Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems

Pei Rongkang; Wang Jie; Li Jiamin; Wang Dongming; Zhu Pengcheng

doi:10.11959/j.issn.1000-0801.2026044

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Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems

Topic: Integration of Communication, Sensing, and Computing for 6G | 更新时间：2026-03-02

- Research on multi-level fusion localization mechanisms in cell-free integrated sensing and communication systems
- Telecommunications Science Vol. 42, Issue 1, Pages: 22-34(2026)
- 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：
- 基金信息：
  
  Major Science and Technology Project of Jiangsu Province(BG2024002)
- DOI：10.11959/j.issn.1000-0801.2026044
  CLC： TP393
- Received：29 August 2025，
  
  Revised：2025-10-11，
  
  Accepted：06 November 2025，
  
  Published：20 January 2026
- 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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