A probe selection method, device, equipment and medium for air interface test

Abstract

The present disclosure provides a probe selection method, device, equipment and medium for air interface test, by acquiring preset information in a multi-probe darkroom, the multiple probes in the multi-probe darkroom are divided into multiple rectangular probe groups; acquiring the position information of the multiple probes, acquiring the weight of the multiple probes based on the position information of the multiple probes, acquiring the sum of the weights of the probes of the multiple rectangular probe groups based on the weight of the multiple probes; selecting a target rectangular probe group in the multiple rectangular probe groups based on the number of ports of the channel simulator and the sum of the weights of the probes of the multiple rectangular probe groups; selecting the probe with the maximum power weight in each target rectangular probe group as the initial probe, grouping the initial probes into an initial probe set, updating the initial probes in the initial probe set, and determining the target probes that need to be activated. The present disclosure can realize high-precision simulation of the spatial distribution characteristics of the target channel, and reduce the hardware complexity of the switch circuit and the calculation complexity of the probe selection algorithm.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication testing, and in particular to a probe selection method and device for air interface testing, equipment and a medium. BACKGROUND

[0002] For a new generation of mobile communication equipment, performance testing is an essential part of the product development and production process. There are two common performance testing methods: radio frequency transmission testing, which tests by connecting a channel simulator to the antenna under test through a wired cable; and over-the-air (OTA) testing, which tests by transmitting / receiving transmission signals simulated by a channel simulator through the air interface. Due to the high integration of new generation wireless communication antenna systems and new testing requirements for technologies such as massive multiple-input multiple-output (Massive MIMO) and beamforming, OTA testing has gradually replaced the traditional radio frequency transmission testing method and become the only viable solution for performance testing of new generation mobile communication equipment, because it can controllably and repeatedly simulate a test scene close to a real channel propagation environment in a test area to test the entire device. There are three main OTA testing methods: reverberation chamber (RC) method, radiated two-stage (RTS) method, and multi-probe anechoic chamber (MPAC) method.

[0003] The Multi-Probe Anechoic Chamber (MPAC) method reconstructs the spatial distribution characteristics of a target channel within a test area using a channel simulator and probes distributed within the chamber via wired cables. It is currently the most widely accepted OTA testing method in the industry and has been standardized by the Cellular Telecommunications Industry Association (CTIA) and the 3rd Generation Partnership Project (3GPP). Due to the high sparsity and directionality of channels in next-generation and future communication bands such as millimeter waves, OTA testing for next-generation wireless communications typically uses a 3D sector MPAC (Sectored Multi-Probe Anechoic Chamber, SMPAC) setup. In this setup, numerous probe antennas are located on a panel covering an angular sector, with each antenna approximately equidistant from the center of the test area and spaced at certain angles. The anechoic chamber primarily shields external signal sources and prevents unwanted reflections. The test area is located at one end of the anechoic chamber, and the device under test (DUT) is located at the center of the test area. The channel simulator generates a fading channel matrix, which is radiated by the active probes at different positions on the probe panel, thereby simulating the spatial distribution characteristics of the target channel in the test area where the device under test is located.

[0004] However, regarding probe selection algorithms, on the one hand, the existing Multishot algorithm, due to its unidirectional search, can further improve accuracy, especially in the millimeter-wave band. To meet the higher channel reconstruction accuracy requirements of Massive MIMO devices compared to MIMO devices, more hardware costs are needed. On the other hand, the Multishot algorithm requires numerous iterations, resulting in high computational complexity. Especially when simulating dynamic channels, the probe selection algorithm needs to be run multiple times to switch the spatial distribution of the simulated channel, leading to significant time costs. In terms of switch matrix design, using a completely free switching circuit to select and switch the active probe position is problematic. Firstly, the expanded search range further increases the computational complexity of the probe selection algorithm, leading to substantial computational costs. Secondly, the complexity of the switching circuit is difficult to achieve, and it also results in reduced switching isolation and increased insertion loss. Summary of the Invention

[0005] Therefore, it is necessary to provide a probe selection method, apparatus, equipment, and medium for air interface testing to address the aforementioned technical problems.

[0006] Firstly, this application provides a probe selection method for over-the-air testing, the method comprising:

[0007] Acquire preset information in a multi-probe anechoic chamber, including: the maximum azimuth angle spread of all clusters of all channels, the maximum pitch angle spread of all clusters of all channels, and the angle interval of the probe walls;

[0008] Based on the preset information, the multiple probes in the multi-probe anechoic chamber are divided into multiple rectangular probe groups;

[0009] Obtain the position information of multiple probes, obtain the weights of multiple probes based on the position information of multiple probes, and obtain the sum of the weights of multiple rectangular probe groups based on the weights of multiple probes;

[0010] Based on the number of ports in the channel simulator and the sum of the weights of the probes in multiple rectangular probe groups, several rectangular probe groups are selected as the target rectangular probe groups.

[0011] The probe with the highest power weight in each target rectangular probe group is taken as the initial probe. The initial probes are then grouped into an initial probe set, and the initial probes in the initial probe set are updated to determine the target probes that need to be activated.

[0012] Secondly, this application provides a probe selection device for over-the-air testing, the device comprising:

[0013] The first acquisition module is used to acquire preset information in the multi-probe anechoic chamber, wherein the preset information includes: the maximum azimuth angle spread of all clusters of all channels, the maximum pitch angle spread of all clusters of all channels, and the angle interval of the probe wall;

[0014] The grouping module is used to divide the multiple probes in the multi-probe anechoic chamber into multiple rectangular probe groups based on the preset information.

[0015] The second acquisition module is used to acquire the position information of the multiple probes, acquire the weight of the multiple probes based on the position information of the multiple probes, and acquire the sum of the weights of the probes in the multiple rectangular probe groups based on the weights of the multiple probes.

[0016] The update module is used to select several rectangular probe groups as target rectangular probe groups based on the number of ports of the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups; to select the probe with the largest power weight in each target rectangular probe group as the initial probe, to form an initial probe set, and to update the initial probes in the initial probe set, thereby determining the target probes that need to be activated.

[0017] Thirdly, this application provides an electronic device, including a processor; and a memory storing a program; wherein the program includes instructions that, when executed by the processor, cause the processor to perform the method.

[0018] Fourthly, this application provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method described thereon.

[0019] The aforementioned probe selection method, apparatus, equipment, and medium for over-the-air testing involves acquiring preset information in a multi-probe anechoic chamber. This preset information includes: the maximum azimuth angle spread of all clusters across all channels, the maximum elevation angle spread of all clusters across all channels, and the angle spacing of the probe walls. Based on this preset information, multiple probes in the multi-probe anechoic chamber are divided into multiple rectangular probe groups. The position information of the multiple probes is acquired, and the weights of the multiple probes are obtained based on their position information. The sum of the weights of the probes in the multiple rectangular probe groups is then obtained based on their weights. Based on the number of ports in the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups, several rectangular probe groups are selected as target rectangular probe groups. The probe with the highest power weight in each target rectangular probe group is selected as the initial probe. These initial probes are then grouped into an initial probe set, and the initial probes in the initial probe set are updated to determine the target probes that need to be activated. Therefore, in this embodiment, the probes are first grouped, then an initial probe set is determined, and the initial probe set is iteratively updated to finally determine the target probes to be activated by the switching circuits in the grouped switching matrix. This reduces the hardware complexity of the switching circuits and the computational complexity of the probe selection algorithm, while ensuring high-precision simulation of the spatial distribution characteristics of the target channel. Attached Figure Description

[0020] Further details, features, and advantages of this disclosure are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0021] Figure 1 A flowchart of a probe selection method for over-the-air testing according to an exemplary embodiment of the present disclosure is shown;

[0022] Figure 2 A schematic diagram of the structure of a 3D sector multi-probe anechoic chamber according to an exemplary embodiment of the present disclosure is shown;

[0023] Figure 3 A schematic diagram of the structure of a group switch matrix according to an exemplary embodiment of the present disclosure is shown;

[0024] Figure 4 A flowchart of another probe selection method for air interface testing according to an exemplary embodiment of this disclosure is shown;

[0025] Figure 5 A schematic diagram of an iterative algorithm flow according to an exemplary embodiment of the present disclosure is shown;

[0026] Figure 6 A schematic block diagram of a probe selection device for air interface testing according to an exemplary embodiment of the present disclosure is shown;

[0027] Figure 7 A structural block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure is shown. Detailed Implementation

[0028] The implementation environment involved in the probe selection method for air interface testing provided in the embodiments of this application will be briefly described below.

[0029] The probe selection method for over-the-air testing provided in this application can be executed by a computer device, which can be a terminal or a server. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, portable wearable devices, and medical electronic devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle devices, etc., and portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. The server can be a standalone server or a server cluster composed of multiple servers.

[0030] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0031] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0032] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc., used in this disclosure are only used to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0033] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0034] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0035] In one embodiment, such as Figure 1 As shown, a probe selection method for over-the-air testing is provided, applied to electronic devices. Taking the electronic device as a terminal as an example, the method includes the following steps:

[0036] Step 101: The electronic device acquires preset information in the multi-probe anechoic chamber.

[0037] like Figure 2 As shown, Figure 2 This is a schematic diagram of a 3D sector multi-probe anechoic chamber. Numerous probe antennas are located on a panel covering an angular sector. Each probe antenna is approximately equidistant from the center of the test area and has a certain angular spacing. The anechoic chamber primarily shields external signal sources and prevents unnecessary reflections. The test area is located at one end of the anechoic chamber, and the device under test (DUT) is located at the center of the test area. A channel simulator generates a fading channel matrix with K ports. Signals are radiated by activation probes at different positions on the probe panel, thus simulating the spatial distribution characteristics of the target channel in the test area where the DUT is located. The anechoic chamber contains P probes. The input ports of multiple probes in the multi-probe anechoic chamber are connected to the output ports of a group switch matrix. The group switch matrix includes multiple single-pole multi-throw electromechanical switches. The group switch matrix is ​​used to activate multiple probes in the multi-probe anechoic chamber. The input ports of the group switch matrix are connected to the output ports of the channel simulator, which generates the fading channel matrix. The input ports of the channel simulator are connected to the output ports of a terminal simulator, which simulates signals and injects the signals into the input ports of the channel simulator.

[0038] According to the testing requirements, the electronic equipment acquires preset information σ in the multi-probe anechoic chamber. phi,max σ theta,max and θ s , σ phi,max and σ theta,max θ represents the maximum azimuth angle spread for all clusters across all channels and the maximum pitch angle spread for all clusters across all channels, respectively. s The angle interval of the probe wall. Preset information σ phi,max σ theta,max and θ s Used to group multiple probes in a multi-probe anechoic chamber.

[0039] Step 102: The electronic device divides the multiple probes in the multi-probe anechoic chamber into multiple rectangular probe groups based on preset information.

[0040] The electronic equipment groups the entire wall of probes into There are three rectangular probe groups, where P is the total number of probes on the probe wall. The input of each probe within a rectangular probe group is connected to the output of a single-pole Q-throw electromechanical switch in a grouped switch matrix, where Q is the number of probes in the rectangular probe group. To balance the complexity and accuracy of the corresponding probe selection algorithm, a [specific algorithm is defined here]. The input port of each single-pole Q-throw electromechanical switch is connected to the output port of the channel simulator. Therefore, at most one probe can be activated within each rectangular probe group. It should be noted that K represents the number of ports on the channel simulator, determined by actual cost and accuracy requirements. For example, when Q=4 and K=4, Figure 3 An exemplary schematic diagram of the structure of a group switch matrix is ​​shown, such as... Figure 3 As shown, the P probes are divided into several rectangular probe groups, with 4 probes in each group. The channel simulator has 4 ports, which correspond to the switching circuits 1, 2, 3 and 4 of the single-pole 4-throw electromechanical switch. Switching circuits 1, 2, 3 and 4 control the probes in the 4 rectangular probe groups 1, 2, 3 and 4 respectively. Only one probe can be activated in each rectangular probe group.

[0041] Step 103: The electronic device acquires the position information of multiple probes, acquires the weights of multiple probes based on the position information of multiple probes, and acquires the sum of the weights of multiple rectangular probe groups based on the weights of multiple probes.

[0042] The spatial characteristics of the channel are represented by the power angular spectrum (PAS)P(Ω) satisfying ∫P(Ω)dΩ=1. Ω is a three-dimensional spatial angle, consisting of the elevation angle θ and the azimuth angle. constitute.

[0043] Using the classic Bartlett beamformer, the Bartlett beamforming power spectrum of the target channel is calculated as follows:

[0044] B(Ω)=a H (Ω)Ra(Ω)

[0045] in,(·) H Represents the Hermitian transpose; R is the spatial correlation matrix of the target channel, given by R = ∫a(Ω)P(Ω)a H Calculation of (Ω)dΩ. a(Ω) is the normalized direction vector from the measured device to the spatial angular direction Ω. (From...) We obtain this formula. Represents the unit vector along the spatial angular direction Ω. Let m represent the position vector of the m-th (1≤m≤M) antenna element, where M is the number of array elements of the antenna array of the device under test, and (·) represents the dot product.

[0046] Using the prefading synthesis method to simulate the spatial characteristics of the channel, the simulated Bartlett beamforming power spectrum is calculated as follows:

[0047]

[0048] in For the selected K probes to simulate the spatial correlation moments of the channel, by Calculate. Where a(Ω) k Let x be the position of the device under test to the k-th probe. k The spatial angle Ω corresponding to (1≤k≤K) k The normalized direction vector on. (From) Calculate. In this formula, d k,m Let PL be the distance between the k-th probe and the m-th antenna of the device under test. PL() represents the path loss.

[0049] To select K probes with specific angular positions Ω1,...,Ω from P (P>>K) probes on a probe wall using a switching matrix, the following method is used: K probes x1,...,x K Connect to the channel simulator and assign appropriate power weights so that the Bartlett beamforming power spectrum B of the target channel is similar to the simulated Bartlett beamforming power spectrum. To minimize the error, the objective function is defined as follows:

[0050]

[0051] Where X = [x1,...,x] K [For the selected K probes x1,...,x] K Position vector, x k Let G be the position of the selected k-th probe (1≤k≤K). G=[g1,...,g K [ ] is the power weight vector of the K probes. 0≤g k ≤1, g k For the selected k-th probe x k The power weights (1≤k≤K) are determined. The power weight vector G of the probe is obtained by optimizing X using a convex optimization algorithm.

[0052] Specifically, the electronic device first acquires the position information of P probes on the probe wall, that is, it acquires X = [x1,...,x...]. P Through the optimization of the above convex optimization algorithm, the power weight vector G = [g1,...,g] of the P probes is calculated. P Then, based on G = [g1,...,g], P The sum of the probe weights of multiple rectangular probe groups is calculated.

[0053] Step 104: The electronic device selects several rectangular probe groups as target rectangular probe groups based on the number of ports of the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups.

[0054] The electronic device selects the K rectangular probe groups with the largest sum of weights as the target rectangular probe groups based on the sum of the weights of the probes in multiple rectangular probe groups, and numbers the selected target rectangular probe groups according to their weight sums: S1,...,S... K ,S k This indicates the target rectangular probe group numbered k (1≤k≤K).

[0055] Specifically, g k,q Represents the rectangular probe group S with target number k. k The power weight of the q-th probe (1≤q≤Q) within the target rectangular probe group. Q is the number of probes in the target rectangular probe group.

[0056] Step 105: The electronic device takes the probe with the largest power weight in each target rectangular probe group as the initial probe, forms an initial probe set from the initial probes, updates the initial probes in the initial probe set, and determines the target probes that need to be activated.

[0057] To accelerate convergence and stabilize the algorithm, the probe with the largest weight in each group of target rectangular probes is selected as the initial probe. These initial probes are then grouped into an initial probe set, and the position vector of this set of K initial probes is used as the initial solution X. 0 Determine the upper limit of the number of iterations N and the initial solution. Indicates the k-th target rectangular probe group S k The initial probe selected in [the context] The electronic device then updates the initial probes in the initial probe set to determine the target probe that needs to be activated.

[0058] The aforementioned probe selection method, apparatus, equipment, and medium for over-the-air testing involves acquiring preset information in a multi-probe anechoic chamber. This preset information includes: the maximum azimuth angle spread of all clusters across all channels, the maximum elevation angle spread of all clusters across all channels, and the angle spacing of the probe walls. Based on this preset information, multiple probes in the multi-probe anechoic chamber are divided into multiple rectangular probe groups. The position information of the multiple probes is acquired, and the weights of the multiple probes are obtained based on their position information. The sum of the weights of the probes in the multiple rectangular probe groups is then obtained based on their weights. Based on the number of ports in the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups, several rectangular probe groups are selected as target rectangular probe groups. The probe with the highest power weight in each target rectangular probe group is selected as the initial probe. These initial probes are then grouped into an initial probe set, and the initial probes in the initial probe set are updated to determine the target probes that need to be activated. Therefore, in this embodiment, the probes are first grouped, then an initial probe set is determined, and the initial probe set is iteratively updated to finally determine the target probes to be activated by the switching circuits in the grouped switching matrix. This reduces the hardware complexity of the switching circuits and the computational complexity of the probe selection algorithm, while ensuring high-precision simulation of the spatial distribution characteristics of the target channel.

[0059] In one embodiment, such as Figure 4 As shown, this embodiment relates to updating the initial probes in the initial probe set of an electronic device and determining the target probes that need to be activated, including the following steps:

[0060] Step 401: The electronic device fixes the initial probes in the initial probe set, which are in other target rectangular probe groups outside the target rectangular probe group where the initial probe to be updated is located, and searches within the target rectangular probe group that needs to be updated, selecting the probe that minimizes the objective function F to replace the original probe.

[0061] Step 402: The electronic device updates the other probes in the initial probe set in descending order of the sum of probe weights in the target rectangular probe group corresponding to the initial probe in the initial probe set. The updated probe set is used as the new initial probe set to enter the next iteration until the error threshold or the maximum number of iterations is reached, and the probes in the current initial probe set are determined as the target probes that need to be activated.

[0062] Specifically, such as Figure 5 As shown, Figure 5 An exemplary schematic diagram of an iterative algorithm flow is shown, and the specific iterative algorithm flow is as follows:

[0063] The electronic device first acquires the position information of P probes on the probe wall, that is, it acquires X = [x1,...,x...]. PThrough the above convex optimization algorithm, the power weight vector G = [g1,...,g] of the P probes is calculated. P Then, based on G = [g1,...,g], P Calculate the sum of the weights of the probes in multiple rectangular probe groups.

[0064] The electronic device selects the K rectangular probe groups with the largest sum of weights as the target rectangular probe groups based on the sum of the weights of the probes in multiple rectangular probe groups. The selected target rectangular probe groups are then numbered in descending order of their weight sums: S1,...,S... K ,S k This indicates the rectangular probe group numbered k (1≤k≤K).

[0065] Specifically, g k,q Represents the rectangular probe group S with target number k. k The power weight of the q-th probe (1≤q≤Q) within the target rectangular probe group. Q is the number of probes in the target rectangular probe group.

[0066] To accelerate convergence and stabilize the algorithm, the probe with the largest weight in each group of target rectangular probes is selected as the initial probe. These initial probes are then grouped into an initial probe set, and the position vector of this set of K initial probes is used as the initial solution X. 0 Determine the upper limit of the number of iterations N and the initial solution. Indicates the k-th target rectangular probe group S k The initial probe selected in [the context]

[0067] The initial solution for the i-th (1≤i≤N) iteration is obtained by dividing the target rectangular probe group numbers in ascending order. In Update This is the position of the k-th initial probe to be updated in the (i-1)-th iteration (when i=1, it is...). When updating, fix the already selected K-1 initial probes, and in the current... Target rectangular probe group S k The search is performed within the range of the initial probe position, selecting the option that makes the objective function... Minimum initial probe position That is, selecting the probe position that minimizes the error between the target PAS and the simulated PAS as... The process continues until the position of the Kth probe is updated, at which point the next iteration begins.

[0068] Specifically, These are the positions of the first k-1 initial probes that have been updated during the i-th iteration. This represents the initial probe positions after the k-th probe, which has not yet been updated in the i-th iteration. A new solution is obtained after updating all probes within the target rectangular probe group. If we proceed to the next iteration, X i This will be used as the initial solution for the (i+1)th iteration. Otherwise, X i The K activation probes X = [x1,...,x] to be activated as the final switch K Repeat this step until the error threshold is reached or i reaches the iteration limit N.

[0069] In one embodiment, the inventors used the probe selection method of the present invention for air interface testing and the traditional probe selection method to conduct a 3D sector multi-probe anechoic chamber test experiment on a device under test.

[0070] Test experiments demonstrate that, taking eight probes selected from a probe wall with a coverage horizontal angle of 180°, an elevation angle of 60°, and a probe angle interval of 5° as an example, the device under test is an 8*8 antenna array, the target channels are CDL-B and CDL-E channels, the carrier frequency is 28GHz, and the traditional method using completely free switching circuits and multishot algorithms is employed. The accuracy of the simulated channel is evaluated using the Angular Power Spectrum Similarity Percentage (PSP), a channel reconstruction accuracy evaluation factor for the FR2 (millimeter wave) band specified in the 3GPP 38.827 standard.

[0071]

[0072] B(Ω) and Bartlett beamforming power spectra (B(Ω)) for the target channel and analog channel, respectively. The calculation method is as described in the specific embodiment). Ω is a three-dimensional spatial angle.

[0073] The running time and channel simulation accuracy of the traditional probe selection method and the probe selection method for air interface testing designed in this invention are shown in the table below:

[0074]

[0075] In one embodiment, such as Figure 6 As shown, a probe selection device for air interface testing is provided, the device comprising:

[0076] The first acquisition module 601 is used to acquire preset information in the multi-probe anechoic chamber, wherein the preset information includes: the maximum azimuth angle spread of all clusters of all channels, the maximum pitch angle spread of all clusters of all channels, and the angle interval of the probe wall;

[0077] Grouping module 602 is used to divide multiple probes in the multi-probe anechoic chamber into multiple rectangular probe groups based on the preset information;

[0078] The second acquisition module 603 is used to acquire the position information of the plurality of probes, acquire the weight of the plurality of probes based on the position information of the plurality of probes, and acquire the sum of the weights of the probes in the plurality of rectangular probe groups based on the weights of the plurality of probes.

[0079] The update module 604 is used to select several rectangular probe groups as target rectangular probe groups based on the number of ports of the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups; to select the probe with the largest power weight in each target rectangular probe group as the initial probe, to form an initial probe set, and to update the initial probes in the initial probe set, thereby determining the target probes that need to be activated.

[0080] Exemplary embodiments of this disclosure also provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the electronic device to perform a method according to an embodiment of this disclosure.

[0081] Exemplary embodiments of this disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform a method according to embodiments of this disclosure.

[0082] refer to Figure 7 The present invention describes a structural block diagram of an electronic device 700 that can serve as a server or client of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0083] likeFigure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 707 into a random access memory (RAM) 703. The RAM 703 may also store various programs and data required for the operation of the device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0084] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, output unit 707, storage unit 708, and communication unit 709. Input unit 706 can be any type of device capable of inputting information to electronic device 700. Input unit 706 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of electronic device. Output unit 707 can be any type of device capable of presenting information and may include, but is not limited to, a display, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 704 may include, but is not limited to, disk and optical disk. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0085] The computing unit 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above. For example, in some embodiments, method 101 may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via ROM 702 and / or communication unit 709. In some embodiments, the computing unit 701 may be configured to perform method 101 by any other suitable means (e.g., by means of firmware).

[0086] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0087] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0088] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0089] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0090] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0091] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

[0092] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this disclosure are performed, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center integrating one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid-state drive (SSD).

[0093] Although this disclosure has been described in conjunction with specific features and embodiments, it will be apparent that various modifications and combinations can be made therein without departing from the spirit and scope of this disclosure. Accordingly, this specification and drawings are merely exemplary illustrations of the disclosure as defined by the appended claims and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this disclosure. It is obvious that those skilled in the art can make various alterations and modifications to this disclosure without departing from its spirit and scope. Thus, this disclosure is also intended to include any such modifications and modifications that fall within the scope of the claims of this disclosure and their equivalents.

Claims

1. A probe selection method for air interface testing, characterized in that, The method includes: Acquire preset information in a multi-probe anechoic chamber, wherein the preset information includes: the maximum azimuth angle spread of all clusters of all channels, the maximum pitch angle spread of all clusters of all channels, and the angle interval of the probe wall; Based on the preset information, the multiple probes in the multi-probe anechoic chamber are divided into multiple rectangular probe groups; The location information of the multiple probes is obtained, the weight of the multiple probes is obtained based on the location information of the multiple probes, and the sum of the weights of the multiple rectangular probe groups is obtained based on the weights of the multiple probes. Based on the sum of the number of ports of the channel simulator and the weights of the probes in the multiple rectangular probe groups, several rectangular probe groups are selected as target rectangular probe groups. The probe with the largest power weight in each target rectangular probe group is taken as the initial probe. The initial probes are combined into an initial probe set, and the initial probes in the initial probe set are updated to determine the target probes that need to be activated. The process of selecting the probe with the highest power weight within each target rectangular probe group as the initial probe, forming an initial probe set from these initial probes, updating the initial probes in the initial probe set, and determining the target probes to be activated includes: Fix the initial probes in other target rectangular probe groups outside the target rectangular probe group where the initial probe to be updated is located in the initial probe set, and search within the target rectangular probe group that needs to be updated, and select the probe that minimizes the objective function F to replace the original probe. Based on the sum of probe weights in the target rectangular probe group corresponding to the initial probe in the initial probe set, the other probes in the initial probe set are updated in descending order. The updated probe set is used as the new initial probe set for the next iteration until the error threshold or the maximum number of iterations is reached, and the probes in the current initial probe set are determined as the target probes to be activated. The input ports of multiple probes in the multi-probe anechoic chamber are connected to the output ports of a group switch matrix. The group switch matrix includes multiple single-pole multi-throw electromechanical switches, and the group switch matrix is ​​used to activate multiple probes in the multi-probe anechoic chamber.

2. The method according to claim 1, characterized in that, The input port of the group switch matrix is ​​connected to the output port of the channel simulator, which is used to generate the fading channel matrix.

3. The method according to claim 2, characterized in that, The input port of the channel simulator is connected to the output port of the terminal simulator. The terminal simulator is used to simulate signals and inject the signals into the input port of the channel simulator.

4. The method according to claim 1, characterized in that, Based on functions The process involves confirming whether an error threshold has been reached. If the value of the function is greater than the threshold, the process continues to the next iteration. If the value of the function is less than the threshold, the probes in the current initial probe set are determined to be the target probes to be activated. The function... middle, Represents the power spectrum of Bartlett beamforming. The function represents the simulated Bartlett beamforming power spectrum. Used to represent the similarity between the Bartlett beamforming power spectrum and the simulated Bartlett beamforming power spectrum.

5. A switch matrix and corresponding probe selection device for over-the-air testing, characterized in that, The device includes: The first acquisition module is used to acquire preset information in the multi-probe anechoic chamber, wherein the preset information includes: the maximum azimuth angle spread of all clusters of all channels, the maximum pitch angle spread of all clusters of all channels, and the angle interval of the probe wall; The grouping module is used to divide the multiple probes in the multi-probe anechoic chamber into multiple rectangular probe groups based on the preset information. The second acquisition module is used to acquire the position information of the multiple probes, acquire the weight of the multiple probes based on the position information of the multiple probes, and acquire the sum of the weights of the probes in the multiple rectangular probe groups based on the weights of the multiple probes. The update module is used to select several rectangular probe groups as target rectangular probe groups based on the number of ports of the channel simulator and the sum of the weights of the probes in the multiple rectangular probe groups; to select the probe with the largest power weight in each target rectangular probe group as the initial probe, to form an initial probe set, and to update the initial probes in the initial probe set to determine the target probes that need to be activated. The update module is further configured to: Fix the initial probes in other target rectangular probe groups outside the target rectangular probe group where the initial probe to be updated is located in the initial probe set, and search within the target rectangular probe group that needs to be updated, and select the probe that minimizes the objective function F to replace the original probe. Based on the sum of probe weights in the target rectangular probe group corresponding to the initial probe in the initial probe set, the other probes in the initial probe set are updated in descending order. The updated probe set is used as the new initial probe set for the next iteration until the error threshold or the maximum number of iterations is reached, and the probes in the current initial probe set are determined as the target probes to be activated. The input ports of multiple probes in the multi-probe anechoic chamber are connected to the output ports of a group switch matrix. The group switch matrix includes multiple single-pole multi-throw electromechanical switches, and the group switch matrix is ​​used to activate multiple probes in the multi-probe anechoic chamber.

6. An electronic device, characterized in that, include: processor; as well as, Memory for stored programs; The program includes instructions that, when executed by the processor, cause the processor to perform the method according to any one of claims 1-4.

7. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the method according to any one of claims 1-4.

Images