Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication

• URL: http://arxiv.org/abs/2311.12223v1
• Date: Mon, 20 Nov 2023 22:27:14 GMT
• Title: Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication
• Authors: Shisheng Hu, Jie Gao, Xinyu Huang, Mushu Li, Kaige Qu, Conghao Zhou, and Xuemin (Sherman) Shen
• Abstract summary: We propose a digital twin (DT)-based user-centric approach for processing sensing data in an ISAC system. A DT of the ISAC device is constructed to predict the impact of potential decisions on the long-term computation cost of the server. Experiments on executing DNN-based human motion recognition tasks are conducted to demonstrate the outstanding performance of the proposed DT-based approach.
• Score: 12.78137871351962
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a digital twin (DT)-based user-centric approach for processing sensing data in an integrated sensing and communication (ISAC) system with high accuracy and efficient resource utilization. The considered scenario involves an ISAC device with a lightweight deep neural network (DNN) and a mobile edge computing (MEC) server with a large DNN. After collecting sensing data, the ISAC device either processes the data locally or uploads them to the server for higher-accuracy data processing. To cope with data drifts, the server updates the lightweight DNN when necessary, referred to as continual learning. Our objective is to minimize the long-term average computation cost of the MEC server by optimizing two decisions, i.e., sensing data offloading and sensing data selection for the DNN update. A DT of the ISAC device is constructed to predict the impact of potential decisions on the long-term computation cost of the server, based on which the decisions are made with closed-form formulas. Experiments on executing DNN-based human motion recognition tasks are conducted to demonstrate the outstanding performance of the proposed DT-based approach in computation cost minimization.

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