English

DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Things

Information Theory 2024-11-18 v3 Machine Learning Systems and Control Signal Processing Systems and Control math.IT

Abstract

At the heart of the Internet of Things (IoT) -- a domain witnessing explosive growth -- the imperative for energy efficiency and the extension of device lifespans has never been more pressing. This paper presents DEEP-IoT, an innovative communication paradigm poised to redefine how IoT devices communicate. Through a pioneering feedback channel coding strategy, DEEP-IoT challenges and transforms the traditional transmitter (IoT devices)-centric communication model to one where the receiver (the access point) play a pivotal role, thereby cutting down energy use and boosting device longevity. We not only conceptualize DEEP-IoT but also actualize it by integrating deep learning-enhanced feedback channel codes within a narrow-band system. Simulation results show a significant enhancement in the operational lifespan of IoT cells -- surpassing traditional systems using Turbo and Polar codes by up to 52.71%. This leap signifies a paradigm shift in IoT communications, setting the stage for a future where IoT devices boast unprecedented efficiency and durability.

Keywords

Cite

@article{arxiv.2403.00321,
  title  = {DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Things},
  author = {Yulin Shao},
  journal= {arXiv preprint arXiv:2403.00321},
  year   = {2024}
}
R2 v1 2026-06-28T15:05:35.379Z