Semantic RF Waveform Adaptation in Flying Ad Hoc Networks via Hybrid Knowledge Bases and Deep Reinforcement Learning

Semantic RF Waveform Adaptation in Flying Ad Hoc Networks via Hybrid Knowledge Bases and Deep Reinforcement Learning

By directly encoding the semantic meaning into each RF waveform symbol, we can significantly reduce the communication overhead. Particularly, semantic communication in Flying Ad Hoc Networks (FANETs)—formed by uncrewed aerial vehicles (UAVs)—is a promising application for enabl...

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Bibliographic Details
Main Authors: Weiqiang Lyu, Linsheng He, Jiamiao Zhao, Fei Hu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Cyclic prefix
deep reinforcement learning
hybrid knowledge base
modulation
OFDM
semantic communications
Online Access:https://ieeexplore.ieee.org/document/11021564/
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