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Coherent superposition has been proposed to synthesize high-order quadrature amplitude modulation (QAM) by coherently superposing low-order QAMs in the optical domain. These approaches could effectively relax the digital-to-analog converter resolution and reduce the complexity of the driving electronics. However, in the superposition process, imperfect phase rotations (IPRs) in low-order QAMs will be transferred to the resultant high-order QAM. Importantly, the induced IPR cannot be compensated for by conventional linear equalizers and carrier recovery methods. To combat the induced IPR, herein, we propose a hierarchical blind phase search (HBPS) algorithm to compensate for the IPRs in synthesized high-order QAMs. The proposed HBPS can match the generation mechanism of the IPRs in coherent superposition, by tracing back and estimating the IPR in the QPSK-like constellation of each hierarchy and finally correcting the induced IPRs. Simulation and experimental results verify that this algorithm could effectively compensate for the IPR in the resultant 16-QAMs synthesized using coherent superposition approaches. The proposed HBPS shows significant optical signal-to-noise ratio (OSNR) gains compared to the conventional blind phase search (BPS) method for high-order QAMs coherently superposed using optical signal processing (OSP) and tandem modulators (TMs). Specifically, at the BER of 2.4e-2, the HBPS achieves a 1.5-dB OSNR sensitivity enhancement over the BPS in either OSP or TMs-based schemes, even with an imperfection rotation of up to 20∘.
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In this paper, we propose a feed-forward equalizer (FFE)-assisted simplified soft-output MLSE (sMLSE) by collaborating the maximum likelihood sequence estimation (MLSE) with soft-decision low-density-parity-check (LDPC) decoding. The simplified sMLSE results in undetermined log-likelihood ratio (LLR) magnitudes when the reserved level is less than or equal to the half of modulation order. This severely degrades the performance of soft-decision forward error correction (SD-FEC) decoding. In the FFE-assisted simplified sMLSE, we use the LLRs calculated from pre-set FFE to replace these undetermined LLRs of simplified sMLSE. Thus, the proposed method eliminates the SD-FEC decoding performance degradation resulted from simplification. We conduct experiments to transmit 184-Gb/s PAM-4 or 255-Gb/s PAM-8 signal in IM-DD system at C-band to evaluate the performance of the proposed sMLSE. The results show that the proposed sMLSE can effectively compensate for the degradation of LLR quality. For 255-Gb/s PAM-8 signal transmissions, the FFE-assisted simplified sMLSE achieves almost the same SD-FEC decoding performance as the conventional sMLSE but with 85% complexity reduction.
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Perfluorinated acrylate polymer materials exhibit low absorption loss at 1310 and 1550â nm, but molecular oxygen inhibits their photocuring. We propose a novel, to our knowledge, UV photolithography method incorporating a pre-exposure process for fabricating low-loss perfluorinated acrylate polymer waveguides. During the pre-exposure process, a partially cured thin layer forms on the core layer, effectively overcoming oxygen inhibition in subsequent lithography. Furthermore, the functional group contents of the polymerized materials were characterized by a Raman spectrometer to analyze the development reaction under the pre-exposure layer. Utilizing this improved method, we fabricated a straight waveguide with a length of 21â cm. The experiments showed that the propagation losses are 0.14â dB/cm at 1310â nm and 0.51â dB/cm at 1550â nm. The inter-channel cross talk for a core pitch of 250â µm was measured as low as -49â dB at 1310â nm. Error-free NRZ data transmission over this waveguide at 25â Gb/s was achieved, showcasing the potential in optical interconnect and communication applications.
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We propose and numerically demonstrate a novel secure key distribution (SKD) scheme by using dynamically synchronized semiconductor lasers (SLs) subject to common dual injections from two mutually coupled SLs. The performance of hybrid chaos synchronization, complexity of chaotic signals, chaos-based key distribution, and the privacy of SKD scheme are systematically discussed. It is shown that high-quality hybrid chaos synchronization of zero lag and lead lag can be both achieved between two local lasers under different injection delay conditions, whereas low cross correlations are observed among the driving lasers and the local lasers. By randomly perturbing the injection delays with four independent random sequences, the outputs of local SLs can be dynamically synchronized. Extracting the outputs in the synchronization time slots of zero lag and lead lag, synchronous entropy sources are obtained and used to generate keys with high consistency at local ends of Alice and Bob, which are robust to the parameter mismatches of local lasers to some extent. Moreover, large BER is calculated in two types of typical illegal attacks, which demonstrates the security of the proposed scheme. This work proposed a high-level secure key distribution solution to one-time pad communication.
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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.
Assuntos
Tecnologia de Fibra Óptica , Processamento de Sinais Assistido por Computador , Desenho de Equipamento , Algoritmos , Redes Neurais de ComputaçãoRESUMO
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.
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We propose an adaptive time-delayed photonic reservoir computing (RC) structure by utilizing the Kalman filter (KF) algorithm as training approach. Two benchmark tasks, namely the Santa Fe time-series prediction and the nonlinear channel equalization, are adopted to evaluate the performance of the proposed RC structure. The simulation results indicate that with the contribution of adaptive KF training, the prediction and equalization performance for the benchmark tasks can be significantly enhanced, with respect to the conventional RC using a training approach based on the least-squares (LS). Moreover, by introducing a complex mask derived from a bandwidth and complexity enhanced chaotic signal into the proposed RC, the performance of prediction and equalization can be further improved. In addition, it is demonstrated that the proposed RC system can provide a better equalization performance for the parameter-variant wireless channel equalization task, compared with the conventional RC based on LS training. The work presents a potential way to realize adaptive photonic computing.
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A novel cluster fusion method is proposed, based on which chaos synchronization in asymmetric coupling semiconductor lasers (ACSLs) networks is systematically demonstrated. Take the cluster fusion of a mutually-coupled network composed of 7 semiconductor lasers (SLs) for instance, the characteristics of chaos synchronization as well as the influences of coupling strength, bias current, and mismatches of intrinsic parameters and injection strength on the quality of chaos synchronization in hybrid clusters composed of ACSLs are thoroughly investigated. The results show that by using cluster fusion, the ACSLs which originally belong to different clusters can form three types of new hybrid clusters, namely, trivial-hybrid cluster, trivial-nontrivial-hybrid cluster, and nontrivial-hybrid cluster. Compared with the low-correlation inter-cluster ACSLs of original SLs network, high-quality chaos synchronization is achieved in three types of newly generated hybrid clusters over a wide parameter range. Moreover, the cluster fusion and synchronization of side-SLs clusters of star-type SLs networks are also verified, which indicate the universality of the proposed method. This work provides a new way to realize the chaos synchronization among ACSLs of different clusters.
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In this paper, we propose and experimentally demonstrate a novel scheme that helps to solve an any-number-armed bandit problem by utilizing two parallel simultaneously-generated chaotic signals and the epsilon (É)-greedy strategy. In the proposed scheme, two chaotic signals are experimentally generated, and then processed by an 8-bit analog-to-digital conversion (ADC) with 4 least significant bits (LSBs), to generate two amplitude-distribution-uniform sequences for decision-making. The correspondence between these two random sequences and different arms is established by a mapping rule designed in virtue of the É-greedy-strategy. Based on this, decision-making for an exemplary 5-armed bandit problem is successfully performed, and moreover, the influences of the mapping rule and unknown reward probabilities on the correction decision rate (CDR) performance for the 4-armed to 7-armed bandit problems are investigated. This work provides a novel way for solving the arbitrary-number-armed bandit problem.
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We experimentally demonstrate a net capacity per wavelength of 1.23 Tb/s with 30 GBaud 16-ary quadrature amplitude modulation (16-QAM) mode-division multiplexing (MDM) signals over a single silicon-on-insulator (SOI) multimode waveguide for optical interconnects employing $11 \times 11$ multiple-in-multiple-out (MIMO) digital signal processing. In order to simplify the receiver architecture for coherent optical interconnects, we further propose and evaluate an on-chip self-homodyne coherent detection (SHCD) scheme. In the experiment, 30 Gbaud quadrature phase shift keying (QPSK) signals carried by 10 waveguide modes are successfully recovered with bit error rates (BERs) below 7% forward error correction (FEC) threshold using the pilot tone delivered by ${{\rm TE}_0}$ mode as a local oscillator. Around 10% penalty on error vector magnitude (EVM) is observed due to modal cross talk compared to homodyne detection.
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Single wavelength 50 Gb/s passive optical network (PON) is an excellent candidate for meeting high capacity requirements. In this paper, we experimentally investigate a symmetrical 50 Gb/s time division multiplexed passive optical network (TDM-PON) system in the O-band based on 25G optics. Semiconductor optical amplifier (SOA) is used in optical line terminal (OLT) side to improve link power budget. We initially investigate the performances of SOA as a booster amplifier with different gain in the downstream and make a trade-off between receiver sensitivity and power budget. The performances of 50 Gb/s non-return-to-zero (NRZ) in the downstream with avalanche photodiode (APD) receiver and upstream with SOA-PIN receiver with different equalization schemes are evaluated. Experimental results show that up to 34.97 dB link power budget is achieved in the downstream direction with 7-tap feed forward equalization (FFE), and 33.76 dB link power budget is achieved in the upstream direction with only 3-tap FFE filtering.
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High peak-to-average power ratio (PAPR) causes nonlinear impairments in intensity modulation direct detection (IM/DD) optical orthogonal frequency division multiplexing (O-OFDM) systems. Selective mapping (SLM) is a well-known effective PAPR reduction technique, but it suffers from high computational complexity due to the bank of inverse fast Fourier transforms (IFFTs) required to generate the set of candidate signals. In this paper, we propose a recombined SLM scheme that can generate up to 2U2 symbol candidates with U IFFTs. The candidate sequences are first partitioned and then recombined to generate new candidate signals, where the addition operation replaces the IFFT block and reduces the computational complexity significantly. Simulations and a real-time end-to-end IM/DD O-OFDM transmission system with line rate 10.5 Gb/s are set up to verify the performance of the proposed scheme. It is demonstrated that compared with conventional SLM, the proposed scheme achieves similar PAPR reduction performance with considerably lower computational complexity and no bit error rate degradation.
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In order to exchange data in a space-division multiplexing (SDM) system, a novel vortex-beam-based data interconnection concept, which is achieved by adjusting the ellipticity of a ring-core fiber, is proposed. A new ring-core fiber is also designed and fabricated for exchanging and propagating the data carried by first- or second-order vortex (orbital angular momentum) beams. The proposed scheme is not only analyzed and simulated in principle, but is also verified through experiments. The numerical results demonstrate that the vortex beams can be exchanged by appropriately adjusting the phase difference (with respect to the ellipticity of a ring-core fiber) between the even and odd vector modes. A new experimental platform is designed and established for the sake of investigating the feasibility of the proposed scheme. The experimental results are consistent with the results of the simulation, and demonstrate that the data carried by the first- or second-order vortex beams can be successfully switched with acceptable bit error rates (BERs) between the first-order vortex beams (L=1 or -1) or between the second-order vortex beams (L=2 or -2, left or right circular polarization), respectively. The measured BERs and constellation diagrams of 16-QAM are employed to evaluate the data exchange performance with respect to different cases (i.e., data exchange once or twice, and data exchange with or without crosstalk). The measured BERs and constellation diagrams also demonstrate that the performance degrades with increase in topological charge or crosstalk. The proposed scheme is flexible, simple, and reliable for data exchange in a SDM system.
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A low-complexity joint symbol synchronization and SFO estimation scheme for asynchronous optical IMDD OFDM systems based on only one training symbol is proposed. Numerical simulations and experimental demonstrations are also under taken to evaluate the performance of the mentioned scheme. The experimental results show that robust and precise symbol synchronization and the SFO estimation can be achieved simultaneously at received optical power as low as -20dBm in asynchronous OOFDM systems. SFO estimation accuracy in MSE can be lower than 1 × 10-11 under SFO range from -60ppm to 60ppm after 25km SSMF transmission. Optimal System performance can be maintained until cumulate number of employed frames for calculation is less than 50 under above-mentioned conditions. Meanwhile, the proposed joint scheme has a low level of operation complexity comparing with existing methods, when the symbol synchronization and SFO estimation are considered together. Above-mentioned results can give an important reference in practical system designs.
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In this paper, an improved end-to-end autoencoder based on reinforcement learning by using Decision Tree for optical transceivers is proposed and experimentally demonstrated. Transmitters and receivers are considered as an asymmetrical autoencoder combining a deep neural network and the Adaboost algorithm. Experimental results show that 48 Gb/s with 7% hard-decision forward error correction (HD-FEC) threshold under 65 km standard single mode fiber (SSMF) is achieved with proposed scheme. Moreover, we further experimentally study the Tree depth and the number of Decision Tree, which are the two main factors affecting the bit error rate performance. Experimental research afterwards showed that the effect from the number of Decision Tree as 30 on bit error rate (BER) flattens out under 48 Gb/s for the fiber range from 25 km and 75 km SSMF, and the influence of Tree depth on BER appears to be a gentle point when Tree Depth is 5, which is defined as the optimal depth point for aforementioned fiber range. Compared to the autoencoder based on a Fully-Connected Neural Network, our algorithm uses addition operations instead of multiplication operations, which can reduce computational complexity from 108 to 107 in multiplication and 106 to 108 in addition on the training phase.
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Although the lab-on-a-chip system has been successfully applied in a wide variety of fields, the goal of achieving a cell counter with simple operation, low cost, and high accuracy still attracts continuous research efforts. In this paper, the authors explore a cell counter based on light beam focusing to measure the density of adherent cells. In this sensor, the light emitted from the optical fibers is collimated by the collimating lens formed in polydimethylsiloxane (PDMS). The uniformly attached adherent cells act as a convex lens, focusing the collimated light propagated through them. The intensity of the focused light indicates the density of the adherent cells. For Hela cells, a detection limit of 8.3 × 104 cells/mL with a detection range from 0.1 × 106 cells/mL to 1.0 × 106 cells/mL is achieved. This sensor is particularly useful for drug screening, cell pathology analysis, and cancer pre-diagnosis.