工业物联网网络中太赫兹通信的设备与智能反射面联合关联
Joint Devices and IRSs Association for Terahertz Communications in Industrial IoT Networks
AI总结：
针对工业物联网太赫兹通信面临的高路径损耗等挑战，提出基于Gale-Shapley算法的设备与智能反射面联合关联方案，在不完美信道状态信息下最大化和速率，效率优于穷举搜索等方法。
摘要：
工业物联网（IIoT）使各行业能够利用各类需要高数据速率的技术构建大型互联系统。太赫兹（THz）通信被视为实现数太比特每秒（Tbps）数据速率的候选技术。尽管如此，由于高路径损耗和分子吸收，在太赫兹频段建立可靠的通信链路仍然是一项挑战。为克服这些限制，本文提出将智能反射面（IRSs）与太赫兹通信结合，以支撑面向工业物联网的未来智能工厂。本文构建了功率分配以及工业物联网设备与智能反射面联合关联（JIIA）问题，该问题属于混合整数非线性规划（MINLP）问题。此外，JIIA问题的目标是在信道状态信息（CSI）不完美的情况下最大化和速率。为解决这一非确定性多项式困难（NP-hard）问题，我们将其分解为多个子问题并迭代求解。具体而言，我们提出了一种基于Gale-Shapley算法的JIIA方案，以实现上下行智能反射面之间的稳定匹配。我们通过将基于Gale-Shapley的JIIA算法与不完美CSI下的穷举搜索（ES）、贪心搜索（GS）和随机关联（RA）进行对比，验证了所提方案的有效性。复杂度分析表明，我们的算法比穷举搜索（ES）效率更高。
英文摘要：
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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