Search

In high-speed optical fiber communications, chromatic dispersion (CD) estimation is essential for the monitoring and compensation of CD-induced impairments. Compared with coherent detection, in short-reach optical communication systems, intensity modulation/direct detection (IM/DD) is more widely used, and the existing dispersion estimation techniques usually require training signals or a large amount of data for curve fitting or machine learning. However, these methods cannot provide in-service estimation. This paper presents a novel technique for in-service CD estimation in IM/DD short-reach optical communication systems based on our derived analytical model. With the analytical model, the in-service CD estimation is realized via the direct power spectrum analysis of the received signal. Unlike previous studies that only work with single-frequency sinusoidal signals, the practical random data with the rectangular type of base waveform is considered in our model. Therefore, our method can be applied to the dispersion estimation of various pulse amplitude modulation (PAM) based systems. Our proposed training free in-service CD estimation method is verified and investigated, where results show that better than 0.5% accuracy in dispersion estimation can be achieved in optical communication systems with up to 40 GBaud data rate and 100 km transmission distance.

In the coherent long-reach passive optical networks (LRPON), it is crucial to propose cost-effective digital signal processing (DSP) technologies to reduce the overall complexity and power consumption. This paper has proposed a low-complexity chromatic dispersion (CD) estimation scheme based on deep neural networks (DNN) and the error vector magnitude (EVM). To add comparisons, the performances of CD estimation schemes using other two well-known machine learning algorithms including the k-nearest neighbor (KNN) and the decision tree (DT) have also been investigated. The simulation results show that the proposed CD estimation scheme is effective in the coherent LRPON with the quadrature phase shift keying (QPSK) and 16-ary quadrature amplitude modulation (QAM) systems at 14Gbaud rate, 28Gbaud rate and 56Gbaud rate. The comprehensive performances of the DNN outperform those of the KNN and the DT. The mean estimation error of the DNN is less than 20ps/nm within the 100 km access distance in the 28Gbaud QPSK/16QAM systems. What's more, compared with classical methods using the CD scanning and frequent domain equalizers (FDE), the computation complexity of the proposed CD estimation scheme based on the DNN-EVM has been respectively reduced by 72.3 times, 86.7 times and 2.8 times about the amount of multipliers, adders and comparators.

This paper considers Godard's error as signal quality metric to monitor chromatic dispersion (CD), nonlinear parameter and modulation format in the DSP module of the coherent receivers. We first review a CD monitoring based on Godard's error that can be able to accurately monitor arbitrarily large dispersion values in uncompensated transmission links in combination with frequency domain equalizer, then extend the previous nonlinear parameter monitoring method based on Godard's error by blindly obtaining the optimized value γξp to significantly improve the adaptive capability, and present a simple and effective modulation format monitoring based on Godard's error. Meanwhile, the effectiveness has been experimentally verified in 128-Gb/s PDM-QPSK, 192-Gb/s PDM-8QAM, and 256-Gb/s PDM-16QAM systems.

We design a new kind of fractional Fourier transform superimposed training sequence (TS) to simultaneously estimate linear distortions including chromatic dispersion (CD), timing offset (TO), and frequency offset (FO), etc. Without sacrificing additional spectrum efficiency, the scheme can reduce the computational complexity sharply compared to a regular estimation method. The feasibility of the proposed scheme is verified by simulations of 28 GBaud dual polarization quadrature phase-shift keying (DP-QSPK) and 16-ary quadrature amplitude modulation (DP-16 QAM) system. Simulation results show that the superimposed TS has negligible negative effects on the transmission performance considering 7% forward error correction while the TO, FO, and rough CD estimation perform well after a long distance transmission. The max TO estimation (TOE) errors are, respectively, eight samples and 12 samples for QPSK and 16 QAM, and the max FO estimation errors are, respectively, 5.7 and 3.6 MHz for QPSK and 16 QAM. The rough CD estimation (CDE) error is below 946 ps/nm. The TOE and rough CDE separately decrease the complexity of frame synchronization and CDE. In total, the computation complexity of the estimations decreases by 91.8% compared to a regular blind estimation method.

In the coherent long-reach passive optical networks (LRPON), it is crucial to propose cost-effective digital signal processing (DSP) technologies to reduce the overall complexity and power consumption. This paper has proposed a low-complexity chromatic dispersion (CD) estimation scheme based on deep neural networks (DNN) and the error vector magnitude (EVM). To add comparisons, the performances of CD estimation schemes using other two well-known machine learning algorithms including the k-nearest neighbor (KNN) and the decision tree (DT) have also been investigated. The simulation results show that the proposed CD estimation scheme is effective in the coherent LRPON with the quadrature phase shift keying (QPSK) and 16-ary quadrature amplitude modulation (QAM) systems at 14Gbaud rate, 28Gbaud rate and 56Gbaud rate. The comprehensive performances of the DNN outperform those of the KNN and the DT. The mean estimation error of the DNN is less than 20ps/nm within the 100 km access distance in the 28Gbaud QPSK/16QAM systems. What's more, compared with classical methods using the CD scanning and frequent domain equalizers (FDE), the computation complexity of the proposed CD estimation scheme based on the DNN-EVM has been respectively reduced by 72.3 times, 86.7 times and 2.8 times about the amount of multipliers, adders and comparators. [ABSTRACT FROM AUTHOR]

We design a new kind of fractional Fourier transform superimposed training sequence (TS) to simultaneously estimate linear distortions including chromatic dispersion (CD), timing offset (TO), and frequency offset (FO), etc. Without sacrificing additional spectrum efficiency, the scheme can reduce the computational complexity sharply compared to a regular estimation method. The feasibility of the proposed scheme is verified by simulations of 28 GBaud dual polarization quadrature phase-shift keying (DP-QSPK) and 16-ary quadrature amplitude modulation (DP-16 QAM) system. Simulation results show that the superimposed TS has negligible negative effects on the transmission performance considering 7% forward error correction while the TO, FO, and rough CD estimation perform well after a long distance transmission. The max TO estimation (TOE) errors are, respectively, eight samples and 12 samples for QPSK and 16 QAM, and the max FO estimation errors are, respectively, 5.7 and 3.6 MHz for QPSK and 16 QAM. The rough CD estimation (CDE) error is below 946 ps/nm. The TOE and rough CDE separately decrease the complexity of frame synchronization and CDE. In total, the computation complexity of the estimations decreases by 91.8% compared to a regular blind estimation method. [ABSTRACT FROM AUTHOR]

This paper considers Godard's error as signal quality metric to monitor chromatic dispersion (CD), nonlinear parameter and modulation format in the DSP module of the coherent receivers. We first review a CD monitoring based on Godard's error that can be able to accurately monitor arbitrarily large dispersion values in uncompensated transmission links in combination with frequency domain equalizer, then extend the previous nonlinear parameter monitoring method based on Godard's error by blindly obtaining the optimized value γξp to significantly improve the adaptive capability and present a simple and effective modulation format monitoring based on Godard's error. Meanwhile, the effectiveness has been experimentally verified in 128-Gb/s PDM-QPSK, 192-Gb/s PDM-8QAM and 256-Gb/s PDM-16QAM systems [ABSTRACT FROM AUTHOR]

We experimentally investigate the performance of the signal power autocorrelation-based method for chromatic dispersion (CD) estimation in a polarization-multiplexing quadrature phase-shift keying (PM-QPSK) 100G coherent optical system conveying optical channel transport unit level-4 (OTU4) frames. It is shown that the typical laboratory setup, where the signal components are generated from delayed versions of the same pseudorandom binary sequence (PRBS), is inadequate for experimental validation because of artifacts in the signal auto-correlation function. This problem is circumvented by the use of a commercial line card transporting independent data sequences. The algorithm is used to estimate accumulated CD values from 0 to 50 000 ps/nm under up to 80-ps differential group delay (DGD). We further evaluate its convergence properties in terms of the length of the sample vector required for correct CD estimation and address the hardware resource requirements. The CD-shifted version of the algorithm yielded a maximum estimation error of 186 ps/nm in all tested conditions.