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Medium Access Control for Double-IRS in IoT Networks

delete2025-12-23
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PRE
AI
G
Ghazy Mahendra
T
Tae‐Jin Lee
DOI:10.1109/TGCN.2025.3614785delete
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Abstract

Abstract

En 中文
The change from a network with single-Intelligent Reflecting Surface (IRS) to Double-IRS tempts us with the increase in gain, from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(M^{2})$ </tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(M^{4})$ </tex-math></inline-formula>, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> is the number of elements of the IRS. However, the existing MAC protocols are not optimally designed for Double-IRS architectures, leading to performance degradation or operational challenges. We address this gap by introducing a novel reservation protocol. This protocol coordinates devices reservation, IRS configuration, and packet transmission phases. We model and analyze the reservation intervals for both Carrier Sense Multiple Access (CSMA) and Frame Slotted ALOHA (FSA)-based contention protocols using a discrete event combinatorics method. Our findings demonstrate that implementing linear estimation in the optimized reservation Medium Access Control (MAC) protocol improves utilization and reduces per-packet delay in quasi-static channel setting. Additionally, cascaded and parallel IRS configurations are shown to lower total power consumption in a quasi-static channel system without device mobility. We transform the original optimization problems into efficiently solvable sub-optimal formulations to enable practical implementation.
Keywords:
Intelligent reflecting surface (IRS)
medium access control (MAC)
double-IRS

Journal

I
IEEE Transactions on Green Communications and Networking
IF:
6.7
Papers:
1.3K
Citations:
4.3K

Organization

S
Sungkyunkwan University
Scholars:
2.8K
Papers: 1.1K
Citations: 2