A Measurement-Based Model for Dynamic Spectrum Access in WLAN Channels

In this paper we consider dynamically sharing the spectrum in the time-domain by exploiting whitespace between the bursty transmissions of a set of users, represented by an 802.11b based wireless LAN (WLAN). Realizing that exploiting the under-utilization of the channel requires a good model of the these users´ medium access, we propose a continuous-time semi-Markov model that captures the WLAN´s behavior yet remains tractable enough to be used for deriving optimal control strategies within a decision-theoretic framework. Our model is based on actual measurements in the 2.4 GHz ISM band using a vector signal analyzer to collect complex baseband data. We explore two different sensing strategies to identify spectrum opportunities depending on whether the primary user´s transmission scheme is known. The collected data is used to statistically characterize the idle and busy periods of the channel. Furthermore, we show that a continuous-time semi-Markov model is able to capture the data with good accuracy. The Kolmogorov-Smirnov test is used to validate the model and to assess the model´s goodness-of-fit quantitatively. A conclusion summarizes the main results of the paper