8th International Conference on Cognitive Radio Oriented Wireless Networks

Research Article

Optimal Entropy-based Spectrum Sensing for Cognitive Radio Networks under Severe Path Loss Conditions

Download586 downloads
  • @INPROCEEDINGS{10.4108/icst.crowncom.2013.252065,
        author={Waleed Ejaz and Mahin K. Atiq and Hyung Seok Kim and Ghalib A. Shah},
        title={Optimal Entropy-based Spectrum Sensing for Cognitive Radio Networks under Severe Path Loss Conditions},
        proceedings={8th International Conference on Cognitive Radio Oriented Wireless Networks},
        publisher={ICST},
        proceedings_a={CROWNCOM},
        year={2013},
        month={11},
        keywords={cognitive radio network maritime communication spectrum sensing cooperative detection},
        doi={10.4108/icst.crowncom.2013.252065}
    }
    
  • Waleed Ejaz
    Mahin K. Atiq
    Hyung Seok Kim
    Ghalib A. Shah
    Year: 2013
    Optimal Entropy-based Spectrum Sensing for Cognitive Radio Networks under Severe Path Loss Conditions
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2013.252065
Waleed Ejaz1, Mahin K. Atiq1, Hyung Seok Kim1,*, Ghalib A. Shah2
  • 1: Sejong University
  • 2: Al-Khawarizmi Institute of Computer Science
*Contact email: hyungkim@sejong.edu

Abstract

Recently maritime cognitive radio network is proposed to provide high bandwidth and low communication cost for maritime users. Spectrum sensing is one of the key issues to develop cognitive radio networks. Radio propagation is one of the main differences between maritime and land environment. Traditional detectors such as matched filter, energy detector and cyclostationary detector are not robust under low signal-to-noise ratio and at high sea state conditions. To deal with maritime environmental challenges, an entropy-based spectrum sensing scheme with the optimal number of samples is presented in this paper. Since spectrum sensing is sensitive to the number of samples, the optimal number of samples has been introduced in the proposed scheme to get minimum sensing time and maximum detection probability. Results reveal that existing scheme works well for the lower sea states but failed to perform at higher sea states. Moreover, simulation results show that the entropy-based scheme is robust at higher sea states in comparison with the traditional energy detector.