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In this paper we consider the energy-efficient resource allocation that minimizes a general cost function of average user powers for small- or medium-scale wireless sensor networks, where the simple time-division multiple-access (TDMA) is adopted as the multiple access scheme. A class of so-called ß-fair cost functions is derived to balance the tradeoff between efficiency and fairness in energy-efficient designs. Based on such cost functions, optimal channel-adaptive resource allocation schemes are developed for both single-hop and multihop TDMA sensor networks. Relying on stochastic optimization tools, we further develop stochastic resource allocation schemes which are capable of dynamically learning the intended wireless channels and converging to the optimal benchmark without a priori knowledge of channel fading distribution function.
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Wang et al. (2010) studied this question.
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