On potential challenges of V2X sidelink relaying under interference: link-level and system-level simulation with neural network assisted

Abstract

The ever-increasing demand for high data rates and high connection densities in the vehicle communication network, along with the widespread adoption of radio access over the Third Generation Partnership Project (3GPP) standard, has been a major driver for the research on cellular vehicle-to-everything (C-V2X) communication. Nevertheless, Wi-Fi and other wireless communication technology work on the 5.9 GHz unlicensed band has also undergone booming proliferation over the years. C-V2X users dedicated band on the 5.9 GHz spectrum may thus suffer from both co-channel and adjacent channel interference, which cannot be negligible, especially in urban scenarios. To this end, 3GPP has standardized relay technology in New Radio (NR) V2X sidelink to extend the transmission range under interference. In this paper, through a link-level and system-level simulation study, we evaluate the sidelink performance in relaying scenarios under different interference. Motivated by the recent success of deep learning, a novel neural network is further introduced as a unified benchmark for interference mitigation evaluation. Numerical results show that there exist challenges in the real-time optimization of transmission scheme selection and power allocation in relay-assisted cases. The simulation also reveals that the interference incurred by NR on unlicensed spectrum (NR-U) signals and other sidelink signals is intractable to be suppressed, which may bring potential challenges in future works.