Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.
Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Link adaptation for QoS provisioning in wireless data networks
Abstract
Due to the time varying and bursty nature of wireless links, it is very difficult to provide guaranteed Quality of Service (QoS) in wireless data networks. Link adaptation techniques are proposed to improve the wireless link quality by adapting Media Access Control (MAC) protocol parameters such as frame size, modulation scheme, and so forth. In this dissertation, the goal was to improve the overall QoS performance of wireless data networks by building a reliable and adaptive MAC layer. We first reviewed all related issues about QoS provisioning in wireless data networks. We then proposed several link adaptation algorithms for QoS provisioning in wireless data networks. These algorithms include adaptive fragmentation algorithms, data rate drafting algorithms, and optimal frame size predictors. The performance of these proposed algorithms for QoS provisioning in the IEEE 802.11 wireless LAN was analyzed. In addition, a network simulator for the theoretical study of the IEEE 802.11 wireless LAN has been developed, which utilizes our proposed theoretical performance model of the wireless LAN. The correctness of the proposed theoretical model has been verified by extensive simulation results. Simulation results have been collected and analyzed. They show that the proposed link adaptation algorithms can greatly improve the throughput performance of the wireless LAN. The proposed algorithms can easily be implemented and integrated with current systems.
Subject Area
Electrical engineering|Computer science
Recommended Citation
Ci, Song, "Link adaptation for QoS provisioning in wireless data networks" (2002). ETD collection for University of Nebraska-Lincoln. AAI3055265.
https://digitalcommons.unl.edu/dissertations/AAI3055265