Equalization device of optical transmission system and operating method of equalization device

Abstract

An equalization device according to an embodiment of the present invention includes a forward equalizer that filters an input signal based on a first tap factor and outputs a first signal, a feedback equalizer that outputs a second signal based on a second tap factor and outputs a third signal based on at least a portion of the second tap factor, a tap factor algorithm operator that generates a first tap factor and a second tap factor, an adder that adds the first signal and the second signal to output an equalized fourth signal, a slicer that outputs a fifth signal based on the level of the fourth signal, a first subtractor that subtracts the third signal and the fourth signal to output a sixth signal, a branch metric operator that calculates a branch metric associated with the sixth signal, and a maximum likelihood sequence estimator that selects an optimal symbol sequence based on the sixth signal and the branch metric.

Description

Technology Field

[0001] The present invention relates to an equalization device for an optical transmission system and a method of operating the equalization device, and more specifically, to an equalization device for an optical transmission system and a method of operating the equalization device that removes a signal from an equalized signal using some equalization coefficients of a feedback filter and transmits it to a maximum likelihood sequence estimation to compensate for signal distortion caused by inter-symbol interference. Background Technology

[0002] High-speed optical transmission systems consist of transmitters, optical channels, and receivers. Due to the imperfect characteristics of each component, inter-symbol interference (ISI) occurs in the signals reaching the receiver. Consequently, when demodulating distorted received signals caused by this phenomenon, a process is required to compensate for the distortion and improve system performance; this process is called equalization. Equalization methods include those utilizing filters. Representative examples include feed-forward equalizers, feedback equalizers, and decision feedback equalizers.

[0003] In optical transmission systems, inter-symbol interference occurs due to interference between adjacent data symbols during transmission, and this can be related to the response characteristics of the communication channel. Inter-symbol interference can be classified into precursor inter-symbol interference (precursor ISI) and postcursor inter-symbol interference (postcursor ISI). If the channel response condition is poor in an optical transmission system (for example, when frequency attenuation in the transmission channel intensifies as the data transmission rate increases), the impact of inter-symbol interference increases, and the performance of the optical transmission system deteriorates.

[0004] Therefore, in order to increase the transmission speed while maintaining the performance of the optical transmission system, a method is required to control the effect of inter-symbol interference on the transmitted data signal. The problem to be solved

[0005] The object of the present invention is to provide an equalizer for an optical transmission system and a method of operation for the equalizer, wherein the remaining signal, excluding filter coefficients composed of some filter coefficients of the feedback equalizer from a signal equalized by a forward equalizer and a feedback equalizer, is transmitted to a maximum likelihood sequence estimator. means of solving the problem

[0006] An equalization device according to an embodiment of the present invention includes a forward equalizer that filters an input signal based on a first tap factor and outputs a first signal, a feedback equalizer that outputs a second signal based on a second tap factor and outputs a third signal based on at least a portion of the second tap factor, a tap factor algorithm operator that generates a first tap factor and a second tap factor, an adder that adds the first signal and the second signal to output an equalized fourth signal, a slicer that outputs a fifth signal based on the level of the fourth signal, a first subtractor that subtracts the third signal and the fourth signal to output a sixth signal, a branch metric operator that calculates a branch metric associated with the sixth signal, and a maximum likelihood sequence estimator that selects an optimal symbol sequence based on the sixth signal and the branch metric. Effects of the invention

[0007] According to the present invention, a receiver of an optical transmission system has the effect of compensating for signal distortion caused by inter-symbol interference by utilizing some equalization coefficients of a feedback filter from an equalized signal. Brief explanation of the drawing

[0008] Figure 1 shows an example of an equalization device of a receiver in an optical transmission system. FIG. 2 shows an example of a lighting device according to one embodiment of the present invention. Figure 3 shows an example of operation in the first mode of the lighting device of Figure 2. Figure 4 shows an example of operation in the second mode of the lighting device of Figure 2. FIG. 5 shows a part of a lighting device according to one embodiment of the present invention. Specific details for implementing the invention

[0009] In the following, embodiments of the present invention will be described clearly and in detail so that a person skilled in the art can easily practice the present invention.

[0010] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The advantages and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments described herein and may be embodied in different forms. Rather, the embodiments introduced herein are provided to ensure that the disclosed content is thorough and complete and to ensure that the spirit of the present invention is sufficiently conveyed to those skilled in the art, and the present invention is defined only by the scope of the claims. Throughout the entire specification, the same reference numerals refer to the same components.

[0011] The terms used herein are for the purpose of describing embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used in this specification, 'comprises' and / or 'comprising' do not exclude the presence or addition of one or more other components, operations, and / or elements to the mentioned components, operations, and / or elements. Furthermore, as they are based on preferred embodiments, the reference numerals presented in the order of description are not necessarily limited to that order.

[0012] Furthermore, the embodiments described herein will be explained with reference to cross-sectional and / or plan views, which are exemplary illustrations of the present invention. In the drawings, the thicknesses of films and regions are exaggerated for effective explanation of the technical content. Accordingly, the shapes of the exemplary illustrations may be modified due to manufacturing techniques and / or tolerances, etc. Therefore, the embodiments of the present invention are not limited to the specific shapes depicted but include variations in shape produced according to the manufacturing process.

[0013] FIG. 1 shows an example of an equalizer for a receiver of an optical transmission system. Referring to FIG. 1, the equalizer (100) may include an analog-to-digital converter (ADC) (110), a forward equalizer (120), an adder (130), a decision feedback equalizer (140), and a maximum likelihood sequence estimation (150).

[0014] The analog-to-digital converter (110) can convert an analog signal received from an external optical transmission channel into a digital signal.

[0015] The forward equalizer (120) can receive a digital signal from the analog-to-digital converter (110). The forward equalizer (120) can generate an output signal with desired characteristics by filtering the input signal using the form of a filter. For example, the forward equalizer (120) can remove precursor symbol interference (precursor ISI) of the received digital signal.

[0016] The adder (130) can output an equalized signal by adding the output signal of the forward equalizer (120) and the output signal of the decision feedback equalizer (140).

[0017] The decision feedback equalizer (140) can receive an equalized signal. The decision feedback equalizer (140) can eliminate postcursor inter-symbol interference (postcursor ISI) based on the equalized signal.

[0018] In one embodiment, the decision feedback equalizer (140) may include a slicer (141) and a feedback filter (142). The slicer (141) may be a decision-making slicer, which is a decision circuit. The feedback filter (142) may remove distortion or interference of the received signal. For example, the feedback filter (142) may remove distortion or interference of the signal received from the slicer (141).

[0019] The maximum likelihood sequence estimator (150) can select (or determine) the symbol data sequence with the highest probability among all possible symbol data sequences based on the received signal. The maximum likelihood sequence estimator (150) can output the selected symbol data sequence.

[0020] In FIG. 1, the output signal of the forward equalizer (120) of the equalization device (100) may have a problem of increasing in-band noise in the high frequency region.

[0021] FIG. 2 shows an example of an equalization device according to an embodiment of the present invention. Referring to FIG. 2, the equalization device (200) may include a forward equalizer (210), a feedback equalizer (220), an adder (230), a slicer (240), subtractors (250_1, 250_2), a tap coefficient algorithm calculator (260), a branch metric calculator (270), and a maximum likelihood sequence estimator (280). The equalization device (200) may operate in one of a first mode and a second mode. For example, the first mode may represent a training mode based on training symbol data, and the second mode may represent an equalization mode based on actual data (hereinafter referred to as 'input data').

[0022] The forward equalizer (210) can be implemented in the form of a filter. For example, the forward equalizer (210) can be implemented as a filter in the form of a finite impulse response (FIR).

[0023] The forward equalizer (210) can receive an input signal (S_IN) from an external channel and receive a first tap count (TC1) from a tap count algorithm operator (260). The forward equalizer (210) can generate a signal (S1) by filtering inter-symbol interference of the input signal (S_IN) based on the first tap count (TC1). For example, the forward equalizer (120) can generate a signal (S1) by removing inter-precursor symbol interference of the input signal (S_IN) based on the first tap count (TC1). The forward equalizer (210) can transmit the signal (S1) to an adder (230).

[0024] In one embodiment, the input signal (S_IN) may be one of training symbol data (TDAT) and input data (IDAT). For example, while the equalizer (200) is operating in a first mode, the forward equalizer (210) may receive training symbol data (TDAT) as the input signal (S_IN). While the equalizer (200) is operating in a second mode, the forward equalizer (210) may receive input data (IDAT) as the input signal (S_IN).

[0025] The feedback equalizer (220) can receive a signal through the switch (SW) and receive a second tap count (TC2) from the tap count algorithm operator (260). Based on the second tap count (TC2), the feedback equalizer (220) can generate a signal (S2) by filtering inter-symbol interference of the signal received through the switch (SW). For example, based on the second tap count (TC2), the feedback equalizer (220) can generate a signal (S2) by removing inter-postcursor symbol interference of the signal received from the switch (SW). The feedback equalizer (220) can transmit the signal (S2) to the adder (230).

[0026] In one embodiment, the signal received through the switch (SW) may be either training symbol data (TDAT) or signal (S5). For example, while the equalizer (200) is operating in a first mode, the feedback equalizer (220) may receive training symbol data (TDAT) from the switch (SW). While the equalizer (200) is operating in a second mode, the feedback equalizer (220) may receive signal (S5) from the switch (SW).

[0027] The feedback equalizer (220) can generate a signal (S3) based on some tap coefficients of the feedback equalizer (220). For example, the feedback equalizer (220) can generate a signal (S3) calculated based on at least some of the second tap coefficients (TC2) from a signal received through a switch (SW). The feedback equalizer (220) can transmit the signal (S3) to a subtractor (250_2).

[0028] The adder (230) can receive a signal (S1) from the forward equalizer (210) and a signal (S2) from the feedback equalizer (220). The adder (230) can generate a signal (S4) based on the received signals (S1, S2). The signal (S4) may be an equalized signal. For example, the adder (230) can generate the signal (S4) by performing an addition operation on the received signals (S1, S2). The adder (230) can output the generated signal (S4).

[0029] The slicer (240) can receive a signal (S4) from the adder (230). The slicer (240) can determine a quantized signal level of a symbol according to the level of the signal (S4) and output a signal (S5) having the determined level. In one embodiment, the slicer (240) may be a decision-making slicer, which is a decision circuit.

[0030] In one embodiment, the feedback equalizer (220) and the slicer (240) may form a decision feedback equalizer.

[0031] The subtractor (250_1) can output a signal (S7) by performing a subtraction operation on the signal received through the switch (SW) and the signal (S4) received from the adder (230).

[0032] The tap count algorithm operator (260) can receive a signal (S7) from the subtractor (250_1). The tap count algorithm operator (260) can determine first and second tap counts (TC1, TC2) based on the received signal (S7). The tap count algorithm operator (260) can output the first tap count (TC1) to the forward equalizer (210) and output the second tap count (TC2) to the feedback equalizer (220).

[0033] The subtractor (250_2) can generate a signal (S6) by performing a subtraction operation on the signal (S4) received from the adder (230) and the signal (S3) received from the feedback equalizer (220). The subtractor (250_2) can transmit the generated signal (S7) to the maximum likelihood sequence estimator (280).

[0034] The branch metric calculator (270) can calculate a branch metric (BM). The branch metric (BM) can represent the state transition probability according to the signal (S6) input to the maximum likelihood sequence estimator (280). In one embodiment, the branch metric calculator (270) can calculate the branch metric (BM) using the second tap coefficient (TC2) of the feedback equalizer (220). The branch metric calculator (270) can transmit the branch metric (BM) to the maximum likelihood sequence estimator (280).

[0035] The maximum likelihood sequence estimator (280) may receive a signal (S6) from a subtractor (250_2) and a branch metric (BM) from a branch metric operator (270). Based on the signal (S6) and the branch metric (BM), the maximum likelihood sequence estimator (280) may select (or determine) the data sequence with the highest probability among all possible symbol data sequences. For example, the maximum likelihood sequence estimator (280) may obtain a path metric based on the branch metric (BM). Based on the path metric, the maximum likelihood sequence estimator (280) may select the sequence having the smallest value.

[0036] The maximum likelihood sequence estimator (280) can operate based on the Viterbi algorithm. For example, the maximum likelihood sequence estimator (280) may use the survivor path algorithm, which selects a path with a high probability among the Viterbi algorithms. When using the survivor path algorithm, the complexity of the maximum likelihood sequence estimator (280) can be significantly reduced because it does not store information about other paths.

[0037] In one embodiment, the equalization device (200) may further include an analog-to-digital converter (not shown). The analog-to-digital converter can convert an input signal (S_IN) received from an external channel into a digital signal. The analog-to-digital converter can transmit the digital signal to a forward equalizer (210).

[0038] In FIG. 2, to compensate for linear and non-linear distorted signals, the frequency response of the forward equalizer (210) can be designed as a full-pass response having a theoretically flat frequency response. The forward equalizer (210) can have a filter structure in the form of a transversal. The output signal (S1) for the input signal (S_IN) of the forward equalizer (210) can be represented by the following Equation 1.

[0039]

[0040] Here, z(k) represents the output signal (S1) of the forward equalizer, P represents the number of filter taps of the forward equalizer, and x[ ] represents the input signal (S_IN) of the forward equalizer, can represent the tap factor. It can be updated based on the least mean square (LMS) algorithm or the recursive least square (RLS) algorithm.

[0041] To reduce the effects of in-band noise in the high frequency range, the equalizer (200) may use a decision feedback equalizer in which a filter with a feedback structure (e.g., a feedback equalizer (220)) is added to a forward equalizer (210). By using the feedback equalizer (220), poles of the spectrum can be provided to the frequency response of the equalizer. Accordingly, zeros and poles of the spectrum can be substantially compensated in the frequency response of the channel. Additionally, the decision feedback equalizer is a non-linear equalizer, composed of a forward filter (e.g., a forward equalizer (210)) and a feedback filter (e.g., a feedback equalizer (220)), and can perform the function of removing inter-symbol interference that will occur in future symbols from currently detected symbols.

[0042] Meanwhile, the channel may have non-flat frequency response characteristics. When a forward equalizer (210) is used, the white noise (additive white Gaussian noise; AWGN) may not retain its white noise characteristics during the equalization process. When a decision feedback equalizer is used, the output (S1) of the forward equalizer (210) may have a signal with the noise whitened by adding a feedback equalizer (220). Through this process, the whitened signal, which is the output (S1) of the forward equalizer (210), can be used as the input to the maximum likelihood sequence estimator (280), rather than the equalized signal.

[0043] In the equalization device (200), there may be cases where the number of filter taps of the feedback equalizer (220) and the memory length of the maximum likelihood sequence estimator (280) do not match. For example, if the number of filter taps of the feedback equalizer (220) is longer than the memory length of the maximum likelihood sequence estimator (280), the equalized output signal of the decision feedback equalizer may not be fully used, and a newly calculated signal may be used as the input signal of the maximum likelihood sequence estimator (280) by considering the feedback signal corresponding to the memory length of the maximum likelihood sequence estimator (280). The signal (S6), obtained by excluding a portion of the signal (S3) of the feedback equalizer (220) from the equalized signal (S4) obtained by summing the output signal (S1) of the forward equalizer (210) and the output signal (S2) of the feedback equalizer (220), may be input to the maximum likelihood sequence estimator (280).

[0044] FIG. 3 shows an example of operation of the equalization device of FIG. 2 in the first mode. Referring to FIG. 3, the equalization device (200) can operate in the first mode based on training symbol data (TDAT). During the first mode, the switch (SW) can be connected to the first terminal.

[0045] The forward equalizer (210) receives training symbol data (TDAT) as an input signal (S1) from an external channel and can receive a first initial tap count (TC1_I) from a tap count algorithm operator (260). At this time, the first initial tap count (TC1_I) may be related to the training symbol data (TDAT). That is, the first initial tap count (TC1_I) may be a value determined in advance based on the training symbol data (TDAT). Based on the first initial tap count (TC1_I) and the training symbol data (TDAT), the forward equalizer (210) can output a signal (S1) in which interference between precursor symbols of the channel impulse response is removed.

[0046] The feedback equalizer (220) receives training symbol data (TDAT) through a switch (SW) and can receive a second initial tap count (TC2_I) from a tap count algorithm operator (260). At this time, the second initial tap count (TC2_I) may be related to the training symbol data (TDAT). That is, the second initial tap count (TC2_I) may be a value determined in advance based on the training symbol data (TDAT). Based on the second initial tap count (TC2_I) and the training symbol data (TDAT), the feedback equalizer (220) can output a signal (S2) with interference between post-cursor symbols removed.

[0047] The adder (230) can perform an addition operation on the received signals (S1, S2) and output an equalized signal (S4).

[0048] The subtractor (250_1) can receive a signal (S3) and training symbol data (TDAT). The subtractor (250_1) can output a signal (S7) representing the difference between the signal (S4) and the training symbol data (TDAT) to the tap count algorithm operator (260). The tap count algorithm operator (260) can generate first and second optimized tap counts (TC1_O, TC2_O) from the signal (S7) based on an optimization algorithm (e.g., LMS algorithm or RLS algorithm). The tap count algorithm operator (260) can store the first and second optimized tap counts (TC1_O, TC2_O).

[0049] FIG. 4 shows an example of operation of the lighting device of FIG. 2 in the second mode. Referring to FIG. 4, the lighting device (200) can operate in the second mode based on input data (IDAT) after the first mode. During the second mode, the switch (SW) can be connected to the second terminal.

[0050] The tap count algorithm operator (260) can transmit the first optimized tap count (TC1_O) to the forward equalizer (210) and transmit the second optimized tap count (TC2_O) to the feedback equalizer (220).

[0051] The forward equalizer (210) outputs a signal (S1) related to the input data (IDAT) based on the first optimized tap factor (TC1_O), and the feedback equalizer (220) can output a signal (S2) related to the input data (IDAT) based on the second optimized tap factor (TC2_O).

[0052] The adder (230) can output an equalized signal (S4) by performing an addition operation on the signal (S1) output from the forward equalizer (210) and the signal (S2) output from the feedback equalizer (220).

[0053] The slicer (240) can determine the quantized signal level of a symbol (e.g., '-3', '-1', '+1', '+3' in the case of a PAM-4 signal) according to the level of the signal (S4) output from the adder (230), and output a signal (S5) having the determined level.

[0054] The feedback equalizer (220) can receive a signal (S5) through a switch (SW).

[0055] The subtractor (250_1) can output a signal (S7) by performing a subtraction operation on the signal (S4) received from the adder (230) and the signal (S5) received through the switch (SW). The signal (S7) can correspond to an error value.

[0056] The tap count algorithm operator (260) can generate first and second tap counts (TC1, TC2) from a signal (S7) received from a subtractor (250_1) based on an optimization algorithm (e.g., LMS algorithm or RLS algorithm). The tap count algorithm operator (260) can transmit the first and second tap counts (TC1, TC2) to a forward equalizer (210) and a feedback equalizer (220), respectively.

[0057] Meanwhile, the error value can be expressed by the following mathematical formula 2.

[0058]

[0059] Here, e(k) represents the error value, d[ ] represents the signal (S4) which is the decision output, and Q represents the number of filter taps of the feedback equalizer (220) (or decision feedback equalizer), and represents the tap coefficient of the forward equalizer (210), and can represent the tap coefficient of the feedback equalizer (220) (or decision feedback equalizer). and Is The LMS algorithm can be used to minimize the value. In one embodiment, can be the expected value of the square of the mean square error e(k).

[0060] The forward equalizer (210) can output a signal (S1) based on input data (IDAT) and a first tap count (TC1) received from the tap count algorithm operator (260). The feedback equalizer (220) can output a signal (S2) based on a signal (S5) output from the slicer (240) and a second tap count (TC2) received from the tap count algorithm operator (260). The adder (230) can output an equalized signal (S4) based on the signals (S1, S2).

[0061] The subtractor (250_2) can output a signal (S6) by performing a subtraction operation on the signal (S4) output from the adder (230) and the signal (S3) output from the feedback equalizer (220). At this time, the feedback equalizer (220) can calculate the signal (S3) from the signal (S5) based on some tap coefficients of the feedback equalizer (220).

[0062] In one embodiment, the signal (S3) may correspond to the output of a feedback equalizer (220) having a tap factor equal to the memory length of the maximum likelihood sequence estimator (280). That is, the tap factor of the signal (S6) may correspond to the memory length of the maximum likelihood sequence estimator (280).

[0063] The signal (S6) output from the subtractor (250_2) can be input to the maximum likelihood sequence estimator (280). The signal (S6) can be represented based on the following mathematical formula 3.

[0064]

[0065] Here, MLSEin(t) represents the signal (S6) at time t, and represents the signal (S4) at time t, and K represents the memory length of the maximum likelihood sequence estimator (280), represents the signal (S5) which is the output of the slicer, and can represent the tap coefficient of the i-th feedback equalizer.

[0066] The maximum likelihood sequence estimator (280) can select (or determine) the optimal symbol sequence (e.g., the most probable data sequence) among all possible symbol data sequences based on the signal (S6) and the branch metric (BM) received from the branch metric operator (270). The maximum likelihood sequence estimator (280) can output the selected symbol sequence as an output signal (S_OUT).

[0067] FIG. 5 shows a part of an equalization device according to one embodiment of the present invention. Referring to FIG. 5, the equalization device (300) may include a forward equalizer (310), a feedback equalizer (320), an adder (330), a slicer (340), a subtractor (350), and a maximum likelihood sequence estimator (360).

[0068] The forward equalizer (310) may include a plurality of delayers (311), a plurality of multipliers (312), and an adder (313).

[0069] The feedback equalizer (320) may include a plurality of delayers (321), a plurality of multipliers (322), and an adder (323).

[0070] As shown in FIG. 5, the tap coefficients of the forward equalizer (310) ( ~ ) and tap coefficients of the feedback equalizer (320) ~ ) can be determined during the first mode. At this time, 'y', which is the output signal of the forward equalizer (310), nf ' and the output signal of the feedback equalizer (320) 'y nbThe signal 'y(t)' based on ' can be a signal that removes interference caused by the channel response and includes the remaining residual interference. The difference between 'y(t)' and the training symbol data can be the error signal 'e(t)'. The equalizer (300) can obtain the tap coefficients of the equalizer through the aforementioned mathematical formulas so that the least mean square error is minimized.

[0071] During the first mode, channel estimation for the equalization process of the maximum likelihood sequence estimator (360) has the advantage of low complexity and being actively adaptable to changes in the channel because it uses the tap coefficients of the feedback equalizer (320). In channel estimation, a branch metric related to the state transition probability according to the input of the maximum likelihood sequence estimator (360) may be required. To calculate this state transition probability, tap coefficients are set during the first mode by assuming an equivalent optical transmission channel formed with a channel length 'L' that reflects the residual interference of the training symbols through the training symbol data. After channel estimation is performed, an equalization process to compensate for the residual optical channel response can be performed through the maximum likelihood sequence estimator (360) during the second mode.

[0072] In the embodiments described above, components according to the technical concept of the present invention have been described using terms such as first, second, third, etc. However, terms such as first, second, third, etc. are used to distinguish the components from one another and do not limit the present invention. For example, terms such as first, second, third, etc. do not imply a sequential order or any numerical meaning.

[0073] The description above describes specific examples for implementing the present invention. The present invention will include not only the embodiments described above, but also embodiments that can be easily modified or simply changed. Furthermore, the present invention will include technologies that can be easily modified and implemented in the future using the embodiments described above. Explanation of the symbols

[0074] 100, 200, 300: Lighting devices

Claims

Claim 1 An equalization device comprising: a forward equalizer that filters an input signal based on a first tap factor and outputs a first signal; a feedback equalizer that outputs a second signal based on a second tap factor and outputs a third signal based on at least a portion of the second tap factor; a tap factor algorithm operator that generates the first tap factor and the second tap factor; an adder that adds the first signal and the second signal to output an equalized fourth signal; a slicer that outputs a fifth signal based on the level of the fourth signal; a first subtractor that subtracts the third signal and the fourth signal to output a sixth signal; a branch metric operator that calculates a branch metric associated with the sixth signal; and a maximum likelihood sequence estimator that selects an optimal symbol sequence based on the sixth signal and the branch metric.

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