CN117061018A - Transmitter equalizer tap extraction - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/10—Monitoring; Testing of transmitters
- H04B17/101—Monitoring; Testing of transmitters for measurement of specific parameters of the transmitter or components thereof
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
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Abstract
A test and measurement instrument having: one or more input ports for connecting an instrument to a Device Under Test (DUT); one or more processors configured to execute code to cause the one or more processors to: receiving equalized waveforms and non-equalized waveforms from the DUT through the input port without knowing the digital patterns corresponding to those waveforms and without extracting digital patterns from those waveforms; aligning the unbalanced waveform and the equalized waveform in time to produce an aligned unbalanced waveform and an aligned equalized waveform; and using the aligned equalized waveform and the aligned non-equalized waveform to determine equalizer tap values.
Description
Cross Reference to Related Applications
The present disclosure claims the benefit of U.S. provisional application No. 63/341,989 entitled "TRANSMITTER EQUALIZER TAP EXTRACTION," filed on 5/13 of 2022, the disclosure of which is incorporated herein by reference in its entirety.
Technical Field
The present disclosure relates to testing and measurement systems, and more particularly to techniques for extracting transmitter equalizer tap values in digital communication systems.
Background
In digital communication systems, as signal speeds increase, equalizers in transmitters (Tx) and receivers (Rx) are widely used to improve system performance. For example, as shown in table 1, for each generation of Peripheral Component Interconnect Express (PCIE) systems, as the transmission speed increases from 32GT/s to 64GT/s, the number of Tx feedforward equalizer (FFE) taps increases from 3 for Gen 5 (generation 5) to 4 for Gen6 (generation 6). Furthermore, the signal modulation scheme was changed from NRZ (non return to zero) in each generation before Gen6 to PAM4 (pulse amplitude modulation 4-level) in Gen 6.
Table 1.Pcie Tx FFE
| Emission speed | Number of Tx FFE taps | Signal modulation | |
| Gen5 | 32GT/s | 3 | NRZ |
| Gen6 | 64GT/s(32GBaud) | 4 | PAM4 |
The PCIE Gen6 Tx FFE structure is shown in FIG. 1 with a main pointer tap c 0 A post pointer tap c +1 And two pairs ofFront pointer tap c -1 、c -2 。
Fig. 2 shows the effect of Tx FFE on the mode waveform. The FFE taps determine four values: deemphasis, pre-shot 1, pre-shot 2, enhancement. If the pulse height V can be measured a 、V b 、V c1 、V c2 、V d These four values can be calculated. The four Tx FFE taps may be derived from four calculated values of de-emphasis, pre-shot 1, pre-shot 2, enhancement. The four equations shown in fig. 2 provide sufficient conditions to solve for the Tx FFE taps.
However, the high frequency nature of PCIE Gen6 signaling makes accurate measurement of single Unit Interval (UI) pulse heights impractical. As the signal reaches higher speeds, the impairments (such as intersymbol interference) caused by higher insertion loss at higher frequencies may increase so much that a single UI pulse cannot stabilize within a single UI and, therefore, pulse heights without the effects of impairments cannot be measured.
To avoid the limitation of pulse height measurement, the method shown in fig. 3 may be used. An oscilloscope or other test and measurement equipment captures a mode waveform from a transmitter Device Under Test (DUT) with and without the transmitter equalizer on, and post-processing software operating in one or more processors extracts a step response waveform with and without the transmitter equalizer on. The transmitter may be configured to have the transmitter equalizer on or off. The transmitter equalizer taps may be obtained by a best fit that minimizes the Mean Square Error (MSE) between the measured and reconstructed equalized step response waveforms. The reconstructed equalized step response waveform is the step response waveform that the transmitter equalizer applies to with the transmitter equalizer turned off. Other variations of this method also use a mean square error method, but instead of using an extracted step response, an extracted impulse response may be used. In either case, the system has pattern information, or the system may extract pattern information from the waveform.
Drawings
Fig. 1 shows a diagram of PCIE Gen6 transmitter FFE structure.
Fig. 2 shows a diagram of the effect of transmitter FFE on waveforms.
Fig. 3 shows a diagram of transmitter FFE measurements.
Fig. 4 shows a diagram of a linear system with a digital mode input and a mode waveform as output.
Fig. 5 shows a diagram of FFE extraction in the case of pattern detection.
Fig. 6 shows a diagram of a transmitter equalizer applied to an unbalanced waveform.
Fig. 7 illustrates an embodiment of spectral domain equalizer tap extraction without mode knowledge.
Fig. 8 shows a graph of the cross-correlation function between two waveforms.
Fig. 9 shows a waveform chart of the alignment.
Fig. 10 shows a graph of expected ratio of waveforms and constructed spectral ratio.
Fig. 11 illustrates a diagram of transmitter FFE taps extracted using one embodiment.
Fig. 12 shows transmitter FFE taps extracted using another embodiment.
Fig. 13 shows a diagram of transmitter FFE taps extracted using another embodiment.
Fig. 14 shows an embodiment of a test and measurement instrument.
Detailed Description
Embodiments herein relate to extracting equalizer taps from input waveform data. These embodiments achieve this without knowing the digital pattern represented by the waveform and without using pattern detection. This alleviates any problems that may occur if an attempt is made to detect a pattern that suffers significant impairment.
The method described above relies on knowledge of the digital pattern corresponding to the pattern waveform. The digital pattern may be a sequence of bits 0,1 for NRZ signals and a sequence of symbols 0,1,2,3 for PAM4 signals. As shown in fig. 4, if the digital pattern is known, a step response or impulse response may be extracted from the pattern waveform. The middle box in fig. 4 represents a linear system, which may equivalently be represented by an impulse response, a step response, or an impulse response.
If the digital pattern is unknown, the process needs to detect the pattern from the pattern waveform. Fig. 5 shows an example of this workflow. However, when the measured mode waveform has significant impairments, correct detection of the digital mode may not be feasible. Errors in digital pattern detection affect the accuracy of step response or impulse response extraction based on the detected digital pattern, resulting in lower accuracy of transmitter equalizer tap values when FFE taps are extracted based on the step response or impulse response.
Embodiments herein provide a method by which equalizer taps may be extracted from a waveform without mode detection. When accurate detection of digital patterns from waveforms is not feasible, the described method may extract taps without involving pattern detection, such as that shown in fig. 5.
As shown in fig. 6, two waveforms acquired by a real-time oscilloscope or equivalent time sampling oscilloscope are correlated with each other by a transmitter equalizer.
Embodiments herein may derive a frequency domain transfer function of a transmitter equalizer as a ratio between an equalized waveform spectrum and a non-equalized waveform spectrum. As shown in fig. 7, tx FFE taps are extracted without knowing the digital pattern. Fig. 7 shows a method of determining FFE taps without knowledge of the digital pattern and without extracting it as in the previous method. This embodiment uses a short Fast Fourier Transform (FFT) to analyze the spectrum of the two signals to extract FFE taps.
An oscilloscope or other test and measurement instrument acquires the unbalanced waveform and the equalized waveform. As an example, the test and measurement instrument may comprise a real-time oscilloscope or an equivalent sampling oscilloscope. The instrument then resamples the waveform synchronized to the unit interval. For example, resampling may have 32 or more samples per unit interval. This process may use one or two of software and hardware clock recovery.
The process then runs a cross-correlation to align the two waveforms. Fig. 8 shows the cross-correlation function. The peak position identified by the circled points indicates the horizontal offset between the two waveforms. Fig. 9 shows a portion of the alignment waveform shown in fig. 9. In this example, the waveforms represent a pair of 53.125GBaud PAM4 optical signals. 53.125GBaud rate is the symbol rate of the signal.
The process selects a window size, for example 40 UIs. The process traverses the mode waveform, takes the mean value for each step, and then applies a window function (e.g., tukey window). The process then runs a short FFT to take the waveform spectrum of both waveforms.
With the waveform spectrum, the ratio of the equalized waveform spectrum and the unbalanced waveform spectrum can be calculated. The process traverses the pattern waveform to calculate the spectral ratio of each step, and then takes an average of the spectral ratios for all steps. Fig. 10 shows the average spectrum ratio from the equivalent frequency of the DC frequency to the frequency of the symbol rate 53.125 GHz.
The process then extrapolates the number of initial low frequency points of the average spectral ratio to obtain a corrected DC value, as shown by the points at DC in fig. 10. Low frequency as used herein means the lower frequency on the left side of the graph. For transmitters with other controls that may produce DC gains that deviate significantly from FFE DC gain, the actual DC gain from the ratio of the two waveform spectrums may be considered separately.
As shown in FIG. 10, the correction value at DC is used by going from DC to f Nyquist Is mirrored as complex conjugate, the process can be derived from f Nyquist To f Symbol rate The spectral ratio is reconstructed. From DC to f Symbol rate The frequency response of the transmitter equalizer is fully described. One embodiment may repeat the frequency response point from DC to symbol rate over multiple symbol rates. For example, 16 times the symbol rate to get the frequency response of the transmitter equalizer with 32 samples per UI setting.
Second, for NRZ, PAM4 and other high speed signals in a digital communication system, the acquired waveforms range from DC to f Nyquist The ratio is higher than f Nyquist Has a higher signal-to-noise ratio at frequencies. Reconstruction of spectral ratios may be usedData points with higher signal-to-noise ratios generate a complete frequency response based on the observed symmetry. As shown in fig. 10, above f Nyquist Lower signal-to-noise ratio at frequencies above f Nyquist A less accurate representation of the transmitter equalizer frequency response to the symbol rate frequency.
To obtain the time domain impulse response, the process runs an IFFT (inverse FFT) on the modified spectral ratio to obtain the time domain impulse response. This allows the FFT tap values to be extracted. Fig. 11 shows the values of 5 tap FFE. Based on some observations, correction of DC values and reconstruction of spectral ratios contribute to the accuracy of the method. First, the transmitter equalizer FFE is a discrete UI-interval FIR filter, so it has a symmetrical frequency response, along f Nyquist Mirror up to the symbol rate and then repeat.
Previous conventional methods require knowledge of the digital pattern. If the digital mode is not available, it requires additional time to detect the mode. Previous methods involved time domain step response or pulse extraction based on the MSE method. In contrast, some embodiments do not detect or extract patterns, possibly because no detection patterns are needed. These embodiments may also use an FFT, resulting in the process running significantly faster than current methods. For example, one example provides a speed improvement of more than a factor of 10.
Returning to fig. 6, the unbalanced waveform and the equalized waveform include inputs and outputs representing a linear system of the transmitter equalizer. The output waveform is the result of convolving the input waveform with FFE taps in the time domain. FFE tap extraction may be achieved by best fitting that minimizes the MSE of the convolution relationship. The method does not involve the digital mode in the previous method as shown in fig. 5.
Fig. 12 shows one embodiment of this process. This embodiment uses the same acquisition, resampling and cross-correlation processes as in the previous embodiments. Using the aligned waveforms, the process constructs a matrix to represent the convolution discussed above. The process finds an offset that minimizes the Mean Square Error (MSE). As discussed above, this process differs from the previous linear fitting process in that the previous linear fitting process uses a numerical pattern. These embodiments do not use digital modes, which use unbalanced waveforms and balanced waveforms. The process then determines a tap value corresponding to minimizing the offset of the MSE.
The matrix equation looks like ax=b, where a and b are constructed from a pair of waveforms. x represents the FFE tap. The minimized "mean square error" solution of the matrix equation is x= (a 'x A) \ (a' x b).
For the same waveform used to extract the Tx FFE taps, this approach produces taps as shown in fig. 13.
The taps from the MSE best fit method shown in fig. 13 match the taps from the short FFT-based method shown in fig. 11. The following table shows that the tap values from both methods (labeled "FFT" and "MSE", respectively) match the tap values obtained based on the linear fit pulse (labeled "LFP"). The linear fitting pulse method depends on a detectable or known digital pattern.
TABLE 1 extracted FFE tap
Embodiments describe two embodiments of a method of extracting Tx FFE taps without involving a digital pattern, whether known or capable of being extracted. One method is based on a short FFT and the other method is based on a best fit that minimizes MSE. When the digital mode is unknown and mode detection is not feasible due to significant impairments in the signal, as compared to fig. 5, embodiments can take accurate values of the Tx FFE taps as shown in fig. 7 and 12, as they operate directly on both waveforms without involving the digital mode.
As previously discussed, an oscilloscope or other test and measurement equipment captures mode waveforms from a transmitter Device Under Test (DUT), with and without a transmitter equalizer. Fig. 14 shows a test and measurement instrument such as oscilloscope 10 that receives a signal at an input port such as 14 from a transmitter that is part of Device Under Test (DUT) 12. The input ports 14 may include one or more input ports. The differential signal has two signal branches representing a pair of signals: a positive branch signal and a negative branch signal. For most high-speed serial data links, the signals are differential. The embodiments herein for Tx FFE apply to both single ended and differential signals. For differential signals, two signals are acquired and then differential operation is performed, where signal_diff=signal_active-signal_negative. One or more processors (such as 16) in the instrument operate on the unbalanced waveform and the equalized waveform without knowing the digital pattern represented by the waveform, without the need to extract FFE taps from the waveform extraction pattern and from the DUT.
It should be noted that the equalizer tap extraction herein focuses on FFE taps based on the IEEE and PCIE standards, but the apparatus and methods disclosed herein may be applicable to other standards, other signaling, and other equalizers.
Aspects of the disclosure may operate on specially created hardware, firmware, digital signal processors, or specially programmed general-purpose computers (which include processors operating according to programmed instructions). The term controller or processor as used herein is intended to include microprocessors, microcomputers, application Specific Integrated Circuits (ASICs), and special purpose hardware controllers. One or more aspects of the present disclosure can be embodied in computer-usable data and computer-executable instructions, such as in one or more program modules that are executed by one or more computers (including monitoring modules) or other devices. Program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types when executed by a processor in a computer or other device. The computer-executable instructions may be stored on a non-transitory computer-readable medium such as a hard disk, optical disk, removable storage medium, solid state memory, random Access Memory (RAM), etc. As will be appreciated by those skilled in the art, the functionality of the program modules may be combined or distributed as desired in various aspects. Furthermore, the functionality may be embodied in whole or in part in firmware or hardware equivalents such as integrated circuits, FPGAs, and the like. Data structures may be used to more effectively implement one or more aspects of the present disclosure, and such data structures are contemplated to be within the scope of the computer-executable instructions and computer-usable data described herein.
In some cases, the disclosed aspects may be implemented in hardware, firmware, software, or any combination thereof. The disclosed aspects may also be implemented as instructions carried by or stored on one or more non-transitory computer-readable media, which may be read and executed by one or more processors. Such instructions may be referred to as a computer program product. As discussed herein, computer-readable media means any medium that can be accessed by a computing device. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media.
Computer storage media means any medium that can be used to store computer readable information. By way of example, and not limitation, computer storage media may include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital Video Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, and any other volatile or non-volatile, removable or non-removable media implemented in any technology. Computer storage media does not include signals themselves and the transitory forms of signal transmission.
Communication media means any medium that can be used for communication of computer readable information. By way of example, and not limitation, communication media may include coaxial cables, fiber-optic cables, air, or any other medium suitable for communication of electrical, optical, radio Frequency (RF), infrared, acoustic, or other types of signals.
Furthermore, this written description relates to specific features. It should be understood that the disclosure in this specification includes all possible combinations of those particular features. For example, where a particular feature is disclosed in the context of a particular aspect, that feature may also be used in the context of other aspects as much as possible.
Furthermore, when a method having two or more defined steps or operations is referred to in this disclosure, the defined steps or operations may be performed in any order or simultaneously unless the context excludes those possibilities.
The previously described variants of the disclosed subject matter have numerous advantages, which are described or will be apparent to those of ordinary skill. Nevertheless, not all illustrated variations of the disclosed devices, systems, or methods are required.
Example
Illustrative examples of the disclosed technology are provided below. Embodiments of these techniques may include one or more of the examples described below, as well as any combination.
Example 1 is a test and measurement instrument, comprising: one or more input ports for connecting an instrument to a Device Under Test (DUT); one or more processors configured to execute code to cause the one or more processors to: receiving equalized waveforms and non-equalized waveforms from the DUT through the input port without knowing the digital patterns corresponding to those waveforms and without extracting digital patterns from those waveforms; aligning the unbalanced waveform and the equalized waveform in time to produce an aligned unbalanced waveform and an aligned equalized waveform; and using the aligned equalized waveform and the aligned non-equalized waveform to determine equalizer tap values.
Example 2 is the instrument of example 1, wherein the code that aligns the one or more processors with the unbalanced waveform and the equalized waveform causes the one or more processors to: resampling the unbalanced waveform and the equalized waveform in synchronization with the unit interval to generate a resampled unbalanced waveform and a resampled equalized waveform; cross-correlating the resampled unbalanced waveform and the resampled equalized waveform to determine a horizontal offset; and using the horizontal offset to produce an aligned unbalanced waveform and an aligned equalized waveform.
Example 3 is the instrument of example 1 or example 2, wherein the code that causes the one or more processors to determine equalizer tap values using the aligned unbalanced waveform and the aligned equalized waveform further comprises code that causes the one or more processors to: code that converts the aligned unbalanced waveform and the aligned equalized waveform into spectra to produce a unbalanced waveform spectrum and an equalized waveform spectrum; finding the average spectrum ratio of the unbalanced waveform spectrum to the balanced waveform spectrum; correcting the average spectral ratio over a range from the Nyquist frequency to the symbol rate frequency to produce a corrected spectrum; converting the modified frequency spectrum to the time domain using inverse fast fourier transform to produce a time domain impulse response; and extracts equalizer tap values from the time domain impulse response.
Example 4 is the instrument of example 3, wherein the code that causes the one or more processors to convert the aligned unbalanced waveform and the aligned balanced waveform further comprises code that causes the one or more processors to: selecting a number of window sizes at unit intervals; traversing the aligned unbalanced waveform and the aligned balanced waveform, and removing the average value of each step; applying a window function; and performs a short fast fourier transform to obtain the spectrum of the unbalanced waveform and the equalized waveform.
Example 5 is the apparatus of example 3, wherein the code that causes the one or more processors to find the average spectral ratio comprises code that causes the one or more processors to: calculating the spectrum ratio of the balanced waveform spectrum to the unbalanced waveform spectrum; traversing the waveform to calculate a spectral ratio for each step; and find an average value of the spectrum ratios for all steps to produce an average spectrum ratio.
Example 6 is the instrument of example 3, wherein the code that causes the one or more processors to modify the spectral ratio comprises code that causes the one or more processors to: a modified DC value is determined based on the number of initial low frequency points and a spectral ratio from the Nyquist frequency to the symbol rate frequency is reconstructed.
Example 7 is the apparatus of example 6, wherein the one or more processors are further configured to execute code that causes the one or more processors to repeat the frequency response points over a plurality of symbol rates within a frequency range from DC to the symbol rate.
Example 8 is the instrument of example 6, wherein the code that causes the one or more processors to reconstruct the spectral ratio includes code that causes the one or more processors to replace data points of a lower signal-to-noise ratio between the Nyquist frequency and the symbol rate frequency with data points of a higher signal-to-noise ratio between the DC and the Nyquist frequency.
Example 9 is the instrument of example 6, wherein the code to cause the one or more processors to reconstruct the spectral ratio includes code to cause the one or more processors to mirror a ratio between DC and Nyquist frequency to construct a ratio between Nyquist frequency and symbol rate frequency.
Example 10 is the instrument of any of examples 1-9, wherein the code that causes the one or more processors to determine equalizer tap values using the aligned equalization waveform and the aligned non-equalization waveform comprises code that causes the one or more processors to: constructing a matrix equation to represent the convolution of the unbalanced waveform with equalizer tap values that produce an equalized waveform; and the equalizer tap values are calculated by finding a solution to the matrix equation that minimizes the mean square error.
Example 11 is a method of determining equalizer tap values, comprising: receiving equalized and non-equalized waveforms from a Device Under Test (DUT) through one or more input ports without knowledge of digital patterns corresponding to the waveforms and without extracting digital patterns from the waveforms; aligning the unbalanced waveform and the equalized waveform in time to produce an aligned unbalanced waveform and an aligned equalized waveform; and determining equalizer tap values using the aligned equalized waveform and the aligned non-equalized waveform.
Example 12 is the method of example 11, wherein aligning the unbalanced waveform and the equalized waveform comprises: resampling the unbalanced waveform and the equalized waveform in synchronization with the unit interval to generate a resampled unbalanced waveform and a resampled equalized waveform; cross-correlating the resampled unbalanced waveform and the resampled equalized waveform to determine a horizontal offset; and generating an aligned unbalanced waveform and an aligned equalized waveform using the horizontal offset.
Example 13 is the method of example 11 or 12, wherein determining tap values using the aligned unbalanced waveform and the aligned equalized waveform further comprises: converting the aligned unbalanced waveform and the aligned equalized waveform into a spectrum to generate a unbalanced waveform spectrum and an equalized waveform spectrum; finding the average spectrum ratio of the unbalanced waveform spectrum to the balanced waveform spectrum; correcting the average spectral ratio over a range from the Nyquist frequency to the symbol rate frequency to produce a corrected spectrum; converting the modified frequency spectrum to the time domain using inverse fast fourier transform to produce a time domain impulse response; and extracting equalizer tap values from the time domain impulse response.
Example 14 is the method of example 13, wherein converting the aligned unbalanced waveform and the aligned equalized waveform further comprises: selecting a number of window sizes at unit intervals; traversing the aligned waveforms and removing the average value of each step; applying a window function; and performing a short fast fourier transform to obtain the spectrum of the unbalanced waveform and the equalized waveform.
Example 15 is the method of example 13, wherein finding the average spectral ratio comprises: calculating the spectrum ratio of the balanced waveform spectrum to the unbalanced waveform spectrum; traversing the waveform to calculate a spectral ratio for each step; and find the average value of the spectrum ratio for all steps.
Example 16 is the method of example 13, wherein modifying the spectral ratio comprises: a modified DC value is determined based on the number of initial low frequency points and a spectral ratio from the Nyquist frequency to the symbol rate frequency is reconstructed.
Example 17 is the method of example 16, further comprising repeating the frequency response point over a plurality of symbol rates within a frequency range from DC to the symbol rate.
Example 18 is the method of example 16, wherein reconstructing the spectral ratio includes replacing data points of lower signal-to-noise ratio between the Nyquist frequency and the symbol rate frequency with data points of higher signal-to-noise ratio between the DC and Nyquist frequencies.
Example 19 is the method of example 16, wherein modifying the spectral ratio includes mirroring a ratio between DC and a Nyquist frequency to construct a ratio between the Nyquist frequency and a symbol rate frequency.
Example 20 is the method of any of examples 11-19, wherein determining equalizer tap values using the aligned equalized waveform and the aligned non-equalized waveform comprises: constructing a matrix of values to represent a convolution of the unbalanced waveform with equalizer tap values that produce an equalized waveform; and calculating equalizer tap values by finding a solution to the matrix equation that minimizes the mean square error.
Although specific examples of the application have been illustrated and described herein for purposes of description, it will be appreciated that various modifications may be made without deviating from the spirit and scope of the application. Accordingly, the application should not be limited except as by the appended claims.
Claims (20)
1. A test and measurement instrument comprising:
one or more input ports for connecting an instrument to a Device Under Test (DUT);
one or more processors configured to execute code to cause the one or more processors to:
the equalized and unbalanced waveforms are received from the DUT through the input ports, without knowing the digital patterns corresponding to those waveforms, and without extracting the digital patterns from those waveforms,
aligning the unbalanced waveform and the equalized waveform in time to produce an aligned unbalanced waveform and an aligned equalized waveform, an
The equalizer tap values are determined using the aligned equalized waveform and the aligned non-equalized waveform.
2. The apparatus of claim 1, wherein code that causes the one or more processors to align unbalanced waveforms and balanced waveforms causes the one or more processors to:
resampling the unbalanced waveform and the equalized waveform in synchronization with the unit interval to generate a resampled unbalanced waveform and a resampled equalized waveform;
cross-correlating the resampled unbalanced waveform and the resampled equalized waveform to determine a horizontal offset; and
the horizontal offset is used to generate an aligned unbalanced waveform and an aligned equalized waveform.
3. The apparatus of claim 1, wherein the code that causes the one or more processors to determine equalizer tap values using the aligned unbalanced waveform and the aligned equalized waveform further comprises code that causes the one or more processors to:
converting the aligned unbalanced waveform and the aligned equalized waveform into a spectrum to generate a unbalanced waveform spectrum and an equalized waveform spectrum;
finding the average spectrum ratio of the unbalanced waveform spectrum to the balanced waveform spectrum;
correcting the average spectral ratio over a range from the Nyquist frequency to the symbol rate frequency to produce a corrected spectrum;
converting the modified frequency spectrum to the time domain using inverse fast fourier transform to produce a time domain impulse response; and
equalizer tap values are extracted from the time domain impulse response.
4. The apparatus of claim 3, wherein the code that causes the one or more processors to convert the aligned unbalanced waveform and the aligned balanced waveform further comprises code that causes the one or more processors to:
selecting a number of window sizes at unit intervals;
traversing the aligned unbalanced waveform and the aligned balanced waveform, and removing the average value of each step;
applying a window function; and
a short fast fourier transform is performed to obtain the spectrum of the unbalanced waveform and the equalized waveform.
5. The apparatus of claim 3, wherein the code that causes the one or more processors to find an average spectral ratio comprises code that causes the one or more processors to:
calculating the spectrum ratio of the balanced waveform spectrum to the unbalanced waveform spectrum;
traversing the waveform to calculate a spectral ratio for each step; and
the average value of the spectrum ratios for all steps is found to produce an average spectrum ratio.
6. The apparatus of claim 3, wherein the code that causes the one or more processors to modify the spectral ratio comprises code that causes the one or more processors to determine a modified DC value based on a number of initial low frequency points and reconstruct the spectral ratio from the Nyquist frequency to the symbol rate frequency.
7. The apparatus of claim 6, wherein the one or more processors are further configured to execute code that causes the one or more processors to repeat frequency response points over a plurality of symbol rates within a frequency range from DC to symbol rate.
8. The apparatus of claim 6, wherein the code that causes the one or more processors to reconstruct the spectral ratio comprises code that causes the one or more processors to replace data points of a lower signal-to-noise ratio between the Nyquist frequency and the symbol rate frequency with data points of a higher signal-to-noise ratio between DC and Nyquist frequency.
9. The apparatus of claim 6, wherein the code that causes the one or more processors to reconstruct the spectral ratio comprises code that causes the one or more processors to mirror a ratio between DC and Nyquist frequency to construct a ratio between Nyquist frequency and symbol rate frequency.
10. The apparatus of claim 1, wherein the code that causes the one or more processors to determine equalizer tap values using the aligned equalized waveforms and the aligned unbalanced waveforms comprises code that causes the one or more processors to:
constructing a matrix equation to represent the convolution of the unbalanced waveform with equalizer tap values that produce an equalized waveform; and
equalizer tap values are calculated by finding a solution to the matrix equation that minimizes the mean square error.
11. A method of determining equalizer tap values, comprising:
receiving equalized and non-equalized waveforms from a Device Under Test (DUT) through one or more input ports without knowledge of digital patterns corresponding to the waveforms and without extracting the digital patterns from the waveforms;
aligning the unbalanced waveform and the equalized waveform in time to produce an aligned unbalanced waveform and an aligned equalized waveform; and
the equalizer tap values are determined using the aligned equalized waveform and the aligned non-equalized waveform.
12. The method of claim 11, wherein aligning the unbalanced waveform and the equalized waveform comprises:
resampling the unbalanced waveform and the equalized waveform in synchronization with the unit interval to generate a resampled unbalanced waveform and a resampled equalized waveform;
cross-correlating the resampled unbalanced waveform and the resampled equalized waveform to determine a horizontal offset; and
the horizontal offset is used to generate an aligned unbalanced waveform and an aligned equalized waveform.
13. The method of claim 11, wherein determining tap values using the aligned unbalanced waveform and the aligned equalized waveform further comprises:
converting the aligned unbalanced waveform and the aligned equalized waveform into a spectrum to generate a unbalanced waveform spectrum and an equalized waveform spectrum;
finding the average spectrum ratio of the unbalanced waveform spectrum to the balanced waveform spectrum;
correcting the average spectral ratio over a range from the Nyquist frequency to the symbol rate frequency to produce a corrected spectrum;
converting the modified frequency spectrum to the time domain using inverse fast fourier transform to produce a time domain impulse response; and
equalizer tap values are extracted from the time domain impulse response.
14. The method of claim 13, wherein converting the aligned unbalanced waveform and the aligned equalized waveform further comprises:
selecting a number of window sizes at unit intervals;
traversing the aligned waveforms and removing the mean value of each step;
applying a window function; and
a short fast fourier transform is performed to obtain the spectrum of the unbalanced waveform and the equalized waveform.
15. The method of claim 13, wherein finding an average spectral ratio comprises:
calculating the spectrum ratio of the balanced waveform spectrum to the unbalanced waveform spectrum;
traversing the waveform to calculate a spectral ratio for each step; and
the average value of the spectrum ratio is found for all steps.
16. The method of claim 13, wherein modifying the spectral ratio comprises determining a modified DC value based on the number of initial low frequency points and reconstructing the spectral ratio from the Nyquist frequency to the symbol rate frequency.
17. The method of claim 16, further comprising repeating the frequency response point over a plurality of symbol rates within a frequency range from DC to symbol rate.
18. The method of claim 16, wherein reconstructing the spectral ratio includes replacing data points of lower signal-to-noise ratio between the Nyquist frequency and the symbol rate frequency with data points of higher signal-to-noise ratio between DC and Nyquist frequency.
19. The method of claim 16, wherein modifying the spectral ratio comprises mirroring a ratio between DC and Nyquist frequency to construct a ratio between Nyquist frequency and symbol rate frequency.
20. The method of claim 11, wherein determining equalizer tap values using the aligned equalized waveform and the aligned non-equalized waveform comprises:
constructing a matrix of values to represent a convolution of the unbalanced waveform with equalizer tap values that produce an equalized waveform; and
equalizer tap values are calculated by finding a solution to the matrix equation that minimizes the mean square error.
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| US63/341989 | 2022-05-13 | ||
| US18/141,438 US20230370242A1 (en) | 2022-05-13 | 2023-04-30 | Transmitter equalizer tap extraction |
| US18/141438 | 2023-04-30 |
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