Optimum Transmission Policies for Energy Harvesting Sensor Networks Powered by a Mobile Control Center

Tao Li, Pingyi Fan, Zhengchuan Chen, Khaled Letaief

Research output: Contribution to journalArticle

24 Citations (Scopus)


Wireless energy transfer, namely, radio frequency (RF)-based energy harvesting, is a potential way to prolong the lifetime of energy-constrained devices, especially in wireless sensor networks. However, due to huge propagation attenuation, its energy efficiency is regarded as the biggest bottleneck to wide applications. It is critical to find appropriate transmission policies to improve the global energy efficiency in this kind of system. To this end, this paper focuses on the sensor networks scenario, where a mobile control center powers the sensors by RF signal and also collects information from them. Two related schemes, called harvest-and-use scheme and harvest-store-use scheme, are investigated. In the harvest-and-use scheme, as a benchmark, both constant and adaptive transmission modes from sensors are discussed. In the harvest-store-use scheme, we propose a new concept, the best opportunity for wireless energy transfer, and use it to derive an explicit closed-form expression of optimal transmission policy. It is shown by simulation that a considerable improvement in terms of energy efficiency can be obtained with the help of the transmission policies developed in this paper. Furthermore, the transmission policies are also discussed under the constraint of fixed information rate. The minimal required power, the performance loss from the new constraint, and the effect of fading are then presented.

Original languageEnglish
Article number7488201
Pages (from-to)6132-6145
Number of pages14
JournalIEEE Transactions on Wireless Communications
Issue number9
Publication statusPublished - 1 Sep 2016
Externally publishedYes



  • circuit energy consumption
  • cumulative throughput
  • Energy harvesting
  • opportunistic wireless energy transfer
  • optimum transmission policy

ASJC Scopus subject areas

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

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