## Abstract

We study long-haul Quasi-Single-mode (QSM) systems in which signals are transmitted in the fundamental modes of a few-mode fiber (FMF) while keeping other system components such as amplifiers and receivers are kept single-moded. The large-effective-area nature of the FMF fundamental modes improves system nonlinear tolerance in the expense of mode coupling along FMF transmissions which induces multi-path interference (MPI) and needs to be compensated. We analytically investigate 6-spatial-polarization mode QSM transmission systems in presence of MPI and show that in the weak coupling regime, the QSM channel is a Gaussian random process in frequency. MPI compensation filters are derived and performance penalties due to MPI and signal loss from higher-order modes are characterized. We also experimentally demonstrate 256 Gb/s polarization multiplexed (PM)-16-QAM QSM transmissions over a record distance of 2600 km with 100-km span using decision directed least mean square (DD-LMS) algorithm for MPI compensation.

© 2015 Optical Society of America

## 1. Introduction

Fiber nonlinearity is a fundamental performance limiting factor in long-haul transmissions. Nonlinearity compensation algorithms such as digital back-propagation [1] are new tools to combat fiber nonlinearities but they are too complex and only bring moderate transmission improvements at best. This partly motivates the current wave of research in FMF MIMO transmissions [2] as alternatives to increase transmission capacities but those are highly impractical at present as they require few-mode amplifiers, multiplexers, de-multiplexers in addition to highly complex digital signal processing (DSP). In this regard, Yaman et al. [3,4] proposed to use the FMF as a large effective-area single-mode fiber and launch signals in the fundamental LP_{01} mode while keeping other single-mode components such as erbium-doped fiber amplifiers (EDFA) and transceivers in the link, otherwise known as QSM transmissions. The large-effective-area nature of the LP_{01} mode considerably extended the transmission distance. However, this may be a specific and overly-optimistic scenario. In general, mode coupling between the LP_{01} and LP_{11} modes are expected to be present in practical QSM systems which will induce multi-path interference (MPI) and potentially limit transmission performance. In other significant QSM transmission work, 16 × 100 Gb/s PM-QPSK signals were successfully transmitted over 635 km of standard 50 *μ*m core diameter multimode fiber, but the reach was ultimately limited by MPI effects [5]. Bai et al. [6] briefly studied DSP techniques to mitigate MPI but long-haul QSM transmission experiments with MPI compensation has yet to be demonstrated.

Recently, we reported 256 Gb/s PM-16-QAM QSM transmission with 100 km per span and EDFA amplification [7,8]. The MPI is compensated by an additional DD-LMS algorithm after carrier phase estimation (CPE) in a standard DSP platform. The DD-LMS increases the optimal signal launch power by around 3 dB and the transmission distance for 256 Gb/s PM-16-QAM signals with 100 km per span can be extended up to 2600 km, which is a new record for 256 Gb/s PM-16-QAM transmissions with 100-km spans. In this paper, we extend our investigations and develop the theoretical foundations for polarization-multiplexed QSM transmission systems in the presence of mode coupling and differential mode loss between different mode groups in the FMF. We show that in the weak coupling regime, the multi-span QSM channel is a Gaussian random process in frequency in the weak coupling regime. MPI compensation filters are derived and mode-coupling-induced performance penalties are characterized. In particular, we show that MPI impairments can be effectively compensated by appropriate DSP techniques while signal loss in higher-order modes at the end of each span plays a significant role in the overall performance gain of QSM transmission systems.

## 2. Mode-coupling dynamics and charactering the QSM channel

#### 2.1 QSM channel model

Consider a span of few-mode fiber of length *L* modeled as a concatenation of *K* sections of length Δ*L* between which mode coupling may occur. For simplicity, we will initially only study the coupling between the fundamental mode and a higher-order mode with differential mode delay (DMD) ∆*τ* and differential mode loss (DML) Δ*α* as shown in Fig. 1. The input *E _{in}*(

*ω*) is the transmitted signal launched into the fundamental mode with unit power and

*E*(

_{out}*ω*) is the signal output at the fundamental mode at the fiber end. Because of mode-coupling along the fiber, some signals will be present at the higher-order mode at the fiber end and will be stripped off as a consequence of butt-coupling with single-mode EDFAs or coherent receiver.

In this case, the output signal is given by

*k*section through independent identically distributed (i.i.d.) uniform random variables

^{th}*η*and

_{k}*θ*with distributions U[0, 2

_{k}*κ*Δ

*L*] and U[0, 2

*π*] respectively. The coupling coefficient

*κ*can be viewed as a measure of coupling strength. We note that there are other 2-mode models proposed in the literature [9,10] but they are fundamentally very similar to ours and give identical statistical predictions. Furthermore, the dynamics of statistical mode coupling in linear fibers have been extensively studied in the ‘90s in which a continuous-fiber model is adopted [11,12]. We hereby choose to use the discrete concatenating-fiber model to better align with theoretical analysis in recent spatial-division multiplexing literature and we again emphasize that the conclusions drawn will be identical regardless of the fiber model chosen.

The transfer function of one span of QSM system is then given by

*h*(

_{1-span}*t*) denote the corresponding impulse response. We are interested in the statistics of

*h*(

_{1-span}*t*) as it characterizes the amount of MPI and the length of the MPI compensation filter. In particular, starting from the Power Spectral Density relation

*κL*is small,

**E**[·] denotes expectation and $E\left[|{h}_{MPI,1-span}(t){|}^{2}\right]$ are the MPI component of

*h*(

_{1-span}*t*). For a multi-span QSM system with per-span amplification, let $\otimes $ denotes convolution and

*h*(

_{MPI,n}*t*) be the MPI component of the

*n*span of fiber. In this case, the overall impulse response

^{th}*h*(

*t*) is given by

*h*(

_{MPI,n}*t*) is small. Now, since

*h*(

_{MPI,n}*t*) are statistically independent for different spans,

The 2-mode coupling model can be readily generalized to 6 spatial-polarization modes for realistic polarization-multiplexed QSM transmissions. In this case, the input-output relation is given by

*V*

_{x}_{(}

_{y}_{)}(

*ω*) is the Fourier Transform of the collective amplifier noise of the link, which is modelled as a circularly symmetric white Gaussian random process. Signals in the two fundamental modes (and any two modes of the 4 higher-order modes) are assumed to couple freely between each other i.e. the corresponding

*η*will be uniformly distributed between 0 and 1. For coupling between any fundamental mode and any higher-order mode, the coupling coefficient is changed from

_{k}*κ*to

*κ*/4. The derivations for the expected impulse response powers for polarization-multiplexed QSM systems are largely similar and will be omitted here. The results are

In addition, we are also interested in the probability density function (pdf) of the QSM channel ** H**(

*ω*). In Appendix II, we show that in the weak coupling regime, the pdf of

**(**

*H**ω*) is independent of

*ω*and approximately complex circularly symmetric Gaussian with

**is the identity matrix. Altogether, in the weak coupling regime, the transfer function of a**

*I**N*-span QSM system

**(**

*H**ω*) is a stationary Gaussian random process in frequency with auto-correlation function $E\left[|{h}_{xx(yy)}(t){|}^{2}\right]$ and $E\left[|{h}_{xy(yx)}(t){|}^{2}\right]$.

Simulations are conducted to verify the theoretical predictions and results shown in Fig. 2, which indicates good agreements between them. Further simulations reveal that $E\left[|{h}_{xx(yy)}(t){|}^{2}\right]$ is insensitive to typical differential group delays (DGD) between the two fundamental modes and thus PMD effects. This should be expected as typical FMFs have DMDs much larger than the DGD between the fundamental modes.

#### 2.2 Transmission penalties and DSP mitigation strategies for QSM systems

Mode coupling effects and DMD induce MPI and inter-symbol interference (ISI) in QSM transmissions. In principle, the ISI or MPI length should scale with increasing DMD and decreasing DML. The MPI length dictates the number of taps and hence the computational complexity of the MPI compensation filter in a digital coherent receiver. If we define *τ _{MPI}* as the length of time that contains 99% of the MPI power, we have

*W*(∙) is the Lambert W function [13]. Figure 3 shows the MPI length

*τ*for various DMD and DML values for a 32Gbaud QSM transmission system.

_{MPI}In the frequency domain, MPI manifests itself as frequency-selective fading, very much like multi-path fading in wireless communications. A sample realization of *H _{xx}*

_{(}

*(*

_{yy)}*ω*) and the pdf of its amplitude is shown in Fig. 4(a). Wiener filter

**(**

*W**ω*) (that minimize the expected mean-square error) can be used to compensate MPI and is given by

*H*^{†}(

*ω*) is the conjugate transpose of

**(**

*H**ω*).

*S*(

_{S}*ω*) is the power spectral density of the input signal.

*N*

_{0}is the power spectral density of the amplifier noise

*V*

_{x}_{(}

_{y}_{)}(

*ω*) and the filter output is given by

Figure 5 shows the *Q* vs. OSNR for 32Gbaud-PM-16-QAM transmissions with and without MPI compensation for a 20-span QSM system with a random realization of the transfer function ** H**(

*ω*). The

*Q*value is derived from $Q=\sqrt{2}erf{c}^{-1}(2\cdot BER)$. It is clear that MPI significantly degrades system performance if left uncompensated. Fortunately, Wiener filtering can almost eliminate the effects of MPI, but not completely. This is because Wiener filtering is based on the minimum mean-squared error-criterion which introduces noise enhancement, residual ISI and hence a performance penalty. Furthermore, the penalty is in general random due to the random fading nature of

*H*

_{xx}_{(}

*(*

_{yy)}*ω*). If we also consider the residual ISI as an additional source of noise, this MPI-induced penalty Λ

*will be given by*

_{MPI}*u*(

_{ij}*ω*) and

*w*(

_{ij}*ω*) denote the

*i,j*entry of

^{th}**(**

*U**ω*) and

**(**

*W**ω*) respectively and

*S*(

_{S}*ω*) is the power spectral density of the input signals

*E*

_{in}_{,}

_{x}_{(}

_{y}_{)}(

*ω*). In addition to Λ

*, another mode-coupling-induced performance penalty Λ*

_{MPI}*stems from the loss of signals in higher-order modes at the end of each span. This penalty can be approximated by the power remaining in the fundamental mode at the end of each span, i.e.*

_{HOM}*G*of QSM relative to standard single-mode fiber transmission systems is then given by

_{overall}Figure 6 shows the pdf of overall performance gain *G _{overall}* of a 20-span QSM transmission system in presence of mode-coupling-induced penalties Λ

*and Λ*

_{MPI}*and an effective area*

_{HOM}*A*2.5 times that of a standard single mode fiber for different coupling strengths. Fiber nonlinearity effects are not included in the simulation as we want to highlight the effects of MPI and higher-order mode stripping loss and nonlinearity should induce the same amount of OSNR penalty for both QSM and standard fiber systems at their respective optimal signal launched powers. It can be seen that, when MPI is appropriately compensated, the higher-order mode loss Λ

_{eff,FMF}*plays a larger role than residual MPI-induced penalties in limiting the overall performance gain. One can define an appropriate threshold, say 1 dB from optimal performance, to statistically characterize acceptable level of performance and outage probabilities of QSM transmission systems.*

_{HOM}## 3. 256 Gb/s PM-16-QAM QSM Transmission Experiments over 2600 km with MPI Compensation

Experiments are also conducted to investigate the performance of QSM transmissions with MPI compensation in practical settings. The FMF used for QSM transmission in our experiments is a step-index silica core fiber with core radius around 9 *μ*m and supports 6 polarization modes. The nominal effective area for the fundamental mode is 220 *μ*m^{2}. The DMD is measured to be around 1.12 ns/km. The higher order modes suffers a higher loss compared with the fundamental mode. The average measured attenuation of two 100 km spans constructed is about 19.1 dB including splices and connectors. At the beginning and end of each span, the FMF is connected with standard single mode fiber jumpers through a bridge fiber to ensure compatibility with single-mode components such as EDFAs and transmitters/receivers. The total loss on the input side including connector loss, splice from single-mode to bridge fiber, and splice from bridge fiber to FMF is about 0.6 dB. At the output of each span, the same level of connection and splicing loss is expected, in addition to a loss rising from the mode stripping. The average fiber loss is approximately in the range of approximately 17.5 dB and the rest is due to splices and connectors. Since the fibers are drawn from two different blanks, measurements of the accumulated MPI or crosstalk level of each of the two 100 km spans shows significantly different behavior with estimated levels of about −24 dB for one span and −30 dB or less for the second span.

The two 100-km spans of FMF are placed in a re-circulating loop configuration for transmission measurements. The experimental setup is shown in Fig. 7. Ten lasers spaced by 50 GHz are modulated together in the 16-QAM format at a symbol rate of 32 Gbaud, and then polarization-multiplexed to produce 256 Gb/s PM-16-QAM channels. The channel under measurement is encoded on an external cavity laser (ECL) while the other 9 channels are encoded on DFB lasers. The channels are passed through a short piece of positive dispersion fiber to de-correlate adjacent channels by a few symbols before being launched in the loop. EDFAs are used to amplify the signals at the output of each FMF span.

The receiver DSP algorithms consist of orthogonalization and normalization followed by frequency-domain CD compensation. The received data is then re-sampled to 2 samples per symbol for timing phase recovery [14]. CMA and CMMA on a 21-tap $2\times 2$MIMO filters are used as a two-stage algorithm for polarization de-multiplexing and PMD compensation. The signals are then down-sampled to 1 sample per symbol followed by frequency offset estimation and CPE [15,16]. A joint-polarization DD-LMS filters with maximum 501 taps is inserted after CPE for MPI compensation. This is followed by symbol decisions and BER calculation.

Figure 8(a) shows the BER vs. OSNR for linear transmission for one of the FMF spans cut into different lengths without using DD-LMS for MPI compensation. These results are obtained for straight-line transmission through the two fiber lengths shown with ASE noise-loading before the receiver. The presence and distributed nature of MPI is evident from the fact that performance degrades with increasing FMF length. We then conducte QSM transmission over 600 km, or 3 loops, and vary the channel launched power to determine the optimal channel power. The measured *Q* values (derived from $Q=\sqrt{2}erf{c}^{-1}(2\cdot BER)$) are shown in Fig. 2(b) along with results over a comparable 600-km standard single mode fiber system. The optimal launched power for the QSM system is about 3-4 dB higher than that of the standard fiber system by virtue of the larger effective area. Without DD-LMS, the FMF system has a maximum *Q* value about 0.5 dB lower than the standard single mode fiber system at this distance because of significant MPI. However, a 101-tap joint-polarization DD-LMS significantly improves QSM performance and a 501-tap DD-LMS enables QSM to outperform the standard fiber by more than 2 dB in *Q*. The convergence time for the DD-LMS is in the order of 50000 symbols in most of our data sets.

It should be noted that the 501-tap DD-LMS does not fully compensate the MPI and further improvement, albeit marginal, can be obtained with increasing number of DD-LMS taps. However, as the delay between x and y polarization in our experimental setup is around 280 symbols, extending the number of taps beyond 560 taps results in double counting the signal and results in an under-estimate of BER. This is clearly evident in Fig. 9 for a single-span 50-km QSM system. Therefore, we choose the maximum number of taps to be 501 in our studies to ensure that our results are free from signal double counting.

With the channel power set at the optimum for both FMF and standard single mode fiber systems, we then measured the *Q* of the central channel as a function of distance. The results are shown in Fig. 10. Without DD-LMS, QSM transmission over the FMF suffers from severe performance degradation due to MPI for all transmission distances. The detrimental effects of MPI offset the benefits of reduced nonlinearity so that the QSM transmission is inferior to standard fiber transmission. However, a joint-polarization 101-tap DD-LMS increases the *Q* considerably so that it becomes slightly better than that of the standard fiber system. The *Q* continues to improve with increasing number of taps until around 501 taps when only marginal improvement is obtained. This may imply that most of the MPI has been compensated with 301-taps DD-LMS. Furthermore, the transmission distance for a SD-FEC threshold of 2E-2 BER (or *Q* of 6.25 dB) has been extended from 1200 km to 2600 km with the help of DD-LMS. It is worth noting that at 2600 km, the calculated total accumulated MPI for the QSM transmission would be greater than −12 dB. In comparison, the standard single mode fiber system has a maximum reach of about 1500 km and the same strength DD-LMS brings negligible performance improvement, thus verifying that the DD-LMS is in fact compensating MPI in QSM systems.

To further quantify the effectiveness of DD-LMS in MPI compensation, we show the *Q* value of the central channel as a function of measured OSNR at the receiver in Fig. 11(a) for both QSM and standard fiber systems at their respective optimal signal launched powers. Note that as the optimal signal launched power is higher for QSM than standard fiber systems due to its reduced fiber nonlinearity, same OSNR actually means a higher signal launched power for QSM system with proportionately more noise, which in turn means the QSM link is longer compared to the corresponding standard fiber system with the same OSNR. The close agreements between QSM with 301- and 501-taps DD-LMS and the standard fiber suggests that the MPI in the FMF is nearly fully compensated. The improvement of the DD-LMS filter for standard fiber systems is minimal, indicating that the transceiver circuitry and components are more or less optimized and there are negligible residual impairments and the DD-LMS are solely compensating MPI effects. Furthermore, Fig. 11(b) shows the *Q* factor vs. distance at −1 and 3 dBm signal launched power and the DD-LMS provides considerable performance improvements in both cases, illustrating that the DD-LMS is not compensating fiber nonlinearity.

The DD-LMS taps after convergence allow us to recover/estimate the impulse response of MPI impairment. Alternatively, applying the method described in Ryf et al. [17], the estimated magnitude squared of the self-polarization impulse responses |*h _{xx}*(

*t*)|

^{2}and |

*h*(

_{yy}*t*)|

^{2}and cross-polarization impulse responses |

*h*(

_{xy}*t*)|

^{2}and |

*h*(

_{yx}*t*)|

^{2}are depicted in Fig. 12 for various transmission distances. The impulse responses shown are obtained by averaging estimates over 5 independent data sets. It is clear that the MPI in QSM systems are distributed in nature as its strength grows with fiber length. Also, self-polarization MPI is more dominant than cross-polarization MPI. It should be noted that the unusual spike at the

*t*< 0 region is merely an artifact of our 16-QAM generation method based on cascading a QPSK signal with its delayed and scaled version. Such configuration has no effect on the overall 16-QAM signal processing and BER performance.

## 4. Conclusions

In this paper, we analytically investigated polarization-multiplexed long-haul QSM transmission systems using 6-spatial-polarization-mode FMF parameterized by the differential mode delay and differential mode loss between the fundamental mode group and higher-order mode group. In the weak coupling regime, a multi-span QSM channel can be modeled as a Gaussian random process in frequency. Mode coupling in FMF result in MPI and additional signal loss at each span of a QSM system. We derived appropriate filters for MPI compensation and showed that they induce minimal noise enhancement and performance penalty. In addition, we experimentally demonstrated 256 Gb/s PM-16-QAM QSM transmission over a record distance of 2600 km for 100-km spans by using a DD-LMS filter to compensate MPI. We showed that QSM transmissions can be a practical and viable option for transmission reach and capacities upgrade for future long-haul systems. Further studies will include higher-order modulation formats, OFDM as well as super-channel QSM transmissions.

## Appendix I: *Derivation of the expected impulse response power for QSM transmission systems*

*Derivation of the expected impulse response power for QSM transmission systems*

We consider the auto-correlation function of *H*_{1-}* _{span}*(

*ω*) in frequency i.e.

*R*is statistically independent of

_{m}*R*for $m\ne n$, we have

_{n}*ξ*=

*e*

^{−(}

^{jω}^{Δ}

^{τ}^{+ Δ}

^{α}^{)Δ}

*,*

^{L}*K*sections, we have

*κ*Δ

^{p}*L*for

^{p}*p*≥ 3. In this case,

*K*→∞, we obtain

## Appendix II: *Derivation of the transfer function of QSM transmission systems*

*Derivation of the transfer function of QSM transmission systems*

In the weak coupling regime, we consider the channel output consists of signals that have stayed in the fundamental mode along transmission as well as accumulated MPI from signals that have ‘coupled up’ to higher-order mode and ‘coupled back down’ to fundamental mode only once during transmission. There are *K*(*K-*1)/2 such configurations in a span of *K* sections and hence *H*_{1-}* _{span}*(

*ω*) can be expressed as

*m*denotes the number of consecutive sections the signal ‘stays’ in the higher-order mode and

*x*=

_{q}*θ*

_{q}_{+1}–

*θ*+ Δ

_{q}*τ*Δ

*Lω*. Note that the

*x*’s are i.i.d. random variables with distribution U[0, 2

_{q}*π*] and is in fact independent of

*ω*due to the modulo 2

*π*nature of phase. Consequently, the distribution of

*H*

_{1-}

*(*

_{span}*ω*) is also independent of

*ω*. As

*K*→∞, ${\prod}_{k=1}^{K}\sqrt{1-{\eta}_{k}}}\to {e}^{-\kappa L/2$ and hence $E\left[{H}_{1-span}(\omega )\right]\to {e}^{-\kappa L/2}$ and

*N*-span QSM transmission system, denote

*n*span. In the weak coupling regime, the transfer function with per-span amplification gain

^{th}*e*becomes

^{κL}*N*gets large. Together with the derived $E\left[|h(t){|}^{2}\right]$ in the paper, one can show that

*H*(

*ω*) is a stationary complex Gaussian random process in

*ω*. Generalizations to the QSM transfer function matrix

*H*(

*ω*) for polarization-multiplexed transmissions in 6-spatial-polarization mode FMF systems are straight forward and are given by

## Acknowledgements

The authors would like to acknowledge the financial support of the Hong Kong Government General Research Fund (GRF) under project number PolyU 519211 and the Hong Kong Polytechnic University under project H-ZG1E and H-ZDA9.

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