  In this paper, we investigate sub-6 GHz V2X sidelink positioning scenarios in
5G vehicular networks through a comprehensive end-to-end methodology
encompassing ray-tracing-based channel modeling, novel theoretical performance
bounds, high-resolution channel parameter estimation, and geometric positioning
using a round-trip-time (RTT) protocol. We first derive a novel, approximate
Cram\'er-Rao bound (CRB) on the connected road user (CRU) position, explicitly
taking into account multipath interference, path merging, and the RTT protocol.
Capitalizing on tensor decomposition and ESPRIT methods, we propose
high-resolution channel parameter estimation algorithms specifically tailored
to dense multipath V2X sidelink environments, designed to detect multipath
components (MPCs) and extract line-of-sight (LoS) parameters. Finally, using
realistic ray-tracing data and antenna patterns, comprehensive simulations are
conducted to evaluate channel estimation and positioning performance,
indicating that sub-meter accuracy can be achieved in sub-6 GHz V2X with the
proposed algorithms.
