Intelligent Reflecting Surface-aided URLLC in a Factory Automation Scenario

Ren, Hong, Wang, Kezhi and Pan, Cunhua (2022) Intelligent Reflecting Surface-aided URLLC in a Factory Automation Scenario. IEEE Transactions on Communications, 70 (1). pp. 707-723. ISSN 0090-6778

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Different from conventional wired line connections, industrial control through wireless transmission is widely regarded as a promising solution due to its reduced cost, increased long-term reliability, and enhanced reliability. However, mission-critical applications impose stringent quality of service (QoS) requirements that entail ultra-reliability low-latency communications (URLLC). The primary feature of URLLC is that the blocklength of channel codes is short, and the conventional Shannon’s Capacity is not applicable. In this paper, we consider the URLLC in a factory automation (FA) scenario. Due to densely deployed equipment in FA, wireless signal are easily blocked by the obstacles. To address this issue, we propose to deploy intelligent reflecting surface (IRS) to create an alternative transmission link, which can enhance the transmission reliability. In this paper, we focus on the performance analysis for IRS-aided URLLC-enabled communications in a FA scenario. Both the average data rate (ADR) and the average decoding error probability (ADEP) are derived under finite channel blocklength for seven cases: 1) Rayleigh fading channel; 2) With direct channel link; 3) Nakagami-m fading channel; 4) Imperfect phase alignment; 5) Multiple-IRS case; 6) Rician fading channel; 7) Correlated channels. Extensive numerical results are provided to verify the accuracy of our derived results.

Item Type: Article
Additional Information: Funding information: This work was supported in part by the National Key Research and Development Project under Grant 2019YFE0123600, National Natural Science Foundation of China (62101128), Basic Research Project of Jiangsu Provincial Department of Science and Technology (BK20210205) , High Level Personal Project of Jiangsu Province (JSSCBS20210105) and the Research Fund of National Mobile Communications Research Laboratory Southeast University (No.2018A01).
Uncontrolled Keywords: Intelligent Reflecting Surface (IRS), Reconfigurable Intelligent Surface (RIS), URLLC, Short-Packet Transmission
Subjects: G400 Computer Science
G500 Information Systems
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 13 Dec 2021 15:34
Last Modified: 24 Jan 2022 16:45

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