Recently, the paper 'Outage Probability Performance Analysis and Prediction for Mobile IoV Networks Based on ICS-BP Neural Network' by Han Wang, a postdoctoral researcher at City University of Macau's Institute of Data Science, and his team was published in the top international journal IEEE Internet of Things Journal. 

 

This paper is one of the phased results of City University’s problem-oriented approach to serving local and regional real-life problems. It is also a reflection of City University of Macau’s teaching and research results on the data science artificial intelligence network. The paper points out that in the field of urban transportation, the Internet of Vehicles is an important part of the urban intelligent Internet of Things, and communication between vehicles is an important condition for realizing intelligent transportation coordination. The level of mobile telematics transmission interruptions can be evaluated through interruption probability performance. If the performance of the Internet of Vehicles network can be accurately analyzed and predicted, the service quality of the mobile Internet of Vehicles network can be improved. However, due to the highly dynamic nature of mobile Internet of Vehicles transmission channels, it is very challenging to analyze and predict them. 

 

Researcher Han Wang cooperated with off-campus research institutions to analyze and predict the outage probability performance of mobile Internet of Vehicles networks. A hybrid decoding amplification and forwarding relay scheme with transmitting antenna selection is proposed: the precise outage probability calculation formula is compiled in a closed form, and the analysis results are verified. In order to achieve real-time analysis of computing performance, an intelligent computing prediction algorithm based on improved cuckoo search is proposed. The algorithm is compared with different prediction methods, and the results show that the algorithm has better prediction performance. Compared with the existing algorithm, the prediction accuracy of the algorithm proposed by the research team increased by 51.8%. In the future, the team will further carry out systematic research and strive to apply the research results to the field of intelligent transportation in high-density cities in Macau and even the Greater Bay Area.