Cognitive radio (CR) lifts efficiency of information resource. As one way of utilizing the renewable energy resources, energy harvesting makes use of energy from the environment. Due to intermitted feature of the renewable energy, the power grid needs to be integrated to regulate the harvested energy supply of the system. Thus, the transmit power of the second user (SU), including the power from both the renewable energy and the power grid is often subject to a peak power constraint to control the interference level of the SU to the primary user (PU). The combination of these three types of emerging communication machineries renders great challenge to provide exact optimal power allocation solution with rapid computation. To the best knowledge of the authors, no such kind of solutions were reported in the open literature. In this paper, our recently proposed geometric water-filling with peak power constraints (GWFPP) and recursion machinery are applied and exploited to solve the throughput maximization problems, making the power grid smart. The proposed algorithms are precisely defined. They provide the exact optimal solution with efficient finite computation. Their optimality is strictly proved. Numerical examples and computational complexity analysis are presented to illustrate the procedures and demonstrate the efficiency of the proposed algorithms.


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    Title :

    Power Allocation for Cognitive Energy Harvesting and Smart Power Grid Coexisting System


    Contributors:
    He, Peter (author) / Zhao, Lian (author) / Venkatesh, Bala (author)


    Publication date :

    2016-09-01


    Size :

    255907 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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