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Chenglin Zhao
Researcher at Beijing University of Posts and Telecommunications
Publications - 210
Citations - 2390
Chenglin Zhao 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 22, co-authored 197 publications receiving 1704 citations. Previous affiliations of Chenglin Zhao include Peking University.
Papers
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Blockchain-Based Software-Defined Industrial Internet of Things: A Dueling Deep ${Q}$ -Learning Approach
TL;DR: This paper proposes a blockchain (BC)-based consensus protocol in SDIIoT, along with detailed consensus steps and theoretical analysis, where BC works as a trusted third party to collect and synchronize network-wide views between different SDN controllers.
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Deep Q-Learning Aided Networking, Caching, and Computing Resources Allocation in Software-Defined Satellite-Terrestrial Networks
TL;DR: This paper proposes a software-defined STN to manage and orchestrate networking, caching, and computing resources jointly, and forms the joint resources allocation problem as a joint optimization problem, and uses a deep Q-learning approach to solve it.
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A study of aerosol liquid water content based on hygroscopicity measurements at high relative humidity in the North China Plain
TL;DR: In this article, a novel method is presented to calculate the aerosol liquid water content at high relative humidity based on measurements of aerosol hygroscopic growth factor, particle number size distribution and relative humidity in the Haze in China (HaChi) summer field campaign (July-August 2009) in the North China Plain.
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TDoA for Passive Localization: Underwater versus Terrestrial Environment
TL;DR: This paper proposes a time difference of arrival (TDoA) algorithm for passive localization in underwater and terrestrial environment and applies a modified UWB Saleh-Valenzuela (S-V) model to characterize the underwater acoustic fading channel.
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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.