Adaptive link quality estimation for wireless ad hoc networks
Due to the complexity and time-variation of wireless channel, it is a great challenge to measure and estimate the channel quality accurately in wireless ad hoc network. To address this problem, we propose a link quality estimator which use the packet loss rate (PLR), round trip time (RTT), available...
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Published in | 2009 7th International Conference on Information, Communications and Signal Processing pp. 1 - 5 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2009
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Subjects | |
Online Access | Get full text |
ISBN | 9781424446568 1424446562 |
DOI | 10.1109/ICICS.2009.5397723 |
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Abstract | Due to the complexity and time-variation of wireless channel, it is a great challenge to measure and estimate the channel quality accurately in wireless ad hoc network. To address this problem, we propose a link quality estimator which use the packet loss rate (PLR), round trip time (RTT), available bandwidth (ABW) at the sender and the feedback information from receiver to continuously tracks the channel error probability and the collision probability of the receiver by using an Unscented Kalman Filter (UKF). Through experiments we demonstrate that our link estimator can quickly adapt to the temporal dynamics of the links and accurately predict the link quality, which is more accurate than the traditional broadcasting-based method. |
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AbstractList | Due to the complexity and time-variation of wireless channel, it is a great challenge to measure and estimate the channel quality accurately in wireless ad hoc network. To address this problem, we propose a link quality estimator which use the packet loss rate (PLR), round trip time (RTT), available bandwidth (ABW) at the sender and the feedback information from receiver to continuously tracks the channel error probability and the collision probability of the receiver by using an Unscented Kalman Filter (UKF). Through experiments we demonstrate that our link estimator can quickly adapt to the temporal dynamics of the links and accurately predict the link quality, which is more accurate than the traditional broadcasting-based method. |
Author | Zheng Wu Wai-Choong Wong Jiankang Wu |
Author_xml | – sequence: 1 surname: Zheng Wu fullname: Zheng Wu organization: Sch. of Inf. Sci. & Eng., Grad. Univ. of Chinese Acad. of Sci., Beijing, China – sequence: 2 surname: Wai-Choong Wong fullname: Wai-Choong Wong organization: Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore Singapore, Singapore, Singapore – sequence: 3 surname: Jiankang Wu fullname: Jiankang Wu organization: Sch. of Inf. Sci. & Eng., Grad. Univ. of Chinese Acad. of Sci., Beijing, China |
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SubjectTerms | Ad Hoc Networks Bandwidth Broadcasting Electric variables measurement Error probability Feedback Hidden Markov models Information science Link Quality Estimation Mobile ad hoc networks Resource management State estimation UKF Wireless Link Modeling |
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