OTA test uncertainty analysis method and apparatus

Abstract

The application provides an OTA test uncertainty analysis method and device, comprising the following steps: measuring the EIS pattern of a main antenna and the EIS pattern of a diversity antenna; performing biasing on the EIS patterns according to a preset penalty term, to obtain biased EIS patterns; calculating a TIS value CTIS by using a standard TIS calculation method according to the obtained combined pattern Std‑i‑j ; calculating a TIS value CTIS by using a single-point compensation method SPOT‑i‑j ; calculating the difference between the two TIS values; repeating the above calculation process for each set of EIS patterns and preset penalty terms to obtain a preset number of difference samples; taking the statistical distribution parameter value of the difference samples as the uncertainty value introduced by the single-point compensation method in a multi-antenna receiving scenario; determining whether the uncertainty value is within a preset limit value range; if yes, determining that the single-point compensation method meets the accuracy requirement of OTA testing in the multi-antenna receiving scenario; if not, determining that the single-point compensation method does not meet the accuracy requirement of OTA testing in the multi-antenna receiving scenario.

Description

Technical Field

[0001] This invention relates to the field of communication testing technology, and more particularly to an OTA testing uncertainty analysis method and apparatus. Background Technology

[0002] This section is intended to provide background or context for embodiments of the present invention. The description herein is not intended to imply that it is prior art simply because it is included in this section.

[0003] Over-the-air (OTA) testing methods have become standard testing methods for wireless communication devices such as smartphones and laptops, as mandated by international standardization organizations such as CTIA and 3GPP, providing an objective standard for performance comparison between devices under test. Traditional single-input single-output (SISO) OTA testing includes measurements of total radiated power (TRP) and total isotropic sensitivity (TIS). For wireless communication devices such as smartphones and laptops, the effective isotropic radiated power (EIRP) and effective isotropic sensitivity (EIS) of the device under test are measured at a large number of test grid points according to the spherical sampling grid distribution specified in the CTIA / 3GPP standard. Specific numerical methods are then applied to perform surface integration and weighted averaging of the measurement data to obtain the corresponding TRP and TIS measurements. Current standard OTA testing methods require grid resolutions of 15° and 30° for TRP and TIS measurements, respectively.

[0004] On the other hand, existing OTA testing methods, especially TIS testing methods, require a significant amount of testing time. Currently, the testing time for a single channel TIS test is over half an hour. Considering that OTA testing for wireless communication devices requires comprehensive measurement of all channels, frequency bands, and frequency band combinations under different testing postures and scenarios, the total testing time will reach hundreds of hours, which is unacceptable for product performance evaluation and certification in the industry.

[0005] Single-point compensation testing is a widely used rapid OTA testing method in the industry. This method measures and compares the difference between the EIS values ​​of the device under test (DUT) in the reference frequency band and the test frequency band by measuring the location (angle / polarization) of the optimal EIS value in the reference frequency band. This difference is then used as the compensation value to determine the TIS value of the DUT in the test frequency band. The calculation formula is as follows:

[0006] TIS B =TIS A +(EIS B -EIS A );

[0007] Where TIS represents the TIS value, EIS represents the EIS value, and subscripts A and B represent the reference frequency band and the test frequency band, respectively.

[0008] This method is applicable only if the device under test (DUT) is a single-antenna device; and if the DUT has the same antenna radiator and the same aperture tuning (e.g., matching on parasitic elements or matching elements on the ground or within the radiator) in both the reference and test frequency bands. However, different impedance matching (e.g., matching elements on the RF feed) can be used between the reference and test frequency bands. These requirements ensure that the DUT has the same antenna pattern shape and maximum value location in both the reference and test scenarios, thus ensuring the test accuracy of this method. This method is not suitable for scenarios where the DUT uses different antenna radiators and aperture tuning in the reference and test frequency bands.

[0009] Considering that this method can effectively reduce test time while maintaining test accuracy, we are also considering extending it to scenarios where the device under test (DUT) uses multiple antenna receivers. In multi-antenna receiver scenarios, even if the DUT uses a set of identical antenna radiators in both the reference and test frequency bands, changing the impedance matching of any single receiving antenna will still alter the direction / polarization of the aggregated peak EIS, thus violating the premise and rationale of single-point compensation testing. Therefore, it is necessary to evaluate the rationality of using this method in multi-antenna scenarios. Currently, there is no uncertainty assessment method in the industry for using single-point compensation in multi-antenna receiver scenarios.

[0010] In summary, there is an urgent need for a technical solution that can effectively assess the uncertainty of using single-point compensation methods in multi-antenna reception scenarios. Summary of the Invention

[0011] To address the problems existing in the prior art, this invention proposes a method and apparatus for OTA testing uncertainty analysis.

[0012] In a first aspect of the present invention, an OTA testing uncertainty analysis method is proposed, the method comprising:

[0013] Measure the EIS pattern of the main antenna and the EIS pattern of diversity antennas

[0014] According to the preset penalty items By applying an offset, the offset EIS pattern is obtained.

[0015] according to and Obtain the combined radiation pattern for The TIS value CTIS was calculated using the standard TIS calculation method. Std-i-jThe TIS value CTIS was calculated using the single-point compensation method. SPOT-i-j ;

[0016] Calculate CTIS Std-i-j With CTIS SPOT-i-j The difference;

[0017] For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples;

[0018] The statistical distribution parameter values ​​of a preset number of difference samples are used as the uncertainty values ​​introduced by the single-point compensation method in a multi-antenna receiving scenario.

[0019] Determine whether the uncertainty value is within a preset limit range; if it is, determine that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if it is not, determine that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna reception scenario.

[0020] In a second aspect of the present invention, an OTA test uncertainty analysis apparatus is provided, the apparatus comprising:

[0021] The radiation pattern measurement module is used to measure the EIS radiation pattern of the main antenna. and the EIS pattern of diversity antennas

[0022] The bias processing module is used to apply a pre-defined penalty term to the biased input. By applying an offset, the offset EIS pattern is obtained.

[0023] The TIS calculation module is used to calculate based on and Obtain the combined radiation pattern for The TIS value CTIS was calculated using the standard TIS calculation method. Std-i-j The TIS value CTIS was calculated using the single-point compensation method. SPOT-i-j ;

[0024] The difference calculation module is used to calculate CTIS. Std-i-j With CTIS SPOT-i-j The difference;

[0025] For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples;

[0026] The uncertainty calculation module is used to take the statistical distribution parameter values ​​of a preset number of difference samples as the uncertainty values ​​introduced by the single-point compensation method in a multi-antenna receiving scenario.

[0027] An uncertainty judgment module is used to determine whether the uncertainty value is within a preset limit range; if it is, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if it is not, it is determined that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna reception scenario.

[0028] In a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement an OTA test uncertainty analysis method.

[0029] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements an OTA test uncertainty analysis method.

[0030] In a fifth aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements an OTA test uncertainty analysis method.

[0031] The OTA test uncertainty analysis method and apparatus proposed in this invention can effectively analyze test data with different penalty terms, different test frequency ranges, and different test scenarios. It provides strong support for the uncertainty analysis of single-point compensation methods in multi-antenna receiving scenarios, improves the accuracy of related uncertainty analysis, expands the applicability of single-point compensation methods to multi-antenna receiving devices, and improves the OTA test accuracy and efficiency of wireless communication devices. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a schematic flowchart of an OTA testing uncertainty analysis method according to an embodiment of the present invention.

[0034] Figure 2 This is a schematic diagram of the architecture of an OTA test uncertainty analysis device according to an embodiment of the present invention.

[0035] Figure 3 This is a schematic diagram of a computer device structure according to an embodiment of the present invention. Detailed Implementation

[0036] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0037] Those skilled in the art will recognize that embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0038] According to an embodiment of the present invention, an OTA test uncertainty analysis method and apparatus are proposed, relating to the field of communication test technology.

[0039] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.

[0040] Figure 1 This is a schematic flowchart of an OTA testing uncertainty analysis method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0041] S101, Measure the EIS pattern of the main antenna. and the EIS pattern of diversity antennas

[0042] S102, according to the preset penalty items, By applying an offset, the offset EIS pattern is obtained.

[0043] S103, according to and Obtain the combined radiation pattern for The TIS value CTIS was calculated using the standard TIS calculation method. Std-i-j The TIS value CTIS was calculated using the single-point compensation method. SPOT-i-j ;

[0044] S104, Calculate CTIS Std-i-j With CTIS SPOT-i-j The difference;

[0045] For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples;

[0046] S105, the statistical distribution parameter values ​​of a preset number of difference samples are used as the uncertainty values ​​introduced by the single-point compensation method in the multi-antenna receiving scenario;

[0047] S106, determine whether the uncertainty value is within a preset limit range; if it is, determine that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna receiving scenario; if it is not, determine that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna receiving scenario.

[0048] The OTA test uncertainty analysis method and apparatus proposed in this invention can effectively analyze test data with different penalty terms, different test frequency ranges, and different test scenarios. It provides strong support for the uncertainty analysis of single-point compensation methods in multi-antenna receiving scenarios, improves the accuracy of related uncertainty analysis, expands the applicability of single-point compensation methods to multi-antenna receiving devices, and improves the OTA test accuracy and efficiency of wireless communication devices.

[0049] To provide a clearer explanation of the above-mentioned OTA test uncertainty analysis method, each step will be explained in detail below.

[0050] In one embodiment, for S101, the EIS pattern of the main antenna is measured. and the EIS pattern of diversity antennas include:

[0051] Directly measure the EIS radiation patterns of the main antenna and diversity antenna; or,

[0052] The EIRP patterns of the main antenna and diversity antenna were measured separately, and the corresponding EIS patterns were obtained by normalization.

[0053] In one embodiment, the method further includes:

[0054] right and Normalization was performed, and the following were respectively... and The peak EIS value in the data is set to the same downlink power value.

[0055] The purpose of normalization is primarily to consider a worst-case scenario. For example, when multiple receiving antennas in a mobile phone have the same peak EIS (and similar antenna efficiencies), changing the peak EIS of one of the receiving antennas (in other words, changing the antenna's radiation efficiency by altering the impedance matching state) will result in the maximum change in the combined EIS of the two antennas and its directional shift, i.e., the maximum measurement error. This ensures that the corresponding uncertainty assessment method and results are suitable for all other combinations of multi-antenna patterns. Considering the performance of current mainstream mobile terminals, this value is preferably defined as -95dBm or -100dBm.

[0056] In one embodiment, for S102, the penalty term is applied according to a preset penalty term. By applying an offset, the offset EIS pattern is obtained. include:

[0057] Penalties and The EIS values ​​at various angles are added together, and the calculation formula is as follows:

[0058]

[0059] In the formula, This represents the EIS pattern of the biased diversity antenna; Delta j This represents the penalty term, with a value range of 0dB to 3dB: This represents the initial EIS pattern of the diversity antenna.

[0060] Considering the adjustment range of the antenna port impedance adjustment module, the maximum change in antenna efficiency it can produce, in other words, the maximum change in antenna peak gain, is no more than 3dB.

[0061] The purpose of the offset operation is to artificially create a deviation between two EIS patterns with the same EIS peak (and similar antenna radiation efficiencies), so that the combined EIS peak of the two EIS patterns, i.e., the combined pattern, is obtained. The peak value produces a certain amplitude change and angle shift, thus deviating from the premise of using the single-point compensation method: that the device under test has the same antenna pattern shape and maximum value position in both the reference and test scenarios. Therefore, it is possible to evaluate the measurement uncertainty introduced by the single-point compensation test method in multi-antenna receiving scenarios.

[0062] In one embodiment, when selecting an EIS pattern, low-frequency EIS patterns are preferred; wherein, the proportion of patterns in the frequency band below 1 GHz shall not be less than 50% of the total number of patterns, and the proportion of patterns in the frequency band above 3 GHz shall not be greater than 20%.

[0063] EIS orientation maps include at least the orientation map for free space scenes, the orientation map for head-and-hand scenes, and the orientation map for one-handed scenes.

[0064] In one embodiment, for S103, according to and Obtain the combined radiation pattern for The TIS value CTIS was calculated using the standard TIS calculation method. Std-i-j The TIS value CTIS was calculated using the single-point compensation method. SPOT-i-j .

[0065] For S104, calculate CTIS. Std-i-j With CTIS SPOT-i-j The difference is calculated using the following formula:

[0066] DCTIS ij =CTIS Std-i-j -CTIS SPOT-i-j

[0067] Among them, DCTIS ij This represents the difference between the two; the TIS value (CTIS) is obtained using the standard TIS calculation method. Std-i-j As a benchmark.

[0068] For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples. That is, multiple DCTIS samples can be obtained through calculation.

[0069] In one embodiment, for S105, the statistical distribution parameter value of a preset number of difference samples is used as the uncertainty value introduced by the single-point compensation method in a multi-antenna receiving scenario.

[0070] Specifically, the statistical distribution parameters of the preset number of difference samples are as follows:

[0071] The standard deviation of the difference sample; or,

[0072] The mean of the difference samples; or,

[0073] The difference sample value at the preset probability value on the cumulative distribution function curve corresponding to the difference sample.

[0074] Furthermore, the uncertainty value is determined by the following method:

[0075] 1. The uncertainty value is based on different penalty terms Delta. j The arithmetic mean of the standard deviations of the lower difference sample.

[0076] 2. The uncertainty value is based on different penalty terms Delta.j The weighted average of the standard deviations of the lower difference sample is calculated using the following formula:

[0077]

[0078] Where MU represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; w j Delta j Corresponding weights; DCTIS j Delta j The standard deviation of the lower difference sample; N is Delta j Quantity;

[0079] w j The calculation method is as follows:

[0080] or, Delta j Arranged in ascending order of numerical value.

[0081] 3. The uncertainty value is the weighted average of the standard deviations of the difference samples in different test frequency intervals, and the calculation formula is:

[0082]

[0083] Where MU' represents the uncertainty introduced by the single-point compensation method in a multi-antenna reception scenario; w j 'These are the weights corresponding to different test frequency ranges; DCTIS j ' is the standard deviation of the difference samples corresponding to the j-th test frequency interval; N' is the number of different test frequency intervals; w j The value of ' is determined by the percentage of difference samples in different test frequency ranges out of the total number of samples;

[0084] The different test frequency ranges include at least: (400MHz, 1GHz), (1GHz, 2GHz) and (2GHz, 3GHz).

[0085] 4. The uncertainty value is the weighted average of the standard deviations of the difference samples under different test scenarios, and the calculation formula is:

[0086]

[0087] Where, "MU" represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; w j "These are the weights corresponding to different test scenarios; DCTIS" j " is the standard deviation of the difference samples corresponding to the j-th test scenario; N" is the number of different test scenarios; w j"This represents the percentage of difference samples from different test scenarios out of the total sample size;

[0088] The different test scenarios include at least: free space, left and right hands, and left and right head and hands. Specifically, the weights for these three test scenarios are 0.2, 0.4, and 0.4, respectively.

[0089] In one embodiment, for S106, it is determined whether the uncertainty value is within a preset limit range;

[0090] If so, the single-point compensation method is determined to meet the accuracy requirements of OTA testing in multi-antenna reception scenarios;

[0091] If not, it is determined that the single-point compensation method does not meet the accuracy requirements of OTA testing in multi-antenna reception scenarios.

[0092] Specifically, the preset limit range corresponding to the uncertainty value is less than 0.5dB, that is, the upper limit is 0.5dB.

[0093] Referring to Table 1, there is a set of uncertainty analysis samples for an exemplary OTA test uncertainty analysis method.

[0094] Table 1

[0095]

[0096]

[0097]

[0098] By comparing the deviations of two sets of data under different test scenarios, the uncertainty changes of the single-point compensation method in each scenario can be clearly seen. Uncertainty analysis can expand the applicability of the single-point compensation method to multi-antenna receiving devices, thereby improving the accuracy and efficiency of OTA testing for wireless communication devices.

[0099] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0100] After introducing the method of exemplary embodiments of the present invention, the following references are made. Figure 2 An OTA test uncertainty analysis apparatus according to an exemplary embodiment of the present invention will be described.

[0101] The implementation of the OTA testing uncertainty analysis device can refer to the implementation of the above method, and repeated details will not be elaborated further. The term "module" or "unit" used below can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0102] Based on the same inventive concept, this invention also proposes an OTA test uncertainty analysis device, such as... Figure 2 As shown, the device includes:

[0103] The radiation pattern measurement module 210 is used to measure the EIS radiation pattern of the main antenna. and the EIS pattern of diversity antennas

[0104] The bias processing module 220 is used to apply a bias to the biased input based on a preset penalty term. By applying an offset, the offset EIS pattern is obtained.

[0105] TIS calculation module 230, used for calculating based on and Obtain the combined radiation pattern for The TIS value CTIS was calculated using the standard TIS calculation method. Std-i-j The TIS value CTIS was calculated using the single-point compensation method. SPOT-i-j ;

[0106] Difference calculation module 240 is used to calculate CTIS. Std-i-j With CTIS SPOT-i-j The difference;

[0107] For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples;

[0108] Uncertainty calculation module 250 is used to take the statistical distribution parameter value of a preset number of difference samples as the uncertainty value introduced by the single-point compensation method in the multi-antenna receiving scenario;

[0109] The uncertainty judgment module 260 is used to determine whether the uncertainty value is within a preset limit range; if it is, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna receiving scenario; if it is not, it is determined that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna receiving scenario.

[0110] It should be noted that although several modules of the OTA testing uncertainty analysis apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided and embodied by multiple modules.

[0111] In one embodiment, the pattern measurement module 210 measures the EIS pattern of the main antenna. and the EIS pattern of diversity antennas include:

[0112] Directly measure the EIS radiation patterns of the main antenna and diversity antenna; or,

[0113] The EIRP patterns of the main antenna and diversity antenna were measured separately, and the corresponding EIS patterns were obtained by normalization.

[0114] In one embodiment, the pattern measurement module 210 is further configured to:

[0115] right and Normalization was performed, and the following were respectively... and The peak EIS value in the data is set to the same downlink power value.

[0116] In one embodiment, the bias processing module 220 applies a preset penalty term to... By applying an offset, the offset EIS pattern is obtained. include:

[0117] Penalties and The EIS values ​​at various angles are added together, and the calculation formula is as follows:

[0118]

[0119] In the formula, This represents the EIS pattern of the biased diversity antenna; Delta j This represents the penalty term, with a value range of 0dB to 3dB: This represents the initial EIS pattern of the diversity antenna.

[0120] In one embodiment, the bias processing module 220 is further configured to:

[0121] When selecting EIS patterns, priority should be given to low-frequency EIS patterns; among them, the proportion of patterns in the frequency band below 1 GHz should not be less than 50% of the total number of patterns, and the proportion of patterns in the frequency band above 3 GHz should not be greater than 20%.

[0122] EIS orientation maps include at least the orientation map for free space scenes, the orientation map for head-and-hand scenes, and the orientation map for one-handed scenes.

[0123] In one embodiment, the statistical distribution parameter value of the preset number of difference samples is:

[0124] The standard deviation of the difference sample; or,

[0125] The mean of the difference samples; or,

[0126] The difference sample value at the preset probability value on the cumulative distribution function curve corresponding to the difference sample.

[0127] In one embodiment, the uncertainty calculation module 250 uses the statistical distribution parameter values ​​of a preset number of difference samples as the uncertainty value introduced by the single-point compensation method in a multi-antenna receiving scenario, including:

[0128] The uncertainty value is determined by the following method:

[0129] The uncertainty value is based on different penalty terms Delta. j The arithmetic mean of the standard deviations of the lower difference sample;

[0130] The uncertainty value is based on different penalty terms Delta. j The weighted average of the standard deviations of the lower difference sample is calculated using the following formula:

[0131]

[0132] Where MU represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; w j Delta j Corresponding weights; DCTIS j Delta j The standard deviation of the lower difference sample; N is the preset Delta. j Quantity;

[0133] w j The calculation method is as follows:

[0134] or, Delta j Arranged in ascending order of numerical value;

[0135] The uncertainty value is the weighted average of the standard deviations of the difference samples in different test frequency intervals, and the calculation formula is:

[0136]

[0137] Where MU' represents the uncertainty introduced by the single-point compensation method in a multi-antenna reception scenario; w j 'These are the weights corresponding to different test frequency ranges; DCTIS j ' is the standard deviation of the difference samples corresponding to the j-th test frequency interval; N' is the number of different test frequency intervals; w j The value of ' is determined by the percentage of difference samples in different test frequency ranges out of the total number of samples;

[0138] The uncertainty value is the weighted average of the standard deviations of the difference samples under different test scenarios, and the calculation formula is:

[0139]

[0140] Where, "MU" represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; w j "These are the weights corresponding to different test scenarios; DCTIS" j " is the standard deviation of the difference samples corresponding to the j-th test scenario; N" is the number of different test scenarios; w j "This represents the percentage of difference samples from different test scenarios out of the total number of samples."

[0141] In one embodiment, the different test frequency ranges include at least:

[0142] (400MHz, 1GHz), (1GHz, 2GHz) and (2GHz, 3GHz);

[0143] Different test scenarios include at least:

[0144] Free space, left and right hands, and left and right head and hands.

[0145] In one embodiment, the preset limit value range corresponding to the uncertainty value is less than 0.5 dB.

[0146] Based on the aforementioned inventive concept, such as Figure 3 As shown, the present invention also proposes a computer device 300, including a memory 310, a processor 320, and a computer program 330 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 330, it implements the aforementioned OTA test uncertainty analysis method.

[0147] Based on the aforementioned inventive concept, this invention proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned OTA test uncertainty analysis method.

[0148] Based on the aforementioned inventive concept, this invention proposes a computer program product, which includes a computer program that, when executed by a processor, implements an OTA test uncertainty analysis method.

[0149] The OTA test uncertainty analysis method and apparatus proposed in this invention can effectively analyze test data with different penalty terms, different test frequency ranges, and different test scenarios. It provides strong support for the uncertainty analysis of single-point compensation methods in multi-antenna receiving scenarios, improves the accuracy of related uncertainty analysis, expands the applicability of single-point compensation methods to multi-antenna receiving devices, and improves the OTA test accuracy and efficiency of wireless communication devices.

[0150] The acquisition, storage, use, and processing of data in this application all comply with relevant laws and regulations.

[0151] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0152] This invention is described with reference to flowchart illustrations and / or block diagrams of methods and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor 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 processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0153] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0155] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for analyzing uncertainty in OTA testing, characterized in that, The method includes: Measure the EIS pattern of the main antenna and the EIS pattern of diversity antennas ; According to the preset penalty items By applying an offset, the offset EIS pattern is obtained. ; according to and Obtain the combined radiation pattern ,for The TIS value was calculated using the standard TIS calculation method. The TIS value was calculated using the single-point compensation method. ; calculate and The difference; For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples; The statistical distribution parameter values ​​of a preset number of difference samples are used as the uncertainty values ​​introduced by the single-point compensation method in a multi-antenna receiving scenario. Determine whether the uncertainty value is within a preset limit range; if it is, determine that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if it is not, determine that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna reception scenario. Among them, according to the preset penalty items, By applying an offset, the offset EIS pattern is obtained. ,include: Penalties and The EIS values ​​at various angles are added together, and the calculation formula is as follows: In the formula, The EIS pattern of the offset diversity antenna is shown. This represents the penalty term, with a value range of 0 dB to 3 dB: This represents the initial EIS pattern of the diversity antenna.

2. The OTA testing uncertainty analysis method according to claim 1, characterized in that, Measure the EIS pattern of the main antenna and the EIS pattern of diversity antennas ,include: Directly measure the EIS radiation patterns of the main antenna and diversity antenna; or, The EIRP patterns of the main antenna and diversity antenna were measured separately, and the corresponding EIS patterns were obtained by normalization.

3. The OTA testing uncertainty analysis method according to claim 1, characterized in that, The method also includes: right and Perform normalization processing, and respectively and The peak EIS value in the data is set to the same downlink power value.

4. The OTA testing uncertainty analysis method according to claim 1, characterized in that, The method also includes: When selecting EIS patterns, priority should be given to low-frequency EIS patterns; among them, the proportion of patterns in the frequency band below 1 GHz should not be less than 50% of the total number of patterns, and the proportion of patterns in the frequency band above 3 GHz should not be greater than 20%. EIS orientation maps include at least the orientation map for free space scenes, the orientation map for head-and-hand scenes, and the orientation map for one-handed scenes.

5. The OTA testing uncertainty analysis method according to claim 1, characterized in that, The statistical distribution parameters of the preset number of difference samples are: The standard deviation of the difference sample; or, The mean of the difference samples; or, The difference sample value at the preset probability value on the cumulative distribution function curve corresponding to the difference sample.

6. The OTA testing uncertainty analysis method according to claim 1, characterized in that, The statistical distribution parameters of a predetermined number of difference samples are used as the uncertainty values ​​introduced by the single-point compensation method in a multi-antenna receiving scenario, including: The uncertainty value is determined by the following method: The uncertainty value is based on different penalty terms. The arithmetic mean of the standard deviations of the lower difference sample; The uncertainty value is based on different penalty terms. The weighted average of the standard deviations of the lower difference sample is calculated using the following formula: in, This represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; for The corresponding weights; for The standard deviation of the lower difference sample; N is a preset value. Quantity; The calculation method is as follows: ,or, ;in, Arranged in ascending order of numerical value; The uncertainty value is the weighted average of the standard deviations of the difference samples in different test frequency intervals, and the calculation formula is: in, This represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; Weights corresponding to different test frequency ranges; For the first The standard deviation of the difference samples corresponding to each test frequency interval; The number of different test frequency ranges; The value is determined by the percentage of difference samples in different test frequency ranges out of the total number of samples; The uncertainty value is the weighted average of the standard deviations of the difference samples under different test scenarios, and the calculation formula is as follows: ； in, This represents the uncertainty introduced by the single-point compensation method in a multi-antenna receiving scenario; Weights corresponding to different test scenarios; For the first The standard deviation of the difference samples corresponding to each test scenario; The number of different test scenarios; This represents the percentage of difference samples from different test scenarios out of the total sample size.

7. The OTA testing uncertainty analysis method according to claim 6, characterized in that, Different test frequency ranges should include at least: (400 MHz, 1 GHz), (1 GHz, 2 GHz) and (2 GHz, 3 GHz); Different test scenarios include at least: Free space, left and right hands, and left and right head and hands.

8. The OTA testing uncertainty analysis method according to claim 1, characterized in that, The preset limit range corresponding to the uncertainty value is less than 0.5 dB.

9. An OTA testing uncertainty analysis device, characterized in that, The device includes: The radiation pattern measurement module is used to measure the EIS radiation pattern of the main antenna. and the EIS pattern of diversity antennas ; The bias processing module is used to apply a pre-defined penalty term to the biased input. By applying an offset, the offset EIS pattern is obtained. ; The TIS calculation module is used to calculate based on and Obtain the combined radiation pattern ,for The TIS value was calculated using the standard TIS calculation method. The TIS value was calculated using the single-point compensation method. ; The difference calculation module is used to calculate... and The difference; For each EIS pattern and the preset penalty term, repeat the above calculation process to obtain a preset number of difference samples; The uncertainty calculation module is used to take the statistical distribution parameter values ​​of a preset number of difference samples as the uncertainty values ​​introduced by the single-point compensation method in a multi-antenna receiving scenario. An uncertainty judgment module is used to determine whether the uncertainty value is within a preset limit range; if it is, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if it is not, it is determined that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna reception scenario. Specifically, the bias processing module is used for: Penalties and The EIS values ​​at various angles are added together, and the calculation formula is as follows: In the formula, The EIS pattern of the offset diversity antenna is shown. This represents the penalty term, with a value range of 0 dB to 3 dB: This represents the initial EIS pattern of the diversity antenna.

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