Automorphism Ensemble Polar Code Decoders for 6G URLLC

TL;DR

This paper introduces an advanced Automorphism Ensemble Decoding architecture for polar codes, achieving significant improvements in latency, area, and energy efficiency over traditional SCL decoders for 6G URLLC applications.

Contribution

It presents a novel AED architecture with an improved path metric for candidate selection, outperforming state-of-the-art SCL decoders in silicon technology.

Findings

Up to 4.4x latency reduction

Up to 8.9x area efficiency improvement

Up to 4.6x energy efficiency gain

Abstract

The URLLC scenario in the upcoming 6G standard requires low latency and ultra reliable transmission, i.e., error correction towards ML performance. Achieving near-ML performance is very challenging especially for short block lengths. Polar codes are a promising candidate and already part of the 5G standard. The Successive Cancellation List (SCL) decoding algorithm provides very good error correction performance but at the cost of high computational decoding complexity resulting in large latency and low area and energy efficiency. Recently, Automorphism Ensemble Decoding (AED) gained a lot of attention to improve the error correction capability. In contrast to SCL, AED performs several low-complexity (e.g., SC) decoding in parallel. However, it is an open question whether AED can compete with sophisticated SCL decoders, especially from an implementation perspective in state of the art silicon technologies. In this paper we present an elaborated AED architecture that uses an advanced path metric based candidate selection to reduce the implementation complexity and compare it to state of the art SCL decoders in a 12nm FinFET technology. Our AED implementation outperform state of the art SCL decoders by up to 4.4x in latency, 8.9x in area efficiency and 4.6x in energy efficiency, while providing the same or even better error correction performance.