PDL and CD insensitive low complexity equalizer for short reach coherent systems.

We propose a polarization dependent loss (PDL) and chromatic dispersion (CD) insensitive, low-complexity adaptive equalizer (AEQ) for short-reach coherent optical transmission systems. The AEQ contains a 1-tap butterfly finite impulse response (FIR) filter and two N-tap FIR filters. It first performs polarization demultiplexing using the 1-tap filter, of which the coefficients are obtained based on Stokes space. Then it mitigates the inter-symbol interference (ISI) using the two N-tap finite impulse response (FIR) filters and adjust the filter's coefficients by utilizing constant modulus algorithm (CMA). Through theoretical and experimental analysis, we verify that this proposed AEQ can perform robust polarization demultiplexing when PDL and CD exists. Besides, our proposed AEQ has faster convergence speed compared with recently proposed AEQs. In addition, it reduces the number of multipliers and thus reduce the computational complexity of conventional butterfly filter structure AEQ. And this proposed AEQ suffers little bit error ratio loss compared with the conventional AEQ. Due to the low-complexity and robustness to PDL and CD, this proposed AEQ is well-suited for future low-cost short-reach optical communication system.

Application analysis of clipping and digital resolution enhancer in high-speed direct-detection PAM4 transmission.

In this paper, the application of a clipping and digital resolution enhancer (DRE) is numerically investigated in 56-GBaud direct-detection four-ary pulse amplitude modulation (PAM4) transmission systems. The influence of the tap length and the digital-to-analog converter (DAC) samples per symbol on DRE gain is first studied. After optimizing clipping probability, sampling jitter is introduced. The combination of clipping and DRE can increase jitter tolerance by ∼1.7% sampling time for 4-bit DAC. Then, the required optical signal-to-noise ratio (OSNR) at the hard-decision forward error correction (HD-FEC) threshold of 3.8×10-3 is investigated in back-to-back case and 80-km fiber transmission. It is shown that the combination of clipping and DRE can reduce the required OSNR significantly for 3-bit and 4-bit DAC. Finally, the performance gain introduced by clipping and DRE is analyzed from a perspective of the transmitted average signal power and the received mean-squared quantization error.

Low-complexity storage-reduced digital spectrum-based soft-failure management with Welch's method.

In this paper, we propose a low-complexity storage-reduced digital spectrum-based soft failure management solution including soft failure detection (SFD), identification (SFI) and failure magnitude estimation (FME). Five soft failures are considered. Random fluctuation of key link parameters is introduced in simulations to investigate the robustness of the proposed solution. To reduce computational complexity and storage requirement for digital spectrum calculation, Welch's method is employed instead of applying fast Fourier transform on a long sampling sequence. A false positive rate below 1% and a false negative rate below 3% are achieved for SFD after extensive numerical simulations. Besides, SFI realizes an identification accuracy of 97.4%. The mean square errors of FME for different soft failures are all below 0.4. Finally, with a very small segment length of 25, 46.2% of computational complexity and 99.6% of storage can be reduced for digital spectrum calculation.

Loss weight adaptive multi-task learning based optical performance monitor for multiple parameters estimation.

A loss weight adaptive multi-task learning based artificial neural network (MTL-ANN) is applied for joint optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI). We conduct an experiment of polarization division multiplexing (PDM) coherent optical system with 5 km standard single mode fiber (SSMF) transmission to verify this monitor. A group of modulation schemes including nine modulation adaptive M-QAM formats are selected as the transmission signals. Instead of circular constellation, signals' amplitude histograms after constant module algorithm (CMA) based polarization de-multiplexing are selected as input features for our proposed monitor. The experimental results show that the MFI accuracy reaches 100% in the estimated OSNR range. Furthermore, when treated as regression problem and classification problem, OSNR estimation with a root mean-square error (RMSE) of 0.68 dB and an accuracy of 98.7% are achieved, respectively. Unlike loss weight fixed MTL-ANN, loss weight adaptive MTL-ANN could search the optimal loss weight ratio automatically for different link configurations. Besides that, the number of estimated parameters can be easily expanded, which is attractive for multiple parameters estimation in future heterogeneous optical networks.

Intelligent optical performance monitor using multi-task learning based artificial neural network.

An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The results obtained from simulation and experiment of NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% for the three modulation formats under consideration. Furthermore, OSNR monitoring with mean-square error (MSE) of 0.12 dB and accuracy of 100% is achieved while regarding it as regression problem and classification problem, respectively. In this intelligent optical performance monitor, only a single MTL-ANN is deployed, which enables reduced-complexity optical performance monitor (OPM) devices for multi-parameters estimation in future heterogeneous optical network.

Single-photodiode 112-Gbit/s 16-QAM transmission over 960-km SSMF enabled by Kramers-Kronig detection and sparse I/Q Volterra filter.

We have experimentally demonstrated a single-photodiode 112-Gbit/s 16-QAM transmission over 960-km standard single mode fiber with Kramers-Kronig (KK) detection and a sparse I/Q Volterra filter (VF). KK detection is used to mitigate the signal to signal beating interference. A novel I/Q VF based on dual-input real-valued Volterra series is proposed to overcome the constraints of non-linear distortions. Two conventional single-input real-valued VFs are employed as a contrast to prove the necessity of I/Q hybrid structure in I/Q VF when the system suffers from severe I/Q imbalance and crosstalk. The proposed I/Q VF brings nearly two order magnitude improvement in BER performance compared with the conventional linear equalizer for back to back case and doubles the transmission distance from 480 km to 960 km at the hard-decision forward error correction threshold of 3.8 × 10-3. To reduce the complexity of full I/Q VF, a simple ℓ1 regularization-based least mean square (LMS) algorithm is employed to identify the significant kernels and construct a sparse I/Q VF. Compared with full I/Q VF, the sparse I/Q VF reduces up to 58% complexity at 960 km while having the similar BER performance.

Nonlinear equalization based on pruned artificial neural networks for 112-Gb/s SSB-PAM4 transmission over 80-km SSMF.

A pruning method of artificial neural network based nonlinear equalizer (ANN-NLE) is proposed and validated for single-sideband 4-ary pulse amplitude modulation (SSB-PAM4) in IM/DD system. As a classifier, ANN is capable to form a complex nonlinear boundary among different classifications, which is considered as an appropriate way to mitigate the nonlinear impairments in optical communication system. In this paper, first, we introduce the operation principle of the traditional linear equalizer (LE) and NLE such as volterra equalizer (VE). Then we make an analogy among the LE, VE and ANN-NLE. After that, a novel pruning method is applied to reduce the complexity of ANN. The BER performance of ANN-NLE outperforms VE after fiber transmission. After 60 km fiber transmission, ANN-NLE decreases the BER by about one order of magnitude compared to VE. By implementing the proposed pruning method, the connections of ANN reduced by a factor of 10x while keeping the BER under the threshold of 3.8x10-3.