March 13, 2024, 4:42 a.m. | Yongjeong Oh, Jaehong Jo, Byonghyo Shim, Yo-Seb Jeon

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.07255v1 Announce Type: cross
Abstract: In this paper, we present a novel approach for joint activity detection (AD), channel estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access (NOMA) systems. Our approach employs an iterative and parallel interference removal strategy inspired by parallel interference cancellation (PIC), enhanced with deep learning to jointly tackle the AD, CE, and DD problems. Based on this approach, we develop three PIC frameworks, each of which is designed for either coherent or …

abstract arxiv communication cs.ai cs.lg data deep learning detection eess.sp free grant interference iterative machine multiple novel paper strategy systems type

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