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
相关论文
共 50 条
  • [31] Resource Allocation for Secure Short Packet Communications in Wireless Powered IoT Networks
    Xu, Ding
    Zhao, Haitao
    Zhu, Hongbo
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (08) : 11000 - 11005
  • [32] Resource Allocation for Wireless-Powered IoT Networks With Short Packet Communication
    Chen, Jie
    Zhang, Lin
    Liang, Ying-Chang
    Kang, Xin
    Zhang, Rui
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2019, 18 (02) : 1447 - 1461
  • [33] Wirelessly Powered Federated Learning Networks: Joint Power Transfer, Data Sensing, Model Training, and Resource Allocation
    Le M.
    Hoang D.T.
    Nguyen D.N.
    Hwang W.
    Pham Q.
    IEEE Internet of Things Journal, 2024, 11 (21) : 1 - 1
  • [34] On Max-Min Throughput in Backscatter-Assisted Wirelessly Powered IoT
    Yang, Changlin
    Wang, Xiaodong
    Chin, Kwan-Wu
    IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (01): : 137 - 147
  • [35] SEAL-RF: Secure Adiabatic Logic for Wirelessly Powered IoT Devices
    Dhananjay, Krithika
    Salman, Emre
    IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (02) : 1112 - 1123
  • [36] OPTIMIZED ENERGY ALLOCATION IN BATTERY POWERED IMAGE SENSOR NETWORKS
    Yu, Chao
    Sharma, Gaurav
    2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 3461 - 3464
  • [37] Wirelessly Powered IoT Sensor Facilitated by A Planar Electrically Small Huygens Rectenna
    Lin, Wei
    Ziolkowski, Richard W.
    2020 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND NORTH AMERICAN RADIO SCIENCE MEETING, 2020, : 17 - 18
  • [38] Wirelessly Powered Backscatter Communication Networks: Modeling, Coverage and Capacity
    Han, Kaifeng
    Huang, Kaibin
    2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2016,
  • [39] The Energized Point Process as a Model for Wirelessly Powered Communication Networks
    Deng, Na
    Haenggi, Martin
    IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2020, 4 (03): : 832 - 844
  • [40] Wirelessly Powered Microactuators
    Abeywardardana, Dulsha K.
    Hu, Aiguo Patrick
    Salcic, Zoran
    2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS FOR SUSTAINABLE ENERGY SYSTEMS (IESES), 2018, : 445 - 450