Receiver device for pulse amplitude modulation signals

Abstract

This disclosure relates to a receiver device for pulse amplitude modulation (PAM) signals. The receiver device calculates a transmit dispersive eye diagram closed quadrature phase (TDECQ). The receiver device first acquires a signal based on a PAM signal transmitted from a transmitter device to the receiver device via a channel, and filters the acquired signal. Furthermore, the transmitter device equalizes the filtered signal using a multi-tap FFE, and filters the equalized signal output from the FFE using a 2-tap post-filter, where high-frequency noise caused by the FFE is compressed. The receiver device applies a maximum logarithmic mapping (MLM) algorithm to the filtered signal output from the 2-tap post-filter, reconstructs the signal constellation of the PAM signal based on the result of the MLM algorithm, and calculates the TDECQ based on the reconstructed signal constellation.

Description

Technical Field

[0001] This disclosure relates to a receiver device and a receiving method for receiving a pulse amplitude modulation (PAM) signal transmitted by a transmitter device through a channel. The receiver device and receiving method of this disclosure are configured to acquire a transmitter dispersion eye closure quaternary (TDECQ). ) TDECQ indicates the quality of the PAM signal transmitted by the transmitter device through the channel. Background Technology

[0002] The latest generation of high-performance optical interconnects used in data communication employs the 4-level PAM format (PAM4). One of the key system-level signal quality metrics is TDECQ. Transmitter eye closure quaternary (TECQ) is also used in channels without chromatic dispersion (CD). ) The difference between these two values ​​provides the CD cost.

[0003] TDECQ utilizes a reference receiver to quantize the cost of impairments that may or may not be equalized. TDECQ is a measure of the vertical eye diagram closure of an optical transmitter transmitting a PAM signal through a worst-case optical channel. TDECQ can be measured using an optical-to-electrical converter (O / E) and an oscilloscope with a combined frequency response, and can be equalized using a reference equalizer. The reference receiver and reference equalizer can be implemented in software or can be part of an oscilloscope or other receiver device. Summary of the Invention

[0004] exist Figure 1 (a) illustrates an exemplary optical interconnect through which a pattern is transmitted from an optical transmitter to a TDECQ tester via a worst-case optical channel.

[0005] The TDECQ tester consists of a reference receiver and the TDECQ algorithm. The reference receiver converts the received optical signal into an electrical signal and filters the electrical signal through a fourth-order Bessel-Thomson (BT4) filter. Then, given the receiver noise shaped by the BT4 filter, the TDECQ algorithm finds the optimal 5-tap feed-forward equalizer (FFE). Figure 1 (a) The addition of noise σG and σeq, as well as the noise enhancement factor C, is also described. eq The reference point is used. The TDECQ algorithm connected to the reference receiver finds the maximum input reference receiver noise σG, which makes the signal enhancement ratio (SER) equal to 4.8 x 10^6. - 4. Target SER (TSER) (KP4 forward error correction (FEC) limit).

[0006] like Figure 1 As shown in (b), the equalizer samples at two sampling points with a distance of 0.1 UI, and the optimal sampling phase (where TDECQ is minimum) is found. With two sampling phases, the TDECQ with the worst value is selected. TEDCQ is calculated using the following formula:

[0007]

[0008] Where R is the root mean square (RMS) noise that can be added to the receiver, and Q... t The value is 3.414, consistent with the bit error rate (BER) and TSER of Gray-coded PAM4. The entire process is performed in blind mode, so that TDECQ is used only for quantizing the transmitter quality, and not for quantizing BER or SER. For example, the calculation of R is described in the IEEE standard for Ethernet (IEEE Std. 802.3, 2018). Optical modulation amplitude (OMA) is the highest amplitude level.

[0009] However, the above process presents challenges. For example, high-speed optical interconnects require very powerful digital signal processing (DSP), including maximum likelihood sequence estimators (MLSE). As another example, next-generation, faster transceivers require more advanced and complex TDECQ computations.

[0010] In view of this, the purpose of this disclosure is to provide an improved TDECQ calculation.

[0011] These and other objectives are achieved through this disclosure, as set forth in the appended independent claims. Advantageous implementation methods are further defined in the dependent claims.

[0012] The first aspect of the disclosure provides a receiver device for PAM signals, the receiver device being configured to: acquire a signal, wherein the signal is based on a PAM signal transmitted to the receiver device by a transmitter device via a channel; filter the acquired signal; equalize the filtered signal using an FFE with multiple taps; filter the equalized signal output from the FFE using a 2-tap post-filter, wherein high-frequency noise caused by the FFE is compressed; apply a Max-Log-Map (MLM) algorithm to the filtered signal output from the 2-tap post-filter; reconstruct the signal constellation of the PAM signal based on the result of applying the MLM algorithm; and calculate TDECQ based on the reconstructed signal constellation of the PAM signal.

[0013] The receiver device according to the first aspect provides improved TDECQ calculation. For example, the receiver device can calculate an accurate TDECQ. Instead of using the output of the FFE to calculate the TDECQ, the receiver device according to the first aspect uses the output of the signal (constellation) reconstruction to calculate the TDECQ.

[0014] In one implementation of the first aspect, the PAM signal transmitted by the transmitter device is an optical signal, wherein the acquired signal is an electrical signal, and wherein the receiver device includes a photodetector for converting the optical signal into an electrical signal.

[0015] For example, the PAM signal can be a PAM4 signal. The optical channel can be an optical fiber.

[0016] In one implementation of the first aspect, the receiver device is configured to filter the acquired signal using a low-pass filter.

[0017] The filter can be an H-BT4 filter or any kind of low-pass filter.

[0018] In one implementation of the first aspect, the FFE is configured to recover the PAM level included in the PAM signal by equalizing the filtered signal.

[0019] This reduces distortion in both the acquired and filtered signals, thereby improving the performance of the receiver equipment.

[0020] In one implementation of the first aspect, the FFE is configured to perform a blind FFE algorithm to equalize the filtered signal.

[0021] Blind FFE algorithms can lead to improved decision-making at the receiver device. For example, FFE can find the tap in blind mode. For example, the decision-directed least-mean-square (DD-LMS) mode can be used in blind mode, but any other blind method can also be used.

[0022] In one implementation of the first aspect, filtering the equalized signal includes: using a 2-tap post-filter to perform linear filtering on the equalized signal based on filter coefficients, wherein the filter coefficients are determined iteratively.

[0023] In one implementation of the first aspect, applying the maximum logarithmic mapping algorithm to the filtered signal output by the 2-tap post-filter results in the logarithmic probability of each PAM level of the PAM signal.

[0024] In one implementation of the first aspect, the receiver device is configured to reconstruct the signal constellation of the PAM signal based on logarithmic probability.

[0025] In one implementation of the first aspect, reconstructing the signal constellation of the PAM signal includes generating a PAM histogram representing the PAM level of the PAM signal.

[0026] In one implementation of the first aspect, the receiver device is configured to calculate TDECQ based on the PAM histogram.

[0027] In one implementation of the first aspect, the receiver device is configured to further calculate TDECQ based on noise, which is added to the reconstructed signal constellation of the PAM signal.

[0028] Adding noise enables the scanning of noise-dependent SERs and the identification of the amount of noise required to achieve the target SER. This noise level can then be used to calculate TDECQ.

[0029] In one implementation of the first aspect, the receiver device is configured to: calculate the TDECQ including the 2-tap post-filter parameter CeqPF, which is equal to sqrt(1+α) 2 ) / (1+α). Introducing CeqPF can improve the accuracy of TDECQ calculation.

[0030] In one implementation of the first aspect, TDECQ indicates the quality of the PAM signal transmitted by the transmitter device.

[0031] In one implementation of the first aspect, the receiver device includes a sampling oscilloscope configured to: perform equalization on the filtered signal, filter the equalized signal, apply an MLM algorithm, reconstruct the signal constellation, and calculate TDECQ.

[0032] A second aspect of the disclosure provides a method for receiving pulse amplitude modulation (PAM) signals, the method comprising: acquiring a signal, wherein the signal is based on a PAM signal transmitted by a transmitter device through a channel; filtering the acquired signal; equalizing the filtered signal using a feedforward equalization with multiple taps; filtering the equalized signal using a 2-tap filter, wherein high-frequency noise caused by the feedforward equalization is compressed; applying an MLM algorithm to the 2-tap filtered signal; reconstructing the signal constellation of the PAM signal based on the result of applying the MLM algorithm; and calculating TDECQ based on the reconstructed signal constellation of the PAM signal.

[0033] In one implementation of the second aspect, the PAM signal transmitted by the transmitter device is an optical signal, wherein the acquired signal is an electrical signal, and wherein the receiving method includes: converting the optical signal into an electrical signal.

[0034] In one implementation of the second aspect, the receiving method includes filtering the acquired signal using a low-pass filter.

[0035] In one implementation of the second aspect, feedforward equalization recovers the PAM level included in the PAM signal by equalizing the filtered signal.

[0036] In one implementation of the second aspect, feedforward equalization includes: performing a blind feedforward equalization algorithm to equalize the filtered signal.

[0037] In one implementation of the second aspect, the 2-tap post-filtering of the equalized signal includes: performing linear filtering on the equalized signal based on filter coefficients, wherein the filter coefficients are determined iteratively.

[0038] In one implementation of the second aspect, the result of applying the MLM algorithm to the filtered signal includes the logarithmic probability of each PAM level of the PAM signal.

[0039] In one implementation of the second aspect, the receiving method device includes: reconstructing the signal constellation of the PAM signal based on logarithmic probability.

[0040] In one implementation of the second aspect, reconstructing the signal constellation of the PAM signal includes generating a PAM histogram representing the PAM level of the PAM signal.

[0041] In one implementation of the second aspect, the receiving method includes: calculating TDECQ based on the PAM histogram.

[0042] In one implementation of the second aspect, the receiving method includes: further calculating TDECQ based on noise, the noise being added to the reconstructed signal constellation of the PAM signal.

[0043] In one implementation of the second aspect, TDECQ indicates the quality of the PAM signal transmitted by the transmitter device.

[0044] In one implementation of the second aspect, the receiving method is performed using a sampling oscilloscope, which performs equalization on the filtered signal, filtering on the equalized signal, applying the MLM algorithm, reconstructing the signal constellation, and calculating TDECQ.

[0045] The second method and its implementation achieve the same advantages as the receiver device described in the first aspect.

[0046] A third aspect of this disclosure provides a computer program including instructions that, when executed by a computer, cause the computer to perform the method according to the second aspect or any implementation thereof.

[0047] A fourth aspect of this disclosure provides a non-transitory storage medium for storing executable program code, which, when executed by a processor, causes the method described in accordance with any implementation thereof, either the second aspect or an implementation thereof.

[0048] This disclosure differs from other exemplary solutions in at least the following ways: Exemplary solutions typically use a simple DSP consisting of linear FFEs. This equalizer architecture is even preferred in commercial systems. FFEs can have more taps, including nonlinear taps, to improve performance. However, next-generation high-speed transceivers will include MLSEs and may require transmitter quality estimation based on MLSEs because MLSEs can handle strong intersymbol interference (ISI).

[0049] The MLM-based TDECQ of this disclosure includes an FFE and an MLM algorithm for reconstructing the signal constellation of a PAM signal, which will be used for TDECQ calculation. Conversely, an exemplary solution directly calculates TDECQ based on the FFE output. This disclosure can perform transmitter quality estimation for various PAM systems (e.g., PAM4 systems). The PAM signal can be a PAM4 signal.

[0050] The benefits of the solution disclosed herein are: more advanced algorithms can be used to detect transmitted signals, and the requirements for transmitter components can be relaxed (more flexible, which ultimately reduces system costs). The solution disclosed herein also enables the comparison of different transmitters to meet future standards.

[0051] It should be noted that all devices, elements, units, and apparatuses described in this application can be implemented in software or hardware elements or any combination thereof. All steps performed by the various entities described in this application, and the functions described to be performed by the various entities, are intended to indicate that the respective entities are suitable for or configured to perform the corresponding steps and functions. Although the specific functions or steps to be performed by external entities are not reflected in the detailed description of the specific elements of the entities performing the specific steps or functions in the following detailed description of embodiments, those skilled in the art should understand that these methods and functions can be implemented by the corresponding software or hardware elements or any combination thereof. Attached Figure Description

[0052] The following detailed description, in conjunction with the accompanying drawings, elucidates the above aspects and implementation methods, as illustrated in the drawings:

[0053] Figure 1 An exemplary scheme for calculating TDECQ is shown in (a), and an exemplary PAM4 eye diagram for calculating TDECQ is shown in (b).

[0054] Figure 2 (a) shows a receiver device for receiving PAM signals according to the present disclosure, and (b) shows another receiver device implemented in an optical transmission system according to the present disclosure.

[0055] Figure 3 An exemplary receiver device implemented in an optical transmission system according to the present disclosure is shown.

[0056] Figure 4 An example of the recovered PAM level of a PAM signal transmitted from a transmitter device to a receiver device according to this disclosure is shown.

[0057] Figure 5 The results of the receiver device according to this disclosure are shown, in particular the histogram levels of the three contrast symbol groups 01, 12 and 23.

[0058] Figure 6 Results of the receiver device according to this disclosure are shown, in particular histograms of the FFE block and MLM block.

[0059] Figure 7Results of a receiver device according to this disclosure are shown, in particular histograms and other histograms of filtered noise.

[0060] Figure 8 The results of a receiver device according to this disclosure are shown, particularly the noise enhancement after the MLM block.

[0061] Figure 9 Results of a receiver device according to this disclosure are shown, particularly the results of multiplying the noise and the bars of the CF histogram, summing them, and selecting the noise at which the SER equals the target SER.

[0062] Figure 10 Results for a receiver device according to this disclosure are shown, particularly histograms after FFE and MLM for four transmitter cases.

[0063] Figure 11 Results of a receiver device according to this disclosure are shown, in particular the relationship between SER and EbN0 and TDECQ.

[0064] Figure 12 Results of a receiver device according to this disclosure are shown, particularly results of offline data from two different transmitter devices Tx1 and Tx2.

[0065] Figure 13 A method for receiving PAM signals according to this disclosure is shown. Detailed Implementation

[0066] Figure 2 (a) and Figure 2 (b) A receiver device 200 according to this disclosure is shown. Figure 2 (b) The receiver device 200 shown is Figure 2 (a) is a further improvement of the receiver device 200 shown, and is illustrated as being implemented in an optical transmission system including transmitter device 209. The receiver device 200 of this disclosure is configured to receive a PAM signal, such as a PAM4 signal. The receiver device 200 of this disclosure can calculate the TDECQ of a received signal (received from channel 208) based on a PAM signal (e.g., a PAM4 signal) transmitted from transmitter device 209 to receiver device 200 via channel 208.

[0067] like Figure 2 As shown in (a), the receiver device 200 of this disclosure is configured to acquire a signal 201, wherein the signal 201 is based on a PAM signal transmitted by the transmitter device 209. The signal 201 may be an electrical signal, while the PAM signal may be an optical signal.

[0068] Receiver device 200 is also configured to filter the acquired signal 201 using filter 202 (e.g., a low-pass filter). Then, receiver device 200 is configured to equalize the filtered signal using an FFE 203 with multiple taps. Receiver device 200 is further configured to filter the equalized signal output from the FFE using a 2-tap post-filter 204. The 2-tap post-filter 204 is configured to compress high-frequency noise caused by the FFE 203.

[0069] Receiver device 200 is also configured to apply MLM algorithm 205 to the filtered (equalized) signal output by 2-tap post-filter 204. Receiver device 200 is then configured to reconstruct the signal constellation of the PAM signal based on the result of applying MLM algorithm 205. Furthermore, receiver device 200 is configured to calculate TDECQ 207 based on the reconstructed signal constellation of the PAM signal obtained using MLM (e.g., in signal reconstruction block 206).

[0070] Figure 2 (b) Receiver device 200 based on Figure 2 (b) The receiver device 200 is configured and can perform the same steps. Figure 2 (a) and Figure 2 The same elements in (b) are labeled with the same reference numerals and can serve a similar purpose. For Figure 2 (b) Receiver device 200, further optional details are shown.

[0071] like Figure 2 As shown in (b), the PAM signal 211 is transmitted by the transmitter device 209, for example, by an optical transmitter. Therefore, the PAM signal 211 in this case is an optical signal. The PAM signal 211 is transmitted through channel 208, which can be considered a worst-case optical channel. After channel 208, the optical signal 213 is received by a PIN-based photodetector 210 of the receiver device 200, which is configured to convert the optical signal 213 (corresponding to the optical PAM signal 211 after channel 208) into an acquired signal 201, which is an electrical signal. The electrical signal can be processed in the receiver device 200.

[0072] The acquired electrical signal 201 can be filtered by the H-BT4 filter of the receiver device 200, and the filtered signal output from the H-BT4 filter can then be equalized by the optimal FFE 203 of the receiver device 200. The equalized signal can then be further filtered by an optimal linear filter (as a post-filter 204), where the filtering is based on the filter coefficient α. The filtered signal can then be input into the MLM algorithm 205 (e.g., an MLM calculation block), and the output of the MLM algorithm 205 is used by the signal reconstruction block 206 to reconstruct the signal constellation of the PAM signal 211. Noise 212 can then be added to the reconstructed signal constellation of the PAM signal 211, and finally, TDECQ 207 is calculated based on the reconstructed signal constellation of the PAM signal 211 with added noise 212.

[0073] Receiver device 200 may include a processor or processing circuitry (not shown) configured to perform, conduct, or initiate various operations of receiver device 200 as described herein. The processing circuitry may include hardware and / or may be software-controlled. Hardware may include analog or digital circuitry, or both. Digital circuitry may include components such as application-specific integrated circuits (ASICs), field-programmable arrays (FPGAs), digital signal processors (DSPs), or multi-purpose processors. Receiver device 200 may also include a memory circuitry storing one or more instructions that can be executed by a processor or the processing circuitry (specifically, under software control). For example, the memory circuitry may include a non-transitory storage medium storing executable software code that, when executed by a processor or the processing circuitry, causes receiver device 200 to perform various operations. In one embodiment, the processing circuitry includes one or more processors and non-transitory memory connected to the one or more processors. Non-transitory memory can carry executable program code that, when executed by one or more processors, causes receiver device 200 to perform, conduct, or initiate the operations or methods described herein.

[0074] Figure 3 A receiver device 200 according to this disclosure is shown, which is built on Figure 2 (a) and Figure 2 (b) On receiver device 200, as shown separately. Identical elements are labeled with the same reference numerals and may serve similar or identical purposes.

[0075] Overall, Figure 3 A novel MLM-based TDECQ acquisition process is proposed. It is worth noting that... Figure 3 The receiver device 200 shown can also be based on Figure 1 The system shown in (a) includes receiver device 200 performing at least the following calculations: a 2-tap post-filter 204, an MLM algorithm 205 (a simplified BCJR algorithm), a signal reconstruction block 206, and a TDECQ calculation 207 based on the output of signal reconstruction block 206. Figure 1 Extend the receiver in (a).

[0076] It is worth noting that receiver device 200 can be used with any PAM modulation format, but this disclosure focuses specifically on PAM4 because PAM4 is likely to be the modulation format used in next-generation high-speed optical transceivers. TDECQ 207 is used to quantify the quality of PAM4 transmitter device 209, but it can also be referred to as a transmitter quality parameter that includes any transmission scenario and any modulation format. The value of TDECQ 207 can indicate the transmitter quality. Therefore, the transmitter quality can be quantified by TDECQ 207, and it can be checked whether the value is below the maximum permissible value (e.g., TDECQmax) defined by the standard.

[0077] Optical signal 213 (e.g., received from an optical fiber as channel 208) is received by photodetector 210 (e.g., implemented by a photodiode) of receiver device 200. Signal x1 acquired after photodetector 210 (corresponding to...) Figure 2 (a) and Figure 2 (b) The acquired signal 201 shown is an electrical signal x1, which is captured (e.g., sampled and stored) by an instrument 300 such as a sampling oscilloscope.

[0078] The captured signal x1 (e.g., millions of samples) can be processed by a software program running in receiver device 200. The signal x1 (e.g., its stored samples) in... Figure 3 The receiver device 200 is low-pass filtered (by H-BT4 filter 202) to remove out-of-band noise because the oscilloscope can have a large bandwidth and sampling rate.

[0079] Signal x2, following H-BT4 filter 202, is equalized by FFE 203, which can have N taps. Signal x2 may be distorted, especially in the histogram based on signal x2, where a clear PAM level cannot be seen. However, signal x3, following FFE 203, is clear, as can be seen in the following diagrams: Figure 4The four PAM4 levels are shown. It is worth noting that after FFE 203, the blind FFE algorithm can be used to obtain better decisions.

[0080] Signal x3 following FFE 203 is filtered by a 2-tap linear post-filter 204. The post-filter is defined by its transfer function 1 + αD, where D represents the delay of the symbol period and α is the filter coefficient. The value of the filter coefficient α can be obtained iteratively. After post-filter 204 (also called a noise decorrelation filter), signal x4 is processed by an MLM block (executing MLM algorithm 205) to obtain an improved decision. This MLM block generates log probabilities for each PAM level. The result of MLM algorithm 205 is signal x5. Post-filters can include more taps. For example, a 3-tap post-filter involving three FFE output samples is defined by 1 + αD + βD. 2 Define, where D 2 This indicates a 2-symbol period delay.

[0081] Signal x5 can include four log-probability values, and these values ​​are used to generate a PAM histogram representing the PAM level, for example... Figure 4 The PAM signal 211 shown has a PAM4 level of 400. That is, reconstructing the signal constellation of the PAM signal 211 at signal reconstruction block 206 may include generating a PAM histogram representing the PAM level of the PAM signal 211. Signal x6 includes the reconstructed signal constellation, which, for example, can be used to represent samples of the PAM signal using PAM levels.

[0082] Then, the receiver device 200 of this disclosure can use the output signal x6 of the signal reconstruction block 206 to calculate TDECQ 207. Since signal x6 is similar to signal x3, the calculation of TDECQ can be similar to... Figure 1 (a) shows an exemplary TDECQ calculation. The TDECQ algorithm is used to calculate TDECQ 207. Therefore... Figure 1 The TDECQ algorithm used in (a) may be modified. Furthermore, noise 212 can be defined before the TDECQ calculation block. Signal x7 is signal x6 with noise 212 added. Then, TEDCQ 207 is calculated on signal x7, i.e., based on the reconstructed signal constellation x6 with noise 212 added. The TDECQ value can be output as signal x8.

[0083] The following text describes, as Figure 2 (a) Figure 2 (b) and Figure 3 Further exemplary implementation details of the receiver device 200 shown.

[0084] FFE 203 can use N linear taps to recover the PAM4 level of the received PAM4 signal 213 from ISI channel 208. N can be an odd number, and N=7 is used exemplarily in the remainder of this disclosure. For N=7, the starting FFE tap can be c=0001000, that is, all taps can be set to 0 and the center tap (N-1) / 2+1 can be set to 1. Then, FFE 203 can follow the following steps:

[0085] 1. The signal x2 prior to FFE 203 is normalized to x = g*(x2 - dc), dc = mean(x2) to enable fast FFE acquisition. FFE 203

[0086] Convert the unipolar signal to a bipolar signal to avoid low-frequency component suppression. Select parameter g to enable fast acquisition and low FFE output noise.

[0087] 2. FFE 203 finds the tap c(i) in blind mode, i = 0, 1, ..., N-1. The gradient algorithm quantizes the output signal to levels l = -3, -1, 1, 3 and thresholds t = -2, 0, 2, using decision-directed least-mean square (DD-WHM) algorithms.

[0088] The decision-making process in the LMS (Limited Subtraction Method) mode is used to adjust the taps. However, DD-LMS can be replaced by other blind methods.

[0089] 3. After stabilizing the FFE tap, the PAM4 output level is found through histogram analysis. The new level is l(i), i = 0, 1, 2, 3, and the new threshold is t(i), i = 0, 1, 2.

[0090] 4. FFE 203 operates using the new level. Steps 3 and 4 can be repeated several times until the tap becomes stable.

[0091] 5. After stabilizing the FFE tap, adjust the output signal x3 using the following formula. ：

[0092] x3 = x3 + g*dc*sum(c).

[0093] 6. Analyze the output signal histogram to find the level l and threshold t. Note that, for example, OMA = l3.

[0094] Post-filter 204 converts the FFE output signal x3 into signal x4 using the following formula. ：

[0095] x4(k) = x3(k) + α*x3(k-1).

[0096] The parameter α is calculated using the following formula:

[0097] α=-mean(error(1:end-1).*error(2:end)) / mean(error.^2),

[0098] Where error = qsym - y, and qsym is the quantization symbol with threshold t and level l. The error is calculated using the FFE output, which may be unreliable; at high BER values, the alpha(α) estimate may be inaccurate. Since the FFE302 is used as a high-pass filter, the post-filter 204 compresses the high-frequency FFE noise caused by FFE noise enhancement.

[0099] MLM Algorithm 205 can provide more reliable decisions. MLM Algorithm 205 can be run multiple times to obtain a more accurate α value that will be used in the final MLM run. The MLM output is the PAM4 symbol log probability. The optimal symbol can be selected to calculate the error. The MLM output symbol x5 can include symMLM and error = l(symMLM) - x3.

[0100] Specifically, the MLM algorithm calculates the log probability of symbol time i for each of the four PAM4 symbol candidates lp(i,j), j = 0, 1, 2, 3. For example, the MLM algorithm can use the algorithm described in the following literature: Lucian Andrei... And Rodica Stoian, " The Decision Reliability of MAP,Log-MAP,Max-Log-MAP and SOVA Algorithms ” International Journal of Communications, Vol. 2, No. 1, 2008, where the branch probability is bp(I,k)=(w(i)-m(k)). 2 (Euclidean distance). Signal x4 is:

[0101] x4(k)=x3(k)+α*x3(k-1)=(1+α)*sl(k)+n(k)+α*n(k-1)=x30(k)+nx3(k),

[0102] Where sl is the transmitted symbol level (sl=l(n), n=0,1,2,3), and nx3 is the filtered noise.

[0103] When considering a single grid level and two symbols s(i) and s(i+1), i = 0, 1, 2, 3 and s(i) = i, the log-likelihood ratio llr is equal to llp(i) = lp(i) - lp(i+1). By collecting the events that determine the symbol s(i) or s(i+1), a histogram (positive and negative histograms combined into a single histogram) with the maximum level at position ll(i) = ±[l(i+1) - l(i)]2 can be obtained, with a threshold of 0 and a standard deviation of noise of σ(i) = 2*[l(i+1) - l(i)].

[0104] Typically, the MLM algorithm 205 uses long sequences to obtain lp values, and the histogram will have values ​​slightly different from those predicted through a single grid level. For example, Figure 5 The three contrasting symbol groups 01, 12 and 23 shown will result in a final histogram level (the value with the highest probability) of ±L(i), where I = 0, 1, 2.

[0105] The preceding histogram (llp(i) = lp(i) – lp(i+1)) is obtained by selecting lp, where the sign s(i) or s(i+1) is the best sign. To calculate TDECQ 207, the PAM4 histogram after the MLM block needs to be obtained based on the lp value. The FFE output level is l(i), I = 0, 1, 2, 3. First, the normalization factor nf of the three sets of histograms described above needs to be obtained. The nf value can be calculated by nf(i) = [l(i+1) - l(i)] / 2 / L(i), resulting in a new level of [l(i+1) - l(i)] / 2.

[0106] Now, for the symbol at position i, where the first column value indicates the best symbol, three sets of positions can be selected using the sorting matrix b(i,j):

[0107] • Group 1 - All positions p0, at all positions p0, [b(i,0)=0 and b(i,1)=1] or [b(i,0)=1 and b(i,1)=0]

[0108] • Group 2 - For all positions p1, at all positions p1, [b(i,0)=1 and b(i,1)=2] or [b(i,0)=2 and b(i,1)=1]

[0109] Group 3 - At all positions p2, [b(i,0)=2 and b(i,1)=3] or [b(i,0)=3 and b(i,1)=2]

[0110] In the next step, the llr vector is constructed as follows:

[0111] ·llr(p0)=nf(0)*[lp(p0,0)-lp(p0,1)]+t(0)

[0112] ·llr(p1)=nf(1)*[lp(p1,1)-lp(p1,2)]+t(1)

[0113] ·llr(p2)=nf(2)*[lp(p2,2)-lp(p2,3)]+t(2)

[0114] Signal reconstruction block 296 generates a signal x6 similar to the FFE output signal x3. The level and threshold are the same as those of the FFE output signal x3, but the noise level is slightly different. The FFE histogram and MLM histogram can be displayed in the same... Figure 6 The blocks are represented in the diagram to visualize their effects. The impact of MLM on BER is evident.

[0115] Normalization based on a single grid analysis requires normalization using nfST(i) = 0.5 / [l(i+1)-l(i)], but this disclosure uses nf(i) = [l(i+1)-l(i)] / 2 / L(i). Some offset exists in the MLM histogram because it consists of three sets of llrs. This is irrelevant to TDECQ accuracy, as the offset is near the PAM4 level. Furthermore, the histogram can be normalized to OMA = 3 without altering the final result.

[0116] The post-filter 204 shapes the FFE output noise using [1α] coefficients. The histogram of the filtered noise is shown below. Figure 7 As shown in the figure. The noise after signal reconstruction (i.e., after MLM) can be less than the noise after filtering ( Figure 7 The MLM curve in the image; MLM uses grid search, which further improves noise statistics (to a smaller extent). To achieve more accurate TDECQ calculations, noise can be added to the TDECQ calculator and further normalized by a factor typically less than 1, nwf(i) = (l(i+1)-l(i)) / sqrt(L(i)). After normalization, the MLM noise is very close to the filtered noise ( Figure 7 (MLM norm curve in the image). There are three SER values ​​to be calculated (three thresholds). Therefore, for each SER calculation, different noise is used, i.e., additive noise is corrected by Ceq and nwf(i).

[0117] It can be noted that there are some biases in the histograms at high histogram values ​​(bars close to 0; smaller noise areas). These biases are unrelated to the TEDCQ calculation, as the contribution of “strong” bars to the SER is negligible.

[0118] The TDECQ calculation follows the calculations described in the IEEE Ethernet standard IEEE Std. 802.3, 2018. The difference is that the CeqMLSE parameters are calculated using FFE, Ceq(CeqFFE), and nwf. The resulting CeqMLSE is CeqMLSE(i) = CeqFFE * nwf(i), where i = 0, 1, or 2.

[0119] In one implementation, the obtained CeqMLSE is CeqMLSE(i) = CeqFFE·CeqPF·nwf(i), i = 0, 1, 2. The 2-tap post-filter parameter CeqPF is equal to sqrt(1 + α). 2 ) / (1+α). For example, from Figure 8 As can be seen, the noise enhancement obtained after the MLM block is very small.

[0120] The three cumulative functions (CFs) are obtained using the method described in the IEEE Ethernet standard IEEE Std. 802.3, 2018. The noise and the CF histogram bars are multiplied, summed, and the noise with a SER equal to the target SER is selected, such as... Figure 9 As shown in the image.

[0121] Select SER_target and apply sigma( σ Search to find the sigma value given SER = SERtarget:

[0122]

[0123] Or in one implementation

[0124]

[0125] The MLM histogram consists of 2K bars of width Δx. The value σt, corresponding to the SER_target value, is used to calculate TDECQ using the following formula. ：

[0126]

[0127] Where qfuncinv represents the inverse Q function.

[0128] Four transmitter scenarios with narrow system bandwidth (α ~ 0.35; EbN0 = 17 dB, ER = 10 dB) were simulated. The target SER was set to 4e-3. Histograms after FFE and MLM are shown in... Figure 10In the middle. MLM improves performance (the histogram is better after MLM). The MLM signal reconstruction block provides a histogram as shown below, which shows somewhat irregular behavior near the signal level. However, this is irrelevant to TDECQ accuracy because the offset is located near the PAM4 level (contributing very little to SER).

[0129] Figure 11 The first subgraph in the diagram shows the relationship between SER and EbN0, while Figure 11 The second sub-figure illustrates TDECQ 207. MLM-based TDECQ clearly distinguishes between better and worse channels. As expected, better channels have smaller TDECQ values. This demonstrates that the new TDECQ 207 can be used for blind estimation of the quality of transmitter device 209.

[0130] Processing offline data Tx1 and Tx2 from two different transmitter devices 209, such as Figure 12 As shown in the diagram. Both data exhibit pattern-dependent behavior, but Tx2 performs better. The TDECQ values ​​(below the marker) are shown. TDECQ clearly distinguishes the two transmitter devices without knowing the SER. In the same... Figure 12 In the simulation, the TEDCQ value of the transmitter in case 4 is added (TDECQ at SER = 3e-4; the Pin value does not correspond to the EbN0 value; this is only for visualization). This transmitter device is not affected by pattern dependence, and even at SER = 2e-4, it has a better (lower) TDECQ value at a higher SER (3e-4) compared to Tx2. This means that Tx2 will suffer greater losses than the transmitter in case 4 in the presence of noise.

[0131] It is worth noting that the receiver device 200 and scheme of this disclosure can be used in measurement equipment to characterize the quality of an optical transmitter. This disclosure can support standardization and optical transmitter selection.

[0132] Figure 13 A method 1300 for receiving PAM signals according to this disclosure is shown. Method 1300 can be performed by receiver device 200 and can be used to receive PAM4 signals.

[0133] Method 1300 includes step 1301 ： Acquire signal 201, x1; wherein signal 201, x1 is based on PAM signal 211 transmitted by transmitter device 209 through channel 208. Method 1300 further includes step 1302. ： The acquired signals 201 and x1 are filtered; method 1300 also includes step 1303. ：The filtered signal x2 is equalized using a feedforward equalizer (FFE 203) with multiple taps. Method 1300 also includes step 1304. ： The equalized signal x3 is filtered using a 2-tap filter (2-tap filter 204), wherein high-frequency noise caused by feedforward equalization is compressed. Then, method 1300 includes step 1305. ： The MLM algorithm 205 is applied to the 2-tap filtered signal x4; then method 1300 includes step 1306. ： The signal constellation x6 of the PAM signal 211 is reconstructed based on the result x5 of the MLM algorithm 205. Finally, method 1300 includes step 1308. ： 1307TDECQ 207 is calculated based on the reconstructed signal constellation x6 of PAM signal 211.

[0134] This disclosure has been described in conjunction with various embodiments as examples and implementations. However, based on a study of the drawings, this disclosure, and the independent claims, those skilled in the art will be able to understand and implement other variations in implementing the claimed subject matter. In the claims and the description, the word "comprising" does not exclude other elements or steps, and the indefinite articles "a" or "an" do not exclude a plurality. A single element or other unit may fulfill the function of several entities or items described in the claims. The fact that certain measures are enumerated in mutually different dependent claims does not mean that a combination of these measures cannot be used in an advantageous implementation.

Claims

1. A receiver device (200) for pulse amplitude modulation (PAM) signals, said receiver device (200) being configured to: Acquire signal (x1), where, The signal (x1) is based on a PAM signal (211) transmitted by the transmitter device (209) to the receiver device (200) via the channel (208); The acquired signal (x1) is filtered; The filtered signal (x2) is equalized using a feedforward equalizer FFE (203) with multiple taps; The equalized signal (x3) output from the FFE (203) is filtered using a 2-tap post-filter (204), wherein the high-frequency noise caused by the FFE (203) is compressed; The maximum logarithmic mapping MLM algorithm (205) is applied to the filtered signal (x4) output by the 2-tap post-filter (204); Based on the results (x5) of the MLM algorithm (205), the signal constellation (x6) of the PAM signal (211) is reconstructed; and Based on the reconstructed signal constellation (x6) of the PAM signal (211), the emission dispersion eye diagram closed quad-phase TDECQ (207) is calculated.

2. The receiver device (200) according to claim 1, wherein, The PAM signal (211) transmitted by the transmitter device (209) is an optical signal, wherein the acquired signal (x1) is an electrical signal, and wherein the receiver device (200) includes a photodetector (210) for converting the optical signal into an electrical signal.

3. The receiver device (200) according to claim 1 is configured to filter the acquired signal (x1) using a low-pass filter (202).

4. The receiver device (200) according to claim 1, wherein, The FFE (203) is configured to recover the PAM level (400) included in the PAM signal (211) by equalizing the filtered signal (x2).

5. The receiver device (200) according to claim 1, wherein, The FFE (203) is configured to execute a blind FFE algorithm to equalize the filtered signal.

6. The receiver device (200) according to claim 1, wherein, Filtering the equalized signal (x3) includes: using the 2-tap post-filter (204) to perform linear filtering on the equalized signal (x3) based on the filtering coefficient α, wherein the filtering coefficient α is determined iteratively.

7. The receiver device (200) according to any one of claims 1 to 6, wherein, The result (x5) of applying the MLM algorithm (205) to the filtered signal (x4) output by the 2-tap post-filter (204) includes the log probability of each PAM level (400) of the PAM signal (211).

8. The receiver device (200) according to claim 7 is configured to reconstruct the signal constellation (x6) of the PAM signal (211) based on the logarithmic probability.

9. The receiver device (200) according to claim 7, wherein, The reconstruction of the signal constellation (x6) of the PAM signal (211) includes generating a PAM histogram representing the PAM level (400) of the PAM signal (211).

10. The receiver device (200) according to claim 9 is configured to calculate the TDECQ (207) based on the PAM histogram.

11. The receiver device (200) according to any one of claims 1 to 6, configured to further calculate the TDECQ based on noise (212). ( 207), the noise (212) is added to the reconstructed signal constellation (x6) of the PAM signal (211).

12. The receiver device (200) according to claim 6, wherein, The TDECQ(207) is calculated to include the 2-tap post-filter parameter CeqPF, which is equal to sqrt(1+α). 2 ) / (1+α).

13. The receiver device (200) according to any one of claims 1 to 6, wherein, The TDECQ (207) indicates the quality of the PAM signal (211) transmitted by the transmitter device (209).

14. The receiver device (200) according to any one of claims 1 to 6, comprising a sampling oscilloscope (300) configured to: perform equalization on the filtered signal (x2), filter the equalized signal (x3), apply the maximum logarithmic mapping algorithm (205), reconstruct the signal constellation (x6), and calculate the TDECQ (207).

15. A method (1300) for receiving pulse amplitude modulation (PAM) signals, the method (1300) comprising: Acquire (1301) signal (x1), wherein the signal (x1) is based on a PAM signal (211) transmitted by the transmitter device (209) through the channel (208); The acquired signal (x1) is filtered (1302); The filtered signal (x2) is equalized (1303) using a feedforward equalizer (203) with multiple taps; The equalized signal (x3) is filtered (1304) using a 2-tap post-filter (204), wherein the high-frequency noise caused by the feedforward equalizer (203) is compressed; The MLM algorithm (205) is applied (1305) to the signal (x4) filtered by the 2-tap post-filter (204); Based on the results (x5) of the MLM algorithm (205) applied, the signal constellation (x6) of the PAM signal (211) is reconstructed (1306); and The TDECQ (207) is calculated based on the reconstructed signal constellation (x6) of the PAM signal (211).

16. A computer program product comprising instructions that, when executed by a computer, cause the computer to perform the method (1300) according to claim 15.

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