Probe position selection method and system

Abstract

The invention discloses a probe position selection method and system, and solves the problem in the prior art that the precision is low when signal spatial characteristics are reconstructed through a probe antenna. The probe position selection method comprises the following steps: determining a target channel model, and extracting target channel parameters; the target channel parameters comprise time, frequency and space parameters; determining a reconstruction criterion, and calculating a target reconstruction parameter according to the target channel parameter; determining at least one coordinate as a probe position; calculating the weight of the probe at each position according to the target reconstruction parameter, and determining a reconstruction error; the reconstruction error is a difference value between a target reconstruction parameter and a target channel parameter; and iterating the probe position, and determining the probe position corresponding to the lowest reconstruction error. According to the probe position selection algorithm provided by the invention, the required calculation amount can be reduced, and the spatial feature precision of the probe antenna reconstruction signal can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a probe position selection method and system. Background Art

[0002] With the rapid development of communication technology, terminal testing technology has also been updated accordingly. Different from the conduction test method that directly transmits the test signal to the RF port through a cable, with the popularization of the fifth generation (5th Generation, 5G) communication system and the application of multiple-input multiple-output (Multiple-Input Multiple-Output, MIMO) technology, the OTA test method that sends the test signal to the device under test through the air interface (Over-the-Air, OTA) has become the only feasible test method for large-scale MIMO terminals.

[0003] Existing OTA test methods include the reverberation chamber method, the radiated two-stage (RTS) method, and the multi-probe anechoic chamber (MPAC) method. Among them, the reverberation chamber method cannot accurately and controllably reconstruct the target channel model in the spatial domain according to its characteristics due to structural limitations; the RTS method cannot change the antenna pattern under test in time according to the changes in the channel to apply to subsequent tests. Therefore, the MPAC method has become a more widely applicable OTA test solution.

[0004] The core idea of ​​the MPAC method is to send signals to the device under test through multiple probe antennas located at different angles to reproduce the required channel spatial characteristics. A small number of probe antennas can be selected through algorithms such as Multishot, and the power added to each activated probe can be calculated using a convex optimization algorithm.

[0005] The Multishot algorithm first calculates the weights of all available probe antennas on the probe wall, and selects the probe with the smallest weight to discard, so that the required number of probe antennas to be activated are retained after multiple calculations. This algorithm can quickly select a small number of probe antennas with higher accuracy from a large number of antennas, but the algorithm may fall into a local optimum. Summary of the invention

[0006] The embodiments of the present application provide a probe position selection method and system, which solve the problem of low accuracy of signal spatial feature reconstruction through probe antenna in the prior art.

[0007] In a first aspect, an embodiment of the present application further provides a method for selecting a probe position, comprising the steps of:

[0008] Determine a target channel model and extract target channel parameters; the target channel parameters include time, frequency, and space parameters;

[0009] Determine a reconstruction criterion, and calculate a target reconstruction parameter according to a target channel parameter;

[0010] determining at least one coordinate as a probe position;

[0011] Calculating the probe weights of each position according to the target reconstruction parameters to determine the reconstruction error; the reconstruction error is the difference between the target reconstruction parameters and the target channel parameters;

[0012] The probe position is iterated to determine the probe position corresponding to the lowest reconstruction error.

[0013] Preferably, obtaining the coordinates as the probe position specifically comprises the steps of:

[0014] determining statistical properties of target reconstruction parameters;

[0015] At least one coordinate is determined as the probe position according to the statistical characteristics.

[0016] Preferably, while iterating the probe positions, it also includes iterating the number of probes to increase or decrease the number of probes.

[0017] In one embodiment, the schemes that can be used as the reconstruction criteria include spatial correlation, angular power spectrum and electric field similarity.

[0018] In one embodiment, determining the probe position according to an artificial bee colony algorithm specifically comprises the steps of:

[0019] determining at least one honey source according to the target channel model;

[0020] Calculate the fitness of the probe at a nectar source based on the reconstruction error; the fitness is the influence of the probe on the reconstruction error within the nectar source range;

[0021] The probe determines whether the corresponding fitness is set at the nectar source according to a preset rule.

[0022] Furthermore, the maximum number of nectar sources and the maximum number of iterations for a single nectar source are preset;

[0023] In response to a nectar source reaching a maximum number of iterations, the nectar source is abandoned and a new nectar source is selected.

[0024] In the second aspect, the embodiment of the present application also provides a probe position selection system, comprising an anechoic chamber, a probe wall, a channel simulator, a base station simulator and a main control device. The anechoic chamber is used as a space for air interface performance testing. The probe wall is arranged in the anechoic chamber, and is used to receive the signal of the probe antenna sent by the channel simulator, and set the probe according to the optimal probe position determined by the main control device. The channel simulator is used to receive the optimal probe position and probe weight determined by the main control device, and the communication signal determined by the base station simulator, and determine that the signal of the probe antenna is transmitted to the probe wall. The base station simulator is used to simulate the communication signal generated by the transmitter. The main control device is used to implement the probe position selection method described in any one of the embodiments of the first aspect, determine the optimal probe position and probe weight to send to the channel simulator, and forward the received signal of the probe antenna sent by the channel simulator to the probe wall.

[0025] Preferably, the probe wall comprises a vertical slide rail, a horizontal slide rail and a probe antenna. A plurality of vertical slide rails are respectively arranged on a horizontal slide rail. The vertical slide rail slides horizontally on the horizontal slide rail. The horizontal slide rail slides vertically on the vertical slide rail. Several probe antennas slide on the vertical slide rail or the horizontal slide rail and can be used to switch between different slide rails. The horizontal slide rail and the vertical slide rail are arc-shaped structures, and the probe antenna is at the same distance from the device to be tested at any position of any slide rail.

[0026] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the first aspect.

[0027] In a fourth aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in any embodiment of the first aspect is implemented.

[0028] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0029] The probe position selection algorithm proposed in this application can reduce the required amount of calculation and effectively improve the spatial feature accuracy of the probe antenna reconstructed signal. In conjunction with the high-degree-of-freedom non-grid probe wall of the system described in this application, it is only necessary to configure the activated number of probe antennas, and the precise change of the probe position can be achieved through the mechanical structure, which can effectively improve the channel reconstruction accuracy, thereby achieving high-precision OTA performance testing, that is, reducing reconstruction errors and saving costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0031] Figure 1 This is a structural diagram of a multi-probe darkroom in the prior art;

[0032] Figure 2-1 A flow chart of a probe position selection method provided in an embodiment of the present application;

[0033] Figure 2-2 A flow chart of another probe position selection method provided in an embodiment of the present application;

[0034] Figure 3 A flow chart of a third probe position selection method provided in an embodiment of the present application;

[0035] Figure 4 A flow chart of calculating the optimal probe position using the artificial bee colony algorithm provided in an embodiment of the present application;

[0036] Figure 5 A structural diagram of a probe position selection system provided in an embodiment of the present application;

[0037] Figure 6 A diagram of the structure of the probe wall provided in the embodiment of the present application;

[0038] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0039] Figure 8 It is the heat map of the angular power spectrum. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0041] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0042] Figure 2-1 A flow chart of a probe position selection method provided in an embodiment of the present application includes steps: 110 to 150.

[0043] Step 110: determine the target channel model and extract target channel parameters; the target channel parameters include time, frequency, and space parameters;

[0044] Step 120, determining a reconstruction criterion, and calculating a target reconstruction parameter according to a target channel parameter;

[0045] According to the target channel parameters, under the selected reconstruction criterion, the target reconstruction parameter ε is calculated.

[0046] The dynamic space-time non-stationary channel to be reconstructed (i.e., the target channel) is composed of multiple paths or clusters of paths. According to the target channel characteristics that need to be prioritized in different test scenarios, different reconstruction target parameters Α can be selected, and the target channel characteristics ε(Α) and the reconstructed channel characteristics ε(Α) can be calculated under specific reconstruction criteria. The reconstruction accuracy of the channel is measured by the Euclidean distance of the statistical parameters between the target and the reconstructed channel. It can be expressed as:

[0047]

[0048] Step 130, determining at least one coordinate as a probe position;

[0049] The coordinates can be determined as the probe position by manually selecting the coordinates as the probe position in response to GUI instructions, or by determining the statistical characteristics of the target reconstruction parameters. Since the coordinates determined based on the statistical characteristics of the target reconstruction parameters have a smaller reconstruction error, it is preferred to determine the coordinates based on the statistical characteristics of the target reconstruction parameters.

[0050] Preferably, in step 130, the coordinates are obtained as the probe position, such as Figure 2-2 As shown, the specific steps include:

[0051] Step 130-1, determining statistical characteristics of target reconstruction parameters;

[0052] Step 130 - 2 : Determine at least one coordinate as a probe position according to the statistical characteristics.

[0053] For example, according to the statistical characteristics of the target reconstruction parameter ε, the initial coordinates of the activated K probes are determined by a sparse sampling method:

[0054] Φ int ={Φ1,...,Φ K} Formula 2

[0055] Step 140, calculating the probe weights of each position according to the target reconstruction parameters, and determining the reconstruction error; the reconstruction error is the difference between the target reconstruction parameters and the target channel parameters;

[0056] For example, the initial probe positions {Φ1, ..., Φ K} probe weight ω={ω1,...,ω K}, and obtain the reconstruction error D0 at this time;

[0057] For example, for a group of K activatable probe antennas, the coordinates Φ={Φ1,...,Φ K The optimization problem of} can be expressed as:

[0058]

[0059] Among them, Φ i is the coordinate of the i-th activated probe antenna.

[0060] Related to ω, ω under different target channels Ω is determined by Φ and ε according to the following optimization problem under the selected reconstruction criterion:

[0061]

[0062] By calculating the power on the probe, the weight of the probe is determined.

[0063] Taking the Prefaded Signal Synthesis (PFS) method as an example, the above calculation process is specifically explained, and the specific application process and optimization problem solving method of the method proposed in this patent are given.

[0064] In one embodiment, the schemes that can be used as the reconstruction criteria include spatial correlation, angular power spectrum and electric field similarity.

[0065] When spatial correlation ρ is used as the reconstruction criterion, the optimization problem of this method can be expressed as:

[0066]

[0067] Where, ρ(Ω)=[ρ q (Ω)]∈C Q×1 and is the spatial correlation vector of the target channel and the reconstructed channel at the Q sampling antenna pairs, ρ q (Ω) and is the spatial correlation vector between the target channel and the reconstructed channel of the qth sampling antenna pair. It should also be noted that the power of all probes should be positive and limited to +1.

[0068] For example, the spatial correlation of the target channel is calculated by the angular power spectrum. q (Ω) can be expressed as:

[0069]

[0070] Where Ψ is the solid angle in the angular direction, λ is the wavelength, and e(·) represents a unit vector. q is the position vector of the qth spatial sampling antenna pair, where each antenna in the antenna pair is placed in opposite directions relative to the center of the test area. In the PFS method, Ω(Ψ) is the Power Angular Spectrum (PAS), which satisfies

[0071] Similarly, the spatial correlation of the reconstructed channel It can be expressed as:

[0072]

[0073] where ω k is the power weight of the kth probe antenna.

[0074] Step 150: Iterate the probe position to determine the probe position corresponding to the lowest reconstruction error.

[0075] Preferably, while iterating the probe positions, it also includes iterating the number of probes to increase or decrease the number of probes.

[0076] Figure 3 The third probe position selection method provided in the embodiment of the present application includes the following steps:

[0077] Step 210: determine the target channel model and extract target channel parameters; the target channel parameters include time, frequency, and space parameters;

[0078] Step 220, determining a reconstruction criterion, and calculating a target reconstruction parameter according to a target channel parameter; the reconstruction error is the difference between the target reconstruction parameter and the target channel parameter;

[0079] Step 230, determining at least one coordinate as a probe position;

[0080] In one embodiment, in step 230, the probe position is determined according to an artificial bee colony algorithm, which specifically includes the steps of:

[0081] Step 230-1, determining at least one honey source according to the target channel model;

[0082] For example, according to the actual form of Ω(Ψ), sparse sampling is performed on it, that is, the positions of the first group of nectar sources are determined according to Formula 2.

[0083] The actual form refers to the Figure 8 As shown, Figure 8It is a heat map of the angular power spectrum, that is, the distribution map of the power of the signal in the channel at different angles of the wave in space. In the figure, the center of the dark color group is red, gradually turning yellow towards the edge, and the periphery is cold color, such as blue or cyan. Activated probes should be distributed in dark places, and activated probes are more likely to appear in the red at the center of each color group. Therefore, the location of the first group of honey sources can be determined according to its color distribution.

[0084] It should be noted that a group of nectar sources can include one or more probes.

[0085] For example, the initial nectar source location can be determined based on the characteristics of PAS, such as the PAS angle of arrival (AoA) The coordinates of are set to the first group of honey sources, or obtained according to the following formula:

[0086]

[0087] The location of the honey source and the i-th honey source setting at the n-th iteration can be expressed as:

[0088]

[0089] It should be noted that since the nectar source may be a range, and the coordinates of the probe can be anywhere within the range of the nectar source, for example, at the coordinates of the center point of the nectar source, or at a randomly selected position in the nectar source, rand(0.1) is added as a random number to make the position of the probe in the nectar source random.

[0090] In the process of determining the nectar source for the probe, the probe is divided into a search probe, a leading probe, and a follower probe. The search probe will first search for the existing cluster (i.e., the nectar source), and after finding the cluster to be reconstructed, it will be converted to a leading probe antenna. The follower probe antenna will find the leading probe antenna that needs help and assist it in reconstruction. When the reconstruction of a cluster has a very small impact on the reconstruction accuracy, the leading probe antenna will switch back to the search probe antenna to continue searching.

[0091] Initially, there is only a search probe antenna, which first updates the nectar source. The search probe antenna searches and updates the i-th:

[0092]

[0093] Among them, a is an accelerating random number, which is used to speed up the algorithm.

[0094] Step 230-2, calculating the fitness of the probe in a nectar source according to the reconstruction error; the fitness is the influence of the probe on the reconstruction error within the nectar source range;

[0095] When the search probe antenna completes the search, the follower probe antenna determines the leading probe antenna to follow (ie, the quality of the nectar source) according to the fitness μ, which is related to the accuracy of reconstructing a single cluster.

[0096] Step 230-3: The probe determines whether the corresponding fitness is set at the nectar source according to a preset rule.

[0097] For example, to calculate the probability based on the fitness:

[0098]

[0099] Where M is the number of nectar sources at that time. Calculate the fitness of following the probe antenna to join a certain nectar source / fitness in all nectar sources = probability. The higher the probability, the greater the probability that the remaining probes are assigned to this cluster.

[0100] Then, the following probe antenna uses the roulette wheel method to select the leading bee, that is, to generate a uniformly distributed random number γ in [0,1]. i >γ, then follow the nectar source.

[0101] Following the nectar source, these probe antennas are updated using a method similar to that described in Equation 10 or a local probe selection method. During the search process, if the nectar source X i,n After multiple iterations, the threshold n is reached lim If the effect is poor, the nectar source will be abandoned and a new nectar source will be generated.

[0102] Furthermore, the maximum number of nectar sources and the maximum number of iterations for a single nectar source are preset;

[0103] Preset the maximum number of nectar sources i max , the maximum number of iterations for a single honey source n lim , after T iterations, the optimal probe position is output. The flowchart of the above algorithm is as follows Figure 4 As shown, n is the number of iterations and T is the maximum number of iterations.

[0104] In response to a nectar source reaching a maximum number of iterations, the nectar source is abandoned and a new nectar source is selected.

[0105] Step 240, calculating the probe weights of each position according to the target reconstruction parameters, and determining the reconstruction error; the reconstruction error is the difference between the target reconstruction parameters and the target channel parameters;

[0106] Step 250: Iterate the probe position to determine the probe position corresponding to the lowest reconstruction error.

[0107] Preferably, each time the probe position is iterated, the artificial bee colony algorithm is used to determine the probe position after the iteration.

[0108] Figure 5 A structure diagram of a probe position selection system provided in an embodiment of the present application includes an anechoic chamber 310 , a probe wall 320 , a channel simulator 330 , a base station simulator 340 and a main control device 350 .

[0109] The anechoic chamber is used as a space for performing air interface performance testing.

[0110] The probe wall is arranged in the anechoic chamber and is used to receive the signal of the probe antenna sent by the channel simulator and to set the probe according to the optimal probe position determined by the main control device.

[0111] The core idea of ​​the MPAC method in the prior art is to send signals to the device under test through multiple probe antennas located at different angles, thereby reproducing the required channel spatial characteristics. In order to achieve this goal, the probe wall structure of the MPAC method has evolved from the early probe ring for two-dimensional channels to the probe ball for three-dimensional channels, and finally formed a fan-shaped probe wall structure for cost considerations. Figure 1 shown.

[0112] Among them, a certain number of probes are equally spaced in the horizontal and vertical directions of the sector probe wall. Taking the commonly used configuration as an example, the sector probe wall is usually covered in the horizontal and vertical directions respectively, and the probes are gridded at intervals of unit angle, so there are multiple available probe antennas. Based on this configuration, a small number of probe antennas can be selected from them through algorithms such as Multishot, and the power added to each activated probe can be calculated using a convex optimization algorithm.

[0113] For example, the horizontal and vertical directions cover 120° and 60° respectively, and the probes are gridded at 10° unit angle intervals, so there are 13×7=91 available probe antennas.

[0114] Preferably in the present application, the probe wall includes a vertical slide rail 320 - 1 , a horizontal slide rail 320 - 2 and a probe antenna 320 - 3 .

[0115] A plurality of vertical slide rails are respectively arranged on a horizontal slide rail.

[0116] The vertical slide rail slides horizontally on the horizontal slide rail.

[0117] The horizontal slide rail slides vertically on the vertical slide rail.

[0118] A plurality of the probe antennas slide on a vertical slide rail or a horizontal slide rail, and the slide rail can be switched.

[0119] For example, it is composed of a plurality of vertical slide rails and a horizontal slide rail. The dual-polarized probe antenna is placed on the probe base and can slide on the slide rails and switch between the slide rails.

[0120] The horizontal slide rail and the vertical slide rail are arc-shaped structures, and the probe antenna is at the same distance from the device to be tested at any position of any slide rail.

[0121] For example, the horizontal slide rail and the vertical slide rail are both arc-shaped structures, so that the probe antenna thereon points to the center of the quiet zone on the opposite side of the darkroom, and the distance from the probe antenna to the center of the quiet zone is consistent.

[0122] For example, the horizontal slide rail structure includes: a track slide rail and a probe slide rail that are stacked in parallel, the track slide rail is in front, and the probe slide rail is in the back. The front and back refer to the distance from the detection area, and the one close to the detection area is regarded as the one in front.

[0123] Track slides are used to limit the vertical slides to slide horizontally on the horizontal slides.

[0124] The probe slide rail is used to limit the probe to slide from the horizontal slide rail to the vertical slide rail and adjust the angle along the vertical slide rail.

[0125] The track clamp is arranged on the track slide rail and is slidably connected with the track slide rail and the vertical slide rail respectively, so as to realize the vertical slide rail sliding on the track slide rail.

[0126] It should be noted that since the track clamp is arranged between the track slide and the probe slide, the vertical slide that is slidably connected to the track clamp is also behind the probe slide. However, in order to enable the probe to move between the vertical slide and the probe slide, the front depth distance between the vertical slide and the probe slide is less than the distance threshold.

[0127] The channel simulator is used to receive the optimal probe position and probe weight determined by the main control device and the communication signal determined by the base station simulator, and determine that the signal of the probe antenna is transmitted to the probe wall.

[0128] The base station simulator is used to simulate the communication signal generated by the transmitting end.

[0129] The main control device is used to implement the probe position selection method described in any one of the embodiments of the first aspect, determine the optimal probe position and probe weight and send them to the channel simulator, and forward the signal of the probe antenna sent by the channel simulator to the probe wall.

[0130] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] Therefore, the present application also proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present application is implemented.

[0132] Furthermore, the present application also proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present application when executing the computer program.

[0133] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0136] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory. The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0137] Figure 7A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 600 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiment of the present application. It includes: one or more processors 620; a storage device 610, which is used to store one or more programs. When the one or more programs are run by the one or more processors 620, the one or more processors 620 implement the probe position selection method provided in the embodiment of the present application, including the steps of:

[0138] Acquire a target channel model and extract target channel parameters; the target channel parameters include space parameters;

[0139] Obtaining a reconstruction criterion, and calculating a target reconstruction parameter according to a target channel parameter;

[0140] determining at least one coordinate as a probe position;

[0141] The probe weights of each position are calculated according to the target reconstruction parameters to determine the reconstruction error; the reconstruction error is

[0142] The probe position is iterated to determine the probe position corresponding to the lowest reconstruction error.

[0143] The electronic device 600 further includes an input device 630 and an output device 640; the processor 620, storage device 610, input device 630 and output device 640 in the electronic device can be connected via a bus or other means, and the figure takes the connection via a bus 650 as an example.

[0144] The storage device 610, as a computer-readable storage medium, can be used to store software programs, computer executable programs, and module units, such as program instructions corresponding to the method for determining the cloud bottom height in the embodiment of the present application. The storage device 610 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to the use of the terminal, etc. In addition, the storage device 610 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the storage device 610 may further include a memory remotely arranged relative to the processor 620, and these remote memories may be connected via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0145] The input device 630 may be used to receive input numbers, character information or voice information, and generate key signal input related to user settings and function control of the electronic device. The output device 640 may include electronic devices such as a display screen and a speaker.

[0146] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0147] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A probe position selection method, characterized in that: Includes steps: Determine a target channel model and extract target channel parameters; the target channel parameters include time, frequency, and space parameters; Determine a reconstruction criterion, and calculate a target reconstruction parameter according to a target channel parameter; determining at least one coordinate as a probe position; Calculating the probe weights of each position according to the target reconstruction parameters to determine the reconstruction error; the reconstruction error is the difference between the target reconstruction parameters and the target channel parameters; The probe position is iterated to determine the probe position corresponding to the lowest reconstruction error.

2. The probe position selection method according to claim 1, characterized in that: Get the coordinates as the probe position, including the following steps: determining statistical properties of target reconstruction parameters; At least one coordinate is determined as the probe position according to the statistical characteristics.

3. The probe position selection method according to claim 1, characterized in that: While iterating the probe positions, it also includes iterating the probe quantity, increasing or decreasing the probe quantity.

4. The probe position selection method according to claim 1, characterized in that: The probe position is determined according to the artificial bee colony algorithm, which specifically includes the following steps: determining at least one honey source according to the target channel model; Calculate the fitness of the probe at a nectar source based on the reconstruction error; the fitness is the influence of the probe on the reconstruction error within the nectar source range; The probe determines whether the corresponding fitness is set at the nectar source according to a preset rule.

5. The probe position selection method according to claim 1, characterized in that: Possible reconstruction criteria include spatial correlation, angular power spectrum and electric field similarity.

6. The probe position selection method according to claim 4, characterized in that: Preset the maximum number of nectar sources and the maximum number of iterations for a single nectar source; In response to a nectar source reaching a maximum number of iterations, the nectar source is abandoned and a new nectar source is selected.

7. A probe position selection system, characterized in that: It includes anechoic chamber, probe wall, channel simulator, base station simulator and main control equipment; The anechoic chamber is used as a space for air interface performance testing; The probe wall is arranged in the anechoic chamber and is used to receive the signal of the probe antenna sent by the channel simulator and to set the probe according to the optimal probe position determined by the main control device; The channel simulator is used to receive the optimal probe position and probe weight determined by the main control device and the communication signal determined by the base station simulator, and determine that the signal of the probe antenna is transmitted to the probe wall; The base station simulator is used to simulate the communication signal generated by the transmitting end; The main control device is used to implement the probe position selection method described in any one of claims 1-5, determine the optimal probe position and probe weight and send them to the channel simulator, and forward the signal of the probe antenna sent by the channel simulator to the probe wall.

8. The probe position selection system according to claim 7, characterized in that: The probe wall comprises a vertical slide rail, a horizontal slide rail and a probe antenna; A plurality of vertical slide rails are respectively arranged on a horizontal slide rail; The vertical slide rail slides horizontally on the horizontal slide rail; The horizontal slide rail slides vertically on the vertical slide rail; Several of the probe antennas slide on vertical or horizontal slide rails and can be switched between different slide rails; The horizontal slide rail and the vertical slide rail are arc-shaped structures, and the probe antenna is at the same distance from the device to be tested at any position of any slide rail.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

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