Details

Autor(en) / Beteiligte

• Ren, Chao
• Song, Jiayin
• Qiu, Mengxuan
• Li, Yingqi
• Wang, Xianmei

Titel

Air–ground integrated artificial intelligence of things with cognition-enhanced interference management

Ist Teil von

• EURASIP journal on advances in signal processing, 2024-12, Vol.2024 (1), p.12-14, Article 12

Ort / Verlag

Cham: Springer International Publishing

Erscheinungsjahr

2024

Quelle

SpringerLink

Beschreibungen/Notizen

• Integrated air–ground network enhances AIoT performance by improving spectral efficiency, achieving high-speed, stable network connectivity, and enabling sensing, learning, and decision-making. However, unmanned aerial vehicles (UAVs) can lead to local spectrum congestion and competition. To address this issue, intelligent signal processing techniques are employed to enhance AIoT system performance and stability through intelligent multi-channel sensing and communication. A novel communication framework inspired by brain cognition for UAV communication in heterogeneous environments is introduced. This framework iteratively determines the importance of signals, effectively eliminating unimportant signals with interference characteristics, and reducing their transmission power. Simulation results demonstrate the superiority of this method in terms of communication performance.