Optimal satisfaction degree in energy harvesting cognitive radio networks

doi:10.1088/1674-1056/24/12/128401

Abstract A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis.

Keywords: cognitive radio (CR) energy harvesting (EH) hidden Markov model (HMM) whole satisfaction degree (WSD)

Received: 25 May 2015
Revised: 14 July 2015
Accepted manuscript online:

PACS:

84.40.Ua

(Telecommunications: signal transmission and processing; communication satellites)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Corresponding Authors: Li Zan
E-mail: zanli@xidian.edu.cn

Cite this article:

Li Zan (李赞), Liu Bo-Yang (刘伯阳), Si Jiang-Bo (司江勃), Zhou Fu-Hui (周福辉) Optimal satisfaction degree in energy harvesting cognitive radio networks 2015 Chin. Phys. B 24 128401

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