On Modeling of 802.1lb Residue Errors
Errors that are observed at the MAC layer of a wireless protocol are known as residue errors due to the failure of the physical layer to correct them. In this paper, based on experimentation with actual 802.11b wireless LANs (WLANs), it is shown that the 802.11b residue error process is a highly non-stationary process; and hence error models derived on the basis of observations at one time/environment may not be applicable at/in another. Thus MAC-layer modeling/prediction techniques need to adapt on the basis of some channel state information (CSI). Consequently, in this work, we characterize the variation in the behavior of the residue error process in accordance to the radio-link signal to silence ratio (SSR) indications (SSRI). The residue error process is treated as a piecewise stationary process, where each piece corresponds to a PHY/MAC packet. In particular, we construct a unified Markov framework to obtain SSR aware Markov models for residue errors. Further, it is shown that the proposed SSR aware Markov framework provides significant performance benefits and can characterize the residue error traces even across varied WLAN setups. This leads to the design of non-homogenous Markov models that can vary the transition matrix on the basis of using SSR indication as side-information. We deploy such a non-homogenous Markov model and show that it can characterize the error process significantly better than Markov models that are derived by ignoring SSR values.