Antenna testing method and related device

Abstract

The embodiment of the invention provides an antenna testing method and a related device, which are applied to the technical field of terminals. The method comprises the following steps: acquiring 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, wherein the receiving antenna is an entity 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 antennas; the throughput rate curve is used for representing the antenna performance of the receiving end. In this way, the radiation pattern of the real antenna is simulated, and the simulated radiation pattern of the entity antenna is coupled with the channel model, so that the scene of receiving signals by the antenna of the receiving end is simulated. Design evaluation of the antenna is achieved in a simulation mode, an entity antenna does not need to be adopted, performance testing can be conducted on the receiving end in the design stage of the antenna, the design risk is reduced, and the development speed is increased.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to an antenna testing method and related devices. Background Art

[0002] Multi-antenna technology is one of the main means to increase channel capacity. At present, the 4th generation mobile communication technology (4G), the 5th generation mobile communication technology (5G), wireless fidelity (WiFi), the Internet of Things and other communications all 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 tested by over the air (OTA) downloading.

[0004] However, this method requires testing the entity of the terminal device, and the performance test of the terminal device is carried out late, which makes the design risk of the terminal device high. Summary of the invention

[0005] The embodiment of the present application provides an antenna testing method and related devices, which are applied to the field of terminal technology. The radiation pattern of the simulated physical antenna is coupled with the channel model to realize the scenario of the antenna receiving the signal at the simulated receiving end. The antenna design evaluation is realized by simulation, without the need for a physical antenna, and the performance of the receiving end can be tested during the antenna design stage, which reduces the design risk and improves the development speed.

[0006] In the first aspect, the embodiment of the present application proposes an antenna testing method. The method includes: obtaining a channel model, a radiation pattern of a transmitting antenna at a transmitting end, and a radiation pattern of a receiving antenna at a receiving end, where the receiving antenna is a physical antenna; obtaining a throughput 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 curve is used to characterize the antenna performance of the receiving end.

[0007] In this way, the radiation pattern of the physical antenna of the simulated receiving end can be obtained, and the radiation pattern can be coupled with the channel model to realize the antenna performance evaluation of the receiving end. Without using a physical antenna, the performance of the receiving end can be tested during the antenna design phase, reducing design risks and improving development speed. In addition, the method of characterizing antenna performance by throughput is more in line with the law of signal transmission changes in the actual use scenario of the receiving end, compared with the method of evaluating antenna performance by superimposing channel capacity and antenna capacity.

[0008] In the embodiment of the present application, the radiation pattern of the receiving antenna may be a radiation pattern corresponding to a directional antenna. Compared with the radiation pattern of an omnidirectional antenna, the radiation pattern corresponding to a 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 in 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 interference between multiple receiving antennas and improving the throughput 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, a 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, including: randomly generating multiple sampling points corresponding to the receiving antenna; obtaining signal-to-noise ratios corresponding to the multiple sampling points and throughputs corresponding to the multiple sampling points according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; obtaining a throughput curve according to the signal-to-noise ratios corresponding to the multiple sampling points and the throughputs corresponding to the multiple sampling points, wherein the throughput curve is used to represent the throughput of the receiving end under different signal-to-noise ratios.

[0011] In this way, the signal-to-noise ratio and throughput rate can be calculated through multiple randomly selected sampling points, which conforms to the changing law of analog signal transmission and improves the accuracy of the throughput rate curve.

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

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

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

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

[0016] Optionally, a throughput curve of the receiving end is obtained according to a channel model, a radiation pattern of a transmitting antenna, and a radiation pattern of a receiving antenna, including: obtaining multiple first throughput curves according to the channel model, the radiation pattern of a transmitting antenna, and the radiation pattern of a receiving antenna, the modulation and coding strategies of the signals corresponding to the multiple first throughput curves are different, and / or the number of data streams of the signals corresponding to the multiple first throughput curves is different; obtaining one or more second throughput curves according to the multiple first throughput curves, the second throughput curve being used to characterize the antenna performance of the receiving end under the modulation and coding strategy of adaptively adjusting the signal; when there is one second throughput curve, the second throughput curve is the throughput curve of the receiving end; when there are multiple second throughput curves, obtaining a third throughput curve according to the second throughput curve, the third throughput curve is the throughput curve of the receiving end, and the third throughput curve is used to characterize the antenna performance of the receiving end corresponding to the number of data streams of the adaptively adjusted signal under the modulation and coding strategy of the adaptively adjusted signal.

[0017] In this way, the impact 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 transmitter adjusts the modulation and coding strategy of the signal and / or the number of signal data streams according to the signal transmission quality, thereby improving the accuracy of the throughput curve obtained by the test.

[0018] Optionally, one or more second throughput curves are obtained based on multiple first throughput curves, including: normalizing multiple first throughput curves of the signal under the same number of data streams to obtain multiple normalized first throughput curves 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 normalized first throughput curves corresponding to the same number of data streams to obtain the second throughput curve.

[0019] In this way, the throughput curves corresponding to multiple modulation and coding strategies under the same number of data streams are normalized. The normalization process can map the data to a range of 0 to 1 for processing, thereby simplifying the calculation and improving the processing speed.

[0020] Optionally, the number of data streams corresponding to the multiple second throughput curves is different; the method also includes: obtaining a third throughput curve based on the multiple second throughput curves, the third throughput curve being used to characterize the antenna performance of the receiving end corresponding to the number of data streams of the adaptive adjustment signal under the modulation and coding strategy of the adaptive adjustment signal.

[0021] In this way, the effects of the modulation and coding strategy and the number of data streams on the throughput are comprehensively considered, so that the throughput curve conforms to the rule that the transmitter adjusts the modulation and coding strategy of the signal and the number of signal data streams according to the signal transmission quality, thereby improving the accuracy of the throughput curve obtained by the test.

[0022] Optionally, obtaining a third throughput curve based on multiple second throughput curves includes: normalizing the multiple second throughput curves to obtain multiple normalized second throughput curves; selecting the maximum throughput under the same signal-to-noise ratio from the multiple normalized second throughput curves to obtain a throughput curve corresponding to the first channel transmission matrix.

[0023] In this way, the throughput curves corresponding to the adaptive modulation and coding strategies under different numbers of data streams are normalized. The normalization process can map the data to a range of 0 to 1 for processing, thereby simplifying the calculation and improving the processing speed.

[0024] Optionally, there are N receiving antennas and the number of data streams is M; multiple first throughput curves are obtained according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, including: obtaining the throughput corresponding to each receiving antenna according to multiple randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna; sorting the throughputs corresponding to the N receiving antennas; selecting the throughputs corresponding to the M receiving antennas before sorting and superimposing them to obtain the first throughput curve corresponding to the number of data streams is M.

[0025] In this way, a receiving antenna with better antenna performance is selected to receive signals, 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, the throughput rate corresponding to each receiving antenna is obtained according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna, including: obtaining the channel coefficient of the sampling point corresponding to each receiving antenna according to multiple randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna; obtaining the 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 the 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, wherein the threshold is the minimum signal-to-noise ratio corresponding to the successful demodulation signal of the receiving end.

[0027] In this way, the throughput rate can be calculated 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 sth transmitting antenna to the uth receiving antenna; h u，s，n is the channel coefficient of the nth cluster from the sth transmitting antenna to the uth receiving antenna; h u，s，n satisfy: Among them, P n is the power of the nth cluster; M is the number of subpaths in each cluster; is the radiation pattern of the sth 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 arrival angle of the mth subpath of the nth cluster, respectively; is the position vector of the sth transmitting antenna; is the position vector of the uth receiving antenna; λ is the wavelength of the electromagnetic wave; τ n is the delay of the nth cluster; f is the carrier frequency; ν n，m is the Doppler shift of the mth subpath of the nth cluster; P n ,M, λ、τ n , f, ν n，m All 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. Among them, h i x i Represents the signal received by the i-th stream data at the receiving end, ∑ j≠i h j x j represents the interference of all other streams to the i-th stream, n is the interference noise when the receiving end receives the i-th stream data; the signal-to-noise ratio of the i-th stream data satisfies: in, H H The superscript H in [X] indicates the conjugate transpose. i，irepresents the i-th diagonal term of the matrix, 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 of the receiving end satisfies: in, N T is the number of transmitting antennas, γ th is the threshold value, F represents the Under the condition γ th The cumulative distribution function, T put，max is the maximum throughput of the receiving end. In this way, the throughput of the receiving end can be obtained by the above formula.

[0029] In a second aspect, an embodiment of the present application provides an antenna testing device, which can be applied to a terminal device, or a chip or chip system in a terminal device, etc.

[0030] The antenna testing device comprises: a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, so that the antenna testing device performs the method of the first aspect.

[0031] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the method of the first aspect is implemented.

[0032] In a fourth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed, the computer executes the method of the first aspect.

[0033] In a fifth aspect, an embodiment of the present application provides a chip, the chip including a processor, the processor being used to call a computer program in a memory to execute the method described in the first aspect.

[0034] It should be understood that the second to fifth aspects of the present application correspond to the technical solutions of the first aspect of the present application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation methods are similar and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of a test scenario in a possible design;

[0036] Figure 2 A schematic diagram of an antenna testing method provided in an embodiment of the present application;

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

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

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

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

[0041] Figure 7 A schematic diagram of a throughput curve corresponding to the number of adaptive data streams provided in an embodiment of the present application;

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

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

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

[0045] 1. Antenna: A type of transducer. Antennas can radiate electromagnetic waves to the outside world and also receive electromagnetic waves from the outside world.

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

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

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

[0049] Modulation scheme refers to the digital modulation method and the modulation order. Modulation schemes include: quadrature phase shift keying (QPSK), 16-quadrature amplitude modulation (QAM), 64QAM and 256QAM. QPSK can transmit 2 bits per RE, 16QAM can transmit 4 bits, 64QAM can transmit 6 bits, and 256QAM can transmit 8 bits.

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

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

[0052] Exemplarily, Table 1 shows a possible correspondence between different MCS indexes and modulation orders, target code rates, and spectrum efficiency.

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

[0054]

[0055]

[0056] It should be noted that MCS depends on the signal quality in the wireless link. If the signal quality is better, more bits can be used to transmit data in one symbol. If the signal quality is poor, the lower the MCS, the fewer bits can be used to transmit data in one symbol.

[0057] The value of MCS depends on the block error rate (BLER), which is usually defined as a threshold of 10%. In order to keep the BLER below this value in different wireless environments, the gNB allocates an MCS based on the link adaptation algorithm and sends it to the terminal device through downlink control signaling (DCI) on the physical downlink control channel (PDCCH).

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

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

[0060] 7. Signal to noise ratio (SNR): refers to the ratio of signal to noise in an electronic device or electronic system. The unit of measurement for SNR is decibel (dB).

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

[0062] In digital communications, It is the receiver demodulation threshold, also known as the bit signal-to-noise ratio.

[0063] 8. Block Error Rate (BLER): It is an indicator to measure the accuracy of data transmission within a specified time. There is a corresponding relationship between the block error rate (BLER) and the simulated signal-to-noise ratio (SNR). As the signal-to-noise ratio increases, the block error rate decreases.

[0064] 9. Other terms

[0065] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same or similar items with substantially the same functions and effects. For example, the first chip and the second chip are only used to distinguish different chips, and their order is not limited. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0066] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0067] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, a--c, bc, or abc, where a, b, c can be single or multiple.

[0068] In the embodiment of the present application, "at..." can be the instant when a certain situation occurs, or can be a period of time after a certain situation occurs, and the embodiment of the present application does not specifically limit this. In addition, the interface of the terminal device provided in the embodiment of the present application is only an example, and the interface can also include more or less content.

[0069] 10. Terminal equipment

[0070] The terminal device of the embodiment of the present application may also be any form of electronic device. For example, the electronic device may include a handheld device with communication function, a vehicle-mounted device, etc. For example, some electronic devices are: mobile phones, tablet computers, PDAs, laptop computers, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, vehicle-mounted devices, wearable devices, terminal devices in 5G networks or future evolved public land mobile communication networks (public land mobile The embodiments of the present application do not limit this.

[0071] As an example but not limitation, in the embodiments of the present application, the electronic device may also be a wearable device. Wearable devices may also be referred to as wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also powerful functions achieved through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include full-featured, large-sized, and fully or partially independent of smartphones, such as smart watches or smart glasses, as well as devices that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various types of smart bracelets and smart jewelry for vital sign monitoring.

[0072] In addition, in the embodiments of the present application, the electronic device can also be a terminal device in the Internet of Things (IoT) system. IoT is an important part of the future development of information technology. Its main technical feature is to connect objects to the network through communication technology, thereby realizing an intelligent network that interconnects people and machines and things.

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

[0074] In an embodiment 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 hardware such as a central processing unit (CPU), a memory management unit (MMU), and a memory (also called main memory). 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. The application layer includes applications such as browsers, address books, word processing software, and instant messaging software.

[0075] MIMO communication technology uses a multi-antenna system to achieve simultaneous transmission of multiple code streams and increase the communication rate. Currently, the multiple-input multiple-output (MIMO) of terminal equipment can be tested in many ways, such as over the air (OTA) and conduction.

[0076] However, both testing methods require testing of the entity of the terminal device. This method cannot be used to predict performance during the design phase of the terminal device, which results in a high risk in the design of the terminal device.

[0077] When using OTA testing, one end of the channel emulator is connected through a base station or a base station simulator, and the other end of the channel emulator is connected to a multi-probe darkroom for testing.

[0078] For example, Figure 1 Figure 1 is a schematic diagram of a possible test scenario in the design. Figure 1 As shown, a base station simulator 101 is connected to a channel emulator 102, and the channel emulator 102 is connected to a plurality of antennas 104 built in an OTA darkroom 103. The terminal device is placed at the center of the OTA darkroom 103.

[0079] The base station simulator 101 and the channel emulator 102 control the antenna 104 to transmit the radio frequency signal, so that the radio frequency signal reaching the terminal device 105 conforms to the description of the channel model, so as to perform a throughput test on the terminal device 105 .

[0080] also, Figure 1 The test shown is a test of the terminal device 105 as a whole. The throughput of the terminal device 105 measured is affected by many factors such as the internal radiation interference of the terminal device, the product structure of the terminal device, the directivity of the antenna, the differences between multiple antennas, the transceiver algorithm of the RF chip, etc. Therefore, Figure 1 The throughput measured in the test method shown cannot be associated with antenna indicators such as the directivity of the antenna in the terminal device 105 and the 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 and installed before testing, which takes a long time and is inefficient.

[0081] When conducting the test, one end of the channel emulator is connected to the base station or base station simulator, and the other end of the channel emulator is connected to the RF chip in the terminal device for testing.

[0082] In this method, the channel emulator is directly connected to the RF chip of the terminal device, and the throughput rate obtained by the test is related to the signal transmission performance in the RF chip. Since the signal is not received through the antenna of the terminal device in this method, the throughput rate obtained by the test is irrelevant to the performance of the antenna receiving signal, and the performance of the antenna of the terminal device cannot be tested.

[0083] In view of this, the embodiments of the present application provide an antenna testing method and related devices. The radiation pattern of a real antenna is coupled with a channel model to simulate the scenario of the antenna receiving a signal of a terminal device, and the design evaluation of the antenna is realized by simulation. In this way, the performance of the terminal device can be tested during the antenna design stage without using a physical antenna, which reduces the design risk and improves the development speed.

[0084] In addition, in the embodiments of the present application, the antenna performance is characterized by the throughput rate, and the method of characterizing the antenna performance by the throughput rate is more in line with the law of signal transmission changes in actual usage scenarios.

[0085] The following specific embodiments are used to describe in detail the technical solution of the present application and how the technical solution of the present application solves the above technical problems. The following specific embodiments can be implemented independently or in combination with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0086] For example, Figure 2 A schematic diagram of an antenna testing method provided in an embodiment of the present application. Figure 2 As shown, the method includes:

[0087] S201. Obtain antenna information of the transmitting end.

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

[0089] In the embodiment of the present application, the antenna information of the transmitting end is used to determine the gain information of each transmitting antenna in each direction, as well as related information such as the phase offset information of the same signal transmitted in each direction by any two transmitting antennas.

[0090] In some embodiments, the antenna information of the transmitting end obtained by the test 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 or a directional antenna, etc., which is not limited here. The parameters of the transmitting antenna include: the structure of the transmitting antenna, polarization discrimination, correlation coefficient (envelop correlation coefficient, ECC), isolation, antenna efficiency, operating frequency and other data. The layout of the transmitting antenna includes: the relative position of each transmitting antenna. The transmitting antenna can be a virtual antenna or a physical antenna, which is not limited here.

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

[0092] In other embodiments, the antenna information of the transmitting end obtained by the test software may also be the radiation pattern of each transmitting antenna, or the OTA direction file of the transmitting antenna input by the user, etc. The embodiment of the present application does not limit the method for obtaining the antenna information.

[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, and antenna position. The test software can coordinate map the OTA direction data in the antenna simulation OTA direction file to convert the OTA direction data in rectangular coordinates (CST format) into OTA direction data in polar coordinate format to obtain the radiation pattern of each transmitting antenna.

[0094] The radiation pattern of the transmitting antenna obtained by the test software may be a radiation pattern of the transmitting antenna generated by simulation, or may be a radiation pattern of the transmitting antenna obtained by actual measurement, and this application does not limit this.

[0095] S202: Obtain information of a channel model.

[0096] In the embodiment of the present application, the channel model is used to represent the signal transmission channel from the transmitting antenna to the receiving antenna. The test software can confirm the transmission channel of the signal according to the channel model, thereby confirming the fading and delay of the signal transmission. The channel model includes factors such as the spatial correlation of the signal (for example, reflection, diffraction, etc.), Doppler, and delay.

[0097] In an embodiment of the present application, the information of the channel model is used to determine the channel model used for antenna testing, as well as channel parameter data. The channel parameters include interference, fading, signal strength and environmental parameters of each signal propagation path. The environmental parameters of each signal propagation path include the departure angle Φ, arrival angle ψ, delay τ and other parameters of the signal propagation path.

[0098] Exemplarily, the channel model can be divided into: clustered delay line model (CDL), tapped delay line model (TDL), QuaDriga channel model, and channel model collected using a channel acquisition device, etc. The embodiments of the present application do not specifically limit the type of channel model.

[0099] The channel model used in the antenna test 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 embodiments of the present application. For example, the user can input the typical channel model collected by the channel acquisition device into the test software to perform a throughput test under the channel model.

[0100] In some embodiments, the channel model used in the antenna test can be determined by the scene information of the receiving end input by the user, for example, indoors, outdoors, suburbs, etc. The test software can determine the type of channel model required for the test and the corresponding channel parameters based on the scene information of the receiving end. Exemplarily, when the receiving end is indoors, the CDL channel model can be used; when the receiving end is outdoors, the QuaDriga channel model can be used; when the receiving end is in an open scene such as the suburbs, the channel model collected by the channel collection device in the open scene can be used. The embodiments of the present application do not specifically limit the channel model, scene, etc.

[0101] The channel parameter data may be channel parameter data input by the user in the test software, or may be channel parameter data selected by the user from one or more sets of pre-stored channel parameter data. The embodiment of the present application does not specifically limit the method for obtaining the channel parameter data.

[0102] S203: Obtain antenna information of the receiving end.

[0103] The receiving end is a terminal device to be tested. In the embodiment of the present application, the antenna information of the receiving end is the antenna information of the physical antenna of the simulated terminal device to be tested. 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, so as to facilitate the subsequent evaluation of the antenna design of the terminal device to be tested.

[0104] In the embodiment of the present application, the antenna information of the receiving end is used to determine the gain information of each receiving antenna in each direction of the terminal device to be tested, as well as the phase offset information of the same signal transmitted in each direction by any two receiving antennas and other related information. 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, etc. 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 or a directional antenna, etc., which is not limited here. The parameters of the receiving antenna include: the structure of the receiving antenna, polarization discrimination rate, correlation coefficient (envelopcorrelation coefficient, ECC), isolation, antenna efficiency, operating frequency and other data. The layout of the receiving antenna includes: the relative position of each receiving antenna.

[0106] In a possible implementation, the test software can obtain the radiation pattern of each receiving antenna according to the parameters of the receiving end antenna input by the user, such as type, layout, number of receptions, etc.

[0107] In other embodiments, the antenna information of the receiving end obtained by the test software may also be the radiation pattern of each receiving antenna, or the OTA direction file of the receiving antenna input by the user, etc. The embodiment of the present application does not limit the method for obtaining the antenna information.

[0108] The radiation pattern of the receiving antenna may be a radiation pattern of the receiving antenna generated by simulation, or may be a radiation pattern of the receiving antenna obtained by actual measurement, which is not limited in the present application.

[0109] S204: Obtain a throughput 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 curve is used to represent the throughput of the receiving end under different signal-to-noise ratios.

[0110] In the embodiment of the present application, the throughput curve is used to represent the corresponding relationship between the throughput and the signal-to-noise ratio. Figure 5 The figure shows a test curve diagram of throughput and signal-to-noise ratio under a fixed modulation and coding strategy.

[0111] It is understandable that the embodiment of the present application can obtain the throughput of the receiving end by any possible calculation method, which is not limited here. Exemplarily, taking the signal transmission probability under different signal-to-noise ratios obtained through multiple sampling points as an example, the test software can randomly generate multiple sampling points, and perform statistics on the signal-to-noise ratio of each sampling point based on 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), and multiply the theoretical throughput by the probability to obtain the throughput of signal transmission under different signal-to-noise ratios, and obtain the throughput curve of the receiving end. The theoretical throughput is the throughput when the sampling point successfully transmits the signal.

[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 a NT×NR MIMO system, the signal propagation formula can be expressed as follows: y=Hx+n. Where 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 present during reception, which can also be called 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, S transmitting antennas as roots, and U receiving antennas as an example, the channel transmission matrix includes: channel coefficients from the transmitting antenna to the receiving antenna. h 1，1 h represents the channel coefficient from the first transmitting antenna to the second receiving antenna after spatial fading;u，1 represents the channel coefficient from the first transmitting antenna to the uth receiving antenna after spatial fading; h 1，s represents the channel coefficient from the sth transmitting antenna to the first receiving antenna after spatial fading; h u，s It represents the channel coefficient from the sth transmitting antenna to the uth receiving antenna after spatial fading.

[0115] The channel coefficient between the sth transmitting antenna and the uth receiving antenna is: u，s x s Taking the channel model as CDL 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). For example, Figure 3 As shown, the channel coefficient of the nth cluster from the sth transmitting antenna to the uth receiving antenna is:

[0116] Among them, P n is the power of the nth cluster; M is the number of subpaths in each cluster; represents the radiation pattern of the sth transmitting antenna; represents the radiation pattern of the u-th receiving antenna; Indicates antenna OTA.

[0117] is a random initial phase; and are the spherical unit vectors of the departure angle and arrival angle of the mth subpath of the nth cluster, respectively; is the position vector of the sth transmitting antenna; is the position vector of the u-th receiving antenna; Represents spatial correlation.

[0118] λ is the wavelength of the electromagnetic wave; τ n is the delay of the nth cluster; f is the carrier frequency; v n，m is the Doppler frequency shift of the mth subpath of the nth cluster, which depends on the radial motion speed of the receiving end relative to the direction of the incoming wave and the frequency. n ) indicates the delay.

[0119] The signal energy received by the receiving antenna can be obtained by the above signal propagation formula. The following is an explanation of the calculation of the signal-to-noise ratio.

[0120] It is understandable that in an open-loop MIMO system with full spatial multiplexing, each receiving antenna can receive multiple signals from multiple transmitting antennas. The receiving antenna may receive a first signal and a second signal, and the second signal may 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] For example, Figure 4 A signal transmission schematic diagram provided in an embodiment of the present application. Figure 4 As shown, there are four transmitting antennas, namely T1, T2, T3, and T4; there are four receiving antennas, namely R1, T2, R3, and R4.

[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; T4 transmits the fourth stream data to R4. R1 also receives the second, third and fourth stream data. The second, third and fourth stream data interfere with the first stream data received by R1.

[0123] Therefore, for an open-loop MIMO system with full spatial multiplexing, the signal propagation formula can be expressed as follows: y = h i x i +∑ j≠ i h j x j +n. Among them, 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 Right now It can also be expressed as in, H H The superscript H in [X] indicates the conjugate transpose. i，i represents the i-th diagonal term of the matrix, and I represents the identity 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. When the signal-to-noise ratio of the signal is less than the threshold, the receiving end fails to demodulate the signal. th ) can also be called the error block SNR threshold, which is not limited here.

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

[0126] In an embodiment of the present application, the test software can randomly generate multiple sampling points according to the channel model and the radiation pattern of the receiving antenna, and perform statistics on the reception conditions of the signals corresponding to the multiple sampling points to obtain the distribution probability of the sampling points under different signal-to-noise ratios; and obtain the throughput of the receiving antenna under different signal-to-noise ratios based on the probability and the maximum throughput of the signal.

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

[0128] In the case of a fixed modulation and coding strategy, the throughput rate of the i-th stream data is: the product of the maximum throughput rate of the i-th stream data and the probability of successful signal demodulation, that is, γ i is the instantaneous signal-to-noise ratio of the i-th stream data; is the average signal-to-noise ratio of the i-th stream data.

[0129] It is understandable that the throughput rate of the terminal device T put is the sum of the throughput rates of all data flows, that is: in, N T is the number of transmit antennas, γ th represents the threshold value, Indicates that in a given Under the condition γ th The probability density distribution (CDF) of put，max It indicates the maximum throughput rate given by the system, which can also be called the theoretical maximum throughput rate.

[0130] It is understandable that due to the different positions and parameters of the receiving antennas, different receiving antennas may have different throughput rates for signals; in the embodiment of the present application, the test software samples each receiving antenna to obtain the throughput rate corresponding to each receiving antenna; and then the throughput rates corresponding to each receiving antenna are superimposed to obtain the throughput rate of the receiving end.

[0131] Exemplarily, the test software can randomly generate multiple sampling points based on the channel model and radiation pattern, and perform statistics on the signal-to-noise ratio of the multiple sampling points to obtain a throughput curve corresponding to each receiving antenna; subsequently, the throughput curve corresponding to each receiving antenna is superimposed to obtain the throughput curve of the receiving end.

[0132] The above embodiment illustrates the calculation process of the throughput rate of the receiving end. The throughput rate may 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 may 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 signal-to-noise ratio requirement for the signal.

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

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

[0135] In other embodiments, the test software may obtain and process the throughput curve corresponding to each modulation and coding strategy to obtain the throughput curve corresponding to the adaptive modulation and coding strategy.

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

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

[0138] In this way, considering the scenario where the transmitter may adaptively adjust the modulation and coding strategy of the signal, the throughput curve corresponding to the adaptive modulation and coding strategy obtained by the test software is more in line with the antenna performance in the actual usage scenario of the receiver, thereby improving the accuracy of the antenna performance evaluation.

[0139] It is understandable that the embodiment of the present application can obtain the throughput curve corresponding to the adaptive modulation and coding strategy by any possible calculation method, which is not limited here. Exemplarily, the maximum value of the throughput under the same signal-to-noise ratio can be directly selected from the throughput curve corresponding to each modulation and coding strategy to obtain the throughput curve corresponding to the adaptive modulation and coding strategy.

[0140] In some embodiments, the test software can normalize the throughput curve corresponding to each modulation and coding strategy. And select the maximum value of the throughput under the same signal-to-noise ratio from the normalized throughput curve corresponding to each modulation and coding strategy to obtain the throughput curve corresponding to the adaptive modulation and coding strategy. In this way, the normalization process can map the data to the range of 0 to 1 for processing, simplify the calculation, and improve the processing speed.

[0141] Exemplarily, the maximum value in the first throughput curve corresponding to when the MCS order is 27 is selected to normalize the throughput curve corresponding to each modulation and coding strategy; that is, the throughput curve corresponding to each modulation and coding strategy is divided by the first value, and the first value is the maximum throughput in the throughput curve corresponding to when the MCS order is 27.

[0142] Exemplarily, taking the throughput curve corresponding to each modulation and coding strategy as the first throughput curve and the throughput curve corresponding to the adaptive modulation and coding strategy as the second throughput curve as an example, Figure 6 As shown, the first throughput curve can be Figure 6 As shown by line 601 in FIG. 1 . The test software can select the maximum throughput under the same signal-to-noise ratio from multiple first throughput curves, and the obtained second throughput curve can be as follows: Figure 6 As shown by line 602 in FIG.

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

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

[0145] In some embodiments, the testing software calculates the throughput of the receiving end with a fixed number of data streams and outputs a corresponding throughput curve.

[0146] Exemplarily, the test software takes 4-stream data as an example, calculates the throughput of the receiving end, and outputs the corresponding throughput curve.

[0147] In some other embodiments, the test software may obtain and process throughput curves corresponding to different numbers of data streams to obtain a throughput curve corresponding to the number of data streams of the adaptive adjustment signal.

[0148] It is understandable that the embodiment of the present application can obtain the throughput curve corresponding to the number of data streams of the adaptive adjustment signal by any possible calculation method, which is not limited here. Exemplarily, the maximum value of the throughput under the same signal-to-noise ratio can be directly selected from the throughput curve corresponding to the number of data streams of each signal to obtain the throughput curve corresponding to the number of data streams of the adaptive adjustment signal.

[0149] In some embodiments, the test software can obtain the throughput curve corresponding to the adaptive modulation and coding strategy under multiple numbers of data streams, and process it to obtain the throughput curve of the number of data streams of the adaptive modulation and coding strategy adaptively adjusting the signal. The number of data streams of the adaptively adjusted signal can also be called adaptive hierarchical multiplexing, or the number of adaptive antennas, which is not limited here. In this way, taking into account factors such as the base station adjusting the modulation and coding strategy and hierarchical multiplexing, the throughput curve obtained by the test conforms to the law of actual signal transmission, thereby improving the accuracy of the test results.

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

[0151] For example, take 4 data streams as an example. Figure 7 As shown, the second throughput curve after normalization can be as follows Figure 7 As shown by line 701 in FIG. 1 . The test software can select the maximum throughput under the same signal-to-noise ratio from multiple second throughput curves, and the obtained third throughput curve can be as follows: Figure 7 As shown by line 702 in FIG.

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

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

[0154] Exemplarily, taking four receiving antennas, namely antenna 1, antenna 2, antenna 3, and antenna 4 as an example, if the antenna performance is arranged from large to small as antenna 1, antenna 2, antenna 3, and antenna 4; when the data stream is 1, antenna 1 is selected to receive the signal, and a first throughput curve is generated according to the throughput corresponding to antenna 1; when the data stream is 2, antenna 1 and antenna 2 are selected to receive the signal, and a first throughput curve is generated according to the throughput corresponding to antenna 1 and the throughput corresponding to antenna 2; when the data stream is 3, antenna 1, antenna 2, and antenna 3 are selected to receive the signal, and a first throughput curve is generated according to the throughput corresponding to antenna 1, the throughput corresponding to antenna 2, and the throughput corresponding to antenna 3; when the data stream is 4, a first throughput curve is generated according to the throughput corresponding to antenna 1, the throughput corresponding to antenna 2, the throughput corresponding to antenna 3, and the throughput corresponding to antenna 4.

[0155] In this way, the test software can select a receiving antenna with better receiving performance for performance evaluation, so that the first throughput curve is more in line with the scenario of using an antenna with better performance for signal reception, thereby improving the accuracy of the evaluation result.

[0156] Based on the above embodiments, the test software can randomly generate multiple sampling points under the same posture of the receiving end to perform antenna testing and generate a throughput curve; the test software can also randomly generate multiple sampling points under multiple postures of the receiving end to perform antenna testing and generate multiple throughput curves.

[0157] In this way, multiple throughput curves can reflect the antenna performance of the receiving end in different postures, which is convenient for subsequent comparative analysis of antenna performance.

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

[0159] Exemplarily, the test software may traverse multiple postures of the receiving end and randomly generate multiple sampling points, which can also be understood as simulating the rotation of the receiving end and randomly generating multiple sampling points.

[0160] It is understandable 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 in different postures. The angle of the radiation pattern of the receiving antenna refers to the angle (or pointing angle) of rotation of the radiation pattern relative to the channel model. Exemplarily, the test software can obtain the radiation pattern at multiple angles based on the radiation pattern at the first angle.

[0161] For example, the radiation patterns of the receiving antennas corresponding to different postures are different. Taking the calculation of the channel coefficients in the above CDL model as an example, the radiation patterns of the receiving antennas corresponding to different postures are different. different.

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

[0163] In the above embodiment, the test software can obtain one or more channel models. When the test software obtains a channel model, the signal-to-noise ratio can be calculated through the signal model, and the throughput curve corresponding to the channel model can be output; when the test software obtains multiple channel models, the signal-to-noise ratio can be calculated through each signal model, and the throughput curve corresponding to each channel model can be output. In this way, the test software can output multiple throughput curves, which can reflect the antenna performance of the receiving end under different channel environments, and facilitate subsequent comparative analysis.

[0164] It is understandable that different channel models correspond to different signal transmission path distributions. Different channel models correspond to different departure angles and arrival angles. Taking the above CDL model as an example, different channel models correspond to and different.

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

[0166] In the embodiment of the present application, the information testing software of multiple channel models can obtain multiple channel models at one time, or can obtain the multiple channel models in multiple times, which is not limited here.

[0167] Based on the above embodiment, the test software can use one channel model to test the antenna and output a throughput curve; it can also use multiple channel models to test the antenna.

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

[0169] 2041. Calculate a 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 refer to the corresponding description above, which will not be repeated here.

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

[0172] The calculation process of the signal-to-noise ratio can refer to the corresponding description above and will not be repeated here.

[0173] S2043. Obtain a throughput curve according to the first algorithm and the second algorithm.

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

[0175] Exemplarily, the first algorithm is used to realize that the throughput when the MCS order is 27 is regarded as the maximum throughput (that is, 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 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 then the throughput curve is compressed according to the normalized maximum relative throughput calculated for different MCS orders, 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, and calculate the relative throughput curve when their adaptive MCS is used. Finally, the 4 new throughput curves are taken as the maximum, and finally the throughput curve of the number of data streams that takes into account both the adaptive MCS and the adaptive adjustment signal is obtained.

[0177] The throughput curve is used to indicate the relationship between the maximum throughput corresponding to the receiving antenna in multiple modulation and coding strategies, multiple data stream numbers, and the signal-to-noise ratio. The specific process can refer to the third throughput curve above, which will not be repeated here.

[0178] In this way, the signal transmission process can be simulated to evaluate the antenna performance of the terminal device. The antenna performance can be evaluated during the design phase of the terminal device to reduce design risks and increase development speed. In addition, considering factors such as base station adjustment of modulation and coding strategies and hierarchical multiplexing, the throughput curve obtained by the test conforms to the law of actual signal transmission, thereby improving the accuracy of the test results.

[0179] It is understandable that in the above embodiment, the antenna performance is characterized by a throughput curve. The test software can also characterize the antenna performance by the throughput within a preset time. The above throughput curve describes the throughput with the signal-to-noise ratio as the horizontal axis, and the signal-to-noise ratio can also be replaced by signal strength, etc. The embodiment of the present application does not specifically limit the way in which the test software characterizes the antenna performance.

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

[0181] The test software can also perform performance analysis based on the throughput curve corresponding to each design solution.

[0182] Exemplarily, the test software may also output a target design solution according to a throughput curve corresponding to each design solution, and the target design solution is used to debug the antenna at the receiving end.

[0183] The embodiment of the present application does not specifically limit the process and method of performance analysis of the throughput curve.

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

[0185] In the above embodiment, a throughput curve is used to characterize the antenna performance of the receiving end. The test software may also use a throughput curve to characterize the antenna performance of the receiving end. The specific calculation process is similar to the above throughput curve calculation process and will not be repeated here.

[0186] The method provided in the embodiment of the present application has been described above, and the device for executing the above method provided in the embodiment 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 relevant device provided in the embodiment of the present application can execute the steps in the above method.

[0187] For example, Figure 8 A schematic diagram of the structure of an antenna testing device provided in an embodiment of the present application. The antenna testing device may be an electronic device in an embodiment of the present application, or may be a partial component in an electronic device, such as a chip or a chip system.

[0188] like Figure 8 As shown, the antenna test device can be used in communication equipment, circuits, hardware components or chips. The antenna test device includes: a communication unit 901, a processing unit 902, a display unit 903, etc. The communication unit 901 is used to obtain a channel model and a radiation pattern of each receiving antenna in the receiving end; the processing unit 902 is used to obtain a throughput curve of the receiving end according to the channel model and the radiation pattern of each receiving antenna; the display unit 903 is used to display the throughput of the receiving end.

[0189] The communication unit 901 is used to support the antenna test device to interact with other devices. Exemplarily, when the antenna test device is a terminal device, the communication unit 901 can be a communication interface or an interface circuit. When the antenna test 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 may be integrated together, and the processing unit 902 and the display unit 903 may communicate with each other.

[0191] In a possible implementation, the antenna testing device may further include: a storage unit 904. The storage unit 904 may include one or more memories, and the memory may be a device in one or more devices or circuits for storing programs or data.

[0192] The storage unit 904 may exist independently and be connected to the processing unit 902 via a communication bus. The storage unit 904 may also be integrated with the processing unit 902.

[0193] Taking the antenna testing device as an example, which can be a chip or chip system of a terminal device in an embodiment of the present application, the storage unit 904 can store computer execution instructions of the method of the terminal device so that the processing unit 902 executes the above antenna testing method. The storage unit 904 can be a register, a cache, or a random access memory (RAM), etc. 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 1304 can be independent of the processing unit 902.

[0194] The device of this embodiment can be used to execute the steps executed in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail here.

[0195] An embodiment of the present application provides an antenna testing device, which includes: a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, so that the antenna testing device performs the above method.

[0196] For example, Fig. 9 This is a schematic diagram of the structure of an antenna testing device provided in an embodiment of the present application. Fig. 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, the processor 1002, the interface circuit 1003 and the display screen 1004 can communicate; illustratively, the memory 1001, the processor 1002, the interface circuit 1003 and the display screen 1004 can communicate through a communication bus, the memory 1001 is used to store computer execution instructions, the execution is controlled by the processor 1002, and the communication is performed by the interface circuit 1003, so as to realize the antenna testing method provided in the embodiment of the present application.

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

[0198] In a possible implementation, the computer-executable instructions in the embodiments of the present application may 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 in the embodiment of the present application is used to execute the antenna testing method of the above embodiment. The technical principles and technical effects are similar and will not be repeated here.

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

[0201] The embodiment of the present application provides a chip. The chip includes a processor, and the processor is used to call a computer program in a memory to execute the technical solution in the above embodiment. Its implementation principle and technical effect are similar to those of the above related embodiments, and will not be repeated here.

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

[0203] In one possible implementation, a computer-readable medium may include RAM, ROM, compact disc read-only memory (CD-ROM) or other optical disk storage, disk storage or other magnetic storage devices, or any other medium that is intended to carry or store the required program code in the form of instructions or data structures and can be accessed by a computer. Moreover, any connection is appropriately referred to as a computer-readable medium. For example, if a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) or wireless technology (such as infrared, radio and microwave) is used to transmit software from a website, server or other remote source, the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technology such as infrared, radio and microwave are included in the definition of medium. Disks and optical disks as used herein include optical disks, laser disks, optical disks, digital versatile disks (DVD), floppy disks and Blu-ray disks, where disks usually reproduce data magnetically, while optical disks reproduce data optically using lasers. Combinations of the above should also be included in the scope of computer-readable media.

[0204] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed, the computer executes the above method.

[0205] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable device to generate a machine, so that the instructions executed by the processing unit of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0206] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0207] The above specific implementation methods further illustrate the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present invention should be included in the scope of protection of the present invention.

Claims

1. An antenna testing method, characterized in that: include: Acquire a channel model, a radiation pattern of a transmitting antenna at a transmitting end, and a radiation pattern of a receiving antenna at a receiving end, wherein the receiving antenna is a physical antenna; Obtaining a throughput 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 curve is used to characterize the antenna performance of the receiving end.

2. The method according to claim 1, characterized in that The obtaining the throughput 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 includes: Randomly generate a plurality of sampling points corresponding to the receiving antenna; Obtaining signal-to-noise ratios corresponding to the plurality of sampling points and throughput rates 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; The throughput curve is obtained according to the signal-to-noise ratios corresponding to the multiple sampling points and the throughput rates corresponding to the multiple sampling points. The throughput curve is used to represent the throughput rates of the receiving end under different signal-to-noise ratios.

3. The method according to claim 2, characterized in that The randomly generating a plurality of sampling points corresponding to the receiving antenna comprises: The plurality of sampling points are randomly generated in the same posture of the receiving end, and the throughput curve is used to indicate the antenna performance of the receiving end in the same posture; Alternatively, the multiple sampling points are randomly generated under multiple postures of the receiving end, and the throughput curve is used to indicate the antenna performance of the receiving end under the multiple postures.

4. The method according to claim 2 or 3, characterized in that: The channel model includes one or more channel models; When the channel model includes 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 includes multiple channel models, the throughput curve is used to indicate the antenna performance of the receiving end under the multiple channel models.

5. The method according to any one of claims 1 to 4, characterized in that: The obtaining the throughput 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 includes: A plurality of first throughput rate curves are obtained according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna, wherein the modulation and coding strategies of the signals corresponding to the plurality of first throughput rate curves are different, and / or the numbers of data streams of the signals corresponding to the plurality of first throughput rate curves are different; Obtaining one or more second throughput rate curves according to the multiple first throughput rate curves, wherein the second throughput rate curves are used to characterize the antenna performance of the receiving end under the modulation and coding strategy of the adaptively adjusted signal; When the second throughput curve is one, the second throughput curve is a throughput curve of the receiving end; When there are multiple second throughput curves, a third throughput curve is obtained according to the second throughput curve, and the third throughput curve is the throughput curve of the receiving end. The third throughput curve is used to characterize the antenna performance of the receiving end corresponding to the number of data streams of the adaptive adjustment signal under the modulation and coding strategy of the adaptive adjustment signal.

6. The method according to claim 5, characterized in that The obtaining one or more second throughput rate curves according to the multiple first throughput rate curves includes: Normalizing the plurality of first throughput curves of the signal under the same number of data streams to obtain a plurality of normalized first throughput curves of the signal under the same number of data streams; The maximum value of the throughput under the same signal-to-noise ratio is selected from the multiple normalized first throughput curves corresponding to the same number of data streams to obtain the second throughput curve.

7. The method according to claim 5 or 6, characterized in that: The numbers of data streams corresponding to the plurality of second throughput curves are different; and the method further comprises: A third throughput curve is obtained according to a plurality of the second throughput curves, and the third throughput curve is used to characterize the antenna performance of the receiving end corresponding to the number of data streams of the adaptively adjusted signal under the modulation and coding strategy of the adaptively adjusted signal.

8. The method according to claim 7, characterized in that The obtaining a third throughput curve according to the plurality of the second throughput curves comprises: Normalizing the plurality of the second throughput rate curves to obtain a plurality of normalized second throughput rate curves; The maximum value of the throughput under the same signal-to-noise ratio is selected from the plurality of normalized second throughput curves to obtain a throughput curve corresponding to the first channel transmission matrix.

9. The method according to any one of claims 5 to 8, characterized in that: The number of receiving antennas is N, and the number of data streams is M; The obtaining of a plurality of first throughput 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, a radiation pattern of the transmitting antenna, and a radiation pattern of the receiving antenna; Sorting the throughput rates corresponding to the N receiving antennas; The throughput rates corresponding to the M receiving end antennas before sorting are selected and superimposed to obtain the first throughput rate curve corresponding to when the number of the data streams is the M.

10. The method according to claim 9, characterized in that The obtaining, according to the channel model, the radiation pattern of the transmitting antenna, and the radiation pattern of the receiving antenna, a throughput rate corresponding to each receiving antenna includes: 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, a radiation pattern of the transmitting antenna, and a radiation pattern of the receiving antenna; Obtaining a signal-to-noise ratio of the sampling point corresponding to each receiving antenna according to a channel coefficient and a signal transmission formula of the sampling point corresponding to each receiving antenna; The throughput of each receiving antenna under different signal-to-noise ratios is obtained according to the signal-to-noise ratio of the sampling point corresponding to each receiving antenna and a threshold, wherein the threshold is a minimum signal-to-noise ratio corresponding to successful demodulation of the signal by the receiving end.

11. The method according to claim 10, characterized in that The channel coefficient of the sampling point corresponding to each receiving antenna satisfies: u,s =h u,s,1 (t,f)+…+h u,s,n (t,f); h u,s is the channel coefficient from the sth transmitting antenna to the uth receiving antenna; u,s,n is the channel coefficient of the nth cluster from the sth transmitting antenna to the uth receiving antenna; The h u,s,n satisfy: Among them, the P n is the power of the nth cluster; M is the number of subpaths in each cluster; is the radiation pattern of the sth transmitting antenna; represents the radiation pattern of the u-th receiving antenna; is a random initial phase; and stated are the spherical unit vectors of the departure angle and arrival angle of the mth subpath of the nth cluster respectively; is the position vector of the sth transmitting antenna; is the position vector of the uth receiving antenna; λ is the wavelength of the electromagnetic wave; τ n is the delay of the nth cluster; f is the carrier frequency; ν n,m is the Doppler shift of the mth subpath of the nth cluster; The P n 、the M、the Said Said The λ, the τ n , said f, said v n,m are all pre-acquired parameters of the channel model; The signal transmission formula satisfies: y=h i x i +∑ j≠i h j x j +n; where h i x i Represents the signal received by the i-th stream data at the receiving end, ∑ j≠i h j x j represents the interference of all other streams to the i-th stream, and n is the interference noise existing when the receiving end receives the i-th stream data; The signal-to-noise ratio of the i-th stream data satisfies: in, The H H The superscript H in [X] represents the conjugate transpose. i,i represents the i-th diagonal term of a matrix, the I represents a unit matrix of the same order, and the H represents a channel transmission matrix composed of channel coefficients for transmitting a signal from the transmitting antenna to the receiving antenna; The throughput rate of the receiving end satisfies: in, The N T is the number of transmitting antennas, the γ th is the threshold value, and F represents the Under the condition γ th The cumulative distribution function, T put,max is the maximum throughput of the receiving end.

12. An antenna testing device, characterized in that: include: Processor and memory; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the antenna testing device performs the method according to any one of claims 1 to 11.

13. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

14. A computer program product, characterized in that The invention comprises a computer program, which, when being executed, enables a computer to execute the method according to any one of claims 1 to 11.

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