Antenna testing method and related apparatus

Abstract

Embodiments of the present application provide an antenna testing method and related device, which are applied to the technical field of terminals. The method comprises: obtaining a channel model, a radiation pattern of a transmitting antenna of a transmitting end, and a radiation pattern of a receiving antenna of a receiving end, the receiving antenna being a physical antenna; obtaining a throughput rate curve of the receiving end according to the channel model and the radiation pattern of each receiving antenna of the receiving antenna; and the throughput rate curve being used to represent the antenna performance of the receiving end. In this way, the radiation pattern of a real antenna is simulated, the simulated radiation pattern of the physical antenna is coupled with the channel model, and a scenario of receiving an antenna signal of the receiving end is simulated. The design evaluation of the antenna is realized in a simulated manner, the physical antenna is not needed, the performance test of the receiving end can be performed in the design stage of the antenna, the design risk is reduced, and the development speed is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of terminal, and in particular to an antenna testing method and related device. BACKGROUND

[0002] Multi-antenna technology is one of the main means to improve channel capacity. Currently, the 4th generation mobile communication technology (4G), the 5th generation mobile communication technology (5G), wireless fidelity (WiFi), Internet of Things and other communications will use multi-antenna multiple-input multiple-output (MIMO) technology to increase the communication rate.

[0003] Currently, the MIMO performance of a terminal device can be detected by over the air (OTA).

[0004] However, this method needs to test the entity of the terminal device, and the performance test time of the terminal device is late, so that the design risk of the terminal device is large. SUMMARY

[0005] Embodiments of the present application provide an antenna testing method and related device, applied to the technical field of terminal. The radiation pattern of the simulated entity antenna is coupled with the channel model to realize the scene of the antenna receiving signal of the simulated receiving end. The design evaluation of the antenna is realized by simulation, without using the entity antenna, so that the performance test of the receiving end can be performed in the design stage of the antenna, the design risk is reduced, and the development speed is improved.

[0006] In a first aspect, an embodiment of the present application provides an antenna testing method. The method comprises: obtaining a channel model, a radiation pattern of a transmitting antenna of a transmitting end, and a radiation pattern of a receiving antenna of a receiving end, the receiving antenna being an entity antenna; obtaining a throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna; and the throughput rate curve is used to represent the antenna performance of the receiving end.

[0007] In this way, the radiation pattern of the physical antenna of the receiving end can be obtained, and the radiation pattern is coupled with the channel model to realize the antenna performance evaluation of the receiving end. Without using the physical antenna, the performance of the receiving end can be tested in the design stage of the antenna, thereby reducing the design risk and improving the development speed. In addition, compared with the way of superimposing the channel capacity and the antenna capacity to evaluate the antenna performance, the way of representing the antenna performance by the throughput rate is more in line with the signal transmission change rule in the actual use scene of the receiving end.

[0008] In the embodiment of the present application, the radiation pattern of the receiving antenna can be the radiation pattern corresponding to the directional antenna. Compared with the radiation pattern of the omnidirectional antenna, the radiation pattern corresponding to the directional antenna is more in line with the antenna design of the receiving end.

[0009] In some embodiments, the electromagnetic wave energy radiated in all directions of the horizontal plane of the radiation pattern of all or part of the receiving antennas is different. In this way, the receiving antenna can be a directional antenna, which is conducive to reducing the interference between multiple receiving antennas and improving the throughput rate of the receiving end. The radiation pattern corresponding to the directional antenna is more in line with the antenna design of the receiving end.

[0010] Optionally, the throughput rate curve of the receiving end is obtained according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, including: randomly generating a plurality of sampling points corresponding to the receiving antenna; obtaining the signal-to-noise ratio corresponding to the plurality of sampling points and the throughput rate corresponding to the plurality of sampling points according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna; and obtaining the throughput rate curve according to the signal-to-noise ratio corresponding to the plurality of sampling points and the throughput rate corresponding to the plurality of sampling points, the throughput rate curve being used to represent the throughput rate of the receiving end under different signal-to-noise ratios.

[0011] In this way, the signal-to-noise ratio and the throughput rate can be calculated through the plurality of randomly selected sampling points, which is in line with the change rule of the simulated signal transmission and improves the accuracy of the throughput rate curve.

[0012] Optionally, the plurality of sampling points corresponding to the receiving antenna are randomly generated, including: randomly generating the plurality of sampling points under the same posture of the receiving end, the throughput rate curve being used to indicate the antenna performance of the receiving end under the same posture; or randomly generating the plurality of sampling points under a plurality of postures of the receiving end, the throughput rate curve being used to indicate the antenna performance of the receiving end under the plurality of postures.

[0013] In this way, when the sampling points are under the same posture, the throughput rate curve reflects the antenna performance of the receiving end under the same posture; and when the sampling points are under different postures, the throughput rate curve reflects the antenna performance of the receiving end under different postures.

[0014] Optionally, the channel model comprises one or more channel models; when the channel model comprises one channel model, the throughput curve is used to indicate the antenna performance of the receiving end under the same channel model; when the channel model comprises multiple channel models, the throughput curve is used to indicate the antenna performance of the receiving end under the multiple channel models.

[0015] In this way, the throughput curve can reflect the antenna performance of the receiving end under a fixed channel environment, or the antenna performance of the receiving end under different channel environments.

[0016] Optionally, the throughput curve of the receiving end is obtained according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, comprising: obtaining multiple first throughput curves according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, the multiple first throughput curves corresponding to different modulation and coding strategies of the signal, and / or the multiple first throughput curves corresponding to different numbers of data streams of the signal; obtaining one or more second throughput curves according to the multiple first throughput curves, the second throughput curve being used to represent the antenna performance of the receiving end under the adaptive adjustment of the modulation and coding strategy of the signal; when the second throughput curve is one, the second throughput curve is the throughput curve of the receiving end; when the second throughput curve is multiple, obtaining a third throughput curve according to the second throughput curve, the third throughput curve being the throughput curve of the receiving end, and the third throughput curve being used to represent the antenna performance of the receiving end corresponding to the adaptive adjustment of the number of data streams of the signal under the adaptive adjustment of the modulation and coding strategy of the signal.

[0017] In this way, the influence of the modulation and coding strategy and / or the number of data streams on the throughput is comprehensively considered, so that the throughput curve conforms to the rule that the transmitting end adjusts the modulation and coding strategy and / or the number of data streams of the signal according to the signal transmission quality, and the accuracy of the obtained throughput curve is improved.

[0018] Optionally, obtaining one or more second throughput curves according to the multiple first throughput curves comprises: performing normalization processing on the multiple first throughput curves of the signal under the same number of data streams to obtain multiple first throughput curves after normalization processing of the signal under the same number of data streams; and selecting the maximum value of the throughput under the same signal-to-noise ratio from the multiple first throughput curves after normalization processing corresponding to the same number of data streams to obtain the second throughput curve.

[0019] In this way, the multiple modulation and coding strategies corresponding to the throughput curves under the same number of data streams are normalized, and the normalization processing can map the data to the range of 0-1 for processing, which simplifies the calculation and improves the processing speed.

[0020] Optionally, the plurality of second throughput rate curves correspond to different numbers of data streams; the method further comprises obtaining a third throughput rate curve from the plurality of second throughput rate curves, the third throughput rate curve being used to represent an antenna performance of a receiving end corresponding to a number of data streams of the adaptive adjustment signal under an adaptive adjustment of a modulation and coding strategy of the adaptive adjustment signal.

[0021] In this way, the influence of the modulation and coding strategy and the number of data streams on the throughput rate is comprehensively considered, so that the throughput rate curve conforms to the law of adjusting the modulation and coding strategy and the number of data streams of the signal according to the signal transmission quality, and the accuracy of the obtained throughput rate curve is improved.

[0022] Optionally, obtaining the third throughput rate curve from the plurality of second throughput rate curves comprises: performing normalization processing on the plurality of second throughput rate curves to obtain a plurality of second throughput rate curves after normalization processing; and selecting a maximum value of the throughput rate under the same signal-to-noise ratio from the plurality of second throughput rate curves after normalization processing to obtain a throughput rate curve corresponding to the first channel transmission matrix.

[0023] In this way, the throughput rate curves corresponding to the adaptive modulation and coding strategy under different numbers of data streams are normalized, and the normalization processing can map the data to the range of 0 to 1 for processing, which simplifies the calculation and improves the processing speed.

[0024] Optionally, the receiving antenna is N-rooted, and the number of data streams is M; obtaining a plurality of first throughput rate curves according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: obtaining a throughput rate corresponding to each receiving antenna according to a plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; sorting the throughput rates corresponding to the N-rooted receiving antennas; and superimposing the throughput rates corresponding to the first M receiving antennas to obtain a first throughput rate curve corresponding to the number of data streams being M.

[0025] In this way, the receiving antennas with better antenna performance are selected for signal reception, which conforms to the law of receiving signals at the receiving end and improves the accuracy of the throughput rate of the receiving end.

[0026] Optionally, obtaining a throughput rate corresponding to each receiving antenna according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: obtaining a channel coefficient of a sampling point corresponding to each receiving antenna according to a plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; obtaining a signal-to-noise ratio of the sampling point corresponding to each receiving antenna according to the channel coefficient of the sampling point corresponding to each receiving antenna and a signal transmission formula; and obtaining a throughput rate of each receiving antenna under different signal-to-noise ratios according to the signal-to-noise ratio of the sampling point corresponding to each receiving antenna and a threshold value, the threshold value being a minimum signal-to-noise ratio corresponding to successful demodulation of the signal at the receiving end.

[0027] In this way, the calculation of the throughput rate can be realized through the channel coefficient and the signal transmission formula.

[0028] Optionally, the channel coefficient of the sampling point corresponding to each receiving antenna satisfies: h u,s = h u,s,1 (t, f) + … + h u,s,n (t, f); h u,s is the channel coefficient from the s th transmitting antenna to the u th receiving antenna; h u,s,n is the channel coefficient of the n th cluster from the s th transmitting antenna to the u th receiving antenna; h u,s,n satisfies: Wherein, P n is the power of the n th cluster; M is the number of sub-radii in each cluster; is the radiation pattern of the s th transmitting antenna; represents the radiation pattern of the u th receiving antenna; is a random initial phase; and are the spherical unit vectors of the departure angle and the arrival angle of the m th sub-radium of the n th cluster, respectively; is the position vector of the s th transmitting antenna; is the position vector of the u th receiving antenna; λ is the wavelength of electromagnetic wave; τ n is the time delay of the n th cluster; f is the carrier frequency; v n,m is the Doppler shift of the m th sub-radium of the n th cluster; P n , M, λ, τ n , f, v n,m are parameters of the channel model obtained in advance; the signal transmission formula satisfies: y = h i x i + ∑ j≠i h j x j +n. Wherein, h i x i represents the signal received by the receiving end i th flow data, ∑ j≠i h j x j represents the interference of all other flows to the i th flow, n is the interference noise existing when the receiving end receives the i th flow data; the signal-to-noise ratio of the i th flow data satisfies: Wherein, H H The superscript H in H represents conjugate transpose, [X] i,iLet I represent the i-th diagonal term of the matrix, and let H represent the channel transmission matrix consisting of the channel coefficients from the transmitting antenna to the receiving antenna. The throughput at the receiving end satisfies: in, N T γ is the number of transmitting antennas. th Let F be the threshold, representing the threshold value at a given time interval. Under the condition γ th The cumulative distribution function, T put,max Let be the maximum throughput of the receiving end. Thus, the throughput of the receiving end can be obtained using the formula above.

[0029] Secondly, embodiments of this application provide an antenna testing device, which can be applied to terminal devices, or chips or chip systems in terminal devices.

[0030] The antenna testing apparatus includes a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the antenna testing apparatus to perform the method as described in the first aspect.

[0031] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the method as described in the first aspect.

[0032] Fourthly, embodiments of this application provide a computer program product, which includes a computer program that, when run, causes a computer to perform the method as described in the first aspect.

[0033] Fifthly, embodiments of this application provide a chip, the chip including a processor, the processor being configured to invoke a computer program in memory to perform the method described in the first aspect.

[0034] It should be understood that the second to fifth aspects of this application correspond to the technical solutions of the first aspect of this application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation are similar, and will not be repeated here. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of a possible test scenario in a design.

[0036] Figure 2 This is a schematic diagram of an antenna testing method provided in an embodiment of this application;

[0037] Figure 3 A schematic diagram of a first-class data transmission path provided for an embodiment of this application;

[0038] Figure 4A signal transmission schematic diagram provided for an embodiment of the present application;

[0039] Figure 5 A throughput rate curve schematic diagram provided for an embodiment of the present application;

[0040] Figure 6 A throughput rate curve schematic diagram corresponding to an adaptive modulation and coding strategy provided for an embodiment of the present application;

[0041] Figure 7 A throughput rate curve schematic diagram corresponding to an adaptive data flow quantity provided for an embodiment of the present application;

[0042] Figure 8 A structure schematic diagram of an antenna testing device provided for an embodiment of the present application;

[0043] Figure 9 A structure schematic diagram of an antenna testing device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to clearly describe the technical solutions of the embodiments of the present application, the following briefly introduces some terms and technologies involved in the embodiments of the present application:

[0045] 1. Antenna: a kind of transducer. The antenna can radiate electromagnetic waves to the outside world, and can also receive electromagnetic waves from the outside world.

[0046] 2. Radiation pattern: refers to the relative field strength (normalized modulus) of the radiation field at a certain distance from the antenna changes with direction pattern, usually represented by two mutually perpendicular plane patterns through the maximum radiation direction of the antenna. The radiation pattern is an important pattern for measuring the performance of the antenna, and various parameters of the antenna can be observed from the radiation pattern. The radiation pattern can also be called antenna pattern, antenna radiation pattern, which is not limited here.

[0047] 3. Modulation and coding strategy (MCS): MCS defines the redundancy coding scheme and modulation scheme adopted when carrying binary data in a resource element (RE), that is, the number of useful bits that can be carried in a RE. At present, there are 0-31 MCS schemes in total, of which 29-31 are reserved. The higher the MCS index, the higher the number of effective bits that can be carried in a RE.

[0048] MCS defines two parts, modulation and code rate.

[0049] The modulation scheme refers to the way of digital modulation and the order of modulation. The modulation scheme includes: quadrature phase shift keying (QPSK), 16 quadrature amplitude modulation (QAM), 64 QAM, and 256 QAM, etc. QPSK can transmit 2 bits per RE, 16 QAM can transmit 4 bits, 64 QAM can transmit 6 bits, and 256 QAM can transmit 8 bits.

[0050] 4. Code rate: the ratio between useful bits and total transmission bits (useful + redundant bits), i.e. the efficiency of the redundancy coding. The code rate is used to measure the redundancy added by the physical layer.

[0051] It should be noted that the signal transmission efficiency in the wireless network is measured by the spectrum efficiency. The spectrum efficiency refers to the ratio between the number of bits transmitted per unit time and the bandwidth of the spectrum used, which can reflect the use efficiency of the signal in a specific frequency band.

[0052] For example, a possible correspondence between different indexes of MCS and modulation order, target code rate and spectrum efficiency is shown in Table 1.

[0053] Table 1: Correspondence between modulation order, target code rate and spectrum efficiency

[0054]

[0055]

[0056] It should be noted that the MCS depends on the signal quality in the wireless link. If the signal quality is better, the number of bits that can be used to transmit data in a symbol is more; if the signal quality is poor, the MCS is lower, and the number of bits that can be used to transmit data in a symbol is less.

[0057] The value of the MCS depends on the blocker error rate (BLER), which is usually defined as a threshold of 10%. In order to keep the BLER not exceeding the value in different wireless environments, the base station (gNB) will assign an MCS according to the link adaptation algorithm, and send it to the terminal device through the downlink control information (DCI) on the physical downlink control channel (PDCCH) channel.

[0058] 5、Cumulative distribution function (CDF): is the integral of the probability density function.

[0059] 6、Throughput: the number of information bits transmitted per unit time.

[0060] 7、Signal to interference plus noise ratio (SNR): refers to the proportion of signal and noise in an electronic device or electronic system. The unit of signal to interference plus noise ratio is decibel (dB). In analog communication,

[0061] Wherein, SNR is the dB form of S / N, Eb is the energy of each bit signal, No is the power spectral density of noise; Rb is the transmission rate (the number of bits transmitted per second); W is the bandwidth of the signal.

[0062] In digital communication, The demodulation threshold of the receiver, also known as bit signal to noise ratio.

[0063] 8、Block error rate (BLER): is an index for measuring the accuracy of data transmission in a specified time. The block error rate ble has a corresponding relationship with the simulated signal to noise ratio SNR. As the signal to noise ratio increases, the block error rate continuously decreases.

[0064] 9、Other terms

[0065] In the embodiments of the present application, the same items or similar items with basically the same functions and effects are distinguished by using "first", "second", etc. For example, the first chip and the second chip are only used to distinguish different chips, and do not limit the sequence. Those skilled in the art can understand that "first", "second", etc. do not limit the quantity and execution sequence, and "first", "second", etc. also do not limit the difference.

[0066] It should be noted that in the embodiments of the present application, the words "exemplary" or "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplary" or "for example" are intended to present the relevant concept in a specific manner.

[0067] In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. The "and / or" describes the association relationship of the associated objects, which means that there can be three kinds of relationships, for example, A and / or B can represent: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0068] In the embodiments of the present application, "at the time of" can be at the moment when a certain condition occurs, or within a period of time after a certain condition occurs, which is not specifically limited in the embodiments of the present application. In addition, the interface of the terminal device provided by the embodiments of the present application is only an example, and the interface can also include more or less content.

[0069] 10. The terminal device

[0070] The terminal device of the embodiments of the present application can also be any form of electronic device. For example, the electronic device can include a handheld device with communication function, a vehicle-mounted device, etc. For example, some electronic devices are: a mobile phone, a tablet computer, a palm computer, a notebook computer, a mobile internet device (MID), a wearable device, a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical surgery, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, a cellular phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a 5G network, or a terminal device in a future evolved public land mobile network (PLMN), etc. The embodiments of the present application are not limited thereto.

[0071] By way of example and not limitation, in the embodiments of the present application, the electronic device can also be a wearable device. The wearable device can also be referred to as a wearable smart device, which is a general term for devices that are designed and developed by applying wearable technology to daily wear, such as glasses, gloves, watches, clothing, and shoes. The wearable device is a portable device that is directly worn on the body or integrated into the clothes or accessories of the user. The wearable device is not only a hardware device, but also a device that realizes powerful functions through software support and data interaction and cloud interaction. The general wearable smart device includes a device with full functions and large size, which can realize complete or partial functions without relying on a smart phone, such as a smart watch or smart glasses, and a device that focuses on a certain application function and needs to cooperate with other devices such as a smart phone, such as various smart wristbands and smart jewelry for monitoring vital signs.

[0072] In addition, in the embodiments of the present application, the electronic device can also be a terminal device in an internet of things (IoT) system. The IoT is an important part of future information technology development, and its main technical feature is to connect objects through communication technology and network, so as to realize the intelligent network of man-machine interconnection and object-object interconnection.

[0073] The electronic device in the embodiments of the present application can also be referred to as a terminal device, a user equipment (UE), a mobile station (MS), a mobile terminal (MT), an access terminal, a subscriber unit, a subscriber station, a mobile station, a mobile terminal, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, a user agent, or a user equipment, etc.

[0074] In the embodiments of the present application, the electronic device or each network device includes a hardware layer, an operating system layer running on the hardware layer, and an application layer running on the operating system layer. The hardware layer includes central processing unit (CPU), memory management unit (MMU), and memory (also known as main memory) and other hardware. The operating system can be any one or more computer operating systems that implement business processing through processes, such as Linux operating system, Unix operating system, Android operating system, iOS operating system, or windows operating system, etc. The application layer includes browser, address book, word processing software, instant messaging software, etc.

[0075] The MIMO communication technology can realize simultaneous transmission of multiple code streams and increase communication rate by means of a multi-antenna system. At present, multiple-input multiple-output (MIMO) of a terminal device can be tested in multiple ways. For example, over the air (OTA) and conduction, etc.

[0076] However, in both testing methods, the entity of the terminal device needs to be tested, and this method cannot be used for performance prediction in the design stage of the terminal device, so that the design risk of the terminal device is large.

[0077] When testing by OTA, one end of the channel simulator is connected to the base station or base station simulator, and the other end of the channel simulator is connected to the multi-probe anechoic chamber for testing.

[0078] Exemplarily, Figure 1 A schematic diagram of one of the possible design test scenarios is shown in FIG. 1. As shown in FIG. 1, the terminal device is connected to the base station through the air, and the base station is connected to the channel simulator through the air.Figure 1 As shown, the base station simulator 101 is connected with the channel simulator 102, and the channel simulator 102 is connected with multiple antennas 104 built in the OTA darkroom 103. The terminal device is placed at the center of the OTA darkroom 103.

[0079] The antennas 104 are controlled by the base station simulator 101 and the channel simulator 102 to emit radio frequency signals, so that the radio frequency signals reaching the terminal device 105 conform to the description of the channel model, to perform throughput testing on the terminal device 105.

[0080] In addition, Figure 1 As shown in the test, the terminal device 105 as a whole is tested. The measured throughput of the terminal device 105 is affected by multiple factors such as internal radiation interference of the terminal device, product structure of the terminal device, directivity of the antenna, difference between multiple antennas, and radio frequency chip transceiver algorithm. Therefore, Figure 1 The throughput measured in the test mode shown cannot be associated with the antenna indicators such as directivity of the antenna in the terminal device 105 and difference between multiple antennas. When the throughput of the terminal device 105 does not meet the standard, a set of antennas needs to be redesigned, installed, and then tested, which is time-consuming and low in efficiency.

[0081] When the test is performed in a conductive mode, one end of the channel simulator is connected with the base station or the base station simulator, and the other end of the channel simulator is connected with the radio frequency chip in the terminal device for testing.

[0082] In this mode, the channel simulator is directly connected with the radio frequency chip of the terminal device, and the throughput obtained by the test is related to the signal transmission performance of the radio frequency chip. Since the signal is not received by the antenna of the terminal device in this mode, the throughput obtained by the test is not related to the performance of the received signal of the antenna, and the performance of the antenna of the terminal device cannot be tested.

[0083] Therefore, the embodiments of the present application provide an antenna testing method and related device. The radiation pattern of a real antenna is coupled with a channel model to simulate a scenario of receiving a signal by an antenna of a terminal device, and design evaluation of the antenna is realized in a simulated manner. In this way, without using a physical antenna, performance testing of the terminal device can be performed in a design stage of the antenna, design risks are reduced, and development speed is improved.

[0084] In addition, in the embodiments of the present application, the antenna performance is represented by the throughput, and the way of representing the antenna performance by the throughput is more in line with the law of signal transmission change in an actual use scenario.

[0085] The technical solutions of the present application and how the technical solutions solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be implemented independently or in combination. Some embodiments may not be described again for the same or similar concepts or processes.

[0086] Exemplary, Figure 2 An antenna testing method provided by an embodiment of the present application is shown in a schematic diagram. As shown in the diagram, Figure 2 The method includes the following steps.

[0087] S201: Obtain antenna information of a transmitting end.

[0088] The transmitting end can be a base station or a terminal device, which is not limited herein.

[0089] In an embodiment of the present application, the antenna information of the transmitting end is used to determine the gain information of each direction of each transmitting antenna, the phase offset information of the same signal in each direction of any two transmitting antennas, and other related information.

[0090] In some embodiments, the antenna information of the transmitting end obtained by the testing software includes but is not limited to the type, parameters, layout, etc. of the transmitting antenna. The transmitting antenna is the antenna of the transmitting end. The type of the transmitting antenna can be an omnidirectional antenna, a directional antenna, etc., which is not limited herein. The parameters of the transmitting antenna include the structure, polarization discrimination rate, envelope correlation coefficient (ECC), isolation, antenna efficiency, working frequency point, etc. of the transmitting antenna. The layout of the transmitting antenna includes the relative positions of each transmitting antenna. The transmitting antenna can be a virtual antenna or a physical antenna, which is not limited herein.

[0091] In a possible implementation, the testing software can obtain the radiation pattern of each transmitting antenna according to the parameters of the transmitting antenna input by the user, such as the type, layout, parameters, etc.

[0092] In other embodiments, the antenna information of the transmitting end obtained by the testing software can also be the radiation pattern of each transmitting antenna or the OTA direction file of the transmitting antenna input by the user, etc. The method for obtaining the antenna information is not limited in the embodiments of the present application.

[0093] Exemplarily, the test software can obtain the radiation pattern of each transmitting antenna through the OTA direction file input by the user. The OTA direction file includes data such as antenna efficiency, operating frequency point, antenna position, and the like. The test software can perform coordinate mapping on the OTA direction data in the simulated OTA direction file of the antenna to convert the OTA direction data in the rectangular coordinate (CST format) into OTA direction data in the polar coordinate format, and obtain the radiation pattern of each transmitting antenna.

[0094] The radiation pattern of the transmitting antenna obtained by the test software can be a simulated radiation pattern of the transmitting antenna, and can also be a measured radiation pattern of the transmitting antenna, which is not limited in the present application.

[0095] S202, information of a channel model is obtained.

[0096] In the embodiment of the present application, the channel model is used to represent the signal transmission channel between the transmitting antenna and the receiving antenna. The test software can confirm the transmission channel of the signal according to the channel model, so as to confirm the fading, time delay and the like of the signal transmission. The channel model contains the spatial correlation (for example, reflection, diffraction and the like) of the signal, Doppler, time delay and the like.

[0097] In the embodiment of the present application, the information of the channel model is used to determine the channel model used for antenna testing, and the channel parameter data, the channel parameters including the interference, fading, signal strength of each signal propagation path and the environmental parameters of each signal propagation path, the environmental parameters of each signal propagation path including the parameters such as the departure angle Ф, the arrival angle ψ, the time delay τ and the like of the signal propagation path.

[0098] Exemplarily, the channel model can be divided into: a clustered delay line (CDL) model, a tapped delay line (TDL) model, a QuaDriga channel model, and a channel model collected by a channel collection device, and the like, and the type of the channel model is not limited in the embodiment of the present application.

[0099] The channel model used for antenna testing can be selected by the user from a plurality of pre-stored channel models, or can be a channel model input by the user, which is not limited in the embodiment of the present application. Exemplarily, the user can input a typical channel model collected by a channel collection device into the test software to perform the throughput test under the channel model.

[0100] In some embodiments, the channel model used for the antenna test can be determined by the scenario information of the receiving end input by the user, for example, indoor, outdoor, suburb, etc. The test software can determine the type of the channel model required for the test and the corresponding channel parameters based on the scenario information of the receiving end. For example, when the receiving end is in an indoor scenario, a CDL channel model can be used; when the receiving end is in an outdoor scenario, a QuaDriga channel model can be used; and when the receiving end is in a suburban or open scenario, a channel model collected by a channel collection device in an open scenario can be used. The embodiments of the present application do not make specific limitations on the channel model, the scenario, and the like.

[0101] The channel parameter data can be channel parameter data input by the user in the test software, or channel parameter data selected by the user from one or more groups of pre-stored channel parameter data. The embodiments of the present application do not make specific limitations on the acquisition method of the channel parameter data.

[0102] S203, antenna information of the receiving end is acquired.

[0103] The receiving end is a terminal device to be tested. In the embodiments of the present application, the antenna information of the receiving end is the antenna information of the physical antenna of the terminal device to be tested simulated. In this way, the physical antenna of the receiving end is simulated, so that the antenna performance obtained by the test software matches the antenna performance of the terminal device to be tested, thereby facilitating the subsequent evaluation of the antenna design of the terminal device to be tested.

[0104] In the embodiments of the present application, the antenna information of the receiving end is used to determine the gain information of each direction of each receiving antenna in the terminal device to be tested, and the phase offset information of the same signal in each direction of any two receiving antennas, and the like. The receiving antenna is a physical antenna.

[0105] In some embodiments, the antenna information of the receiving end includes but is not limited to the type, parameters, layout, and the like of the receiving antenna. The receiving antenna is the antenna of the receiving end. The type of the receiving antenna can be an omnidirectional antenna, a directional antenna, or the like, which is not limited herein. The parameters of the receiving antenna include the structure, polarization discrimination rate, envelope correlation coefficient (ECC), isolation, antenna efficiency, operating frequency point, and the like of the receiving antenna. The layout of the receiving antenna includes the relative positions of the receiving antennas.

[0106] In a possible implementation manner, the test software can obtain the radiation pattern of each receiving antenna according to the parameters of the receiving antenna of the receiving end input by the user, for example, the type, layout, and number of receiving antennas.

[0107] In some other embodiments, the antenna information of the receiving end obtained by the test software can also be the radiation pattern of each receiving antenna, or an OTA direction file of the receiving antenna input by a user, etc. The embodiments of the present application do not limit the obtaining manner of the antenna information.

[0108] The radiation pattern of the receiving antenna can be a simulation generated radiation pattern of the receiving antenna, or a measured radiation pattern of the receiving antenna, and the present application does not limit this.

[0109] S204, obtaining the throughput rate curve of the receiving end based on the antenna information of the transmitting end, the antenna information of the receiving end, and the information of the channel model. The throughput rate curve is used to represent the throughput rate of the receiving end under different signal-to-noise ratios.

[0110] In the embodiments of the present application, the throughput rate curve is used to represent the corresponding relationship between the throughput rate and the signal-to-noise ratio. For example, as shown in Figure 5 is a test curve diagram of the throughput rate and the signal-to-noise ratio under a fixed modulation and coding strategy.

[0111] It can be understood that the throughput rate of the receiving end can be obtained by any possible calculation manner in the embodiments of the present application, which is not limited here. For example, taking the signal transmission probability under different signal-to-noise ratios obtained by multiple sampling points as an example, the test software can randomly generate multiple sampling points, and statistically calculate the signal-to-noise ratio of each sampling point according to the antenna information of the transmitting end, the antenna information of the receiving end, and the information of the channel model, to obtain the probability of signal transmission under different signal-to-noise ratios (i.e., the cumulative probability distribution of the signal-to-noise ratio). The theoretical throughput rate is multiplied by the probability to obtain the throughput rate of signal transmission under different signal-to-noise ratios, and the throughput rate curve of the receiving end is obtained. The theoretical throughput rate is the throughput rate when the sampling point successfully performs signal transmission.

[0112] The calculation process of the signal-to-noise ratio is described below. Since the signal-to-noise ratio is the ratio of the signal to the noise, the signal received by the receiving antenna is described below.

[0113] For example, for an NT×NR MIMO system, the signal propagation formula can be expressed as: y=Hx+n. Wherein, y is the signal received by the receiving antenna, x is the signal transmitted by the transmitting antenna, H is the channel transmission matrix, and n is the interference noise existing when receiving, which can also be referred to as a noise signal with independent and identically distributed complex Gaussian elements. The signal-to-noise ratio is

[0114] Taking the CDL model as the channel model, the S root as the transmitting antenna, and the U root as the receiving antenna as an example, the channel transmission matrix includes: the channel coefficients from the transmitting antenna to the receiving antenna. h 1,1 represents the channel coefficient received by the second receiving antenna through spatial fading from the first transmitting antenna; hu,1 denotes the channel coefficient from the 1st transmit antenna, through spatial fading to the u-th receive antenna; h 1,s denotes the channel coefficient from the s-th transmit antenna, through spatial fading to the 1st receive antenna; h u,s denotes the channel coefficient from the s-th transmit antenna, through spatial fading to the u-th receive antenna.

[0115] denotes the channel coefficient between the s-th transmit antenna and the u-th receive antenna; h u,s x s . Taking the CDL model as the channel model, and each path including 20 clusters as an example, h u,s = h u,s,1 (t, f) + … + h u,s,n (t, f). As shown in FIG. 3, the channel coefficient of the n-th cluster from the s-th transmit antenna to the u-th receive antenna is: Figure 3

[0116] where P n is the power of the n-th cluster; M is the number of sub-paths in each cluster; denotes the radiation pattern of the s-th transmit antenna; denotes the radiation pattern of the u-th receive antenna; denotes the antenna OTA.

[0117] is a random initial phase; and are the spherical unit vectors of the departure angle and the arrival angle of the m-th sub-path of the n-th cluster, respectively; is the position vector of the s-th transmit antenna; is the position vector of the u-th receive antenna; denotes the spatial correlation.

[0118] λ is the wavelength of the electromagnetic wave; τ n is the time delay of the n-th cluster; f is the carrier frequency; v n,m is the Doppler shift of the m-th sub-path of the n-th cluster, which depends on the radial motion speed of the receiving end relative to the direction of arrival and the frequency size. exp(-j2πfτ n ) represents the time delay.

[0119] The signal energy received by the receiving antenna can be obtained through the above signal propagation formula. The calculation of the ratio of the signal to the noise is described below.

[0120] ​It can be understood that in the open-loop MIMO system with full spatial multiplexing, each receiving antenna can receive multiple signals from multiple transmitting antennas. The receiving antenna can receive a first signal and a second signal, and the second signal can interfere with the first signal. The first signal is the signal corresponding to the receiving antenna, and the second signal is the signal corresponding to the receiving antenna other than the receiving antenna.

[0121] Exemplarily, Figure 4 A signal transmission schematic diagram is provided for an embodiment of the present application. As shown in the figure, the transmitting antennas are 4, which are T1, T2, T3 and T4 respectively; the receiving antennas are 4, which are R1, R2, R3 and R4 respectively. Figure 4

[0122] T1 transmits the first stream data to R1; T2 transmits the second stream data to R2; T3 transmits the third stream data to R3; and T4 transmits the fourth stream data to R4. R1 also receives the second stream data, the third stream data and the fourth stream data. The second stream data, the third stream data and the fourth stream data interfere with the first stream data received by R1.

[0123] Therefore, for the open-loop MIMO system with full spatial multiplexing, the signal propagation formula can be expressed as: y = h i x i + ∑ j≠ i h j x j +n. Wherein h i x i represents the i-th stream data received by the receiving end, ∑ j≠i h j x j represents the interference of all other stream data on the i-th stream data. The signal-to-noise ratio of the i-th stream data is That is Also can be expressed as Wherein, H H The superscript H in H i,i represents the conjugate transpose, [X] i,i represents the i-th diagonal item of the matrix, and I represents the unit matrix of the same order.

[0124] It should be noted that when the signal-to-noise ratio of the signal is greater than or equal to the threshold (γ th ), the receiving end can successfully demodulate the signal, and when the signal-to-noise ratio of the signal is less than the threshold, the receiving end fails to demodulate the signal. The threshold (γ th ) can also be referred to as the block error SNR threshold, which is not limited here.

[0125] The testing software can obtain the signal-to-noise ratio (SNR) of each data stream based on the channel transmission matrix H, obtain the probability distribution of the SNR of each data stream at multiple sampling points, and then obtain the throughput of the receiving antenna corresponding to each data stream; subsequently, the throughput of the receiving antenna corresponding to each data stream is superimposed to obtain the throughput of the receiving end.

[0126] In this embodiment, the testing software can randomly generate multiple sampling points based on the channel model and the radiation pattern of the receiving antenna, and statistically analyze the reception of the signals corresponding to the multiple sampling points to obtain the distribution probability of the sampling points under different signal-to-noise ratios; based on this probability and the maximum throughput of the signal, the throughput of the receiving antenna under different signal-to-noise ratios is obtained.

[0127] For example, taking the receiving antenna corresponding to the i-th stream of data as an example, the i-th stream of data in a given... Under the condition γ th The probability distribution function is This can be understood as the probability of signal demodulation failure; This indicates the probability of successful signal demodulation.

[0128] Under a fixed modulation and coding strategy, the throughput of the i-th stream of data is the product of the maximum throughput of the i-th stream of data and the probability of successful signal demodulation, i.e. γ i Let be the instantaneous signal-to-noise ratio of the i-th stream of data; Let be the average signal-to-noise ratio of the i-th stream of data.

[0129] Understandably, the throughput T of the terminal device put The sum of the throughput of all data streams, i.e.: in, N T It is the number of transmitting antennas, γ th Indicates the threshold. Indicates that in a given Under the condition γ th The probability density distribution (CDF), T put,max This represents the maximum throughput given by the system, which can also be called the theoretical maximum throughput.

[0130] It is understandable that different receiving antennas may have different signal throughput due to differences in their location and parameters. In this embodiment, the testing software samples each receiving antenna to obtain the throughput corresponding to each antenna. Subsequently, the throughput corresponding to each receiving antenna is superimposed to obtain the throughput of the receiving end.

[0131] Exemplarily, the test software can randomly generate a plurality of sampling points according to the channel model and the radiation pattern, and statistically process the signal-to-noise ratios of the plurality of sampling points to obtain a throughput rate curve corresponding to each receiving antenna; subsequently, the throughput rate curves corresponding to each receiving antenna are superimposed to obtain a throughput rate curve of the receiving end.

[0132] The above embodiments describe the calculation process of the throughput rate of the receiving end. The throughput rate can also be related to the modulation and coding strategy of the signal and the number of data streams of the signal. It should be noted that the modulation and coding strategy of the signal can affect the throughput rate of the receiving end. Generally, the higher the order corresponding to the modulation and coding strategy, the higher the throughput rate. Correspondingly, the higher the order corresponding to the modulation and coding strategy, the higher the requirement for the signal-to-noise ratio of the signal.

[0133] In some embodiments, the test software calculates the throughput rate of the receiving end with a fixed signal modulation and coding strategy, and outputs a corresponding throughput rate curve.

[0134] Exemplarily, the test software calculates the throughput rate of the receiving end with a high-order modulation and high-rate signal modulation and coding strategy, and outputs a corresponding throughput rate curve.

[0135] In other embodiments, the test software can obtain throughput rate curves corresponding to each modulation and coding strategy and process them to obtain a throughput rate curve corresponding to an adaptive modulation and coding strategy.

[0136] Exemplarily, the test software selects the maximum value of the throughput rate at the same signal-to-noise ratio from the throughput rate curves corresponding to each modulation and coding strategy to obtain a throughput rate curve corresponding to an adaptive modulation and coding strategy.

[0137] It can be understood that the higher the number of valid bits that can be carried in one RE in the modulation and coding strategy, the higher the requirement for the quality of signal transmission. Therefore, when the signal-to-noise ratio is high, the throughput rate corresponding to the high-order modulation and high-rate channel coding mode is large; when the signal-to-noise ratio is low, the throughput rate corresponding to the low-order modulation mode and low-rate channel coding scheme is large.

[0138] In this way, considering the scenario where the transmitting end can adaptively adjust the modulation and coding strategy of the signal, the test software obtains a throughput rate curve corresponding to an adaptive modulation and coding strategy, which is more consistent with the performance of the antenna in the actual use scenario of the receiving end, thereby improving the accuracy of the evaluation of the performance of the antenna.

[0139] It can be understood that the embodiments of the present application can obtain a throughput rate curve corresponding to an adaptive modulation and coding strategy through any possible calculation method, which is not limited here. Exemplarily, the maximum value of the throughput rate at the same signal-to-noise ratio can be directly selected from the throughput rate curves corresponding to each modulation and coding strategy to obtain a throughput rate curve corresponding to an adaptive modulation and coding strategy.

[0140] In some embodiments, the test software can normalize each of the throughput rate curves corresponding to each modulation and coding strategy. The test software can then select the maximum value of the throughput rate at the same signal-to-noise ratio from each of the normalized throughput rate curves corresponding to each modulation and coding strategy to obtain the throughput rate curve corresponding to the adaptive modulation and coding strategy. In this way, normalization can map the data to a range of 0-1, simplifying the calculation and improving the processing speed.

[0141] For example, the test software can normalize each of the throughput rate curves corresponding to each modulation and coding strategy by selecting the maximum value in the first throughput rate curve corresponding to the MCS with the order of 27. In other words, each of the throughput rate curves corresponding to each modulation and coding strategy can be divided by the maximum value in the throughput rate curve corresponding to the MCS with the order of 27.

[0142] For example, the test software can normalize each of the throughput rate curves corresponding to each modulation and coding strategy by selecting the maximum value in the first throughput rate curve corresponding to the MCS with the order of 27. In other words, each of the throughput rate curves corresponding to each modulation and coding strategy can be divided by the maximum value in the throughput rate curve corresponding to the MCS with the order of 27. Figure 6 Figure 6 For example, the test software can normalize each of the throughput rate curves corresponding to each modulation and coding strategy by selecting the maximum value in the first throughput rate curve corresponding to the MCS with the order of 27. In other words, each of the throughput rate curves corresponding to each modulation and coding strategy can be divided by the maximum value in the throughput rate curve corresponding to the MCS with the order of 27. Figure 6

[0143] In this way, the test software can simulate the signal transmission process to evaluate the performance of the antenna at the receiving end. The performance of the antenna can be evaluated during the design phase of the receiving end to reduce the design risk and improve the development speed. In addition, the relationship between the maximum throughput rate corresponding to each modulation and coding strategy and the signal-to-noise ratio can be obtained to improve the accuracy of the performance evaluation of the antenna.

[0144] It should be noted that the number of data streams can affect the throughput rate of the receiving end. The higher the number of data streams, the higher the requirement for the quality of signal transmission. Therefore, when the signal-to-noise ratio is high, the throughput rate corresponding to the mode with a large number of data streams is high; when the signal-to-noise ratio is low, the throughput rate corresponding to the mode with a small number of data streams is high.

[0145] In some embodiments, the test software can calculate the throughput rate of the receiving end with a fixed number of data streams and output the corresponding throughput rate curve.

[0146] For example, the test software can calculate the throughput rate of the receiving end with 4 data streams and output the corresponding throughput rate curve.

[0147] In other embodiments, the test software can obtain the throughput rate curves corresponding to different numbers of data streams and process the throughput rate curves to obtain the throughput rate curve corresponding to the adaptive adjustment of the number of data streams.​​

[0148] It can be understood that the embodiments of the present application can obtain the throughput rate curve corresponding to the number of data streams of the adaptive adjustment signal in any possible calculation manner, which is not limited here. Exemplarily, the maximum value of the throughput rate at the same signal-to-noise ratio can be directly selected from the throughput rate curve corresponding to the number of data streams of each signal to obtain the throughput rate curve corresponding to the number of data streams of the adaptive adjustment signal.

[0149] In some embodiments, the test software can obtain the throughput rate curve corresponding to the adaptive modulation and coding strategy under multiple numbers of data streams, and process to obtain the throughput rate curve corresponding to the number of data streams of the adaptive modulation and coding strategy of the adaptive adjustment signal. The number of data streams of the adaptive adjustment signal can also be referred to as adaptive hierarchical multiplexing, or adaptive antenna number, which is not limited here. In this way, considering the factors such as adjustment of the modulation and coding strategy, hierarchical multiplexing, etc. of the base station, the throughput rate curve obtained by the test conforms to the law of actual signal transmission, and the accuracy of the test result is improved.

[0150] Taking the throughput rate curve corresponding to the adaptive modulation and coding strategy as the second throughput rate curve as an example, the test software can obtain the second throughput rate curve under multiple numbers of data streams, and perform normalization processing on the multiple second throughput rate curves. The maximum value of the throughput rate at the same signal-to-noise ratio is selected from the normalized second throughput rate curve to obtain the throughput rate curve corresponding to the number of data streams of the adaptive modulation and coding strategy of the adaptive adjustment signal. In this way, the normalization processing can map the data to the range of 0-1 for processing, simplify the calculation, and improve the processing speed.

[0151] Exemplarily, taking 4 data streams as an example, as shown in FIG. 7A, the normalized second throughput rate curve can be as shown by line 701 in FIG. 7B. The test software can select the maximum value of the throughput rate at the same signal-to-noise ratio from the multiple second throughput rate curves, and the third throughput rate curve obtained can be as shown by line 702 in FIG. 7C. Figure 7 Figure 7 Exemplarily, taking 4 data streams as an example, as shown in FIG. 7A, the normalized second throughput rate curve can be as shown by line 701 in FIG. 7B. The test software can select the maximum value of the throughput rate at the same signal-to-noise ratio from the multiple second throughput rate curves, and the third throughput rate curve obtained can be as shown by line 702 in FIG. 7C. Figure 7

[0152] If the test software calculates the throughput rate of the receiving end with a fixed modulation and coding strategy, and outputs the corresponding throughput rate curve. The test software can obtain the throughput rate curve under multiple numbers of data streams.

[0153] Exemplarily, the test software can sort the throughput rates of U receiving antennas, and select the throughput rates corresponding to the first M receiving antennas to generate the throughput rate curve corresponding to each modulation and coding strategy (first throughput rate curve).

[0154] ​​Exemplarily, taking 4 receiving antennas, namely, antenna 1, antenna 2, antenna 3, and antenna 4, as an example, if the antenna performance is ranked in descending order as antenna 1, antenna 2, antenna 3, and antenna 4, when the data stream is 1, antenna 1 is selected to receive a signal, and a first throughput rate curve is generated according to the throughput rate corresponding to antenna 1; when the data stream is 2, antenna 1 and antenna 2 are selected to receive a signal, and the first throughput rate curve is generated according to the throughput rate corresponding to antenna 1 and the throughput rate corresponding to antenna 2; when the data stream is 3, antenna 1, antenna 2, and antenna 3 are selected to receive a signal, and the first throughput rate curve is generated according to the throughput rate corresponding to antenna 1, the throughput rate corresponding to antenna 2, and the throughput rate corresponding to antenna 3; and when the data stream is 4, the first throughput rate curve is generated according to the throughput rate corresponding to antenna 1, the throughput rate corresponding to antenna 2, the throughput rate corresponding to antenna 3, and the throughput rate corresponding to antenna 4.

[0155] In this way, the test software can select a receiving antenna with better receiving performance to perform performance evaluation, so that the first throughput rate curve is more consistent with the scenario of receiving a signal by using an antenna with better performance, and the accuracy of the evaluation result is improved.

[0156] On the basis of the above embodiment, the test software can randomly generate a plurality of sampling points under the same posture of the receiving end to perform antenna testing and generate a throughput rate curve; and the test software can also randomly generate a plurality of sampling points under a plurality of postures of the receiving end to perform antenna testing and generate a plurality of throughput rate curves.

[0157] In this way, the plurality of throughput rate curves can reflect the antenna performance of the receiving end under different postures, facilitating subsequent comparative analysis of the antenna performance.

[0158] In other embodiments, the test software can perform antenna testing on a plurality of sampling points under a plurality of postures to generate a throughput rate curve. In this way, the test software can use one throughput rate curve to reflect the antenna performance of one receiving end under different postures.

[0159] Exemplarily, the test software can traverse a plurality of postures of the receiving end to randomly generate a plurality of sampling points, which can also be understood as simulating rotation of the receiving end to randomly generate a plurality of sampling points.

[0160] It can be understood that the posture of the receiving end corresponds to the angle of the radiation pattern of the receiving end, and the angle of the radiation pattern of the receiving end is different under different postures. The angle of the radiation pattern of the receiving antenna refers to the angle (or pointing angle) of the radiation pattern relative to the channel model. Exemplarily, the test software can obtain the radiation pattern under a plurality of angles according to the radiation pattern under the first angle.

[0161] Exemplarily, the radiation pattern of the receiving antenna corresponding to different postures is different, and the above calculation of the channel coefficient in the CDL model is taken as an example. The radiation pattern of the receiving antenna corresponding to different postures is different, and the above calculation of the channel coefficient in the CDL model is taken as an example. different.

[0162] In this way, the angle of the radiation pattern of the receiving antenna is correlated with the throughput curve, so that the throughput curve can reflect the antenna performance of the terminal device in different orientations under the same channel environment.

[0163] In the above embodiments, the testing software can acquire one or more channel models. When the testing software acquires one channel model, it can calculate the signal-to-noise ratio (SNR) using that signal model and output the throughput curve corresponding to that channel model. When the testing software acquires multiple channel models, it can calculate the SNR using each signal model and output the throughput curve corresponding to each channel model. In this way, the testing software can output multiple throughput curves, which can reflect the antenna performance of the receiver under different channel environments, facilitating subsequent comparative analysis.

[0164] Understandably, different channel models correspond to different signal transmission path distributions. Different channel models also correspond to different departure and arrival angles. Taking the CDL model mentioned above as an example, different channel models correspond to... and different.

[0165] In other embodiments, the testing software can perform antenna tests on multiple sampling points under multiple channel models to generate a throughput curve. In this way, the testing software can use a single throughput curve to reflect the antenna performance of a receiver under different channel environments.

[0166] In this embodiment, the information testing software for multiple channel models can acquire multiple channel models at once or in multiple sessions; no limitation is made here.

[0167] Based on the above embodiments, the testing software can use a single channel model to perform antenna testing and output a throughput curve; alternatively, it can use multiple channel models to perform antenna testing.

[0168] Optionally, S204 above includes: S2041-S2043.

[0169] 2041. Calculate the channel transmission matrix based on the antenna information of the transmitting end, the antenna information of the receiving end, and the information of the channel model.

[0170] The calculation process of the channel transmission matrix can be referred to the corresponding explanation above, and will not be repeated here.

[0171] S2042, Calculate the signal-to-noise ratio.

[0172] The calculation process for the signal-to-noise ratio can be found in the above explanations, and will not be repeated here.

[0173] S2043, obtaining the throughput rate curve according to the first algorithm and the second algorithm.

[0174] The first algorithm is related to adaptive adjustment of modulation and coding strategies of signals, and the second algorithm is related to adaptive adjustment of the number of data streams of signals.

[0175] For example, the first algorithm is used to regard the throughput when the MCS order is 27 as the maximum throughput (i.e., the relative throughput is 1), and the normalized maximum relative throughput of other MCS orders is determined by Modulation Order and Code Rate. Then, the signal-to-noise ratio of the throughput rate curve obtained by the fixed MCS at the relative throughput of 0.9 is moved to the signal-to-noise ratio corresponding to the BLER of 0.1 of each MCS order, and the normalized maximum relative throughput calculated according to different MCS orders is used to compress the throughput rate curve, and then the maximum value of all curves is taken.

[0176] The second algorithm is used to fix 4 streams, 3 streams, 2 streams and 1 stream respectively, obtain the relative throughput rate curve when the adaptive MCS is performed, and finally take the maximum of the four new throughput rate curves to obtain the throughput rate curve considering the adaptive MCS and the adaptive adjustment of the number of data streams.

[0177] The throughput rate curve is used to indicate the relationship between the maximum throughput of the receiving antenna in multiple modulation and coding strategies and multiple numbers of data streams and the signal-to-noise ratio. For details, refer to the third throughput rate curve described above, which will not be described here.

[0178] In this way, the transmission process of the signal can be simulated, and the antenna performance of the terminal device can be evaluated. The performance of the antenna is evaluated in the design stage of the terminal device, which reduces the design risk and improves the development speed. Moreover, considering the factors such as adjustment of modulation and coding strategies by the base station and hierarchical multiplexing, the throughput rate curve obtained by the test conforms to the actual transmission rule of the signal, and the accuracy of the test result is improved.

[0179] It can be understood that in the above embodiments, the antenna performance is represented by the throughput rate curve. The test software can also represent the antenna performance by the throughput in a preset time. The above throughput rate curve is described by taking the signal-to-noise ratio as the horizontal axis and the throughput as the vertical axis. The signal-to-noise ratio can also be replaced by the signal strength, etc. The embodiments of the present application do not specifically limit the representation method of the test software for the antenna performance.

[0180] On the basis of the above embodiments, the test software can obtain the antenna information of the receiving end corresponding to one or more design schemes, and output the throughput rate curve corresponding to each design scheme.

[0181] The test software can also perform performance analysis according to the throughput rate curve corresponding to each design scheme.

[0182] The test software can also output a target design scheme according to the throughput rate curve of each design scheme, and the target design scheme is used for debugging the antenna of the receiving end.

[0183] The process and manner of performance analysis of the throughput rate curve are not limited in the embodiments of the present application.

[0184] The test software can obtain the antenna information of the receiving end corresponding to multiple design schemes at one time, or obtain a fixed number of the antenna information of the receiving end corresponding to multiple design schemes each time. In the above embodiments, the performance of the antenna of the receiving end in one design scheme is taken as an example for description. The test software can also test the antenna of the receiving end in multiple design schemes.

[0185] In the above embodiments, the throughput rate curve is used to represent the performance of the antenna of the receiving end. The test software can also use the throughput curve to represent the performance of the antenna of the receiving end, and the specific calculation process is similar to the calculation process of the throughput rate curve, which is not described herein again.

[0186] The method provided in the embodiments of the present application has been described above, and the device for executing the above method provided in the embodiments of the present application is described below. Those skilled in the art can understand that the method and the device can be combined and referenced with each other, and the related device provided in the embodiments of the present application can execute the steps in the above method.

[0187] For example, Figure 8 A structural schematic diagram of an antenna testing device provided in the embodiments of the present application is shown. The antenna testing device can be an electronic device in the embodiments of the present application, or can be a part of components in the electronic device, such as a chip or a chip system.

[0188] As shown in Figure 8 The antenna testing device can be used in a communication device, a circuit, a hardware component or a chip. The antenna testing device includes a communication unit 901, a processing unit 902, a display unit 903 and the like. The communication unit 901 is used for obtaining a channel model and a radiation pattern of each receiving antenna in a receiving end; the processing unit 902 is used for obtaining a throughput rate curve of the receiving end according to the channel model and the radiation pattern of each receiving antenna; and the display unit 903 is used for displaying the throughput rate of the receiving end.

[0189] The communication unit 901 is used for supporting the antenna testing device to interact with other devices. For example, when the antenna testing device is a terminal device, the communication unit 901 can be a communication interface or an interface circuit. When the antenna testing device is a chip or a chip system in the terminal device, the communication unit 901 can be a communication interface. For example, the communication interface can be an input / output interface, a pin or a circuit, etc.

[0190] Specifically, the processing unit 902 and the display unit 903 can be integrated together, and the processing unit 902 and the display unit 903 may communicate with each other.

[0191] In one possible implementation, the antenna testing device may further include a storage unit 904. The storage unit 904 may include one or more memories, which may be devices in one or more devices or circuits used to store programs or data.

[0192] The storage unit 904 can exist independently or be connected to the processing unit 902 via a communication bus. Alternatively, the storage unit 904 can be integrated with the processing unit 902.

[0193] Taking the antenna testing device as an example, which can be the chip or chip system of the terminal device in this application embodiment, the storage unit 904 can store the computer execution instructions of the terminal device's method, so that the processing unit 902 can execute the above-mentioned antenna testing method. The storage unit 904 can be a register, cache, or random access memory (RAM), etc., and the storage unit 904 can be integrated with the processing unit 902. The storage unit 904 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, and the storage unit 904 can be independent of the processing unit 902.

[0194] The apparatus in this embodiment can be used to execute the steps performed in the above method embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0195] This application provides an antenna testing device, which includes a processor and a memory; the memory stores computer-executed instructions; the processor executes the computer-executed instructions stored in the memory, causing the antenna testing device to perform the above-described method.

[0196] For example, Figure 9 This is a schematic diagram of an antenna testing device provided in an embodiment of this application. Figure 9 As shown, the antenna testing device includes a memory 1001, a processor 1002, and an interface circuit 1003. The device may also include a display screen 1004, wherein the memory 1001, processor 1002, interface circuit 1003, and display screen 1004 can communicate. For example, the memory 1001, processor 1002, interface circuit 1003, and display screen 1004 can communicate via a communication bus. The memory 1001 stores computer execution instructions, which are controlled by the processor 1002 and communicated by the interface circuit 1003, thereby implementing the antenna testing method provided in this embodiment.

[0197] Optionally, the interface circuit 1003 can further include a transmitter and / or a receiver. Optionally, the processor 1002 can include one or more CPUs, and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), or the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like. The steps of the method disclosed in the present application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0198] In a possible implementation, the computer execution instruction in the embodiments of the present application can also be referred to as application code, which is not specifically limited in the embodiments of the present application.

[0199] The antenna testing device provided by the embodiments of the present application is used to execute the antenna testing method of the above-mentioned embodiments, and the technical principles and technical effects are similar, which will not be described here.

[0200] The antenna testing method provided by the embodiments of the present application can be applied in an electronic device with display function. The electronic device includes a terminal device, and the specific device form of the terminal device can refer to the above-mentioned related description, which will not be described here.

[0201] The embodiments of the present application provide a chip. The chip includes a processor configured to invoke a computer program in a memory to execute the technical solutions in the above-mentioned embodiments. The implementation principles and technical effects are similar to the above-mentioned related embodiments, which will not be described here.

[0202] The embodiments of the present application further provide a computer readable storage medium. The computer readable storage medium stores a computer program. The computer program is executed by the processor to implement the above-mentioned method. The method described in the above-mentioned embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. If realized in software, the functions can be stored as one or more instructions or codes on a computer readable medium or transmitted on a computer readable medium. The computer readable medium can include computer storage medium and communication medium, and can also include any medium that can transfer computer programs from one place to another. The storage medium can be any target medium that can be accessed by a computer.

[0203] In a possible implementation, the computer readable medium can include a RAM, a ROM, a compact disc read-only memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that is suitable for storing desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray® disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer readable media.

[0204] The embodiment of the present application provides a computer program product, which comprises a computer program, and when the computer program is executed, the computer executes the above method.

[0205] The embodiment of the present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device implemented in the flowcharts and / or block diagrams. Figure 1 The device for implementing the function specified in one flow or multiple flows and / or one block or multiple blocks. Figure 1 The device for implementing the function specified in one flow or multiple flows and / or one block or multiple blocks.

[0206] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use, and processing of related data need to comply with relevant laws, regulations, and standards, and provide corresponding operation entrances for the user to select authorization or refusal.

[0207] The above detailed description of the specific embodiments of the present application is provided for the purpose of further explaining the objects, technical solutions and advantages of the present application, and it should be understood that the above is only a specific embodiment of the present application and is not used to limit the protection scope of the present application, and any modification, equivalent replacement, improvement, etc. made on the basis of the technical solutions of the present application should be included in the protection scope of the present application.

Claims

1. An antenna testing method, characterized by, The method comprises: obtaining a channel model, a radiation pattern of a transmitting antenna of a transmitting end, and a radiation pattern of a receiving antenna of a receiving end, the receiving antenna being a physical antenna; obtaining a throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; the throughput rate curve is used to represent antenna performance of the receiving end; the obtaining of the throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: obtaining a plurality of first throughput rate curves according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna, the plurality of first throughput rate curves corresponding to different modulation and coding strategies of a signal, and / or the plurality of first throughput rate curves corresponding to different numbers of data streams of the signal; obtaining one or more second throughput rate curves according to the plurality of first throughput rate curves, the second throughput rate curves being used to represent antenna performance of the receiving end under adaptive adjustment of the modulation and coding strategy of the signal; when the second throughput rate curves are one, the second throughput rate curve is the throughput rate curve of the receiving end; when the second throughput rate curves are a plurality, obtaining a third throughput rate curve according to the second throughput rate curves, the third throughput rate curve being the throughput rate curve of the receiving end, and the third throughput rate curve being used to represent antenna performance of the receiving end corresponding to adaptive adjustment of the number of data streams of the signal under adaptive adjustment of the modulation and coding strategy of the signal.

2. The method of claim 1, wherein, the obtaining of the throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: randomly generating a plurality of sampling points corresponding to the receiving antenna; obtaining a signal-to-noise ratio corresponding to the plurality of sampling points and a throughput rate corresponding to the plurality of sampling points according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; obtaining the throughput rate curve according to the signal-to-noise ratio corresponding to the plurality of sampling points and the throughput rate corresponding to the plurality of sampling points, the throughput rate curve being used to represent a throughput rate of the receiving end under different signal-to-noise ratios.

3. The method of claim 2, wherein, the randomly generating of the plurality of sampling points corresponding to the receiving antenna comprises: randomly generating the plurality of sampling points under a same posture of the receiving end, the throughput rate curve being used to indicate antenna performance of the receiving end under the same posture; or, randomly generating the plurality of sampling points under a plurality of postures of the receiving end, the throughput rate curve being used to indicate antenna performance of the receiving end under the plurality of postures.

4. The method of claim 3, wherein, the channel model comprises one or more channel models; when the channel model comprises one channel model, the throughput rate curve is used to indicate antenna performance of the receiving end under the same channel model; when the channel model comprises a plurality of channel models, the throughput rate curve is used to indicate antenna performance of the receiving end under the plurality of channel models.

5. The method of claim 1, wherein, the obtaining of the one or more second throughput rate curves according to the plurality of first throughput rate curves comprises: normalizing the plurality of first throughput rate curves of the signal under the same number of data streams to obtain a plurality of normalized first throughput rate curves of the signal under the same number of data streams; selecting a maximum value of a throughput rate under a same signal-to-noise ratio from the plurality of normalized first throughput rate curves corresponding to the same number of data streams to obtain the second throughput rate curve.

6. The method of claim 5, wherein, The plurality of second throughput rate curves correspond to different numbers of data streams; and the method further comprises: obtaining a third throughput rate curve from the plurality of second throughput rate curves, the third throughput rate curve being used to represent an antenna performance of the receiving end corresponding to an adaptive adjustment of a number of data streams of an adaptive adjustment signal under an adaptive adjustment of a modulation and coding strategy of the adaptive adjustment signal.

7. The method of claim 6, wherein, The obtaining of the third throughput rate curve from the plurality of second throughput rate curves comprises: normalizing the plurality of second throughput rate curves to obtain a plurality of normalized second throughput rate curves; selecting a maximum value of a throughput rate under a same signal-to-noise ratio from the plurality of normalized second throughput rate curves to obtain a throughput rate curve corresponding to a first channel transmission matrix.

8. The method according to any one of claims 1 to 7, characterized in that, The receiving antenna is N-rooted, and the number of data streams is M; The obtaining of the plurality of first throughput rate curves from the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: obtaining a throughput rate corresponding to each receiving antenna according to a plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; sorting the throughput rates corresponding to the N-rooted receiving antennas; superimposing the throughput rates corresponding to the M-rooted receiving antennas before sorting to obtain the first throughput rate curve corresponding to the number of data streams being M.

9. The method of claim 8, wherein, The obtaining of the throughput rate corresponding to each receiving antenna according to the plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna comprises: obtaining a channel coefficient of a sampling point corresponding to each receiving antenna according to the plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; obtaining a signal-to-noise ratio of the sampling point corresponding to each receiving antenna according to the channel coefficient of the sampling point corresponding to each receiving antenna and a signal transmission formula; obtaining a throughput rate of each receiving antenna under different signal-to-noise ratios according to the signal-to-noise ratio of the sampling point corresponding to each receiving antenna and a threshold value, the threshold value being a minimum signal-to-noise ratio corresponding to a successful demodulation of the signal by the receiving end.

10. The method of claim 9, wherein, The channel coefficient of the sampling point corresponding to each of the receiving antennas satisfies: h u,s = h u,s,1 (t, f) + … + h u,s,n (t, f); the h u,s is the channel coefficient of the s-th transmitting antenna to the u-th receiving antenna; the h u,s,n is the channel coefficient of the n-th cluster of the s-th transmitting antenna to the u-th receiving antenna; The h u,s,n satisfies: wherein the P n is the power of the nth cluster; the M is the number of sub-paths in each cluster; the is the radiation pattern of the s-th transmit antenna; the denotes the radiation pattern of the u-th receive antenna; the is a random initial phase; the and the are the spherical unit vectors of the departure angle and the arrival angle of the m-th sub-path of the nth cluster, respectively; the is the position vector of the s-th transmit antenna; the is the position vector of the u-th receive antenna; the λ is the wavelength of the electromagnetic wave; the τ n is the time delay of the nth cluster; the f is the carrier frequency; the ν n,m is the Doppler shift of the m-th sub-path of the nth cluster; The P n , the M, the The The The λ, the τ n , the f, the v n,m are parameters of the channel model acquired in advance; The signal transmission formula satisfies: y = h i x i +∑ j≠i h j x j +n; wherein, h i x i represents the signal received by the receiving end of the i flow data, ∑ j≠i h j x j represents the interference of all other flows to the i flow, and the n is the interference noise existing when the receiving end receives the i flow data. The signal-to-noise ratio of the i-th stream of data satisfies: in, The H H The superscript H in [X] indicates conjugate transpose. i,i Let I represent the i-th diagonal term of the matrix, where I represents the identity matrix of the same order, and H represents the channel transmission matrix composed of the channel coefficients of the signal transmitted from the transmitting antenna to the receiving antenna; The throughput rate of the receiving end satisfies: wherein, The N T is the number of transmitting antennas, the γ th is the threshold value, the F represents the cumulative distribution function of γ under the condition that T th is the maximum throughput rate of the receiving end, put,max is the average signal-to-noise ratio of all transmitting antennas.​ 11. An antenna test device, characterized by comprise: a processor and a memory; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory, so that the antenna testing device executes the method according to any one of claims 1-10.

12. A computer-readable storage medium, the computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the method according to any one of claims 1-10.

13. A computer program product, characterised in that, The computer program, when executed, causes a computer to execute the method according to any one of claims 1-10.

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