GRAND-assisted Optimal Modulation

TL;DR

This paper introduces a GRAND-assisted optimal modulation scheme for Gaussian channels that effectively mitigates insertion and deletion errors, achieving over 2 dB gain in bit-error-rate compared to traditional 128-QAM.

Contribution

It proposes a lightweight GRAND variant with padding to handle insertion/deletion errors in optimal modulation, improving performance over existing coding schemes.

Findings

Over 2 dB Eb/N0 gain in bit-error-rate compared to 128-QAM.

GRAND-assisted modulation outperforms LDPC coding at similar rates.

Effective error correction for nonuniform symbol distributions in Gaussian channels.

Abstract

Optimal modulation (OM) schemes for Gaussian channels with peak and average power constraints are known to require nonuniform probability distributions over signal points, which presents practical challenges. An established way to map uniform binary sources to non-uniform symbol distributions is to assign a different number of bits to different constellation points. Doing so, however, means that erroneous demodulation at the receiver can lead to bit insertions or deletions that result in significant binary error propagation. In this paper, we introduce a light-weight variant of Guessing Random Additive Noise Decoding (GRAND) to resolve insertion and deletion errors at the receiver by using a simple padding scheme. Performance evaluation demonstrates that our approach results in an overall gain in demodulated bit-error-rate of over 2 dB Eb/N0 when compared to 128-Quadrature Amplitude Modulation (QAM). The GRAND-aided OM scheme outperforms coding with a low-density parity check code of the same average rate as that induced by our simple padding.