The present disclosure relates to compensating for optical transmission impairments in the electronic or software domain.
Channel impairments in transmission systems result in signal degradation and thus limit the carrying capacity of these systems. In optical transmission systems, some of these impairments are linear (e.g., fiber chromatic dispersion or CD) and some are non-linear (e.g., cross-phase modulation and four-wave mixing caused by the Kerr effect). To minimize the effect of impairments, transmission systems may include various types of compensation systems or devices. A signal can be modified before, or as part of, transmission to account for the effect of impairment (a technique known as pre-compensation). Conversely, knowledge about an impairment can be used to modify a received signal to compensate for the impairment (a technique known as post-compensation). Such compensation systems or devices can be implemented in the optical domain or in the electrical/electronic domain.
Many aspects of the disclosure can be better understood with reference to the following drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure.
The inventive techniques described herein compensate for optical distortion, using backward propagation in the electrical domain. Specifically, the receiver uses digital backward propagation to convert the received optical signal into an estimate of the transmitted signal.
Optical signal 130 travels through an optical channel 140, which includes optical fiber 150. Optical fiber 150 introduces various types of distortion, resulting in a distorted optical signal 160. Distorted optical signal 160 is provided to an optical detector 170, which converts the distorted optical signal to a signal in the electrical domain. Distorted electrical signal 180 is processed in the electrical (digital) domain by impairment compensation logic 190 to remove the distortion produced in the optical (physical) domain. Impairment compensation logic 190 operates by modeling the characteristics of optical fiber 150 in a virtual optical fiber 185. The output of impairment compensation logic 190 is a compensated electrical signal 195. Carried within compensated electrical signal 195 is data which is a replica (or near replica) of the originally transmitted data.
The model embodied in impairment compensation logic 190 accounts for, and reverses the effect of, various impairments introduced by optical fiber 150. As will be discussed below, different types of impairments, or combinations thereof, can be accounted for by using different models. For example, one model discussed herein compensates for fiber dispersion, intra-channel impairments (e.g., self-phase modulation or SPM), and inter-channel impairments (e.g., cross-phase modulation and four-wave mixing). This model is referred to herein as “total” or “universal” compensation. Another model discussed herein compensates for fiber dispersion, intra-channel impairments, and cross-phase modulation (XPM) while ignoring four-wave mixing (FWM). Yet another model is contemplated which fully compensates for fiber dispersion, intra-channel impairments, and cross-phase modulation, while partially compensating for four-wave mixing. These two models are referred herein as “selective non-linear” compensation.
The NLSE includes parameters which correspond to the characteristics of the physical optical fiber (150 in
The total or universal compensation model takes into account the total electrical field to compensate for all forms of fiber impairment: dispersion (second and third order); self-phase modulation; cross-phase modulation; and four-wave mixing. This model solves a form of NLSE known as total NLSE (T-NSLE) which governs the backward propagation of the total electrical field. Backward T-NLSE can be written as
where, γ is the nonlinear parameter, βj represents the j th-order chromatic dispersion parameter, α is the absorption coefficient, and t is the retarded time. Other impairments including scattering (Raman, Rayleigh and Brillouin scattering) can also be included in the T-NLSE. Likewise, polarization impairments such as nonlinear polarization rotation can be included. Here, two coupled-NLSE equations are used to describe backward propagation. Polarization-related distortions can be corrected using a z-reversed two coupled-NLSE equations provided that signal state of polarization is monitored in some points of the transmission link.
The total compensation model discussed above accounts for intra-channel non-linear impairments, inter-channel non-linear impairments, and linear transmission impairments related to dispersion. Selective non-linear compensation accounts for particular types of non-linear impairments, while ignoring other types of non-linear impairments. The effects of four-wave-mixing (FWM) can be omitted by simplifying the total NLSE described above to produce a system of coupled equations referred to herein as “coupled NLSE” (C-NLSE). The following techniques are used to derive C-NLSE from T-NLSE.
First, the full optical field can be expressed as E=ΣÊm exp(imΔωt), where Êm is the mth WDM channel envelope and Δω is the inter-channel frequency spacing. Next, the expression for E is introduced into Eq. 1, the |E|2 term is expanded, and the terms related to FWM are neglected. The result is the set of coupled equations (C-NLSE):
where, K1m=β2m2Δω−β3m2Δω2/2, K2m=β2/2+β3mΔω/2, K3m=−β3/6. C-NLSE (Eq. 2) describes the backward propagation of fiber channels where only dispersion, self-phase modulation and cross-phase modulation are compensated (i.e., FWM is not compensated for).
In yet another model, the NLSE can be generalized to describe spatial and temporal evolution of images using the paraxial (3D+1)-NLSE below:
where k is the propagation constant.
The model described above for the time-domain signals can be used to reverse distortions for static images in which case ∂/∂t=0, and
In so doing, the effects of nonlinearity and diffraction described by the −iγ|E|2E and
terms can be compensated.
Furthermore, Eq. 3 can also be solved using the split-step method so that the effects of dispersion, diffraction and nonlinearity can be compensated for transmission of time-varying images (e.g., videos) in dispersive media.
Some embodiments of the virtual fiber model solve the NLSE using the split-step Fourier method (SSFM). The steps themselves are specific to the equation being solved, and will be discussed in more detail later. The dispersive and nonlinear contributions to impairment are considered to be independent within a relatively short segment propagation. The backward propagation process is therefore broken into a series of iterations or steps, one for each segment within a span.
The dispersion, power, and exponential operators are given by D(x)=φ−1[Hφ(x)], P(x)=|x|2, and E(x)=exp(iγxh) where h is the step size. The transfer function H for fiber dispersion and absorption is given by
with ω being the angular frequency. It should be appreciated that dispersion operator 420 can be implemented in various ways, in either the frequency domain or the time domain (e.g., finite impulse response (FIR) filter, infinite impulse response (IIR) filter). This example performs two iterations (sub-steps) for the power averaging, but other numbers of sub-steps are also contemplated. Details of the split-step algorithm are shown in the block diagram of branch sub-unit 830 in
Receiver 725 mixes the signal in a 90° optical hybrid 730 with a set of phase-locked local oscillators 735. After demultiplexing (blocks 737), a set of balanced photo-detectors 740 obtains in-phase and quadrature components of each WDM channel. The I and Q components are provided to complex field reconstructor 745, which produces the complex form of the signal for each channel, E^1 . . . E^N(Ej=Ij+iQj).
After upsampling (block 750), spectral reconstructor 755 produces the signals E1 . . . En (Ej exp(imΔωt)), which are supplied to summator 760. As described earlier in connection with
After up-sampling (block 810), Nb sampling points are generated in parallel and output simultaneously in Nb branches. This sampling point generation occurs every period T, where Nb=M·FsIRp is the number of parallel processing branches, and T=1/Rp is the clock cycle in each branch. Some branches use one-symbol delay latches to obtain additional outputs for the parallel implementation of the following dispersion operator. This number of additional outputs is Nt−1, where Nt is the dispersion operator filter length or tap number (for the split-step FIR method case). Ak,i is the kth sampling point in the ith symbol and is processed in the kth branch (Ak,i represents the sampling points of the signal after module 760 in
Sampled data from all the branches are then sent into backward propagation logic 765, which is composed of a number of cascaded modules (820) which perform the split-step FIR method. Each module 820 performs one step in the backward propagation, compensating loss, dispersion and nonlinearity of a small segment of fiber. The number of modules equals to the step number. Each step contains Nb sub-units (830) to perform backward propagation for each branch respectively. Mk is the sub-unit in the kth branch of each step. Ak,i(n) is the output of the kth branch in the nth step and i is the symbol index.
Following the backward propagation, the per-channel outputs from backward propagation logic 765 are provided to respective filters (840) and phase estimator (850) units to recover the data. In some embodiments, the filter is a low-pass finite impulse response filter (FIR). In some embodiments, the signal in each channel is resampled to one sample per symbol before phase estimtation.
are the non-linear and linear operators respectively.
To improve the accuracy and thus increase the step size for the split-step FIR method, some embodiments use the trapezoidal rule to calculate the nonlinearity and approximate the integral by
An iterative procedure is followed, one that is initiated by replacing {circumflex over (N)}−1(z+h) by {circumflex over (N)}−(z), then using Eq. 5 to estimate E(z+h,i) which in turn is used to calculate the new value of {circumflex over (N)}−1(z+h). The example embodiment of
The FIR filter is implemented in a parallel configuration, which has multiple inputs instead of one input combined with a series of delay latches (p·T is the delay of the FIR filter, and q·T is the delay of inverse non-linear operator 2 (block 950)). Therefore, each branch sub-unit operates at a speed of Rp although the overall bandwidth is Nb·Rp. Since the FIR filters use multiple inputs, all the branches interface with adjacent ones. This is represented in
The additional outputs in branch sub-unit Nt−1 are used as the inputs of the FIR filters in the next step (performed by a different step module 810). Also, additional interfaces with adjacent branches are used in these Nt−1 sub-units. Additional outputs and modules required in some sub-units are indicated by the dashed lines in
Receiver 1025 mixes the signal in a 90° optical hybrid 1030 with a set of co-polarized free-running local oscillators 1035. Notably, phase locking on the LOs is not a requirement here since XPM is insensitive to the inter-channel relative phase. (This is in contrast to the total compensation WDM system of
In other embodiments (not shown), impairment compensation logic 190 and/or backward propagation logic 765/1065 is implemented in hardware, including, but not limited to, a programmable logic device (PLD), a programmable gate array (PGA), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a system on chip (SoC), and a system in package (SiP).
Impairment compensation logic 190, backward propagation logic 765/1065, or combinations thereof, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device. Such instruction execution systems include any processor-containing system, or other system that can fetch and execute instructions. In the context of this disclosure, a “computer-readable medium” can be any means that can contain or store the instructions for use by the instruction execution system. The computer readable medium can be, for example but not limited to, a system or that is based on electronic, magnetic, optical, electromagnetic, or semiconductor technology.
Specific examples of a computer-readable medium using electronic technology would include (but are not limited to) the following: random access memory (RAM); read-only memory (ROM); and erasable programmable read-only memory (EPROM or Flash memory). A specific example using magnetic technology includes (but is not limited to) a portable computer diskette. Specific examples using optical technology include (but are not limited to) compact disk (CD) and digital video disk (DVD).
The foregoing description has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. Obvious modifications or variations are possible in light of the above teachings. The implementations discussed, however, were chosen and described to illustrate the principles of the disclosure and its practical application to thereby enable one of ordinary skill in the art to utilize the disclosure in various implementations and with various modifications as are suited to the particular use contemplated. All such modifications and variation are within the scope of the disclosure as determined by the appended claims when interpreted in accordance with the breadth to which they are fairly and legally entitled.
This application claims priority to U.S. Provisional Application having Ser. No. 61/031,852 filed Feb. 27, 2008, and claims priority to U.S. Provisional Application having Ser. No. 61/097,731 filed Sep. 17, 2008, each of which is hereby incorporated by reference herein in its entirety.
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