Topology-Aware Integrated Sensing, Communication, Charging in Massive Low-Altitude Wireless Network

2026-10-01

AI Summary

This study addresses the high computational complexity and poor scalability arising from the multi-objective coupling of sensing, communication, and charging in large-scale low-altitude networks. To this end, we propose a topology-aware collaborative optimization framework that pioneers the abstraction of heterogeneous devices into node-edge relationships within a bipartite graph. Furthermore, a low-complexity topology reconstruction algorithm and a unified resource adjustment strategy are designed to effectively overcome the performance bottlenecks inherent in conventional alternating optimization approaches. Experimental results demonstrate that the proposed method significantly enhances system-wide collaborative efficiency in multi-user scenarios while maintaining robustness and scalability, achieving superior overall performance compared to existing baseline methods.

Abstract

Future low-altitude wireless networks (LAWNs) are expected to simultaneously support sensing, communication, and charging, resulting in tightly coupled multi-objective optimization problems with strong interdependencies among heterogeneous functions. However, existing multi-objective frameworks typically rely on complex problem-specific formulations and alternating optimization procedures, which suffer from high computational complexity and limited scalability in large-scale, highly dynamic deployments. In this paper, we propose a unified topology-aware (TA) framework that abstracts terrestrial and non-terrestrial devices as nodes, and models their interactions as edges, forming a bipartite graph representation of the LAWN. By leveraging this graph representation, we develop a low-complexity topology reconfiguration algorithm based on a unified resource-adjustment rule. Simulation results demonstrate that the proposed TA-based method consistently outperforms state-of-the-art approaches in multi-functional coordination efficiency, while maintaining robustness and scalability in scenarios involving massive terrestrial and airborne user equipments.

Problem

• Low-Altitude Wireless Networks
• Integrated Sensing Communication Charging
• Multi-objective Optimization
• Scalability
• Computational Complexity

Innovation

• Topology-Aware Framework
• Bipartite Graph Representation
• Integrated Sensing Communication Charging
• Low-Altitude Wireless Networks
• Topology Reconfiguration Algorithm