The Experts below are selected from a list of 121455 Experts worldwide ranked by ideXlab platform
Ming Tang - One of the best experts on this subject based on the ideXlab platform.
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modulation format identification assisted by sparse fast fourier transform for hitless flexible coherent transceivers
Optics Express, 2019Co-Authors: Zhongwei Tan, Alan Pak Tao Lau, Ming TangAbstract:For hitless flexible coherent transceivers based next-generation agile optical network, efficient modulation format identification (MFI) is an essential element in digital signal processing (DSP) flow at the receiver-side (Rx). In this paper, we propose a blind and fast MFI scheme with high identification accuracy at low optical signal-to-noise ratio (OSNR) regime. This is achieved by first raising the signal to the 4th power and calculate the peak-to-average power ratio (PAPR) of the corresponding spectra to distinguish 32 quadrature amplitude modulation (QAM) from quadrature phase shift keying (QPSK), 16 and 64QAM signals. Then, followed by iterative partition schemes to remove signals with phase ±π4,±3π4 (or QPSK-like phases) based on the signal amplitudes, the PAPR of the remaining signals is calculated to distinguish the other three formats. Additionally, by frequency offset (FO) pre-compensation, the spectrum can be obtained using sparse-fast-Fourier-transform (S-FFT), which greatly reduces the Total Complexity. The MFI performance is numerically and experimentally investigated by 28 Gbaud dual-polarization (DP) coherent optical back-to-back (B2B) and up to 1500 km standard single mode fiber (SSMF) transmission system using QPSK, 16QAM, 32QAM, and 64QAM. Results show that high identification accuracy can be achieved, even when OSNR is lower than that required for the 20% forward error correction (FEC) threshold of BER=2×10-2 for each format. Furthermore, fast format switching between 64QAM-32QAM and 32QAM-16QAM are demonstrated experimentally for B2B scenario and 900 km SSMF with the proposed MFI technique, respectively.
Xiaoshan Gao - One of the best experts on this subject based on the ideXlab platform.
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revisit sparse polynomial interpolation based on randomized kronecker substitution
Computer Algebra in Scientific Computing, 2019Co-Authors: Qiaolong Huang, Xiaoshan GaoAbstract:In this paper, a new reduction based interpolation algorithm for general black-box multivariate polynomials over finite fields is given. The method is based on two main ingredients. A new Monte Carlo method is given to reduce the black-box multivariate polynomial interpolation problem to the black-box univariate polynomial interpolation problem over any ring. The reduction algorithm leads to multivariate interpolation algorithms with better or the same complexities in most cases when combining with various univariate interpolation algorithms. A modified univariate Ben-Or and Tiwari algorithm over the finite field is proposed, which has better Total Complexity than the Lagrange interpolation algorithm. Combining our reduction method and the modified univariate Ben-Or and Tiwari algorithm, we give a Monte Carlo multivariate interpolation algorithm, which has better Total Complexity in most cases for sparse interpolation of black-box polynomial over finite fields.
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revisit sparse polynomial interpolation based on randomized kronecker substitution
arXiv: Symbolic Computation, 2017Co-Authors: Qiaolong Huang, Xiaoshan GaoAbstract:In this paper, a new reduction based interpolation algorithm for black-box multivariate polynomials over finite fields is given. The method is based on two main ingredients. A new Monte Carlo method is given to reduce black-box multivariate polynomial interpolation to black-box univariate polynomial interpolation over any ring. The reduction algorithm leads to multivariate interpolation algorithms with better or the same complexities most cases when combining with various univariate interpolation algorithms. We also propose a modified univariate Ben-or and Tiwarri algorithm over the finite field, which has better Total Complexity than the Lagrange interpolation algorithm. Combining our reduction method and the modified univariate Ben-or and Tiwarri algorithm, we give a Monte Carlo multivariate interpolation algorithm, which has better Total Complexity in most cases for sparse interpolation of black-box polynomial over finite fields.
Zhongwei Tan - One of the best experts on this subject based on the ideXlab platform.
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modulation format identification assisted by sparse fast fourier transform for hitless flexible coherent transceivers
Optics Express, 2019Co-Authors: Zhongwei Tan, Alan Pak Tao Lau, Ming TangAbstract:For hitless flexible coherent transceivers based next-generation agile optical network, efficient modulation format identification (MFI) is an essential element in digital signal processing (DSP) flow at the receiver-side (Rx). In this paper, we propose a blind and fast MFI scheme with high identification accuracy at low optical signal-to-noise ratio (OSNR) regime. This is achieved by first raising the signal to the 4th power and calculate the peak-to-average power ratio (PAPR) of the corresponding spectra to distinguish 32 quadrature amplitude modulation (QAM) from quadrature phase shift keying (QPSK), 16 and 64QAM signals. Then, followed by iterative partition schemes to remove signals with phase ±π4,±3π4 (or QPSK-like phases) based on the signal amplitudes, the PAPR of the remaining signals is calculated to distinguish the other three formats. Additionally, by frequency offset (FO) pre-compensation, the spectrum can be obtained using sparse-fast-Fourier-transform (S-FFT), which greatly reduces the Total Complexity. The MFI performance is numerically and experimentally investigated by 28 Gbaud dual-polarization (DP) coherent optical back-to-back (B2B) and up to 1500 km standard single mode fiber (SSMF) transmission system using QPSK, 16QAM, 32QAM, and 64QAM. Results show that high identification accuracy can be achieved, even when OSNR is lower than that required for the 20% forward error correction (FEC) threshold of BER=2×10-2 for each format. Furthermore, fast format switching between 64QAM-32QAM and 32QAM-16QAM are demonstrated experimentally for B2B scenario and 900 km SSMF with the proposed MFI technique, respectively.
D T Lee - One of the best experts on this subject based on the ideXlab platform.
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higher order geodesic voronoi diagrams in a polygonal domain with holes
Symposium on Discrete Algorithms, 2013Co-Authors: Chihhung Liu, D T LeeAbstract:We investigate the higher-order Voronoi diagrams of n point sites with respect to the geodesic distance in a simple polygon with h > 0 polygonal holes and c corners. Given a set of n point sites, the kth-order Voronoi diagram partitions the plane into several regions such that all points in a region share the same k nearest sites. The nearest-site (first-order) geodesic Voronoi diagram has already been well-studied, and its Total Complexity is O(n+c). On the other hand, Bae and Chwa [3] recently proved that the Total Complexity of the farthest-site ((n -- 1)st-order) geodesic Voronoi diagram and the number of faces in the diagram are Θ(nc) and Θ(nh), respectively. It is of high interest to know what happens between the first-order and the (n -- 1)st-order geodesic Voronoi diagrams. In this paper we prove that the Total Complexity of the kth-order geodesic Voronoi diagram is Θ(k(n -- k) + kc), and the number of faces in the diagram is Θ(k(n -- k) + kh). Our results successfully explain the variation from the nearest-site to the farthest-site geodesic Voronoi diagrams, i.e., from k = 1 to k = n -- 1, and also illustrate the formation of a disconnected Voronoi region, which does not occur in many commonly used distance metrics, such as the Euclidean, L1, and city metrics. We show that the kth-order geodesic Voronoi diagram can be computed in O(k2(n+c) log(n+c)) time using an iterative algorithm.
Hidetoshi Kayama - One of the best experts on this subject based on the ideXlab platform.
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low Complexity multiuser detection using block fourier transforms
Asia-Pacific Conference on Communications, 2006Co-Authors: Mingshu Wang, Hidetoshi KayamaAbstract:Linear multiuser detection is demanded in a CDMA mobile radio system while always with an unacceptable Complexity. To overcome the drawback, we propose a low Complexity zero forcing (ZF) multiuser detection scheme, namely block Fourier Transform ZF (BFT-ZF). In the proposed transmitter, the only difference from the traditional one is that a cyclic prefix (CP) is added into each transmission unit. Then, the system transfer matrix can be equivalent to a block-circulant matrix by utilizing the information from CP. And, it is easy to be block-diagonalized by block Fast Fourier Transforms. Thus, on the receiver side, the Complexity of matrix inversion decreases dramatically. Accordingly, the Total Complexity of the ZF receiver is obviously reduced. The analysis and simulation results show that the proposed scheme is able to achieve almost the same bit error rate (BER) performance with much less Complexity than the traditional ZF multiuser detector.
