NOMA Joint Decoding based on Soft-Output Ordered-Statistics Decoder for Short Block Codes

Yue, Chentao; Kosasih, Alva; Shirvanimoghaddam, Mahyar; Park, Giyoon; Park, Ok-Sun; Hardjawana, Wibowo; Vucetic, Branka; Li, Yonghui

doi:10.48550/arxiv.2110.15010

Cited by 1 publication

(8 citation statements)

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“…The signal r given by ( 1) is decoded by an iterative JD receiver based on SOSD [30], as shown in Fig. 1.…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

“…2) Decoding Switch: DS was proposed in our previous work [30] to determine the engagement of SOSD in JD iterations. Specifically, when PIC fails to cancel the MAI properly and produces low-quality LLRs, the DS is set to "off".…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

“…When the quality of outputs of PIC improves after a few iterations of the DSoff phase, the DS is turned "on" and decoding begins. In [30], a "simple DS" strategy was introduced: the receiver performs n u iterations without decoding, and then turns on DS for subsequent iterations. In other words, the DS-off phase has n u iterations.…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

“…3) SOSD Decoders: If the original SOSD is employed, the output of decoder, δ (u) (t), is obtained according to (3). Alternatively, the original SOSD can be replaced by a low-complexity SOSD (LC-SOSD) devised in [30]. In a nutshell, LC-SOSD determines δ (u) (t) in a reduced space of codewords compared to the original SOSD, which applies a stopping condition that terminates the decoding process early.…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

“…It was validated that LC-SOSD has a very similar mutual information transform property to the original SOSD with a significantly reduced complexity. We refer interested readers to [30] for details. Moreover, [30] showed that the input and output of SOSD can be adaptively combined according to a predefined decoding quality γ to accelerate the convergence, known as decoding combiner (DC).…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

See 4 more Smart Citations

Density Evolution Analysis of the Iterative Joint Ordered-Statistics Decoding for NOMA

Yue¹,

Shirvanimoghaddam²,

Kosasih³

et al. 2021

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In this paper, we develop a density evolution (DE) framework for analyzing the iterative joint decoding (JD) for non-orthogonal multiple access (NOMA) systems, where the ordered-statistics decoding (OSD) is applied to decode short block codes. We first investigate the density-transform feature of the soft-output OSD (SOSD), by deriving the density of the extrinsic log-likelihood ratio (LLR) with known densities of the priori LLR. Then, we represent the OSD-based JD by bipartite graphs (BGs), and develop the DE framework by characterizing the density-transform features of nodes over the BG. Numerical examples show that the proposed DE framework accurately tracks the evolution of LLRs during the iterative decoding, especially at moderate-to-high SNRs. Based on the DE framework, we further analyze the BER performance of the OSD-based JD, and the convergence points of the two-user and equal-power systems.

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“…The signal r given by ( 1) is decoded by an iterative JD receiver based on SOSD [30], as shown in Fig. 1.…”

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%

Section: Noma Joint Decoding With Sosdmentioning

confidence: 99%