报告题目：TOSE: A Fast Capacity Estimation Algorithm Based on Spike Approximations

报告人：姜丹丹 教授西安交通大学

报告时间：2023年4月28日上午10:30—12:00

报告地点：南校区网安大楼会议中心104会议室

报告人简介：姜丹丹现任西安交通大学best365亚洲版登录教授、博士生导师，陕西省基础科学（数学、物理学）研究院副院长，国家级青年人才计划入选者、陕西省高层次人才引进计划青年项目入选者，主要从事随机矩阵、高维统计分析等理论研究及其在通信领域中的应用研究。研究成果发表在Annals of Statistics、Biometrika、Bernoulli、Statistica Sinica等统计学权威期刊。著有《大维统计分析》、《大维随机矩阵谱理论在多元统计分析中的应用》2本学术专著。主持国家重点研发计划课题1项，国家自然科学基金面上项目2项、青年项目1项，省部级科研项目6项，横向项目2项。作为第一获奖人曾获吉林省自然科学学术成果奖特别奖、全国百篇优博论文提名奖、吉林省优秀博士学位论文奖。

报告摘要：To support the growing demand for wireless traffic, wireless networks are becoming more dense and complicated, leading to a higher difficulty to derive the capacity. In this paper, we propose a fast algorithm TOSE to estimate the capacity for ultra-dense wireless networks. Our algorithm can avoid the exact eigenvalue derivations of large dimensional matrices, which are complicated and inevitable in conventional capacity calculation methods. Instead, fast eigenvalue estimations can be realized based on the spike approximations in our TOSE algorithm. Our simulation results show that TOSE is an accurate and fast capacity approximation algorithm. In addition, TOSE has superior generality, since it is independent of the distributions of BSs and users, and the shape of network areas.

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