Coherent Optical Communication Systems Research Articles

Implementation of Optical Coherent Communication System between Two Computers

This work represents implementation and investigation of optical coherent communication system between two computers. A single mode optical fiber is selected as transmission medium. The data are sent via the RS-232 standard interface with a bit rate of 9.6 kbps from personal computer (PC1) by line receive to convert the data from electrical levels (-12/+12 V) into TTL level (0/5 V). The modulation of this data was accomplished by internal modulation using laser diode type (HFCT-5208M) 1310 nm wavelength. The optical D-coupler was used to combine the optical signal that come from laser source with optical signal of laser local oscillator (OTS-304XI) at 1310/1550 nm wavelength to obtain coherent (homodyne and heterodyne) detection respectively. A PIN photodetector (HFCT-5208M) is used. Calculations of Signal to Noise Ratio (SNR) and Bit Error Rate (BER) for coherent detection were measured at different length of the optical fiber. Result show that high SNR and low BER for heterodyne detection than for homodyne detection.

Modulation Format Recognition Scheme Based on Discriminant Network in Coherent Optical Communication System

In this paper, we skillfully utilize the discriminative ability of the discriminator to construct a conditional generative adversarial network, and propose a scheme that uses few symbols to achieve high accuracy recognition of modulation formats under low signal-to-noise ratio conditions in coherent optical communication. In the one thousand kilometres G.654E optical fiber transmission system, transmission experiments are conducted on the PDM-QPSK/-8PSK/-16QAM/-32QAM/-64QAM modulation format at 8G/16G/32G baud rates, and the signal-to-noise ratio parameters are traversed under experimental conditions. As a key technology in the next-generation elastic optical networks, the modulation format recognition scheme proposed in this paper achieves 100% recognition of the above five modulation formats without distinguishing signal transmission rates. The optical signal-to-noise ratio thresholds required to achieve 100% recognition accuracy are 12.4 dB, 14.3 dB, 15.4 dB, 16.2 dB, and 17.3 dB, respectively.

Performance analysis of optimized equilibrium optimizer algorithm in coherent free-space optical communication system

Sensor-less adaptive optics (SLAO) is commonly employed in coherent free-space optical communication (CFSOC) system due to its capacity to mitigate the impact of atmospheric turbulence. The control algorithm determines the SLAO system's capacity to efficiently recorrect wavefront aberrations. In this study, we apply an Optimized Equilibrium Optimizer (OEO) algorithm as a control algorithm to the CFSOC system, the dynamic parameters and search framework of the Equilibrium Optimizer (EO) are modified to enhance the algorithm's resilience in strong atmospheric turbulence. Both theoretical analysis and simulation results demonstrate that the OEO algorithm exhibits exceptional calibration performance and robustness, effectively enhancing ME and reducing BER. In the simulation, the Stochastic Parallel Gradient Descent (SPGD) algorithm takes 10 times longer to achieve the same performance as the OEO algorithm. Meanwhile, the OEO algorithm and the other 6 algorithms were simulated with strong turbulence. Results demonstrated that the OEO algorithm outperforms other algorithms. The OEO algorithm is suitable for SLAO systems to enhance the communication quality of the CFSOC systems.

Amplitude-boosting attack against practical discrete-modulated continuous-variable quantum key distribution

Discrete-modulated continuous-variable quantum key distribution offers significant practical deployment advantages due to its straightforward state preparation and high compatibility with coherent optical communication systems. However, security analysis and parameter estimation of discrete-modulated protocol are different with Gaussian-modulated protocols, which could cause different practical security problems. Herein, we investigate the amplitude-boosting attack against discrete-modulated continuous-variable quantum key distribution systems and assess its impact on system performance. Our findings reveal that this attack could cause overestimation of secret key rate perceived by Alice and Bob, thereby opening a security loophole, and the vulnerability could be severer than Gaussian modulation. Additionally, we summarize defensive countermeasures, marking a crucial step towards enhancing the practical security of discrete-modulated continuous-variable quantum key distribution.

Low complexity and finer granularity quantization scheme for perturbation-based fiber nonlinearity compensation in coherent optical communication systems

In the efficient implementation of perturbation theory-based nonlinearity compensation method for reliable fiber-optic coherent communication systems, different quantization schemes have been proposed to reduce the required computational and implementation complexity. For example, the k-means clustering algorithm focused on reducing the number of perturbation coefficients to alleviate the burden of calculating the perturbation terms. In this paper, from the bit-level architectures of multipliers, we propose a multi-segment mixed-word-length quantization scheme that assigns different word lengths for the quantized perturbative coefficients to save computational resources, where Bayesian optimization is employed to derive the optimal hyperparameters involved in this scheme. The proposed scheme was evaluated by numerical simulations of single-channel and multi-channel optical fiber communication systems with dual-polarization 16-QAM modulation. The comprehensive numerical simulation results show that our proposed scheme demonstrates a complexity reduction of more than 65% without performance degradation compared with the traditional uniform quantization method with fixed-word-length, and was robust to the fiber length and baud-rate. We also carried out an experiment of single-carrier transmission over 18 × 100 km standard single-mode fiber with 20 Gbaud single-polarization 16-QAM signal. Similar to the numerical results, the hardware complexity can be reduced by 70.7% with negligible performance deterioration over the uniform quantization scheme. The proposed scheme shows great potential in real-world applications.

Experimental demonstration of quantum encryption in phase space with displacement operator in coherent optical communications

We provide experimental validation of quantum encryption in phase space using displacement operators in coherent states (DOCS) in a conventional coherent optical communication system. The proposed encryption technique is based on displacing the information symbols in the phase space using random phases and amplitudes to achieve encryption randomly and provide security at the physical layer. We also introduce a dual polarization encryption approach where we use two different and random DOCS to encrypt the X and Y polarizations separately. The experimental results show that only authorized users can decrypt the signal correctly, and any mismatch in the displacement operator coefficients, amplitudes, or phases will lead to a bit error ratio (BER) of approximately 50%. We also compare the performance of the system with and without encryption over 80 km of standard-single mode fiber (SSMF) transmission to assess the added penalty of such encryption. The achieved net bit rates are 224, 448, and 560 Gb/s for QPSK, 16QAM, and 32QAM modulation formats, respectively. The experimental results showcase the efficacy of the DOCS encryption technique in resisting various decryption attempts, demonstrating its effectiveness in ensuring the security and confidentiality of transmitted data in a real-world transmission scenario.

Low-complexity two-stage carrier phase recovery using principal component reconstruction analysis and optimal decision maximum likelihood for PS-MQAM systems

A low-complexity two-stage carrier phase recovery (CPR) scheme based on principal component reconstruction analysis and optimal decision maximum likelihood (PCRA-OML) is proposed for probabilistic shaping (PS)-M quadrature amplitude modulation (QAM) coherent optical communication systems. In the first stage, symbols on the QPSK-shaped ring are selected, their amplitude noise is eliminated, and their amplitudes are increased, thus completing the reconstruction of the principal component. Lastly, the carrier phase is recovered using principal component phase estimation (PCPE). In the second stage, a maximum likelihood phase estimation algorithm based on optimal decision-making is employed to further enhance the stability and robustness of the scheme. The effectiveness of the proposed scheme is validated through 28 GBaud polarization division multiplexing PS-64QAM simulations and 28 GBaud PS-16QAM experiments. The experimental results indicate that in the PS-16QAM entropy of 3 bit/symbol system, when the threshold for normalized generalized mutual information is 0.9, the proposed scheme provides a 1.7 dB optical signal-to-noise ratio (OSNR) gain compared to blind phase search (BPS), and an additional 0.9 dB OSNR gain compared to the PCPE scheme. The proposed PCRA-OML scheme exhibits versatility across various shaping strengths and is less susceptible to probabilistic influences than the BPS and PCPE schemes. Additionally, under the premise of comparable performance in the PS-64QAM system, the proposed scheme reduces over 90% of the computational complexity associated with multiplication compared to BPS. In the PS-16QAM system, the proposed scheme's real multiplication complexity is only 17.8% of BPS, achieving an overall O(N) complexity.

Low complexity equalization in coherent optical communication based on Fermat number transform.

In order to reduce the power consumption of digital signal processing (DSP) in a coherent optical communication system, a low complexity equalization scheme in DSP flow of a 400 Gb/s DP-16QAM system has been proposed. This scheme is based on Fermat number transform (FNT), which sequentially performs static equalization (SE) and dynamic equalization (DE) in the transform domain. For different distances, the proposed scheme finds the optimal solution under the condition that transform length and data bit width are mutually restricted under different transmission distances while achieving low complexity and optimal performance. The experimental results show that the adopted transform-domain equalization (TrDE) scheme has much lower computational complexity than the traditional frequency-domain equalization (FDE) and time-domain equalization (TDE) nearly without any performance loss. In the 80, 160, and 240 km scenarios, the number of multiplier is reduced by more than 72%, and the advantage becomes more obvious as the transmission capacity increases.

High-Capacity Coherent WDM Networks Empowered by Probabilistic Shaping and End-to-End Deep Learning

To optimize the functionality of coherent optical fiber communication (OFC) systems and enhance their capacity related to long-haul transmissions, wavelength-division multiplexing (WDM) and probabilistic constellation shaping (PCS) techniques have been used. This paper develops an end-to-end (E2E) deep learning (DL)-based PCS algorithm, i.e., autoencoder (AE) for a high-order modulation format WDM system that minimizes nonlinear effects while ensuring high capacity and considers system parameters, in particular those related to the OFC channel. Only the AE of the central channel is trained to meet the specified performance objective, as the system design employs identical AEs in each WDM channel. The simulation results show that the architecture should consist of two hidden layers, with thirty two nodes per hidden layer and a ”32×modulation order” batch size to obtain optimal system performance, when designing AE using a dense layer neural network. The behavior of the AE is examined to determine the optimum launch-power ranges that enhance the system's performance. The developed AE-based PCS-WDM provides a 0.4 shaping gain and outperforms conventional solutions.

Capacity enhancement through entropy loading with probabilistically shaped signals in a frequency comb-based transmission system.

We demonstrate a multichannel entropy loading mechanism in an optical frequency comb-based coherent communication system. In high-capacity wavelength division multiplexing communications, the individual laser sources can be replaced by an optical frequency comb, thus reducing the complexity and energy consumption of the transmitter. However, the power variation among different comb lines will lead to performance discrepancies. Spectral flattening filters can be adopted to suppress the variation at the expense of an additional system loss. Alternatively, by applying probabilistic shaping, we have implemented multichannel entropy loading to facilitate a continuous adaptation of the source entropy. The data rate can be dynamically allocated according to the performance of each channel. Through the loading scheme, the non-uniform performances across the channels are effectively mitigated, achieving a capacity enhancement of 34.91 Gbit/s.

Combined modulation format identification and optical signal-to-noise ratio monitoring with high accuracy and generalizability based on a proposed fused module few-shot learning algorithm in dynamic coherent optical transmissions

Modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring are important portions of optical performance monitoring (OPM) for future dynamic optical networks. In this paper, we proposed a fusion module few-shot learning (FMFSL) algorithm as an improvement upon the ordinary few-shot learning algorithms for image recognition with the specialty in adopting a combination of a dilated convolutional group and an asymmetric convolutional group to advance the feature extraction. FMFSL algorithm is applied in MFI and OSNR monitoring in coherent optical communication systems with its performance investigated in both back-to-back and fiber transmission scenarios using small-scale constellation diagrams. The results show that FMFSL algorithm can achieve 100% accuracy in MFI and higher OSNR monitoring accuracy compared to the few-shot learning algorithms Deep Nearest Neighbor Neural Network (DN4) and Prototypical Nets (PN) with 2.14% and 4.28% for 64QAM and 3.38% and 8.06% for 128QAM, respectively, without much increase in time consumption. Furthermore, the trained FMFSL algorithm remains excellent in MFI and OSNR monitoring without retraining while employed in back-to-back transmission scenarios with smaller OSNR intervals and fiber transmission scenarios with different amounts of Kerr nonlinearity, demonstrating its high capabilities in generalization and robustness. FMFSL algorithm provides a potential solution for OPM in future dynamic optical networks as a novel machine learning tool.

Exploration of Four-Channel Coherent Optical Chaotic Secure Communication with the Rate of 400 Gb/s Using Photonic Reservoir Computing Based on Quantum Dot Spin-VCSELs

In this work, we present a novel four-channel coherent optical chaotic secure communication (COCSC) system, incorporating four simultaneous photonic reservoir computers in tandem with four coherent demodulation units. We employ a quartet of photonic reservoirs that capture the chaotic dynamics of four polarization components (PCs) emitted by a driving QD spin-VCSEL. These reservoirs are realized utilizing four PCs of a corresponding reservoir QD spin-VCSEL. Through these four concurrent photonic reservoir structures, we facilitate high-quality wideband-chaos synchronization across four pairs of PCs. Leveraging wideband chaos synchronization, our COCSC system boasts a substantial 4 × 100 GHz capacity. High-quality synchronization is pivotal for the precise demasking or decoding of four distinct signal types, QPSK, 4QAM, 8QAM and 16QAM, which are concealed within disparate chaotic PCs. After initial demodulation via correlation techniques and subsequent refinement through a variety of digital signal processing methods, we successfully reconstruct four unique baseband signals that conform to the QPSK, 4QAM, 8QAM and 16QAM specifications. Careful examination of the eye diagrams, bit error rates, and temporal trajectories of the coherently demodulated baseband signals indicates that each set of baseband signals is flawlessly retrieved. This is underscored by the pronounced eye openings in the eye diagrams and a negligible bit error rate for each channel of baseband signals. Our results suggest that delay-based optical reservoir computing employing a QD spin-VCSEL is a potent approach for achieving multi-channel coherent optical secure communication with optimal performance and enhanced security.

Investigation of Costas loop phase deviation effect on BER performance of space downlink coherent communication system with DPSK scheme

The Costas loop is an important technology for synchronous demodulation in space coherent communication. However, due to the limitation of the loop device and processing technology, it is difficult to achieve high-precision locking, which results in the Costas loop phase deviation and further affects the quality of the demodulation signal. In this paper, a closed-form bit error rate (BER) model is derived to evaluate the Costas loop phase deviation effect on BER performance in the space differential phase shift keying (DPSK) modulation and heterodyne detection communication system, considering laser phase noise, atmospheric turbulence, and detector noise. Based on the BER model, analytical solution simulation is conducted. The results show that the BER performance deteriorates varying with the increase of the Costas loop phase deviation. In addition, we research how to better balance the laser linewidth and Costas loop accuracy in the system design to ensure good communication status. We find that the wider the laser linewidth, the more stringent the Costas loop accuracy. Furthermore, the BER performance versus the Costas loop phase deviation under different satellite-to-ground communication system parameter settings including divergence angle, receiving aperture, signal laser power, and data rate are analyzed. This work provides valuable references for space optical coherent communication systems design.

Transformer-Based Nonlinear Equalization for DP-16QAM Coherent Optical Communication Systems

Transformer-Based Nonlinear Equalization for DP-16QAM Coherent Optical Communication Systems

DACNN-aided nonlinear equalizer for a probabilistic shaping coherent optical communication system.

The probabilistic shaping (PS) technique is a key technology for fiber optic communication systems to further approach the Shannon limit. To solve the problem that nonlinear equalizers are ineffective for probabilistic shaping optical communication systems with non-uniform distribution, a distribution alignment convolutional neural network (DACNN)-aided nonlinear equalizer is proposed. The approach calibrates the equalizer using the probabilistic shaping prior distribution, which reduces the training complexity and improves the performance of the equalizer simultaneously. Experimental results show nonlinear equalization of 120Gb/s PS 64QAM signals in a 375km transmission scenario. The proposed DACNN equalizer improves the receiver sensitivity by 2.6dB and 1.1dB over the Volterra equalizer and convolutional neural network (CNN) equalizer, respectively. Meanwhile, DACNN converges with fewer training epochs than CNN, which provides great potential for mitigating the nonlinear distortion of PS signals in fiber optic communication systems.

Performance investigation of geometric constellation shaping-based coherent WDM optical fiber communication system supported by deep-learning autoencoder

Geometric constellation shaping (GCS) has been proposed to enhance the performance of wavelength-division multiplexing (WDM) coherent optical fiber communication (OFC) systems. This paper presents a comprehensive simulation platform to design and simulate these systems' performance using an advanced autoencoder (AE) technique. The design of the AE is based on end-to-end deep learning and takes into account the system parameters, especially those related to the OFC channel. The system design uses identical AEs, one in each WDM channel, and only the AE of the central channel is trained to achieve the required performance target. The developed AE simulation platform is capable of assessing the bit error rate characteristics, signal-to-noise ratio, and mutual information for long-haul coherent OFC-WDM systems operating with various modulation formats. The simulation results indicate that using a multilayer perceptron neural network to design AE requires four hidden layers, sixteen nodes per hidden layer, and a “16x modulation order” batch size to achieve optimum system performance. The AE's behaviour is investigated to identify the allowed ranges of the optimal launch power using two different procedures that achieve better system performance for 2D and 4D constellations.

Wide and Deep Learning-Aided Nonlinear Equalizer for Coherent Optical Communication Systems

In this study, we developed a wide and deep network-based nonlinear equalizer to compensate for nonlinear impairment in coherent optical communication systems. In our proposed equalizer, the power feature factor and inter-symbol feature sequence in the received signal are analyzed by two combined networks, wide and deep, respectively, so that the information contained in the signal can be fully utilized. We designed an experiment using a 120 Gbit/s 64-quadrature amplitude modulation (64-QAM) coherent optical communication system over a 375 km standard single-mode fiber (SSMF) to verify the performance of the proposed wide and deep network-based nonlinear equalizer. The experimental results showed that the proposed wide and deep network-based nonlinear equalizer achieved better performance at lower complexity compared with the traditional neural network-based nonlinear equalizer. The proposed equalizer significantly improved the equalization effect at a cost of a 0.3% increase in parameters, which indicates the potential of the proposed method for application in coherent optical communication systems.

Generalized Rayleigh quotient optimization method for inter-channel nonlinearity compensation in coherent optical communication systems.

Inter-channel nonlinearity compensation plays a crucial role in wavelength division multiplexing (WDM) systems for improving transmission capacity and distance. In this work, we propose a novel, to the best of our knowledge, inter-channel nonlinearity compensation method called generalized Rayleigh quotient optimization (GRQO) method with two different working modes. In an 8 × 64 GBaud 16-ary quadrature amplitude modulation (16-QAM) experimental system over 1600 km standard single-mode fiber (SSMF), the proposed method shows a 0.40 dB Q2 factor improvement over nonlinear polarization cross talk canceller (NPCC) with a moderately low computational complexity of about 2000 real multiplications per bit (RMb).

16QAM optical signal generation scheme based on weighted optimal Euclidean distance.

A two-dimensional signal constellation scheme for binary uniform memoryless source transmission in optical fiber channels is studied in this paper. In geometric shaping (GS), optimization algorithms are usually used to change the overall position of constellation points while maintaining the probability of constellation points unchanged. Different optimization functions are used to allocate the position of constellation symbols, thereby improving constellation performance. A 16 quadrature amplitude modulation (QAM) optical signal generation scheme based on weighted optimal Euclidean distance is proposed in this paper. In order to obtain the best constellation diagram and increase the shaping gain, the weighted optimal Euclidean distance that can minimize the bit error rate (BER) over multiple iterative optimizations is used as the objective function. On the one hand, the proposed 16QAM optical signal generation scheme based on weighted optimal Euclidean distance always outperforms the uniform square 16QAM and the uniform circle 16QAM schemes in the back to back (BTB) transmission. On the other hand, after analyzing the simulation demonstration in a 50GBaud coherent optical communication system over 3000km, results demonstrate that the optical signal to noise ratio (OSNR) performance of this system is better than that of the uniform square 16QAM and the uniform circle 16QAM, which is improved by 0.52dB and 0.85dB, respectively. In addition, the proposed 16QAM system increases the transmission distance by 989km and 741km, respectively, compared to the other two systems. The performance confirms that the proposed novel 16QAM scheme, to the best of our knowledge, can effectively improve the reliability and transmission distance. Therefore, the proposed scheme has a certain development prospect in the future long-distance transmission of high-speed optical fiber communication.

Nonlinear compensation for few-mode fiber MDM-WDM systems using probabilistic neural network

In this paper, we propose for the first time to apply probabilistic neural network (PNN) to fiber nonlinear compensation (NLC) in a high-speed coherent optical communication system that combines few-mode fiber (FMF) mode division multiplexing (MDM) with wavelength division multiplexing (WDM). By training on a small number of symbols, the PNN equalizer can compute the statistical distribution of the signal nonlinearity, make decisions on test symbols, and thereby compensate for the nonlinear impairments of the signals. To verify the effectiveness of the proposed scheme, we construct a MDM-WDM simulation system with 28 GBaud polarization division multiplexing (PDM) 16-quadrature amplitude modulation(QAM) and 64 GBaud PDM-64QAM, 6 spatial mode signals are transmitted over 11 wavelength channels with link lengths of 1500 km and 400 km, respectively. The results show that the PNN equalizer can make nonlinear judgments on received signals and effectively compensate the signal impairments caused by Kerr nonlinearity and device nonlinearity in a large launch power range after undergoing carrier phase recovery (CPR). Meanwhile, this scheme exhibits strong robustness against residual linear mode coupling (LMC), differential mode group delay (DMGD), and amplified spontaneous emission (ASE) noise. Finally, by the computational complexity comparison, it is proved that the complexity of the probabilistic neural network nonlinear compensation (PNN NLC) scheme is lower than that of digital back propagation (DBP) with comparable performance, which is on the order O(N).