报告题目：A Construction of Maximum Distance Profile Convolutional Codes With Small Alphabet Sizes

报告人：罗高骏  南京航空航天大学

报告时间：2024年4月21日（星期日）16:00

报告地点：文理楼290

报告人简介：罗高骏，南京航空航天大学，副研究员。2019年博士毕业于南京航空航天大学，导师曹喜望教授。2021年至2024年于新加坡南洋理工大学从事博士后研究工作，合作导师Ling San教授。主要研究方向为代数编码理论、序列设计与量子信息。近五年，以第一/通讯作者发表SCI检索论文20余篇，包括IEEE Trans系列10篇。曾获得江苏省科学技术奖。2022年至今，担任期刊COAM（《Computational and Applied Mathematics》）的 Associate Editor。曾应邀访问土耳其Sabanci大学，韩国庆北国立大学。

报告摘要：Convolutional codes are essential in a wide range of practical applications due to their efficient non-algebraic decoding algorithms. In this paper, we first propose a new family of matrices over finite fields by combining Vandermonde and Moore matrices. Using favourable properties of the matrices in this new family enables us to construct a new family of convolutional codes with memory 1 and maximum distance profile. It is notable that the alphabet sizes of this new family of convolutional codes with maximum distance profile can be kept significantly smaller than those in the literature. Keeping the code rate to a constant, the alphabet size is roughly the square root of the previously best-known value.

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