The fast fading channel modeling traditionally focuses on physical-level dynamics such as signal strength and bit error rate. In this paper we characterize fast fading channel dynamics at packet-level and analyze the corresponding data queueing performance in various environments. The integration of wireless channel modeling and data queueing analysis provides us a unique way to capture important channel statistics with respect to various wireless network factors such as channel bandwidth, mobile speed and channel coding. The second order channel statistics, i.e., channel power spectrum, is identified to play a dominant role in fast fading channel modeling. The data queueing performance is largely dependent on the interaction between channel power spectrum and data arrival power spectrum, whichever has more low frequency power will have dominant impact on queueing performance. The data arrival power spectrum provides a measure of burstiness and correlation behavior of data packet arrivals. In queueing analysis, we use a Markov chain modeling technique to match the measured important channel statistics.