GLGuopeng Liu

Guopeng Liu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Guopeng Liu has a total of 2 co-authors. Here are the top co-authors by number of shared publications:

  • Linlin Mao

    Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China, and also with the University of Chinese Academy of Sciences, Beijing 101408, China

    1 shared publication
  • Shefeng Yan

    Institute of AI for Industries, Chinese Academy of Sciences

    1 shared publication

Latest Publications

  • Receiver-Only-Based Time Synchronization Under Exponential Delays in Underwater Wireless Sensor Networks

    by Guopeng Liu, Shefeng Yan, Linlin Mao

    In this paper, we consider the receiver-only-based time synchronization in underwater wireless sensor networks with exponential delays emerging during the message exchanges. Our study is motivated by the fact that 25% of timing messages are discarded in existing Receiver-Only-Synchronization (ROS) based schemes to cope with the interaction between the discontinuity of the likelihood function and the unknown clock skews, which would result in a massive waste of energy. To account for this issue, a general ROS model under the exponential delay assumption, with clock skews taken into consideration and all timing messages utilized, is introduced. Following the proposed ROS model, we develop a three-step method to jointly estimate clock offsets and skews of both active and silent nodes, as well as other unknown parameters. Specifically, an estimation on clock offset and skew for the active node using support vector machine is followed by a joint maximum likelihood estimation of the clock skew and clock offset for silent node as well as clock offset for active node, and a minimum variance unbiased estimation of the offsets for both active and silent nodes. Such method further improves the estimation accuracy of the proposed ROS model. The effectiveness and robustness of the proposed method is verified by simulations results.