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Zibo Zheng

Researcher at Beijing University of Posts and Telecommunications

Publications -  43
Citations -  224

Zibo Zheng is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Kalman filter & Extended Kalman filter. The author has an hindex of 7, co-authored 34 publications receiving 138 citations.

Papers
More filters
Journal ArticleDOI

Two-parameter-SOP and three-parameter-RSOP fiber channels: problem and solution for polarization demultiplexing using Stokes space.

TL;DR: A DSP tracking and equalization scheme for the fast time-varying RSOP using the extended Kalman filter (EKF) is proposed and is proved to be universal and can solve all the PolDemux problems based on the 2- or 3-parameter RSOP model.
Journal ArticleDOI

Window-split structured frequency domain Kalman equalization scheme for large PMD and ultra-fast RSOP in an optical coherent PDM-QPSK system.

TL;DR: Compared with the generally used constant modulus algorithm (CMA), the proposed Kalman scheme provides excellent performance and stability to cope with large range DGD from 20ps to 200ps and RSOP from 200krad/s to 2Mrad/s, with less computational complexity.
Journal ArticleDOI

Blind and low-complexity modulation format identification scheme using principal component analysis of Stokes parameters for elastic optical networks.

TL;DR: The proposed blind and low-complexity modulation format identification scheme for elastic optical networks (EONs) exhibits good resilience towards fiber nonlinear impairments and its time complexity can be reduced to O(N).
Journal ArticleDOI

Joint equalization scheme of ultra-fast RSOP and large PMD compensation in presence of residual chromatic dispersion

TL;DR: A new Kalman filter structure is proposed, which can jointly compensate ultra-fast RSOP, large PMD and RCD, and compared with CMA/MMA, the proposed Kalman scheme can provide a significant performance enhancement.
Journal ArticleDOI

Robust neural network receiver for multiple-eigenvalue modulated nonlinear frequency division multiplexing system.

TL;DR: This work proposes an innovative receiver based on regression neural networks (NNs), which can demodulate information correctly for both single- and dual-polarization NFDM systems and has strong robustness and has a certain tolerance to the impairments of communication systems.