Paired-subcarrier equalization for phase noise and transmitter IQ skew in digital subcarrier multiplexing system.

The digital subcarrier multiplexing (DSCM) transmission scheme is expected for future ultra-large baud rate transmission. However, the phase noise and transmitter (Tx) IQ skew tolerance are decreased due to the narrow sub-band transmission and conjugated interference from symmetric subcarrier. In this paper, we propose a paired-subcarrier equalization scheme to jointly mitigate the phase noise and Tx IQ skew. We use a phase locking loop (PLL) embedded 4 × 4 MIMO equalizer to simultaneously realize polarization demultiplexing, phase noise and Tx IQ skew compensation. The 4 × 4 MIMO can deal with the paired-subcarrier interference in the DSCM transmission. Besides, since the inner subcarrier suffers smaller interference from its symmetric subcarrier, we estimate the phase noise by inner subcarriers and share the phase noise information with other subcarriers to reduce the overall complexity. Through simulations of 100-GBaud 64-QAM DSCM coherent optical fiber transmission consisting of eight 12.5-Gbaud subcarriers and experiment of 10-GBaud four-subcarriers PM-16QAM transmission, we find that the PLL embedded equalizer for DSCM scheme exhibits better skew and phase noise compensation ability compared with other equalizers. Additionally, we compare the performance of single-carrier and DSCM schemes with the proposed equalizers in simulation. The influence of phase noise and Tx IQ skew on DSCM transmission can be largely relaxed.

Partially decoupled polarization demultiplexing and phase noise equalizer for Alamouti code-based simplified coherent systems.

Alamouti space-time block code (STBC) combined with a simple heterodyne coherent receiver can realize polarization-insensitive phase-diversity detection to reduce the cost. In the receiver, a joint equalizer has been used for STBC's polarization demultiplexing and phase tracking. However, the joint equalizer requires two different step size parameters to update the tap weight coefficients for polarization demultiplexing and the phase noise estimation. This leads to the search process being complex so requiring more iterations for convergence. In this paper, we propose a partially decoupled equalizer that consists of a polarization and phase decoupled equalizer (PPDE) and a pilot-aided blind phase search (P-BPS) algorithm to accelerate the convergence and improve the phase noise tolerance. By theoretically calculating the phase noise, the PPDE can achieve polarization demultiplexing with only one single step size parameter, thus suppressing the searching space and greatly reducing the iterations required for convergence. In the carrier phase recovery stage, the P-BPS algorithm can effectively improve the phase noise tolerance and solve the cyclic slip problem of BPS. We conduct numerical simulations and an experiment to transmit a quadrature phase-shift keying (QPSK) signal. The results demonstrate that the number of iterations required for PPDE convergence is only half of that of the joint equalizer while maintaining polarization-insensitive characteristics in large phase noise. Meanwhile, the achievable linewidth tolerance of P-BPS is increased by three times compared with DD-LMS.

Burst errors suppression for MLSE in high-speed IM/DD transmission systems using PAM.

Maximum likelihood sequence estimation (MLSE) is the optimal signal sequence detection that can remove the inter-symbol interference (ISI). However, we find that the MLSE causes burst consecutive errors alternating between +2 and -2 in M-ary pulse amplitude modulation (PAM-M) IM/DD systems with large ISI. In this paper, we propose to use precoding to suppress the burst consecutive errors resulted from MLSE. A 2 M modulo operation is employed to guarantee that the probability distribution as well as the peak-to-average power ratio (PAPR) of encoded signal remain unchanged. After the receiver-side MLSE, the decoding process that involves adding the current MLSE output to the previous one and applying a 2 M modulo is implemented to break the burst consecutive errors. We conduct experiments to transmit 112/150-Gb/s PAM-4 or beyond 200-Gb/s PAM-8 signals at C-band to investigate the performance of the proposed MLSE integrated with precoding. The results show that the precoding can break burst errors effectively. For 201-Gb/s PAM-8 signal transmission, the precoding MLSE can achieve 1.4-dB receiver sensitivity gain and reduce the maximum length of burst consecutive errors from 16 to 3.

Advanced nonlinearity equalizer with TC-NL-MLSE for transmitting beyond 200-Gb/s PAM-8 in IM/DD systems.

The severe band-limited effect resulted from the low-cost optical transceiver increases the channel memory length and the number of taps of the equalizers. Besides, the interaction of fiber dispersion and square-law detection introduce nonlinear distortions in intensity modulation and direct-detection (IM/DD) transmission systems. The serious band-limited effect and nonlinear distortions degrade the transmission performance and bring challenges to current equalizers for low-complexity implementation. In this paper, we propose a trellis-compression nonlinear maximum likelihood sequence estimation (TC-NL-MLSE) algorithm to compensate the linear and nonlinear distortions with lower complexity. In the TC-NL-MLSE, we introduce a polynomial nonlinear filter (PNLF) to partly compensate both the linear distortions and nonlinear distortions. Then, we establish a look-up-table (LUT) to calculate the nonlinear branch metric (BM). To simplify the calculation, two or three levels with the highest probabilities are selected according to decision thresholds for each symbol to compress the state-trellis graph (STG). This significantly reduces computational complexity on BM calculations especially for high-order modulations. We conduct experiments to transmit beyond the 200-Gb/s PAM-8 signal over 2-km standard single mode fiber (SSMF) at C-band. The TC-NL-MLSE outperforms the reduced-state MLSE with PNLF, and can reach the 7%-overhead hard-decision forward error correction threshold. Moreover, the TC-NL-MLSE reduces the complexity by 97% compared with standard LUT-MLSE, limiting the multipliers around 100 at the expense of only 0.2-dB receiver sensitivity penalty.

Design of fully interpretable neural networks for digital coherent demodulation.

In this paper, we propose a digital coherent demodulation architecture using fully interpretable deep neural networks (NNs). We show that all the conventional coherent digital signal processing (DSP) is deeply unfolded into a well-structured NN so that the established training algorithms in machine learning can be applied. In contrast to adding or replacing certain algorithms of existing DSP in coherent receivers, we replace all the coherent demodulation algorithms with a fully interpretable NN (FINN), making the whole NN interpretable. The FINN is modular and flexible to add or drop modules, including chromatic dispersion compensation (CDC), the digital back-propagation (DBP) algorithm for fiber nonlinearity compensation, carrier recovery and residual impairments. The resulted FINN can be quickly initialized by straightforwardly referring to the conventional DSP, and can also enjoy further performance enhancement in the nonlinear fiber transmissions by NN. We conduct a 132-Gb/s polarization multiplexed (PM)-16QAM transmission experiment over 600-km standard single mode fiber. The experimental results show that without fiber nonlinearity compensation, FINN-CDC obtains less than 0.06-dB SNR gain than chromatic dispersion compensation (CDC). However, with fiber nonlinearity compensation, 2-steps per span FINN-DBP (FINN-2sps-DBP) and FINN-1sps-DBP bring about 0.59-dB and 0.53-dB SNR improvement compared with the conventional 2sps-DBP and 1sps-DBP, respectively.

Multi-constraint Gerchberg-Saxton iteration algorithms for linearizing IM/DD transmission systems.

Chromatic dispersion-enhanced signal-signal beating interference (SSBI) considerably affects the performance of intensity-modulation and direct-detection (IM/DD) fiber transmission systems. For recovering optical fields from received double sideband signals after propagating through IM/DD transmission systems, Gerchberg-Saxton (G-S) iterative algorithms are promising, which, however, suffers slow convergence speeds and local optimization problems. In this paper, we propose a multi-constraint iterative algorithm (MCIA) to extend the Gerchberg-Saxton-based linearized detection. The proposed technique can accelerate the convergence speed and realize nonlinear-equalization-free detection. Based on the data-aided iterative algorithm (DIA) and the decision-directed data-aided iterative algorithm (DD-DIA), the proposed technique reuses redundant bits from channel coding to not only correct decision errors but also enforce the constraints on the task function to further accelerate the whole optical field retrieval processing. Simulation results show that, compared with the DD-DIA, the MCIA reduces the received optical power (ROP) by about 1.5-dB for a 100-Gb/s over 50-km SSMF PAM-4 signal transmission at the symbol error rate (SER) of 2×10-2. For a 100-Gb/s over 400-km SSMF transmission system, just 30 MCIA iterations is needed, which is 30% reduction in iteration count compared with the DD-DIA. For further increased transmission capacities, the MCIA can improve the SER by two orders of magnitude compared with the conventional IA. To validate the effectiveness of the MCIA, we also conduct experiments to transmit 92-Gb/s PAM-4 signals over 50-km IM/DD fibre systems. We find that the MCIA has a 1-dB ROP improvement compared with the DD-DIA. Compared with Volterra nonlinear equalization, the BERs of the MCIA with a simple linear equalizer are reduced by more than one order of magnitude with only 52 MCIA iterations.

Panax ginseng ginsenoside-Rg2 protects memory impairment via anti-apoptosis in a rat model with vascular dementia.

ETHNOPHARMACOLOGICAL RELEVANCE: Ginsenosides, the major active ingredients of Panax ginseng, produce a variety of pharmacological or physiological responses with effects on the central and peripheral nervous systems. AIM OF THE STUDY: In this report, we investigated the effects of ginsenoside Rg2 on cerebral ischemia-reperfusion induced impairment of neurological responses, memory and caudate-putamen neuronal apoptosis in a vascular dementia (VD) rat model. MATERIALS AND METHODS: Neurological evaluation was performed 24h after reperfusion and Y-maze memory performance was assessed at 48 h after reperfusion. Immunocytochemical techniques were employed to check the protein expression of BCL-2, BAX, heat shock protein 70 and P53, which are related with cell apoptosis. RESULTS: Neurological responses and memory ability of the ginsenoside Rg2 or nimodipine groups improved significantly compared with the VD group. The expression of BCL-2 and HSP70 were decreased, while BAX and P53 were increased in the VD model. The expression of BCL-2 and HSP70 proteins were increased, while BAX and P53 decreased after ginsenoside Rg2 (2.5, 5 and 10mg/kg) and nimodipine (50 microg/kg) treatment compared with the VD group. The study suggests that ginsenoside Rg2 improved neurological performance and memory ability of VD rats through mechanisms related to anti-apoptosis. CONCLUSIONS: The capacity for ginsenoside Rg2 to modulate the expression of apoptotic related proteins suggests that ginsenoside Rg2 may represent a potential treatment strategy for vascular dementia or other ischemic insults.