Joint Devices and IRSs Association for Terahertz Communications in Industrial IoT Networks

IF 5.3 2区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Green Communications and Networking Pub Date : 2023-11-14 DOI:10.1109/TGCN.2023.3332571
Muddasir Rahim;Georges Kaddoum;Tri Nhu Do
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Abstract

The Industrial Internet of Things (IIoT) enables industries to build large interconnected systems utilizing various technologies that require high data rates. Terahertz (THz) communication is envisioned as a candidate technology for achieving data rates of several terabits-per-second (Tbps). Despite this, establishing a reliable communication link at THz frequencies remains a challenge due to high pathloss and molecular absorption. To overcome these limitations, this paper proposes using intelligent reconfigurable surfaces (IRSs) with THz communications to enable future smart factories for the IIoT. In this paper, we formulate the power allocation and joint IIoT device and IRS association (JIIA) problem, which is a mixed-integer nonlinear programming (MINLP) problem. Furthermore, the JIIA problem aims to maximize the sum rate with imperfect channel state information (CSI). To address this non-deterministic polynomial-time hard (NP-hard) problem, we decompose the problem into multiple sub-problems, which we solve iteratively. Specifically, we propose a Gale-Shapley algorithm-based JIIA solution to obtain stable matching between uplink and downlink IRSs. We validate the proposed solution by comparing the Gale-Shapley-based JIIA algorithm with exhaustive search (ES), greedy search (GS), and random association (RA) with imperfect CSI. The complexity analysis shows that our algorithm is more efficient than the ES.
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工业物联网网络太赫兹通信联合设备和 IRS 协会
工业物联网(IIoT)使各行业能够利用各种需要高数据传输速率的技术构建大型互联系统。太赫兹(THz)通信被认为是实现每秒数太比特(Tbps)数据传输速率的候选技术。尽管如此,由于高路径损耗和分子吸收,在太赫兹频率下建立可靠的通信链路仍然是一项挑战。为了克服这些限制,本文建议使用具有太赫兹通信功能的智能可重构表面(IRS)来实现 IIoT 的未来智能工厂。在本文中,我们提出了功率分配和 IIoT 设备与 IRS 的联合关联(JIIA)问题,这是一个混合整数非线性编程(MINLP)问题。此外,JIIA 问题的目标是在信道状态信息(CSI)不完善的情况下最大化总和速率。为了解决这个非确定性多项式时间难(NP-hard)问题,我们将问题分解成多个子问题,并进行迭代求解。具体来说,我们提出了一种基于 Gale-Shapley 算法的 JIIA 解决方案,以获得上行和下行 IRS 之间的稳定匹配。我们通过比较基于 Gale-Shapley 算法的 JIIA 算法与穷举搜索 (ES)、贪婪搜索 (GS) 和不完美 CSI 随机关联 (RA) 算法,验证了所提出的解决方案。复杂性分析表明,我们的算法比 ES 算法更有效。
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来源期刊
IEEE Transactions on Green Communications and Networking
IEEE Transactions on Green Communications and Networking Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
6.20%
发文量
181
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