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Xiaoming Zhu
Researcher at University of California, Berkeley
Publications - 13
Citations - 2162
Xiaoming Zhu is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Fading & Fading distribution. The author has an hindex of 8, co-authored 12 publications receiving 2012 citations. Previous affiliations of Xiaoming Zhu include Qualcomm.
Papers
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Journal ArticleDOI
Free-space optical communication through atmospheric turbulence channels
Xiaoming Zhu,Joseph M. Kahn +1 more
TL;DR: The use of ML detection in spatial diversity reception to reduce the diversity gain penalty caused by correlation between the fading at different receivers is described.
Journal ArticleDOI
Performance bounds for coded free-space optical communications through atmospheric turbulence channels
Xiaoming Zhu,Joseph M. Kahn +1 more
TL;DR: This work derives an approximate upper bound on the pairwise codeword-error probability for transmission through channels with correlated turbulence-induced fading for block codes, convolutional codes, and turbo codes for free-space optical communication through weak atmospheric turbulence channels.
Journal ArticleDOI
Markov chain model in maximum-likelihood sequence detection for free-space optical communication through atmospheric turbulence channels
Xiaoming Zhu,Joseph M. Kahn +1 more
TL;DR: A single-step Markov chain (SMC) model for the fading correlation is introduced and used to derive two low-complexity, suboptimal MLSD algorithms based on per-survivor processing (PSP).
Journal ArticleDOI
Mitigation of turbulence-induced scintillation noise in free-space optical links using temporal-domain detection techniques
TL;DR: In this paper, maximum-likelihood sequence detection (MLSD) and pilot-symbol assisted detection (PSAD) were used to mitigate the effect of atmospheric turbulence-induced intensity fluctuations.
Proceedings ArticleDOI
Pilot-symbol assisted modulation for correlated turbulent free-space optical channels
Xiaoming Zhu,Joseph M. Kahn +1 more
TL;DR: The PS assisted maximum-likelihood (PSA-ML) decision rule is derived under the assumption that the temporal coherence of fading is known, but the instantaneous fading state is not known, and a simpler PS assisted detection scheme with variable threshold is proposed.