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Semidefinite Relaxations for MIMO Detection: Tightness, Tighterness, and Beyond

Abstract

Multiple-input multi-output (MIMO) detection is a fundamental problem in modern digital communications. Semidefinite relaxation (SDR) based algorithms are a popular class of approaches to solving the problem because the algorithms have a polynomial-time worst-case complexity and generally can achieve a good detection error rate performance. In this talk, we shall present some recent results on SDRs for the MIMO detection problem.

 

About the speaker

刘亚锋,2012年在中国科学院数学与系统科学研究院获得博士学位,师从戴彧虹研究员,现任中国科学院数学与系统科学研究院计算数学所副研究员。他的主要研究兴趣是最优化理论与算法及其在信号处理和无线通信等领域中的应用。曾获2011年国际通信大会“最佳论文奖”,2018年中国运筹学会“青年科技奖”,2020年IEEE通信学会亚太地区杰出青年学者奖,2020年自然科学基金优青项目资助。