  Vehicle-to-everything (V2X) communication is a key enabler that connects
vehicles to neighboring vehicles, infrastructure and pedestrians. In the past
few years, multimedia services have seen an enormous growth and it is expected
to increase as more devices will utilize infotainment services in the future
i.e. vehicular devices. Therefore, it is important to focus on user centric
measures i.e. quality-of-experience (QoE) such as video quality (resolution)
and fluctuations therein. In this paper, a novel joint video quality selection
and resource allocation technique is proposed for increasing the QoE of
vehicular devices. The proposed approach exploits the queuing dynamics and
channel states of vehicular devices, to maximize the QoE while ensuring
seamless video playback at the end users with high probability. The network
wide QoE maximization problem is decoupled into two subparts. First, a network
slicing based clustering algorithm is applied to partition the vehicles into
multiple logical networks. Secondly, vehicle scheduling and quality selection
is formulated as a stochastic optimization problem which is solved using the
Lyapunov drift plus penalty method. Numerical results show that the proposed
algorithm ensures high video quality experience compared to the baseline.
Simulation results also show that the proposed technique achieves low latency
and high-reliability communication.
