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Jianshe Ma

dblp:124/7293 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Computer networks · 1

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
Physical-layer communications · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel modeling
0.412020
Monte-Carlo Integration Models for Multiple Scattering Based Optical Wireless Communication · IEEE Trans. Commun. 2020
Physical-layer communications › channel modeling › channel characterization
impulse response
0.412020
Monte-Carlo Integration Models for Multiple Scattering Based Optical Wireless Communication · IEEE Trans. Commun. 2020
Physical-layer communications
optical wireless communication
0.412020
Monte-Carlo Integration Models for Multiple Scattering Based Optical Wireless Communication · IEEE Trans. Commun. 2020

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

monte carlo integration · 0.4importance sampling · 0.4
YearPublicationVenuePosition
2020 Monte-Carlo Integration Models for Multiple Scattering Based Optical Wireless Communication
abstract
Monte-Carlo models are analyzed for multiple scattering channels in optical wireless communications. It is demonstrated that the system impulse response function can be obtained by Monte-Carlo integration model. The convergence performance for the Monte-Carlo integration model is analyzed and improved by introducing different sampling methods. The simulation results show that the gamma function model for channel impulse response function can only be applied to the cases where the common volume between the transmitted light beam and the receiving field-of-view is open. Numerical simulation suggests that for a three-order scattering case, the computation efficiency of the Monte-Carlo integration model based on partial importance sampling is about 12 times of the original Monte-Carlo integration model based on uniform sampling, and 5.6 times of the widely used Monte-Carlo simulation model. The numerical results also show that the Monte-Carlo integration model based on partial importance sampling has higher computation efficiency than the Monte-Carlo simulation model in a higher-order scattering communication scenario.
Renzhi Yuan, Jianshe Ma, Ping Su, Yuhan Dong, Julian Cheng 0001
IEEE Trans. Commun.2