Optimum transmission policies for battery limited energy harvesting nodes

Kaya Tutuncuoglu, Aylin Yener

    Research output: Contribution to journalArticlepeer-review

    589 Scopus citations

    Abstract

    Wireless networks with energy harvesting battery equipped nodes are quickly emerging as a viable option for future wireless networks with extended lifetime. Equally important to their counterpart in the design of energy harvesting radios are the design principles that this new networking paradigm calls for. In particular, unlike wireless networks considered to date, the energy replenishment process and the storage constraints of the rechargeable batteries need to be taken into account in designing efficient transmission strategies. In this work, such transmission policies for rechargeable nodes are considered, and optimum solutions for two related problems are identified. Specifically, the transmission policy that maximizes the short term throughput, i.e., the amount of data transmitted in a finite time horizon is found. In addition, the relation of this optimization problem to another, namely, the minimization of the transmission completion time for a given amount of data is demonstrated, which leads to the solution of the latter as well. The optimum transmission policies are identified under the constraints on energy causality, i.e., energy replenishment process, as well as the energy storage, i.e., battery capacity. For battery replenishment, a model with discrete packets of energy arrivals is considered. The necessary conditions that the throughput-optimal allocation satisfies are derived, and then the algorithm that finds the optimal transmission policy with respect to the short-term throughput and the minimum transmission completion time is given. Numerical results are presented to confirm the analytical findings.

    Original languageEnglish (US)
    Article number6144764
    Pages (from-to)1180-1189
    Number of pages10
    JournalIEEE Transactions on Wireless Communications
    Volume11
    Issue number3
    DOIs
    StatePublished - Mar 2012

    All Science Journal Classification (ASJC) codes

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Applied Mathematics

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