  This work aims to investigate semantic communication in high-speed mobile
Internet of vehicles (IoV) environments, with a focus on the spectrum sharing
between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I)
communications. We specifically address spectrum scarcity and network traffic
and then propose a semantic-aware spectrum sharing algorithm (SSS) based on the
deep reinforcement learning (DRL) soft actor-critic (SAC) approach. Firstly, we
delve into the extraction of semantic information. Secondly, we redefine
metrics for semantic information in V2V and V2I spectrum sharing in IoV
environments, introducing high-speed semantic spectrum efficiency (HSSE) and
semantic transmission rate (HSR). Finally, we employ the SAC algorithm for
decision optimization in V2V and V2I spectrum sharing based on semantic
information. This optimization encompasses the optimal link of V2V and V2I
sharing strategies, the transmission power for vehicles sending semantic
information and the length of transmitted semantic symbols, aiming at
maximizing HSSE of V2I and enhancing success rate of effective semantic
information transmission (SRS) of V2V. Experimental results demonstrate that
the SSS algorithm outperforms other baseline algorithms, including other
traditional-communication-based spectrum sharing algorithms and spectrum
sharing algorithm using other reinforcement learning approaches. The SSS
algorithm exhibits a 15% increase in HSSE and approximately a 7% increase in
SRS.
