This paper presents the link-level performance of sparse code multiple access (ScMA) for pc5-basedcellular-vehicle-to-everything (c-v2x) with different channel estimation errors (cEEs) for every user, called a hetero...
详细信息
ISBN:
(纸本)9781728189642
This paper presents the link-level performance of sparse code multiple access (ScMA) for pc5-basedcellular-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-basedv2x.
暂无评论