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Huajun Ye

dblp:119/8954 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Optical networks · 50% Physical-layer communications · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Optical networks
coherent optical communication
0.912025
Time-Domain Maximum Likelihood Estimation of Ultra-Fast RSOP and Phase in Coherent Optical PDM Systems · IEEE Trans. Commun. 2025
Physical-layer communications › signal processing for communications › statistical signal processing › estimation theory
phase noise estimation
0.912025
Time-Domain Maximum Likelihood Estimation of Ultra-Fast RSOP and Phase in Coherent Optical PDM Systems · IEEE Trans. Commun. 2025

Methods — techniques the papers use, named apart from their topics

maximum likelihood estimation · 0.9expectation-maximization · 0.9decision-aided tracking · 0.9
YearPublicationVenuePosition
2025 Time-Domain Maximum Likelihood Estimation of Ultra-Fast RSOP and Phase in Coherent Optical PDM Systems
abstract
Coherent optical polarization-division multiplexing (PDM) is a promising technique to enhance spectral efficiency by transmitting data streams independently using orthogonal polarizations of light. However, in challenging conditions like lightning strikes, rotation of state of polarization (RSOP) due to Kerr and Faraday effects can cause significant signal distortions at speeds up to Mrad/s. In this paper, we propose a maximum likelihood (ML) and an expectation maximization (EM) estimator for the estimation of RSOP and laser phase noise (PN). The ML estimator utilizes pilot symbols for deriving explicit RSOP estimates, while the EM estimator iteratively refines estimates by incorporating unknown transmitted data as latent variables, which approximates the ML estimator’s performance while enhancing spectral efficiency. A decision-aided (DA) scheme is subsequently proposed for dynamic tracking of RSOP and PN, as well as signal detection. The Cramér-Rao lower bounds (CRLBs) are derived for performance evaluation, and simulation results demonstrate the superior RSOP tracking performance of our proposed estimators over conventional methods, with capable tracking speed beyond 100 Mrad/s. The proposed methods also exhibit robustness to impairments such as laser PN, polarization dependent loss (PDL), fiber nonlinearity and residual chromatic dispersion (CD).
Xinwei Du, Huajun Ye, Changyuan Yu
IEEE Trans. Commun.3