4.6 Article

Optimal Power Allocation for Maximizing Energy Efficiency in DAS-Based IoT Network

期刊

IEEE SYSTEMS JOURNAL
卷 15, 期 2, 页码 2342-2348

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2020.3013693

关键词

Resource management; Receivers; RF signals; Wireless communication; Antennas; Wireless sensor networks; Power demand; Distributed antenna system (DAS); energy efficiency (EE); optimal power allocation; simultaneous wireless information and power transfer (SWIPT); spectral efficiency (SE)

资金

  1. Basic Science Research Program through the National Research Foundation of Korea - Ministry of Education [NRF-2019R1I1A3A01060631]

向作者/读者索取更多资源

This article discusses the maximization of energy efficiency (EE) for distributed antenna systems based on simultaneous wireless information and power transfer (SWIPT), presenting a tradeoff between EE and spectral efficiency and proposing an algorithm to optimize power allocation. The proposed algorithm uses Lagrangian multiplier method and Karush-Kuhn-Tucker conditions to find the optimal solution without iterative computation, achieving maximum energy transfer through optimal power splitting ratio.
Distributed antenna system based on simultaneous wireless information and power transfer (SWIPT) can be one of the promising solutions in maximizing energy efficiency (EE), where ultra low power devices harvest energy in power splitting (PS) mode. The paradigm shift of the internet-of-things (IoT) has increased the number of IoT devices and associated sensitive data exchange on the internet. Like the EE is a noteworthy aspect in ultra low power devices, energy harvesting (EH) is an active approach from surrounding electromagnetic sources. This article deals with EE maximization for SWIPT using PS mode. In the SWIPT system, this article presents a tradeoff between EE and spectral efficiency and proposes an algorithm, which allocates optimal power to each distributed antenna port. For an IoT device, the PS scheme implements EH and information decoding operations. The proposed algorithm is based on the Lagrangian multiplier method and Karush-Kuhn-Tucker conditions to find the optimal solution without iterative computation compared to the conventional iterative method. Simulation results reveal that the proposed algorithm achieves maximum energy transfer by the using optimal PS ratio.

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