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FSF-LoRa: Fractional-Spreading-Factor-LoRa for Flexible Resource Allocation

研究成果: Conference contribution

抄録

With the development of the Internet of Things (IoT), Long Range Wide Area Network (LoRaWAN) that enables communication over long distances with low power consumption has attracted attention in recent years. LoRaWAN adopts LoRa modulation as the physical layer technology, with high noise immunity but a low data rate. Until now, various studies have attempted to increase the data rate of LoRaWAN by increasing the number of bits per LoRa symbol. Several studies increase throughput by using an algorithm to separate LoRa signals by transmitting multiple LoRa signals using the same spreading factor. Signal separation requires complex algorithms on the demodulator, and they have yet to try to increase the overall system throughput by increasing the number of semi-orthogonal channels. This paper proposes Fractional Spreading Factor (FSF)-LoRa, which introduces fractional spreading factors. This is achieved by introducing a new parameter called the Fractional Coefficient (FC). FSF-LoRa increases the number of new semi-orthogonal channels. Computer simulations show that the proposed FSF-LoRa with FC of 0.5 can improve the system throughput by about more than 6% compared to the conventional LoRa.

本文言語English
ホスト出版物のタイトル2024 IEEE 100th Vehicular Technology Conference, VTC 2024-Fall - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9798331517786
DOI
出版ステータスPublished - 2024
外部発表はい
イベント100th IEEE Vehicular Technology Conference, VTC 2024-Fall - Washington, United States
継続期間: 2024 10月 72024 10月 10

出版物シリーズ

名前IEEE Vehicular Technology Conference
ISSN(印刷版)1550-2252

Conference

Conference100th IEEE Vehicular Technology Conference, VTC 2024-Fall
国/地域United States
CityWashington
Period24/10/724/10/10

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 電子工学および電気工学
  • 応用数学

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