Adaptive Transmission Power Control for Wireless Sensor Networks

Report
Authors:Lin, Shan, Department of Computer ScienceUniversity of Virginia Zhang, Jingbin, Department of Computer ScienceUniversity of Virginia Zhou, Gang, Department of Computer ScienceUniversity of Virginia Stankovic, John, Department of Computer ScienceUniversity of Virginia
Abstract:

Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.
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Rights:
All rights reserved (no additional license for public reuse)
Language:
English
Source Citation:

Lin, Shan, Jingbin Zhang, Gang Zhou, and John Stankovic. "Adaptive Transmission Power Control for Wireless Sensor Networks." University of Virginia Dept. of Computer Science Tech Report (2006).

Publisher:
University of Virginia, Department of Computer Science
Published Date:
2006