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西安交大-华为数学技术联合实验室
日期:2021-01-22 点击:

实验室定位:基于“以发展数学前沿技术为导向,以解决国家重大需求为目标,创新校企合作共建新模式”的发展理念,围绕未来无线通信发展,聚焦“基于AI和无线通信的融合研究”,形成下一代的无线通信架构体系创新,深化双方在无线通信领域的合作,共同创新发展以数学为主导的新一代信息技术。实验室拟建成一个以数学为主导的信息技术协同创新平台,在无线通讯与人工智能领域的方法与技术研究上实现重要创新,在关键核心技术上取得重大突破,建设引领该领域发展的全球顶尖实验室。

Positioning: Adhering to the development concept of "developing cutting-edge mathematics technologies, addressing major national needs, and committing to innovating university-industry cooperation models", XJTU-Huawei Joint Laboratory of Mathematical Technology focuses on research of the integration of AI and wireless communications, making innovations in the next-generation wireless communication architecture and systems, deepen the cooperation between university and industry in the field of wireless communication, and jointly innovate and develop new-generation information technologies led by mathematics. The laboratory intends to build a mathematics-led collaborative innovation platform for information technologies, achieve important breakthroughs and innovations in methodology and technology of wireless communication and AI, in order to build a world-leading laboratory in this field.

目前主要人员构成如下:

The main members of the Laboratory are listed below:

徐宗本、孙剑、孙建永、孟德宇、杨树森、曾薇、杨在、薛江、李慧斌、刘军民、段启宏、赵谦

Xu Zongben, Sun Jian, Sun Jianyong, Meng Deyu, Yang Shusen, Zeng Wei, Yang Zai, Xue Jiang, Li Huibin, Liu Junmin, Duan Qihong, and Zhao Qian

 

 

代表性成果:研究团队长期从事智能信息处理方面的研究,在智能信息处理的数学基础与图像处理新机制方面成果丰硕。例如,提出并建立了稀疏信息处理的L1/2正则化理论, 形成了“基于L1/2正则化的合成孔径雷达成像新方法”和“不直接基于雷达观测矩阵的稀疏微波成像新原理”。研究成果已被国家安全重大基础研究(国防973)项目采用。

Representative achievements: The research group has been long engaged in the research on intelligent information processing, yielding fruitful results in the mathematical foundation of intelligent information processing and new image processing mechanisms. For example, the L1/2 regularization theory for sparse information processing was proposed and established, thus forming a new method of synthetic aperture radar imaging based on L1/2 regularization and a new principle of sparse microwave imaging. These achievements have been adopted in the projects of the National Basic Major Security Research Program of China (National Defense 973).

提出基于视觉认知的数据建模新原理与新方法, 形成了聚类分析的“视觉聚类器”、模式识别的“视觉分类机”和信息融合的“响尾蛇模式”等数据挖掘核心算法。上述成果获得国家自然科学二等奖1项,国家科技进步二等奖1项,陈嘉庚信息技术科学奖,陕西省基础研究重大贡献奖。

The research group has proposed new principles and methods for data modeling based on visual cognition principle, including the visual clustering algorithm for data clustering, visual classifier for data classification and infrared & visible information fusion based on visual mechanism of rattlesnake. The above achievements won 1 Second Class National Natural Science Award, 1 Second Class National Prize for Progress in Science and Technology, the Tan Kah Kee Science Award in Information Technology, and the Award for Major Contribution to Basic Research of Shaanxi Province.

成立至今,提出多项“智能通信”、“智能运维”、“优化体验”理论与应用技术,并已在华为公司得到验证与应用,例如基于自主搜索深度神经网络(LISA)的MIMO检测人工智能方法;基于元学习机器学习算法的相位噪声盲估计方法;基于深度学习和小样本学习的电信网络运维架构与核心算法;基于网络优化理论的5G网络传输协议与优化方法等。

Since founded, the laboratory has proposed a number of theories and applied technologies for intelligent communication, intelligent operation & maintenance and optimized experience, which have been verified and applied in Huawei, e.g., the AI MIMO detection method based on AI-based iterative search algorithm for MIMO detection (LISA); the blind estimation method for the phase noise based on the meta-learning machine learning algorithm; the telecommunication network operation & maintenance architecture and core algorithms based on deep learning and small-sample learning; the 5G network transmission protocol and optimization methods based on network optimization theory, and others.

研究方向:实验室将结合华为公司的产业发展需求,针对无线通信、人工智能领域内的共性基础与关键技术,开展面向信息产业应用的数学与信息技术的基础理论与方法研究。目前聚焦的研究内容有:

Research direction: The laboratory will carry out research on basic theories and methods of mathematics and information technologies for applications in the information industry based on the common foundations and key technologies in the fields of wireless communications and artificial intelligence, so as to meet Huawei’s needs for industrial development. The major research directions include:

  • 无线通信架构体系创新,推动无线通信物理层智能化的理论及应用研究;

    Innovations in wireless communication architecture system, promoting the theories and applications in the AI-based physical layer of wireless communication.

  • 构建基于元学习(机器学习自动化)的“模型+数据”双驱的算法体系和方法论,突破传统设计方法的性能瓶颈。

    Proposing the model and data driven approach based on meta-learning in order to break the performance bottleneck of traditional methods in communication.

  • 设计机理和数据双驱动的理论、架构、算法及协议,以全面赋能华为GTS智能运维、体验优化和站点集成三大业务模块。

    Designing theories, architectures, algorithms and protocols driven by mechanism and data, so as to fully empower Huawei's three business modules, i.e., GTS intelligent operation & maintenance, user experience optimization and site integration.

 

 



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