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Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

Reddy, S and Murthy, CR (2010) Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization. In: Communications (ICC), 2010 IEEE International Conference on , 23-27 May 2010, Cape Town.

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In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Item Type: Conference Paper
Publisher: IEEE
Additional Information: Copyright 2010 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 20 Dec 2011 06:45
Last Modified: 20 Dec 2011 06:45
URI: http://eprints.iisc.ac.in/id/eprint/38972

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