Efficient Spectral Allocation for Cognitive Full Duplex Relay Network Systems Based Soft Computing Technique

Author(s): C. Senthamarai*, N. Malmurugan

Journal Name: Current Signal Transduction Therapy

Volume 15 , Issue 1 , 2020

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Graphical Abstract:


Background: Due to the huge development of wireless devices and mobile data traffic had gained attention towards identifying accurate solutions for more proficient utilization of the wireless spectrum. An essential issue confronting the future in wireless systems is to identify the appropriate spectrum bands to satisfy the request of future administrations. While the greater part of the radio spectrum is allocated to various services, applications and users show that spectrum usage is quite low.

Materials and Methods: The spectrum sensing is performed at the start of each time slot before the data transmission. As a promising framework to improve the spectrum utilization, Cognitive Radio (CR) technique has the immense potential to meet such a necessity by permitting unlicensed users to exist together in licensed bands. In this paper Cognitive radio and Full-Duplex (FD) based two-way relay communications are developed to enhance spectrum utilization for multichannel and to decrease the false alarm rate.

Results: To solve the optimization problems in spectral efficiency, soft computing techniques is proposed to minimize the self-interference and delay to the licensed users. In this proposed work the kurtosis parameter is used for channel detection to determine whether the signal is present or not.

Conclusion: The performance results of the proposed method are evaluated in terms of spectral allocation and outage probability which achieves better performance than the existing Multi- Objective Genetic Algorithm (MOGA) optimization.

Keywords: Cognitive radio, full duplex, two-way relay, sensing spectrum, optimization and soft computing technique, MOGA.

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Article Details

Year: 2020
Published on: 31 July, 2020
Page: [46 - 55]
Pages: 10
DOI: 10.2174/1574362413666180831105203

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