OTA test uncertainty analysis method and device

Abstract

The invention provides an OTA test uncertainty analysis method and device, and the method comprises the steps: measuring an EIS pattern # imgabs0 # of a main antenna and an EIS pattern # imgabs1 # of a diversity antenna, carrying out the offset of # imgabs2 # according to a preset penalty term, obtaining a biased EIS pattern # imgabs3 #, obtaining a combined pattern # imgabs6 #, carrying out the calculation of a standard TIS calculation method, and obtaining a TIS value CTIStd-i-j, calculating to obtain a TIS value CTISSPOT-i-j by adopting a single-point compensation method, and calculating a difference value of the TIS value CTISSPOT-i-j; for each group of EIS directional diagrams and a preset penalty term, repeating the above calculation process to obtain a preset number of difference samples; taking the statistical distribution parameter value of the difference value sample as an uncertainty value introduced by the single-point compensation method in the multi-antenna receiving scene; judging whether the uncertainty value is within a preset limit value range or not; if yes, judging that the single-point compensation method meets the accuracy requirement of the OTA test in the multi-antenna receiving scene; and if not, judging that the single-point compensation method does not meet the accuracy requirement of the OTA test in the multi-antenna receiving scene.

Description

Technical Field

[0001] The present invention relates to the field of communication testing technology, and in particular to an OTA test uncertainty analysis method and device. Background Art

[0002] This section is intended to provide a background or context for embodiments of the present invention. No description herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] Over-the-air (OTA) testing has become a standard test method for wireless communication devices such as smartphones and laptops 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 the measurement 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 must be measured at a large number of test grid points according to the spherical sampling grid distribution specified by the CTIA / 3GPP standards. The measured data are then integrated over the spherical surface and weighted averaged using specific numerical methods to obtain the corresponding TRP and TIS values. The OTA test method specified in the current standard requires a grid resolution of 15° for TRP and 30° for TIS measurements, respectively.

[0004] On the other hand, existing OTA testing methods, especially TIS testing, require a significant amount of testing time. Currently, a single-channel TIS test can take over half an hour. Considering that OTA testing of wireless communication devices requires comprehensive measurement of all channels, frequency bands, and frequency band combinations in various test postures and scenarios, the total testing time can reach hundreds of hours, making it prohibitive for product performance evaluation and certification testing in the industrial sector.

[0005] Single-point compensation testing is a fast OTA test method currently widely used in the industry. This method measures and compares the difference in the EIS values of the device under test in the reference frequency band and the test frequency band at the location (angle / polarization) of the optimal EIS value in the reference frequency band. This difference is used as the compensation value to determine the TIS value of the device under test in the test frequency band. The calculation relationship is:

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

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

[0008] The prerequisite for applying this method is that the device under test is a single-antenna device; and that the device under test has the same antenna radiator and the same aperture tuning (for example, matching on a parasitic element or matching elements in the ground or radiator) in the reference frequency band and the test frequency band, but different impedance matching can be used between the reference frequency band and the tested frequency band (for example, matching elements on the RF feed). The above requirements ensure that the device under test has the same antenna pattern shape and maximum position in the reference scenario and the test scenario, thereby ensuring the test accuracy of this method. This method is not applicable to scenarios where the device under test uses different antenna radiators and aperture tuning in the reference frequency band and the test frequency band.

[0009] Considering that this method can effectively reduce the test time while ensuring test accuracy, we are also considering extending it to scenarios where the device under test uses multiple antennas for reception. In the multi-antenna reception scenario, even if the device under test uses a set of completely identical antenna radiators in the reference frequency band and the test frequency band, changing the impedance matching of any receiving antenna will still cause the direction / polarization of the multi-antenna aggregate peak EIS to change, thereby deviating from the premise and rationality of the single-point compensation test. Therefore, it is necessary to evaluate the rationality of the use of this method in multi-antenna scenarios. At present, there is no uncertainty assessment method for the use of the single-point compensation method in multi-antenna reception scenarios in the industry.

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

[0011] In order to solve the problems existing in the prior art, the present invention proposes an OTA test uncertainty analysis method and device.

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

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

[0014] According to the preset penalty Perform bias and obtain the EIS pattern after bias

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

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

[0017] For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples;

[0018] 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 the multi-antenna reception scenario;

[0019] Determine whether the uncertainty value is within a preset limit value range; if so, determine that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if 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 an embodiment of the present invention, an OTA test uncertainty analysis device is provided, the device comprising:

[0021] Pattern measurement module, used to measure the EIS pattern of the main antenna and EIS pattern of diversity antenna

[0022] Bias processing module, used to adjust the Perform bias and obtain the EIS pattern after bias

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

[0024] Difference calculation module, used to calculate CTIS Std-i-j With CTIS SPOT-i-j The difference between

[0025] For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples;

[0026] An uncertainty calculation module is used to use 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 reception scenario;

[0027] An uncertainty judgment module is used to determine whether the uncertainty value is within a preset limit value range; if so, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if 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 an embodiment of the present invention, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements an OTA test uncertainty analysis method when executing the computer program.

[0029] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, an OTA test uncertainty analysis method is implemented.

[0030] In a fifth aspect of an embodiment of the present invention, a computer program product is proposed. The computer program product includes a computer program. When the computer program is executed by a processor, the computer program implements an OTA test uncertainty analysis method.

[0031] The OTA test uncertainty analysis method and device proposed in the present invention can effectively analyze test data of different penalty items, different test frequency ranges, different test scenarios, etc., provide strong support for the uncertainty analysis of the single-point compensation method in the multi-antenna reception scenario, improve the accuracy of related uncertainty analysis, expand the applicability of the single-point compensation method to multi-antenna receiving equipment, and improve the OTA test accuracy and test efficiency of wireless communication equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

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

[0034] Figure 2 FIG. 1 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 It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

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

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

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

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

[0040] Figure 1 FIG. 1 is a flow chart of an OTA test 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 EIS pattern of diversity antenna

[0042] S102, according to the preset penalty item Perform bias and obtain the EIS pattern after bias

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

[0044] S104, calculate CTIS Std-i-j With CTIS SPOT-i-j The difference between

[0045] For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples;

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

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

[0048] The OTA test uncertainty analysis method and device proposed in the present invention can effectively analyze test data of different penalty items, different test frequency ranges, different test scenarios, etc., provide strong support for the uncertainty analysis of the single-point compensation method in the multi-antenna reception scenario, improve the accuracy of related uncertainty analysis, expand the applicability of the single-point compensation method to multi-antenna receiving equipment, and improve the OTA test accuracy and test efficiency of wireless communication equipment.

[0049] In order to explain the above OTA test uncertainty analysis method more clearly, each step is described in detail below.

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

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

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

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

[0054] right and Normalize the and The peak EIS value in is set to the same downlink power value.

[0055] The purpose of normalization is mainly to consider the worst case scenario. For example, when multiple receiving antennas in a mobile phone have the same peak EIS (and similar antenna efficiency), changing the peak EIS of one of the receiving antennas (in other words, changing the radiation efficiency of the antenna by changing the impedance matching state) will produce the maximum change in the maximum value of the dual-antenna aggregate EIS and its direction offset, that is, the maximum measurement error. This ensures that the corresponding uncertainty evaluation method and results are suitable for all other combinations of multiple antenna radiation patterns. Taking into account the performance of current mainstream mobile phone terminals, it is preferred to define this value as: -95dBm or -100dBm;

[0056] In one embodiment, for S102, according to the preset penalty item Perform bias and obtain the EIS pattern after bias include:

[0057] The penalty item and The EIS values at each angle are added together, and the calculation formula is:

[0058]

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

[0060] Taking into account the adjustment range of the antenna port impedance adjustment module, the change in antenna efficiency that can be generated, in other words, the change in antenna peak gain generated, does not exceed 3dB at most.

[0061] The purpose of the bias operation is to artificially create a deviation between two EIS patterns with the same EIS peak (similar antenna radiation efficiency) so that the aggregate EIS peak of the two EIS patterns, that is, the combined pattern The peak value of the antenna pattern produces a certain amplitude variation and angular offset, thus deviating from the premise of the single-point compensation method: the DUT has the same antenna pattern shape and maximum position in the reference and test scenarios. This allows the measurement uncertainty introduced by the single-point compensation test method to be evaluated in multi-antenna reception scenarios.

[0062] In one embodiment, when selecting EIS patterns, priority is given to EIS patterns in low frequency bands; wherein, the proportion of patterns in frequency bands less than 1 GHz to the total number of patterns shall not be less than 50%, and the proportion of patterns in frequency bands greater than 3 GHz shall not be greater than 20%.

[0063] The EIS directional pattern includes at least a directional pattern of a free space scenario, a directional pattern of a head-hand scenario, and a directional pattern of a single-hand scenario.

[0064] In one embodiment, for S103, according to and Get the combined pattern for The TIS value CTIS is calculated using the standard TIS calculation method. Std-i-j , the TIS value CTIS is 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 as:

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

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

[0068] For each set of EIS patterns and preset penalty items, the above calculation process is repeated 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 values of a preset number of difference samples are used as uncertainty values introduced by the single-point compensation method in a multi-antenna reception scenario.

[0070] Specifically, the statistical distribution parameter value of the preset number of difference samples is:

[0071] the standard deviation of the sample of differences; 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 one of the following methods:

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

[0076] 2. The uncertainty value is based on different penalty terms Deltaj The weighted average of the standard deviation of the lower difference samples is calculated as follows;

[0077]

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

[0079] w j The calculation method is:

[0080] or, Among them, Delta j Arrange the values from smallest to largest.

[0081] 3. The uncertainty value is the weighted average of the standard deviation of the difference samples in different test frequency ranges. The calculation relationship is:

[0082]

[0083] Where MU' represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j ' is the weight corresponding to different test frequency intervals; DCTIS j ' is the standard deviation of the difference samples corresponding to the jth 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 intervals to 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] Wherein, MU” represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j " is the weight corresponding to different test scenarios; DCTIS j ” is the standard deviation of the difference samples corresponding to the jth test scene; N” is the number of different test scenes; w j” is the percentage of difference samples in different test scenarios to the total number of samples;

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

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

[0090] If yes, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario;

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

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

[0093] Refer to Table 1, which shows a set of uncertainty analysis samples of an exemplary OTA test uncertainty analysis method.

[0094] Table 1

[0095]

[0096]

[0097]

[0098] Comparing the deviations between the two sets of data in different test scenarios clearly demonstrates the variation in uncertainty of the single-point compensation method in each scenario. This uncertainty analysis can expand the applicability of the single-point compensation method to multi-antenna receiving devices, improving the accuracy and efficiency of OTA testing of wireless communication equipment.

[0099] It should be noted that although the operations of the method of the present invention are described in a specific order in the above embodiments and drawings, this does not require or imply that these operations must be performed in this specific order, or that all illustrated operations must be performed to achieve the desired results. 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 the exemplary embodiment of the present invention, next, reference is made to Figure 2 An OTA test uncertainty analysis device according to an exemplary embodiment of the present invention is introduced.

[0101] The implementation of the OTA test uncertainty analysis device can be referenced to the implementation of the above-mentioned method, and any repetitions will not be repeated here. The terms "module" or "unit" used below may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

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

[0103] Directional pattern measurement module 210, used to measure the EIS directivity pattern of the main antenna and EIS pattern of diversity antenna

[0104] The bias processing module 220 is used to adjust the bias according to the preset penalty term. Perform bias and obtain the EIS pattern after bias

[0105] TIS calculation module 230 is used to calculate the and Get the combined pattern for The TIS value CTIS is calculated using the standard TIS calculation method. Std-i-j , the TIS value CTIS is calculated using the single point compensation method SPOT-i-j ;

[0106] Difference calculation module 240, used to calculate CTIS Std-i-j With CTIS SPOT-i-j The difference between

[0107] For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples;

[0108] The uncertainty calculation module 250 is configured to use 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 reception scenario;

[0109] The uncertainty judgment module 260 is used to determine whether the uncertainty value is within a preset limit value range; if so, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if 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.

[0110] It should be noted that while the detailed description above mentions several modules of the OTA test uncertainty analysis device, this division is merely exemplary and not mandatory. In practice, according to embodiments of the present invention, the features and functions of two or more modules described above may be embodied in a single module. Conversely, the features and functions of a single module described above may 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 EIS pattern of diversity antenna include:

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

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

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

[0115] right and Normalize the and The peak EIS value in is set to the same downlink power value.

[0116] In one embodiment, the bias processing module 220, according to a preset penalty term Perform bias and obtain the EIS pattern after bias include:

[0117] The penalty item and The EIS values at each angle are added together, and the calculation formula is:

[0118]

[0119] Where, Delta represents the EIS pattern of the biased diversity antenna; j Indicates the penalty term, with a value range of 0dB to 3dB: 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 shall be given to EIS patterns in low frequency bands; the proportion of patterns in frequency bands less than 1 GHz to the total number of patterns shall not be less than 50%, and the proportion of patterns in frequency bands greater than 3 GHz shall not be greater than 20%;

[0122] The EIS directional pattern includes at least a directional pattern of a free space scenario, a directional pattern of a head-hand scenario, and a directional pattern of a single-hand scenario.

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

[0124] the standard deviation of the sample of differences; 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 values introduced by the single-point compensation method in the multi-antenna reception scenario, including:

[0128] The stated uncertainty value is determined by one of the following methods:

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

[0130] The uncertainty value is based on different penalty terms Delta j The weighted average of the standard deviation of the lower difference samples is calculated as follows;

[0131]

[0132] Where MU represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception 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 the number of

[0133] w j The calculation method is:

[0134] or, Among them, Delta j Arrange in ascending order of value;

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

[0136]

[0137] Where MU' represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j ' is the weight corresponding to different test frequency intervals; DCTIS j ' is the standard deviation of the difference samples corresponding to the jth 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 intervals to 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 relationship is:

[0139]

[0140] Wherein, MU” represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j " is the weight corresponding to different test scenarios; DCTIS j ” is the standard deviation of the difference samples corresponding to the jth test scene; N” is the number of different test scenes; w j ” is the percentage of difference samples in different test scenarios to the total number of samples.

[0141] In one embodiment, different test frequency intervals 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 uncertainty value corresponds to a preset limit value range of less than 0.5 dB.

[0146] Based on the above invention concept, 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, wherein the processor 320 implements the aforementioned OTA test uncertainty analysis method when executing the computer program 330.

[0147] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned OTA test uncertainty analysis method is implemented.

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

[0149] The OTA test uncertainty analysis method and device proposed in the present invention can effectively analyze test data of different penalty items, different test frequency ranges, different test scenarios, etc., provide strong support for the uncertainty analysis of the single-point compensation method in the multi-antenna reception scenario, improve the accuracy of related uncertainty analysis, expand the applicability of the single-point compensation method to multi-antenna receiving equipment, and improve the OTA test accuracy and test efficiency of wireless communication equipment.

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

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

[0152] The present invention is described with reference to flowcharts and / or block diagrams of methods and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0153] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0155] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. 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 above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection 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 EIS pattern of diversity antenna According to the preset penalty Perform bias and obtain the EIS pattern after bias according to and Get the combined pattern for The TIS value CTIS is calculated using the standard TIS calculation method. Std-i-j , the TIS value CTIS is calculated using the single point compensation method SPOT-i-j ; Calculate CTIS Std-i-j With CTIS SPOT-i-j The difference between For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples; 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 the multi-antenna reception scenario; Determine whether the uncertainty value is within a preset limit value range; if so, determine that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if not, determine that the single-point compensation method does not meet the accuracy requirements of OTA testing in a multi-antenna reception scenario.

2. The OTA test uncertainty analysis method according to claim 1, wherein Measure the EIS pattern of the main antenna and EIS pattern of diversity antenna include: Directly measure the EIS patterns of the main and diversity antennas; or, The EIRP patterns of the main antenna and diversity antenna are measured respectively, and the corresponding EIS patterns are obtained by normalization.

3. The OTA test uncertainty analysis method according to claim 1, wherein: The method further includes: right and Perform normalization processing and and The peak EIS value in is set to the same downlink power value.

4. The OTA test uncertainty analysis method according to claim 1, wherein: According to the preset penalty Perform bias and obtain the EIS pattern after bias include: The penalty item and The EIS values at each angle are added together, and the calculation relationship is: Where, Delta represents the EIS pattern of the biased diversity antenna; j Indicates the penalty term, with a value range of 0dB to 3dB: represents the initial EIS pattern of the diversity antenna.

5. The OTA test uncertainty analysis method according to claim 1, wherein: The method further includes: When selecting EIS patterns, priority shall be given to EIS patterns in low frequency bands; the proportion of patterns in frequency bands less than 1 GHz to the total number of patterns shall not be less than 50%, and the proportion of patterns in frequency bands greater than 3 GHz shall not be greater than 20%; The EIS directional pattern includes at least a directional pattern of a free space scenario, a directional pattern of a head-hand scenario, and a directional pattern of a single-hand scenario.

6. The OTA test uncertainty analysis method according to claim 1, characterized in that: The statistical distribution parameter value of the preset number of difference samples is: the standard deviation of the sample of differences; 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.

7. The OTA test uncertainty analysis method according to claim 1, characterized in that: 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 reception scenario, including: The stated uncertainty value is determined by one of the following methods: The uncertainty value is based on different penalty terms Delta j The arithmetic mean of the standard deviations of the lower difference samples; The uncertainty value is based on different penalty terms Delta j The weighted average of the standard deviation of the lower difference samples is calculated as follows; Where MU represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception 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 the number of w j The calculation method is: or, Among them, Delta j Arrange in ascending order of value; The uncertainty value is the weighted average of the standard deviations of the difference samples in different test frequency ranges, and the calculation relationship is: Where MU' represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j ' is the weight corresponding to different test frequency intervals; DCTIS j ' is the standard deviation of the difference samples corresponding to the jth 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 intervals to 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 relationship is: Wherein, MU” represents the uncertainty value introduced by the single-point compensation method in the multi-antenna reception scenario; w j " is the weight corresponding to different test scenarios; DCTIS j ” is the standard deviation of the difference samples corresponding to the jth test scene; N” is the number of different test scenes; w j ” is the percentage of difference samples in different test scenarios to the total number of samples.

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

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

10. An OTA test uncertainty analysis device, characterized in that: The device includes: Pattern measurement module, used to measure the EIS pattern of the main antenna and EIS pattern of diversity antenna Bias processing module, used to adjust the Perform bias and obtain the EIS pattern after bias TIS calculation module is used to calculate the and Get the combined pattern for The TIS value CTIS is calculated using the standard TIS calculation method. Std-i-j , the TIS value CTIS is calculated using the single point compensation method SPOT-i-j ; Difference calculation module, used to calculate CTIS Std-i-j With CTIS SPOT-i-j The difference between For each set of EIS patterns and the preset penalty term, the above calculation process is repeated to obtain a preset number of difference samples; An uncertainty calculation module is used to use 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 reception scenario; An uncertainty judgment module is used to determine whether the uncertainty value is within a preset limit value range; if so, it is determined that the single-point compensation method meets the accuracy requirements of OTA testing in a multi-antenna reception scenario; if 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.

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