Modeling of ultra-high speed optical transmission systems

Modeling of Ultra-High Speed Optical Transmission Systems H. Louchet1, K. Kuzmin2, C. Arellano1, I. Koltchanov1, A. Richter1,*

1VPIsystems, Carnotstr. 6, 10587 Berlin, Germany; 2VPI Development Center Minsk, Belarus

ABSTRACT

Key issues related to the modeling of ultra-high speed transmission are discussed in this paper. These topics include components modeling, link modeling and BER estimation. Different solutions for the transport of 100 Gb/s over a single wavelength including technologies such as coherent detection, polarization multiplexing, optical OFDM, and digital signal processing are reviewed and compared with means of numerical simulations.

Keywords: High-speed, optical transmission, modeling, coherent detection, digital signal processing, mQAM, mPSK

1. INTRODUCTION The growing trend to ultra-high-speed transmission (e.g. 100 Gb/s Ethernet) and high spectral efficiency WDM systems has boosted new technologies such as polarization multiplexing (PolMux) and multilevel modulation formats [1], [2]. Initiated by the recent progress of high-speed electronics, great attention has recently been paid to transmission systems combining coherent detection and digital signal processing (DSP) [3]. This approach enables powerful mitigation of chromatic dispersion (CD) and polarization-induced distortions (e.g. PMD, polarization cross-talk), and presents improved noise characteristics compared to direct detection receivers. These advanced design concepts raise new challenges in photonic simulations [4] that will be addressed in the following sections:

Transmitter and receiver modeling: Transmission of high-speed signals increases the requirements on electrical and electro-optical components. At high frequencies, the modulation bandwidth of Mach-Zehnder (MZ) and electro-absorption (EA) modulators is limited by the mismatch between microwave and optical velocities and by frequency-dependent microwave attenuation. Accurate modeling of passive optical devices such as couplers is also of importance, particularly for coherent transmission systems. For example the temperature and wavelength dependence of their characteristics (loss, PDL, refractive index, etc.) should be taken into account.

Link modeling: Besides classical transmission impairments (CD, 1st order PMD and fiber nonlinearities), impairments from higher order effects such as dispersion slope, 2nd order PMD, and the interplay between these effects and fiber nonlinearities need to be taken into account when simulating high-speed transmission systems. The statistical behavior of the fiber polarization characteristics (principal states of polarization, PMD, PDL) can be investigated by carrying out Monte-Carlo (MC) simulations using the coarse-step or Hinge fiber models. The use of a link emulator to investigate the impact of combined CD-PMD and PDL effects represents another possible approach for modeling the transmission link.

BER estimation: Bit-Error-Rate (BER) of optical transmission systems can be estimated using MC simulation (error-counting method) or by estimating the probability density function (PDF) of the received signal. Stochastic or deterministic methods can be used to estimate the PDF of the detected signal. Such methods are already available for OOK, DPSK and DQPSK signals [5]. However, we will show that with the advent of multi-level modulation formats associated to coherent detection and DSP, new methods for BER-estimation need to be developed.

100 Gb/s Systems: Finally, the performance of possible implementations of 100 Gb/s transmission reported in the literature will be assessed with means of numerical simulation.

*[email protected]; www.VPIphotonics.com

Optical Transmission, Switching, and Subsystems VI, edited by Ken-ichi Kitayama, Pierpaolo C. Ghiggino, Kim Roberts,Yikai Su, Proc. of SPIE Vol. 7136, 713632 · © 2008 SPIE · CCC code: 0277-786X/08/$18 · doi: 10.1117/12.804321

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2. TRANSMITTER AND RECEIVER MODELING Transmission of high-speed signals increases the requirements on electrical and electro-optical components (particularly when using binary modulation formats as electrical signals with ~100 GHz bandwidth must be managed). At high frequencies, the modulation bandwidth of Mach-Zehnder and electro-absorption modulators is limited by the mismatch between microwave and optical velocities and by frequency-dependent microwave attenuation occurring in the MZ driving circuit and in the connectors. In simulations, these effects can be represented by adding electrical filters corresponding to the transfer function (E-O response) of the modulator. For example, Fig. 1 represents the measured transfer function of a MZ modulator (Sumitomo 40 Gb/s) for the upper and lower branches. The impact of the bandwidth limitation of this modulator is illustrated in Fig. 2 in the case of a 40 and 100 Gb/s NRZ drive signal.

Fig. 1: Measured transfer function (magnitude) of a MZ modulator. Left: upper branch; right: bottom branch.

Fig. 2: Simulated eye diagrams with realistic MZ modulator transfer function (magnitude and phase). Left: 40 Gb/s; right: 100 Gb/s.

100 Gb/s binary signals are very sensitive to CD and PMD because of their broad spectrum (see Fig. 3). Duobinary or vestigial side band (VSB) modulation can be used to narrow their spectrum. VSB modulation uses strong optical filtering to suppress one of the side bands, and thus, has a narrow bandwidth resulting in a larger dispersion tolerance compared to the unfiltered NRZ signal. VSB modulation can as well increase the signal quality, and thus, improve system performance in case of electrical-bandwidth limited systems. The distortion imposed by electronics can be regarded similar to the one imposed by dispersion as the limitation of electrical bandwidth implies a widening of the pulses in time domain. In our studies, vestigial modulation is accomplished by a Gaussian filter with 200 GHz bandwidth centered at 193.2 THz. It is applied after the electro-optical modulator to a 100 Gb/s data signal centered at 193.1 THz. BER versus dispersion results for several filter orders are reported in Fig. 4. (left). The impact of filter detuning (which can be also seen as a variation of the effective bandwidth) was also investigated. The results reported in Fig. 4. (right) show that the best dispersion tolerance is achieved by detuning the 200 GHz filter by 20 GHz corresponding to an effective filter bandwidth of 180 GHz.

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Fig. 3: BER versus accumulated CD for 100 Gb/s NRZ with different modulator bandwidths (OSNR= 32 dB).

Fig. 4: 100 Gb/s VSB performance for different amount of filtering.

Left: 200 GHz Gaussian filter with different orders; right: Impact of detuning (filter order = 1).

Accurate modeling of passive optical devices such as couplers is also of importance, particularly for coherent transmission systems. For example, the 90°-hybrid is a key component for coherent transmission. It enables the separation of the Inphase (I) and Quadrature (Q) components by mixing the incoming signal with a local oscillator (LO). Real components may contain inaccuracies due to manufacturing tolerances, and frequency / temperature dependences which can lead to significant deviations from the ideal case. These discrepancies can be taken into account by writing the transfer matrix of the 90°-hybrid as follows [6]:

ILS, ILO describe the insertion loss of the signal and local oscillator, and ImbI, ImbQ, describe the insertion loss imbalances for the I and Q components. ϕSLOrad and ϕIQrad represent the phase imbalances between the signal and local oscillator, and between I and Q components, respectively. Passive optical devices may also exhibit PMD and PDL, which can lead to signal distortions.

Simple system models of electrical devices usually cannot account for effects like frequency-dependent gain of driver amplifiers or phase and frequency instabilities of clock-recovery modules. In order to include these aspects in simulations, electrical devices should be precisely characterized (e.g., via S-parameters). Further on, ideal models can be improved to better fit the real device by using separate electrical filters and sources for noise and/or deterministic distortions that account for the measured device characteristics. An alternative to this impairment-oriented modeling is


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to simulate the real electrical device by taking advantage of the co-simulation capability between simulation tools dedicated to photonics systems and electronic devices like VPItransmissionMaker from VPIsystems and Advanced Design System from Agilent. Proper modeling of digital devices like analog-to-digital converters (ADC), digital filters (FIR) or DSP receiver is also important as they can ultimately limit the performance of coherent transmission systems. For example, speed, bandwidth and dynamic range of ADCs are of particular importance in coherent systems where DSP is used to mitigate transmission impairments like CD and PMD.

3. LINK MODELING Besides classical transmission impairments (CD, 1st order PMD and fiber nonlinearities), higher order effects like dispersion slope, 2nd order PMD, and their interplay with fiber nonlinearities need to be taken into account when simulating high-speed transmission systems. Advanced fiber models supporting the polarization-dependence of nonlinear effects (Kerr & Raman) have been developed for this purpose [7]. The statistical behavior of the fiber polarization characteristics (principal states of polarization, PMD, PDL) can be investigated by carrying out Monte-Carlo (MC) simulations using the coarse step or Hinge fiber models [8].

The use of “link emulators” [9], [10] to investigate the impact of combined CD-PMD and PDL effects is another possible approach for modeling the transmission link. With such emulators the differential group delay (DGD), the polarization chromatic dispersion (PCD), and the depolarization rate (DR) can be set individually and specific combinations of 1st and 2nd order PMD can be selected. As an example, two orthogonal channels of a 100 Gb/s PolMux DQPSK signal are displayed on the Poincaré sphere in Fig. 5 at the link emulator output (CD=PDL=DGD=0, PCD=0.16 s/m, DR= 30 ps over 1000 km). It can be observed that the channels are losing their distinct polarization states as a result of 2nd order PMD. This leads to additional penalty due to channel cross-talk, as illustrated in Fig. 6.

Fig. 5: Depolarization of a 100 Gb/s PolMux DQPSK signal due to higher order PMD

(polarization of the X/Y channels are represented by solid/dash lines).

Fig. 6: Eye diagram (Xpol. channel) of the PolMux DQPSK signal without (left) and with (right) 2nd order PMD.


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The emulators reported in [9] and [10] can be extended to account for polarization changes that are slow (minute or hour scale to account for temperature-induced variations) or fast (sub-millisecond scale to account for vibrations). However, such “lumped” models cannot account for nonlinear effects that are distributed in the line. The stochastic nature of polarization effects together with the large computational effort required to simulate Kerr effects make such a joint investigation difficult with standard simulation techniques. Techniques such as importance sampling [11] allow examining low-probability states that would result in strongly degraded system performance with less numerical effort.

4. BER ESTIMATION METHODS The Bit-Error-Rate (BER) of optical transmission systems can be calculated using MC simulation (error-counting method) or by estimating the probability density function (PDF) of the received signal. The last approach enables BER estimation as low as 10-15 whereas the first one is usually limited to BER values not lower than 10-5. Stochastic or deterministic methods can be used to estimate the PDF of the received signal. These methods are usually available for OOK, DPSK and DQPSK signals [5]. However, with the advent of multi-level modulation formats (mQAM, mPSK) associated with coherent detection and DSP, new BER-estimation methods have to be developed. While ASE and phase noise (phase mismatch between the transmitter laser and local oscillator due to non-zero linewidth ∆ν) can be described easily, after photo-detection, the impact of pre- and post sampling signal processing on the error probability is more difficult to predict. Some attempts to include the impact of signal processing on the BER estimation have already been reported [12]. In an ideal case, all signal distortions except those due to ASE noise can be completely mitigated. The system performance is then limited by the SNR of the received electrical signal (that can be derived from the OSNR and from the noise and filter characteristics of the receiver). For example, when linear filters are used to mitigate CD or polarization-induced impairments, the derivation of the BER can be straight forward as the PDFs of the distorted symbols remain Gaussian. Numerical simulations illustrating this point are reported in Fig. 7.

Fig. 7: Estimated (Gaussian fit) and exact (Monte-Carlo) BER versus fiber length for a 100Gbit/s coherent PolMux QPSK system.

CMA-optimized MIMO is used to compensate for CD and PMD-induced distortion. Phase noise is not considered (∆ν=0).

Other algorithms, like for example the phase correction algorithm for mPSK systems (multi-symbol phase estimation, MSPE) proposed in [13], use nonlinear signal transformation to remove the modulation. Most phase-error correction algorithms reported so far [14], [15], [16] rely on the principle of this algorithm. After such nonlinear operations, the PDF of the received signal may be non-Gaussian and new BER estimation methods are required. Nonetheless, we verified that the Gaussian approach can still provide a good estimation of the system performance in the case of a 30 Gb/s 8PSK signal with coherent detection, where this algorithm is used to mitigate the phase error due to laser noise. The system BER has been estimated using the Gaussian approach and Monte-Carlo simulations for different laser linewidths at an OSNR of 20 dB. The phase error is averaged over 5 symbols to reduce the impact of ASE-noise. The results are reported in Fig. 8. We believe that this result can be extended to other mPSK systems where this algorithm is implemented.


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MSPE is used to compensate for phase error.

5. EXEMPLARY 100 GB/S TRANSMISSION SYSTEMS Several technologies are available for the realization of 100 Gb/s transmission over a single wavelength. For example, complex transmitter and receiver architectures with enhanced bandwidth and stability characteristics can be realized as photonic integrated circuits (PICs). Recent progress of high-speed electronics, and particularly, of FPGA and analog-to-digital converter developments (see [17] for instance), supports high-speed digital signal processing for 100 Gb/s signals. Moreover, techniques like polarization multiplexing (PolMux), multi-level or multi-carrier modulation formats (mPSK, mQAM, OFDM) enable to reduce the signal baud-rate relaxing the requirements on electrical components as well as on electronics. The final section of this paper provides a non-exhaustive overview of 100 Gb/s transmission reported so far using different approaches.

5.1 Coherent PolMux QPSK

The feasibility of 100 Gb/s transmission using coherent PolMux QPSK has been demonstrated in [18]. In the experiments reported so far, signal processing is performed off-line as commercially available ADCs did not meet the desired requirements (at least 25 GSa/s, 4 bits quantization, 40 GHz bandwidth). In this section, the performance of a 100 Gb/s coherent PolMux QPSK transmission system is investigated using numerical simulations (see Fig. 9). The system performance is assumed to be limited by ASE-noise, by the phase and frequency mismatch between the transmitter laser and local oscillator and by channel cross-talk due to polarization misalignment between the channels and polarization beam splitter (PBS) at the receiver side. The I and Q components of both polarizations are detected using a polarization- and phase-diversity receiver with balanced detection. The four electrical signals are digitized (2 samples per symbol, 6 bits quantization) for DSP. A complex filter structure (MIMO) optimized with the constant modulus algorithm (CMA) is used for cross-talk mitigation. A classical multi-symbol phase estimation (MSPE) is used for phase error correction (average over 5 symbols). System performances are reported in Fig. 10.

Fig. 9: Simulation setup in VPItransmissionMaker. The transmission line is modeled using the “link emulator” reported in section 3.


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5.2 PolMux DQPSK with orthogonal optical subcarriers

To achieve high spectral efficiency while keeping the electrical drive requirements low, 100 Gbit/s data rate can be generated using two optical subcarriers, polarization multiplexing and DQPSK modulation of the 4 tributaries at 25 Gbaud as proposed in Error! Reference source not found.. The first MZ modulator converts the single carrier into two subcarrier signals with 25 GHz spacing. Note that the amplitude level of the sin-generator determines the levels of the center carrier (to be suppressed) and of the higher-order intermodulation products. It is followed by a MZI-based filter with 50 GHz free spectral range (FSR), polarization beam splitters and four DQPSK modulators. As result, each subcarrier is individually modulated in both polarizations with a 25 Gbaud DQPSK signal. Fig. 11 shows the simulation setup and Fig. 12 shows the optical subcarriers before and after modulation.

Fig. 11: Simulation setup in VPItransmissionMaker.

At the receiver, first the signal is split into both orthogonal polarizations again, and passed to two MZI-based filters with 50 GHz FSR before DQPSK demodulation. For long haul transmissions, coherent instead of interferometric detection can be used to take advantage of DSP for CD and PMD compensation [19]. In that case, the subcarriers are separated in the electrical domain using a low-pass filter.

System performances are reported in Fig. 13. Results show that polarization misalignment between channels and polarization beam splitter at the receiver side leads to an important penalty. For this reason, polarization tracking at the receiver would be required in commercial systems.


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Fig. 13: BER vs. OSNR of all 4 channels in presence of channel cross-talk due to PBS misalignment.

5.3 Orthogonal Frequency Division Multiplexing

100 Gb/s transmission using OFDM in combination with coherent detection and polarization multiplexing has been demonstrated (e.g. [21], [22]). Contrary to other modulation formats, coherent detection is not necessary for OFDM signals to perform CD mitigation [23] but is used to improve the receiver sensitivity as OSNR requirements of direct-detected OFDM signals are very stringent. As stressed in [24] drawbacks of OFDM are mainly due to its large peak-to-average power ratio (PAPR) leading to strong nonlinear impairments in periodic dispersion maps and to its complex transmitter and receiver structure (high-speed DSP and ADC are required at both sides).

Fig. 14: Simulation setup in VPItransmissionMaker.


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Using the setup displayed in Fig. 14, we generate and decode a 50 Gb/s electrical OFDM signal with 1024 sub-carriers and 10% cyclic prefix. Raised-cosine filters (with 18% roll-off) are used for pulse-shaping. Different modulation formats are considered for sub-carrier encoding. Using higher level modulation formats helps to reduce the required sampling rate but also increases the number of required quantization levels. This is illustrated in Fig. 15 and Fig. 16.

Fig. 15: Received QPSK and 16QAM constellations for 4 and 5 bits quantization.

Fig. 16: OFDM spectrum (real part) for QPSK and 16QAM modulation.

6. CONCLUSION We discussed and illustrated the challenges related to the modeling of high-speed transmission systems with data rates of 100 Gbit/s. We particularly focused on the impact of components modeling, polarization effects and on the impact of new technologies like multilevel modulation, coherent detection and digital signal processing. This paper provides some general guidelines to researchers and engineers aiming to design next generation systems with the help of photonic systems simulation.

7. ACKNOWLEDGMENTS This work has been partly founded by the German Ministry of Education and Research in framework of the Celtic project “100 GET”.


REFERENCES

[1] C. Wree et al., “High spectral efficiency 1.6-b/s/Hz transmission (8×40 Gb/s with a 25-GHz grid) over 200-km SSMF using RZ-DQPSK and polarization multiplexing”, IEEE Photonics Technology Letters, vol. 15, 1303-1305 (2003)

[2] C.R.S. Fludger, et al., “10 x 111 Gbit/s, 50 GHz spaced, POLMUX-RZ-DQPSK transmission over 2375 km employing coherent equalisation”, OFC/NFOEC 2007, paper PDP22 (2007)

[3] S. Savory et al., “ Digital filters for coherent optical receivers”, Optics Express, vol. 16, 804-817, (2008) [4] A. Richter et al., “Pitfalls when Modeling High-Speed Optical Transmission Systems”, IEEE LEOS Summer

Topicals, 238-239 (2007) [5] A. Richter et al., “Issues on Bit-Error Rate Estimation for Fiber-Optic Communication Systems” OFC/NFOEC

2005, paper NTuH3 (2005) [6] M. Seimetz et al.,”Options, Feasibility, and Availability of 2 x 4 90° Hybrids for Coherent Optical systems”, IEEE

Journal of Lightwave Technology, vol. 24, (2006). [7] I. Poloyko, et al., “Photonic Design Automation of Raman Amplified Systems” NFOEC 2003, paper P29 (2003) [8] Kogelnik, et al,, Ch.15 in Optical Fiber Telecommunications IVB, Academic Press (2002). [9] Francia, et al,, “PMD Second-Order Effects on Pulse Propagation in Single-Mode Optical Fibers”, IEEE Photonics

Technology Letters, vol. 10, 1739-1741 (1998) [10] P. Krummrich et al., “A novel, easy to use Emulator for deterministic generation of pure first and second order

PMD”, OFC/NFOEC 2007, paper OMH3 (2007) [11] R. Srinivasan, Importance sampling - Applications in communications and detection, Springer-Verlag, Berlin, 2002. [12] Goldfarb, et al., “BER estimation of QPSK homodyne detection with carrier phase estimation using digital signal

processing”, Optics Express, vol. 14, 8043-8053 (2006) [13] A. J. Viterbi et al., "Nonlinear Estimation of PSK-Modulated Carrier Phase with Application to Burst Digital

Transmission“ IEEE Transactions On Information Theory, vol. IT-29 (1983) [14] S. Tsukamoto et al., “Coherent Demodulation of Optical Multilevel Phase-Shift-Keying Signals Using Homodyne

Detection and Digital Signal Processing”, IEEE Photonics Technology Letters, vol. 18, 1131-1133 (2006) [15] E. Ip et al., “Feedforward Carrier Recovery for Coherent Optical Communications”, IEEE Journal of Lightwave

Technology, vol. 25 (2007) [16] M. Seimetz, “Performance of Coherent Optical Square-16-QAM-Systems Based on IQ-Transmitters and

Homodyne Receivers with Digital Phase Estimation”, OFC/NFOEC 2006, paper NWA4 (2006) [17] www.micram.com and www.xilinx.com. [18] C.R.S. Fludger et al., “Coherent Equalization and POLMUX-RZ-DQPSK for Robust 100-GE Transmission”,

Journal of Lightwave Technology, Vol. 26, 64, (2008) [19] E.Yamada et al., "30 x 100-Gb/s all-optical OFDM transmission over 1300 km SMF with 10 ROADM nodes",

ECOC 2007, paper PD1.7 (2007) [20] E. Yamada1 et al., “Novel No-Guard-Interval PDM CO-OFDM Transmission in 4.1 Tb/s (50 x 88.8-Gb/s) DWDM

Link over 800 km SMF Including 50-GHz Spaced ROADM Nodes”, OFC/NFOEC 2008, paper PDP8 (2008) [21] S. L. Jansen et al., “10x121.9-Gb/s PDM-OFDM transmission with 2-b/s/Hz spectral efficiency over 1000 km of

SSMF”, OFC/NFOEC 2008, paper PDP2 (2008) [22] W. Shieh et al., “107 Gb/s coherent optical OFDM transmission over 1000-km SSMF fiber using orthogonal band

multiplexing”, Optics Express, Vol. 16, 6378-6386 (2008) [23] A.J. Lowery et al., ““Orthogonal frequency division multiplexing for adaptive dispersion compensation in long-haul

WDM systems,” OFC/NFOEC 2006, paper PDP39 (2006) [24] S. L. Jansen et al., “Optical OFDM, a Hype or is it Real?”, ECOC 2008, paper Mo.3.E.3 (2008)

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