Energy Allocation and Utilization for Wirelessly Powered IoT Networks

被引:19
|
作者
Zhong, Shan [1 ]
Wang, Xiaodong [1 ]
机构
[1] Columbia Univ, Dept Elect Engn, New York, NY 10032 USA
来源
IEEE INTERNET OF THINGS JOURNAL | 2018年 / 5卷 / 04期
关键词
Discrete concavity; discrete steepest ascent; Internet of Things (IoT); Markov decision process (MDP); value iteration; wireless charging; TRANSMISSION; CAPACITY; MOBILE;
D O I
10.1109/JIOT.2018.2828851
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent development in wireless power transfer enables a new paradigm of energy harvesting communications that can significantly impact in Internet of Things (IoT) applications. In this paper, we study the wirelessly powered IoT networks, in which a central node transmits radio frequency (RF) energy to power the IoT sensors, and the sensors harvest RF power to transmit data back to the central node. In this IoT network, the sensors transmit data according to their energy utilization policies, and the central node allocates charging powers to all sensors. We design the sensor energy utilization policies and the power allocation among sensors by maximizing the total data throughput of the system. In particular, the subproblem of energy utilization policy design is formulated as a Markov decision process and the power allocation subproblem is formulated as discrete optimization. By showing several key properties of these two subproblems, we propose low-complexity algorithms to solve the subproblems optimally. We demonstrate the performance gains of the proposed algorithms over some simple heuristics via simulations in terms of the total data throughput in wireleslly powered IoT networks.
引用
收藏
页码:2781 / 2792
页数:12
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