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    A New Non-linear Joint Model for RF Energy Harvesters in Wireless Networks

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    Type
    Article
    Authors
    Qahtani, Dokhyl Al
    Chen, Yunfei
    Feng, Wei
    Alouini, Mohamed-Slim cc
    KAUST Department
    Communication Theory Lab
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2021
    Permanent link to this record
    http://hdl.handle.net/10754/667653
    
    Metadata
    Show full item record
    Abstract
    Many previous works have treated the conversion efficiency of an energy harvester as a constant or a non-linear function of input power, ignoring the non-linear effect of the operating frequency. Such assumption may lead to erroneous performance analysis or improper resource allocation. In this paper, a novel model is proposed to capture the non-linearity of the conversion efficiency as a function of the frequency and power. The paper first exploits the practical harvesters in the literature to model the conversion efficiency as a function of frequency at fixed power. Based on the shape of the efficiency curve, two categories of harvesters are referred to as Type-1 and Type-2. The best-fit model for each category is selected based on the adjusted R-square test. Next, these models are extended to jointly consider both power and frequency dependencies. Using these models, the performances of broad-band simultaneous wireless information and power transfer and OFDM hybrid access point are analysed and optimised. Iterative algorithms are used to find low-complexity solutions. Moreover, the impact of the non-linear conversion efficiency on the average battery life in LoRaWAN is analysed. Our results highlight the significant impact of using the joint model of conversion efficiency.
    Citation
    Qahtani, D. A., Chen, Y., Feng, W., & Alouini, M.-S. (2021). A New Non-linear Joint Model for RF Energy Harvesters in Wireless Networks. IEEE Transactions on Green Communications and Networking, 1–1. doi:10.1109/tgcn.2021.3059728
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Green Communications and Networking
    DOI
    10.1109/TGCN.2021.3059728
    Additional Links
    https://ieeexplore.ieee.org/document/9354851/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9354851
    ae974a485f413a2113503eed53cd6c53
    10.1109/TGCN.2021.3059728
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Electrical Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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