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EPS-TRA: Energy efficient Peer Selection and Time switching Ratio Allocation for SWIPT-enabled D2D Communication

Khan, MS, Jangsher, S, Aloqaily, M, Jararweh, Y and Baker, T (2020) EPS-TRA: Energy efficient Peer Selection and Time switching Ratio Allocation for SWIPT-enabled D2D Communication. IEEE Transactions on Sustainable Computing, 5 (3). pp. 428-437. ISSN 2377-3782

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This paper considers device-to-device (D2D) network with Simultaneous Wireless Information and Power Transfer (SWIPT) enabled devices to ensure selfsustained communication in situations like disasters. Such direct link networks can ensure connectivity with devices having drained back-up, when trapped in collapsed infrastructure, through mutual sharing of energy on RF link. To guarantee successful execution of SWIPT session for an isolated device in wake of disasters, it is pertinent to select a reliable peer with ultimate aim to maximize link Energy Efficiency (EE). In practice, Energy Harvesting (EH) is not achievable after Information Decoding (ID), however, it has been made possible through splitting the signal in the time domain. Selection of D2D peer for selfsustained communication with an objective to maximize EE through optimum time based splitting of signal has not been extensively studied . In this paper to manifest the aforesaid goal, we worked out a joint problem of peer association and time switching ratio allocation with an objective to maximize the EE for a device contained under collapsed infrastructure. We propose an Energy efficient Peer Selection and Time switching Ratio Allocation (EPS-TRA) algorithm to solve the proposed mixed integer problem. Numerical results validate our proposed approach in acquiring better EE when compared with Uniform Allocation Scheme of time slots for EH & ID. Furthermore, results explain how EE of the link varies with the choice of constrained variables i.e. data rate and harvested energy.

Item Type: Article
Additional Information: © 2019 IEEE
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: IEEE
Date Deposited: 08 Jan 2020 11:32
Last Modified: 04 Sep 2021 08:12
DOI or Identification number: 10.1109/TSUSC.2020.2964897
URI: https://researchonline.ljmu.ac.uk/id/eprint/11976

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