Muriel Médard - Universal decoding and the grand irrelevance of code construction
Much of the recent debate on the adoption of 5G wireless technology has centred on the issue of standards. To maintain data integrity in the face of network unreliability, systems rely on error-correcting codes. System standardization is predicated on co-designing these error-correcting codes and, most importantly, their generally complex decoders, into efficient, dedicated and customized chips.
In this talk, we describe “Guessing Random Additive Noise Decoding,” or GRAND, by Duffy, Médard and their research groups, which renders universal, optimal, code-agnostic decoding possible for low to moderate redundancy settings. Moreover, recent work with Yazicigil and her group has demonstrated that such decoding can be implemented with extremely low latency in silicon. GRAND enables a new exploration of codes, in and of themselves, independently of tailored decoders, over a rich family of code designs, including random ones.
Surprisingly, even the simplest code constructions, such as those used merely for error checking, match or outperform state of the art codes when optimally decoded with GRAND. Without the need for highly tailored codes and bespoke decoders, we can envisage using GRAND to avoid the issue of fixing code choices that 5G encountered, and instead have an open platform for coding and decoding.