TY - JOUR
T1 - Phase-aware directional energy transmission algorithm in multiple directional RF energy source environments
AU - Ko, Haneul
AU - Pack, Sangheon
N1 - Funding Information:
Manuscript received June 3, 2018; revised September 19, 2018; accepted November 2, 2018. Date of publication November 5, 2018; date of current version January 15, 2019. This work was supported in part by the National Research Foundation of Korea Grant funded by the Korean Government (MSIP) Grant 2017R1E1A1A01073742 and in part by the Institute for Information and communications Technology Promotion Grant funded by the Korea government (MSIT) Grant 2017-0-00195, Development of Core Technologies for Programmable Switch in Multi-Service Networks. The review of this paper was coordinated by Prof. Y. Li. (Corresponding author: Sangheon Pack.) The authors are with the School of Electrical Engineering, Korea University, Seoul 02841, Korea (e-mail:,st_basket@korea.ac.kr; shpack@korea.ac.kr).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2019/1
Y1 - 2019/1
N2 - Radio frequency (RF) energy harvesting technique has received high attention as a promising technology for Internet of Things (IoT) based industrial systems due to its flexibility of energy supply. When multiple IoT gateways are used as directional RF energy sources, the direction and phase of RF energy transmissions influence the RF energy transmission efficiency. In this paper, we propose a phase-aware directional energy transmission algorithm (PA-DETA) where directional RF energy sources (e.g., IoT gateways) are connected to a controller and their operation parameters (i.e., RF energy transmission direction and initial phase) are decided by the controller to maximize the total harvested energy while maintaining the energy consumption in RF energy sources and the number of discarded packets due to energy depletion of harvesting nodes below certain levels. To optimize the performance of PA-DETA, we formulate a constraint Markov decision process and the optimal policy on the direction and initial phase of RF energy transmissions is obtained by a linear programming. Evaluation results demonstrate that PA-DETA with the optimal policy outperforms the comparison schemes in terms of the total harvested energy, the energy consumption in RF energy sources, and the packet discard rate.
AB - Radio frequency (RF) energy harvesting technique has received high attention as a promising technology for Internet of Things (IoT) based industrial systems due to its flexibility of energy supply. When multiple IoT gateways are used as directional RF energy sources, the direction and phase of RF energy transmissions influence the RF energy transmission efficiency. In this paper, we propose a phase-aware directional energy transmission algorithm (PA-DETA) where directional RF energy sources (e.g., IoT gateways) are connected to a controller and their operation parameters (i.e., RF energy transmission direction and initial phase) are decided by the controller to maximize the total harvested energy while maintaining the energy consumption in RF energy sources and the number of discarded packets due to energy depletion of harvesting nodes below certain levels. To optimize the performance of PA-DETA, we formulate a constraint Markov decision process and the optimal policy on the direction and initial phase of RF energy transmissions is obtained by a linear programming. Evaluation results demonstrate that PA-DETA with the optimal policy outperforms the comparison schemes in terms of the total harvested energy, the energy consumption in RF energy sources, and the packet discard rate.
KW - Energy harvesting
KW - Internet of Things (IoT)
KW - constraint Markov decision process (CMDP)
KW - directional energy transmission
KW - radio frequency (RF) energy
UR - http://www.scopus.com/inward/record.url?scp=85056188180&partnerID=8YFLogxK
U2 - 10.1109/TVT.2018.2879723
DO - 10.1109/TVT.2018.2879723
M3 - Article
AN - SCOPUS:85056188180
SN - 0018-9545
VL - 68
SP - 359
EP - 367
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 1
M1 - 8523799
ER -