Energy Management in Wireless Communications
In this paper, our goal is to study the “bits per joule” efficiency rating of a protocol in the wireless environment. We explore and compare three approaches to evaluating the energy efficiency and assess their accuracy and complexity. Although our technique allows us to accommodate other profiles, for concreteness we model the battery as a device that has the means to support the transmission of a fixed number of packets. We model the fading as a Markov channel, and we present some particular results for link error control protocols. For the particular examples considered, the exact recursive approach and an asymptotic approach were found to predict results that were very close. In addition, a lower bound and an approximation lead to analytical expressions. The quality of the bound and the accuracy of the approximation improves quite quickly as the amount of available energy increases.
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- N. Bambos, J.M. Rulnick, “Mobile power management for maximum battery life in wireless communication networks,” in Proc. IEEE INFOCOM’96, pp. 443–50, Mar. 1996.Google Scholar
- N Bambos, J.M. Rulnick, “Performance evaluation of power-managed mobile communication devices,” in Proc. IEEE ICC’96, pp. 1477–81, Mar. 1996.Google Scholar
- M. Zorzi, R.R. Rao, “Energy Constrained Error Control for Wireless Channels,” in Proc. IEEE GLOBECOM’96, Nov. 1996.Google Scholar
- E.J. Podlaha, H.Y. Cheh, “Modeling of cylindrical alkaline cells. VI: variable discharge conditions,” J. Electrochem. Soc., vol. 141, pp. 28–35, Jan. 1994.Google Scholar
- D. Linden, ed., Handbook of Batteries, 2nd edition, New York: McGraw-Hill, 1995.Google Scholar
- S.H. Ross, Stochastic processes, John Wiley & Sons, 1983.Google Scholar
- A. Gut, Stopped Random Walks: limit theorems and applications, New York: Springer-Verlag, 1988.Google Scholar
- R.A. Howard, Dynamic probabilistic systems, New York: John Wiley & Sons, 1971.Google Scholar