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arXiv 2512.02464eess.SP
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通道知识图谱赋能的低空ISAC网络:联合空域走廊规划与基站部署

Channel Knowledge Map Enabled Low-Altitude ISAC Networks: Joint Air Corridor Planning and Base Station Deployment

Jiaxuan Li, Yilong Chen, Fan Liu, Jie Xu

AI总结:

本文提出利用通道知识图谱进行低空ISAC网络的联合空域走廊规划与基站部署,通过分层网格分解算法降低部署成本并确保覆盖。

摘要:

本文针对低空一体化感知与通信(ISAC)网络的联合空域走廊规划和基站(BS)部署问题进行了研究。在所考虑的系统中,无人机(UAV)在由连接的立方体段组成的结构化空域走廊内运行,多个BS需要在一组候选位置上选择性部署,以确保整个走廊的感知和通信覆盖。特别是,我们利用通道知识图谱(CKM)在部署前表征候选BS站点的无线信道,从而促进离线规划。在此设置下,我们最小化系统成本,即在满足走廊内感知和通信性能约束的情况下,加权和的空域走廊长度与部署的BS数量。为了解决所提出的大规模非凸整数规划问题,我们开发了一种分层粗到细的网格分解算法。仿真结果展示了所提联合设计在降低总体部署成本的同时确保低空ISAC网络覆盖方面的优势。

英文摘要:

This letter addresses the joint air corridor planning and base station (BS) deployment problem for low-altitude integrated sensing and communication (ISAC) networks. In the considered system, unmanned aerial vehicles (UAVs) operate within a structured air corridor composed of connected cubic segments, and multiple BSs need to be selectively deployed at a set of candidate locations to ensure both sensing and communication coverage throughout the corridor. In particular, we leverage the channel knowledge map (CKM) to characterize wireless channels for candidate BS sites prior to deployment, thereby facilitating the offline planning. Under this setup, we minimize the system cost in terms of the weighted sum of the air corridor length and the number of deployed BSs, subject to the constraints on both sensing and communication performance across the corridor. To solve the formulated large-scale nonconvex integer programming problem, we develop a hierarchical coarse-to-fine grid decomposition algorithm. Simulation results demonstrate the benefit of the proposed joint design in reducing the overall deployment cost while ensuring the coverage of the low-altitude ISAC networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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