基于测量的60 GHz毫米波工业通信随机信道模型

IF 5.2 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of the Industrial Electronics Society Pub Date : 2023-11-20 DOI:10.1109/OJIES.2023.3334299
Joseba Osa;Niclas Björsell;Iñaki Val;Mikel Mendicute
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引用次数: 0

摘要

毫米波频谱中的通信在过去几年中变得越来越重要,因为它们是应对不同用例中不断增长的吞吐量和延迟需求的有希望的候选者。目前,已经进行了一些努力来表征这些信号的传播介质,目的是相应地设计相应的通信协议,并且已经研究了各种室外/室内位置。然而,很少有作品支持工业场景,由于它们在可靠性、确定性和延迟方面的严格要求,工业场景要求特别高。本研究旨在深入了解60 GHz毫米波信号在典型工业车间中的传播情况,以探索这种场景的特殊性。为了实现这一目标,在这种环境下进行了广泛的测量活动,并提出并验证了随机信道模型。
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Measurement Based Stochastic Channel Model for 60 GHz Mmwave Industrial Communications
Communications in the mmWave spectrum are gaining relevance in the last years as they are a promising candidate to cope with the increasing demand of throughput and latency in different use cases. Nowadays, several efforts have been carried out to characterize the propagation medium of these signals with the aim of designing their corresponding communication protocols accordingly, and a wide variety of both outdoor/indoor locations have already been studied. However, very few works endorse industrial scenarios, which are particularly demanding due to their stringent requirements in terms of reliability, determinism, and latency. This work aims to provide an insight of the propagation of 60 GHz mmWave signals in a typical industrial workshop in order to explore the particularities of this kind of scenario. In order to achieve this, an extensive measurement campaign has been carried out in this environment and a stochastic channel model has been proposed and validated.
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来源期刊
IEEE Open Journal of the Industrial Electronics Society
IEEE Open Journal of the Industrial Electronics Society ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
10.80
自引率
2.40%
发文量
33
审稿时长
12 weeks
期刊介绍: The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments. Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.
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