基于稀疏码多址接入（SCMA）启发的稀疏向量编码：一种增强型超可靠低延迟传输方案
SCMA Inspired Sparse Vector Coding: An Enhanced URLLC Transmission Scheme
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中文总结 AI 辅助
研究探索SCMA与SVC相互作用，提出SCMA - SVC方案，利用SCMA特性扩大SVC码本最小欧式距离，收获相关增益，经随机相位旋转实现全分集阶数，开发低复杂度解码器，在高斯和瑞利衰落信道提升可靠性。
中文摘要 AI 辅助
稀疏性在稀疏码多址接入（SCMA）和稀疏向量编码（SVC）中被固有利用，但二者间相互作用此前未被探索。本文提出名为SCMA - SVC的新型方案用于增强超可靠低延迟通信。关键是利用SCMA稀疏模式和多维星座特性扩大SVC码本最小欧式距离，收获多用户编码增益和星座整形增益。通过对稀疏向量应用随机相位旋转，在瑞利衰落信道实现全分集阶数。在最大似然解码下，该方案在高斯和瑞利衰落信道均有出色误码率表现。还开发了低复杂度解码器，仿真结果表明其可靠性显著优于现有SVC变体。
英文摘要
Sparsity is inherently exploited in sparse code multiple access (SCMA) and sparse vector coding (SVC), yet the interaction between these two has not been explored before. It is intriguing to ask if one can be used to improve the other, and vice versa. In this work, we present a novel SCMA inspired SVC scheme, called SCMA-SVC, for enhanced ultra-reliable low-latency communications. Our key idea is to exploit the sparse pattern and multidimensional constellation nature of SCMA, with which one is able to further enlarge the minimum Euclidean distance (MED) of the corresponding SVC codebooks. Such an innovation allows us to harvest the multiuser coding gain and the constellation shaping gain which are pertinent to SCMA. Moreover, by applying random phase rotations to the sparse vectors, it is shown that the proposed SCMA-SVC achieves full diversity order over Rayleigh fading channels. Under maximum likelihood (ML) decoding, the proposed SCMA-SVC demonstrates remarkable error rate performances over both Gaussian and Rayleigh fading channels. Additionally, we develop a low-complexity decoder that exploits the structural sparsity of SCMA-SVC while maintaining near-ML performance. Simulation results demonstrate that the proposed SCMA-SVC achieves significantly improved reliability over the existing SVC variants.
