Markov-based modeling of wireless local area networks

ABSTRACT

Errors introduced by a wireless medium are more frequent and profound than contemporary wired media. Some of these errors, which are not corrected by the physical layer, result in Medium Access Control (MAC) layer bit errors and packet losses. Design of wireless protocols and applications can benefit substantially from a thorough understanding of these MAC layer impairments. This paper evaluates and proposes Markov-based stochastic chains to model the 802.11b MAC-to-MAC channel behavior for both bit errors and packet losses. We introduce an Entropy Normalized Kullback-Leibler measure to evaluate the performance of existing and new bit error and packet loss models. Based on the proposed measure, and contrary to recent results for mobile networks, we demonstrate that the traditional two-state Markov chain provides a very suitable model for the 802.11b MAC-to-MAC packet loss process. However, this simple model is not adequate for bit errors observed at the MAC layer of wireless local area networks. Consequently, we evaluate three other Markov-based chains for modeling these errors: full-state, hidden, and hierarchical Markov chains. Among these chains, we illustrate that the full-state Markov bit error model, evaluated under a wide range of order values, renders the best performance.

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication

General Terms:
Experimentation, Measurement, Performance, Theory

Keywords:
802.11b networks, MAC-to-MAC, Markov-based modeling, information theoretic evaluation