arXiv:2507.17188v2 Announce Type: replace-cross Abstract: This paper investigates secure communications in rate-splitting multiple access (RSMA) enabled heterogeneous UAV networks, where multiple UAVs collaboratively serve ground terminals in the presence of eavesdroppers. By jointly considering secrecy rate maximization and propulsion energy consumption minimization, we formulate a multi-objective optimization problem involving UAV trajectory design, service association, power allocation, and secrecy precoding under mobility, collision-avoidance, service-capacity, and communication constraint
The increasing sophistication and integration of AI, particularly LLMs, with wireless communication and UAV technologies is rapidly progressing, making secure and efficient UAV networks a current focus of research and development.
This research addresses critical challenges in secure communications for UAV networks, a foundational element for future autonomous systems and defence applications, by integrating advanced AI for optimization.
The explicit incorporation of LLM-aided design for secure precoding and trajectory in heterogeneous UAV networks represents an advancement in optimizing complex multi-objective communication and mobility problems.
- · Defence contractors
- · Telecommunication companies
- · AI/ML research institutions
- · UAV manufacturers
- · Legacy secure communication providers
- · Organizations relying on easily intercepted wireless communications
More robust, secure, and energy-efficient UAV operations for various applications including surveillance and logistics.
Accelerated development of autonomous drone swarms for defence and commercial purposes, increasing strategic capabilities.
Enhanced AI-driven electronic warfare capabilities and counter-measures, leading to an arms race in aerial autonomy and secure communications.
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Read at arXiv cs.AI