| Type of Document |
Dissertation |
| Author |
Arauz, Julio Nicolas
|
| URN |
etd-11302004-094018 |
| Title |
802.11 Markov Channel Modelling |
| Degree |
Doctor of Philosophy |
| Program |
Information Science |
| School |
School of Information Sciences |
| Advisory Committee |
| Advisor Name |
Title |
| Dr. Prashant Krishnamurthy |
Committee Chair |
| Dr. Joseph Kabara |
Committee Member |
| Dr. Martin Weiss |
Committee Member |
| Dr. Richard A. Thompson |
Committee Member |
| Dr. Thomas Savits |
Committee Member |
|
| Keywords |
- channel
- markov
- rayleigh
- fading
- 802.11
- modeling
- wireless
|
| Date of Defense |
2004-09-21 |
| Availability |
unrestricted |
Abstract
In order to understand the behavior of upper layer protocols and to design or fine tune their parameters over wireless networks, it is common to assume that the underlying channel is a flat Rayleigh fading channel. Such channels are commonly modeled as finite state Markov chains. Recently, hidden Markov models have also been employed to characterize these channels. Although Markov models have been widely used to study the performance of communications protocols at the link and transport layers, no validation of their accuracy has been performed against experimental data. These models are not applicable to frequency selective fading channels. Moreover, there are no good models to consider the effects of path loss (average received SNR), the packet size, and transmission rate variations which are significant in IEEE 802.11 wireless local area networks.
This research performs validation of Markov models with experimental data and discusses the limitations of the process. In this dissertation, we present different models that have been proposed along with their validity analysis. We use the experimental data with stochastic modeling approaches to characterize the frame losses in IEEE 802.11 wireless LANs. We also characterize the important factor of current wireless LAN technology, the transmission rate variations. New guidelines for the construction of Markov and hidden Markov models for wireless LAN channels are developed and presented along the necessary data to implement them in performance studies. Furthermore we also evaluate the validity of using Markovian models to understand the effects on upper layer protocols such as TCP.
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arauzja_etdpitt2004.pdf |
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