长期远程状态估计的最优功率控制:权衡角度
Optimal Power Control for Long-term Remote State Estimation: A Tradeoff Perspective
   Wei Xing Zheng
报告人照片   Wei Xing Zheng教授分别于1982、1984、1989年在东南大学获得学士、硕士、博士学位,曾于东南大学、英国帝国理工学院、西澳大利亚大学、科廷理工大学、慕尼黑工业大学、弗吉尼亚大学和加州大学戴维斯分校任教、研究或访问,现任澳大利亚西悉尼大学全职教授。Zheng教授是IEEE Fellow,并入选为2015、2016和2017年年度汤森路透全球高被引科学家。过去曾担任5个IEEE期刊副主编(TCS-I:STA, TAC, SPL, TCS-II:EB, TFS),以及IEEE IEEE Transactions on Circuits and Systems-I: Regular Papers客座主编。现担任Automatica, IEEE Transactions on Automatic Control (the second term), IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Control of Network Systems等期刊副主编。
  This talk considers the scenario that a power-limited sensor sends the state information of a physical plant to a remote estimator over a correlated block fading wireless channel. It is of importance to design a proper transmission power scheduling policy to achieve desirable long-term estimation quality at the remote estimator side and save the power cost at the sensor side concurrently. To achieve this, we construct an optimization problem which minimizes the weighted sum of the average estimation error and the average power cost in an infinite time horizon. We derive the existence of the optimal solution and its structure. To approximate the unclear part in the optimal solution, we restrain the sensor power control policy and obtain a close-form expression of this part. Then a suboptimal power scheduling strategy with the explicit expression is presented.
报告时间:2018年07月23日15时00分    报告地点:西区电二楼208会议室
报名截止日期:2018年07月23日    可选人数:40