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arXiv · 2609.33830

Soft-Output GRAND-Aided Macrosymbol

Sarah Khalifeh·Alexander Mariona·Ken R. Duffy·Muriel Medard
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Abstract

Guessing Random Additive Noise Decoding-Aided Macrosymbol (GRAND-AM) provides a coding-based solution for non-orthogonal multiple access (NOMA) systems, enabling joint multiuser detection and error correction. GRAND-AM outperforms prior methods in symbol error rates while providing hard-detection output. We introduce soft-output GRAND-AM (SOGRAND-AM), a macrosymbol-level joint multiuser detection and decoding framework which generates calibrated bitwise a posteriori error probabilities. SOGRAND-AM extends GRAND-AM by enabling soft-decision outer forward error correction decoders, transparently integrating with existing decoders. SOGRAND-AM achieves approximately 2 dB improvement in bit error rate at the output of the outer soft-input decoder compared to hard input with GRAND-AM.

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Sarah Khalifeh, Alexander Mariona, Ken R. Duffy, Muriel Medard. 2026-09-27. Soft-Output GRAND-Aided Macrosymbol. https://arxiv.org/abs/2609.33830

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