(d,Ω) a (t) is the transfer matrix of the probe antenna in the quiet zone, expressed as:

[0073] a(d,Ω a (t))=[a1(d,Ω a (t)),...,a N (d,Ω a (t))] T ,

[0074]

[0075] In the above formula, λ is the wavelength. and The antenna of the device under test points to Ω. a (t) and the pointing θ of the nth reference antenna n The direction vector in the global coordinate system, ω d For Doppler frequency shift;

[0076] To achieve higher channel reconstruction accuracy, this embodiment adjusts the antenna pointing Ω of the device under test in real time. a (t) and jointly optimize the pointing and probe antenna weight w(t) to obtain a reconstruction scheme with minimum error accumulation;

[0077] A multi-probe anechoic chamber is used, with a fan-shaped probe wall structure placed on it, and N probes are arranged on it. v Line N h N columns v ×N h =N probe antennas, with equal spacing in the x and y directions, covering 180° horizontally and [missing information] vertically. The distance between the probe wall and the device under test is L;

[0078] A controllable turntable capable of rotating at different adjustable angular velocities in the horizontal and vertical directions is used to achieve real-time adjustment of the antenna pointing of the device under test. Due to the physical speed limit of the CNC turntable, when the spatial angular velocity is ω... Ω At that time, within a time interval [t] i ,t i+1 Within [the specified range], the antenna pointing of the device under test can only be changed from its initial position. After adjusting the turntable to align a portion of the probe antenna positions, the set of coordinates of the positions that can be achieved can be obtained. Represented as:

[0079]

[0080] The set of coordinates that can reach a position lies on an arc of length Δtω. Ω Within the sphere of L, where Δt = t i+1 -t i In other words, the position of the probe antenna that the antenna of the device under test can reach in the next moment is related to and determined by the position of the probe antenna that was aligned in the previous moment. Therefore, the model has the Markov property.

[0081] Among them, the spatial angle Ω pointed to by the antenna of the device under test a It can be determined by the horizontal angle. and the vertical angle is Confirm that the antenna pointing spatial angle Ω of the device under test is... a The direction vector at time t Represented as:

[0082]

[0083] In summary, within a continuous time window T∈[t0,t... n Within this framework, the optimization problem for dynamic non-stationary space-time channel reconstruction is expressed as:

[0084]

[0085]

[0086]

[0087]

[0088] In actual engineering implementation, the range of achievable angles of the turntable within the continuous time window in the above optimization problem is adjusted according to the turntable speed used, thereby obtaining a more practical reconstruction scheme.

[0089] This problem can be transformed into a dynamic path planning problem, and the solution algorithms include, but are not limited to, heuristic algorithms, machine learning, and dynamic path planning with multi-stage decision-making.

[0090] By solving the above equation, we obtain the result within the time window t∈[t0,t... n The time-varying antenna pointing adjustment vector Φ of the device under test when reconstructing a dynamic non-stationary space-time channel h(t,τ,φ) is described. a (t)={Ω a Unlike traditional methods, this embodiment improves channel reconstruction accuracy by continuously adjusting the antenna pointing of the device under test, and is applicable to any channel reconstruction target parameters.

[0091] like Figure 3 As shown, the dynamic non-stationary space-time channel reconstruction system for air interface performance testing includes:

[0092] The joint optimization module calculates the channel reconstruction error through the central processing unit based on different channel reconstruction criteria, and performs joint optimization of probe weighting and antenna pointing of the device under test.

[0093] The global control module is used to control the base station simulator to generate the required source data, provide the channel simulator with the required channel files and probe weights, and control the controllable turntable to adjust the antenna pointing of the device under test.

[0094] A controllable turntable is used for real-time adjustment of the antenna pointing of the device under test;

[0095] Fan-shaped probe wall, used to deploy probe antennas.

[0096] The dynamic non-stationary space-time channel reconstruction device for air interface performance testing includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the reconstruction method.

[0097] As another improvement, taking the PFS channel reconstruction method as an example, the reconstruction accuracy is measured by spatial correlation error, and the specific application process and optimization problem-solving method of the dynamic non-stationary space-time channel reconstruction method are given. It should be noted that the dynamic non-stationary space-time channel reconstruction method is still effective when other methods such as the PWS method are used to implement the channel reconstruction scheme.

[0098] When spatial correlation ρ(d,Ω) is used as the channel reconstruction metric, ε is expressed as:

[0099]

[0100] Where Ω is the beam arrival angle Ωp Relative to Ω a spatial angle, G p1 (Ω) and G p2 (Ω) is the radiation pattern of antenna pair (p1,p2), and P(·) is the angular power spectrum (PAS), satisfying ∮P(Ω)dΩ=1;

[0101] Correspondingly, there are:

[0102]

[0103] Considering the physical constraint that the probe antenna weights are positive and time-dependent, i.e.:

[0104] ||w(t)|| 1=1, 0≤w i ≤1, i∈[1,N], t∈[t0,t1];

[0105] In summary, the optimization problem can now be expressed as:

[0106]

[0107] st||w(t)||1=1,0≤w i ≤1, i∈[1,N], t∈[t0,t1]

[0108]

[0109]

[0110]

[0111] ||w(t)|| 1=1, 0≤w i ≤1, i∈[1,N], t∈[t0,t1]

[0112] Reconstructing t0 to t using the PFS method n For the above optimization problem, the target channel at different times t and the antenna pointing Ω of the device under test are calculated. a The probe antenna weight w(t) and spatial correlation error Δρ(t) under (t):

[0113] <![CDATA[Ω a =α1]]> <![CDATA[α1,w(t0)→Δρ(t0)]]> <![CDATA[α1,w(t1)→Δρ(t1)]]> <![CDATA[α1,w(t n )→Δρ(t n )]]> <![CDATA[Ω a =α2]]> <![CDATA[α2,w(t0)→Δρ(t0)]]> <![CDATA[α2,w(t1)→Δρ(t1)]]> <![CDATA[α2,w(t n )→Δρ(t n )]]> … … … … … <![CDATA[Ω a =a max ]]> <![CDATA[α max ,w(t0)→Δρ(t0)]]> <![CDATA[α max ,w(t1)→Δρ(t1)]]> <![CDATA[α max ,w(t n )→Δρ(t n )]]>

[0114] Table 1. Antenna pointing Ω of different devices under test at different times t. a The probe antenna weight w(t) and the reconstruction spatial correlation error Δρ(t) under (t)

[0115] Based on the table above, the continuous time window T∈[t0,t] is calculated. nThe cumulative channel spatial correlation reconstruction error Δρ after continuously adjusting the antenna pointing of the device under test (DUT) can be used to obtain the optimal time-varying antenna pointing adjustment vector Φ. a (t)={Ω a The time-varying probe antenna weight vector w(t) = {w(t)}.

[0116] like Figure 2 As shown, the method for generating dynamic feature parameters of a non-stationary channel to be reconstructed includes:

[0117] Based on the target channel model, this embodiment generates a virtual movement trajectory of the device under test, including obstacle locations, device orientation, movement direction, and movement speed, thereby extracting the large-scale and small-scale fading parameters required for reconstruction. Specifically, the large-scale fading parameters include path loss, shadow fading, and scatterer absorption caused by the UHF band. The path loss at the corresponding location and the standard deviation of shadow fading in the required scenario are calculated based on the generated movement trajectory of the device under test. At the same time, the atmospheric molecular absorption effect of the frequency band used is considered to calculate the corresponding parameters.

[0118] Clusters at the device under test are classified into static clusters and dynamic clusters. Static clusters only need to be considered in terms of their birth and death, and their PAS does not change with time. However, the PAS of dynamic clusters changes with time. The intensity of the dynamic change of the channel is determined according to the required scenario. The corresponding stochastic process modeling method is used to model the changes in the number of clusters and small-scale fading parameters, including cluster delay, Doppler shift, and angle spread, so as to obtain the dynamic non-stationary spatiotemporal information of the target to be reconstructed. Specifically, the initial number of clusters is first determined. The number of cluster birth and death is modeled according to the Markov stochastic process model. The intensity of the non-stationarity of the channel is determined according to the required scenario, so as to determine the birth and death rate and angle spread of clusters in the channel. Homogeneous Poisson stochastic process modeling is used to obtain the arrival interval and mean survival time of clusters, ensuring the spatiotemporal consistency of the channel. For dynamic clusters, they are modeled as actively disappearing clusters and passively disappearing clusters. Actively disappearing clusters become invisible due to changes in distance, that is, the angle spread will gradually decrease and become "0" at the disappearance time. Passively disappearing clusters disappear due to the influence of high-speed birth and death scatterers in the environment. The continuous change of cluster angle spread is reflected by Markov stochastic process modeling.

[0119] Finally, a specific cluster delay is assigned to each cluster, and the Doppler frequency shift and the receiving and transmitting angle information are calculated based on the movement mode of the device under test and the frequency band used.

[0120] like Figure 3-4As shown, in order to realize dynamic space-time non-stationary channel reconstruction, this embodiment proposes an air interface performance testing system including a main control device that can realize overall system control. The main control device includes a central processing unit, a memory, and input / output ports. It is connected to a base station simulator, a channel simulator, and a controllable turntable through a communication serial port. The main control device is used to control the base station simulator to generate source data, provide the channel simulator with the required channel file and probe weights, and control the controllable turntable to adjust the antenna pointing of the device under test.

[0121] The main control equipment can calculate and reconstruct the target parameters through the central processing unit and realize the joint optimization of the antenna pointing of the device under test and the antenna weight of the probe, thereby controlling the controllable turntable to adjust the spatial angle of the antenna pointing of the device under test;

[0122] like Figure 5 As shown, the test method based on the air interface performance test system includes:

[0123] The device under test is fixed on a controllable turntable in the darkroom, so that the device under test faces the center of the fan-shaped probe wall;

[0124] Based on the required scenario and device characteristics, generate the virtual movement trajectory of the device under test and obtain the dynamic non-stationary channel and its characteristic parameters required for reconstruction.

[0125] Channel reconstruction is performed using a preset method. A transmission signal is generated by a base station simulator and then convolved with the simulated channel impulse response generated by the channel simulator. Appropriate weights are assigned to the probe antenna and sent to the device under test.

[0126] According to different φ a (t) and φ p (t) Calculate the target and reconstructed channel target parameter errors at each time step, and jointly optimize the probe antenna weighting and the antenna aperture pointing of the device under test to obtain the optimal channel reconstruction scheme.

[0127] This invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims.

Claims

1. A dynamic non-stationary space-time channel reconstruction method for air interface performance testing, characterized in that, include: Establish a target non-stationary channel model to be reconstructed, and adjust the antenna pointing of the device under test in real time during the establishment of the target non-stationary channel model. And the antenna is pointed With probe antenna weight Perform joint optimization; A controllable turntable capable of rotating at different adjustable angular velocities in the horizontal and vertical directions is used. The device under test is fixed on the controllable turntable in an anechoic chamber, enabling real-time adjustment of the antenna pointing of the device under test. When the spatial angular velocity is... At that time, within a time interval Inside, the antenna pointing of the device under test is only changed from its initial position. After adjusting and aligning a portion of the probe antenna positions using the turntable, the set of coordinates of the reachable positions can be obtained. Represented as: ……（6）； In an arc length of Within the curved surface of the sphere, where, This indicates the position of the probe antenna that the antenna of the device under test can reach in the next moment, which is determined by the position of the probe antenna that was aligned in the previous moment. Among them, the spatial angle pointed to by the antenna of the device under test From the horizontal angle and the vertical angle is Determine the spatial pointing angle of the antenna of the device under test. exist Direction vector at time Represented as: ……（7）； In continuous time window The optimization problem for dynamic non-stationary space-time channel reconstruction is expressed as: ... (8); According to the above formula (8), we obtain the time window China's dynamic non-stationary space-time channel Time-varying device under test antenna pointing adjustment vector during reconstruction and time-varying probe antenna weight vector ; The target channel is reconstructed within a continuous time window. Based on different channel reconstruction criteria, the probe antenna weight and channel reconstruction accuracy error under different antenna pointing directions of the device under test at different times are calculated. By jointly optimizing the antenna pointing of the device under test and the antenna weight of the probe, a reconstruction scheme with the lowest cumulative reconstruction error within a continuous time window is obtained. The reconstruction of the dynamic non-stationary space-time channel is achieved by adjusting the antenna pointing of the device under test and the antenna weight of the probe in real time.

2. The dynamic non-stationary space-time channel reconstruction method for air interface performance testing according to claim 1, characterized in that, Establishing the target non-stationary channel model to be reconstructed includes: Based on the test scenario, generate a virtual movement trajectory of the device under test relative to the base station; Based on the virtual movement trajectory of the device under test, large-scale fading parameters of path loss, molecular absorption effect and shadow fading are generated. Based on the changing dynamic characteristics of sub-paths or clusters in the virtual moving trajectory, the changes in the number of sub-paths and clusters, as well as the changes in small-scale fading parameters including cluster delay, Doppler shift, and angle spread, are modeled using the stochastic process method to obtain the dynamic non-stationary space-time channel model of the target to be reconstructed.

3. The dynamic non-stationary space-time channel reconstruction method for air interface performance testing according to claim 1, characterized in that, The target non-stationary channel model to be reconstructed consists of multiple paths or clusters of paths, and the impulse response... Represented as: ……（1）； in, For time, For AoA, For cluster delay, The channel impulse response of the Loss path, The impulse response is for a non-line-of-sight channel. Rice factor; For clustered indexes, in Total time indivual; For the first Sub-path indexes in each cluster, total indivual, To improve reconstruction accuracy, , , These represent the Loss path, the nth cluster, and its nth cluster. The time delay of each sub-path; Different reconstruction target parameters are selected for different channel characteristics, and the reconstruction accuracy of the channel is measured by the Euclidean distance between the target and the statistical parameters of the reconstruction channel. For reconstruction accuracy at a single moment The optimization problem is expressed as: ……（2）； in, To represent the spatial, temporal, and frequency correlations and electric field strength of the target channel selected based on different channel reconstruction criteria, the time-varying parameters or statistical characteristics of the channel are described. In a multi-probe anechoic chamber, a time-varying weight vector was added to the probe antenna. Thus, the corresponding parameters or statistical characteristics of the reconstructed channel synthesized within the quiet zone are obtained within a continuous time window. Inside, Represented as: ……（3）； in, The antenna spacing of the device under test. The spatial angle of the antenna of the device under test. The spatial angle between the probe antenna and the device under test is determined by controlling the probe antenna weight vector. Able to obtain the desired reconstructed beam, The transfer matrix of the probe antenna in the quiet zone is expressed as: ……（4）； ……（5）； in, For wavelength, and Antenna pointing of the device under test and the The direction of each reference antenna The direction vector in the global coordinate system. This is the Doppler frequency shift.

4. The dynamic non-stationary space-time channel reconstruction method for air interface performance testing according to claim 2, characterized in that, The virtual motion trajectory includes the obstacle location, the orientation of the device under test, the direction of movement, and the speed of movement. Based on the obstacle location, the orientation of the device under test, the direction of movement, and the speed of movement, the large-scale fading parameters and small-scale fading parameters of the channel required for reconstruction are extracted.

5. The dynamic non-stationary space-time channel reconstruction method for air interface performance testing according to claim 1, characterized in that, When adjusting the antenna pointing of the device under test in real time, the device under test should face the center of the fan-shaped probe wall, where the fan-shaped probe wall is equipped with... OK Lieutenant General One probe antenna, and the probe antenna in , The structures are evenly spaced in all directions, covering 180° horizontally and [missing information] vertically. The distance between the probe wall and the device under test is .

6. A dynamic non-stationary space-time channel reconstruction system for air interface performance testing using the reconstruction method of any one of claims 1-5, characterized in that, include: The joint optimization module calculates the channel reconstruction error through the central processing unit based on different channel reconstruction criteria, and performs joint optimization of probe weighting and antenna pointing of the device under test. The global control module is used to control the base station simulator to generate the required source data, provide the channel simulator with the required channel files and probe weights, and control the controllable turntable to adjust the antenna pointing of the device under test. A controllable turntable is used for real-time adjustment of the antenna pointing of the device under test; Fan-shaped probe wall, used to deploy probe antennas.

7. A dynamic non-stationary space-time channel reconstruction device for air interface performance testing, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the reconfiguration method as described in any one of claims 1-5.

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