A Theoretical Framework on Real-Time Communication and Information Estimation in Ultra Large-Scale 6G C-V2X Networks

The emergence of sixth generation communication (6G) wireless networks is set to revolutionize vehicular communication by enabling ultra-reliable, low-latency, and high-capacity connectivity in cellular vehicle-to-everything (C-V2X) environments. This paper presents a theoretical framework on novel cooperative vehicular communication and information perception algorithms for large-scale 6G C-V2X networks while leveraging integrated space-air-ground communication system. Specifically, we address key challenges in real-time information exchange and fusion among multiple vehicles. Utilizing inequality theory and functional mapping theory, we derive an upper bound on channel capacity for a fixed number of relays and propose a lowcomplexity, multi-class relay selection algorithm. Furthermore, we introduce an optimal mobile edge computing (MEC) based correspondence strategy to improve vehicle-to-vehicle communication, alongside an efficient information estimation algorithm to facilitate real-time data sharing. Our simulation results confirm that the proposed algorithms significantly outperform existing cooperative vehicular schemes in terms of channel capacity, while the developed evaluation theory ensures accurate cooperative perception with reduced computational complexity. The proposed framework and theoretical contributions offer a foundational basis for 6G C-V2X networks.