上行无蜂窝通感一体化系统的导频设计与优化
Pilot design and optimization in uplink cell-free integrated sensing and communication systems
- 电信科学 2026年42卷第1期 页码：43-52
- 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：
[ "田卓岩（2001- ），女，东南大学信息科学与工程学院博士生，主要研究方向为通感一体化。" ]
[ "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。" ]
[ "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。" ]
[ "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、超可靠低时延通信和毫米波通信等。" ]
[ "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和大规模分布式MIMO系统（无蜂窝大规模MIMO）等。" ]
- 基金信息：江苏省重大科技项目(BG2024002)
DOI：10.11959/j.issn.1000-0801.2026045
中图分类号： TN929.5收稿：2025-08-29，
修回：2025-10-21，
录用：2025-11-06，
纸质出版：2026-01-20
- 稿件说明：
移动端阅览
田卓岩,王洁,李佳珉等.上行无蜂窝通感一体化系统的导频设计与优化[J].电信科学,2026,42(01):43-52.
Tian Zhuoyan,Wang Jie,Li Jiamin,et al.Pilot design and optimization in uplink cell-free integrated sensing and communication systems[J].Telecommunications Science,2026,42(01):43-52.
田卓岩,王洁,李佳珉等.上行无蜂窝通感一体化系统的导频设计与优化[J].电信科学,2026,42(01):43-52. DOI： 10.11959/j.issn.1000-0801.2026045.
Tian Zhuoyan,Wang Jie,Li Jiamin,et al.Pilot design and optimization in uplink cell-free integrated sensing and communication systems[J].Telecommunications Science,2026,42(01):43-52. DOI： 10.11959/j.issn.1000-0801.2026045.
摘要
针对导频在信道估计与目标定位中的双重作用，提出了一种面向上行无蜂窝通感一体化（cell-free integrated sensing and communication，CF-ISAC）系统的导频结构设计与优化方法。首先，设计了一种联合长度与功率分配的导频结构；在此基础上，构建了同时最大化上行通信速率与感知估计速率的多目标优化问题（multi-objective optimization problem，MOOP）；进而，提出一种基于非支配排序遗传算法II（non-dominated sorting genetic algorithm II，NSGA-II）的导频优化算法，以实现通信与感知性能的最优权衡。仿真结果表明，与随机导频和等功率导频方案相比，所提方法能够在相同信噪比条件下降低信道估计误差，并获得分布均衡的通信-感知帕累托前沿（Pareto front），验证了该方法在上行CF-ISAC系统中的有效性与实用性。
Abstract
In response to the dual role of pilot signals in channel estimation and target localization
a pilot structure design and optimization method was proposed for the uplink cell-free integrated sensing and communication (CF-ISAC) system. Firstly
a pilot structure jointly considering length and power allocation was designed. On this basis
a multi-objective optimization problem (MOOP) was formulated to simultaneously maximize the uplink communication rate and the sensing estimation rate. Subsequently
a pilot optimization algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) was proposed to achieve the optimal trade-off between communication and sensing performance. Simulation results show that
compared with random pilot and equal-power pilot schemes
the proposed method is able to reduce channel estimation error under the same signal-to-noise ratio conditions and achieve a well-distributed communication-sensing Pareto front
which verifies the effectiveness and practicality of the method in uplink CF-ISAC systems.
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references
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