Random Access for Semantic Transmission Under Finite Buffer and Retransmission in Vehicular Networks

The rapid advancement of autonomous driving brings large amount of data to transmit in vehicular networks, which increases the burden of channels. While semantic communication (SemCom) can alleviate bandwidth pressure by transmitting semantics rather than raw data, random access (RA) for SemCom may still suffer from collisions and delays due to resource competition. This indicates that, in current vehicular networks, a unified modeling and analysis framework integrating SemCom and access schemes is supposed to be designed and explored. In this correspondence, we propose a RA scheme named SVRA under the buffer and retransmission constraints, where the state characterizations are determined using Markov chain. Furthermore, we introduce the age of incorrect information (AoII) by considering the structure similarity index measure (SSIM). We compare SVRA with existing schemes, the results of which validate that SVRA has a better performance.