With the expanding scale of airport operations in China, the demand for low-altitude emergency support is increasingly urgent. Unmanned Aerial Vehicle Ad Hoc Networks (UANETs) have become a key technology for airport low-altitude emergency communications, but traditional neighbor discovery algorithms suffer from high delay, large energy consumption, poor connectivity and weak anti-interference ability due to UAV high-speed movement and dynamic blind zones in airport low-altitude scenarios. To address this issue, this paper proposes a fast neighbor discovery algorithm (DM-ND) integrating directional antennas and multi-channel parallel technology, combined with unequal-length slot allocation and dynamic duty cycle adjustment to optimize discovery efficiency and energy consumption. Verified by theoretical modeling and MATLAB simulation, all performance indicators of the algorithm meet the requirements of airport low-altitude emergency communications, providing reliable technical support and a reference for similar scenarios.
Na Zhao, Changlian Zheng, Weiyu Shi et al.· International Conference on...· 0 citations
To mitigate the impact of false-negative associations caused by negative sampling of DPPs, the proposed SENT-DTI method is inspired by the advantage of negative training (NT) strategy on identification of false-negative samples and design a novel NT strategy that adaptively learns the probability distribution of known DPP features by incorporating a unified high-confidence false-negative association filtering mechanism into a negative loss objective function.