Disclosure of Invention
The embodiment of the application provides an antenna testing method and a related device, which are applied to the technical field of terminals. And coupling the radiation pattern of the simulated entity antenna with the channel model to realize the scene of receiving signals by the antenna of the simulated receiving end. The design evaluation of the antenna is realized in a simulation mode, a physical antenna is not needed, the performance of the receiving end can be tested in the design stage of the antenna, the design risk is reduced, and the development speed is improved.
In a first aspect, an embodiment of the present application provides an antenna testing method. The method comprises the steps of obtaining a channel model, a radiation pattern of a transmitting antenna of a transmitting end and a radiation pattern of a receiving antenna of a receiving end, wherein the receiving antenna is a solid antenna, obtaining a throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, and the throughput rate curve is used for representing the antenna performance of the receiving end.
Therefore, the radiation pattern of the entity antenna of the analog receiving end can be obtained, and the radiation pattern is coupled with the channel model, so that the antenna performance of the receiving end is evaluated. The performance test can be carried out on the receiving end in the design stage of the antenna without adopting an entity antenna, so that the design risk is reduced, and the development speed is improved. In addition, the antenna performance is represented by the throughput rate, and compared with a mode of evaluating the antenna performance by superposing the channel capacity and the antenna capacity, the mode of representing the antenna performance by the throughput rate is more in accordance with the rule of signal transmission change in the actual use scene of the receiving end.
In the embodiment of the application, the radiation pattern of the receiving antenna may be a radiation pattern corresponding to the directional antenna, and compared with the radiation pattern of the omni-directional antenna, the radiation pattern corresponding to the directional antenna is more in accordance with the antenna design of the receiving end.
In some embodiments, all or part of the receive antennas radiate electromagnetic wave energy differently in all directions along the horizontal plane in the radiation pattern. Thus, the receiving antenna can be a directional antenna, which is beneficial to reducing interference among a plurality of receiving antennas, improving throughput rate of a receiving end, and the radiation pattern corresponding to the directional antenna is more in accordance with the antenna design of the receiving end.
Optionally, obtaining a throughput rate curve of the receiving end according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna comprises randomly generating a plurality of sampling points corresponding to the receiving antenna, obtaining signal-to-noise ratios corresponding to the sampling points and throughput rates corresponding to the sampling points according to the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, and obtaining the throughput rate curve according to the signal-to-noise ratios corresponding to the sampling points and the throughput rates corresponding to the sampling points, wherein the throughput rate curve is used for representing the throughput rates of the receiving end under different signal-to-noise ratios.
Therefore, the signal-to-noise ratio and the throughput rate can be calculated through a plurality of randomly selected sampling points, the change rule of analog signal transmission is met, and the accuracy of the throughput rate curve is improved.
Optionally, the step of randomly generating a plurality of sampling points corresponding to the receiving antenna comprises the step of randomly generating a plurality of sampling points under the same gesture of the receiving end, wherein a throughput rate curve is used for indicating the antenna performance of the receiving end under the same gesture, or the step of randomly generating a plurality of sampling points under the plurality of gestures of the receiving end, and the throughput rate curve is used for indicating the antenna performance of the receiving end under the plurality of gestures.
Thus, the throughput rate curve reflects the antenna performance of the receiving end in the same gesture when the sampling points are in the same gesture, and the throughput rate curve reflects the antenna performance of the receiving end in different gestures when the sampling points are in different gestures.
Optionally, the channel model comprises one or more channel models, the throughput rate curve is used for indicating the antenna performance of the receiving end under the same channel model when the channel model comprises one channel model, and the throughput rate curve is used for indicating the antenna performance of the receiving end under a plurality of channel models when the channel model comprises a plurality of channel models.
Thus, the throughput rate curve may reflect the antenna performance of the receiving end in a fixed channel environment, or the antenna performance in a different channel environment.
The method comprises the steps of obtaining a plurality of first throughput rate curves according to a channel model, a radiation pattern of a transmitting antenna and a radiation pattern of a receiving antenna, obtaining one or more second throughput rate curves according to the first throughput rate curves, wherein the 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, the third throughput rate curves are obtained according to the second throughput rate curves, and/or the data streams of the signals corresponding to the first throughput rate curves are different, the second throughput rate curves are obtained according to the first throughput rate curves, and are used for representing the antenna performance of the receiving terminal under the modulation coding strategy of the adaptive adjustment signal.
In this way, the influence of the modulation and coding strategy and/or the number of the data streams on the throughput rate is comprehensively considered, so that the throughput rate curve accords with the rule of adjusting the modulation and coding strategy of the signals and/or the number of the signal data streams according to the signal transmission quality by the transmitting end, and the accuracy of the throughput rate curve obtained by the test is improved.
Optionally, obtaining one or more second throughput rate curves according to the plurality of first throughput rate curves includes normalizing the plurality of first throughput rate curves of the signal under the same number of data streams to obtain a plurality of normalized first throughput rate curves of the signal under the same number of data streams, and selecting a maximum value of throughput rates under the same signal-to-noise ratio from the plurality of normalized first throughput rate curves corresponding to the same number of data streams to obtain a second throughput rate curve.
Therefore, the normalization processing is carried out on throughput rate curves corresponding to a plurality of modulation and coding strategies in the same number of data streams, the normalization processing can map the data to be processed within the range of 0-1, calculation is simplified, and processing speed is improved.
Optionally, the number of the data streams corresponding to the plurality of second throughput rate curves is different, and the method further comprises obtaining a third throughput rate curve according to the plurality of second throughput rate curves, wherein the third throughput rate curve is used for representing the antenna performance of a receiving end corresponding to the number of the data streams of the adaptive adjustment signal under the modulation coding strategy of the adaptive adjustment signal.
In this way, the influence of the modulation and coding strategy and the number of the data streams on the throughput rate is comprehensively considered, so that the throughput rate curve accords with the rule of adjusting the modulation and coding strategy of the signals and the number of the signal data streams according to the signal transmission quality by the transmitting end, and the accuracy of the throughput rate curve obtained by the test is improved.
Optionally, obtaining a third throughput rate curve according to the plurality of second throughput rate curves includes normalizing the plurality of second throughput rate curves to obtain a plurality of normalized second throughput rate curves, and selecting the maximum value of throughput rates under the same signal-to-noise ratio from the plurality of normalized second throughput rate curves to obtain a throughput rate curve corresponding to the first channel transmission matrix.
Therefore, the throughput rate curves corresponding to the adaptive modulation and coding strategies under different data streams are normalized, the data can be mapped to the range of 0-1 for processing through normalization, calculation is simplified, and processing speed is improved.
The method comprises the steps of obtaining a plurality of first throughput rate curves according to a channel model, a radiation pattern of a transmitting antenna and a radiation pattern of a receiving antenna, obtaining throughput rates corresponding to each receiving antenna according to a plurality of randomly generated sampling points, the channel model, the radiation pattern of the transmitting antenna and the radiation pattern of the receiving antenna, sorting the throughput rates corresponding to the N receiving antennas, and selecting and superposing the throughput rates corresponding to the M receiving end antennas before sorting to obtain the first throughput rate curves corresponding to the data streams with the number M.
Therefore, a receiving antenna with better antenna performance is selected to receive signals, the rule of receiving signals by the receiving end is met, and the accuracy of the throughput rate of the receiving end is improved.
The method comprises the steps of obtaining a channel coefficient of a sampling point corresponding to each receiving antenna according to a plurality of sampling points which are randomly generated, a channel model, a radiation pattern of a transmitting antenna and a radiation pattern of a receiving antenna, obtaining a signal-to-noise ratio of the sampling point corresponding to each receiving antenna according to the channel coefficient of the sampling point corresponding to each receiving antenna and a signal transmission formula, and obtaining throughput rates of each receiving antenna under different signal-to-noise ratios according to the signal-to-noise ratio of the sampling point corresponding to each receiving antenna and a threshold value, wherein the threshold value is the minimum signal-to-noise ratio corresponding to a successfully demodulated signal of a receiving terminal.
Thus, the calculation of the throughput rate can be realized through the channel coefficient and the signal transmission formula.
Optionally, the channel coefficient of the sampling point corresponding to each receiving antenna satisfies that hu,s＝hu,s,1(t,f)+…+hu,s,n(t,f);hu,s is the channel coefficient from the s-th transmitting antenna to the u-th receiving antenna, hu,s,n is the channel coefficient from the s-th transmitting antenna to the n-th cluster of the u-th receiving antenna, and hu,s,n satisfies that: wherein Pn is the power of the nth cluster, M is the number of sub-paths in each cluster; a radiation pattern for the s-th transmitting antenna; A radiation pattern representing the u-th receiving antenna; is a random initial phase; AndSpherical unit vectors of the departure angle and the arrival angle of the mth sub-path of the nth cluster respectively; Position vector for the s-th transmitting antenna; is the position vector of the u-th receiving antenna, lambda is the wavelength of electromagnetic wave, taun is the delay of the n-th cluster, f is the carrier frequency, vn,m is the Doppler shift of the M-th sub-path of the n-th cluster, Pn, M,Λ, τn、f、νn,m are parameters of a channel model acquired in advance, and the signal transmission formula satisfies that y=hixi+∑j≠ihjxj +n. Wherein hixi represents a signal received by the ith stream data of the receiving end, sigmaj≠ihjxj represents interference of all other streams to the ith stream, n is interference noise existing when the receiving end receives the ith stream data, and the signal-to-noise ratio of the ith stream data meets the following conditions: Wherein,The superscript H in HH represents conjugate transpose, [ X ]i,i represents the I-th diagonal term of the matrix, I represents the identity matrix of the same order, H represents the channel transmission matrix formed by the channel coefficients of the signal transmitted from the transmitting antenna to the receiving antenna, and the throughput rate of the receiving end meets the following conditions: Wherein,NT is the number of transmit antennas, gammath is the threshold, and F is expressed at a given timeThe cumulative distribution function of gammath under the condition of (a), Tput,max is the maximum throughput rate of the receiving end. Thus, the throughput rate of the receiving end can be obtained through the formula.
In a second aspect, an embodiment of the present application provides an antenna testing apparatus, where the antenna testing apparatus may be applied to a terminal device, or a chip system in the terminal device, or the like.
The antenna test apparatus comprises a processor and a memory, the memory storing computer-executable instructions, the processor executing the computer-executable instructions stored in the memory to cause the antenna test apparatus to perform a method as in the first aspect.
In a third aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program. The computer program, when executed by a processor, implements a method as in the first aspect.
In a fourth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when run, causes a computer to perform the method as in the first aspect.
In a fifth aspect, an embodiment of the present application provides a chip comprising a processor for invoking a computer program in a memory to perform a method according to the first aspect.
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 advantages obtained by each aspect and the corresponding possible embodiments are similar, and are not repeated.
Detailed Description
In order to facilitate the clear description of the technical solutions of the embodiments of the present application, the following simply describes some terms and techniques involved in the embodiments of the present application:
1. an antenna is a transducer. The antenna can radiate electromagnetic waves to the outside and can also receive the electromagnetic waves from the outside.
2. Radiation pattern-refers to a pattern of the relative field strength (normalized modulus) of the radiation field as a function of direction at a distance from the antenna, typically represented by two mutually perpendicular planar patterns in the maximum radiation direction through the antenna. The radiation pattern is an important figure for measuring the performance of the antenna, and various parameters of the antenna can be observed from the radiation pattern. The radiation pattern may also be referred to as an antenna pattern, an antenna radiation pattern, and is not limited herein.
3. Modulation coding strategy (modulation and coding scheme, MCS) the MCS defines the redundancy coding scheme and modulation scheme employed when carrying binary data within one resource element (rsource element, RE), i.e. the number of useful bits that can be carried in one RE. Currently, there are a total of 0-31 MCS schemes, with 29-31 reserved. The higher the MCS index, the higher the number of valid bits that can be carried in one RE.
The MCS defines two parts, modulation scheme (code rate).
The modulation scheme refers to the manner of digital modulation and the order of modulation. Modulation schemes include Quadrature PHASE SHIFT KEYING (QPSK), 16 quadrature amplitude modulation (quadrature amplitude modulation, QAM), 64QAM, 256QAM, and the like. QPSK may transmit 2 bits per RE, 16QAM may transmit 4 bits, 64QAM may transmit 6 bits, and 256QAM may transmit 8 bits.
4. The code rate is the ratio between useful bits and total transmitted bits (useful + redundant bits), i.e. the efficiency of redundant coding. The code rate is used to measure the redundancy added by the physical layer.
It should be noted that, in the wireless network, the signal transmission efficiency is measured by the spectrum efficiency. The spectrum efficiency refers to the ratio between the number of bits transmitted per unit time and the spectrum bandwidth used, and may reflect the efficiency of use of a signal in a specific frequency band.
By way of example, one possible correspondence of different indices of MCS to modulation order, target code rate and spectral efficiency is shown in table 1.
Table 1 table of correspondence between modulation order, target code rate and spectral efficiency
It should be noted that MCS depends on signal quality in the radio link, and if the signal quality is better, the more bits can be used for transmitting data in one symbol, and if the signal quality is poor, the lower the MCS, the fewer bits can be used for transmitting data in one symbol.
The value of MCS depends on the block error rate (blocker error rate, BLER), which is typically defined as a threshold of 10%, and in order to keep the BLER not to exceed this value in different radio environments, the base station (gNB) allocates one MCS according to the link adaptation algorithm and sends it to the terminal device via downlink control signaling (downlink control information, DCI) on the physical downlink control channel (physical downlink control channel, PDCCH) channel.
5. The cumulative distribution function (cumulative distribution function, CDF) is the integral of the probability density function.
6. Throughput rate, the number of information bits transmitted per unit time.
7. Signal to noise ratio (signal to interference plus noise ratio, SNR) refers to the ratio of signal to noise in an electronic device or electronic system. The unit of measure of signal-to-noise ratio is decibel (dB). In the case of an analog communication, the data processing system,
Where SNR is the dB form of S/N, eb is the energy of a signal per bit (bit), no is the power spectral density of noise, rb is the signaling rate (bits transmitted per second), and W is the bandwidth of the signal.
In the case of a digital communication system,For the receiver demodulation threshold, also known as bit signal to noise ratio.
8. Block error rate (BLER) is an indicator of how accurately data is transmitted over a specified time period. The block error rate ble has a corresponding relation with the simulated signal-to-noise ratio SNR, and the block error rate is continuously reduced along with the increase of the signal-to-noise ratio.
9. Other terms
In embodiments of the present application, the words "first," "second," and the like are used to distinguish between identical or similar items that have substantially the same function and effect. For example, the first chip and the second chip are merely for distinguishing different chips, and the order of the different chips is not limited. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.
It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or" describes an association of associated objects, meaning that there may be three relationships, e.g., A and/or B, and that there may be A alone, while A and B are present, and B alone, where A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (a, b, or c) of a, b, c, a-b, a-c, b-c, or a-b-c may be represented, wherein a, b, c may be single or plural.
In the embodiment of the present application, "when the case is" may be an instant when a certain condition occurs, or may be a period of time after a certain condition occurs, which is not particularly limited. In addition, the interface of the terminal device provided by the embodiment of the application is only used as an example, and the interface can also comprise more or less contents.
10. Terminal equipment
The terminal device of the embodiment of the application can also be any form of electronic device, for example, the electronic device can include a handheld device with a communication function, a vehicle-mounted device and the like. For example, some electronic devices are mobile phone, tablet, palm, notebook, mobile internet device (mobile INTERNET DEVICE, MID), wearable device, virtual Reality (VR) device, augmented reality (augmented reality, AR) device, wireless terminal in industrial control (industrial control), wireless terminal in unmanned (SELF DRIVING), wireless terminal in tele-surgery (remote medical surgery), wireless terminal in smart grid (SMART GRID), wireless terminal in transportation security (transportation safety), wireless terminal in smart city (SMART CITY), wireless terminal in smart home (smart home), cellular phone, cordless phone, session initiation protocol (session initiation protocol, SIP) phone, wireless local loop (wireless local loop, WLL) station, personal digital assistant (personal DIGITAL ASSISTANT, PDA), handheld device with wireless communication function, computing device or other processing device connected to wireless modem, vehicle-mounted device, wearable device, terminal device in 5G network or evolving terminal in the future public network (public land mobile network), and the like without limiting the application.
By way of example, and not limitation, in embodiments of the application, the electronic device may also be a wearable device. The wearable device can also be called as a wearable intelligent device, and is a generic name for intelligently designing daily wear by applying wearable technology and developing wearable devices, such as glasses, gloves, watches, clothes, shoes and the like. The wearable device is a portable device that is worn directly on the body or integrated into the clothing or accessories of the user. The wearable device is not only a hardware device, but also can realize a powerful function through software support, data interaction and cloud interaction. The generalized wearable intelligent device comprises full functions, large size and complete or partial functions which can be realized independently of a smart phone, such as a smart watch, a smart glasses and the like, and is only focused on certain application functions, and needs to be matched with other devices such as the smart phone for use, such as various smart bracelets, smart jewelry and the like for physical sign monitoring.
In addition, in the embodiment of the application, the electronic equipment can also be terminal equipment in an internet of things (internet of things, ioT) system, and the IoT is an important component of the development of future information technology, and the main technical characteristics of the IoT are that the article is connected with a network through a communication technology, so that the man-machine interconnection and the intelligent network of the internet of things are realized.
The electronic device in the embodiments of the present application may also be referred to as a terminal device, a User Equipment (UE), a Mobile Station (MS), a Mobile Terminal (MT), an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent, a user equipment, or the like.
In an embodiment of the present application, the electronic device or each network device includes a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on top of the operating system layer. The hardware layer includes hardware such as a central processing unit (central processing unit, CPU), a memory management unit (memory management unit, MMU), and a memory (also referred to as a main memory). The operating system may be any one or more computer operating systems that implement business processes through processes (processes), such as a Linux operating system, a Unix operating system, an Android operating system, an iOS operating system, or a windows operating system. The application layer comprises applications such as a browser, an address book, word processing software, instant messaging software and the like.
The MIMO communication technology can realize the simultaneous transmission of multiple code streams by means of a multi-antenna system, and increases the communication rate. Currently, multiple-input multiple-output (MIMO) of a terminal device can be tested in a variety of ways. Such as Over The Air (OTA) and conduction, etc.
However, in both test modes, the entity of the terminal equipment needs to be tested, and the performance of the terminal equipment cannot be predicted by using the method in the design stage of the terminal equipment, so that the design risk of the terminal equipment is high.
When the OTA mode is adopted for testing, one end of the channel simulator is connected through the base station or the base station simulator, and the other end of the channel simulator is connected with the multi-probe darkroom for testing.
By way of example, fig. 1 is a schematic diagram of one possible design for a test scenario. As shown in fig. 1, the base station simulator 101 is connected to a channel simulator 102, and the channel simulator 102 is connected to a plurality of antennas 104 built in an OTA darkroom 103. The terminal device is placed in the center of the OTA darkroom 103.
The antenna 104 is controlled by the base station simulator 101 and the channel simulator 102 to transmit radio frequency signals so that the radio frequency signals arriving at the terminal equipment 105 conform to the description of the channel model to perform throughput test on the terminal equipment 105.
In the test shown in fig. 1, the test is performed on the entire terminal device 105. The measured throughput of the terminal device 105 is affected by various factors such as internal radiation interference of the terminal device, product structure of the terminal device, directivity of antennas, differences between multiple antennas, radio frequency chip transceiving algorithm, and the like. Therefore, the throughput measured in the test method shown in fig. 1 cannot be correlated with the antenna index such as the directivity of the antenna in the terminal device 105, the difference between the multiple antennas, and the like. When the throughput rate of the terminal device 105 does not reach the standard, a group of antennas needs to be redesigned, and the test is performed after the antennas are installed, so that the test time is long and the efficiency is low.
When the conduction mode is adopted for testing, one end of the channel simulator is connected through the base station or the base station simulator, and the other end of the channel simulator is connected with the radio frequency chip in the terminal equipment for testing.
In the mode, the channel simulator is directly connected with the radio frequency chip of the terminal equipment, and the throughput rate obtained by testing is related to the signal transmission performance in the radio frequency chip. In this manner, the antenna of the terminal device is not used for receiving signals, and the throughput rate obtained by the test is irrelevant to the performance of the antenna for receiving signals, so that the performance of the antenna of the terminal device cannot be tested.
In view of this, the embodiments of the present application provide an antenna testing method and related apparatus. And coupling the radiation pattern of the real antenna with the channel model to simulate the scene of the antenna of the terminal equipment receiving the signal, and realizing the design evaluation of the antenna in a simulation mode. Therefore, the performance test can be performed on the terminal equipment in the design stage of the antenna without adopting an entity antenna, the design risk is reduced, and the development speed is improved.
In addition, the antenna performance is represented by the throughput rate in the embodiment of the application, and the mode of representing the antenna performance by the throughput rate is more in line with the rule of signal transmission change in the actual use scene.
The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The following embodiments may be implemented independently or combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 2 is a schematic diagram of an antenna testing method according to an embodiment of the present application. As shown in fig. 2, the method includes:
s201, acquiring antenna information of a transmitting end.
The transmitting end may be a base station or a terminal device, which is not limited herein.
In the embodiment of the application, the antenna information of the transmitting end is used for determining the gain information of each transmitting antenna in each direction and transmitting the same signal phase offset information and other related information in each direction of any two transmitting antennas.
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 an antenna of the transmitting end. The type of the transmitting antenna may be an omni-directional antenna, a directional antenna, etc., which is not limited herein. The parameters of the transmitting antenna comprise data such as the structure of the transmitting antenna, the polarization discrimination, the correlation coefficient (envelop correlation coefficient, ECC), the isolation, the antenna efficiency, the working frequency point and the like. The layout of the transmit antennas includes the relative positions of the individual transmit antennas. The transmitting antenna may be a virtual antenna or a physical antenna, which is not limited herein.
In a possible implementation, the test software may obtain the radiation patterns of the respective transmitting antennas by using parameters, such as type, layout, parameters, etc., of the transmitting antennas input by the user.
In other embodiments, the antenna information of the transmitting end obtained by the test software may also be a radiation pattern of each transmitting antenna, or an OTA direction file of the transmitting antenna input by the user, or the like. The embodiment of the application does not limit the acquisition mode of the antenna information.
The test software may obtain radiation patterns of the respective transmitting antennas through an OTA direction file input by a user. The OTA direction file includes data such as antenna efficiency, operating frequency point, antenna position, etc. The test software can coordinate map the OTA direction data in the antenna simulation OTA direction file to coordinate map so as to convert the OTA direction data in rectangular coordinates (CST format) into the OTA direction data in polar coordinate format, and obtain the radiation patterns of all transmitting antennas.
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, which is not limited in the present application.
S202, obtaining information of a channel model.
In the embodiment of the application, a channel model is used for representing a signal transmission channel between a transmitting antenna and a receiving antenna. The test software can confirm the transmission channel of the signal according to the channel model, thereby confirming the fading, time delay and the like of the signal transmission. The channel model includes factors such as spatial correlation (e.g., reflection, diffraction, etc.), doppler, and delay of the signal.
In the embodiment of the application, the information of the channel model is used for determining the channel model used for antenna test and channel parameter data, the channel parameters comprise interference, fading, signal strength and environment parameters of each signal propagation path, and the environment parameters of each signal propagation path comprise parameters such as departure angle phi, arrival angle phi, time delay tau and the like of the signal propagation path.
Exemplary channel models can be classified into a cluster delay line model (clustered DELAY LINE, CDL), a tap delay line model (TAPPED DELAY LINE, TDL), a QuaDriga channel model, a channel model acquired by using a channel acquisition device, and the like, and the embodiment of the present application does not specifically limit the type of the channel model.
The channel model used for the antenna test may be selected by the user from a plurality of pre-stored channel models, or may be a channel model input by the user, which is not limited in the embodiment of the present application. For example, a user may input a typical channel model acquired by a channel acquisition device into test software to perform throughput testing under the channel model.
In some embodiments, the channel model used by the antenna test may be determined by the scene information in which the receiving end is located, which is input by the user, for example, indoor, outdoor, suburban, etc. The test software can determine the type of channel model required by the test and the corresponding channel parameters based on the scene information of the receiving end. For example, when the receiving end is indoor, a CDL channel model may be used; when the receiving end is outdoors, a QuaDriga channel model can be adopted; when the receiving end is in an open scene such as suburb, a channel model acquired by using the channel acquisition equipment in the open scene can be adopted, and the embodiment of the application does not specifically limit the channel model, the scene and the like.
The channel parameter data can be channel parameter data input by a user in test software, or channel parameter data selected by the user from one or more groups of pre-stored channel parameter data. The method for acquiring the channel parameter data is not particularly limited in the embodiment of the application.
S203, acquiring antenna information of a receiving end.
The receiving end is the terminal equipment to be tested. In the embodiment of the application, the antenna information of the receiving end is the antenna information of the entity antenna of the terminal equipment to be tested. In this way, the entity antenna of the receiving end is simulated, so that the antenna performance obtained by the test software is matched with the antenna performance of the terminal equipment to be tested, and the subsequent evaluation of the antenna design of the terminal equipment to be tested is facilitated.
In the embodiment of the application, the antenna information of the receiving end is used for determining the gain information of each receiving antenna in the terminal equipment to be tested in all directions, and the related information such as the phase offset information of the same signal transmitted in all directions of any two receiving antennas. The receiving antenna is a physical antenna.
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 an antenna of the receiving end. The type of the receiving antenna may be an omni-directional antenna, a directional antenna, or the like, which is not limited herein. The parameters of the receiving antenna comprise data such as the structure of the receiving antenna, the polarization discrimination, the correlation coefficient (envelop correlation coefficient, ECC), the isolation, the antenna efficiency, the working frequency point and the like. The layout of the receive antennas includes the relative positions of the individual receive antennas.
In a possible implementation manner, the test software can obtain the radiation patterns of the receiving antennas according to parameters, such as type, layout, number of receiving antennas, etc., input by a user.
In other embodiments, the antenna information of the receiving end obtained by the test software may be a radiation pattern of each receiving antenna, or an OTA direction file of the receiving antenna input by the user, or the like. The embodiment of the application does not limit the acquisition mode of the antenna information.
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.
S204, obtaining a throughput rate curve of the receiving end based on the antenna information of the transmitting end, the antenna information of the receiving end and the information of the channel model. The throughput rate curve is used for representing the throughput rate of the receiving end under different signal-to-noise ratios.
In the embodiment of the application, the throughput rate curve is used for representing the corresponding relation between the throughput rate and the signal-to-noise ratio. For example, fig. 5 shows a schematic diagram of a test curve of throughput and signal-to-noise ratio in the case of a fixed modulation coding strategy.
It will be appreciated that the throughput rate of the receiving end may be obtained by any possible calculation, and the embodiments of the present application are not limited herein. Taking the example of obtaining the signal transmission probability under different signal to noise ratios through a plurality of sampling points as the example, the test software can randomly generate a plurality of sampling points, count the signal to noise ratio of each sampling point according to the antenna information of a transmitting end, the antenna information of a receiving end and the information of a channel model to obtain the probability (namely, the cumulative probability distribution of the signal to noise ratio) of the signal transmission under different signal to noise ratios, and multiply the theoretical throughput rate with the probability to obtain the throughput rate of the signal transmission under different signal to noise ratios to obtain the throughput rate curve of the receiving end. The theoretical throughput rate is the throughput rate when the sampling point successfully transmits signals.
The following describes the process of calculating the signal-to-noise ratio. Since the signal-to-noise ratio is a ratio of signal to noise, the signal received by the receiving antenna will be described below.
For an exemplary, nt×nr MIMO system, the signal propagation formula may 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, n is the interference noise during reception, and may also be referred to as a noise signal with independent co-distributed complex gaussian elements. Signal to noise ratio
Taking the channel model as a CDL model, the transmitting antennas as S and the receiving antennas as U as examples, the channel transmission matrix comprises channel coefficients from the transmitting antennas to the receiving antennas.H1,1 denotes a channel coefficient received from the 1 st transmitting antenna through spatial fading to the 2 nd receiving antenna, hu,1 denotes a channel coefficient received from the 1 st transmitting antenna through spatial fading to the u th receiving antenna, h1,s denotes a channel coefficient received from the s th transmitting antenna through spatial fading to the 1 st receiving antenna, and hu,s denotes a channel coefficient received from the s th transmitting antenna through spatial fading to the u th receiving antenna.
The channel coefficient between the s-th transmitting antenna and the u-th receiving antenna is hu,sxs. Taking the channel model as the CDL model, and each path includes 20 clusters, hu,s＝hu,s,1(t,f)+…+hu,s,n (t, f) for example. Illustratively, as shown in fig. 3, the channel coefficients of the nth cluster from the s-th transmit antenna to the u-th receive antenna are:
wherein Pn is the power of the nth cluster, M is the number of sub-paths in each cluster; representing the radiation pattern of the s-th transmitting antenna; representing a radiation pattern of the u-th receiving antenna; Representing the antenna OTA.
Is a random initial phase; AndSpherical unit vectors of the departure angle and the arrival angle of the mth sub-path of the nth cluster respectively; Position vector for the s-th transmitting antenna; a position vector for the u-th receive antenna; Representing spatial correlation.
Lambda is the wavelength of electromagnetic wave, taun is the time delay of the nth cluster, f is the carrier frequency, vn,m is the Doppler shift of the mth sub-path of the nth cluster, which depends on the radial movement speed and frequency of the receiving end relative to the incoming wave direction. exp (-j 2 pi f taun) represents the delay.
The signal energy received by the receiving antenna can be obtained through the signal propagation formula. The calculation of the ratio of signal to noise is described below.
It will be appreciated that in an all-spatial multiplexed open loop MIMO system, each receive antenna may receive multiple signals from multiple transmit antennas. The receiving antenna may receive a first signal and a second signal, which may interfere with the first signal. The first signal is a signal corresponding to the receiving antenna, and the second signal is a signal corresponding to a receiving antenna other than the receiving antenna.
Fig. 4 is a schematic diagram of signal transmission according to an embodiment of the present application. As shown in FIG. 4, the number of transmitting antennas is 4, and T1, T2, T3 and T4 are respectively adopted, and the number of receiving antennas is 4, and R1, T2, R3 and R4 are respectively adopted.
T1 transmits stream 1 data to R1, T2 transmits stream 2 data to R2, T3 transmits stream 3 data to R3, and T4 transmits stream 4 data to R4. R1 also receives stream 2 data, stream 3 data, and stream 4 data. Stream 2, stream 3 and stream 4 interfere with stream 1 received by R1.
Thus, for an open loop MIMO system with full spatial multiplexing, the signal propagation formula can be expressed as y=hixi+∑j≠ihjxj +n. Where hixi denotes the i-th stream data received by the receiving end, Σj≠ihjxj denotes the interference of all other stream data on the i-th stream data. The signal-to-noise ratio of the ith stream data isI.e.Can also be expressed asWherein,The superscript H in HH denotes the conjugate transpose, [ X ]i,i denotes the I-th diagonal term of the matrix, and I denotes the identity matrix of the same order.
It should be noted that, when the signal-to-noise ratio of the signal is greater than or equal to the threshold (γth), the receiving end may successfully demodulate the signal, and when the signal-to-noise ratio of the signal is less than the threshold, the receiving end fails to demodulate the signal. The threshold (γth) may also be referred to as a block error SNR threshold, and is not limited herein.
The test software can obtain the signal-to-noise ratio of each stream of data according to the channel transmission matrix H, obtain the probability distribution of the signal-to-noise ratio of each stream of data under a plurality of sampling points, further obtain the throughput rate of the receiving antenna corresponding to each stream of data, and then superimpose the throughput rates of the receiving antennas corresponding to each stream of data to obtain the throughput rate of the receiving end.
In the embodiment of the application, the test software can randomly generate a plurality of sampling points according to the channel model and the radiation pattern of the receiving antenna, count the receiving conditions of signals corresponding to the sampling points to obtain the distribution probability of the sampling points under different signal to noise ratios, and obtain the throughput rate of the receiving antenna under different signal to noise ratios according to the probability and the maximum throughput rate of the signals.
Illustratively, taking the receiving antenna corresponding to the ith stream data as an example, the ith stream data is givenThe probability distribution function of gammath under the condition of (3) isThe probability of signal demodulation failure can be understood; Indicating the probability that the signal demodulation was successful.
In the case of a fixed modulation and coding strategy, the throughput rate of the ith stream data is the product of the maximum throughput rate of the ith stream data and the probability of successful signal demodulation, i.eGammai is the instantaneous signal-to-noise ratio of the ith stream data; is the average signal-to-noise ratio of the ith stream data.
It can be appreciated that the throughput rate Tput of the terminal device is the sum of the throughput rates of all data streams, i.e.: Wherein,NT is the number of transmit antennas, yth represents a threshold,Is shown in givenThe probability density distribution (CDF) of γth, Tput,max represents the maximum throughput rate given by the system, which may also be referred to as the theoretical maximum throughput rate.
It will be appreciated that the location and parameters of the receiving antennas are different. In the embodiment of the application, the test software samples each receiving antenna to obtain the corresponding throughput rate of each receiving antenna, and then the throughput rates corresponding to each receiving antenna are overlapped to obtain the throughput rate of the receiving end.
The test software can randomly generate a plurality of sampling points according to the channel model and the radiation pattern, count the signal to noise ratios of the sampling points to obtain a throughput rate curve corresponding to each receiving antenna, and then superimpose the throughput rate curves corresponding to the receiving antennas to obtain the throughput rate curve of the receiving end.
The above embodiment describes a process of calculating the throughput rate of the receiving end. Throughput may also be related to the modulation 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. In general, the higher the order corresponding to the modulation coding strategy, the higher the throughput. Correspondingly, the higher the corresponding order of the modulation coding strategy, the higher the signal-to-noise ratio requirement on the signal.
In some embodiments, the test software calculates the throughput rate of the receiving end according to a fixed signal modulation and coding strategy, and outputs a corresponding throughput rate curve.
The test software calculates the throughput rate of the receiving end according to the signal modulation coding strategies of high-order modulation and high-speed, and outputs a corresponding throughput rate curve.
In other embodiments, the test software may obtain and process the throughput rate curves corresponding to each modulation and coding strategy, and obtain throughput rate curves corresponding to the adaptive modulation and coding strategy.
The test software selects the maximum value of the throughput rate under the same signal-to-noise ratio from the throughput rate curves corresponding to each modulation and coding strategy, and obtains the throughput rate curve corresponding to the adaptive modulation and coding strategy.
It can be appreciated that the higher the number of valid bits that can be carried in one RE in the modulation coding strategy, the higher the quality requirement for signal transmission. Therefore, when the signal-to-noise ratio is high, the throughput rate corresponding to the high-order modulation mode and the high-rate channel coding mode is high, and when the signal-to-noise ratio is low, the throughput rate corresponding to the low-order modulation mode and the low-rate channel coding mode is high.
In this way, considering the scene of the modulation and coding strategy of the possible self-adaptive regulation signal of the transmitting end, the throughput rate curve corresponding to the self-adaptive modulation and coding strategy obtained by the test software is more in line with the antenna performance in the actual use scene of the receiving end, and the accuracy of the antenna performance evaluation is improved.
It can be understood that, in the embodiment of the present application, the throughput rate curve corresponding to the adaptive modulation and coding strategy may be obtained by any possible calculation method, which is not limited herein. For example, the maximum value of the throughput rate under the same signal-to-noise ratio can be directly selected from the throughput rate curves corresponding to each modulation and coding strategy, so as to obtain the throughput rate curve corresponding to the adaptive modulation and coding strategy.
In some embodiments, the test software may normalize the throughput rate curves corresponding to each modulation and coding strategy. And selecting the maximum value of the throughput rate under the same signal-to-noise ratio from the normalized throughput rate curves corresponding to each modulation and coding strategy to obtain the throughput rate curve corresponding to the adaptive modulation and coding strategy. Therefore, the normalization processing can map the data to be processed within the range of 0-1, so that the calculation is simplified, and the processing speed is improved.
The maximum value in the first throughput rate curve corresponding to the MCS with the order of 27 is selected for normalization processing of the throughput rate curve corresponding to each modulation and coding strategy, that is, the throughput rate curve corresponding to each modulation and coding strategy is divided by the first value, and the first value is the maximum value of the throughput rates in the throughput rate curve corresponding to the MCS with the order of 27.
Illustratively, taking the throughput rate curve corresponding to each modulation and coding scheme as a first throughput rate curve and the throughput rate curve corresponding to the adaptive modulation and coding scheme as a second throughput rate curve as an example, as shown in fig. 6, the first throughput rate curve may be shown by a line 601 in fig. 6. The test software may select a maximum value of throughput rate at the same signal-to-noise ratio from a plurality of first throughput rate curves, and the resulting second throughput rate curve may be shown as line 602 in fig. 6.
Thus, the transmission process of the signal can be simulated through the test software, and the antenna performance of the receiving end can be evaluated. And the performance of the antenna is evaluated in the design stage of the receiving end, so that the design risk is reduced, and the development speed is improved. And the corresponding maximum throughput rate of the receiving antenna in various modulation and coding strategies and the relation between signal to noise ratios can be obtained, and the accuracy of antenna performance evaluation is improved.
It should be noted that the number of data streams may affect the throughput rate of the receiving end. The higher the number of data streams, the higher the quality requirements for the signal transmission. Therefore, when the signal-to-noise ratio is high, the throughput rate corresponding to the mode with a large number of data streams is high, and when the signal-to-noise ratio is low, the throughput rate corresponding to the mode with a small number of data streams is high.
In some embodiments, the test software calculates the throughput rate of the receiving end according to the fixed number of data streams, and outputs a corresponding throughput rate curve.
By taking 4-stream data as an example, the test software calculates the throughput rate of the receiving end and outputs a corresponding throughput rate curve.
In other embodiments, the test software may obtain and process throughput rate curves corresponding to different numbers of data streams, and obtain throughput rate curves corresponding to the numbers of data streams of the adaptive adjustment signal.
It will be appreciated that the embodiment of the present application may obtain the throughput rate curve corresponding to the number of data streams of the adaptive adjustment signal by any possible calculation method, which is not limited herein. For example, the maximum value of the throughput rate under the same signal-to-noise ratio may be directly selected from the throughput rate curves corresponding to the number of the data streams of each signal, so as to obtain the throughput rate curve corresponding to the number of the data streams of the adaptive adjustment signal.
In some embodiments, the test software may obtain throughput rate curves corresponding to adaptive modulation and coding schemes for a plurality of data streams, and process the throughput rate curves to obtain throughput rate curves for the number of data streams of the adaptive modulation and coding scheme adaptive adjustment signal. The number of data streams of the adaptive adjustment signal may also be referred to as adaptive hierarchical multiplexing or as adaptive antenna number, without limitation. Therefore, factors such as modulation and coding strategies, hierarchical multiplexing and the like are considered in the base station, so that the throughput rate curve obtained through testing accords with the actual transmission rule of the signals, and the accuracy of the test result is improved.
Taking the throughput rate curve corresponding to the adaptive modulation and coding strategy as the second throughput rate curve as an example, the test software can obtain the second throughput rate curves of a plurality of data streams, and normalize the second throughput rate curves. And selecting the maximum value of the throughput rate under the same signal-to-noise ratio from the normalized second throughput rate curve to obtain the throughput rate curve of the number of the data streams of the adaptive modulation and coding strategy adaptive adjustment signal. Therefore, the normalization processing can map the data to be processed within the range of 0-1, so that the calculation is simplified, and the processing speed is improved.
Illustratively, taking 4 data streams as an example, as shown in fig. 7, the normalized second throughput curve may be shown by a line 701 in fig. 7. The test software may select the maximum value of the throughput rate under the same signal-to-noise ratio from the plurality of second throughput rate curves, and the resulting third throughput rate curve may be shown by a line 702 in fig. 7.
If the test software calculates the throughput rate of the receiving end by using a fixed modulation and coding strategy, outputting a corresponding throughput rate curve. The test software can obtain throughput rate curves for a plurality of data streams.
For example, the test software may sort the throughput rates of the U receive antennas, and select the throughput rates corresponding to the first M receive antennas to generate throughput rate curves (first throughput rate curves) corresponding to each modulation and coding strategy.
The method includes taking 4 receiving antennas as an example, namely an antenna 1, an antenna 2, an antenna 3 and an antenna 4, if the antenna performance is ranked as the antenna 1, the antenna 2, the antenna 3 and the antenna 4 from big to small, selecting the antenna 1 to receive signals when the data stream is 1, generating a first throughput rate curve according to the throughput rate corresponding to the antenna 1, selecting the antenna 1 and the antenna 2 to receive signals when the data stream is 2, generating a first throughput rate curve according to the throughput rate corresponding to the antenna 1 and the throughput rate corresponding to the antenna 2, selecting the antenna 1, the antenna 2 and the antenna 3 to receive signals when the data stream is 3, generating a first throughput rate curve according to the throughput rate corresponding to the antenna 1, the throughput rate corresponding to the antenna 2, the throughput rate corresponding to the antenna 3 and the throughput rate corresponding to the antenna 4 when the data stream is 4.
Therefore, the test software can select the receiving antenna with better receiving performance to perform performance evaluation, so that the first throughput rate curve is more in line with the scene of using the antenna with better receiving performance to perform signal receiving, and the accuracy of the evaluation result is improved.
On the basis of the embodiment, the test software can randomly generate a plurality of sampling points for antenna test under the same gesture of the receiving end to generate a throughput rate curve, and can also randomly generate a plurality of sampling points for antenna test under the plurality of gestures of the receiving end to generate a plurality of throughput rate curves.
Therefore, the multiple throughput rate curves can reflect the antenna performance of the receiving end under different postures, and the subsequent comparison analysis of the antenna performance is convenient.
In other embodiments, the test software may perform antenna testing on multiple sampling points in multiple poses to generate a throughput rate curve. Thus, the test software can reflect the antenna performance of a receiving end under different postures by using a throughput rate curve.
The test software may traverse a plurality of poses of the receiving end to randomly generate a plurality of sampling points, or may simulate rotation of the receiving end to randomly generate a plurality of sampling points.
It can be understood that the posture of the receiving end corresponds to the angle of the radiation pattern of the receiving end, and the angles of the radiation patterns of the receiving end are different in different postures. The angle of the radiation pattern of the receiving antenna refers to the angle (or pointing angle) at which the radiation pattern rotates relative to the channel model. For example, the test software may derive radiation patterns at a plurality of angles from the radiation patterns at the first angle.
Exemplary, the radiation patterns of the receiving antennas corresponding to different poses are different, and the channel coefficient calculation in the CDL model is taken as an exampleDifferent.
In this way, the angle of the radiation pattern of the receiving antenna is related to the throughput rate curve, so that the throughput rate curve can reflect the antenna performances of the terminal equipment in different postures under the same channel environment.
In the above embodiments, the test software may obtain one or more channel models. When the test software acquires a plurality of channel models, the signal-to-noise ratio calculation can be performed through each signal model, and the throughput rate curve corresponding to each channel model is output. Therefore, the test software can output a plurality of throughput rate curves, can reflect the antenna performance of the receiving end under different channel environments, and is convenient for subsequent comparison analysis.
It will be appreciated that the paths of signal transmission corresponding to different channel models are distributed differently. The departure angle and arrival angle corresponding to different channel models are different, and the CDL model is taken as an example, and the different channel models correspond toAndDifferent.
In other embodiments, the test software may perform antenna testing on multiple sampling points under multiple channel models to generate a throughput rate curve. Thus, the test software can reflect the antenna performance of a receiving end under different channel environments by using a throughput rate curve.
In the embodiment of the application, the information testing software of the multiple channel models can acquire the multiple channel models at one time, or can acquire the multiple channel models for multiple times, which is not limited herein.
Based on the above embodiment, the test software can use one channel model to perform antenna test and output a throughput rate curve, or can use multiple channel models to perform antenna test,
Optionally, the step S204 includes steps S2041-S2043.
2041. And calculating 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.
The calculation process of the channel transmission matrix may refer to the corresponding description above, and will not be repeated here.
S2042, calculating a signal to noise ratio.
The calculation process of the signal to noise ratio can refer to the corresponding description, and will not be repeated here.
S2043, obtaining a throughput rate curve according to the first algorithm and the second algorithm.
The first algorithm is related to a modulation coding strategy of the adaptive adjustment signal and the second algorithm is related to a number of data streams of the adaptive adjustment signal.
Illustratively, the first algorithm is used to achieve that the throughput at MCS level 27 is considered the maximum throughput (i.e., relative throughput is 1), with the other MCS levels determining their normalized maximum relative throughput by means of the Modulation Order and Code Rate. And then, the signal-to-noise ratio of the throughput rate curve obtained by the fixed MCS at the relative throughput of 0.9 is respectively moved to the signal-to-noise ratio of the BLER corresponding to each MCS order of 0.1, the throughput rate curve is compressed according to the normalized maximum relative throughput calculated by different MCS orders, and then the maximum value of all the curves is taken.
The second algorithm is used for realizing the fixed 4-stream, 3-stream, 2-stream and 1-stream respectively, solving the relative throughput rate curves when the adaptive MCS is adopted, finally taking the 4 new throughput rate curves to a max, and finally obtaining the throughput rate curves which simultaneously consider the adaptive MCS and the number of the data streams of the adaptive adjustment signal.
The throughput rate curve is used to indicate a relationship between a corresponding maximum throughput rate of the receiving antenna among a plurality of modulation and coding strategies, a plurality of data stream numbers, and a signal-to-noise ratio. The specific process may refer to the third throughput rate curve, and will not be described herein.
In this way, the transmission process of the signal can be simulated, and the antenna performance of the terminal equipment can be evaluated. And the performance evaluation is carried out on the antenna in the design stage of the terminal equipment, so that the design risk is reduced, and the development speed is improved. And in addition, factors such as modulation and coding strategies, hierarchical multiplexing and the like are considered, so that the throughput rate curve obtained by testing accords with the law of actual signal transmission, and the accuracy of a test result is improved.
It will be appreciated that in the above embodiments, the antenna performance is characterized by a throughput rate curve. The test software may also characterize the antenna performance by throughput over a preset time. The throughput rate curve describes the throughput rate with the signal-to-noise ratio as the horizontal axis, and the signal-to-noise ratio can be replaced by the signal strength. The embodiment of the application does not limit the characterization mode of the test software on the antenna performance.
Based on the above embodiment, the test software may obtain the antenna information of the receiving end corresponding to one or more design schemes, and output the throughput rate curve corresponding to each design scheme.
The test software can also perform performance analysis according to the throughput rate curves corresponding to each design scheme.
The test software may also output a target design scheme according to the throughput rate curve corresponding to each design scheme, where the target design scheme is used for debugging the antenna at the receiving end.
The process and mode of performance analysis of the throughput rate curve in the embodiment of the application are not particularly limited.
The test software may acquire the antenna information of the receiving end corresponding to multiple design schemes at one time, or may acquire a fixed number of antenna performance of the receiving end in one design scheme for test in the above embodiment. The test software may also test the receiver antennas in a variety of designs.
In the above embodiment, the throughput rate curve is used to represent the antenna performance of the receiving end, and the test software may also use the throughput rate curve to represent the antenna performance of the receiving end, and the specific calculation process is similar to the calculation process of the throughput rate curve, which is not repeated here.
The method provided by the embodiment of the application is described above, and the device for executing the method provided by the embodiment of the application is described below. It will be appreciated by those skilled in the art that the methods and apparatus may be combined and referenced with each other, and that the related apparatus provided by the embodiments of the present application may perform the steps of the methods described above.
Fig. 8 is a schematic structural diagram of an antenna testing device according to an embodiment of the present application. The antenna testing device may be an electronic device in the embodiment of the present application, or may be a part of a component in the electronic device, for example, a chip or a chip system.
As shown in fig. 8, the antenna test apparatus may be used in a communication device, a circuit, a hardware component, or a chip. The antenna test apparatus includes a communication unit 901, a processing unit 902, a display unit 903, and the like. The communication unit 901 is used for obtaining a channel model and a radiation pattern of each receiving antenna in a receiving end, the processing unit 902 is used for obtaining a throughput rate curve of the receiving end according to the channel model and the radiation pattern of each receiving antenna, and the display unit 903 is used for displaying the throughput rate of the receiving end.
The communication unit 901 is used to support the antenna test apparatus to interact with other devices. For example, when the antenna test apparatus is a terminal device, the communication unit 901 may be a communication interface or an interface circuit. When the antenna test apparatus is a chip or a chip system in a terminal device, the communication unit 901 may be a communication interface. For example, the communication interface may be an input/output interface, pins or circuitry, etc.
In particular, the processing unit 902 may be integrated with the display unit 903, and communication may occur between the processing unit 902 and the display unit 903.
In one possible implementation, the antenna test apparatus may further include a storage unit 904. The memory unit 904 may include one or more memories, which may be one or more devices, circuits, or devices for storing programs or data.
The memory unit 904 may be separate and coupled to the processing unit 902 via a communication bus. The memory unit 904 may also be integrated with the processing unit 902.
Taking an example that the antenna test apparatus may be a chip or a chip system of the terminal device in the embodiment of the present application, the storage unit 904 may store computer-executed instructions of a method of the terminal device, so that the processing unit 902 performs the above-described antenna test method. The memory unit 904 may be a register, a cache or a random access memory (random access memory, RAM) or the like, and the memory unit 904 may be integrated with the processing unit 902. The memory unit 904 may be a read-only memory (ROM) or other type of static storage device that may store static information and instructions, and the memory unit 1304 may be independent of the processing unit 902.
The apparatus of this embodiment may be correspondingly configured to perform the steps performed in the foregoing method embodiments, and the implementation principle and technical effects are similar, which are not described herein again.
The embodiment of the application provides an antenna testing device which comprises a processor and a memory, wherein the memory stores computer execution instructions, and the processor executes the computer execution instructions stored in the memory so that the antenna testing device executes the method.
Fig. 9 is a schematic structural diagram of an antenna testing device according to an embodiment of the present application. As shown in fig. 9, the antenna test apparatus includes a memory 1001, a processor 1002, and an interface circuit 1003. The apparatus may further include a display 1004, where the memory 1001, the processor 1002, the interface circuit 1003, and the display 1004 may communicate, and by way of example, the memory 1001, the processor 1002, the interface circuit 1003, and the display 1004 may communicate through a communication bus, and the memory 1001 is configured to store computer execution instructions, be controlled by the processor 1002, and be executed by the interface circuit 1003 to perform communication, thereby implementing the antenna test method provided by the embodiment of the present application.
Optionally, the interface circuit 1003 may also include a transmitter and/or a receiver. Alternatively, the processor 1002 may include one or more CPUs, and may be other general purpose processors, digital signal processors (DIGITAL SIGNAL processor, DSP), application Specific Integrated Circuits (ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present application may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
In a possible implementation manner, the computer-executed instructions in the embodiment of the present application may also be referred to as application program code, which is not limited in particular by the embodiment of the present application.
The antenna testing device provided by the embodiment of the application is used for executing the antenna testing method of the embodiment, and the technical principle and the technical effect are similar and are not repeated here.
The antenna testing method provided by the embodiment of the application can be applied to the electronic equipment with the display function. The electronic device includes a terminal device, and specific device forms and the like of the terminal device may refer to the above related descriptions, which are not repeated herein.
The embodiment of the application provides a chip. The chip comprises a processor for invoking a computer program in a memory to perform the technical solutions in the above embodiments. The principle and technical effects of the present application are similar to those of the above-described related embodiments, and will not be described in detail herein.
The embodiment of the application also provides a computer readable storage medium. The computer-readable storage medium stores a computer program. The computer program realizes the above method when being executed by a processor. The methods described in the above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer readable media can include computer storage media and communication media and can include any medium that can transfer a computer program from one place to another. The storage media may be any target media that is accessible by a computer.
In one possible implementation, the computer readable medium may include RAM, ROM, a compact disk-read only memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium targeted for carrying or storing the desired program code in the form of instructions or data structures and accessible by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (Digital Subscriber Line, DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes optical disc, laser disc, optical disc, digital versatile disc (DIGITAL VERSATILE DISC, DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
Embodiments of the present application provide a computer program product comprising a computer program which, when executed, causes a computer to perform the above-described method.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of the related data need to comply with related laws and regulations and standards, and provide corresponding operation entries for the user to select authorization or rejection.
The foregoing detailed description of the invention has been presented for purposes of illustration and description, and it should be understood that the foregoing is by way of illustration and description only, and is not intended to limit the scope of the invention.