The disclosure is generally related to optical communications systems and in particular to coherent optical receivers equipped with frequency-domain adaptive equalizers.
Next-generation long-haul, fiber-optic communications systems are being designed to operate at 100 gigabits per second over distances of 1,000 kilometers or more. Coherent optical receivers have been proposed as an alternative to conventional direct detection receivers for high-speed, fiber-optic systems because, among other reasons, they recover the phase of optical electric fields. When in-phase (I) and quadrature (Q) components of an optical signal are known, exact equalization of linear channel impairments is possible in principle and the effects of nonlinear impairments may be reduced.
Frequency-domain adaptive equalizers provide optimal linear channel compensation. The frequency taps of such an equalizer may be updated according to feedback from a slicer that makes symbol identification decisions. The difference between the slicer's output and input is used as an error signal to adjust equalizer taps. In quasi steady-state operation, an adaptive equalizer can run indefinitely with its taps being adjusted by small amounts to compensate for slowly changing channel conditions.
Starting an adaptive equalizer “blind” (i.e. with no channel knowledge), however, is problematic. The equalizer may be slow to converge to an optimal compensation estimate or it may not converge at all. It can get hung up on singularities. Therefore what is needed is a coherent optical receiver that has an adaptive equalizer initialization system. Such a system should allow a blind, adaptive equalizer to converge rapidly so that a high-speed fiber-optic link can be started or re-started in just a few milliseconds.
A coherent optical receiver with an adaptive equalizer initialization system is part of a fiber-optic communication link that is robust and quick to re-start. The equalizer compensates for channel impairments to maintain high symbol fidelity. Examples of channel impairments include optical fiber properties such as birefringence, chromatic dispersion, polarization mode dispersion and optical nonlinearities, as well as effects due to components such as reconfigurable optical add/drop multiplexers and optical amplifiers.
out=Hin
where in and out are the transmitted and received electric fields respectively and
represents the channel for orthogonal polarizations, x and y. in may be estimated at the receiver through the use of an equalizer represented by W:
in≈Wout
W is not (merely) H−1; rather W is an optimal compensation estimate that minimizes received symbol errors. W may be updated according to an equalizer update equation:
Wk+1T=WkT2λεkrkH
where μ is equalizer gain, ε is a symbol error term, and r is a received symbol. (T indicates transpose, H indicates hermitian conjugate, and k is an index.) An adaptive equalizer running in a coherent optical receiver is stable in the presence of perturbations. However, if the equalizer is started blind with no channel information, it may converge slowly or not at all.
The coherent optical receiver described below includes an initialization system for a frequency-domain adaptive equalizer. The initialization system is configured to cause the equalizer to converge rapidly. The system uses a short, repetitive sequence of known data (sent by the transmitter and compared to the same known data at the receiver) to generate initial equalizer frequency-domain taps.
Adaptive equalizer 220 is a frequency-domain, 2×2 equalizer. Its output is sent to carrier phase estimation (CPE) filter 245 and delay block 255. The outputs of CPE filter 245 and delay 255 are mixed and sent to slicer 250 which makes symbol decisions. Estimated symbols {tilde over (x)}i,k are input to the slicer; exact, “decided” symbols xD,k are its output, where subscript k is a time step index. The difference between the decided and estimated value for each symbol is fed back to equalizer 220 which uses that information according to an equalizer update equation such as the one discussed above.
In one embodiment, equalizer initialization system 240 contains a continuously running, fast Fourier transform (FFT) unit and a peak detector unit that act as a sequence start detector. The FFT and peak detector are both implemented in hardware as part of an application specific integrated circuit (ASIC). Receiver 200, as a whole, is implemented in a combination of hardware ASIC and software. For example, ADCs within block 205, initialization system 240, CD filters 230 and 235, equalizer 220, carrier phase estimation filter 245, and slicer 250 are parts of an ASIC, while other functions may be performed in hardware or software. In other embodiments, a sequence start detector in equalizer initialization system 240 may detect the arrival of an initialization sequence with a narrow bandwidth filter, a cross-correlator, a power threshold detector, a combination of any of these devices, or one or more of these devices in combination with a hardware FFT and peak detector unit.
Equalizer initialization system 240 is configured to cause a blind equalizer (e.g. 220) to converge to an optimal compensation estimate. The initialization system detects a known, short data sequence that is sent from time to time by a transmitter in an optical communications link. For example,
Details concerning how initialization system 240 uses a known, short data sequence (e.g. 320), and how such a data sequence may be constructed, are now discussed.
Equalizer initialization system 240 contains a continuously running, fast Fourier transform (FFT) unit and a peak detector unit. As described below, part of an initialization sequence (e.g. short data sequence 320) is a pure tone. The FFT and peak detector detect this pure tone and measure its frequency. (The Fourier transform of a pure tone is sharply peaked.) The difference between the measured tone frequency and its known value gives a frequency offset estimate that is sent to chromatic dispersion filters 230 and 235.
As described below, another part of an initialization sequence (e.g. short data sequence 320) is short, repetitive data with concentrated spectral components. This part of the sequence is used for estimating chromatic dispersion filter taps and providing an initial estimate for adaptive equalizer taps.
Chromatic dispersion (CD) filters 230 and 235 compensate chromatic dispersion introduced by physical properties of an optical fiber link. The frequency domain transfer function for an optical fiber has the form:
where CD is the cumulative chromatic dispersion of the fiber (e.g. in ps/nm), λ is the wavelength of the optical carrier (e.g. in nm), f is the frequency (e.g. in GHz) of the signal that represents transmitted data and c is the speed of light (e.g. in m/s). k is an adjustable chromatic dispersion parameter. CD filters 230 and 235 find and use optimum values of k to compensate for chromatic dispersion in an optical fiber transmission system.
Estimating chromatic dispersion filter taps is done by varying k to find the sharpest possible cross correlation between the CD filter input and output when the input is known. CD filters for each polarization may be adjusted separately since CD is polarization insensitive. As an example, the width of cross correlation function
rxe−jkf
varies depending on k. The optimum value of k for the CD filter is the one that yields the narrowest cross correlation peak. (The star symbol (*) represents cross correlation.) Here rx is the x-polarized received signal corresponding to known, x-polarized sequence tx. Examples of short sequences, tx and ty (where subscripts indicate polarization) include sequences 510, 515, 520 and 525 described below. Once an optimum value for k is found, taps for the CD filter provide a digital representation of the transfer function H(f)∝exp[−jkf2].
Transmitted signal tx usually does not remain in its original polarization because birefringence and polarization mode dispersion in a fiber alter the polarization of optical signals. Thus, the cross correlation rxe−jkf
Other methods for optimizing k are possible. For example, starting from the channel, G, as determined from a short initialization data sequence,
one may calculate G−1,
the matrix inverse of G. Next, one may determine which vector in G−1 (i.e. uxx, uxy, etc.) is most useful in further calculations by calculating energy content by summing squared magnitude over frequency taps, e.g.,
Denote the vector having the greatest energy, u0.
Now, to optimize k, form the expression,
A=|IFFT{u0e−jkf
and record the value of the maximum tap in A. Finally, sweep k until the value of the maximum tap in A is greatest.
A second use of the short, repetitive data sequences by the equalizer initialization system is to provide an initial estimate for adaptive equalizer taps after chromatic dispersion has been compensated. Equalizer 220, among other things, compensates for effects that mix x and y polarization frequency responses. Thus the channel as determined from a short initialization data sequence, and compensated for chromatic dispersion, may be written:
where k has been determined by one or more of the methods described above.
G−1, the matrix inverse of G, is now a “zero forcing” solution to compensate the channel. G−1 is not a very good estimate for W, but it is easy to calculate and provides a robust input to an adaptive equalizer. Thus, G−1, expressed in terms of frequency domain taps is loaded into the equalizer as an initial condition from which the equalizer quickly and reliably converges to an optimal channel compensation estimate. Robust initial conditions for the equalizer may also be determined by other methods including, for example, minimum mean squared error (MMSE) techniques.
We have seen that the initialization system performs three functions: frequency offset estimation, taps estimation for chromatic dispersion filters, and taps initialization for an adaptive equalizer. The system contains hardware FFT and peak detector units that sense a pure tone that marks the beginning of a known, short data sequence. The known data sequence is now described in more detail.
In the example of
The equalizer initialization system may use many different types of initialization data; however, the sequences described above have several distinct properties: they start with a pure tone; they are short; and, they concentrate energy in a few sharp spectral peaks. The pure tone is used for initialization data detection and frequency offset estimation. The short sequence length ensures that the initialization system does not add excessive overhead to the channel and therefore allows a short, known data sequence to be repeated often enough that an equalizer can be restarted quickly after a system interruption. The known data is designed so that its energy is concentrated in a few, sharp spectral peaks leading to better channel estimation for equalizer initialization.
The description of the disclosed embodiments is provided to enable any person skilled in the art to make or use them. Various modifications to these embodiments will be readily apparent to those skilled in the art and the principles explained herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and novel features disclosed.
Number | Name | Date | Kind |
---|---|---|---|
6370188 | Wu et al. | Apr 2002 | B1 |
7027429 | Laroia et al. | Apr 2006 | B2 |
7227835 | Belotserkovsky et al. | Jun 2007 | B2 |
7245677 | Pare, Jr. | Jul 2007 | B1 |
7336732 | Wiss | Feb 2008 | B1 |
7636525 | Bontu et al. | Dec 2009 | B1 |
7801233 | Chow et al. | Sep 2010 | B1 |
7924910 | Bhoja et al. | Apr 2011 | B2 |
8005368 | Roberts et al. | Aug 2011 | B2 |
8095019 | Kaneda et al. | Jan 2012 | B2 |
8233809 | Qian et al. | Jul 2012 | B2 |
8260156 | Qian et al. | Sep 2012 | B2 |
8295714 | Winzer | Oct 2012 | B2 |
20050058193 | Saed | Mar 2005 | A1 |
20060104257 | Laroia et al. | May 2006 | A1 |
20060146945 | Chow et al. | Jul 2006 | A1 |
20070133697 | Spock et al. | Jun 2007 | A1 |
20070147850 | Savory et al. | Jun 2007 | A1 |
20080212717 | Wiss | Sep 2008 | A1 |
20080219340 | Saed | Sep 2008 | A1 |
20090161782 | Kolze et al. | Jun 2009 | A1 |
20100003028 | Zhang et al. | Jan 2010 | A1 |
20100008678 | Caggioni et al. | Jan 2010 | A1 |
20100119241 | Yang et al. | May 2010 | A1 |
20100316094 | Tung | Dec 2010 | A1 |
20100329677 | Kaneda et al. | Dec 2010 | A1 |
20110150477 | Winzer | Jun 2011 | A1 |
20110150503 | Winzer | Jun 2011 | A1 |
20110268459 | Rollins et al. | Nov 2011 | A1 |
20120106982 | Wagner et al. | May 2012 | A1 |
Number | Date | Country |
---|---|---|
2146448 | Jan 2010 | EP |
Entry |
---|
Winzer et al., “Spectrally Efficient Long-Haul Optical Networking Using 112-Gb/s Polarization-Multiplexed 16-QAM”, Journal of Lightwave Technology, vol. 28, No. 4, Feb. 15, 2010, pp. 547-556. |
Authorized Officer Hannelore Filip, International Search Report/Written Opinion in PCT/US2011/058170 mailed Dec. 28, 2011, 12 pages. |
Number | Date | Country | |
---|---|---|---|
20120106982 A1 | May 2012 | US |