WO2014166398A1 - 非线性加权系数的计算装置以及方法 - Google Patents

非线性加权系数的计算装置以及方法 Download PDF

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WO2014166398A1
WO2014166398A1 PCT/CN2014/075024 CN2014075024W WO2014166398A1 WO 2014166398 A1 WO2014166398 A1 WO 2014166398A1 CN 2014075024 W CN2014075024 W CN 2014075024W WO 2014166398 A1 WO2014166398 A1 WO 2014166398A1
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nonlinear
weighting coefficient
nonlinear weighting
coefficient
function
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PCT/CN2014/075024
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English (en)
French (fr)
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赵颖
窦亮
陶振宁
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富士通株式会社
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Priority to JP2016506771A priority Critical patent/JP6260687B2/ja
Publication of WO2014166398A1 publication Critical patent/WO2014166398A1/zh
Priority to US14/879,374 priority patent/US9998223B2/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/25—Arrangements specific to fibre transmission
    • H04B10/2507—Arrangements specific to fibre transmission for the reduction or elimination of distortion or dispersion
    • H04B10/2543—Arrangements specific to fibre transmission for the reduction or elimination of distortion or dispersion due to fibre non-linearities, e.g. Kerr effect
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/50—Transmitters
    • H04B10/58—Compensation for non-linear transmitter output
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/60—Receivers
    • H04B10/61—Coherent receivers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/60—Receivers
    • H04B10/61—Coherent receivers
    • H04B10/616—Details of the electronic signal processing in coherent optical receivers
    • H04B10/6163—Compensation of non-linear effects in the fiber optic link, e.g. self-phase modulation [SPM], cross-phase modulation [XPM], four wave mixing [FWM]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/60—Receivers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J14/00—Optical multiplex systems
    • H04J14/02—Wavelength-division multiplex systems
    • H04J14/0227—Operation, administration, maintenance or provisioning [OAMP] of WDM networks, e.g. media access, routing or wavelength allocation
    • H04J14/0254—Optical medium access
    • H04J14/0267—Optical signaling or routing
    • H04J14/0271—Impairment aware routing

Definitions

  • the present invention relates to a long-distance optical fiber communication system, and more particularly to a computing device and method for nonlinear weighting coefficients. Background technique
  • the physical mechanism of nonlinear effects in the channel is derived from the nonlinear Kerr effect of electromagnetic waves interacting with the fiber medium.
  • the dispersion length and the nonlinear length I :V i are much smaller than the system transmission distance, so the light
  • the pulse signal is combined by the nonlinear effect in the channel and the dispersion effect of the fiber, resulting in energy exchange between adjacent pulses, causing significant signal waveform distortion.
  • the pulse signal still produces nonlinear distortion, and the transmission system is still subject to significant nonlinear damage.
  • the time domain pulse sequence is mainly subject to waveform distortion caused by intra-channel cross-phase modulation (IXPM) and intra-channel four-wave mixing (IFWM) effects.
  • IXPM intra-channel cross-phase modulation
  • IFWM intra-channel four-wave mixing
  • the propagation equation of pulse evolution in fiber can be described by the nonlinear Schrödinger equation (described by Manakov equation under random polarization).
  • the nonlinear Schrödinger equation does not have an analytical solution considering the nonlinear and dispersion effects
  • the quantitative study of the nonlinearity in the channel and the related theoretical models are all developed and established for the approximate solution of the nonlinear Schrödinger equation.
  • the methods for solving the nonlinear Schrödinger equation are divided into two methods: numerical solution and approximate analytical method.
  • the numerical solution mainly includes the distributed Fourier method and the time-domain finite difference method.
  • the approximate analytical method mainly includes the inverse scattering method and the Volterra expansion method.
  • DSP digital signal processing
  • Kahii et al. examined the nonlinear compensation performance when the calculated step size is equal to the length of the fiber span.
  • F. Yaman et al. applied the method to a polarization multiplexing system. When the step size is less than or equal to 1/3 of the fiber span, the compensation performance is optimized.
  • the disadvantage of the distributed Fourier numerical solution is that the complexity is too large. Even if the step size is equal to the length of the fiber span, the number of calculations of the method is still a huge challenge to the current DSP technology.
  • the approximate analytical method is expected to significantly reduce the computational complexity of nonlinear analysis, it has received extensive attention in the academic world and has been rapidly developed in recent years.
  • Using the backscattering method to solve the Schrödinger equation can be used to derive the soliton solution of the nonlinear transmission system, which is used for the analysis of soliton communication systems.
  • the Volterm series expansion method is another method for solving the nonlinear Schrödinger equation, so that the analysis framework of the traditional communication system can be borrowed into the fiber-optic communication system, and has good versatility for different pulse shapes and link types.
  • the weighting coefficient occupies an important position in the nonlinear distortion estimation, but at present, there is no research on how to obtain a high-precision weighting coefficient, and it cannot be damaged. High-precision estimation of nonlinear distortion is performed.
  • Non-Patent Document 1 A. Mecozzi et. al., IEEE PTL Vol. 12, No. 4, pp. 392-394, 2000
  • Non-Patent Document 2 GP Agrawal, Nonlinear Fiber Optics, 2nd ed. New York: Academic, 1995
  • Non-Patent Document 3 KV Peddanarappagari et. al., IEEE JLT Vol. 15, pp. 2232-2241, 1997
  • Non-Patent Document 4 IEEE JLT Vol. 16, pp. 2046-1055, 1998
  • Non-Patent Document 5 E. Ip and J. Kahn, IEEE JLT Vol. 26, No. 20, pp. 3416-3425, 2008
  • Non-Patent Document 6 F. Yaman et. al., IEEE Photonics Journal Vol. 1, No. 2, pp. 144-152, 2009
  • Non-Patent Document 7 A. Vannucci et. al, IEEE JLT Vol 20, No. 7, pp.1102-1111, 2002
  • Non-Patent Document 8 S. Kumar et. al., Optics Express, Vol. 20, No. 25, pp.27740-27754, 2012
  • Non-Patent Document 9 E. Ciaramella et. al., IEEE PTL Vol. 17, No. 1, pp. 91-93, 2005
  • Non-Patent Document 10 A. Carena et.al, IEEE JLT Vol. 30, No. 10, pp.1524-1539, 2012
  • Non-Patent Document 11 X. Chen et. al., Optics Express, Vol. 18, No. 18, pp. 19039-19054, 2010
  • Non-Patent Document 12 X. Wei, Optics Letters, Vol. 31 , No. 17, pp. 2544-2546, 2006
  • Embodiments of the present invention provide a computing apparatus and method for nonlinear weighting coefficients, aiming at obtaining a high-precision weighting coefficient, thereby accurately estimating nonlinear distortion in a lossy condition.
  • a computing device for nonlinear weighting coefficients includes:
  • An approximate processing unit that approximates the link loss/gain function in the nonlinear distortion estimation in the channel by using a rational function
  • the coefficient calculation unit calculates the nonlinear weighting coefficient in the nonlinear distortion estimation by the approximated link loss/gain function and the large dispersion approximation.
  • a method for calculating a nonlinear weighting coefficient includes:
  • the link loss/gain function in the nonlinear distortion estimation is approximated by a rational function; the non-linear weighting coefficient in the nonlinear distortion estimation is processed by the approximated link loss/gain function and large dispersion approximation.
  • a predistortion apparatus for nonlinear distortion wherein the precompensation apparatus includes:
  • a perturbation term calculation unit that calculates a vector perturbation term superimposed on the transmitted signal by using a nonlinear weighting coefficient obtained by the computing device of the nonlinear weighting coefficient
  • a post-compensation apparatus for nonlinear distortion
  • the post-compensation apparatus includes:
  • a perturbation term calculation unit that calculates a vector perturbation term superimposed on the transmitted signal by using a nonlinear weighting coefficient obtained by the computing device of the nonlinear weighting coefficient
  • a compensation unit that compensates for the received signal using the vector perturbation term.
  • the beneficial effects of the embodiments of the present invention are: approximating the link loss/gain function by using a rational function, so that the nonlinear weighting coefficient has an expression form of the analytical closed solution; and obtaining a high-precision weighting coefficient, thereby causing a lossy condition High-precision estimation of nonlinear distortion.
  • Figure 1 is a schematic diagram of a typical optical communication system
  • FIG. 2 is a schematic diagram of a power weighted dispersion distribution function in the case of no dispersion compensation
  • Figure 3 is a schematic diagram of the power weighted dispersion distribution function in the case of 95% dispersion compensation
  • FIG. 4 is a schematic diagram showing the structure of a nonlinear weighting coefficient calculation apparatus according to Embodiment 1 of the present invention
  • 5 is another schematic configuration diagram of a non-linear weighting coefficient calculation apparatus according to Embodiment 1 of the present invention
  • FIG. 6 is another schematic configuration diagram of a nonlinear weighting coefficient calculation apparatus according to Embodiment 1 of the present invention
  • FIG. 8 is a schematic flowchart of a method for calculating a nonlinear weighting coefficient according to Embodiment 2 of the present invention
  • FIG. 9 is another schematic flowchart of a method for calculating a nonlinear weighting coefficient according to Embodiment 2 of the present invention
  • FIG. 11 is a schematic diagram of a configuration of a nonlinear distortion pre-compensation apparatus according to Embodiment 3 of the present invention
  • FIG. 12 is a schematic diagram of nonlinear distortion of Embodiment 3 of the present invention
  • FIG. 13 is a schematic diagram showing a configuration of a nonlinear distortion post-compensation apparatus according to Embodiment 4 of the present invention
  • FIG. 14 is a flow chart showing a nonlinear distortion post-compensation method according to Embodiment 4 of the present invention.
  • the nonlinear effect can be fully described by the Volterra series (first-order perturbation) below the third order. Therefore, the current popular nonlinear analysis is subject to the analysis of low-order Volterra series expansion. Frame, the quasi-linear approximation. Under the quasi-linear approximation, the nonlinear perturbation theory develops to the following branches: For example, conventional perturbation method: The conventional perturbation method based on quasi-linear approximation approximates nonlinear distortion with a first-order perturbation term.
  • the first-order perturbation describes the vector sum of the nonlinear distortions of the points passing through the dispersion on the propagation path, and the analytical expression is the triple integral with the product of the three-term transmission pulse as the integrand.
  • Theoretical analysis shows that the numerical integration of the first-order perturbation has similar computational complexity to the distributed Fourier method. Therefore, the first-order perturbation method is not applicable to the DSP of nonlinear estimation without integral analytical calculation. achieve. In order to further reduce the computational complexity of the conventional perturbation method, it is necessary to further analyze the triple integral. At present, the calculation of this triple integral is only seen. Two methods are reported:
  • Enhanced Conventional Perturbation (ERP) and Multiplicative Perturbation Models Since conventional perturbation methods only consider first-order perturbations, they are usually only applicable to situations where the transmit power is small. In order to further increase the accuracy of nonlinear distortion estimation at higher power levels, the extrapolation-based high-order perturbation theory has been developed accordingly.
  • the enhanced conventional perturbation method is a high-order correction of the conventional perturbation method. By introducing the phase shift factor intuitively in the conventional first-order perturbation, the accuracy of the perturbation method at a large power can be significantly improved.
  • the multiplicative perturbation model [9] is another approximate solution considering high-order perturbation. The basic idea is to modify the additive perturbation to multiplicative perturbation to approximate the high-order perturbation term of the conventional perturbation method. Increase the accuracy at higher power.
  • PSD power spectral density
  • FIG. 1 is a schematic diagram of a typical optical communication system in which a signal transmitted by a transmitter reaches a receiver through different devices (fiber, optical amplifier, dispersion compensation fiber, etc.) in a transmission link.
  • the intra-channel nonlinear model can be first established in the process of implementing the present invention.
  • the basic model of the nonlinearity in the channel will be briefly described below.
  • the polarization multiplexing optical fiber transmission system can be abstracted into the Manakov equation under the assumption of slow envelope and random polarization rotation:
  • M t, Z ) and Mf t, Z ) are the electric field components of the signal in the H and polarization states, respectively, ⁇ ( ⁇ ), ⁇ 2 ( ⁇ ) and ⁇ ( ⁇ ) represent the fiber link, respectively.
  • the signal generated by the transmitter is often composed of light pulses and can be written in the form of equation (2)
  • Equation (3) shows that the perturbation at the first pulse sampling moment of the receiver is the weighted sum of multiple interaction terms, each of which is the product of the three-term product of the transmitted pulse information symbol and the corresponding weighting coefficient.
  • the weighting coefficient is the only parameter that determines the nonlinear perturbation, which is related to the pulse shape, the interaction pulse timing (, n) and the link parameters.
  • this weighting coefficient can be expressed by an analytical closed solution (a primary function or a special function that can be calculated by a table lookup method)
  • the nonlinear distortion ( ⁇ . ⁇ , Au v ) can also be obtained based on this closed solution. But without considering any approximation, the coefficient can only be expressed as a triple integral form:
  • FIG. 2 is a schematic diagram of a power weighted dispersion distribution function in the case of no dispersion compensation
  • FIG. 3 is a schematic diagram of a power weighted dispersion distribution function in the case of 95% dispersion compensation.
  • Example 1 The following is a detailed description of how to obtain high-precision weighting coefficients under loss/gain conditions.
  • Example 1 The following is a detailed description of how to obtain high-precision weighting coefficients under loss/gain conditions.
  • FIG. 4 is a schematic structural diagram of a computing device for nonlinear weighting coefficients according to an embodiment of the present invention.
  • the non-linear weighting coefficient computing device 400 includes an approximation processing unit 401 and a coefficient calculation unit 402.
  • the approximation processing unit 401 approximates the link loss/gain function in the nonlinear distortion estimation in the channel by using the rational function; the coefficient calculation unit 402 approximates the nonlinear distortion by the approximated link loss/gain function and the large dispersion approximation
  • the nonlinear weighting coefficients in the estimation are calculated to obtain an analytical closed solution of the nonlinear weighting coefficients.
  • the path loss/gain function can be approximated by the rational function chain, so that the nonlinear weighting coefficient as shown in equation (4) can have an expression of the analytical closed solution, and thus the calculated weighting The coefficient has a significant improvement in accuracy.
  • Fig. 5 is a block diagram showing another configuration of a non-linear weighting coefficient calculating apparatus according to an embodiment of the present invention.
  • the non-linear weighting coefficient computing device 500 includes an approximation processing unit 401 and a coefficient calculation unit 402, as described above.
  • the non-linear weighting coefficient computing device 500 may further include: a coefficient processing unit 503; the coefficient processing unit 503 performs integration processing on the nonlinear weighting coefficients in the nonlinear distortion estimation by using a dispersion distribution function; The coefficient calculation unit 402 passes the approximated link loss/gain function and large dispersion near It is like calculating the nonlinear weighting coefficient after the integral processing.
  • the coefficient processing unit 503 can be used to process the triple integration of the nonlinear weighting coefficient as shown in the equation (4), thereby expressing the unweighted coefficient more intuitively and accurately.
  • the triple integral form as shown in the equation (4) can be further integrated by the dispersion distribution function to obtain a one-fold integral form; for example, the equation (6) as described later can be obtained.
  • the present invention is not limited thereto, and for example, any other pulse shape may be employed to obtain other one-fold integral forms.
  • the present invention can also calculate nonlinear weighting coefficients for a plurality of fiber spans, and obtain a nonlinear weighting coefficient of the entire link after summing.
  • Fig. 6 is a block diagram showing another configuration of a non-linear weighting coefficient calculating apparatus according to an embodiment of the present invention.
  • the non-linear weighting coefficient computing device 600 includes an approximation processing unit 401, a coefficient calculation unit 402, and a coefficient processing unit 503, as described above.
  • the computing device 600 for nonlinear weighting coefficients may further include: a fiber dividing unit 604 and a coefficient summing unit 605.
  • the fiber dividing unit 604 divides the fiber of the entire transmission link into multiple fiber spans;
  • the non-linear weighting coefficients corresponding to the fiber span are calculated by the approximation processing unit 401 and the coefficient calculation unit 402, or the approximate processing unit 401, the coefficient processing unit 503, and the coefficient calculation unit 402.
  • the coefficient summation unit 605 sums the nonlinear weighting coefficients of the different fiber spans obtained respectively to obtain an analytical closed solution of the nonlinear weighting coefficients of the entire transmission link.
  • the approximation processing unit 401 may also be further configured to use a Gaussian pulse function, or a non-return-to-zero pulse (NRZ) function, or a return-to-zero pulse (RZ) function, or a Nyquist pulse function. Etc. to approximate the shape of the pulse in the nonlinear distortion estimation in the channel.
  • NRZ non-return-to-zero pulse
  • RZ return-to-zero pulse
  • Nyquist pulse function a Nyquist pulse function.
  • the present invention is not limited thereto, and for example, other pulse shapes may be employed, and it may be applied to any other pulse shape.
  • the present invention will be described in detail by taking a pulse shape as a Gaussian pulse as an example.
  • the coefficient processing unit 503 may substitute the above condition into the equation (5) to obtain: JiiC) -: p[ ⁇ - (C'/0 '- (i - - ⁇ ) £, / ⁇ /3 ⁇ 4
  • the coefficient processing unit 503 can first integrate tl and t2 by the formula (4):
  • the approximation processing unit 401 approximates the standard fiber attenuation G (. J exp b can be approximated by a rational function, and for the exponential decay function, it can be approximated by the following rational fraction:
  • N is the attenuation control factor
  • i is the fiber span index
  • i-th fiber is the transmission distance in the i-th fiber.
  • the pulse shape is not limited to a Gaussian pulse or a pulse example as exemplified above, and the present invention can be applied to any other pulse shape.
  • Figure 7 is a schematic illustration of an approximate attenuation function of an embodiment of the present invention. As shown in Fig. 7, the approximation function is shown in the second fiber span (the length of each segment is 100km, ⁇ ( ⁇ ⁇ ( ⁇ ⁇ approximates the trend of the exponential decay function. As shown in Figure 7, when ⁇ is sufficient When large, the approximation function can accurately approximate the exponential decay function.
  • the coefficient calculation unit 402 may substitute (7) into (6) and introduce a large dispersion approximation (C':») to further calculate the integral.
  • the coefficient summation unit 605 can sum the nonlinear weighting coefficients of different fiber spans obtained respectively to obtain an analytical closed solution of the weighting coefficients: , ⁇ ". ; .; ⁇ , ⁇ ' ⁇ (]... ⁇ .. iAi ⁇ "- -; ⁇ , -- ⁇ ?
  • the present invention proposes to approximate the approximation using a rational function, so that the integral expression (6) has an expression form of the analytical closed solution.
  • the weighting coefficients calculated using equation (8) have significant accuracy improvements over the prior art methods.
  • the invention is not limited to standard attenuation links, but can also be applied to links with exponential gain or other forms of attenuation/gain function. Compatibility and high accuracy for other pulse shapes is also one of the significant advantages of the present invention.
  • the link loss/gain function is approximated by the rational function, so that the nonlinear weighting coefficient has the expression form of the analytical closed solution; the high-precision weighting coefficient can be obtained, so that the nonlinearity is in the lossy case. Distortion is estimated with high precision.
  • the fiber of the entire transmission link is divided into multiple fiber spans and nonlinear weighting coefficients are calculated for different fiber spans, so that the calculation of nonlinear weighting coefficients can be applied not only to the dispersion-free compensation link, but also to Dispersion management link.
  • Example 2
  • the embodiment of the present invention provides a method for calculating a nonlinear weighting coefficient, which corresponds to the non-linear weighting coefficient computing device of Embodiment 1, and the same content is not described herein again.
  • FIG. 8 is a schematic flowchart of a method for calculating a nonlinear weighting coefficient according to an embodiment of the present invention. As shown in FIG. 8, the method for calculating the nonlinear weighting coefficient includes:
  • Step 801 using a rational function to approximate the link loss/gain function in the nonlinear distortion estimation; Step 802, nonlinearly weighting the nonlinear distortion estimation by the approximated link loss/gain function and large dispersion approximation The coefficients are processed.
  • FIG. 9 is another schematic flowchart of a method for calculating a nonlinear weighting coefficient according to an embodiment of the present invention. As shown in FIG. 9, the method for calculating the nonlinear weighting coefficient includes:
  • Step 901 using a rational function to approximate the link loss/gain function in the nonlinear distortion estimation
  • Step 902 Perform integration processing on the nonlinear weighting coefficients in the nonlinear distortion estimation by using a dispersion distribution function
  • Step 903 Calculate the nonlinearly weighted coefficients after the integral processing in the nonlinear distortion estimation by using the approximated link loss/gain function and the large dispersion approximation to obtain an analytical closed solution of the nonlinear weighting coefficients.
  • the present invention can also calculate nonlinear weighting coefficients for a plurality of fiber spans, and obtain a nonlinear weighting coefficient of the entire link after summing.
  • FIG. 10 is another schematic flowchart of a method for calculating a nonlinear weighting coefficient according to an embodiment of the present invention. As shown in FIG. 10, the method for calculating the nonlinear weighting coefficient includes:
  • Step 1001 Divide the fiber of the entire transmission link into multiple fiber spans.
  • Step 1002 approximate the link loss/gain function in the nonlinear distortion estimation by using a rational function
  • Step 1003 Integrate the nonlinear weighting coefficient in the nonlinear distortion estimation by using a dispersion distribution function
  • Step 1004 Calculate the nonlinearly weighted coefficients after the integral processing in the nonlinear distortion estimation by the approximated link loss/gain function and large dispersion approximation.
  • Step 1005 Calculate the nonlinear weighting coefficients of the plurality of different fiber spans obtained separately to obtain an analytical closed solution of the nonlinear weighting coefficients of the entire transmission link.
  • the link loss/gain function is approximated by the rational function, so that the nonlinear weighting coefficient has the expression form of the analytical closed solution; the high-precision weighting coefficient can be obtained, so that the nonlinearity is in the lossy case. Distortion is estimated with high precision.
  • the fiber of the entire transmission link is divided into multiple fiber spans and nonlinear weighting coefficients are calculated for different fiber spans, so that the calculation of nonlinear weighting coefficients can be applied not only to the dispersion-free compensation link, but also to Dispersion management link.
  • Embodiments of the present invention provide a predistortion apparatus and method for nonlinear distortion.
  • Figure 11 is an embodiment of the present invention
  • a schematic diagram of a configuration of a nonlinear distortion pre-compensation device, as shown in FIG. 11, a nonlinear distortion pre-compensation device 1100 includes: a nonlinear weighting coefficient calculation device 1101, a perturbation term calculation unit 1102, and a pre-compensation unit 1103 .
  • the computing device 1101 for nonlinear weighting coefficients can be as shown in Embodiment 1.
  • the perturbation term calculation unit 1102 calculates a vector perturbation term superimposed on the transmission signal using the nonlinear weighting coefficient obtained by the calculation device 1101 of the nonlinear weighting coefficient; the pre-compensation unit 1103 precompensates the transmission signal with the vector perturbation term to Obtain a predistorted signal that is input to the transmitter.
  • the basic idea of the pre-compensation method is to transmit signals that are subjected to a specific deformation, and these signals obtain an ideal lossless signal at the receiving end after the nonlinear effect transmitted through the optical fiber. It is worth noting that the linear impairment of the channel is assumed to be compensated by other methods in this embodiment.
  • the vector perturbation superimposed on the transmitted signal can be more accurately calculated, so that the nonlinear distortion can be realized by decomposing the vector perturbation in advance by the transmitter.
  • Pre-compensation The sequence of information obtained by pre-compensation is calculated as follows:
  • Equation can be understood as the pre-compensated information sequence equal to the original information sequence minus the vector perturbation term generated by the nonlinear effect at the distance L.
  • the calculation of the weighting coefficient C3 ⁇ 4e/(m., n, z - ) can be performed as in Embodiment 1 or 2.
  • FIG. 12 is a schematic flow chart of a method for pre-compensating nonlinear distortion according to an embodiment of the present invention. As shown in Figure 12, the predistortion method for nonlinear distortion includes:
  • Step 1201 Calculate a nonlinear weighting coefficient of each item
  • the nonlinear weighting coefficient of each term can be calculated by using the calculation method or apparatus of the nonlinear weighting coefficient described in Embodiment 1 or 2.
  • Step 1202 Calculate a vector perturbation term of the sampling point at the current time.
  • Step 1203 Calculate a pre-compensation waveform of the sampling point at the current time.
  • step 1204 the original information sequence is pre-compensated to obtain a pre-distorted waveform input to the transmitter. It can be seen from the above embodiment that by using the calculation method of the above nonlinear weighting coefficient to perform pre-compensation, the vector perturbation superimposed on the transmitted signal can be calculated more accurately, so that the method of deducting the vector perturbation in the transmitter can be realized. Pre-compensation for nonlinear distortion. Example 4
  • FIG. 13 is a schematic diagram of a non-linear distortion post-compensation device according to an embodiment of the present invention.
  • the nonlinear distortion post-compensation device 1300 includes : a non-linear weighting coefficient calculation means 1301, a perturbation term calculation unit 1302, and a compensation unit 1303.
  • the computing device 1301 for nonlinear weighting coefficients can be as shown in Embodiment 1.
  • the perturbation term calculation unit 1302 calculates a vector perturbation term superimposed on the transmission signal using the nonlinear weighting coefficient obtained by the calculation device 1301 of the nonlinear weighting coefficient; the compensation unit 1303 compensates the received signal by using the vector perturbation term .
  • the vector perturbation superimposed on the ideal transmission signal can be calculated by the calculation method of the nonlinear weighting coefficient of the above embodiment 1 or 2.
  • the calculated nonlinear perturbation can accurately reflect the distortion of the corresponding sampling point at the receiver end. Therefore, this part of the nonlinear perturbation can be directly deducted at the receiver end to obtain compensation.
  • the sequence of information is described by:
  • R' H k , R' v k are the sampling point information of the two polarization states at time k after compensation by the receiver
  • R H k , R V k are respectively the receiver after compensating for other damages at k
  • the sampling point information input to the post-compensation device at the moment.
  • FIG. 14 is a schematic flow chart of a post-compensation method for nonlinear distortion according to an embodiment of the present invention. As shown in Figure 14, the post-compensation method for nonlinear distortion includes:
  • Step 1401 calculating a nonlinear weighting coefficient of each item
  • the nonlinear weighting coefficient of each term can be calculated by the calculation method or apparatus for the nonlinear weighting coefficient described in the first or second embodiment.
  • Step 1402 Calculate a vector perturbation term of the sampling point at the current time.
  • Step 1403 Calculate a distortion waveform of the sampling point at the current time.
  • Step 1404 compensating the sampling point waveform received by the receiver to obtain the compensated sampling point waveform. It can be seen from the above embodiment that by using the calculation method of the above nonlinear weighting coefficient to compensate, the vector perturbation superimposed on the transmitted signal can be calculated more accurately, so that the nonlinear perturbation method can be used at the receiver to achieve nonlinearity. Distortion compensation.
  • the above apparatus and method of the present invention may be implemented by hardware, or may be implemented by hardware in combination with software.
  • the present invention relates to a computer readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to cause the logic component to implement the various methods described above Or steps.
  • the present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, and the like.
  • a computing device for nonlinear weighting coefficients comprising:
  • An approximate processing unit that approximates the link loss/gain function in the nonlinear distortion estimation in the channel by using a rational function
  • the coefficient calculation unit calculates the nonlinear weighting coefficient in the nonlinear distortion estimation by the approximated link loss/gain function and the large dispersion approximation to obtain an analytical closed solution of the nonlinear weighting coefficient.
  • a coefficient processing unit that uses a dispersion distribution function to integrate the nonlinear weighting coefficients in the nonlinear distortion estimation
  • the coefficient calculation unit calculates the nonlinear weighting coefficient after the integration processing by the approximated link loss/gain function and the large dispersion approximation.
  • the fiber dividing unit divides the fiber of the entire transmission link into a plurality of fiber spans
  • the approximation processing unit is further configured to use a Gaussian pulse function, or a non-return-to-zero pulse function, or a return-to-zero pulse function, Or the Nyquist pulse function to approximate the shape of the pulse in the nonlinear distortion estimation within the channel.
  • N is the attenuation control factor
  • Z! is the transmission distance in the first segment of the fiber.
  • a method for calculating a nonlinear weighting coefficient, and the method for calculating the nonlinear weighting coefficient includes:
  • a rational function is used to approximate the link loss/gain function in the nonlinear distortion estimation; the nonlinear weighting coefficient in the nonlinear distortion estimation is processed by the approximated link loss/gain function and large dispersion approximation, An analytical closed solution of the nonlinear weighting coefficients is obtained.
  • the nonlinear weighting coefficients in the nonlinear distortion estimation are integrated by the dispersion distribution function; and the integral processed nonlinear weighting coefficients are calculated by the approximated link loss/gain function and large dispersion approximation.
  • the nonlinear weighting coefficients of the plurality of different fiber spans obtained separately are summed to obtain an analytical closed solution of the nonlinear weighting coefficients of the entire transmission link.
  • N is the attenuation control factor
  • a non-linear distortion pre-compensation device comprising: the calculation device of the nonlinear weighting coefficient according to any one of the supplementary notes 1 to 5;
  • a perturbation term calculation unit that calculates a vector perturbation term superimposed on the transmitted signal by using a nonlinear weighting coefficient obtained by the computing device of the nonlinear weighting coefficient
  • a pre-compensation unit that pre-compensates the transmission signal with the vector perturbation term to obtain a pre-distortion signal input to the transmitter.
  • a pre-compensation method for nonlinear distortion comprising: a calculation step of the nonlinear weighting coefficient according to any one of the supplementary notes 6 to 10;
  • the transmitted signal is pre-compensated with the vector perturbation term to obtain a pre-distorted signal input to the transmitter.
  • the compensating apparatus comprises: the calculation apparatus of the non-linear weighting coefficient according to any one of claims 1 to 5;
  • a perturbation term calculation unit that calculates a vector perturbation term superimposed on the transmitted signal by using a nonlinear weighting coefficient obtained by the computing device of the nonlinear weighting coefficient
  • a compensation unit that compensates for the received signal using the vector perturbation term.
  • a post-compensation method for nonlinear distortion wherein the compensation method comprises: a calculation step of the nonlinear weighting coefficient according to any one of claims 6 to 10;
  • the received signal is compensated by the vector perturbation term.
  • (Supplement 15) A computer readable program, wherein the program causes a computer to perform a predistortion method of nonlinear distortion as described in Attachment 12 in the transmitter when the program is executed in a transmitter .
  • a storage medium storing a computer readable program, wherein the computer readable program causes a computer to perform a predistortion method of nonlinear distortion as described in Attachment 12 in a transmitter.
  • (Supplement 18) A storage medium storing a computer readable program, wherein the computer readable program causes a computer to perform a post-compensation method of nonlinear distortion as described in Attachment 14 in a receiver.

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Abstract

本发明实施例提供一种非线性加权系数的计算装置以及方法，所述非线性加权系数的计算装置包括：近似处理单元，利用有理函数对信道内非线性失真估计中的链路损耗/增益函数进行近似处理；系数计算单元，通过近似后的所述链路损耗/增益函数以及大色散近似对非线性失真估计中的非线性加权系数进行计算，以获得所述非线性加权系数的解析闭解。通过本发明实施例，可以获得高精度的加权系数，从而在有损情况下对非线性失真进行高精度估计。

Description

非线性加权系数的计算装置以及方法 技术领域
本发明涉及长距离光纤通信系统，特别涉及一种非线性加权系数的计算装置以及 方法。 背景技术
多媒体等宽带业务需求的增长推动光纤通信系统向单信道传输 100Gbit/S以上方 向发展。 当单信道速率达到 40Gbit/s以上时， 信道内非线性效应会显著作用于传输信 号， 从而对通信质量产生影响。
信道内非线性效应的物理机制源于电磁波与光纤媒质相互作用的非线性克尔效 应。 在高速长距离光纤传输系统中， 由于光脉冲信号符号周期很短 （<100ps) 同时发 送功率较高 （>0dBm)， 使色散长度 与非线性长度 I :V i远小于系统传输距离， 因此 光脉冲信号受到信道内非线性效应与光纤色散效应的联合作用，导致相邻脉冲之间产 生能量交换， 造成显著的信号波形失真。 在这种情况下， 即使在接收端对链路中的残 余色散进行补偿， 脉冲信号仍然会产生非线性畸变， 传输系统也依然会受到显著的非 线性损伤。
考虑光纤中信道内非线性和色散的联合作用，时域脉冲序列主要受到由信道内交 叉相位调制 （IXPM) 与信道内四波混频 （IFWM) 效应导致的波形失真。 这些失真 可定性描述为： 定时抖动、 脉冲幅度波动以及影子脉冲的产生。 其中定时抖动与脉冲 幅度波动源于由 IXPM效应导致的非对称啁啾； 影子脉冲则来源于 IFWM效应导致 的脉冲能量交换。如何定量计算以上脉冲失真现象对长距离光纤系统的影响以及评价 传输系统性能一直是光纤通信系统研究的重要课题。
基于慢变包络近似和恒定偏振态假设，光纤内脉冲演化的传输方程可由非线性薛 定谔方程来描述 （随机偏振下用 Manakov方程描述）。 但由于非线性薛定谔方程在考 虑非线性和色散效应共同作用下没有解析解，故针对信道内非线性的定量研究以及相 关的理论模型都是针对非线性薛定谔方程的近似解法发展和建立的。目前求解非线性 薛定谔方程的方法分为数值解法和近似解析法两类，其中数值解法主要包括分布傅里 叶法和时域有限差分法； 近似解析法主要包括反散射法和 Volterra展开方法。 随着数字信号处理（DSP) 技术在长距离光纤通信系统中的广泛应用， 在数字域 进行对系统非线性失真的估计或补偿成为对抗光纤链路非线性的有效方法。分布傅里 叶算法作为非线性薛定谔方程的标准数值解法，可以作为估计和消除非线性畸变的候 选方法。
Kahii等人考察了计算步长等于光纤跨段长度时的非线性补偿性能。 F. Yaman等 人将该方法应用于偏振复用系统之中， 当步长为光纤跨段的 1/3以下时， 补偿的性能 达到最优。分布傅里叶数值解法的缺点在于复杂度过大， 即便步长等于光纤跨段的长 度时， 该方法的计算次数仍然对目前的 DSP技术是一个巨大的挑战。
由于近似解析方法有望显著减小非线性分析的计算复杂度，因而受到了学术界的 广泛关注并且在近些年得到了迅速的发展。利用反散射法求解薛定谔方程可用于导出 非线性传输系统的孤子解， 从而用于孤子通信系统的分析。 Volterm级数展开方法作 为求解非线性薛定谔方程的另外一种方法，使传统通信系统的分析框架可以被借用到 光纤通信系统， 并且对不同的脉冲形状和链路类型具有较好的通用性。 Paolo Serena 基于 Volterm展开方法发展得到了常规微扰法（RP)并赋予各阶微扰较明确的物理意 义， 从而使微扰求解薛定谔的方法得到了迅速的发展， 衍生出了多种理论框架用于在 时域或频域定量非线性失真。
但是， 在实现本发明的过程中， 发明人发现现有技术的缺陷在于： 加权系数在非 线性失真估计中占有重要位置，但是目前没有对如何获得高精度的加权系数进行研究， 不能在有损情况下对非线性失真进行高精度估计。
下面列出了对于理解本发明和常规技术有益的文献，通过引用将它们并入本文中， 如同在本文中完全阐明了一样。
[非专利文献 1]： A. Mecozzi et. al.， IEEE PTL Vol. 12, No. 4, pp.392-394, 2000
[非专利文献 2] : G. P. Agrawal, Nonlinear Fiber Optics, 2nd ed. New York: Academic, 1995 [非专利文献 3] : K. V. Peddanarappagari et. al.， IEEE JLT Vol. 15, pp.2232-2241, 1997 [非专利文献 4] : IEEE JLT Vol. 16, pp.2046-1055, 1998
[非专利文献 5]： E. Ip and J. Kahn, IEEE JLT Vol. 26, No. 20, pp.3416-3425, 2008
[非专利文献 6]： F. Yaman et. al.， IEEE Photonics Journal Vol. 1, No. 2, pp.144-152, 2009 [非专利文献 7] : A. Vannucci et. al, IEEE JLT Vol. 20, No. 7, pp.1102-1111, 2002
[非专利文献 8] : S. Kumar et. al., Optics Express, Vol. 20, No. 25, pp.27740-27754, 2012 [非专利文献 9]： E. Ciaramella et. al.， IEEE PTL Vol. 17, No. 1, pp.91-93, 2005
[非专利文献 10]： A. Carena et.al, IEEE JLT Vol. 30, No. 10, pp.1524-1539, 2012
[非专利文献 11]： X. Chen et. al.， Optics Express, Vol. 18, No. 18, pp.19039-19054, 2010 [非专利文献 12]: X. Wei, Optics Letters, Vol. 31, No. 17, pp.2544-2546, 2006
应该注意， 上面对技术背景的介绍只是为了方便对本发明的技术方案进行清楚、 完整的说明， 并方便本领域技术人员的理解而阐述的。不能仅仅因为这些方案在本发 明的背景技术部分进行了阐述而认为上述技术方案为本领域技术人员所公知。 发明内容
本发明实施例提供一种非线性加权系数的计算装置以及方法， 目的在于获得高精 度的加权系数， 从而在有损情况下对非线性失真进行高精度估计。
根据本发明实施例的一个方面， 提供一种非线性加权系数的计算装置， 所述非线 性加权系数的计算装置包括：
近似处理单元， 利用有理函数对信道内非线性失真估计中的链路损耗 /增益函数 进行近似处理；
系数计算单元， 通过近似后的所述链路损耗 /增益函数以及大色散近似对非线性 失真估计中的非线性加权系数进行计算。
根据本发明实施例的另一个方面， 提供一种非线性加权系数的计算方法， 所述非 线性加权系数的计算方法包括：
利用有理函数对非线性失真估计中的链路损耗 /增益函数进行近似处理； 通过近似后的所述链路损耗 /增益函数以及大色散近似对非线性失真估计中的非 线性加权系数进行处理。
根据本发明实施例的另一个方面， 提供一种非线性失真的预补偿装置， 其中， 所 述预补偿装置包括：
如前所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
预补偿单元， 利用所述矢量微扰项预补偿所述发送信号， 以获得输入到发射机的 预失真信号。 根据本发明实施例的另一个方面， 提供一种非线性失真的后补偿装置， 其中， 所 述后补偿装置包括：
如前所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
补偿单元， 利用所述矢量微扰项对接收到的信号进行补偿。
本发明实施例的有益效果在于： 利用有理函数对链路损耗 /增益函数进行近似， 从而使非线性加权系数具有解析闭解的表达形式； 可以获得高精度的加权系数， 从而 在有损情况下对非线性失真进行高精度估计。
参照后文的说明和附图， 详细公开了本发明的特定实施方式， 指明了本发明的原 理可以被采用的方式。应该理解， 本发明的实施方式在范围上并不因而受到限制。 在 所附权利要求的精神和条款的范围内，本发明的实施方式包括许多改变、修改和等同。
针对一种实施方式描述和 /或示出的特征可以以相同或类似的方式在一个或更多 个其它实施方式中使用， 与其它实施方式中的特征相组合， 或替代其它实施方式中的 特征。
应该强调，术语 "包括 /包含"在本文使用时指特征、整件、步骤或组件的存在， 但并不排除一个或更多个其它特征、 整件、 步骤或组件的存在或附加。 附图说明
参照以下的附图可以更好地理解本发明的很多方面。 附图中的部件不是成比例 绘制的， 而只是为了示出本发明的原理。 为了便于示出和描述本发明的一些部分， 附 图中对应部分可能被放大或缩小。
在本发明的一个附图或一种实施方式中描述的元素和特征可以与一个或更多个 其它附图或实施方式中示出的元素和特征相结合。 此外， 在附图中， 类似的标号表示 几个附图中对应的部件， 并可用于指示多于一种实施方式中使用的对应部件。
图 1为典型的光通信系统示意图；
图 2是无色散补偿情况下的功率加权色散分布函数的一示意图；
图 3是 95%色散补偿情况下的功率加权色散分布函数的一示意图；
图 4是本发明实施例 1的非线性加权系数的计算装置的一构成示意图； 图 5是本发明实施例 1的非线性加权系数的计算装置的另一构成示意图； 图 6是本发明实施例 1的非线性加权系数的计算装置的另一构成示意图； 图 7是本发明实施例 1的近似衰减函数的一示意图；
图 8是本发明实施例 2的非线性加权系数的计算方法的一流程示意图； 图 9是本发明实施例 2的非线性加权系数的计算方法的另一流程示意图； 图 10是本发明实施例 2的非线性加权系数的计算方法的另一流程示意图; 图 11是本发明实施例 3的非线性失真的预补偿装置的一构成示意图； 图 12是本发明实施例 3的非线性失真的预补偿方法的一流程示意图； 图 13是本发明实施例 4的非线性失真的后补偿装置的一构成示意图； 图 14是本发明实施例 4的非线性失真的后补偿方法的一流程示意图。
具体实施方式
参照附图， 通过下面的说明书， 本发明的前述以及其它特征将变得明显。 在说明 书和附图中， 具体公开了本发明的特定实施方式， 其表明了其中可以采用本发明的原 则的部分实施方式， 应了解的是， 本发明不限于所描述的实施方式， 相反， 本发明包 括落入所附权利要求的范围内的全部修改、 变型以及等同物。
下面结合附图对本发明的各种实施方式进行说明。 这些实施方式只是示例性的， 不是对本发明的限制。为了使本领域的技术人员能够容易地理解本发明的原理和实施 方式，本发明的实施方式以偏振复用型光纤传输系统为例进行说明。但应该注意的是， 本发明不限于此， 本发明的实施方式可以适用于所有长距离光纤通信系统中。
对于典型的长距离光纤传输系统， 非线性作用主要可以由三阶以下的 Volterra级 数 （一阶微扰） 充分地予以描述， 故目前流行的非线性分析均接受低阶 Volterra级数 展开的分析框架，即准线性近似。在准线性近似下，非线性微扰理论向以下分支发展： 例如常规微扰法： 基于准线性近似的常规微扰法用一阶微扰项近似非线性失真。 一阶微扰描述经过色散作用的脉冲在传播路径上各点所受非线性失真的矢量和，解析 表达为以发送脉冲三项乘积为被积函数的三重积分。理论分析表明， 一阶微扰的数值 积分与分布傅里叶方法具有相近的计算复杂度， 因此， 在不进行积分解析计算的情况 下， 一阶微扰方法也不适用于非线性估计的 DSP实现。为了进一步减小常规微扰法的 计算复杂度， 需要对三重积分进行进一步解析运算。 目前， 对此三重积分的计算仅见 两种方法被报道：
( 1 ) 无损大色散链路的闭解： 此方法假设光纤传输链路无损耗且积累色散足够 大， 同时保证发送波形为高斯脉冲的情况下， 一阶微扰的三重积分严格可积， 可表达 为特殊函数的闭解形式， 从而使三重积分的计算无需数值积分， 直接通过函数査表法 即可实现。 此方法虽可大幅降低计算复杂度， 但由于存在无损和大色散约束， 计算精 度有限并且无法应用于色散管理链路；同时高斯脉冲的假设进一步限制了此方法的应 用范围。
(2 ) 有损大色散链路的一重积分： 此方法在色散足够大的假设下， 利用静态相 位（ Stationary Phase )近似可计算对时间的二重积分，使原三重积分化简为一重积分。 此方法不对链路损耗和脉冲波形进行约束，但得到的一重积分通常无法进一步表达为 闭解形式， 从而仍需要利用数值积分计算非线性失真。
或者， 例如增强的常规微扰法 （ERP) 与乘性微扰模型： 由于常规微扰法只考虑 一阶微扰， 故其通常只适用于发射功率很小的情况。 为了进一步增加在较大功率水平 下的非线性失真估计精度， 基于外推的高阶微扰理论得到了相应的发展。增强的常规 微扰法是常规微扰法的高阶修正， 通过在常规一阶微扰中直观引入相移因子， 可以显 著改善微扰法在较大功率下的精确度。 乘性微扰模型 [9]是另一种考虑高阶微扰的近似 解法， 基本思想是把加性微扰修正为乘性微扰， 从而近似得到常规微扰法的高阶微扰 项， 增加在较大功率下的精确度。
或者， 例如功率谱密度 （PSD ) 分析： 由于计算非线性失真波形的复杂度较高， 而评价传输系统性能通常只需要了解非线性噪声的统计特性，故目前针对准线性传输 系统比较通用的分析方法是把非线性失真视为噪声，针对噪声的功率谱密度进行分析。 这种分析方法的优点在于可以简化二重积分的计算并且适用于对色散管理链路的分 析， 但通常假设发送信号频谱之间没有相关性并且满足高斯假设， 这种约束成为降低 谱密度分析精确度的主要因素。
图 1为典型的光通信系统示意图， 其中， 发射机发射的信号经过传输链路中不同 的器件 （光纤、 光放大器、 色散补偿光纤等） 到达接收机。 在图 1所示的系统中， 为 了在发射端对输入的脉冲信号进行补偿，可以在实现本发明的过程中首先建立信道内 非线性模型， 以下对信道内非线性的基本模型进行简要说明。偏振复用型光纤传输系 统在慢包络、 随机偏振旋转的假设下， 可以抽象为 Manakov方程：
Figure imgf000009_0001
(1) 其中， M t,Z)和 Mf t,Z)分别为信号在 H和 偏振态上的电场分量， α(ζ)、 β2 (ζ) 与 γ(ζ)分别表示光纤链路中的衰减系数、色散系数和非线性系数沿传输距离的分布。
发射机产生的信号往往由光脉冲组成， 可以写成式 （2) 的形式
■k k
(2) 其中， ^^和 分别为 H和 扁振态上的第 个脉冲的信息符号， r为脉冲间 隔， g(0为每个脉冲的波形。
将输入信号 （2) 带入 （1) 式， 在准线性近似下， 利用一阶常规微扰解法， 可以 得到距离 L处非线性薛定谔方程的解析解：
Figure imgf000009_0002
= kT ,z = L)
uH{t = kT,z = Q) + j-
Figure imgf000009_0003
m,n,z = L
Figure imgf000009_0004
(3) 式 （3) 说明在接收机端第 个脉冲采样时刻的微扰量是多个相互作用项的加权 和， 每一项为发射脉冲信息符号的三项积与相应加权系数的乘积。其中加权系数是唯 一决定非线性微扰的参数， 其与脉冲形状、 相互作用脉冲时刻 （ ， n) 及链路参数 都有关。 当此加权系数可以用解析闭解 （初等函数或可通过査表法计算的特殊函数） 表达时， 非线性失真 （Δ.Η、 Auv) 也可基于此闭解得到。 但在不考虑任何近似下， 系数只可表示为三重积分形式：
. 、 r : -/iC) ,r广 广 d —― i h
C\ ( 4 ) 其中， C^ ^ ¾'为积累色散， J(C为功率加权的色散分布函数， 其只决 定于传输链路参数：
Figure imgf000010_0001
( 5 ) 其中， 为第 个光纤跨段的损耗 /增益函数。
图 2是无色散补偿情况下的功率加权色散分布函数的一示意图，图 3是 95%色散 补偿情况下的功率加权色散分布函数的一示意图。 其中， 如图 2和 3所示， 具有 10 个光纤跨段， 每段跨段长度 100km, β2(ζ) ^ 2L6p^/kn a(z) - ί)扁/ km。
以下将对在损耗 /增益条件下， 如何获得高精度的加权系数进行详细的说明。 实施例 1
本发明实施例提供一种非线性加权系数的计算装置，图 4是本发明实施例的非线 性加权系数的计算装置的一构成示意图。如图 4所示， 该非线性加权系数的计算装置 400包括： 近似处理单元 401和系数计算单元 402。
其中， 近似处理单元 401 利用有理函数对信道内非线性失真估计中的链路损耗 / 增益函数进行近似处理； 系数计算单元 402通过近似后的链路损耗 /增益函数以及大 色散近似对非线性失真估计中的非线性加权系数进行计算，以获得非线性加权系数的 解析闭解。
在本实施例中， 可以通过有理函数链对路损耗 /增益函数进行近似处理， 由此可 以使得如式 （4 ) 所示的非线性加权系数具有解析闭解的表达式， 因此计算出的加权 系数具有显著的精确度的改善。
图 5是本发明实施例的非线性加权系数的计算装置的另一构成示意图。如图 5所 示，该非线性加权系数的计算装置 500包括：近似处理单元 401和系数计算单元 402， 如上所述。
如图 5所示，该非线性加权系数的计算装置 500还可以包括：系数处理单元 503 ; 该系数处理单元 503 利用色散分布函数对非线性失真估计中的非线性加权系数进行 积分处理； 并且， 系数计算单元 402通过近似后的链路损耗 /增益函数以及大色散近 似对积分处理后的非线性加权系数进行计算。
在具体实施时， 可以使用系数处理单元 503对如式 （4) 所示的非线性加权系数 的三重积分进行处理， 从而更直观准确地表达该非加权系数。可以利用色散分布函数 对如式 （4) 所示的三重积分形式进一步积分， 来获得一重积分形式； 例如可以获得 如后所述的式（6)。 但本发明不限于此， 例如还可以采用其他任意脉冲形状， 获得其 他的一重积分形式。
以上说明了可以使用有理函数链对路损耗 /增益函数进行近似处理。 进一步地， 本发明还可以对多个光纤跨段分别计算非线性加权系数，并进行求和之后获得整个链 路的非线性加权系数。
图 6是本发明实施例的非线性加权系数的计算装置的另一构成示意图。如图 6所 示， 该非线性加权系数的计算装置 600包括： 近似处理单元 401、 系数计算单元 402 和系数处理单元 503， 如上所述。
如图 6所示， 非线性加权系数的计算装置 600还可以包括： 光纤划分单元 604和 系数求和单元 605。 其中， 光纤划分单元 604将整个传输链路的光纤划分为多个光纤 跨段；
对于每一个光纤跨段， 通过近似处理单元 401和系数计算单元 402， 或者近似处 理单元 401、 系数处理单元 503和系数计算单元 402， 来计算该光纤跨段对应的非线 性加权系数。
系数求和单元 605对分别获得的不同光纤跨段的非线性加权系数进行求和，以得 到整个传输链路的非线性加权系数的解析闭解。
在本实施例中， 近似处理单元 401还可以还用于使用高斯脉冲函数、 或者非归零 脉冲 （NRZ) 函数、 或者归零脉冲 （RZ) 函数、 或者内奎斯特 （Nyquist) 脉冲函数 等等来近似信道内非线性失真估计中的脉冲形状。但本发明不限于此， 例如还可以采 用其他的脉冲形状， 可以适用于其他任意脉冲形状。 以下仅以脉冲形状为高斯脉冲为 例， 对本发明进行详细说明。
例如， 在脉冲形状为高斯脉冲 = 2 ( τ为高斯脉冲脉宽因子）， 标 准光纤衰减 以及色散补偿率为 W (无色散补偿链路， W 的情况 下具体说明本发明。但本发明并不限于高斯脉冲以及标准光纤衰减链路等， 可以根据 实际情况确定具体的实施方式。 在具体实施时， 系数处理单元 503可以将上述条件代入式 （5) 中， 得到： JiiC) -: p[~- (C'/0 '- (i - - ί)£, /Ί/¾| 其中， 为每个光纤跨段的长度。
对于高斯脉冲， 系数处理单元 503可以通过式 （4) 对 tl与 t2先进行积分得到:
Figure imgf000012_0001
(6) 上式表示对于高斯脉冲， 加权系数可化简为一重积分， 此积分无解析闭解， 必须 通过进一步施加近似条件使其可积。
在具体实施时， 近似处理单元 401对于标准光纤衰减 G(. J exp卜 可通过 有理函数对其近似， 对于指数型衰减函数， 可以用如下有理分式对其进行逼近：
G ™ i?xpi'、、、 :》 ¾ . 」 " i:— ：
、、 'V、、、— (7) 其中， N为衰减控制因子； 为光纤衰减系数； i 为光纤跨段指标； 为在第 i 段光纤内的传输距离。
值得注意的是，以上仅以指数型衰减函数为例，采用上述有理函数进行近似处理。 但本发明不限于此， 对于其他形式的函数可以采用其他的有理函数的形式， 可以根据 实际情况确定具体的实施方式。对于脉冲形状， 也不仅限于高斯脉冲或上面所举出的 脉冲例子， 本发明可以适用于其他任意脉冲形状。
图 7是本发明实施例的近似衰减函数的一示意图。如图 7所示， 示出了近似函数 在第二个光纤跨段（每段跨段长度 100km， α(ζ} ^(} Ββηύ逼近指数衰减函数的趋 势。 如图 7所示， 当 Ν足够大时， 近似函数可准确逼近指数衰减函数。
在具体实施时， 系数计算单元 402可以把 （7) 式代入 （6) 式， 并引入大色散近 似 （C':» ）进一步对积分进行计算。
系数求和单元 605可以对分别获得的不同光纤跨段的非线性加权系数进行求和， 得到加权系数的解析闭解： ， ^^ ".;.； ■、 ■' Γ(】… ^..iAi^"- -；·,…" ····"········"··；··；■!} - Γ: I - k. jAi-^ "- -- :ν)?
\ 、- ί /、 ^ "i
(8) 其中， 6i = -iV7a -f (ί - - η)1 4 = ¾ ¾ = h, A, Γ(·, .)为不 完全伽马函数。 上式 （8) 即为有损链路非线性加权系数的解析闭解表达式。 在本实施例中， 从传输链路的功率加权色散分布函数 J(e)出发， 对不同光纤跨段 分别计算， 从而可以使非线性加权系数的计算不仅适用于无色散补偿链路， 也适用于 色散管理链路。
对于链路损耗 /增益函数的近似， 本发明提出利用有理函数进行近似逼近， 从而 使积分表达式（6)具有解析闭解的表达形式。对于实际的标准衰减链路，利用式（8) 计算所得的加权系数相对于现有技术中的方法具有显著的精确度改善。
值得注意的是， 本发明并不局限应用于标准衰减链路， 同时还可应用于具有指数 增益或其他形式衰减 /增益函数的链路中。 对于其他脉冲形状的兼容性和高精确度也 是本发明的显著优势之一。
由上述实施例可知， 利用有理函数对链路损耗 /增益函数进行近似， 从而使非线 性加权系数具有解析闭解的表达形式； 可以获得高精度的加权系数， 从而在有损情况 下对非线性失真进行高精度估计。
此外，将整个传输链路的光纤划分为多个光纤跨段并对不同光纤跨段分别计算非 线性加权系数， 从而可以使非线性加权系数的计算不仅适用于无色散补偿链路， 也适 用于色散管理链路。 实施例 2
本发明实施例提供一种非线性加权系数的计算方法，对应于实施例 1的非线性加 权系数的计算装置， 相同的内容不再赘述。
图 8是本发明实施例的非线性加权系数的计算方法的一流程示意图，如图 8所示， 该非线性加权系数的计算方法包括：
步骤 801，利用有理函数对非线性失真估计中的链路损耗 /增益函数进行近似处理; 步骤 802，通过近似后的链路损耗 /增益函数以及大色散近似对非线性失真估计中 的非线性加权系数进行处理。
图 9是本发明实施例的非线性加权系数的计算方法的另一流程示意图，如图 9所 示， 该非线性加权系数的计算方法包括：
步骤 901，利用有理函数对非线性失真估计中的链路损耗 /增益函数进行近似处理; 步骤 902， 利用色散分布函数对非线性失真估计中的非线性加权系数进行积分处 理；
步骤 903， 通过近似后的链路损耗 /增益函数以及大色散近似， 对非线性失真估计 中的积分处理后的非线性加权系数进行计算， 以获得非线性加权系数的解析闭解。
以上说明了可以使用有理函数链对路损耗 /增益函数进行近似处理。 进一步地， 本发明还可以对多个光纤跨段分别计算非线性加权系数，并进行求和之后获得整个链 路的非线性加权系数。
图 10是本发明实施例的非线性加权系数的计算方法的另一流程示意图， 如图 10 所示， 该非线性加权系数的计算方法包括：
步骤 1001， 将整个传输链路的光纤划分为多个光纤跨段。
对于每一个光纤跨段， 执行如下步骤 1002至步骤 1004。
步骤 1002， 利用有理函数对非线性失真估计中的链路损耗 /增益函数进行近似处 理；
步骤 1003， 利用色散分布函数对非线性失真估计中的非线性加权系数进行积分 处理；
步骤 1004， 通过近似后的链路损耗 /增益函数以及大色散近似， 对非线性失真估 计中的积分处理后的非线性加权系数进行计算。
在分别获得多个不同光纤跨段的非线性加权系数之后， 执行如下步骤 1005。 步骤 1005， 对分别获得的多个不同光纤跨段的非线性加权系数进行求和， 以得 到整个传输链路的非线性加权系数的解析闭解。
由上述实施例可知， 利用有理函数对链路损耗 /增益函数进行近似， 从而使非线 性加权系数具有解析闭解的表达形式； 可以获得高精度的加权系数， 从而在有损情况 下对非线性失真进行高精度估计。
此外，将整个传输链路的光纤划分为多个光纤跨段并对不同光纤跨段分别计算非 线性加权系数， 从而可以使非线性加权系数的计算不仅适用于无色散补偿链路， 也适 用于色散管理链路。
实施例 3
本发明实施例提供一种非线性失真的预补偿装置以及方法。 图 11是本发明实施 例的非线性失真的预补偿装置的一构成示意图， 如图 11所示， 非线性失真的预补偿 装置 1100包括： 非线性加权系数的计算装置 1101、微扰项计算单元 1102以及预补偿 单元 1103。
其中， 非线性加权系数的计算装置 1101可以如实施例 1所示。 微扰项计算单元 1102利用由该非线性加权系数的计算装置 1101获得的非线性加权系数计算叠加在发 送信号上的矢量微扰项； 预补偿单元 1103利用矢量微扰项预补偿发送信号， 以获得 输入到发射机的预失真信号。
在本实施例中， 预补偿方法的基本思想是发射经过特定形变的信号， 这些信号在 经过光纤传输的非线性效应后， 在接收端得到理想的无损信号。 值得注意的是， 本实 施例中假定信道的线性损伤已经通过其他方法进行补偿。
在本实施例中， 利用以上非线性加权系数的计算方法， 可以更准确地计算叠加在 发送信号上的矢量微扰，从而可以利用在发射机预先将矢量微扰扣除的办法实现对非 线性失真的预补偿。 预补偿得到的信息序列按如下方法计算：
(9) 其中， A'H k， A'v k分别为预补偿后两个偏振态在 k时刻的符号信息， AH k， Av k分 别为两个偏振态在 k时刻的原始符号信息， £为预补偿调整常数。 （9) 式可以理解为 预补偿后的信息序列等于原始信息序列减去非线性效应在距离 L处产生的矢量微扰 项。 其中加权系数 C¾e/(m., n， z - )的计算可以按实施例 1或 2进行。
图 12是本发明实施例的非线性失真的预补偿方法的一流程示意图。如图 12所示， 非线性失真的预补偿方法包括：
步骤 1201， 计算各项的非线性加权系数；
在具体实施时， 对于如式 （9) 所示的信号， 可以利用实施例 1或 2所述的非线 性加权系数的计算方法或装置， 计算每一项的非线性加权系数。
步骤 1202， 计算当前时刻采样点的矢量微扰项。
步骤 1203， 计算当前时刻采样点的预补偿波形。
步骤 1204， 对原始信息序列进行预补偿， 以获得输入到发射机的预失真波形。 由上述实施例可知， 利用以上非线性加权系数的计算方法进行预补偿， 可以更准 确地计算叠加在发送信号上的矢量微扰，从而可以利用在发射机预先将矢量微扰扣除 的办法实现对非线性失真的预补偿。 实施例 4
本发明实施例提供一种非线性失真的后补偿装置， 图 13是本发明实施例的非线 性失真的后补偿装置的一构成示意图， 如图 13所示， 非线性失真的后补偿装置 1300 包括： 非线性加权系数的计算装置 1301、 微扰项计算单元 1302以及补偿单元 1303。
其中， 非线性加权系数的计算装置 1301可以如实施例 1所示。 微扰项计算单元 1302利用由非线性加权系数的计算装置 1301获得的非线性加权系数计算叠加在发送 信号上的矢量微扰项； 补偿单元 1303利用该矢量微扰项对接收到的信号进行补偿。
在本实施例中， 可以利用以上实施例 1或 2的非线性加权系数的计算方法， 计算 出叠加在理想发送信号上的矢量微扰。在无噪声的理想链路中， 计算所得的非线性微 扰可以较准确地反映接收机端相应采样点的失真大小，故在接收机端可以将这部分非 线性微扰直接扣除， 得到补偿后的信息序列， 由下式描述：
^ - ^f ~ ί∑ί¾^ -& ( ；責 + ' - r z - L)
:::: ""
Figure imgf000016_0001
:' (.m？ n、 z ::::
( 10) 其中， R'H k， R'v k分别为接收机补偿后两个偏振态在 k时刻的采样点信息， RH k， RV k分别为接收机在补偿其他损伤后在 k时刻输入到后补偿装置的采样点信息。
图 14是本发明实施例的非线性失真的后补偿方法的一流程示意图。如图 14所示， 非线性失真的后补偿方法包括：
步骤 1401， 计算各项的非线性加权系数；
在具体实施时， 对于如式（10)所示的信号， 可以利用实施例 1或 2所述的非线 性加权系数的计算方法或装置， 计算每一项的非线性加权系数。
步骤 1402， 计算当前时刻采样点的矢量微扰项。
步骤 1403， 计算当前时刻采样点的失真波形。
步骤 1404， 对接收机接收到的采样点波形进行补偿， 以获得补偿后的采样点波 形。 由上述实施例可知， 利用以上非线性加权系数的计算方法进行补偿， 可以更准确 地计算叠加在发送信号上的矢量微扰，从而可以利用在接收机将矢量微扰扣除的办法 实现对非线性失真的补偿。
本发明以上的装置和方法可以由硬件实现， 也可以由硬件结合软件实现。本发明 涉及这样的计算机可读程序， 当该程序被逻辑部件所执行时， 能够使该逻辑部件实现 上文所述的装置或构成部件， 或使该逻辑部件实现上文所述的各种方法或步骤。本发 明还涉及用于存储以上程序的存储介质， 如硬盘、 磁盘、 光盘、 DVD、 flash存储器 等。 以上结合具体的实施方式对本发明进行了描述， 但本领域技术人员应该清楚， 这 些描述都是示例性的， 并不是对本发明保护范围的限制。本领域技术人员可以根据本 发明的精神和原理对本发明做出各种变型和修改，这些变型和修改也在本发明的范围 内。
关于包括以上实施例的实施方式， 还公开下述的附记：
(附记 1 ) 一种非线性加权系数的计算装置， 所述非线性加权系数的计算装置包 括：
近似处理单元， 利用有理函数对信道内非线性失真估计中的链路损耗 /增益函数 进行近似处理；
系数计算单元， 通过近似后的所述链路损耗 /增益函数以及大色散近似对非线性 失真估计中的非线性加权系数进行计算， 以获得所述非线性加权系数的解析闭解。
(附记 2) 根据附记 1所述的非线性加权系数的计算装置， 其中， 所述非线性加 权系数的计算装置还包括：
系数处理单元，利用色散分布函数对非线性失真估计中的非线性加权系数进行积 分处理；
并且， 所述系数计算单元通过近似后的所述链路损耗 /增益函数以及大色散近似 对积分处理后的非线性加权系数进行计算。
(附记 3 ) 根据附记 1或 2所述的非线性加权系数的计算装置， 其中， 所述非线 性加权系数的计算装置还包括：
光纤划分单元， 将整个传输链路的光纤划分为多个光纤跨段；
系数求和单元， 对分别获得的不同光纤跨段的非线性加权系数进行求和， 以得到 整个传输链路的非线性加权系数的解析闭解。
(附记 4) 根据附记 1或 2所述的非线性加权系数的计算装置， 其中， 所述近似 处理单元还用于使用高斯脉冲函数、 或者非归零脉冲函数、 或者归零脉冲函数、 或者 内奎斯特脉冲函数来近似信道内非线性失真估计中的脉冲形状。
(附记 5 ) 根据附记 3所述的非线性加权系数的计算装置， 其中， 所述近似处理 单元采用如下公式对链路损耗 /增益函数进行近似处理，
Figure imgf000018_0001
其中， G^)为所述链路损耗 /增益函数， N为衰减控制因子， "为光纤的衰减系数，
Z!为在第 段光纤内的传输距离。
(附记 6) —种非线性加权系数的计算方法， 所述非线性加权系数的计算方法包 括：
利用有理函数对非线性失真估计中的链路损耗 /增益函数进行近似处理； 通过近似后的所述链路损耗 /增益函数以及大色散近似对非线性失真估计中的非 线性加权系数进行处理， 以获得所述非线性加权系数的解析闭解。
(附记 7) 根据附记 6所述的非线性加权系数的计算方法， 其中， 所述非线性加 权系数的计算方法还包括：
利用色散分布函数对非线性失真估计中的非线性加权系数进行积分处理； 并且， 通过近似后的所述链路损耗 /增益函数以及大色散近似对积分处理后的非 线性加权系数进行计算。
(附记 8) 根据附记 6或 7所述的非线性加权系数的计算方法， 其中， 所述非线 性加权系数的计算方法还包括：
将整个传输链路的光纤划分为多个光纤跨段；
对分别获得的多个不同光纤跨段的非线性加权系数进行求和， 以得到整个传输链 路的非线性加权系数的解析闭解。
(附记 9) 根据附记 6或 7所述的非线性加权系数的计算方法， 其中， 使用高斯 脉冲函数、 或者非归零脉冲函数、 或者归零脉冲函数、 或者内奎斯特脉冲函数来近似 信道内非线性失真估计中的脉冲形状。
(附记 10) 根据附记 8所述的非线性加权系数的计算方法， 其中， 采用如下公 式对链路损耗 /增益函数进行近似处理，
Figure imgf000019_0001
其中， Gfe)为所述链路损耗 /增益函数， N为衰减控制因子， "为光纤的衰减系数， 为在第 i段光纤内的传输距离。
(附记 11 ) 一种非线性失真的预补偿装置， 其中， 所述预补偿装置包括： 根据附记 1至 5任一项所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
预补偿单元， 利用所述矢量微扰项预补偿所述发送信号， 以获得输入到发射机的 预失真信号。
(附记 12 ) —种非线性失真的预补偿方法， 其中， 所述预补偿方法包括： 根据附记 6至 10任一项所述的非线性加权系数的计算步骤；
利用由所述非线性加权系数的计算步骤获得的非线性加权系数计算叠加在发送 信号上的矢量微扰项；
利用所述矢量微扰项预补偿所述发送信号， 以获得输入到发射机的预失真信号。 (附记 13 ) —种非线性失真的后补偿装置， 其中， 所述补偿装置包括： 根据权利要求 1至 5任一项所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
补偿单元， 利用所述矢量微扰项对接收到的信号进行补偿。
(附记 14) 一种非线性失真的后补偿方法， 其中， 所述补偿方法包括： 根据权利要求 6至 10任一项所述的非线性加权系数的计算步骤；
利用由所述非线性加权系数的计算步骤获得的非线性加权系数计算叠加在发送 信号上的矢量微扰项；
利用所述矢量微扰项对接收到的信号进行补偿。
(附记 15 ) —种计算机可读程序， 其中当在发射机中执行所述程序时， 所述程 序使得计算机在所述发射机中执行如附记 12所述的非线性失真的预补偿方法。
(附记 16) —种存储有计算机可读程序的存储介质， 其中所述计算机可读程序 使得计算机在发射机中执行如附记 12所述的非线性失真的预补偿方法。
(附记 17) —种计算机可读程序， 其中当在接收机中执行所述程序时， 所述程 序使得计算机在所述接收机中执行如附记 14所述的非线性失真的后补偿方法。
(附记 18) —种存储有计算机可读程序的存储介质， 其中所述计算机可读程序 使得计算机在接收机中执行如附记 14所述的非线性失真的后补偿方法。

Claims

权利要求书
1、 一种非线性加权系数的计算装置， 所述非线性加权系数的计算装置包括： 近似处理单元， 利用有理函数对信道内非线性失真估计中的链路损耗 /增益函数 进行近似处理；
系数计算单元， 通过近似后的所述链路损耗 /增益函数以及大色散近似对非线性 失真估计中的非线性加权系数进行计算。
2、 根据权利要求 1所述的非线性加权系数的计算装置， 其中， 所述非线性加权 系数的计算装置还包括：
系数处理单元，利用色散分布函数对非线性失真估计中的非线性加权系数进行积 分处理；
并且， 所述系数计算单元通过近似后的所述链路损耗 /增益函数以及大色散近似 对积分处理后的非线性加权系数进行计算。
3、 根据权利要求 1所述的非线性加权系数的计算装置， 其中， 所述非线性加权 系数的计算装置还包括：
光纤划分单元， 将整个传输链路的光纤划分为多个光纤跨段；
系数求和单元， 对分别获得的不同光纤跨段的非线性加权系数进行求和， 以得到 整个传输链路的非线性加权系数的解析闭解。
4、 根据权利要求 1所述的非线性加权系数的计算装置， 其中， 所述近似处理单 元还用于使用高斯脉冲函数、 或者非归零脉冲函数、 或者归零脉冲函数、 或者内奎斯 特脉冲函数来近似信道内非线性失真估计中的脉冲形状。
5、 根据权利要求 3所述的非线性加权系数的计算装置， 其中， 所述近似处理单 元采用如下公式对链路损耗 /增益函数进行近似处理，
Figure imgf000021_0001
其中， Gfe)为所述链路损耗 /增益函数， N为衰减控制因子， "为光纤的衰减系数， 为在第 段光纤内的传输距离。
6、 一种非线性失真的预补偿装置， 其中， 所述预补偿装置包括：
根据权利要求 1所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
预补偿单元， 利用所述矢量微扰项预补偿所述发送信号， 以获得输入到发射机的 预失真信号。
7、 一种非线性失真的后补偿装置， 其中， 所述后补偿装置包括：
根据权利要求 1所述的非线性加权系数的计算装置； 以及
微扰项计算单元，利用由所述非线性加权系数的计算装置获得的非线性加权系数 计算叠加在发送信号上的矢量微扰项；
补偿单元， 利用所述矢量微扰项对接收到的信号进行补偿。
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Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2804334A1 (en) * 2013-05-13 2014-11-19 Xieon Networks S.à.r.l. Method, device and communication system for reducing optical transmission impairments
CN106161125B (zh) * 2015-03-31 2019-05-17 富士通株式会社 非线性特性的估计装置及方法
JP6759742B2 (ja) * 2016-06-16 2020-09-23 富士通株式会社 受信装置及び設定方法
US10218765B1 (en) * 2016-09-21 2019-02-26 Cisco Technology, Inc. Content-independent evaluation of streaming media based on packet transmission performance
WO2018083522A1 (en) * 2016-11-03 2018-05-11 Nokia Technologies Oy Beamforming
US10887022B2 (en) * 2017-06-15 2021-01-05 Nokia Of America Corporation Backward propagation with compensation of some nonlinear effects of polarization mode dispersion
JP7069578B2 (ja) * 2017-07-05 2022-05-18 富士通株式会社 光伝送装置及び方法
US10236982B1 (en) * 2017-12-21 2019-03-19 Ciena Corporation Fiber parameter identification
US10536221B2 (en) * 2018-06-14 2020-01-14 Juniper Networks, Inc. Methods and apparatus for detecting and compensating bandwidth limitation and modulation nonlinearity of a coherent optical transponder
US10985951B2 (en) 2019-03-15 2021-04-20 The Research Foundation for the State University Integrating Volterra series model and deep neural networks to equalize nonlinear power amplifiers
CN111726307B (zh) * 2020-06-11 2022-02-11 河海大学 信道冲激响应双伽马函数ls拟合系数迭代初值求解方法及系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102332956A (zh) * 2011-08-23 2012-01-25 天津大学 一种宽带光源的色散补偿方法
CN102420660A (zh) * 2010-09-28 2012-04-18 富士通株式会社 非线性补偿装置和发射机
CN102655433A (zh) * 2011-03-04 2012-09-05 富士通株式会社 非线性损伤补偿方法和装置
CN103023828A (zh) * 2011-09-26 2013-04-03 富士通株式会社 非线性估计装置、方法和接收机

Family Cites Families (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998023068A1 (fr) * 1996-11-19 1998-05-28 Matsushita Electric Industrial Co., Ltd. Emetteur
US6690739B1 (en) * 2000-01-14 2004-02-10 Shou Yee Mui Method for intersymbol interference compensation
US6441950B1 (en) * 2000-11-03 2002-08-27 Onetta, Inc. Distributed raman amplifier systems with transient control
US6633712B2 (en) * 2001-03-16 2003-10-14 Sowilo Networks, Inc. Method and system for dispersion maps and enhanced distributed gain effect in long haul telecommunications
US6735264B2 (en) * 2001-08-31 2004-05-11 Rainmaker Technologies, Inc. Compensation for non-linear distortion in a modem receiver
US6621626B1 (en) * 2001-12-05 2003-09-16 Cisco Technology, Inc. Modular optical amplifier structure for highly dense interleaved WDM systems
US20040208525A1 (en) * 2002-01-29 2004-10-21 Nortel Networks Limited SRS-immune optical performance monitoring
DE102004018166A1 (de) * 2003-05-08 2004-12-16 Siemens Ag Verfahren zur Preemphase eines optischen Multiplexsignals
US7558479B1 (en) * 2004-04-15 2009-07-07 Nortel Networks Limited Analysis and control of optical communications systems
US7869680B2 (en) * 2004-07-02 2011-01-11 Olambda, Inc. Nonlinearity compensation in a fiber optic communications system
US7623790B2 (en) * 2005-09-24 2009-11-24 Alcatel-Lucent Usa Inc. Signal identification method
US7720136B2 (en) * 2006-12-26 2010-05-18 Provigent Ltd Adaptive coding and modulation based on link performance prediction
JP5147582B2 (ja) * 2008-07-18 2013-02-20 日本電信電話株式会社 受信装置、補償演算回路、および受信方法
US8437643B2 (en) * 2009-03-20 2013-05-07 University Of Central Florida Research Foundation, Inc. Compensation of transmission impairments in polarization multiplexed systems
US9209829B2 (en) * 2009-06-26 2015-12-08 Syntropy Systems, Llc Sampling/quantization converters
US8943112B2 (en) * 2009-06-26 2015-01-27 Syntropy Systems, Llc Sampling/quantization converters
US8386216B1 (en) * 2009-12-17 2013-02-26 Cadence Design Systems, Inc. Method and system for adaptive modeling and simulation of lossy transmission lines
US8737490B1 (en) * 2010-08-20 2014-05-27 Cadence Design Systems, Inc. Analog-to-digital converter based decision feedback equalization
CN102386968B (zh) * 2010-08-31 2015-07-15 富士通株式会社 自相位调制噪声计算装置、消除装置和光相干接收机
US8934786B2 (en) * 2011-09-16 2015-01-13 Alcatel Lucent Communication through pre-dispersion-compensated phase-conjugated optical variants
CN103023570B (zh) * 2011-09-26 2016-03-30 富士通株式会社 非线性补偿装置、方法和发射机
US8948253B2 (en) * 2011-12-15 2015-02-03 Flextronics Ap, Llc Networked image/video processing system
CN103259597B (zh) * 2012-02-20 2016-12-07 富士通株式会社 非线性补偿装置、方法和发射机
WO2014019631A1 (en) * 2012-08-03 2014-02-06 Telefonaktiebolaget L M Ericsson (Publ) Method of optimizing optical signal quality in an optical communications link, optical network element and optical communications link
CN104253650B (zh) * 2013-06-27 2016-12-28 富士通株式会社 信道内非线性损伤的估计装置及方法
US9438369B2 (en) * 2014-05-19 2016-09-06 Ciena Corporation Margin-based optimization systems and methods in optical networks for capacity boosting

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102420660A (zh) * 2010-09-28 2012-04-18 富士通株式会社 非线性补偿装置和发射机
CN102655433A (zh) * 2011-03-04 2012-09-05 富士通株式会社 非线性损伤补偿方法和装置
CN102332956A (zh) * 2011-08-23 2012-01-25 天津大学 一种宽带光源的色散补偿方法
CN103023828A (zh) * 2011-09-26 2013-04-03 富士通株式会社 非线性估计装置、方法和接收机

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