Y
Yaseein Soubhi Hussein
Researcher at Qatar Airways
Publications - 16
Citations - 220
Yaseein Soubhi Hussein is an academic researcher from Qatar Airways. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Visible light communication. The author has an hindex of 7, co-authored 16 publications receiving 157 citations. Previous affiliations of Yaseein Soubhi Hussein include Universiti Putra Malaysia & Multimedia University.
Papers
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Proceedings ArticleDOI
On performance analysis of LS and MMSE for channel estimation in VLC systems
TL;DR: This paper presents an evaluation of channel estimation techniques for indoor visible light communication (VLC) systems using a direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) scheme, and shows that the MMSE algorithm outperforms the LS for both BER and MSE.
Journal ArticleDOI
A novel cell-selection optimization handover for long-term evolution (LTE) macrocellusing fuzzy TOPSIS
Yaseein Soubhi Hussein,Borhanuddin Mohd Ali,Mohd Fadlee A. Rasid,Aduwati Sali,Ali Mohammed Mansoor +4 more
TL;DR: A novel method called fuzzy multiple-criteria cell selection (FMCCS), which uses an integrated fuzzy technique for order preference by using similarity to ideal solution on S-criterion, availability of resource blocks (RBs), and uplink signal-to-interference-plus-noise ratio, is proposed in this paper.
Proceedings ArticleDOI
Performance analysis of DCO-OFDM in VLC system
TL;DR: Simulation results show that the bit error rate (BER) decreases as the degree of nonlinearity increases and a better BER can be achieved as the LED behavior approaches linear model, thus improving the BER performance of the VLC system.
Journal ArticleDOI
Enhanced handover mechanism in long term evolution (LTE) networks
TL;DR: This paper investigates the improvement steps for HO mechanisms in long term evolution (LTE) system which is being formally submitted as a candidate 4G system and aims to reduce the number of unnecessary HOs.
Journal ArticleDOI
A review on utilizing machine learning technology in the fields of electronic emergency triage and patient priority systems in telemedicine: Coherent taxonomy, motivations, open research challenges and recommendations for intelligent future work.
Omar Hussein Salman,Zahraa K. Taha,Muntadher Alsabah,Yaseein Soubhi Hussein,Ahmed S. Mohammed,Mohammed I. Aal-Nouman +5 more
TL;DR: In this paper, the authors provide a literature review and an in-depth study on the roles of machine learning in the fields of electronic emergency triage (E-triage) and prioritize patients for fast healthcare services in telemedicine applications.