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

Authors :
Ren, Chao
Song, Jiayin
Qiu, Mengxuan
Li, Yingqi
Wang, Xianmei
Source :
EURASIP Journal on Advances in Signal Processing; 1/13/2024, Vol. 2024 Issue 1, p1-14, 14p
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16876172
Volume :
2024
Issue :
1
Database :
Complementary Index
Journal :
EURASIP Journal on Advances in Signal Processing
Publication Type :
Academic Journal
Accession number :
174798704
Full Text :
https://doi.org/10.1186/s13634-023-01100-4