Link-level Performance Evaluations of Sparse Code Multiple Access for PC5-based Cellular-V2X with Heterogeneous Channel Estimation Errors
Link-level Performance Evaluations of Sparse Code Multiple Access for PC5-based Cellular-V2X with Heterogeneous Channel Estimation Errors
复制标题
DOI：
10.1109/vtc2021-spring51267.2021.9448797
复制
发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Takeshi Hirai;P. Spasojevic
中科院分区：
文献类型：
--
作者：
Takeshi Hirai;P. Spasojevic
本文介绍了基于 PC5 的蜂窝车辆到一切 (C-V2X) 的稀疏码多址 (SCMA) 的链路级性能，由于用户移动性，每个用户具有不同的信道估计误差 (CEE)，称为异构 CEE。由于非正交性，这种 CEE 可能会通过 SCMA 中使用的消息传递算法导致没有 CEE 的用户解码错误传播。首先，我们分析基本异构 CEE 模型中的错误传播，其中我们的分析表明，错误传播取决于因子图上与特定用户的边缘连通性；接下来，我们评估异构 CEE 模型中每个用户的链路级性能，以确认错误传播的影响，我们的评估结果表明，在 CEE 方差为 0.1 的情况下，错误传播使间接连接用户的误码率性能下降了 8.1 倍。通过我们的模拟结果，本文强调错误传播是基于 PC5 的 V2X 中 SCMA 的潜在挑战。
This paper presents the link-level performance of sparse code multiple access (SCMA) for PC5-based cellular-vehicle-to-everything (C-V2X with different channel estimation errors (CEEs) for every user, called a heterogeneous CEE, due to user mobility. Such a CEE may cause decoding error propagation for users experiencing no CEEs through the message passing algorithm used in SCMA due to the non-orthogonality. First, we analyze the error propagation in a basic heterogeneous CEE model, in which a specific user provides a Gaussian CEE. Our analysis shows that the error propagation depends on the edge connectivity with the specific user on the Factor graph; its directly connected users’ signals show worse decoding performance than its indirectly connected users’ signals. Next, we evaluate the link-level performance of each user in the heterogeneous CEE model to confirm the impacts of the error propagation. Our evaluation results demonstrated that the error propagation degraded 8.1 times worse bit error rate performance of the indirectly connected user at a CEE variance of 0.1 than no CEE for all users. Through our simulation results, this paper highlights that error propagation is a potential challenge for SCMA in PC5-based V2X.