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In this paper, we develop a density evolution (DE) framework for analyzingthe iterative joint decoding (JD) for non-orthogonal multiple access (NOMA)systems, where the ordered-statistics decoding (OSD) is applied to decode shortblock codes. We first investigate the density-transform feature of thesoft-output OSD (SOSD), by deriving the density of the extrinsic log-likelihoodratio (LLR) with known densities of the priori LLR. Then, we represent theOSD-based JD by bipartite graphs (BGs), and develop the DE framework bycharacterizing the density-transform features of nodes over the BG. Numericalexamples show that the proposed DE framework accurately tracks the evolution ofLLRs during the iterative decoding, especially at moderate-to-high SNRs. Basedon the DE framework, we further analyze the BER performance of the OSD-basedJD, and the convergence points of the two-user and equal-power systems.

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