CTN - April 2026 - Channel Coding, 6G and More

The podcast touches on the key elements of coding for 6G, including: The Future of Channel Coding: Why better decoding is the central issue and how 6G can improve through modularity. GRAND (Guessing Random Additive Noise Decoding): An exploration of universal decoding which identifies errors by guessing the noise rather than relying on code structure, and how it allows simple product codes to outperform current 5G standards. Security and Quantum Readiness: Insights into how error-correcting codes are becoming the essential foundation for post-quantum encryption. Hardware and Efficiency: The potential for universal decoders to reduce hardware footprints, increase speed, and improve energy efficiency across 6G systems. The podcast also discusses Professor Médard’s new book, Network Coding for Engineers, and her experiences transitioning algorithms from academic research to startups in the Web3 space. Speakers Prof. Muriel Médard, Electrical Engineering and Computer Science (EECS) Department, Massachusetts Institute of Technology (MIT). Dr. Prakash Chaki, Senior Researcher, NEC Labs, Japan. Podcast Timestamps 00:00 Introduction 01:45 Muriel’s wishlist for 6G 04:32 Where channel coding stands today? 08:13 Good old 1950’s product codes 08:42 Random codes and capacity 12:43 Role of machine learning in coding 13:40 Challenges at short blocklengths 16:32 “Inventing new codes” vs “better decoding” 19:31 Decoding has been causing the choice of codes 20:09 CRC-interleaved polar codes 21:20 Modularization of 5G’s layered architecture can accelerate 6G 24:57 Network coding versus ARQ/HARQ 28:10 Coding as a security tool 31:23 Coding and post-quantum encryption 33:58 Experimenting with AES encryption for error correction 35:35 Reducing hardware footprint by replacing multiple decoders of 5G by a single universal decoder 38:10 Soft-output GRAND 40:11 Coopman’s CRCs are funnily good error-correcting codes 41:30 Why is guessing the noise so powerful? 45:29 Teaching coding theory at MIT using GRAND 47:18 Lessons from building GRAND chips 51:12 The book “Network Coding for Engineers” 54:23 The hardest part about moving algorithms into products 56:15 Quick fire