No abstract

Elias Giacoumidis, et al, 'Volterra-Based Reconfigurable Nonlinear Equalizer for Coherent OFDM', IEEE Photonics Technology Letters, Vol 26 (14): 1383-1386, June 2014, doi: https://doi.org/10.1109/LPT.2014.2321434. Published by IEEE.A reconfigurable nonlinear equalizer (RNLE) based on inverse Volterra series transfer function is proposed for dual-polarization (DP) and multiband coherent optical orthogonal frequency-division multiplexing (OFDM) signals. It is shown that the RNLE outperforms by 2 dB the linear equalization in a 260-Gb/s DP-OFDM system at 1500 km. The RNLE improves the tolerance to inter/intraband nonlinearities, being independent on polarization tributaries, modulation format, signal bit rate, subcarrier number, and distance

We experimentally demonstrate ∼2  dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40  Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4  dBQ-factor enhancement at 70  Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2  dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN.

No abstract

Digital-based artificial neural network (ANN) machine learning is harnessed to reduce fiber nonlinearities, for the first time in ultra-spectrally-efficient optical fast orthogonal frequency division multiplexed (Fast-OFDM) signals. The proposed ANN design is of low computational load and is compared to the benchmark inverse Volterra-series transfer function (IVSTF)-based nonlinearity compensator. The two aforementioned schemes are compared for long-haul single-mode-fiber-based links at 9.69 Gb/s direct-detected optical Fast-OFDM signals. It is shown that an 80 km extension in transmission-reach is feasible when using ANN compared to IVSTF. This occurs because ANN can tackle stochastic nonlinear impairments, such as parametric noise amplification. Using ANN, the dynamic parameters requirements of the sub-ranging quantizers can also be relaxed compared to linear equalization, such as the reduction of the optimum clipping ratio and quantization bits by 2 dB and 2-bits, respectively, and by 2 dB and 2 bits when compared to the IVTSF equalizer.

A number of critical issues for dual-polarization single-and multi-band optical orthogonal-frequency division multiplexing (DP-SB/MB-OFDM) signals are analyzed in dispersion compensation fiber (DCF)-free long-haul links. For the first time, different DP crosstalk removal techniques are compared, the maximum transmission-reach is investigated, and the impact of subcarrier number and high-level modulation formats are explored thoroughly. It is shown, for a bit-error-rate (BER) of 10 −3 , 2000 km of quaternary phase-shift keying (QPSK) DP-MB-OFDM transmission is feasible. At high launched optical powers (LOP), maximum-likelihood decoding can extend the LOP of 40 Gb/s QPSK DP-SB-OFDM at 2000 km by 1.5 dB compared to zero-forcing. For a 100 Gb/s DP-MB-OFDM system, a high number of subcarriers contribute to improved BER but at the cost of digital signal processing computational complexity, whilst by adapting the cyclic prefix length the BER can be improved for a low number of subcarriers. In addition, when 16-quadrature amplitude modulation (16QAM) is employed the digital-toanalogue/analogue-to-digital converter (DAC/ADC) bandwidth is relaxed with a degraded BER; while the 'circular' 8QAM is slightly superior to its 'rectangular' form. Finally, the transmission of wavelength-division multiplexing DP-MB-OFDM and single-carrier DP-QPSK is experimentally compared for up to 500 Gb/s showing great potential and similar performance at 1000 km DCF-free G.652 line.

Coherent fiber-optic communication systems are limited by the Kerr-induced nonlinearity. Benchmark optical and digital nonlinearity compensation techniques are typically complex and tackle deterministic-induced nonlinearities. However, these techniques ignore the impact of stochastic nonlinear distortions in the network, such as the interaction of fiber nonlinearity with amplified spontaneous emission from optical amplification. Unsupervised machine learning clustering (e.g., K-means) has recently been proposed as a practical approach to the blind compensation of stochastic and deterministic nonlinear distortions. In this work, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is employed, for the first time, for blind nonlinearity compensation. DBSCAN is tested experimentally in a 40 Gb/s 16 quadrature amplitude-modulated system at 50 km of standard single-mode fiber transmission. It is shown that at high launched optical powers, DBSCAN can offer up to 0.83 and 8.84 dB enhancement in Q-factor when compared to conventional K-means clustering and linear equalisation, respectively.

This paper presents a long-reach orthogonal frequency division multiplexing wavelength division multiplexing passive optical network (OFDM WDM-PON), a system capable of delivering 100  Gb/s of data downstream and 2  Gb/s of data upstream on a single wavelength. The optical sources for downstream data and upstream data are a continuous-wave laser at a central office and a reflective semiconductor optical amplifier (RSOA) at each optical network unit.