@inproceedings{dba2d0820bc84922b55bce6497286f6c,
title = "AI/ML-Based Sensing-Assisted Edge Computing in Next-Generation Mobile Networks",
abstract = "Integrated sensing and communications (ISAC) has received increased attention in light of the high-frequency bands to be employed by next-generation mobile networks; such wave-form technologies natively support high-speed communications and high-resolution sensing, the latter of which, thus far, has been reserved exclusively for radar sensing platforms. To advance this integration, we propose two sensing parameters and corresponding analytics to be incorporated into two sequential optimization problems to minimize the latency in an end-to-end edge computing network. It is shown that without vital sensing functionalities, the network consistently executes poor offloading decisions. However, when equipped with crucial sensing-analytics, the best latency performance is guaranteed.",
keywords = "artificial intelligence, core network, edge computing, latency, offloading, sensing",
author = "Hossain, {Abdullah Ridwan} and Abbas Kiani and Tony Saboorian and Amanda Xiang and John Kaippallimali and Nirwan Ansari",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023 ; Conference date: 06-11-2023 Through 08-11-2023",
year = "2023",
doi = "10.1109/CSCN60443.2023.10453202",
language = "English (US)",
series = "2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "77--82",
booktitle = "2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023",
address = "United States",
}