An Optimal Mode Selection Policy in CCRNs with Energy Harvesting Capability | Zendy

Jinlu Ding | Zendy; Tao Jing | Zendy; Fan Zhang | Zendy; Honghao Ma | Zendy; Yan Huo | Zendy

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An Optimal Mode Selection Policy in CCRNs with Energy Harvesting Capability

Author(s) -

Jinlu Ding,

Tao Jing,

Fan Zhang,

Honghao Ma,

Yan Huo

Publication year - 2018

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2018.03.037

Subject(s) - computer science , throughput , cognitive radio , markov decision process , selection (genetic algorithm) , partially observable markov decision process , mode (computer interface) , focus (optics) , energy harvesting , process (computing) , mathematical optimization , markov process , energy (signal processing) , distributed computing , energy consumption , markov chain , markov model , telecommunications , human–computer interaction , wireless , artificial intelligence , machine learning , ecology , statistics , physics , optics , biology , operating system , mathematics

In an energy harvesting powered cooperative cognitive radio network, secondary users are mostly distributed in mobile environments. It is necessary to design an optimal policy to maximize secondary throughput. In this paper, we focus on maximizing the long-term secondary throughput by providing the secondary users two modes to choose at the start of each time slot. Under the partially observable Markov decision process framework, we propose an optimal mode selection policy for the distributed secondary users. Finally, we explore the influence of different parameters on the proposed policy with numerical simulations.

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