On the Use of Learning Automata in Tuning the Channel Split Ratio of WiMAX Networks

Abstract

The Worldwide Interoperability for Microwave Access (WiMAX) family of standards have introduced a flexible, efficient, and robust wireless interface. Among other interesting features, WiMAX access networks bring into play a flexible determination of the ratio between the downlink and uplink directions, allowing a relation width from 3 : 1 to 1 : 1, respectively. However, this promising feature is not properly utilized, since hitherto scheduling and mapping schemes proposed neglect it. In this paper, this challenging issue is effectively addressed by proposing an adaptive model that attempts to adequately adjust the downlink-to-uplink subframe width ratio according to the current traffic conditions. In the context of a mobile WiMAX wireless access network, the base station is enhanced with an error-aware learning automaton in order to be able to identify the magnitude of the incoming and outgoing traffic flows and, in turn, to suitably define the ratio on a frame-by-frame basis. The model designed is extensively evaluated under realistic and dynamic scenarios, and the results indicate that its performance is clearly improved compared with schemes having predefined and fixed ratio values.