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Reinforcement Learning-based MAC for Reconfigurable Intelligent Surface-Assisted Wireless Sensor Networks
- Ahmed, Faisal;
- Shitiri, Ethungshan;
- Cho, Ho-Shin
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0초록
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).
키워드
back-off; interference; medium access control; RIS; Q-learning; wireless sensor networks; CHALLENGES
- 제목
- Reinforcement Learning-based MAC for Reconfigurable Intelligent Surface-Assisted Wireless Sensor Networks
- 저자
- Ahmed, Faisal; Shitiri, Ethungshan; Cho, Ho-Shin
- 발행일
- 2022
- 유형
- Proceedings Paper
- 저널명
- 2022 THIRTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN)
- 페이지
- 253 ~ 255
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 3 페이지
- ISSN
- E 2165-8536
P 2165-8528