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).

Intelligent and adaptive intra-channel and inter-channel fiber nonlinearity compensation in coherent optical transmission systems.

Fiber nonlinearity mitigation is a crucial technology for extending transmission reach and increasing channel capacity in high-baud rate wavelength division multiplexing (WDM) systems. In this work, we propose a novel, to the best of our knowledge, architecture that combines learned modified digital back-propagation (L-MDBP) to compensate for intra-channel nonlinearity and a two-stage decision-directed least mean square (DDLMS) adaptive equalizer to mitigate inter-channel nonlinearity. By leveraging globally optimized model parameters and adaptive channel estimation, the proposed scheme achieves superior performance and lower computation complexity compared with conventional DBP. Specifically, in an 8 × 64 Gbaud 16-ary quadrature amplitude modulation (16QAM) experimental system over 1600 km of standard single-mode fiber (SSMF), our approach shows a 0.30-dB Q2-factor improvement and a complexity reduction of 82.3% compared with DBP with 8 steps per span (SPS). Furthermore, we enhance the adaptability of the architecture by introducing an online transfer learning (TL) technique, which requires only 2% of initial training epochs.

Energy consumption modeling and analysis for short-reach optical transmissions using irregular LDPC codes.

As the transmission rate of data center (DC) related short-reach optical transmissions quickly increases to keep up with internet services' data demand pace, advanced FEC technology starts to establish its key role in short reach optical transmission systems. Coding strategy using Quasi-Cyclic LDPC (QC-LDPC) codes with hard-decision (HD) decoders stands out due to its excellent error correction ability and simple hardware implementation. Meanwhile, with the introduction of green communication concept and increasingly extensive applications of DC, energy consumption of short-reach links has become an urgent problem to be studied. Based on tanner-graph, energy consumption models of regular LDPC codes' HD decoding circuits over AWGN channel have been proposed. In this work, for the first time, we introduce energy consumption of optical transmitters and characteristics of short reach optical channels into energy consumption modeling. Besides, probability distributions of flipping operation as well as bit errors during irregular QC-LDPC codes' HD decoding iterations are analytically derived using density evolution algorithm. Based on our proposed model and post-layout circuit simulation, systems' total power when using four QC-LDPC codes in IEEE and 3GPP with Gallager A/B decoders together with the case of using no FEC are analyzed in two typical scenarios. Numerical results show that, in short range scenario with slight bandwidth limit, uncoded strategy is much more energy-saving than all adopted LDPC-coded strategies in 50Gbaud OOK and 25Gbaud PAM4 transmissions. While in severely band-limited case when FEC is necessary, a tradeoff between energy consumption of transmitters and decoders occurs in 70Gbaud OOK and 35Gbaud PAM4 transmissions. Besides, LDPC codes with longer length at similar rate are proved to consume less power for their better error correction ability. And in long range scenario, power differences among coding strategies grow significantly when pre-bit error rate (BER) approaches their error correction threshold, reflecting the great influence of error correction threshold on the energy consumption of LDPC decoders. Among all adopted coding strategies, a (19200, 15872) LDPC code with Gallager B decoder consumes minimum power in both two scenarios. However, it is also found that decoding algorithm minimizing the total power differs at different pre-BER if we concentrate on decoding algorithm, justifying the significance of our modeling in minimizing system energy consumption.

AMCC nonlinear baseband superimposition and extraction aided by proposed interference cancellation for WDM-PON used in 5G mobile fronthaul.

As the demand for mobile Internet capacity explodes, the research on fifth-generation (5G) mobile communication systems has gradually deepened, which has stringent requirements for latency and transmission capacity, especially in the section called mobile fronthaul (MFH). Wavelength division multiplexing passive optical network (WDM-PON) is an attractive technology for 5G MFH which requires an auxiliary management and control channel (AMCC) to achieve efficient network deployment. In previous studies, more research has been done on AMCC superimposition methods and transmission performance on 10 Gbps WDN-PON systems, and the role of AMCC in wavelength management has been studied at the system level. In this paper, we realize non-linear baseband modulation of AMCC signals up to 20 Mbps in a single wavelength 25-Gbps PON system through the distributed feed-back laser and Mach-Zehnder modulator. At the receiving end, we propose a low-complexity interference cancellation method to suppress the interference caused by WDM-PON signals and significantly reduce the bit error rate of AMCC signals. The method realizes a simplified scheme to reconstruct the PON signals by analyzing the characteristics of nonlinear modulation and the reconstructed signals can be applied to the original AMCC signals through filtering and subtraction to eliminate interference. These operations have low complexity and can be easily implemented by analog circuits, thus making it an effective way to improve the quality of AMCC signals. With the help of the proposed method, AMCC transmission at 20 Mbps can be achieved with different modulation depths, which is very promising for 5G MFH.

Utility-Privacy Trade-Off in Distributed Machine Learning Systems.

In distributed machine learning (DML), though clients' data are not directly transmitted to the server for model training, attackers can obtain the sensitive information of clients by analyzing the local gradient parameters uploaded by clients. For this case, we use the differential privacy (DP) mechanism to protect the clients' local parameters. In this paper, from an information-theoretic point of view, we study the utility-privacy trade-off in DML with the help of the DP mechanism. Specifically, three cases including independent clients' local parameters with independent DP noise, dependent clients' local parameters with independent/dependent DP noise are considered. Mutual information and conditional mutual information are used to characterize utility and privacy, respectively. First, we show the relationship between utility and privacy for the three cases. Then, we show the optimal noise variance that achieves the maximal utility under a certain level of privacy. Finally, the results of this paper are further illustrated by numerical results.

Adaptive SVM-based pixel accumulation technique for a SPAD-based lidar system.

This paper proposes an adaptive support vector machine (SVM)-based pixel accumulation technique for the single-photon avalanche diode (SPAD)-based flash lidar system to greatly improve the accuracy of depth images. In this method, an adaptive incremental SVM classifier is proposed to distinguish the target and background to avoid the boundary blur caused by accumulation. With the SVM classifier, only the pixels belonging to the same target are accumulated. Then by accumulating the multiple measurements of the results of neighboring pixels, the influence of noisy photons can be reduced, and an accurate peak position of the laser signal in the histogram generated by the SPAD detector can be derived. Different from most existing classification algorithms in which the SVM model is used to recognize the target in depth, the image is trained with huge amounts of offline data, which neglect the ability to handle the changes of target's features by building a small subset of input data that contains all needed information of the trained SVM model. The new method could quickly update itself with the motion of target or light intensity changes online and definitely enhance the practicability of the proposed depth image-processing method. Experimental results show that using the proposed adaptive pixel accumulation technique, the mean squared error of depth images can be reduced by 61% compared with raw images and 44% compared with the static SVM-based method when the target moves.

Low-complexity adaptive radius outlier removal filter based on PCA for lidar point cloud denoising.

In autonomous driving, cars rely on light detection and ranging (lidar) to navigate the surroundings, but interference from the environment makes it difficult to retrieve useful information. To address this problem, this paper develops a noise reduction method to filter lidar point clouds (i.e., an adaptive radius outlier removal filter based on principal component analysis). We believe this method can outperform existing clustering algorithms when applied to point cloud images captured at a large distance from the lidar. Compared to traditional methods, the proposed method has higher precision and recall with an F-score up to 0.876 and complexity reduced by at least 50%.

Simultaneous Determination of 5 Components in the Leaves of Dimocarpus longan by Quantitative Analysis of Multicomponents by Single Marker (QAMS) Based on UPLC and HPLC.

The pharmacodynamic effect of longan leaves was attributed to various components, especially the flavonoids. In this paper, a new strategy of quantitative analysis of multicomponents by a single marker (QAMS) method was first established to synchronously determine 5 components (ethyl gallate (C1), astragalin (C2), quercetin (C3), luteolin (C4), and kaempferol (C5)) in Dimocarpus longan by ultra-performance liquid chromatography (UPLC) and high-performance liquid chromatography (HPLC). Quercetin (C3) was chosen as the internal reference. Relative correction factors (RCFs, ƒs/i) of the other 4 components were calculated by two correction methods (multipoint correction and slope correction) to effectuate QAMS. At the same time, the difference between the results measured by the QAMS and external standard methods was compared to verify the accuracy of QAMS. Within the linear range, the results showed that all ƒs/i values were obtained with good durability under diverse chromatographic conditions (RSD < 2.28%). The quantitative results of 5 components in the leaves of Dimocarpus longan collected from 10 producing areas by different chromatographic systems and quantitative methods were significantly correlated (Pearson's r > 97.0%). The applicability and feasibility of the QAMS method established in this study were evaluated to be favorable for quality control of the leaves of Dimocarpus longan. As a new model of quality control, it can provide one more choice of multicomponent quality-control method in the absence of standard substances or instruments.

Gaussian mixture model-hidden Markov model based nonlinear equalizer for optical fiber transmission.

The demand for high speed data transmission has increased rapidly over the past few years, leading to the development of the data center concept. As is known, nonlinear effects in optical fiber transmission systems are becoming significant with the development of transmission speed. Since it is difficult for conventional DSP algorithms to accurately capture these nonlinear distortions, many machine learning-based equalizers have been proposed. However, previous corresponding experiments mainly focused on achieving low BER while the computational complexity is much greater. In this paper, we propose a Gaussian mixture model (GMM)-hidden Markov model (HMM) based nonlinear equalizer, which utilizes the received signals' statistical characteristics as the priori information to reduce the computational complexity. The BER performance of the GMM-HMM based equalizer has been evaluated in a PAM-4 modulated VCSEL-MMF optical interconnect link, which shows an excellent capability of mitigating nonlinear distortions. In addition, the computational complexity of GMM-HMM based equalizer is about 73% lower than that of recurrent neural networks (RNN) based methods with similar BER performance.

Efficient coding and detection of ultra-long IDs for visible light positioning systems.

Visible light positioning (VLP) is a promising technique to complement Global Navigation Satellite System (GNSS) such as Global positioning system (GPS) and BeiDou Navigation Satellite System (BDS) which features the advantage of low-cost and high accuracy. The situation becomes even more crucial for indoor environments, where satellite signals are weak or even unavailable. For large-scale application of VLP, there would be a considerable number of Light emitting diode (LED) IDs, which bring forward the demand of long LED ID detection. In particular, to provision indoor localization globally, a convenient way is to program a unique ID into each LED during manufacture. This poses a big challenge for image sensors, such as the CMOS camera in everybody's hands since the long ID covers the span of multiple frames. In this paper, we investigate the detection of ultra-long ID using rolling shutter cameras. By analyzing the pattern of data loss in each frame, we proposed a novel coding technique to improve the efficiency of LED ID detection. We studied the performance of Reed-Solomon (RS) code in this system and designed a new coding method which considered the trade-off between performance and decoding complexity. Coding technique decreases the number of frames needed in data processing, significantly reduces the detection time, and improves the accuracy of detection. Numerical and experimental results show that the detected LED ID can be much longer with the coding technique. Besides, our proposed coding method is proved to achieve a performance close to that of RS code while the decoding complexity is much lower.

Step angles to reduce the north-finding error caused by rate random walk with fiber optic gyroscope.

We study the relationship between the step angles and the accuracy of north finding with fiber optic gyroscopes. A north-finding method with optimized step angles is proposed to reduce the errors caused by rate random walk (RRW). Based on this method, the errors caused by both angle random walk and RRW are reduced by increasing the number of positions. For when the number of positions is even, we proposed a north-finding method with symmetric step angles that can reduce the error caused by RRW and is not affected by the azimuth angles. Experimental results show that, compared with the traditional north-finding method, the proposed methods with the optimized step angles and the symmetric step angles can reduce the north-finding errors by 67.5% and 62.5%, respectively. The method with symmetric step angles is not affected by the azimuth angles and can offer consistent high accuracy for any azimuth angles.

The application of cost-effective lasers in coherent UDWDM-OFDM-PON aided by effective phase noise suppression methods.

Digital coherent passive optical network (PON), especially the coherent orthogonal frequency division multiplexing PON (OFDM-PON), is a strong candidate for the 2nd-stage-next-generation PON (NG-PON2). As is known, OFDM is very sensitive to the laser phase noise which severely limits the application of the cost-effective distributed feedback (DFB) lasers and more energy-efficient vertical cavity surface emitting lasers (VCSEL) in the coherent OFDM-PON. The current long-reach coherent OFDM-PON experiments always choose the expensive external cavity laser (ECL) as the optical source for its narrow linewidth (usually<100 KHz). To solve this problem, we introduce the orthogonal basis expansion based (OBE) phase noise suppression method to the coherent OFDM-PON and study the possibility of the application of the DFB lasers and VCSEL in coherent OFDM-PON. A typical long-reach coherent ultra dense wavelength division multiplexing (UDWDM) OFDM-PON has been set up. The numerical results prove that the OBE method can stand severe phase noise of the lasers in this architecture and the DFB lasers as well as VCSEL can be used in coherent OFDM-PON. In this paper, we have also analyzed the performance of the RF-pilot-aided (RFP) phase noise suppression method in coherent OFDM-PON.

All-digital signal-processing open-loop fiber-optic gyroscope with enlarged dynamic range.

We propose and realize a new open-loop fiber-optic gyroscope (FOG) with an all-digital signal-processing (DSP) system where an all-digital phase-locked loop is employed for digital demodulation to eliminate the variation of the source intensity and suppress the bias drift. A Sagnac phase-shift tracking method is proposed to enlarge the dynamic range, and, with its aid, a new open-loop FOG, which can achieve a large dynamic range and high sensitivity at the same time, is realized. The experimental results show that compared with the conventional open-loop FOG with the same fiber coil and optical devices, the proposed FOG reduces the bias instability from 0.259 to 0.018 deg/h, and the angle random walk from 0.031 to 0.006 deg/h(1/2), moreover, enlarges the dynamic range to ±360 deg/s, exceeding the maximum dynamic range ±63 deg/s of the conventional open-loop FOG.

Enhanced multiposition method to suppress the north finding error caused by bias drift with fiber optic gyroscopes.

We present an enhanced multiposition method (EMM) to suppress the north finding error caused by bias drift with fiber optic gyroscopes (FOGs). The new proposal is a static method to find the true north, and it employs a differential strategy and a rotation scheme of increasing step angle. Using the noise model of Allan variance, we analyze the north finding errors caused by angle random walk (ARW), rate random walk (RRW), and rate ramp (RR) theoretically, where RRW and RR are two main noise sources of bias drift, and ARW is the rate white noise. Theoretical analysis indicates that, in the traditional multiposition method (TMM), as the position number increases, the error caused by ARW decreases while that by bias drift increases. Therefore, the suppressions of ARW and bias drift are conflicted with each other. The north finding accuracy is limited by bias drift. In contrast, in EMM, both errors caused by ARW and bias drift will decrease as the position number increases. Experimental results with two specific FOGs verify our theoretical analysis. In our experiments, we study the effect of position number and step angle on the north finding accuracy. Utilizing the proposed EMM, for FOG-1, the north finding error has been reduced by 76.60%, and for FOG-2, a 36.33% reduction has been achieved. Our proposal provides a more effective and stable way to find true north, and it can also be applied to other rate gyroscopes.

Nonlinear performance of multi-granularity orthogonal transmission systems with frequency division multiplexing.

Orthogonal transmission with frequency division multiplexing technique is investigated for next generation optical communication systems. Coherent optical orthogonal frequency division multiplexing (OFDM) and single-carrier frequency division multiplexing (SCFDM) schemes are compared in combination with polarization-division multiplexing quadrature phase shift keying (QPSK) or 16-QAM (quadrature amplitude modulation) formats. Multi-granularity transmission with flexible bandwidth can be realized through ultra-dense wavelength division multiplexing (UDWDM) based on the orthogonal technique. The system performance is numerically studied with special emphasis on transmission degradations due to fiber Kerr nonlinearity. The maximum reach and fiber capacity for different spectral efficiencies are investigated for systems with nonlinear propagation over uncompensated standard single-mode fiber (SSMF) links with lumped amplification.

Phase noise suppression for coherent optical block transmission systems: a unified framework.

A unified framework for phase noise suppression is proposed in this paper, which could be applied in any coherent optical block transmission systems, including coherent optical orthogonal frequency-division multiplexing (CO-OFDM), coherent optical single-carrier frequency-domain equalization block transmission (CO-SCFDE), etc. Based on adaptive modeling of phase noise, unified observation equations for different coherent optical block transmission systems are constructed, which lead to unified phase noise estimation and suppression. Numerical results demonstrate that the proposal is powerful in mitigating laser phase noise.

Phase noise estimation and mitigation for DCT-based coherent optical OFDM systems.

In this paper, as an attractive alternative to the conventional discrete Fourier transform (DFT) based orthogonal frequency division multiplexing (OFDM), discrete cosine transform (DCT) based OFDM which has certain advantages over its counterpart is studied for optical fiber communications. As is known, laser phase noise is a major impairment to the performance of coherent optical OFDM (CO-OFDM) systems. However, to our knowledge, detailed analysis of phase noise and the corresponding mitigation methods for DCT-based CO-OFDM systems have not been reported yet. To address these issues, we analyze the laser phase noise in the DCT-based CO-OFDM systems, and propose phase noise estimation and mitigation schemes. Numerical results show that the proposal is very effective in suppressing phase noise and could significantly improve the performance of DCT-based CO-OFDM systems.