MPC for Online Power Control in Energy Harvesting Sensor Networks

Hanan Al-Tous, Imad Barhumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper, model-predictive-control (MPC) framework is proposed for an online power control and data scheduling of energy-harvesting (EH) multi-hop wireless-sensor-networks (WSNs). The network consists of M sensor nodes transmitting their sensed information to a sink node through multi-hop transmission. Each sensor node has a battery of limited capacity to save the harvested energy and a buffer of limited size to store both the sensed and relayed data. The dynamic resource allocation problem is formulated using the MPC framework aiming to efficiently utilize the available harvested energy and transmit the data of all sensor nodes. The solution of the proposed MPC framework is compared with an offline solution, which is obtained assuming prior knowledge of the sensed data and harvested energy. Simulation results demonstrate the merits of the proposed approach.

Original languageEnglish
Title of host publication2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781538663554
Publication statusPublished - Jul 20 2018
Event87th IEEE Vehicular Technology Conference, VTC Spring 2018 - Porto, Portugal
Duration: Jun 3 2018Jun 6 2018

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252


Other87th IEEE Vehicular Technology Conference, VTC Spring 2018


  • Wireless sensor network
  • energy harvesting
  • model predictive control
  • offline control

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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