@inproceedings{05ef59ae49e444d6a7e4dd2677731c38,
title = "Reinforcement Learning-based MAC for Reconfigurable Intelligent Surface-Assisted Wireless Sensor Networks",
abstract = "In this short paper, a reinforcement learning based back-off mechanism is proposed for a Reconfigurable Intelligent Surface (RIS)-assisted wireless sensor network. The proposed scheme has the capability to enable the sensors to access the RIS in an interference-free manner based on the intelligently selected back-off values. One of the main features of the proposed scheme is that sensors can avoid access interference without any need of additional signaling. Simulation results demonstrate that the proposed scheme significantly achieves higher network throughput and energy efficiency compared to benchmark Binary Exponential Back-off (BEB).",
keywords = "Back-off, interference, medium access control, Q-learning, RIS, wireless sensor networks",
author = "Faisal Ahmed and Ethungshan Shitiri and Cho, \{Ho Shin\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th International Conference on Ubiquitous and Future Networks, ICUFN 2022 ; Conference date: 05-07-2022 Through 08-07-2022",
year = "2022",
doi = "10.1109/ICUFN55119.2022.9829609",
language = "English",
series = "International Conference on Ubiquitous and Future Networks, ICUFN",
publisher = "IEEE Computer Society",
pages = "253--255",
booktitle = "ICUFN 2022 - 13th International Conference on Ubiquitous and Future Networks",
address = "United States",
}