저작근 근전도에 관한 정상교합자와 ii급 부정교합자의 비교 연구

国際会議開催報告:2013 IEEE International Symposium on Information Theory

Fiber-optic communication systems are nowadays facing serious challenges due to the fast growing demand on capacity from various new applications and services. It is now well recognized that nonlinear effects limit the spectral efficiency and transmission reach of modern fiber-optic communications. Nonlinearity compensation is therefore widely believed to be of paramount importance for increasing the capacity of future optical networks. Recently, there has been steadily growing interest in the application of a powerful mathematical tool—the nonlinear Fourier transform (NFT)—in the development of fundamentally novel nonlinearity mitigation tools for fiber-optic channels. It has been recognized that, within this paradigm, the nonlinear crosstalk due to the Kerr effect is effectively absent, and fiber nonlinearity due to the Kerr effect can enter as a constructive element rather than a degrading factor. The novelty and the mathematical complexity of the NFT, the versatility of the proposed system designs, and the lack of a unified vision of an optimal NFT-type communication system, however, constitute significant difficulties for communication researchers. In this paper, we therefore survey the existing approaches in a common framework and review the progress in this area with a focus on practical implementation aspects. First, an overview of existing key algorithms for the efficacious computation of the direct and inverse NFT is given, and the issues of accuracy and numerical complexity are elucidated. We then describe different approaches for the utilization of the NFT in practical transmission schemes. After that we discuss the differences, advantages, and challenges of various recently emerged system designs employing the NFT, as well as the spectral efficiency estimates available up-to-date. With many practical implementation aspects still being open, our mini-review is aimed at helping researchers assess the perspectives, understand the bottlenecks, and envision the development paths in the upcoming NFT-based transmission technologies.

Nonlinear Fourier transform for optical data processing and transmission: advances and perspectives

国際会議参加報告:2014 IEEE International Symposium on Information Theory

Nowadays, 5G is in its initial phase of commercialization. The 5G network will revolutionize the existing wireless network with its enhanced capabilities and novel features. 5G New Radio (5G NR), referred to as the global standardization of 5G, is presently under the $3^{\mathrm {rd}}$ Generation Partnership Project (3GPP) and can be operable over the wide range of frequency bands from less than 6GHz to mmWave (100GHz). 3GPP mainly focuses on the three major use cases of 5G NR that are comprised of Ultra-Reliable and Low Latency Communication (uRLLC), Massive Machine Type Communication (mMTC), Enhanced Mobile Broadband (eMBB). For meeting the targets of 5G NR, multiple features like scalable numerology, flexible spectrum, forward compatibility, and ultra-lean design are added as compared to the LTE systems. This paper presents a brief overview of the added features and key performance indicators of 5G NR. The issues related to the adaptation of higher modulation schemes and inter-RAT handover synchronization are well addressed in this paper. With the consideration of these challenges, a next-generation wireless communication architecture is proposed. The architecture acts as the platform for migration towards beyond 5G/6G networks. Along with this, various technologies and applications of 6G networks are also overviewed in this paper. 6G network will incorporate Artificial intelligence (AI) based services, edge computing, quantum computing, optical wireless communication, hybrid access, and tactile services. For enabling these diverse services, a virtualized network slicing based architecture of 6G is proposed. Various ongoing projects on 6G and its technologies are also listed in this paper.

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A Survey on Beyond 5G Network With the Advent of 6G: Architecture and Emerging Technologies

A Stokes-space modulation format classification (MFC) technique is proposed for coherent optical receivers by using a non-iterative clustering algorithm. In the clustering algorithm, two simple parameters are calculated to help find the density peaks of the data points in Stokes space and no iteration is required. Correct MFC can be realized in numerical simulations among PM-QPSK, PM-8QAM, PM-16QAM, PM-32QAM and PM-64QAM signals within practical optical signal-to-noise ratio (OSNR) ranges. The performance of the proposed MFC algorithm is also compared with those of other schemes based on clustering algorithms. The simulation results show that good classification performance can be achieved using the proposed MFC scheme with moderate time complexity. Proof-of-concept experiments are finally implemented to demonstrate MFC among PM-QPSK/16QAM/64QAM signals, which confirm the feasibility of our proposed MFC scheme.

Stokes space modulation format classification based on non-iterative clustering algorithm for coherent optical receivers.

We propose a blind transmitter (Tx) and receiver (Rx) in-phase/quadrature (IQ) amplitude and phase imbalances estimation scheme based on a combination of analytical modeling and clustering algorithms. The proposed scheme can isolate and separately estimate Tx and Rx phase and amplitude imbalances, applicable to high-order multi-modulus signals, and hence, is a great physical-layer-monitoring tool for network disaggregation. We first estimate the Rx imbalances by identifying the fact that the received signal distribution in presence of laser frequency offset (FO), phase noise (PN), and Rx imbalance forms concentric ellipses. A convex hull assisted ellipse correction algorithm is used to determine the Rx IQ imbalance parameters that best match the ellipses. Standard laser FO compensation algorithm follows. A k -means clustering assisted blind phase search algorithm is then employed to mitigate the PN in presence of Tx imbalances. Finally, another iterative k -means clustering procedure is used to estimate the Tx IQ imbalances. The proposed scheme is evaluated experimentally for 34 Gbaud QPSK and 16-quadratic-amplitude modulation signals. The accurate estimation for a wide range of Tx and Rx IQ imbalances and good robustness to amplified spontaneous emission noise is demonstrated.

Algorithms for Blind Separation and Estimation of Transmitter and Receiver IQ Imbalances

We propose a noise adaptive Kalman filter for joint polarization tracking and channel equalization using cascaded covariance matching. With the process noise covariance (Q) and the measurement noise covariance (R) estimated in a cascaded manner, the proposed Kalman filter scheme can be implemented in adaptive mode. The experimental results demonstrate that in wide range of OSNR and polarization rotation, the scheme can adaptively configure noise covariance parameters and consequently can achieve optimal performance even in long transmission cases. Besides, the scheme is more robust against the initial errors in Q and R compared to nonadaptive filter and R /Q-adaptive algorithms with the allowable initial values of Q and R within 6 and 9 magnitudes, respectively.

Noise Adaptive Kalman Filter for Joint Polarization Tracking and Channel Equalization Using Cascaded Covariance Matching

In this paper, we make the first step on encoding information using the spectral amplitudes, which provides a potential of increasing the data rate of N-soliton communication systems. Specifically, we propose a noise model for the magnitudes of the spectral amplitudes. Its statistics are obtained without the Gaussian approximation on the noise distribution when N = 1.

A spectral domain noise model for optical fibre channels

Using the nonlinear Fourier transform, one can transform a time-domain fibre channel (characterised by the nonlinear Schrodinger equation) into multiple parallel independent channels. Exploiting this property, nonlinear frequency division multiplexing (NFDM) was proposed [1]. Such an NFT-based transmission approach has prompted the study of the channel noise (on the eigenvalues and spectral amplitudes) in the (nonlinear) spectral domain. In this paper, we propose a consistent noise model for the evolution of an eigenvalue. Then, following the approach in [2], we develop a Gaussian noise model for a spectral amplitude (assuming its perturbation is largely due to the perturbation in the eigenvalue).

Qun Zhang

Papers

Stokes space modulation format classification based on non-iterative clustering algorithm for coherent optical receivers.

Algorithms for Blind Separation and Estimation of Transmitter and Receiver IQ Imbalances

Noise Adaptive Kalman Filter for Joint Polarization Tracking and Channel Equalization Using Cascaded Covariance Matching

A spectral domain noise model for optical fibre channels

A Gaussian noise model of spectral amplitudes in soliton communication systems