AI/ML-Based Sensing-Assisted Edge Computing in Next-Generation Mobile Networks
Document Type
Conference Proceeding
Publication Date
1-1-2023
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.
Identifier
85187790699 (Scopus)
ISBN
[9798350395389]
Publication Title
2023 IEEE Conference on Standards for Communications and Networking Cscn 2023
External Full Text Location
https://doi.org/10.1109/CSCN60443.2023.10453202
First Page
77
Last Page
82
Recommended Citation
Hossain, Abdullah Ridwan; Kiani, Abbas; Saboorian, Tony; Xiang, Amanda; Kaippallimali, John; and Ansari, Nirwan, "AI/ML-Based Sensing-Assisted Edge Computing in Next-Generation Mobile Networks" (2023). Faculty Publications. 2146.
https://digitalcommons.njit.edu/fac_pubs/2146