2nd International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Cognitive Radio Sensing Information-Theoretic Criteria Based

  • @INPROCEEDINGS{10.1109/CROWNCOM.2007.4549803,
        author={Majed Haddad and Aawatif Menouni Hayar and Mohamed Hedi Fetoui and M\^{e}rouane Debbah},
        title={Cognitive Radio Sensing Information-Theoretic Criteria Based},
        proceedings={2nd International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        keywords={Bandwidth  Cognitive radio  Computer vision  Covariance matrix  Detectors  Frequency  Interference  Signal processing  White spaces  Wireless sensor networks},
  • Majed Haddad
    Aawatif Menouni Hayar
    Mohamed Hedi Fetoui
    Mérouane Debbah
    Year: 2008
    Cognitive Radio Sensing Information-Theoretic Criteria Based
    DOI: 10.1109/CROWNCOM.2007.4549803
Majed Haddad1,*, Aawatif Menouni Hayar1,*, Mohamed Hedi Fetoui1,*, Mérouane Debbah1,*
  • 1: Mobile Communications Group, Institut Eurecom, 2229 Route des Cretes, B.P. 193, 06904 Sophia Antipolis, France
*Contact email: haddadm@eurecom.fr, menouni@eurecom.fr, fetoui@eurecom.fr, debbah@eurecom.fr


In this paper, we explore the Information- Theoretic Criteria, namely, Akaikes Information Criterion (AIC) and Minimum Description Length (MDL) as a tool to sense vacant sub-band over the spectrum bandwidth. The proposed technique is motivated by the fact that an idle sub-band (Normal process) presents a number of independent eigenvectors appreciably larger than for an occupied sub-band (Non-normal process). It turns out that, based on the number of the independent eigenvectors of a given covariance matrix of the observed signal, one can conclude on the nature of the sensed sub-band. Our theoretical result as well as the empirical results are first applied on experimental measurement campaign conducted at the Eur´ecom PLATON Platform. We then apply our method to an IEEE 802.11b Wireless Fidelity (Wi-Fi) signal in order to analyze the robustness of the proposed approach in presence of increased levels of noise. We argue that the proposed sub-space based techniques give interesting results in terms of sensing the white space in the spectrum.