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Jiandong Li

Researcher at Xidian University

Publications -  670
Citations -  9377

Jiandong Li is an academic researcher from Xidian University. The author has contributed to research in topics: Wireless network & MIMO. The author has an hindex of 37, co-authored 620 publications receiving 6970 citations. Previous affiliations of Jiandong Li include Cornell University & Nanjing University of Information Science and Technology.

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Maximum likelihood method for integer frequency offset estimation of OFDM systems

TL;DR: In this paper, a novel method for integer frequency offset estimation of OFDM systems is derived, which is based on the maximum likelihood (ML) technique and exploits the differential information between two consecutive blocks of OFD data symbols in the frequency domain.
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Scalable and robust medium access control protocol in wireless body area networks

TL;DR: A modified medium access control (MAC) protocol for WBAN with focus on the simplicity, dependability and power efficiency is proposed and results show that the protocol effectively decreases the probability of collision in a CAP and extends the CFP slots to support more traffic with quality of service (QoS) guarantee.
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Influences of external forcing changes on the summer cooling trend over East Asia

TL;DR: In this article, the authors investigated the influence of changes in external forcing such as greenhouse gases (GHGs), total solar irradiance (TSI), ozone, and direct effects of aerosols on the cooling trend over East Asia.
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On the Capacity of Downlink Multi-Hop Heterogeneous Cellular Networks

TL;DR: The spectral efficiency enhancement condition under which the increase of BS density and transmit power improve the spectral efficiency, thereby enhancing the capacity of MHCNs is obtained and quantified for the first time.
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Critical nodes detection in mobile ad hoc network

TL;DR: A novel critical node detection algorithm-DMCC (detection algorithm based on midpoint coverage circle) is presented, a distributed algorithm which adapts the dynamic topology adaptively, detects the critical node faster and more reliably, and decreases the detection overheads efficiently.