Organizers 组织者

Invited Speakers 特邀报告嘉宾

Abstract / 摘要

With the rapid development of the low-altitude economy, unmanned systems, and sixth-generation mobile communication technologies, unmanned aerial vehicles, low-altitude aerial platforms, ground terminals, and edge nodes are increasingly forming integrated air-ground intelligent networks. Owing to high node mobility, dynamically varying network topologies, spatiotemporally heterogeneous task demands, and unevenly distributed communication, sensing, and computing resources, low-altitude intelligent networks face significant challenges in real-time environmental perception, reliable information transmission, efficient task processing, and autonomous collaborative decision-making. Integrated sensing, communication, and computing enables deep coordination among sensing, communication, and computing functions, thereby providing unified capabilities for information acquisition, transmission, and processing. Edge intelligent computing further leverages artificial intelligence, edge computing, distributed learning, and intelligent optimization to support real-time analysis, intelligent inference, and autonomous decision-making in dynamic network environments. This special session focuses on integrated sensing, communication, and computing architectures, cooperative sensing, edge intelligence, task offloading, resource optimization, distributed learning, multi-agent decision-making, and representative applications in low-altitude intelligent networks, with the aim of advancing the underlying theories, enabling technologies, and implementation methods for the deep integration of low-altitude networking and intelligent computing.

随着低空经济、无人系统及第六代移动通信技术的快速发展，无人机、低空飞行器、地面终端和边缘节点正逐步构成空地融合的低空智能网络。由于节点高速移动、网络拓扑动态变化、任务需求时空异构以及通信、感知和计算资源分布不均，低空智能网络在实时环境感知、可靠信息传输、高效任务处理和自主协同决策等方面面临诸多挑战。通感算融合通过推动通信、感知与计算功能的深度协同，为低空网络提供一体化的信息获取、传输与处理能力；边缘智能计算则借助人工智能、边缘计算、分布式学习和智能优化等技术，实现面向动态网络环境的实时分析、智能推理与自主决策。本专题重点关注低空智能网络中的通感算一体化架构、协同感知、边缘智能、任务卸载、资源优化、分布式学习、多智能体决策及典型应用，旨在探讨相关基础理论、关键技术与实现方法，推动低空智能网络与智能计算技术的深度融合。

Topics 主题征稿范围

The following topics are within the scope of this special session, but are not limited to: 以下为本分论坛征稿范围，但不限于：

• Architectures and Enabling Technologies for Low-Altitude Intelligent Networks
  低空智能网络体系架构与关键技术
• Theories and Methods of Integrated Sensing, Communication, and Computing for Low-Altitude Networks
  低空网络中的通感算一体化理论与方法
• Edge Intelligent Computing Architectures for Low-Altitude Networks
  面向低空网络的边缘智能计算架构
• UAV-Assisted Communications, Sensing, and Edge Computing
  无人机辅助通信、感知与边缘计算
• Multi-UAV Cooperative Sensing and Multi-Source Information Fusion
  多无人机协同感知与多源信息融合
• Intelligent Task Offloading and Resource Allocation for Low-Altitude Networks
  低空网络中的智能任务卸载与资源分配
• Collaborative Optimization of Communication, Sensing, Computing, and Control Resources
  通信、感知、计算与控制资源协同优化
• Task Allocation and Collaborative Decision-Making for UAV Swarms
  无人机集群任务分配与协同决策
• Multi-Agent Reinforcement Learning and Distributed Intelligence for Low-Altitude Networks
  低空网络中的多智能体强化学习与分布式智能
• Federated Learning, Distributed Learning, and Edge Learning
  联邦学习、分布式学习与边缘学习
• Graph Neural Networks and Spatiotemporal Intelligent Computing
  图神经网络与时空智能计算
• Low-Altitude Target Detection, Tracking, and Environmental Perception
  低空目标检测、跟踪与环境感知
• UAV Trajectory Planning, Deployment Optimization, and Mobility Management
  无人机轨迹规划、部署优化与移动性管理
• UAV Swarm Networking and Dynamic Topology Optimization
  无人机集群组网与动态拓扑优化
• Security, Privacy Preservation, and Trustworthy Intelligence for Low-Altitude Networks
  低空网络安全、隐私保护与可信智能
• Energy-Constrained and Energy-Harvesting-Enabled Low-Altitude Intelligent Networks
  能量受限与能量收集驱动的低空智能网络
• Large Models and Generative Artificial Intelligence for Low-Altitude Intelligent Networks
  低空智能网络中的大模型与生成式人工智能