Emerging multi-rate wireless systems both cellular (cdma2000, High Data Rate (HDR)) and Wi-Fi like systems demand that the currently used channel estimation and scheduling techniques be revisited. Not only the channel estimation, prediction algorithms, and protocols need to be modified, the premise for evaluating their performance needs to be changed. Current techniques comprise of scheduling algorithms based on existing channel state. We recommend that for enhanced performance in terms of user satisfaction and system throughput not only channel state but also the demand rate needed for satisfying the user needs to be considered.

In this paper, we devise new mechanisms to estimate the varying channel conditions using information theoretic techniques for multi-rate wireless systems. We utilized a nonparametric estimator of R?enyi?s entropy using the Parzen windowing technique to estimate the probability density function of the channel rate variation as experienced by every user in the system. Scheduling algorithms are proposed based on the channel conditions estimated by the proposed technique as well as the data rate needed for satisfying each user . The proposed mechanism ensures the highest number of satisfied users by maintaining the stipulated QoS requirements and fairness amonst users. We also demonstrate that maximizing the throughput does not necessarily result in maximizing the number of satisfied users. Results demonstrate that the proposed estimation techniques perform better than existing schemes both in terms of number of satisfied user and throughput.