@techreport{TD:101170,
	att_abstract={{In this paper, we develop efficient algorithm to
obtain the optimal energy schedule for fading channel with
energy harvesting. We assume that the side information of
both the channel states and energy harvesting states for K
time slots is known a priori, and the battery capacity and the
maximum transmission power in each time slot are limited. To
obtain the achievable transmission rate, we formulate a convex
optimization problem with O(K) constraints. Since the computational
complexity of a generic convex solver is exponential in
the number of constraints, it is hard to solve using a general
convex solver and this paper gives an efficient energy scheduling
algorithm, called the dynamic water-filling algorithm, obtaining
the optimal energy schedule within a computational complexity
of O(K2). Indifferent to the traditional water-filling algorithm,
the water level in dynamic water-filling is not constant but
changes when the battery overflows or depletes. Moreover, the
numerical results show that the proposed algorithm achieves
the optimal performance, providing a significant improvement
from the traditional native scheduling policies.}},
	att_authors={va037f},
	att_categories={},
	att_copyright={{IEEE}},
	att_copyright_notice={{This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2013. {{, 2013-10-06}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:101170},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101170_DS1_2013-12-02T19:37:24.440Z.pdf},
	author={Vaneet Aggarwal and Xiaodong Wang and Zhe Wang},
	institution={{Allerton Conference}},
	month={October},
	title={{Renewable Energy Scheduling for Fading Channels
with Maximum Power Constraint}},
	year=2013,
}