Wireless Information and Power Transfer: Probability-Based Power Allocation and Splitting With Low Complexity

Kisong Lee, Jeong Gil Ko

Research output: Contribution to journalArticle

Abstract

Despite energy harvesting (EH) using radio frequency (RF) signals and the concept of simultaneous wireless information and power transfer (SWIPT) being attractive technologies to adapt in various low-power wireless systems, the research in these fields was mostly built upon less-practical configurations. While a resource allocation strategy was proposed to identify the optimal performance bounds for SWIPT systems, a huge computational complexity makes it impractical to apply to real-world systems. In this work, we figure out that the strategy for achieving the optimal performance bounds follows a water-filling algorithm similarly. We use this observation to propose a heuristic algorithm for finding a water level for power allocation and effective power splitting ratio with minimal complexity. Using analysis and simulations, we show that the proposed scheme achieves near-optimal performance with a significant lower complexity compared to previously proposed optimal-bound identifying schemes.

Original languageEnglish
Pages (from-to)1060-1064
Number of pages5
JournalIEEE Systems Journal
Volume12
Issue number1
DOIs
Publication statusPublished - 2018 Mar

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Energy harvesting
Heuristic algorithms
Water levels
Resource allocation
Computational complexity
Water

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

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Wireless Information and Power Transfer : Probability-Based Power Allocation and Splitting With Low Complexity. / Lee, Kisong; Ko, Jeong Gil.

In: IEEE Systems Journal, Vol. 12, No. 1, 03.2018, p. 1060-1064.

Research output: Contribution to journalArticle

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