Artificial Intelligence on Mobile Multimedia Networks for Call Admission Control Systems

An increased demand for multimedia services necessitates the implementation of high-speed networks and call admission control (CAC) schemes. Increasingly, consumers want to be able to watch movies and TV shows on their smartphones. The primary goal of this integrated neural fuzzy-based CAC method is to enhance quality of service (QoS) while also ensuring equitable allocation of resources, with the end goal of reducing the likelihood of calls being dropped or blocked in mobile multimedia networks. This results in a more accurate and reliable control system. This hybrid technique is further developed to produce a more effective computational model for traffic management and the equitable allocation of radio resources for new calls and handoff calls. The findings of the simulation reveal that a neural fuzzy-based CAC has the potential to achieve low call-dropping probability and maximum resource utilization in high-speed networks.