Joint Beamforming and Offloading Design for Integrated Sensing, Communication, and Computation System

Mobile edge computing (MEC) is powerful in alleviating the heavy computing tasks in integrated sensing and communication (ISAC) systems. In this paper, we investigate joint beamforming and offloading design within a three-tier integrated sensing, communication, and computation (ISCC) framework comprising one cloud server, multiple mobile edge servers, and multiple terminals. While executing sensing tasks, the user terminals can optionally offload sensing data to either MEC servers or the cloud server. To minimize the execution latency, we jointly optimize the transmit beamforming vectors and offloading decision variables under the constraint of sensing performance. An alternating optimization algorithm based on fractional programming is proposed to tackle the non-convex problem. Simulation results demonstrate the superiority of the proposed mechanism in terms of convergence and task execution time reduction, compared with the state-of-the-art two-tier ISCC framework.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-04-16
DOI
https://doi.org/10.1109/tvt.2025.3561430
Citations
12
Primary Topic
Antenna Design and Optimization
Type
article
Field-Weighted Citation Impact
49.94
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article

Joint Beamforming and Offloading Design for Integrated Sensing, Communication, and Computation System

Zesong Fei, Yiqing Zhou, Peng Liu, Fan Liu et al.
12 citations
IEEE Transactions on Vehicular Technology
Antenna Design and Optimization
49.94
article

Joint Beamforming and Offloading Design for Integrated Sensing, Communication, and Computation System

Zesong Fei, Yiqing Zhou, Peng Liu, Fan Liu, Xinyi Wang, Yan Zhang
article en
12 citations

Abstract

Mobile edge computing (MEC) is powerful in alleviating the heavy computing tasks in integrated sensing and communication (ISAC) systems. In this paper, we investigate joint beamforming and offloading design within a three-tier integrated sensing, communication, and computation (ISCC) framework comprising one cloud server, multiple mobile edge servers, and multiple terminals. While executing sensing tasks, the user terminals can optionally offload sensing data to either MEC servers or the cloud server. To minimize the execution latency, we jointly optimize the transmit beamforming vectors and offloading decision variables under the constraint of sensing performance. An alternating optimization algorithm based on fractional programming is proposed to tackle the non-convex problem. Simulation results demonstrate the superiority of the proposed mechanism in terms of convergence and task execution time reduction, compared with the state-of-the-art two-tier ISCC framework.

IEEE Transactions on Vehicular TechnologyVol. 74(9)
Beijing Institute of Technology (CN), Institute of Computing Technology (CN), University of Chinese Academy of Sciences (CN), Southeast University (CN)
Openalex Percentile: Top 0%
Antenna Design and Optimization
49.94
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