Energy transfer (ET) and energy harvesting (EH) through radio frequency (RF) signals are a promising technology that can reduce the dependency on batteries in wireless sensor networks. However, there is a tradeoff between the RF-based ET and data communication when they operate in the same frequency band. Therefore, a proper medium access control (MAC) protocol is needed in wireless powered sensor networks (WPSNs). However, a utilization degradation problem occurs when the distributed coordination function (DCF) MAC protocol of the IEEE 802.11 is applied to WPSNs. In order to overcome this problem, this paper extends the IEEE 802.11e enhanced DCF (EDCF) into a harvest-then-transmit-based modified EDCF MAC (HE-MAC) protocol. In addition, the HE-MAC's Markov chain model and steady-state probabilities are derived and used in the performance analysis. Next, based on the steady-state conditions, optimization is conducted to maximize the EH rate, which satisfies the frame generation rate and transfers additional energy to achieve a self-sustained energy consumption profile. Finally, the simulation performance of EH protocols HE-MAC, RF-MAC, and DOS are compared, where the results show that HE-MAC provides in a superior performance for the range of interest.
Bibliographical noteFunding Information:
Manuscript received February 14, 2017; revised May 25, 2017 and August 18, 2017; accepted September 10, 2017. Date of publication September 29, 2017; date of current version January 8, 2018. This work was supported by the Institute for Information and Communications Technology Promotion through the Korea government MSIT Project, The Development of Adaptive Network Technology with Multi-Media Multi-Path, under Grant 2017-0-00282. The associate editor coordinating the review of this paper and approving it for publication was W. Chen. (Corresponding author: Jong-Moon Chung.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: email@example.com; firstname.lastname@example.org; email@example.com). Digital Object Identifier 10.1109/TWC.2017.2757024
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics