An effective rate adaptation scheme for multihop wireless networks

The nature of a time variant channel environment have posed significant challenges on the design of new communication protocols and applications for IEEE 802.11 based multihop networks. The ability to predict the channel status enables these networks to better exploit the network resources and take precautionary measures, when necessary, to improve the channel reuse through tuning protocol parameters (such as transmit power, carrier sensing threshold and transmission data rate). This work suggests the use of Interacting Multiple Model (IMM) estimator, which is build from a (K) number of Kalman Filters to work in parallel, in order to predict the future signal-to-interference in a wireless network with time-varying channel conditions. These predictions are then used by a rate adaptation scheme in discrete event simulation environment to ensure proper and predictable resource usage.