Computational Experiments of Signal Detection Algorithms in VANETs based on Parallel Intelligence

With the rapid growth of connected vehicles in Internet of Vehicle (IoV), ensuring reliable and secure communication is significant. This paper presents a parallel intelligence-based signal detection method for vehicular networks. The proposed method exploits the main idea of parallel intelligent to analyze wireless communication signal in real-time, achieving efficient and accurate algorithm options for difference IoV environment and different requirements. Experimental results demonstrate that the comparison and analysis of the proposed method based on the detection accuracy and computational complexity, while also contributing to enhanced security in vehicular networks. This approach offers a promising solution for timely, reliable and secure communication in the era of connected vehicles.