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Joint Relay Selection and Power Allocation through a Genetic Algorithm for Secure Cooperative Cognitive Radio Networks.
Rahman, Md Arifur; Lee, YoungDoo; Koo, Insoo.
Afiliación
  • Rahman MA; School of Electrical Engineering, University of Ulsan, 93-Daehak-ro, Namgu, Ulsan 44610, Korea. rassel.aece@gmail.com.
  • Lee Y; School of Electrical Engineering, University of Ulsan, 93-Daehak-ro, Namgu, Ulsan 44610, Korea. leeyd1004@naver.com.
  • Koo I; School of Electrical Engineering, University of Ulsan, 93-Daehak-ro, Namgu, Ulsan 44610, Korea. iskoo@ulsan.ac.kr.
Sensors (Basel) ; 18(11)2018 Nov 14.
Article en En | MEDLINE | ID: mdl-30441817
In cooperative cognitive radio networks (CCRNs), there has been growing demand of transmitting secondary user (SU) source information secretly to the corresponding SU destination with the aid of cooperative SU relays. Efficient power allocation (PA) among SU relays and multi-relay selection (MRS) are a critical problem for operating such networks whereas the interference to the primary user receiver is being kept below a tolerable level and the transmission power requirements of the secondary users are being satisfied. Subsequently, in the paper, we develop the problem to solve the optimal solution for PA and MRS in a collaborative amplify-and-forward-based CCRNs, in terms of maximizing the secrecy rate (SR) of the networks. It is found that the problem is a mixed integer programming problem and difficult to be solved. To cope with this difficulty, we propose a meta-heuristic genetic algorithm-based MRS and PA scheme to maximize the SR of the networks while satisfying transmission power and the interference requirements of the networks. Our simulation results reveal that the proposed scheme achieves near-optimal SR performance, compared to the exhaustive search scheme, and provides a significant SR improvement when compared with some conventional relay selection schemes with equal power allocation.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2018 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2018 Tipo del documento: Article Pais de publicación: Suiza