Online computation and competitive analysis
Online computation and competitive analysis
Mathematics of Operations Research
On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract)
LATIN '00 Proceedings of the 4th Latin American Symposium on Theoretical Informatics
Budget constrained bidding in keyword auctions and online knapsack problems
Proceedings of the 17th international conference on World Wide Web
A jamming game in wireless networks with transmission cost
NET-COOP'07 Proceedings of the 1st EuroFGI international conference on Network control and optimization
Dynamic power allocation under arbitrary varying channels - the multi-user case
INFOCOM'10 Proceedings of the 29th conference on Information communications
Online primal-dual algorithms for covering and packing problems
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Capacity of fading channels with channel side information
IEEE Transactions on Information Theory
Reliable communication under channel uncertainty
IEEE Transactions on Information Theory
Fading channels: information-theoretic and communications aspects
IEEE Transactions on Information Theory
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A major problem in wireless networks is coping with limited resources, such as bandwidth and energy. These issues become a major algorithmic challenge in view of the dynamic nature of the wireless domain. We consider in this paper the single-transmitter power assignment problem under time-varying channels, with the objective of maximizing the data throughput. It is assumed that the transmitter has a limited power budget, to be sequentially divided during the lifetime of the battery. We deviate from the classic work in this area, which leads to explicit "water-filling" solutions, by considering a realistic scenario where the channel state quality changes arbitrarily from one transmission to the other. The problem is accordingly tackled within the framework of competitive analysis, which allows for worst-case performance guarantees in setups with arbitrarily varying channel conditions. We address both a "discrete" case, where the transmitter can transmit only at a fixed power level, and a "continuous" case, where the transmitter can choose any power level out of a bounded interval. For both cases, we propose online power-allocation algorithms with proven worst-case performance bounds. In addition, we establish lower bounds on the worst-case performance of any online algorithm and show that our proposed algorithms are optimal.