Step-GRAND: A Low Latency Universal Soft-input Decoder

TL;DR

Step-GRAND is a novel soft-input decoding algorithm that significantly reduces worst-case latency and improves hardware efficiency for decoding polar codes, enabling high-throughput, low-latency communication systems.

Contribution

It introduces step-GRAND, a soft-input variant of GRAND that enhances worst-case latency and hardware efficiency compared to previous soft-input decoders.

Findings

Decodes CA-polar code (128,105+11) at 47.7 Gbps throughput

Achieves 10x area efficiency over previous ORBGRAND hardware

Reduces worst-case latency to 1/6.8 of prior ORBGRAND hardware

Abstract

GRAND features both soft-input and hard-input variants that are well suited to efficient hardware implementations that can be characterized with achievable average and worst-case decoding latency. This paper introduces step-GRAND, a soft-input variant of GRAND that, in addition to achieving appealing average decoding latency, also reduces the worst-case decoding latency of the corresponding hardware implementation. The hardware implementation results demonstrate that the proposed step-GRAND can decode CA-polar code $(128,105+11)$ with an average information throughput of $47.7$ Gbps at the target FER of $\leq10^{-7}$. Furthermore, the proposed step-GRAND hardware is $10\times$ more area efficient than the previous soft-input ORBGRAND hardware implementation, and its worst-case latency is $\frac{1}{6.8}\times$ that of the previous ORBGRAND hardware.