Optimal satisfaction degree in energy harvesting cognitive radio networks

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

中国物理B ›› 2015, Vol. 24 ›› Issue (12): 128401-128401.doi: 10.1088/1674-1056/24/12/128401

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Optimal satisfaction degree in energy harvesting cognitive radio networks

李赞, 刘伯阳, 司江勃, 周福辉

State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China

收稿日期:2015-05-25 修回日期:2015-07-14 出版日期:2015-12-05 发布日期:2015-12-05
通讯作者: Li Zan E-mail:zanli@xidian.edu.cn
基金资助:
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).

Optimal satisfaction degree in energy harvesting cognitive radio networks

Li Zan (李赞), Liu Bo-Yang (刘伯阳), Si Jiang-Bo (司江勃), Zhou Fu-Hui (周福辉)

State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China

Received:2015-05-25 Revised:2015-07-14 Online:2015-12-05 Published:2015-12-05
Contact: Li Zan E-mail:zanli@xidian.edu.cn
Supported by:
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).

摘要/Abstract

摘要： 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.

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

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.

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

中图分类号: (Telecommunications: signal transmission and processing; communication satellites)

84.40.Ua

李赞, 刘伯阳, 司江勃, 周福辉. Optimal satisfaction degree in energy harvesting cognitive radio networks[J]. 中国物理B, 2015, 24(12): 128401-128401.

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[J]. Chin. Phys. B, 2015, 24(12): 128401-128401.

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Optimal satisfaction degree in energy harvesting cognitive radio networks

Optimal satisfaction degree in energy harvesting cognitive radio networks

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