Cross-layer modeling of wireless channels for data-link and IP layer performance evaluation

To provide a tool for performance evaluation of IP-based delay- and loss-sensitive applications running over wireless channels we propose a novel cross-layer wireless channel modeling approach. We firstly develop simple and computationally efficient wireless channel modeling algorithm. For this purpose we adopt the special solution of the inverse eigenvalue problem and show that its complexity significantly decreases when the time-series is covariance stationary two-valued in nature. Our model explicitly takes into account autocorrelation and distributional properties of empirical data. Then, we extend this model to IP layer using the cross-layer mappings. The resulting model is represented by the IP packet error process and reflects memory properties of initial bit error process. We show that our approach allows to get accurate estimators of IP packet error probabilities in presence of FEC at the data-link layer eliminating the need for computationally expensive time-consuming bit level simulations. It also provides a way to choose the required correction capabilities of FEC codes resulting in best possible performance at the data-link and IP layers.