
NEWS
2024年9月24日,中国移动在北京隆重举办主题为“协同众创 智启未来”的“未来启航·6G创新发展论坛”,围绕 6G 未来发展方向,分享前沿技术观点、研判机遇挑战、发布创新成果。中国工程院院士张平、中国工程院外籍院士王江舟、中国通信标准化协会理事长闻库等众多6G领域产学研专家出席了本次“未来启航6G创新发展论坛”,共同研讨6G领域重点技术、典型场景和重大工程等方向的发展现状与演进趋势。
此次论坛向产学研各界广泛征集6G领域网络架构、关键技术、平台装置等方面成果进展,并遴选出十项“2024年度未来产业6G领域重大成果”进行表彰。其中由北京邮电大学和中国移动研究院联合研发的“6G空口AI信道数据集及仿真器” 入选2024年度未来产业6G领域重大成果,并进一步发布了6G空口AI信道数据集及仿真器的升级版(BUPTCMCC-6G-DataAI+,BUPTCMCC-6G-CMG+)。

信道测量与建模研究是每代移动通信系统的基础性研究。信道仿真器是在实验室环境下, 根据场景配置需求, 实现多种场景信道数据生成的计算平台。信道仿真器支撑了通信算法设计优化和网络系统性能评估。随着6G演进 ,ITU在原有5G场景的基础上新增了三大应用场景,即AI通信融合、通感融合、泛在连接。AI通信融合已成为6G典型应用场景,尤其对于物理层AI技术研究,将AI技术融入到空口各个模块,亟需丰富多样信道数据的支撑。
北京邮电大学联合中国移动研究院提出了面向6G的统一信道建模基础理论“扩展的GBSM模型”(Extended GBSM, E-GBSM)。E-GBSM在统一的模型框架下精确刻画出近远场和空间非平稳、信道稀疏、信道级联和共享等6G信道新特性,具有统计模型低复杂度、可泛化的优势,并后向兼容5G标准模型。基于该理论,在2023年6月4号发布了面向6G AI通信融合需求的信道数据集“BUPTCMCC-6G-DataAI”以及全球首个面向6G的信道仿真器“BUPTCMCC-6G-CMG”;2024年3月19日,BUPTCMCC-DataAI-6G上线中国移动创新平台,供产业界和学术界共享使用;截至目前数据集及仿真器已被全球超50所企业及科研单位下载,使用总数超2300次。近期随着3GPP 6G ISAC和7-24 GHz信道模型标准化最新进展和用户需求的反馈,团队进一步开发和升级了信道数据集(BUPTCMCC-6G-DataAI+)和仿真器(BUPTCMCC-6G-CMG+)。
本次升级和发布的BUPTCMCC-6G-DataAI+首次采用生成式的数据构建方法,产生信道数据量高达3亿组,进一步增加了超高速移动、多视角感知、工业互联网、室内RIS等新场景,以及7-24 GHz新中频,支持CSI压缩反馈、遮挡和波束预测、感知定位、空口资源管理、网络规划优化等空口AI算法需求。升级后的BUPTCMCC-6G-DataAI+为多样化任务需求提供多场景数据,从信道数据支撑6G AI通信融合研究。

本次升级和发布的BUPTCMCC-6G-CMG+是业界首个具备3GPP ISAC标准化信道仿真能力的仿真器,根据3GPP R19 RAN1 118bis次会议最新进展,新增ISAC单站、双站两种感知模式下人、车、UAV等三类感知目标的信道仿真能力。平台兼容3GPP标准化的RCS大小尺度建模与极化特性,并集成了团队大量实测RCS数据,从信道仿真软件支撑6G通信算法设计优化和网络系统性能评估。

参考文献:
[1] J. Zhang, J. Lin, P. Tang, Y. Zhang, H. Xu, T. Gao, H. Miao, Z. Chai, Z. Zhou, Y. Li, H. Gong, Y. Liu, Z. Yuan, X. Liu, L. Tian, S. Yang, L. Xia, G. Liu, and P. Zhang, “Channel Measurement, Modeling, and Simulation for 6G: A Survey and Tutorial,” arXiv preprint arXiv: 2305.16616, 2023.
[2] 张建华,王珩,张宇翔,唐盼,于力,许慧鑫,刘亚萌,刘西曼,巩汇文,田磊. 6G 信道新特性与建模研究:挑战、进展与展望. 中国科学:信息科学, vol. 54, no. 5, pp. 1114-1143, 2024.
[3] L. Yu, J. Zhang, M. Fu, and Q. Wang, “BUPTCMCC-6G-DataAI+: A Generative Channel Dataset for 6G AI Air Interface Research,” arXiv preprint arXiv: 2410.10839, 2024.
[4] C. Zhao, Y. Zhang, H. Wang, L. Tian, J. Zhang, and H. Jiang, “BUPTCMCC-6G-CMG+: A GBSM-Based ISAC Channel Model Simulator,” arXiv preprint arXiv: 2409.14441, 2024.
[5] Y. Zhang, J. Zhang, Y. Pei, Y. Liu, and T. Jiang, “Latest Progress For 3GPP ISAC Channel Modeling Standardization,” Sci. China Inf. Sci., vol. 67, no. 11, 2024.
[6] P. Tang, J. Zhang, H. Xu, H. Miao and X. Liu, "Preliminary Perspectives on 3GPP Standardization of the Propagation Channel Model for 6G FR3 Bands," submitted to Sci. China Inf. Sci.
[6] Z. Shen, L. Yu, Y. Zhang, J. Zhang, Z. Zhang, X. Hu, S. Han, J. Jin, and G. Liu, “DataAI-6G: A System Parameters Configurable Channel Dataset for AI-6G Research,” in 2023 IEEE Globecom Workshops, pp. 1910-1915, 2023.
[7] J. Zhang, J. Wang, Y. Zhang, Y. Liu, Z. Chai, G. Liu, and T. Jiang, “Integrated Sensing and Communication Channel: Measurements, Characteristics, and Modeling,” IEEE Commun. Mag., vol. 62, no. 6, pp. 98-104, 2024.
[8] Y. Liu, J. Zhang, Y. Zhang, Z. Yuan, and G. Liu, “A Shared Cluster-Based Stochastic Channel Model for Joint Communication and Sensing Systems,” IEEE Trans. Veh. Technol., pp.1-13, 2023.
[9] Y. Liu, J. Zhang, Y. Zhang, H. Gong, T. Jiang and G. Liu, “How to Extend 3-D GBSM to Integrated Sensing and Communication Channel With Sharing Feature?” IEEE Wireless Commun. Lett., vol. 13, no. 8, pp. 2045-2049, 2024.
[10] J. Wang, J. Zhang, Y. Zhang, T. Jiang, L. Yu, and G. Liu, “Empirical Analysis of Sensing Channel Characteristics and Environment Effects at 28 GHz,” in 2022 IEEE Globecom Workshops, pp. 1323-1328, 2022.
[11] J. Zhang, H. Miao, P. Tang, L. Tian and G. Liu, “New Mid-Band for 6G: Several Considerations from the Channel Propagation Characteristics Perspective,” IEEE Commun. Mag., pp. 1-6, 2024.
[12] H. Miao, J. Zhang, P. Tang L. Tian, X. Zhao, B. Guo, and G. Liu, “Sub-6 GHz to mmWave for 5G-Advanced and Beyond: Channel Measurements, Characteristics and Impact on System Performance,” IEEE J. Sel. Areas Commun., vol. 41, no. 6, pp. 1945-1960, 2023.
[13] Z. Yuan, J. Zhang, Y. Ji, G. F. Pedersen, and W. Fan, “Spatial Non-Stationary Near-Field Channel Modeling and Validation for Massive MIMO Systems,” IEEE Trans. Antenn. Propag., vol. 71, no. 1, pp. 921-933, 2023.
[14] Z. Yuan, J. Zhang, V. Degli-Esposti, Y. Zhang and W. Fan, “Efficient Ray-Tracing Simulation for Near-Field Spatial Non-Stationary mmWave Massive MIMO Channel and Its Experimental Validation,” IEEE Trans. Wireless Commun., vol. 23, no. 8, pp. 8910-8923, 2024.
[15] Z. Yuan, F. Zhang, Y. Zhang, J. Zhang, G. F. Pedersen and W. Fan, “On Phase Mode Selection in the Frequency-Invariant Beamformer for Near-Field mmWave Channel Characterization,” IEEE Trans. Antenn. Propag., vol. 71, no. 11, pp. 8975-8986, 2023.
[16] X. Liu, J. Zhang, P. Tang, L. Tian, H. Tataria, S. Sun, and M. Shafi, “Channel Sparsity Variation and Model-Based Analysis on 6, 26, and 132 GHz Measurements,” IEEE Trans. Veh. Technol., pp.1-10, 2024.
[17] H. Gong, J. Zhang, Y. Zhang, Z. Zhou, and G, Liu, “How to Extend 3D GBSM Model to RIS Cascade Channel with Non-ideal Phase Modulation?” IEEE Wireless Commun. Lett., vol. 13, no. 2, pp. 555-559, 2024.
[18] H. Wang, J. Zhang, G. Nie, L. Yu, Z. Yuan, T. Li, J. Wang, and G. Liu, “Digital Twin Channel for 6G: Concepts, Architectures and Potential Applications,” IEEE Commun. Mag., accepted, arXiv preprint arXiv:2403.12467, 2024.
[19] J. Wang, J. Zhang, Y. Zhang, Y. Sun, G. Nie, L. Shi, P. Zhang, and G. Liu. “Towards 6G Digital Twin Channel Using Radio Environment Knowledge Pool,” IEEE Commun. Mag., accepted, arXiv preprint arXiv:2312.10287, 2023.
关注我们

6G研究苑公众号
北邮-中移研究院
联合创新中心公众号

夜雨聆风