Energy-Efficiency Performance Analysis and Maximization Using Wireless Energy Harvesting in Wireless Sensor Networks

Zaki Masood, Sokhee P. Jung and Yonghoon Choi
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Zaki Masood: Department of Electrical Engineering, Chonnam National University, Gwangju 61186, Korea
Sokhee P. Jung: Department of Environment and Energy Engineering, Chonnam National University, Gwangju 61186, Korea
Yonghoon Choi: Department of Electrical Engineering, Chonnam National University, Gwangju 61186, Korea

Energies, 2018, vol. 11, issue 11, 1-15

Abstract: Paradigm shift to wireless power transfer provides opportunities for ultra-low-power devices to increase energy storage from electromagnetic (EM) sources. The notable gain occurs when EM sources deliver information as a meaningful signal with power transfer. Thus, energy harvesting (EH) is an active approach to obtain power from surrounding EM sources that transfer energy deliberately. This paper discusses energy efficiency (EE) trade-offs and EE maximization in simultaneous wireless power and information transfer (SWIPT) for wireless sensor networks (WSNs). The power splitting (PS) and time switching (TS) model for SWIPT are investigated in detail, where EE optimization is essential. This work formulates EE maximization problem as non-linear fractional programming and proposes a novel algorithm to solve the maximization problem using Lagrange dual decomposition. Numerical results reveal that the proposed algorithm maximizes EE in both PS and TS modes through noteworthy improvements.

Keywords: energy efficiency; energy harvesting; information decoding; quasi-concavity; wireless power transfer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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