UP	Paper 1011	US-W-E	DOWN
A Measurement-Based Model for Dynamic Spectrum Access in WLAN Channels
Tong,Lang		Cornell University
Sadler,Brian M.		Army Research Laboratory
Geirhofer,Stefan		Cornell University
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 2.4GHz 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.
Stefan Geirhofer received the M.S. degree in electrical enginnering from the Vienna University of Technology, Austria, in March 2005. He is currently pursuing his doctoral studies at Cornell University, Ithaca, NY. Stefan's research focuses on the application of signal processing concepts in wireless communications and sensor networks.