Symmetry in Syndrome Decoding of Reed-Muller Codes


Andrew Thangaraj


IIT Madras


Tuesday, 2 June 2020, 14:00


  • A-201 (STCS Seminar Room)


Reed--Muller (RM) codes, a classical family of codes known for their elegant algebraic structure, have recently been shown to achieve capacity under maximum-likelihood (ML) decoding on the binary erasure channel and this has rekindled interest in their efficient decoding. We consider the code family RM(m-3,m) and develop a new ML decoder, for transmission over the binary symmetric channel, that exploits their large symmetry group. The new decoder has complexity O(m^3), which is lower than an earlier method introduced by Seroussi and Lempel in 1983.

Bio: Andrew Thangaraj received his B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT), Madras, India in 1998 and a PhD in Electrical Engineering from the Georgia Institute of Technology, Atlanta, USA in 2003. He was a post-doctoral researcher at the GTL-CNRS Telecom lab at Georgia Tech Lorraine, Metz, France from August 2003 to May 2004. From June 2004, he has been with the Department of Electrical Engineering, IIT Madras, where he is currently a professor. From Jan 2012 to Jan 2018, he served as Editor for the IEEE Transactions on Communications.

Since July 2018, he has been serving as an Associate Editor for Coding Techniques for the IEEE Transactions on Information Theory. Since Oct 2011, he has been serving as NPTEL coordinator at IIT Madras. He has played a key role in initiating and running NPTEL online courses and certification. He is currently a National MOOCs Coordinator for NPTEL in the SWAYAM project of the MHRD.