B
Bin Li
Researcher at Beijing University of Posts and Telecommunications
Publications - 63
Citations - 1076
Bin Li is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Communication channel & Cognitive radio. The author has an hindex of 16, co-authored 62 publications receiving 918 citations. Previous affiliations of Bin Li include Peking University.
Papers
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Journal ArticleDOI
Molecular communications: channel model and physical layer techniques
Weisi Guo,Taufiq Asyhari,Nariman Farsad,H. Birkan Yilmaz,Bin Li,Andrew W. Eckford,Chan-Byoung Chae +6 more
TL;DR: In this paper, the authors present a series of physical layer techniques that are necessary to produce reliable and practical molecular communications, equipped with the appropriate channel knowledge, the design of appropriate modulation and error correction coding schemes, and transmitter and receiver side signal processing methods that suppress inter-symbol interference.
Posted Content
Molecular Communications: Channel Model and Physical Layer Techniques
Weisi Guo,Taufiq Asyhari,Nariman Farsad,H. Birkan Yilmaz,Bin Li,Andrew W. Eckford,Chan-Byoung Chae +6 more
TL;DR: This article examines recent research in molecular communications from a telecommunications system design perspective, and focuses on channel models and state-of-the-art physical layer techniques.
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Efficient Beamforming Training for 60-GHz Millimeter-Wave Communications: A Novel Numerical Optimization Framework
TL;DR: This paper forms realistic beamforming (BF) training (or beam steering) in the emerging 60-GHz millimeter-wave communications as a numerical optimization problem, and presents an appealing global numerical algorithm inspired by simulated annealing (SA) mechanics.
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Energy Detection Based Spectrum Sensing for Cognitive Radios Over Time-Frequency Doubly Selective Fading Channels
TL;DR: While classical schemes fail to deal with doubly selective channels, the new sensing scheme can exploit the underlying channel memory and operate well, which provides a great promise to realistic applications.
Journal ArticleDOI
Deep Sensing for Future Spectrum and Location Awareness 5G Communications
TL;DR: A new joint estimation paradigm, namely deep sensing, is proposed for such challenging spectrum and location awareness applications that the mutual interruption between the two unknown quantities is fully considered and, therefore, the PU's emission state is identified by estimating its moving positions jointly.