User-Driven Call Admission Control for VoIP Over WLAN With a Neural Network Based Cognitive Engine
In this paper, the authors deal with the problem of user-driven Call Admission Control for Voice over IP communications in a Wireless LAN environment. They argue that state-of-the-art solutions to this problem are suboptimal, since they leverage on analytical models whose assumptions are not necessarily verified in the scenario considered. To overcome this problem, they propose a cognitive solution based on Multilayer Feed-forward Neural Networks. According to their solution, the mobile station learns from past experience how application-layer service quality depends on the wireless link conditions.