Error Vector Magnitude Measurement Correction

Abstract

An exemplary process determines a first error vector magnitude (EVM) of a signal output by a device under test (DUT), the process including adding attenuation on a signal path between the DUT and a vector signal analyzer (VSA), where the attenuation is variable, measuring at least two second EVMs at the VSA for different values ​​of attenuation of the signal output by the DUT, where the at least two second EVMs are corrupted by noise from the VSA, each of the at least two second EVMs being based on two or more measurements, and determining a first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and a function based on the attenuation, where the first EVM does not include at least a portion of the noise from the VSA.

Description

[Technical field]

[0001] This specification describes an example system for correcting error vector magnitude measurements. [Background technology]

[0002] Test systems are configured to test the operation of electronic devices. Testing may include sending signals to the devices and determining how the devices reacted to those signals based on the responses. For example, testing may include sending test signals to a device, such as an integrated circuit (IC), and receiving radio frequency (RF) signals returning from the device. The RF signals are processed to determine whether the device is operating acceptably. Error Vector Magnitude (EVM) is a measure of the quality of the signal received from the DUT. Summary of the Invention [Means for solving the problem]

[0003] An exemplary process determines a first error vector magnitude (EVM) of a signal output by a device under test (DUT), the process including adding attenuation on a signal path between the DUT and a vector signal analyzer (VSA), the attenuation being variable, measuring at least two second EVMs at the VSA for different values ​​of attenuation of the signal output by the DUT, the at least two second EVMs being corrupted by noise from the VSA, each of the at least two second EVMs being based on two or more measurements, and determining a first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and a function based on the attenuation, the first EVM not including at least a portion of the noise from the VSA. The process may include one or more of the following exemplary features, alone or in combination.

[0004] The process may include determining the noise from the VSA based on a slope of a line fit to the at least two second EVMs. The process may include holding an output signal from the DUT constant while varying attenuation using an attenuator to generate an input signal to the VSA. For each different value of attenuation, the process may include measuring one or more additional second EVMs at the VSA, each of the one or more additional second EVMs being based on two or more measurements, and determining the first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and the one or more additional second EVMs, and a function based on attenuation.

[0005] The process may include varying a reference level signal to the VSA corresponding to a maximum signal the VSA can handle without causing significant distortion in the signal output by the DUT, and repeating the adding, measuring, and determining for each change in the input signal to generate a different first EVM. The linear relationship may include an intersection of a line passing through at least two second EVM-based values ​​with a zero value of the attenuation-based function. The linear relationship may include a slope of the line passing through at least two second EVM-based values. Determining the first EVM based on the linear relationship may include extrapolating the line based on the slope to a zero value of the attenuation-based function. The attenuation-based function may include the inverse of the square of the attenuation.

[0006] The compression distortion is a function of the gain of the VSA. The process may include reducing the gain of the VSA to reduce the distortion added in the first EVM. An optimized first EVM may be determined at a VSA gain that substantially eliminates the compression distortion from the VSA. Reducing the VSA gain may reduce the contribution of the compression distortion of the VSA to the first EVM.

[0007] The process may include obtaining a value of attenuation based on varying a gain of the VSA. Obtaining a value of attenuation may include obtaining EVM measurements based on different gain settings of the VSA corresponding to different noise contributions of the VSA and different attenuation values, and identifying one of the attenuation values ​​based on the EVM measurements, where the EVM measurements are substantially the same. If the EVM measurements do not change, one of the attenuation values ​​is the actual attention in the test channel. If the EVM measurements decrease in response to the change in attenuation value, the value of attenuation may be decreased to obtain additional EVM measurements. If the EVM increases in response to the change in attenuation value, the value of attenuation may be increased to obtain additional EVM measurements.

[0008] The process may be performed on an automatic test equipment (ATE) that includes at least one processor and a memory that stores instructions executable by the at least one processor, and the VSA may or may not be part of the ATE. The process may be performed using an attenuator between the ATE and the DUT. The process may be performed using an attenuator that is part of the ATE.

[0009] An exemplary process compensates for the effect of phase noise on a first error vector magnitude (EVM) of a signal output by a device under test (DUT). The process includes estimating an EVM contribution from phase noise of a vector signal analyzer (VSA) and removing the EVM contribution from the phase noise from the first EVM. The process may include one or more of the following exemplary features, either alone or in combination:

[0010] Estimating the phase noise may include obtaining a first EVM contribution from the phase noise based on measurements obtained from a first VSA having a local oscillator in common with a vector signal generator (VSG), obtaining a second EVM contribution from the phase noise based on measurements obtained from a second VSA having a local oscillator independent or different from the VSG, the second VSA having performance and signal levels comparable to the first VSA, and estimating the EVM contribution from the phase noise based on a difference between the first EVM contribution and the second EVM contribution. The first VSA and the second VSA may be different. The first VSA and the second VSA may be the same.

[0011] Any two or more of the features described herein, including in this Summary, may be combined to form implementations not specifically described herein.

[0012] Various systems described herein, or portions thereof, may be implemented at least in part by a computer program product that includes instructions stored on one or more non-transitory machine-readable storage media and executable on one or more processing devices (e.g., programmed logic such as a microprocessor, application specific integrated circuit, programmable gate array, etc.). The processes described herein, or portions thereof, may be implemented as an apparatus, method, or system that may include one or more processing devices and a computer memory that stores executable instructions for implementing control of the described functions. The apparatus, systems, processes, and / or components described herein may be configured, for example, by design, construction, arrangement, positioning, programming, operation, activation, deactivation, and / or control.

[0013] The details of one or more implementations are set forth in the accompanying drawings and the description below. Other features and advantages will become apparent from the description and drawings, and from the claims. [Brief description of the drawings]

[0014] [Figure 1]1 is a graph illustrating an example error vector. [Diagram 2] 1 is a block diagram illustrating components of an example test channel and components of an example test system. [Diagram 3] 1 is a graph showing error vector magnitude information plotted against a function based on attenuation. [Figure 4] 5 is a flowchart illustrating an exemplary process for identifying and removing white noise from error vector magnitude measurements. [Diagram 5] 1 is a graph showing error vector magnitude information plotted against reference levels for different vector signal analyzers. [Figure 6] 4 is a flowchart illustrating an example process for determining attenuation in a test channel of a test system. [Figure 7] FIG. 1 is a block diagram illustrating a vector signal analyzer and a vector signal generator that operate using independent local oscillators. [Figure 8] FIG. 1 is a block diagram illustrating a vector signal analyzer and a vector signal generator that operate using a common local oscillator. [Figure 9] 5 is a flowchart illustrating an exemplary process for determining and removing phase noise from an error vector magnitude measurement. [Figure 10] 1 is a graph showing error vector magnitude information plotted against reference levels for different vector signal analyzers and the effect of reducing compression distortion. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Like reference numbers in different drawings indicate like elements.

[0016] Described herein are exemplary implementations of techniques, processes, and test systems, such as automatic test equipment (ATE), configured to correct error vector magnitude (EVM) measurements. EVM is a measure of how accurately a device under test (DUT) transmits symbols in a signal space. An example of a signal space diagram includes a graphical representation of symbols transmitted using a radio frequency (RF) signal. In this regard, a digitally modulated signal encodes information using a sinusoidal carrier signal by mixing the sinusoidal carrier with a data signal. The data signal modifies the amplitude, phase angle, or both the amplitude and phase angle of the carrier signal to generate a modulated signal. The modulated signal includes a combination of amplitude and phase values. This combination of amplitude and phase values ​​may represent symbols that represent one or more bits of data. These symbols correspond to points on the signal space diagram. The location of each point on the signal space diagram is based on the amplitude and phase angle associated with the corresponding symbol.

[0017] In the example signal space diagram 10 of Figure 1, points representing 4-bit symbols are placed on a two-dimensional graph representing the in-phase (I) and quadrature (Q) complex planes. In this example, each point represents the ideal location of the symbol within that plane. However, in other examples, each point may represent an estimated location of the ideal point within the plane.

[0018] When the received data is demodulated, the location of the symbol represented by the data, such as "0001," is identified on the constellation diagram. In some cases, the location of the symbol represented by the data does not match the location of that symbol on the constellation diagram. For example, the symbol represented by the data (0001) may be located at point 12 on the constellation diagram. The difference between the ideal point 11 of "0001" and the measured point 12 constitutes an error, which may be due to noise in the RF signal on which the data is based. This error can be determined with respect to the nearest predetermined point in the constellation diagram. An error vector 13 represents this difference in location between the predetermined point and the measured point. The magnitude of this vector 13 is the EVM.

[0019] EVM measurements may be corrupted, which may adversely affect the accuracy of the EVM measurement. For example, white noise, compression distortion, and phase noise may degrade the accuracy of the EVM measurement. The exemplary systems, techniques, and processes described herein address white noise, compression distortion, and phase in the EVM measurement, thereby improving the accuracy of the EVM measurement. The techniques and processes are described in the context of a test system, but are not limited to use with a test system or in a test context.

[0020] Figure 2 illustrates an exemplary test channel ("channel") 14 of an exemplary test system 15 or ATE. As shown in Figure 2, the channel 14 is configured to connect to a DUT 17, such as an 802.11be Wi-Fi device or other type of device, that is configured to transmit an RF signal to the test system for analysis. Although an 802.11be Wi-Fi device is mentioned, any type of DUT that outputs an RF signal can be tested by the test system.

[0021] The channel 14 includes attenuation circuitry 18 configured to provide attenuation 19 to the channel 14. Attenuation includes loss of signal strength in a channel and is typically measured in decibels (dB) or voltage units. Exemplary levels of attenuation include, but are not limited to, 30db or less, 20db or less, 15db or less, 10db or less, etc. The level of attenuation can be varied, and the amount of acceptable variation can vary depending on the type of test system and the type of DUT being tested by the test system. The attenuation circuitry 18 can be or include an adjustable attenuator 20 or one or more variable path loss circuit elements. In one example, the adjustable attenuator is a step attenuator that provides discrete steps or levels of attenuation selectable by a control system. In some implementations, the attenuation circuitry 18 is part of the test system 15. In some implementations, the attenuation circuitry 18 is not part of the test system 15 as shown in FIG. 2.

[0022] The channel 14 includes a vector signal analyzer (VSA) 22. An exemplary vector signal analyzer is a hardware device configured to measure the amplitude and phase of an input signal at a frequency within the bandwidth of the VSA. The VSA may also be configured to perform in-channel signal measurements, including measuring the EVM of the input signal. In this example, the input signal is a signal from a DUT. The signal from the DUT may be a response to a test stimulus or may be independent of the test stimulus. The VSA 22 may include a local oscillator (LO) 23. An exemplary LO is a hardware device that includes one or more voltage controlled oscillators and / or one or more phase-locked loops (PLLs) configured to change the frequency of the VSA input signal. In some implementations, the local oscillator is a separate component from the VSA. In some implementations, the attenuation circuitry 18 is part of the VSA. In any case, in some implementations, the attenuation is configured to occur before the gain of the VSA.

[0023] Test system 15 also includes a control system 25. Control system 25 may include one or more processing devices 26, examples of which are described herein. Control system 25 also includes memory 27 that stores computer code or instructions 28 executable by one or more computing devices to perform at least a portion of the processes described herein for correcting EVM measurements.

[0024] In this regard, as previously discussed, VSA 22 is used to receive and analyze an input signal from DUT 17 to determine an EVM measurement of the input signal. The EVM determined by the VSA includes the EVM error contributions of both the DUT and the VSA. Thus, the EVM determined by the VSA may not be an accurate representation of the signal EVM, especially if the variances of the error contributions from the DUT and VSA are comparable. For example, if the error contributions are in-phase, they may have a cumulative effect on the EVM measured by the VSA.

[0025] Part of the error contribution of VSA22 is called white noise, which can be or include one or more random signals, can have equal intensity at different frequencies, and gives a substantially constant power spectral density to the white noise. In some examples, the signal output of the change in the received input signal, although not limited to this, when within a certain range such as from 6 dB to 3 dB or 2 dB or less, the white noise of VSA22 does not change. Therefore, the attenuation applied to channel 14 does not substantially affect the white noise of the VSA within that range. However, other errors that may be introduced into the EVM are scaled according to the following equation: y = Ax + An x +n VSA,WN where A represents the attenuation introduced by the attenuator 20 (0 < A < 1), y represents the input signal in VSA22 received from the DUT17, x represents the ideal version of the input signal from the DUT without error, and n VSA,WN represents the error contribution due to the white noise introduced by VSA22, and n x represents the error other than the white noise introduced by VSA22, including the error introduced into the input signal by the DUT17. Therefore, the EVM measurement from the VSA including all error contributions ("original EVM result") can be expressed as follows:

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[0026] As shown in Figure 3, E[EVM 2 ] is 1 / A 2 More specifically, graph 30 includes data points 33 and 34, which represent E[EVM 2 ]. Line 35 can therefore be obtained by keeping the signal output from the DUT constant (e.g. at constant power) and varying the channel attenuation 19 which causes a change in the signal input to the VSA. E[EVM 2 The more data points of ] are available, the more accurate the resulting line 35 can be.

[0027] In Figure 3, the EVM VSA,WN 37 is the white noise contribution of the VSA. EVM x 38 is the EVM measured by the VSA with the white noise contribution to the EVM due to the VSA removed. x The expectation value E[EVM 2 x ] is the zero intercept 38 of the line 35, and EVM VSA,WN The expectation value E[EVM 2 VSA,WN ] is the slope 37 of the line 35. Therefore, when the graph shown in FIG. VSA,WN and EVM x The value of E[EVM 2VSA,WN ] and E[EVM 2 x ], where E[] is the expectation of a random variable. In an exemplary implementation, this expectation is obtained by averaging. In particular, the process described herein uses the expectation of (E[EVM 2 ]) 1 / 2 is determined as the EVM. In other words, the "EVM" determined is the instance EVM for simplicity, since a single instance may not be used due to possible EVM value fluctuations. 2 Therefore, the EVM determined in the exemplary implementation described herein is (E[EVM 2 ]) 1 / 2 is equivalent to

[0028] Figure 4 shows the EVM VSA,WN and EVM x 6 is a flow chart illustrating an example process 40 for obtaining an attenuation on the signal path / channel 14 between the DUT 17 and the VSA 22 (40a). The attenuator 20 may be controlled by a control system, for example, to set its initial attenuation level between 0 (maximum attenuation) and 1 (no attenuation). The obtained attenuation value (40a) may be the attenuation set by the control system, or may be the attenuation determined using a process 50 described below with respect to FIG.

[0029] The DUT 17 is controlled by the control system to output a constant level signal, such as a constant power (40b). This signal from the DUT signal is input to and received by the VSA 22 (40c). The VSA 22 measures the EVM of this input signal (40d) to obtain an original EVM result (i.e., the EVM of the input signal without the VSA's white noise contribution removed). As mentioned above, the VSA corrupts the EVM by introducing white noise into the EVM. The measurement of the EVM of a signal may be based on at least two (or multiple) EVM measurements of the same signal performed by the VSA. E[EVM 2] may be based on an average of at least two EVM measurements or other processing performed on the EVM measurements. The VSA may provide the EVM information to a control system (40e). For example, E[EVM 2 ], or the VSA itself may provide the individual EVMs to a control system to determine E[EVM 2 ] and provide it to the control system (40e).

[0030] Process 40 then adds additional EVM information (e.g., E[EVM 2 ] data points) are needed (40f). The number of data points needed can be set programmatically in the control system or by the user. 2 If a ] data point is required, then the attenuator 20 is controlled by the control system (40g). The attenuator 20 is controlled by the control system to change its attenuation, for example by 2%, 5%, 10% or so from its previous value, or in one or more steps in the case of a step attenuator. Operations 40a through 40f are then repeated for the new attenuation to determine the E[EVM 2 ] is obtained. 2 Operations 40a through 40g can be repeated to obtain as many values ​​of [EVM] as desired, for example two, three, four, five, six, or more EVM values.

[0031] All EVM information (e.g., the required number of E[EVM 2 ] data points), the control system calculates the 1 / A 2 For a function based on attenuation such as 32, E[EVM 2 ] (e.g., points 33 and 34 in FIG. 3) (40h). The control system performs linear interpolation to fit a line through these values ​​(40i). The control system calculates E[EVM 2 VSA,WNThe slope of the resulting line is taken to obtain the value of E[EVM 2 x To obtain the value of , we use the function 1 / A 2 The line can be extrapolated to reach a zero intercept value of (40k). E[EVM 2 x ] corresponds to the EVM measured by the VSA with the white noise contribution to the EVM due to the VSA removed. 2 VSA,WN ] to EVM VSA,WN To obtain the values ​​of and E[EVM 2 x ] to EVM x Mathematical operations as described herein may be performed (401) to obtain a value of E[EVM 2 VSA,WN ] and E[EVM 2 x ] could be the square root of

[0032] 5 is a graph 42 showing various EVM values ​​for an exemplary input signal having an output of -30 dBm (decibels per milliwatt) as measured by the VSA 22. More specifically, graph 42 shows EVM measurements 43 as a function of different values ​​of the VSA Reference Level (RLEV) 44 (in dBm), the VSA Reference Level being a setting that tells the VSA the expected RMS (root mean square) output of all signals entering the VSA and configures the VSA for use with such signals. The VSA Reference Level generally corresponds to the largest signal that the VSA can analyze without introducing significant distortion into the signal.

[0033] In Fig. 5, curve 45 represents the original EVM results for different VSA reference levels, i.e., the EVM of the input signal from the DUT as measured by the VSA and including white noise introduced by the VSA. Curve 46 represents the EVM results for different VSA reference levels. VSA,WN , the white noise contribution to the EVM from the VSA. For each value of RLEV, the EVM VSA,WNCorresponding values ​​of can be determined as described herein and in relation to Figures 2-4. Curve 47 shows the EVM for different VSA reference levels. x Curve 47 thus also represents the difference between curves 45 and 46. For each VSA reference level, the EVM x Corresponding values ​​of can be determined in the manner described herein and with respect to FIGS.

[0034] In this particular non-limiting example, the original EVM result can reach -40 dB (decibels) by adjusting the value of RLEV. Since further reduction of the RLEV value starts to compress the received input signal, -40 dB is approximately the best original EVM result that can be achieved. However, since the white noise error of the VSA dominates, the original EVM result does not provide any clue to the true EVM of the DUT signal. Using the techniques described herein, it is possible to split the original EVM of curve 45 into curves 46 and 47. As a result, it can be seen that the true EVM of the DUT signal is approximately -51 dB, which is approximately 10 dB lower than the original EVM result of curve 45.

[0035] To generate the graph shown in Figure 5, the control system varies the VSA reference level inputs to the VSA, performing operations 40a through 40l of Figure 4 for each of the VSA reference level inputs. The control system essentially x To obtain the EVM (curve 47 in Figure 5), the EVM signal (curve 45 in Figure 5) was corrupted by white noise from the VSA. VSA,WN (curve 46 in FIG. 5) or the EVM of curve 47. x The value of can be obtained directly as described above.

[0036] In addition to white noise, a VSA may introduce compression error (also called compression distortion or simply "compression") into the EVM measurement. Both the white noise and compression distortion of the VSA are functions of the gain of the VSA ("VSA gain"), where gain is an adjustable setting of the VSA to add power and / or amplitude to the signal. In a conventional exemplary raw EVM measurement designed to minimize the overall error in EVM, the optimization of the VSA gain g is as follows:

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[0037] 10 is a graph illustrating the removal of compressive distortion from the original EVM results for different VSA reference levels, i.e., EVM measurement 70, which represents the EVM of an input signal from a DUT, including white noise and compressive noise, as measured by a VSA. Curve 71 shows the EVM for different VSA reference levels. VSA,WN , i.e., the white noise contribution to the EVM from the VSA. Curve 72 represents the EVM for different VSA reference levels. x RLEV, i.e., the EVM measured by the VSA with the white noise contribution to the EVM from the VSA removed. Curve 72 therefore also represents the difference between curves 70 and 71. As shown in Figure 10, region 74 is the region where the VSA gain is the greatest, and therefore most of the compression distortion occurs here. Outside this region, the VSA gain is controlled to be relatively low, which reduces the compression distortion in the compression region and changes EVMx from an original average of -51db to a compensated average of -55db. This figure shows that by increasing RLEV to obtain about 4dB less gain, the noise compensated EVM (71) can be reduced by an additional 2dB.

[0038] The accuracy of the results provided by the techniques described with respect to Figures 2 to 5 may be based on the accuracy of the attenuation values ​​used. In one example, the attenuator 20 is a step attenuator, and the attenuation values ​​generated are set in the attenuator by the control system. However, the actual attenuation value in the test channel may differ from the value set by the attenuator. For example, the structure and other components of the test channel may add attenuation, or the performance of the attenuator may change, for example, based on temperature. Thus, the following techniques may be used to determine the actual attenuation in the test channel. These techniques may be performed by the control system each time the attenuation is changed by the control system (40g in Figure 4).

[0039] The estimated damping is defined as the damping set in the damper by the control system.

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[0040] To provide accurate attenuation estimation, the process described herein uses the EVM x Sweep the VSA gain to measure the attenuation based on the results of EVM VSA,Wn Since is a function of the VSA gain, the estimate

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[0041] 6 illustrates an exemplary process 50 that may be performed in part by control system 25 to estimate one or more values ​​of attenuation based on varying the gain of a VSA. Process 50 includes estimating an attenuation estimate A, such as an attenuation setting set in an attenuator by the control system. 1 The process 50 selects (50a) an EVM value, e.g., E[EVM 2 2 through 5 for the current gain. x Value (e.g. (E[EVM 2 ]) 1 / 2) (50c). If additional EVMx values ​​are needed (50d), processing proceeds to obtain EVM and EVMx values ​​for the new gain (50e). In this regard, the number of EVMx values ​​required by process 50 may be set by a control system and may be based on the number of gain values ​​to be tested using the VSA. Larger gain values ​​may provide more accurate results, and the number of gain values ​​to be used may be determined empirically. Process 50 changes the gain of the VSA (50e). For example, process 50 may increase or decrease the gain by 1%, 2%, 3%, 4%, 5%, 10%, etc. Process 50 obtains an EVM value, e.g., E[EVM 2 ](50b) and E.V.M. x Value (e.g. (E[EVMx 2 ]) 1 / 2 ) (50c). Operations 50c through 50e may be repeated for multiple gain values ​​within the range of gains that may be set by the control system. Each increment or decrement in the VSA gain may be the same or different.

[0042] After repeating operations 50c to 50e as many times as necessary, the resulting EVM x Compare the values ​​with each other (50f). EVM x If the values ​​are all the same (50g) or within a predefined tolerance of each other, such as within 1%, 2%, 3%, 4%, or 5% of each other, the process 50 considers the attenuation to be the actual attenuation (50i). x If two or more of the values ​​are different or not within a predefined tolerance of each other, a new attenuation estimate A k (50h) and compare the previously measured EVM values ​​E[EVM 2 ] and the corresponding E[EVM 2 VSA,WN ] value and create a new A k About the new EVM x Continue the process according to equation (1) above to calculate the value. The resulting calculated EVM x Compare the values ​​with each other (50f). EVM xIf the values ​​are all the same (50g) or within a predefined tolerance of each other, such as within 1%, 2%, 3%, 4%, or 5% of each other, the process 50 creates a new decay estimate A k is considered as the actual attenuation (50i). But EVM x If two or more of the values ​​are different or not within a predefined tolerance of each other, the next new / estimated value A k Repeat the operations 50g, 50h, 50j, and 50f for EVM x If decreases with VSA gain, A k+1 A k / step_scale, where step_scale is the step size of the step attenuator. EVM x If increases with VSA gain, A k+1 A k * The step_scale may be set to 0. The process 50 may continue until an accurate value for the attenuation is determined (50i). If none of the values ​​of attenuation meet the above criteria, the value of attenuation that most closely meets the criteria may be selected as the actual value.

[0043] The processes described herein can also be used to address the phase noise contribution of the VSA to the EVM measurement. In this regard, the VSA phase noise is proportional to the power of the received signal, not the VSA gain. Therefore, the VSA phase noise is proportional to the EVM measurement determined using the techniques described with respect to FIGS. x Therefore, we estimate the EVM contribution due to the phase noise of the VSA and calculate the EVM x By removing the EVM contribution due to phase noise from x To compensate for the effects of phase noise in , the process described below can be implemented.

[0044] 7 and 8, VSAs 60a and 60b, which may be the same as VSA 22 in FIG. 2, receive and analyze (e.g., measure the EVM of) signals from individual vector signal generators (VSGs) 61a and 61b. In the configuration of FIG. 7, VSG 61a and VSA 60a operate using independent LOs 62a and 63a, respectively, which may have similar performance but are uncorrelated. In the configuration of FIG. 8, VSG 61b and VSA 60b operate using the same LO 64b. VSA 60a may be the same as VSA 60b, or VSA 60a may be different from VSA 60b. If the VSAs are the same, they may have the same configuration and performance. VSG 61a may be the same as VSG 61b, or VSG 61a may be different from VSG 61b. If the VSGs are the same, they may have the same configuration and performance. LO 64b may be the same as LO 62a or LO 63a, or may be different from LO 62a or LO 63a. If LO 64b is the same as LO 62a or LO 63a, the two LOs that are the same may have the same configuration and performance.

[0045] Figure 9 shows an exemplary process 61 for estimating the VSA phase noise contribution to EVM using the configurations of Figures 7 and 8. The process 61 estimates a first EVM contribution from phase noise (EVM x ) is obtained (61a). Specifically, the first EVM obtained using the configuration of FIG. x The contribution can be expressed as:

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[0046] The process 61 calculates a second EVM contribution from phase noise (EVM x ) is obtained (61b). The second EVM obtained using the configuration of FIG. x,SLO The contribution can be expressed as:

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[0047] The process 61 includes estimating (61c) the EVM contribution from the phase noise based on a difference between the first EVM contribution and the second EVM contribution. More specifically, x Results and 2nd EVM x Combining the results and knowing that the phase noise contribution from the VSG and VSA with similar performance LO of FIG. 8 is the same, the VSA phase noise contribution can be expressed as:

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[0048] All or portions of the systems and processes described herein and various modifications thereof may be configured or controlled at least in part by one or more computers, such as control system 25, using one or more computer programs tangibly embodied in one or more information carriers, such as one or more non-transitory machine-readable storage media. The computer programs may be written in any type of programming language, including compiled or interpreted languages, and may be implemented in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. The computer programs may be implemented to be executed on one computer or on multiple computers at one site, or may be distributed across multiple sites and interconnected by a network.

[0049] Actions relating to the configuration or control of the test systems and processes described herein may be performed by one or more programmable processors executing one or more computer programs for controlling or performing all or a portion of the operations described herein. All or a portion of the test system may be configured or controlled by special purpose logic circuitry such as FPGAs (field programmable gate arrays) and / or ASICs (application specific integrated circuits) or embedded microprocessors that are local to the hardware of the instrument.

[0050] Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor receives instructions and data from a read-only or random access memory area, or both. Elements of a computer include one or more processors for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer also includes one or more machine-readable storage media, such as a mass storage device for storing data, such as a magnetic disk, a magneto-optical disk, or an optical disk, or is operatively coupled to receive, transfer, or both data from such machine-readable storage media. Non-transitory machine-readable storage media suitable for embodying computer program instructions and data include all types of non-volatile storage including, by way of example, semiconductor storage devices such as EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory) and flash storage devices, magnetic disks such as internal hard disks or removable disks, magneto-optical disks, and CD-ROMs (Compact Disk-Read-Only Memory) and DVD-ROMs (Digital Versatile Disk-Read-Only Memory).

[0051] Elements of the various implementations described may be combined to form other embodiments not specifically described above. Elements may be removed from the systems described above without adversely affecting the operation of the systems or the operation of the overall system. Additionally, various separate elements may be combined into one or more individual elements to perform the functions described herein.

[0052] Other implementations not specifically described herein are within the scope of the following claims.

Claims

1. 1. A method for determining a first error vector magnitude (EVM) of a signal output by a device under test (DUT), comprising: adding attenuation on a signal path between the DUT and a vector signal analyzer (VSA), the attenuation being variable; measuring at least two second EVMs at the VSA for different values ​​of attenuation of the signal output by the DUT, the at least two second EVMs being corrupted by noise from the VSA, each of the at least two second EVMs being based on two or more measurements; determining the first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and a function based on the attenuation, the first EVM being free of at least a portion of the noise from the VSA; A method comprising:

2. determining the noise from the VSA based on a slope of a line fit to the at least two second EVMs; The method of claim 1 further comprising:

3. Using an attenuator to generate an input signal to the VSA, while varying the attenuation, keeping the output signal from the DUT constant. Further comprising: The method further comprises: for each different value of the attenuation: measuring one or more additional second EVMs at the VSA, each of the one or more additional second EVMs being based on two or more measurements; determining the first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and the one or more additional second EVMs, and the function based on the attenuation; The method of claim 2 , comprising:

4. Varying a reference level signal to the VSA corresponding to the largest signal that the VSA can handle without causing significant distortion in the signal output by the DUT; repeating the adding, measuring, and determining for each change in the input signal to generate a different first EVM; The method of claim 1 further comprising:

5. The method of claim 1 , wherein the linear relationship comprises an intersection of a line passing through the at least two second EVM-based values ​​with a zero value of the attenuation-based function.

6. the linear relationship includes a slope of a line passing through the at least two second EVM-based values; determining includes extrapolating the line based on the slope to a zero value of a function based on the attenuation, the function based on the attenuation including the inverse of the square of the attenuation. The method of claim 1.

7. the compression distortion is a function of the gain of the VSA; the method further comprising reducing a gain of the VSA to reduce added distortion in the first EVM. The method of claim 1.

8. The method of claim 1 , wherein a first EVM optimized at a VSA gain that substantially eliminates compressive distortion from the VSA is determined.

9. The method of claim 1 , wherein a compressive distortion contribution of the VSA to the first EVM is reduced by reducing a VSA gain.

10. Obtaining the value of the attenuation based on varying the gain of the VSA The method of claim 1 further comprising:

11. Obtaining the value of the attenuation obtaining EVM measurements based on different gain settings of the VSA corresponding to different noise contributions and different attenuation values ​​of the VSA; identifying one of the attenuation values ​​based on the EVM measurements, wherein the EVM measurements are substantially the same; and The method of claim 10, comprising:

12. The method of claim 11 , wherein if the EVM measurement does not change, the one of the attenuation values ​​is the actual attention in a test channel.

13. If the EVM measurement decreases in response to a change in the attenuation value, decreasing the attenuation value to obtain an additional EVM measurement; if EVM increases in response to a change in attenuation value, increasing the value of attenuation to obtain an additional EVM measurement; The method of claim 11.

14. 10. The method of claim 1, wherein the method is performed on automatic test equipment (ATE) including at least one processing unit and a memory storing instructions executable by the at least one processing unit, and the VSA is part of the ATE.

15. The method of claim 14 , wherein the method is performed using an attenuator between the ATE and the DUT.

16. The method of claim 14 , wherein the method is performed using an attenuator that is part of the ATE.

17. 1. A method for compensating for an effect of phase noise on a first error vector magnitude (EVM) of a signal output by a device under test (DUT), comprising: Estimating the EVM contribution from vector signal analyzer (VSA) phase noise; removing the EVM contribution from phase noise from the first EVM; A method comprising:

18. estimating the phase noise obtaining a first EVM contribution from phase noise based on measurements obtained from a first VSA having a common local oscillator with a vector signal generator (VSG); obtaining a second EVM contribution from phase noise based on measurements obtained from a second VSA having a local oscillator independent or different from the VSG, the second VSA having performance and signal levels comparable to the first VSA; estimating the EVM contribution from phase noise based on a difference between the first EVM contribution and the second EVM contribution; 20. The method of claim 17, comprising:

19. The method of claim 18 , wherein the first VSA and the second VSA are different.

20. 20. The method of claim 18, wherein the first VSA and the second VSA are the same.

21. 1. A system for determining a first error vector magnitude (EVM) of a signal output by a device under test (DUT), comprising: A vector signal analyzer (VSA); attenuation circuitry for adding attenuation on a signal path between the DUT and the VSA, the attenuation being variable; and one or more processing devices; Including, The one or more processing devices include: obtaining at least two second EVM measurements from the VSA for different values ​​of attenuation of the signal output by the DUT, the at least two second EVMs being corrupted by noise from the VSA, and each of the at least two second EVMs being based on two or more measurements; determining the first EVM based on a linear relationship based on the first EVM, the at least two second EVMs, and a function based on the attenuation, the first EVM being free of at least a portion of the noise from the VSA; A system configured to perform operations including:

22. 1. A system for reducing phase noise in a first error vector magnitude (EVM) of a signal output by a device under test (DUT), comprising: A vector signal analyzer (VSA); one or more processing devices; Including, The one or more processing devices include: Estimating the EVM contribution from phase noise of the VSA; and controlling the first VSA to remove the EVM contribution from phase noise from the first EVM; A system configured to perform operations including:

23. estimating the phase noise obtaining a first EVM contribution from phase noise based on measurements obtained from a first VSA having a common local oscillator with a vector signal generator (VSG); obtaining a second EVM contribution from phase noise based on measurements obtained from a second VSA having a local oscillator independent or different from that of the VSG, the second VSA having performance and signal levels comparable to that of the first VSA; estimating the EVM contribution from phase noise based on a difference between the first EVM contribution and the second EVM contribution; 23. The system of claim 22, comprising:

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