ملخص: Wireless local area networks are becoming very popular in many scenarios because they are very simple, convenient and cheap. This paper focuses on multimedia tra.c management in wireless networks, where we consider to provide di.erentiated Quality of Service (QoS) levels. We address the complex task of tra.c scheduling with multi-objective requirements in the presence of errors introduced by the radio channel. In particular, we focus on managing downlink tra.c in both wireless ATM and WiFi scenarios, referring to an infrastructure wireless access network where a central coordinator takes scheduling decisions for the mobile users in its cell. Our scheduler is based on an Arti.cial Neural Network (ANN) with reinforcement learning. The ANN is trained from examples to behave as an ‘‘optimal’’ scheduler, according to an Actor-Critic model. The results obtained in scheduling concomitant voice, video and Web tra.c classes permit to show the signi.cant capacity improvement that can be achieved by our scheme with respect to other techniques previously proposed in the literature.

لغة: إنجليزية