Cognitive Radio Oriented Wireless Networks. 12th International Conference, CROWNCOM 2017, Lisbon, Portugal, September 20-21, 2017, Proceedings

Research Article

Lessons Learned from Long-Term and Imperfect Sensing in 2.4 GHz Unlicensed Band

  • @INPROCEEDINGS{10.1007/978-3-319-76207-4_12,
        author={Jacek Dzikowski and Cynthia Hood},
        title={Lessons Learned from Long-Term and Imperfect Sensing in 2.4 GHz Unlicensed Band},
        proceedings={Cognitive Radio Oriented Wireless Networks. 12th International Conference, CROWNCOM 2017, Lisbon, Portugal, September 20-21, 2017, Proceedings},
        proceedings_a={CROWNCOM},
        year={2018},
        month={3},
        keywords={Cognitive radio Wireless environment model WiSpy Long-term measurement},
        doi={10.1007/978-3-319-76207-4_12}
    }
    
  • Jacek Dzikowski
    Cynthia Hood
    Year: 2018
    Lessons Learned from Long-Term and Imperfect Sensing in 2.4 GHz Unlicensed Band
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-319-76207-4_12
Jacek Dzikowski1,*, Cynthia Hood1,*
  • 1: Illinois Institute of Technology
*Contact email: dzikjac@hawk.iit.edu, hood@iit.edu

Abstract

Accuracy of spectrum sensing affects the decision making operation of cognitive radio. In order to achieve meaningful results, in related experimental and simulation work, realistic wireless environment representation is a necessity. Existing spectrum occupancy models range from simple additive white Gaussian noise to elaborate, based on large scale wireless spectrum measurements, but universal models are not available. Creating such a model for unlicensed bands would be particularly difficult, if not impossible, because of its unpredictability and inherent dynamics. On the other hand, our experience shows that using real-life, relatively low-resolution, data collected using inexpensive spectrum analyzer provides insight consistent with observations made with more sophisticated setups, preserves more nuances than simple models, and could be a viable alternative to spectrum occupancy modeling.