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Optimizing the energy-spectrum efficiency of cellular systems by evolutionary multi-objective algorithm

Authors: Wang, Qiang; Liu, Hai-Lin; Yuan, Jiawei; Chen, Lei;

Optimizing the energy-spectrum efficiency of cellular systems by evolutionary multi-objective algorithm

Abstract

Energy harvesting is one of the most important technologies in green communication. Wireless systems usually have different traffic loads and available renewable energy, and thus we consider the energy cooperation technology to decrease renewable energy waste. In this paper, a flexible spectrum sharing scheme among multi-systems is proposed. To be specific, the wide-band spectrum is divided into several narrow band carriers. Each system can flexibly select these narrow carriers which are not needed to be adjacent, and different systems can share the same narrow band carriers, which can improve the spectrum efficiency. Then, the carrier-aggregation technology is adopted to aggregate these narrow band carriers into wide-band spectrum to support each wireless system. Furthermore, we study the energy cooperation among multi-systems to improve the renewable energy efficiency. Accordingly, the proposed model is formulated into a multi-objective mixed integer optimization problem. To solve it, simplex-dominance is presented to replace the Pareto-dominance in the established MOEA/D-M2M. The simplex-dominance can effectively improve the convergence performance by producing more selection pressure towards Pareto front. The Lagrangian dual method is also adopted to optimize the transmit power to eliminate the co-channel interference caused by the spectrum sharing. In final simulation, the comparison between the proposed joint renewable energy cooperation and spectrum sharing scheme and some benchmarks has been carried out. Experimental results prove that the proposed scheme can effectively improve the spectrum efficiency, and decrease the GHG emission. In addition, the MOEA/D-M2M based on simplex-diminance is compared with NSGA-II, and the results shows the effectiveness of the proposed algorithm.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
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