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

被引:0
|
作者
He, Peter [1 ]
Zhao, Lian [1 ]
Venkatesh, Bala [1 ]
机构
[1] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada
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中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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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页数:5
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