Joint Optimization of Digital Twin Synchronization Performance for ISAC-Enabled Low-Altitude UAV Systems

DAI Chen; ZHU Jingyi; ZUO Yiping; CAO Haotong; XIAO Fu

doi:10.11999/JEIT261138

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DAI Chen, ZHU Jingyi, ZUO Yiping, CAO Haotong, XIAO Fu. Joint Optimization of Digital Twin Synchronization Performance for ISAC-Enabled Low-Altitude UAV Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT261138

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DAI Chen, ZHU Jingyi, ZUO Yiping, CAO Haotong, XIAO Fu. Joint Optimization of Digital Twin Synchronization Performance for ISAC-Enabled Low-Altitude UAV Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT261138

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Joint Optimization of Digital Twin Synchronization Performance for ISAC-Enabled Low-Altitude UAV Systems

doi: 10.11999/JEIT261138 cstr: 32379.14.JEIT261138

DAI Chen^{1, 2
,},
ZHU Jingyi^{1, 2},
ZUO Yiping^{1, 2},
CAO Haotong³,
XIAO Fu^{1, 2
,
,}

1.
School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2.
Jiangsu Provincial Key Laboratory of Internet of Things Intelligent Perception and Computing, Nanjing 210023, China
3.
College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Accepted Date: 2026-10-16
Rev Recd Date: 2026-10-16

Available Online: 2026-10-22

Abstract

Abstract

Objective With the rapid development of low-altitude intelligent networks, uncrewed aerial vehicles (UAVs) are increasingly used in inspection, logistics, and emergency response. These applications require continuous state sensing, wireless transmission, and interaction with digital twin (DT) models to support real-time decision-making. However, existing UAV DT systems generally separate sensing and communication, resulting in inefficient resource utilization, increased update latency, and limited synchronization accuracy. Integrated Sensing and Communication (ISAC) enables sensing and communication to share spectrum, transmit power, and hardware resources. Nevertheless, the coupling among UAV trajectory control, ISAC resource allocation, and DT synchronization performance remains insufficiently investigated. Therefore, this paper investigates the joint optimization of DT synchronization performance in ISAC-enabled low-altitude UAV systems. Methods An ISAC-enabled low-altitude UAV DT architecture consisting of the physical layer, ISAC module, and DT layer deployed on a mobile edge computing (MEC) server is established. Communication latency, sensing error, and DT mapping error models are developed to characterize the coupling among bandwidth allocation, transmit power, channel conditions, UAV trajectory, and synchronization performance. A joint optimization problem is formulated to minimize the long-term average DT mapping error subject to UAV mobility, wireless resource, and synchronization delay constraints. To solve the resulting non-convex problem, a collaborative framework integrating Digital Twin-aware Proximal Policy Optimization (DT-aware PPO) and Alternating Optimization (AO) is proposed. DT-aware PPO optimizes long-term UAV trajectory decisions, while the AO-based resource optimization module dynamically allocates bandwidth and transmit power at each time slot. The resulting DT synchronization performance is fed back to the PPO agent to coordinate long-term trajectory control and short-term resource allocation. Results and Discussions Simulation experiments are conducted on a MATLAB-based low-altitude UAV digital twin platform under a dynamic inspection scenario. Compared with the Non-ISAC-PPO scheme, the proposed method reduces the DT mapping error from 2.009 to 1.084 and the average communication delay from 13.102 s to 3.200 s (Fig. 4). Compared with the Random Trajectory and Equal Resource Allocation schemes, the proposed method achieves lower system objective value, synchronization delay, and DT mapping error by jointly optimizing UAV trajectory and wireless resources (Fig. 5). The average reward gradually converges during training, indicating stable learning of the DT-aware PPO policy (Fig. 6). Compared with Non-ISAC A*, ISAC-Greedy, and ISAC-RRT*, the proposed method achieves lower system cost, faster decision making, and improved performance recovery under dynamic disturbances (Fig. 7). Parameter sensitivity analysis further shows that increasing bandwidth and transmit power improves DT synchronization performance, whereas excessive task arrival rates degrade performance due to queue accumulation (Fig. 8). Conclusions This paper proposes a joint optimization method for DT synchronization in ISAC-enabled low-altitude UAV systems. A unified communication-sensing-DT coupling model is established to characterize the interactions among UAV trajectory, wireless resource allocation, communication latency, sensing accuracy, and DT synchronization performance. A collaborative framework integrating DT-aware PPO and AO-based resource allocation is developed for long-term trajectory control and short-term resource allocation. Simulation results demonstrate that the proposed method effectively reduces DT mapping error and communication latency while maintaining stable learning and a certain degree of adaptability to dynamic disturbances.
- Low-altitude UAV,
- Digital twin (DT),
- Integrated sensing and communication (ISAC),
- Trajectory optimization,
- Resource allocation

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References(20)

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