ORBGRAND Is Exactly Capacity-achieving via Rank Companding

TL;DR

This paper proves that CDF-ORBGRAND, a decoding algorithm using rank companding based on the inverse CDF of channel reliability, exactly achieves the capacity of binary-input symmetric channels and BICM systems.

Contribution

It establishes that CDF-ORBGRAND attains the mutual information and BICM capacity, providing a capacity-achieving decoding method for various channels.

Findings

CDF-ORBGRAND exactly achieves the mutual information of symmetric channels.

It can achieve BICM capacity under mismatched decoding conditions.

The method is suitable for high-order input constellations in BICM systems.

Abstract

Within the family of guessing-based decoding algorithms, ordered reliability bits GRAND (ORBGRAND) has attracted considerable attention due to its efficient use of soft information and suitability for hardware implementation. It has also been shown that ORBGRAND achieves a rate very close to the capacity of an additive white Gaussian noise channel under antipodal signaling. In this work, it is further established that, for general binary-input memoryless channels under symmetric input distribution, via suitably companding the ranks in ORBGRAND according to the inverse cumulative distribution function (CDF) of channel reliability, the resulting CDF-ORBGRAND algorithm exactly achieves the mutual information, i.e., the symmetric capacity. This result is then applied to bit-interleaved coded modulation (BICM) systems to handle high-order input constellations. Via considering the effects of mismatched decoding due to both BICM and ORBGRAND, it is shown that CDF-ORBGRAND is capable of achieving the BICM capacity, which was initially derived in the literature by treating BICM as a set of independent parallel channels.