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6G环境认知通信与感知课题组-曾勇

Intro block 移动通信全国重点实验室

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信道知识地图

研究简介

什么是信道知识地图?

(1)以移动节点物理或虚拟位置为主要索引的数据库

(2)直接反映特定位置的本地化信道特征,与收发机活动无关,可融合区域内所有终端的海量历史数据

(3)直接基于位置提前获取信道先验信息

(4)提升当地无线环境的认知能力,实现信道知识的快速实时预测推理

(5)避免重复的在线环境感知及信道获取

(6)由环境未知通信与感知迈向环境认知通信与感知的使能技术

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研究方向

1. 信道知识地图应用

信道知识地图在环境认知通信与感知拥有广泛的应用前景,其典型应用场景包括:

(1)未到达位置的信道:主动切换、网联无人机或网联机器人路径规划

(2)非合作节点间的信道:认知无线电:次发射机到主接收机; 物理层安全:发射机到窃听者

(3)大维信道:大规模MIMO、超大规模MIMO (XL-MIMO)

(4)硬件/信号处理受限的信道:混合波束赋形、低分辨率模数转换器、可重构智能表面(RIS)

2. 信道知识地图构建

为了实现基于信道知识地图的的通信与感知,首先需要以一种有效的方式构建信道知识地图。信道知识地图构建的本质是基于在少数位置获得的数据来重构出环境中所有感兴趣位置的信道信息,其主要方法可分为数据驱动和模型驱动两类。其中,数据驱动构建方法包括克里金法、张量补全、深度学习等;模型驱动构建方法包括空间损失场模型、虚拟障碍物模型等。

 

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研究成果

期刊

Y.  Zeng  and  X.  Xu, “Toward  environment-aware  6G  communicationsvia  channel  knowledge  map,”IEEE Wireless Commun.,  vol.  28,  no.  3,pp. 84–91, Jun. 2021. (首次提出了信道知识地图概念)

Y.  Zeng,  J.  Chen,  J.  Xu,  D.  Wu,  X.  Xu,  S.  Jin,  X.  Gao,  D.  Gesbert, S. Cui, and R. Zhang,“A tutorial on environment-aware communicationsvia channel knowledge map for 6G,”IEEE Commun. Surv. Tutor., Feb. 2024. (首篇信道知识地图综述论文)

D. Wu, Y. Zeng, S. Jin, and R. Zhang, “Environment-aware hybrid beamforming by leveraging channel knowledge map,” IEEE Trans. Wireless Commun., 2023.

Y. Zeng, X. Xu, S. Jin, and R. Zhang, “Simultaneous navigation and radio mapping for cellular-connected UAV with deep reinforcement learning,” IEEE Trans. Wireless Commun., vo. 20, no. 7, pp. 4205-4220, Jul. 2021.

H. Li, P. Li, G. Cheng, J. Xu, J. Chen, and Y. Zeng, “Channel knowledge map (CKM)-assisted multi-UAV wireless network: CKM construction and UAV placement,” Journal of Commun. and Inf. Netw., vol. 8, no. 3, pp. 256-270, Sep. 2023.

会议

D. Wu, Y. Zeng, S. Jin, and R. Zhang, “Environment-aware and training-free beam alignment for mmWave massive MIMO via channel knowledgemap,”in Proc. IEEE Int. Conf. Commun. Workshops (ICC Workshops), Jun. 2021, pp. 1–7.

D. Ding, D. Wu, Y. Zeng, S. Jin, and R. Zhang, “Environment-aware beam selection for IRS-aided communication via channel knowledge map,” IEEE GLOBECOM 2021.

K. Li, P. Li, Y. Zeng, and J. Xu, “Channel knowledge map forenvironment-aware communications: EM algorithm for map construc-tion,” in 2022 IEEE Wireless Communications and Networking Confer-ence (WCNC), 2022, pp. 1659–1664.

H Li, P Li, J Xu, J Chen and Y Zeng, “Derivative-free placement optimization for multi-UAV wireless networks with channel knowledge map”, in Proc. IEEE Int. Conf. Commun. Workshops (ICC Workshops), May. 2022, pp. 1029–1034.

Y. Long, Y. Zeng, X. Xu, and Y. Huang,“Environment-Aware Wireless Localization Enabled by Channel Knowledge Map,” IEEE Globecom 2022.

S. Zeng, X. Xu, Y. Zeng, and F. Liu, “CKM-assisted LoS identificationand  predictive  beamforming  for  cellular-connected  UAV,”  inProc.IEEE ICC, 2023.

D. Wu and Y. Zeng, “Environment-Aware Coordinated Multi-Point mmWave Beam Alignment via Channel Knowledge Map,” IEEE ICC 2023.

W. Xie, X. Xu, Z. Dai, and Y. Zeng, "On the Construction of Channel Gain Map: Model-Based or Model-Free Approach?", IEEE VTC20224-Spring Workshop, Singapore

预印本

X. Xu and Y. Zeng, “How much data is needed for channel knowledgemap construction?”IEEE Trans. Wireless Commun., Major Revision, [Online] Available: http://arxiv.org/abs/2312.06966.

 

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Demo展示

信道知识地图辅助高效波束对齐原型系统

视频链接:https://www.bilibili.com/video/BV1A8411o7Hv/?spm_id_from=333.999.0.0

 

 

 

Created: Dec 18, 2023 | 17:28