Parallel Performance Analysis of Cyclic Correntropy for Energy-Efficient Wireless Communications

Authors

Keywords:

Cognitive Radio, Cyclic Correntropy, Cyclostationary Process, Low Power, Spectrum Sensing, Parallel Scalability

Abstract

Cognitive radio (CR) based systems appear as an efficient alternative for providing higher throughput in wireless systems, mainly through dynamic spectrum access (DSA), and automatic adaptation of the transmitter in terms of modulation format, coding rate, among other parameters, as a function of the communication channel conditions accessed by the system. In this context, processing techniques for spectrum sensing and automatic modulation classifications (AMC) has been widely developed in recent years. Among these techniques, cyclostationary correntropy can be applied to both problems the spectrum sensing and automatic modulation classification. However, this technique has a high computational cost that may increase significantly the system energy consumption. This work proposes a strategy to calculate the cyclic correntropy by using parallel processing on multi-core processors in order to decrease energy consumption in spectrum sensing tasks. A mathematical model is used to relate the power consumption of the processors with their parallel performance. The results demonstrate a decrease in the energy consumption of the proposed architecture.

Author Biography

SAVIO RENNAN MENEZES MELO, UFRN

Possui graduação em Análise e Desenvolvimento de Sistemas pelo Instituto Federal do Rio Grande do Norte (IFRN). Seus interesses de pesquisa estão voltados para o desenvolvimento de sistemas móveis colaborativos, sistemas distribuídos, tópicos de algoritmos e programação paralela. Em geral, suas maiores experiências estão concentradas na área de Sistemas da Computação, com ênfase em Ciência da Computação.

Published

2020-11-04
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