Precoding design for integrated sensing and communication in cell-free massive MIMO based on multiple reflection points

TANG Pule; ZHANG Qi; ZHANG Jun; CAI Shu

doi:10.11959/j.issn.2096-3750.WLW26033

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Precoding design for integrated sensing and communication in cell-free massive MIMO based on multiple reflection points

更新时间：2026-06-30

- Precoding design for integrated sensing and communication in cell-free massive MIMO based on multiple reflection points
- Chinese Journal on Internet of Things (2026)
- 作者机构：
  
  南京邮电大学通信与信息工程学院，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62171231;62571267);the Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry)(BE2023022-3)
- DOI：10.11959/j.issn.2096-3750.WLW26033
  CLC： TN929.5
- Received：16 March 2026，
  
  Revised：2026-05-26，
  
  Accepted：30 June 2026，
- 稿件说明：
移动端阅览
TANG Pule, ZHANG Qi, ZHANG Jun, et al. Precoding design for integrated sensing and communication in cell-free massive MIMO based on multiple reflection points[J/OL]. Chinese Journal on Internet of Things, 2026.
DOI：

TANG Pule, ZHANG Qi, ZHANG Jun, et al. Precoding design for integrated sensing and communication in cell-free massive MIMO based on multiple reflection points[J/OL]. Chinese Journal on Internet of Things, 2026. DOI： 10.11959/j.issn.2096-3750.WLW26033.

摘要

通信感知一体化（以下简称通感一体化）通过共享频谱和软硬件等资源，在目标定位、环境感知等方面展现出广泛的应用前景。无蜂窝大规模多输入多输出（CF-mMIMO

Cell-Free Massive Multiple-Input Multiple-Output）能够消除小区间干扰并提升频谱效率。二者结合构建的CF-mMIMO通感一体化系统，有望同时实现高速率通信与高精度感知。现有研究中大多将感知目标建模为单反射点模型，而在分布式接入点（AP

Access Point）密集部署的CF-mMIMO系统中，AP与目标的距离较近，单反射点模型获取的感知信息有限，难以刻画目标的空间分布特性。为此，本文构建了多反射点目标模型，用于提升感知信息的获取量，还可增大通信和速率，并围绕系统预编码设计展开研究。为在感知约束下最大化系统和速率，提出了一种两阶段求解框架：先采用加权最小均方误差方法将非凸问题等效转化，再通过半正定松弛算法得到预编码的闭式解，最后借助交替优化算法求解最优预编码。仿真结果表明，在满足感知约束的条件下，增加反射点数量可将系统通信和速率提升约30%；且随着用户或AP数量的增加，多反射点模型提升通信性能的效果更加明显，这与未来通信场景下大规模用户和超密集CF-mMIMO的趋势高度契合，进一步凸显多反射点建模的研究意义。

Abstract

Integrated sensing and communication (ISAC) achieves promising applications in target localization and environment sensing by sharing spectrum

hardware and software resources. Cell-free massive multiple-input multiple-output (CF-mMIMO) can suppress inter-cell interference and improve spectral efficiency. The CF-mMIMO ISAC system is expected to support both high-rate communication and high-precision sensing. Most existing studies model sensing targets as a single reflection point ones in CF-mMIMO ISAC systems. Massive distributed access point (AP) deployed in such systems shorten the distance between AP and targets

resulting in limited sensing information and failure to characterize target spatial distribution. This paper proposes a multiple reflection points target model to enrich sensing information and improve sum-rate

and focuses on precoding design.. For maximizing the system sum rate under sensing performance constraints

a two-stage framework is proposed: transform the non-convex problem via weighted minimum mean square error

derive a closed-form precoding solution using semi-definite relaxation

and solve optimal precoding via alternating optimization. Simulation results demonstrate that under sensing constraints

more reflection points boost the system sum-rate by around 30%. Moreover

the multiple reflection points model achieves greater communication gains with more users or AP

which aligns with future communication scenarios trends of massive users and ultra-dense CF-mMIMO

further underscoring its research significance.

关键词

Keywords

references

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