Research on environment perception and behavior prediction of intelligent UAV based on semantic communication

• URL: http://arxiv.org/abs/2501.04480v1
• Date: Wed, 08 Jan 2025 13:03:34 GMT
• Title: Research on environment perception and behavior prediction of intelligent UAV based on semantic communication
• Authors: Kechong Ren, Li Gao, Qi Guan,
• Abstract summary: A reinforcement learning approach is introduced to enable drones with fast training capabilities and the ability to autonomously adapt to new virtual scenarios for effective resource allocation. A semantic communication framework for meta-universes is proposed, which utilizes the extraction of semantic information to reduce the communication cost and incentivize the transmission of information for meta-universe services. In our experiments, the drone adaptation performance is improved by about 35%, and the local offloading rate can reach 90% with the increase of the number of base stations.
• Score: 8.481025063242473
• License:
• Abstract: The convergence of drone delivery systems, virtual worlds, and blockchain has transformed logistics and supply chain management, providing a fast, and environmentally friendly alternative to traditional ground transportation methods;Provide users with a real-world experience, virtual service providers need to collect up-to-the-minute delivery information from edge devices. To address this challenge, 1) a reinforcement learning approach is introduced to enable drones with fast training capabilities and the ability to autonomously adapt to new virtual scenarios for effective resource allocation.2) A semantic communication framework for meta-universes is proposed, which utilizes the extraction of semantic information to reduce the communication cost and incentivize the transmission of information for meta-universe services.3) In order to ensure that user information security, a lightweight authentication and key agreement scheme is designed between the drone and the user by introducing blockchain technology. In our experiments, the drone adaptation performance is improved by about 35\%, and the local offloading rate can reach 90\% with the increase of the number of base stations. The semantic communication system proposed in this paper is compared with the Cross Entropy baseline model. Introducing blockchain technology the throughput of the transaction is maintained at a stable value with different number of drones.

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