6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

B-SSCT: A Block Sequential Spectrum Sensing Scheme for Cognitive Radio

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2011.245942,
        author={Yan Xin and Honghai Zhang and Sampath Rangarajan and Kyungtae Kim},
        title={B-SSCT: A Block Sequential Spectrum Sensing Scheme for Cognitive Radio},
        proceedings={6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2012},
        month={5},
        keywords={average sample number cognitive radio energy detection sequential detection spectrum sensing},
        doi={10.4108/icst.crowncom.2011.245942}
    }
    
  • Yan Xin
    Honghai Zhang
    Sampath Rangarajan
    Kyungtae Kim
    Year: 2012
    B-SSCT: A Block Sequential Spectrum Sensing Scheme for Cognitive Radio
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2011.245942
Yan Xin1,*, Honghai Zhang1, Sampath Rangarajan1, Kyungtae Kim1
  • 1: NEC Labs America Inc
*Contact email: yanxin@nec-labs.com

Abstract

Recently, it has been shown that in comparison to the well-known energy detection scheme, the sequential shifted chi-square test (SSCT) is capable of delivering considerable reduction on the average sample number (ASN) while maintaining a comparable detection error performance for spectrum sensing. Nonetheless, SSCT needs to perform threshold comparisons on every received sample, which may be difficult or even infeasible in practice particularly when the sampling rate is high and/or the signal-to-noise ratio is low. This paper proposes an extension of SSCT, called block-wise SSCT (B-SSCT), to overcome this shortcoming. Numerical algorithms are applied to evaluate the false-alarm and miss-detection probabilities and the ASN of B-SSCT, in a recursive fashion. Simulation and numerical results show that compared to the original SSCT, B-SSCT is capable of achieving almost the same detection error performance with a significantly reduced number of threshold comparisons and a slightly increased ASN. An implementation example demonstrates potential practical feasibility of B-SSCT in a real environment.