Optimization of Short Packet Communication Resources for UAV Assisted Power Inspection

CHU Hang; DONG Zhihao; CAO Jie; SHI Huaifeng; ZENG Haiyong; ZHU Xu

doi:10.11999/JEIT250852

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CHU Hang, DONG Zhihao, CAO Jie, SHI Huaifeng, ZENG Haiyong, ZHU Xu. Optimization of Short Packet Communication Resources for UAV Assisted Power Inspection[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250852

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CHU Hang, DONG Zhihao, CAO Jie, SHI Huaifeng, ZENG Haiyong, ZHU Xu. Optimization of Short Packet Communication Resources for UAV Assisted Power Inspection[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250852

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Optimization of Short Packet Communication Resources for UAV Assisted Power Inspection

doi: 10.11999/JEIT250852 cstr: 32379.14.JEIT250852

1.
School of Information Science and Technology, Harbin Institute of Technology, Shenzhen Shenzhen 518055, China
2.
School of Electronics and Information Engineering‌, Nanjing University of Information Science and Technology Nanjing 210044, China
3.
School of Electronics and Information Engineering, Guangxi Normal University, Guilin 541001, China

Funds: The National Natural Science Foundation of China (62401182, 62171161), Guangdong Basic and Applied Basic Research Foundation (2025A1515010182), The Challenge-Driven Program of the Ministry of Industry and Information Technology, The Key Laboratory of Intelligent Support Technology for Complex Environments, Ministry of Education, Nanjing University of Information Science and Technology (NUIST-IST-JJ-2024-003)

Received Date: 2025-08-31
Accepted Date: 2025-11-05
Rev Recd Date: 2025-09-25

Available Online: 2025-11-15

Abstract

Abstract

Objective In Unmanned Aerial Vehicle (UAV)–assisted power grid inspection, the real-time acquisition and transmission of multi-modal data (key parameters, images, and videos) are essential for secure grid operation. These tasks require heterogeneous communication conditions, including ultra-reliable low-latency transmission and high-bandwidth data delivery. The limited wireless communication resources and UAV energy constraints restrict the ability to meet these conditions and reduce data timeliness and task performance. The present study is designed to establish a collaborative optimization framework for transmission scheduling and communication resource allocation, ensuring minimal system overhead while meeting task performance and reliability requirements. Methods To address the challenges mentioned above, a collaborative optimization framework is established for data transmission scheduling and communication resource allocation. Data transmission scheduling is formulated as a Markov Decision Process (MDP), in which communication consumption is incorporated into the decision cost. At the resource allocation level, Non-Orthogonal Multiple Access (NOMA) technology is applied to increase spectral efficiency. This approach reduces communication cost, maintains transmission reliability, and supports heterogeneous data transmission requirements in UAV-assisted power inspection. Results and Discussions The effectiveness of the proposed framework is verified through comprehensive simulations. A scenario is established in which the UAV is required to collect data from multiple distributed power towers within a designated area. A trade-off is observed between reliability and transmission speed (Fig. 3). At the same transmission rate, the bit error rate is reduced by approximately one order of magnitude. When a minimum long-packet signal-to-noise ratio threshold of 7 dB is applied, the optimized transmission system reduces the bit error rate from the 10^–3 level to the 10^–5 level while requiring only about a 0.4 Mbps decrease in transmission rate. After algorithm optimization, a lower effective signal-to-noise ratio is needed to achieve the same bit error rate; under the same signal-to-noise ratio, the short-packet error performance is improved, indicating more stable system behavior and higher transmission efficiency (Fig. 4). Conclusions This study presents a collaborative optimization framework that addresses the challenges posed by limited communication resources and heterogeneous data transmission requirements in UAV power inspection. By integrating MDP-based adaptive scheduling with NOMA-based joint resource allocation, the framework maintains an appropriate balance between communication performance and system overhead. The findings provide a theoretical and practical foundation for efficient, low-cost, and reliable data transmission in future intelligent autonomous aerial systems.
- Short-packet communication,
- Non-Orthogonal Multiple Access (NOMA),
- Data timeliness,
- MDP

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References(17)

References

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