Orbital angular momentum (OAM) mode-division multiplexing (MDM) is a key technique to achieve ultra-high-capacity optical fiber communications. However, the high nonlinear impairment from optoelectronic devices, such as spatial light modulators, modulators, and photodiodes, is a long-standing challenge for OAM-MDM. In this paper, an equalizer based on a probabilistic neural network (PNN) is presented to mitigate the nonlinear impairment for an OAM-MDM fiber communication system with 32 GBaud Nyquist pulse amplitude modulation-8 (PAM8) intensity-modulation direct-detection (IM-DD) signals. PNN equalizer can calculate the distribution of the nonlinearity using Bayesian decision theory and thus mitigate the stochastic nonlinear impairment of the received signal. Experimental results show that compared with the convolutional neural network (CNN) equalizer, the PNN equalizer improves the receiver sensitivity by 0.6dB and 2dB for two OAM modes with l = + 3 and l = + 4 at the 20% FEC limit, respectively. Moreover, compared with Volterra or CNN equalizers, the PNN equalizer can reduce the computation complexity significantly, which has great potential to mitigate the nonlinear signal distortions in high-speed IM-DD OAM-MDM fiber communication systems.
A twin-single-sideband (twin-SSB) signal single-photodiode (PD) detection system without optical bandpass filter is experimentally demonstrated for the first time. After direct detection by a single-ended PD at the receiver side, we can directly separate the optical left sideband (LSB) and right sideband (RSB) using a simple one-path digital signal processing algorithm without separating the two sideband signals using an optical bandpass filter (OBPF), thus achieving lower complexity and low cost while doubling the spectral efficiency. Using our proposed twin-SSB scheme, we demonstrate 1-, 2-, and 4-Gbaud LSB geometric shaping 4-quadrature amplitude modulation and RSB quadrature phase shift keying signal transmission over 10 km of single-mode fiber (SMF). Our experimental results demonstrate that the bit-error rate (BER) of the 4-Gbaud LSB geometric shaping 4-quadrature amplitude modulation (GS-4QAM) and RSB quadrature phase shift keying (QPSK) transmission system is below the 7% hard decision forward error correction threshold.
Nonlinear impairment in a high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication system presents high complexity and strong stochasticity due to the massive optoelectronic devices. In this paper, we propose an Affinity Network (AffinityNet) nonlinear equalizer for an OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with four OAM modes. The labeled training and testing signals from the OAM-MDM system can be regarded as “small sample” and “large target”, respectively. AffinityNet can be used to build an accurate nonlinear model using “small sample” based on few-shot learning and can predict the stochastic characteristic nonlinearity of OAM-MDM with a high level of generalization. As a result, the AffinityNet nonlinear equalizer can effectively compensate the stochastic nonlinearity in the OAM-MDM system, despite the large difference between the training and testing signals due to the stochastic nonlinear impairment. An experiment was conducted on a 400 Gbit/s transmission with four OAM modes using a pulse amplitude modulation-8 (PAM-8) signal over a 2 km ring-core fiber (RCF). Our experimental results show that the proposed nonlinear equalizer outperformed the conventional Volterra equalizer with improvements in receiver sensitivity of 1.7, 1.8, 3, and 3.3 dB for the four OAM modes at the 15% forward error correction (FEC) threshold, respectively. In addition, the proposed equalizer outperformed a convolutional neural network (CNN) equalizer with improvements in receiver sensitivity of 0.8, 0.5, 0.9, and 1.4 dB for the four OAM modes at the 15% FEC threshold. In the experiment, a complexity reduction of 37% and 83% of the AffinityNet equalizer is taken compared to the conventional Volterra equalizer and CNN equalizer, respectively. The proposed equalizer is a promising candidate for a high-speed OAM-MDM optical fiber communication system.
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