TST, Vol. 17, No. 2, PP. 12-37
(Invited paper) Resource management in THz-based system: background, modelling and challenges
Zhuocheng Lai 1*, Chao Ren 1, Xu Ma 1, Lixin Sun 2, Xiang Yun 2, and Haijun Zhang 1,
1 University of Science and Technology, School of Computer & Communication Engineering, 30 Xueyuan Rd., Haidian District, Beijing, China
2 Baicells Technologies Co., Ltd., 10/11F, Building A1, Zhongguancun No.1, Yongfeng Industrial Base, Haidian District, Beijing, China
*1 Email: lzc@xs.ustb.edu.cn
(Received June 2024)
Abstract: Terahertz (THz) technology, with its ultra-wide bandwidth, is poised to play a significant role in the future of 6G wireless communications and sensing systems. This leap in technology, however, raises the bar for channel modelling, data transmission, structure of transceivers’ design, and signal processing. This paper delves into the propagation characteristics of communications within the THz band, outlines the architecture of THz transceivers, and explores the intricacies of managing wireless resources when THz communication intersects with other critical communication technologies. Furthermore, prevalent resource management issues within THz communications, together with strategies for addressing these challenges in model-based and machine learning (ML)-based methods are discussed, and concludes with a discussion on the future hurdles in managing resources within THz communication systems with integrated sensing and communication (ISAC) functionalities. As we navigate the convergence of varied communication technologies and escalating business demands, there’s a pressing need to merge traditional model-based optimization techniques with ML approaches to achieve effective and robust resource management.
Keywords: Terahertz communication, ISAC, Resource management, Machine learning
doi:
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