无蜂窝通感一体化中多级融合定位机制研究
Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems
- 电信科学 2026年42卷第1期 页码：22-34
- 作者机构：
1.东南大学移动通信全国重点实验室，江苏 南京 210096
2.东南大学信息科学与工程学院，江苏 南京 210096
- 作者简介：
[ "裴荣康（2002- ），男，东南大学信息科学与工程学院硕士生，主要研究方向为通感一体化、多站协同感知。" ]
[ "王洁（1998- ），女，东南大学信息科学与工程学院博士生，主要研究方向为无蜂窝大规模MIMO、通感一体化等。" ]
[ "李佳珉（1983−），男，东南大学信息科学与工程学院教授，主要研究方向为6G无蜂窝智能无线接入网、海量终端高可靠低时延通信、多站协同通感一体化、6G极致连接（空时互换理论、空时二维编码）、未来移动通信综合试验平台。" ]
[ "王东明（1977−），男，东南大学信息科学与工程学院教授，主要研究方向为无线通信信号处理、大规模分布式MIMO 系统（无蜂窝大规模MIMO）等。" ]
[ "朱鹏程（1978−），男，东南大学信息科学与工程学院教授，主要研究方向为无线通信和移动网络，涵盖5G/6G移动通信系统、大规模MIMO、超可靠低时延通信（URLLC）和毫米波通信等。" ]
- 基金信息：江苏省重大科技项目(BG2024002)
DOI：10.11959/j.issn.1000-0801.2026044
中图分类号： TP393收稿：2025-08-29，
修回：2025-10-11，
录用：2025-11-06，
纸质出版：2026-01-20
- 稿件说明：
移动端阅览
裴荣康,王洁,李佳珉等.无蜂窝通感一体化中多级融合定位机制研究[J].电信科学,2026,42(01):22-34.
Pei Rongkang,Wang Jie,Li Jiamin,et al.Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems[J].Telecommunications Science,2026,42(01):22-34.
裴荣康,王洁,李佳珉等.无蜂窝通感一体化中多级融合定位机制研究[J].电信科学,2026,42(01):22-34. DOI： 10.11959/j.issn.1000-0801.2026044.
Pei Rongkang,Wang Jie,Li Jiamin,et al.Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems[J].Telecommunications Science,2026,42(01):22-34. DOI： 10.11959/j.issn.1000-0801.2026044.
摘要
随着6G移动通信技术的发展，通信与感知一体化（integrated sensing and communication，ISAC）成为未来无线网络的重要方向。在大规模分布式场景中，高精度定位仍面临计算和通信开销过大、参数不可靠等挑战。为此，提出一种多级融合的ISAC定位架构：在接入点（access point，AP）级对感知信号进行预处理，并将结果上传至边缘分布式单元（edge distributed unit，EDU）；EDU级利用神经网络将信噪比映射为时延参数的权重，并结合几何精度因子（geometric dilution of precision，GDOP）策略进行加权最小二乘局部定位；中央处理单元（central processing unit，CPU）级则在全局视角下对EDU上传的可靠参数进行二次动态筛选与最终定位。仿真结果表明，该架构能显著降低整体区域内的定位误差，通信和计算开销均优于集中式方案，具有良好的系统可扩展性。
Abstract
With the development of sixth-generation mobile communication systems
integrated sensing and communication (ISAC) is recognized as an important direction for future wireless networks. In large-scale distributed scenarios
high-precision positioning still faces challenges such as excessive computational and communication overhead and unreliable parameters. To address these issues
a multi-level fusion ISAC positioning architecture was proposed: at the access point (AP) level
sensing signals were preprocessed
and the results were uploaded to the edge distributed unit (EDU); at the EDU level
the signal-to-noise ratio was mapped to the weights of delay parameters via a neural network
and weighted least squares local positioning was performed in combination with a geometric dilution of precision (GDOP) strategy; at the central processing unit (CPU) level
the reliable parameters uploaded by the EDU were subjected to secondary dynamic screening and final positioning from a global perspective. Simulation results demonstrate that the proposed architecture significantly reduces positioning errors across the entire area. Moreover
it outperforms the centralized scheme in both communication and computational overhead
ensuring good system scalability.
关键词
Keywords
references
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