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Poster: Time Encoding for Energy Efficiency and Scalability in Wireless Networks

Published:04 October 2019Publication History

ABSTRACT

Low Power Wide Area Networks (LPWAN) desire 1) energy efficiency, 2)long communication range, and 3) scalability for ubiquitous connectivity. Existing technologies any two and trade off the third. We propose a differential time modulation that is energy efficient in a large-scale, long-range network.

References

  1. Yacine Challal Tifenn Rault, Abdelmadjid Bouabdallah. Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 2014.Google ScholarGoogle Scholar
  2. Marco Di Felice Luciano Bononi Federico Montori, Luca Bedogni. Machine-to-machine wireless communication technologies for the internet of things: Taxonomy, comparison and open issues. Pervasive and Mobile Computing, 2018.Google ScholarGoogle Scholar
  3. Zabih Ghassemlooy, AR Hayes, NL Seed, and ED Kaluarachchi. Digital pulse interval modulation for optical communications. IEEE Communications Magazine, 1998.Google ScholarGoogle Scholar
  4. Lawrence J. Mueller. Synchronization of pulse code modulation telemetry. Master's thesis, University of Missouri at Rolla, 1968.Google ScholarGoogle Scholar

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  1. Poster: Time Encoding for Energy Efficiency and Scalability in Wireless Networks

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      • Published in

        cover image ACM Conferences
        S3'19: Proceedings of the 2019 on Wireless of the Students, by the Students, and for the Students Workshop
        October 2019
        50 pages
        ISBN:9781450369299
        DOI:10.1145/3349621

        Copyright © 2019 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 4 October 2019

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        Overall Acceptance Rate65of93submissions,70%
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