Aug 2026· 2026 IEEE/CIC International Conference on Communications in China (ICCC)· pp. 1034-1039· 0 citations· 18 references
Abstract
Vision-language models (VLMs) have achieved remarkable success, yet their substantial resource demands far exceed the capabilities of typical IoT devices. This paper investigates collaborative VLM inference across IoT devices, mobile UAV relays, and a ground base station to bring intelligence to the edge. The collaborative inference problem can be formulated as a constrained optimization that minimizes a weighted sum of delay, energy, and inference distortion over time. However, a direct solution is challenging due to rapidly changing wireless channels, coupled with per-slot resource constraints across multiple tasks, and the presence of discrete decision variables. Our core idea is to decouple the problem: we propose DOpt, a framework in which slow UAV mobility is learned via multi-agent reinforcement learning and fast per-slot compression allocation is solved via convex optimization. Extensive simulations demonstrate that DOpt improves the weighted objective by up to 23.1% over all baselines, with ablation studies confirming the necessity of both adaptive compression and learned mobility.
Unmanned Aerial Vehicles (UAVs) are envisioned as key enablers for time-sensitive data collection in 6G cognitive networks. Semantic communication offers a promising solution to overcome bandwidth scarcity by transmitting only essential information. However, the heavy computational burden of semantic extraction is ofte...
Zhi-Long Kou, Xiang-Dong Jia, Jun Lan et al.· IEEE Wireless Communications...· 0 citations
In the sixth-generation (6G) era, wireless networks need to support a large number of ultra-low latency and high-reliability applications. However, conventional bit-level communication paradigms fail to capture the intrinsic meaning of multi-modal data, leading to inefficiencies in both communication and computation fo...
Fang-Fang Yin, Yue-Xin Liu, Wanli Ni et al.· IEEE Transactions on Communi...· 0 citations
sys is presented, a content-aware hierarchical scheduler that screens constellation-wide options to retain a bounded candidate set, then refines each candidate into a complete token compression and layer offloading trajectory using quality prediction and joint planning and balances per-task latency, energy, and quality...
Yan Chen, Yun-Xiang Zhang, Guan-Jun Jiang et al.· 0 citations
UAVs have emerged as highly flexible platforms for data sensing in Wireless Sensor Networks (WSNs). Path planning for UAVs in such tasks plays a key role to assure remote sensing effectiveness and friendly energy consumption. However, existing approaches show two key limitations: i) they are primarily hand-crafted with...
Si-Jie Ma, Ze-Yuan Ma, Wei-Jia Cao et al.· 1 citation
